Cart

  • SUGGESTED TOPICS
  • The Magazine
  • Newsletters
  • Managing Yourself
  • Managing Teams
  • Work-life Balance
  • The Big Idea
  • Data & Visuals
  • Reading Lists
  • Case Selections
  • HBR Learning
  • Topic Feeds
  • Account Settings
  • Email Preferences

HBR’s Most-Read Research Articles of 2021

  • Dagny Dukach

research papers on business

A look back at the insights that resonated most with our readers.

What will it take to make work better? Over the past year, HBR has published a wide array of research-backed articles that explore topics ranging from retaining employees to overcoming meeting overload to fostering gender equity in the workplace. In this end-of-year roundup, we share key insights and trends from our most-read research articles of 2021.

As the workplace rapidly transforms in the wake of the pandemic, social movements, and more, a fundamental question remains: How can we ensure we’re making work better — for employees, organizations, and society at large?

research papers on business

  • Dagny Dukach is a former associate editor at Harvard Business Review.

Partner Center

Ethical Research in Business Ethics

  • Editorial Essay
  • Published: 29 November 2022
  • Volume 182 , pages 1–5, ( 2023 )

Cite this article

  • Gazi Islam 1 &
  • Michelle Greenwood 2  

6048 Accesses

3 Altmetric

Explore all metrics

In this editorial essay, we argue that business ethics research should be aware of the ethical implications of its own methodological choices, and that these implications include, but go beyond, mere compliance with standardized ethical norms. Methodological choices should be made specifically with reference to their effects on the world, both within and outside the academy. Awareness of these effects takes researchers beyond assuring ethics in their methods to more fully consider the ethics of their methods as knowledge practices that have broader institutional consequences. Drawing from examples in published research, we examine five ways in which authors can formulate their methodological approaches with purpose, care and reflexivity.

Avoid common mistakes on your manuscript.

Business ethicists are accustomed to confronting the “hard cases” of ethical choices in organizational life. We believe that business ethics scholarship must be equally sensitive to ethical nuances in the design and implementation of research methods in our own activities. In the complexities of research practice, ethical considerations around method and design exceed the standardized templates of methods textbooks. Where research designs begin and end and whom they implicate as protagonists, who receives voice, protection and authority, and what is rendered visible and invisible within the field of study. These are thorny questions that are not amenable to check-list style compliance guidelines, even where such guidelines also have an important role (cf., Greenwood, 2016 ).

In our exchanges with authors and within the editorial team, we have confronted a plethora of hard cases that highlight the challenges of research ethics beyond rule compliance. To what extent should the mode of data collection (such as crowdsourced data or social media platforms) answer to ethical quandaries around digital labour and online surveillance? When should organizations or individuals engaging in ethically problematic practices be named, and when must they be anonymized? To what extent should the relationships between researchers and participants be problematized within methods sections, including financial and power relationships between funders, researchers and participants? What are the respective roles of institutional ethics boards and journal editorial teams (along with other actors in the research ecosystem) in validating the ethical permissibility of a design? When should hard ethical questions lead a study to be rejected at the review stage, rather than passed along to the research community to make its own judgment? Such questions (and many, many more) have filled our days with deep reflection, and the current editorial aims to share some of these reflections with the Journal of Business Ethics community, albeit in necessarily schematic form. Specifically, we aim to both expand thinking about research ethics to include elements that are often considered outside of methods, and situate conventional methodological ethics in relation to this broader vision. The result will be a plea for a research ethics based on purpose, care and reflexivity.

Between Prescriptive and Evaluative Research Ethics

In a previous editorial essay (Islam & Greenwood, 2021 ), we borrowed a distinction by Williams ( 1985 ) between prescriptive and evaluative ethics; the former refers to what one should do, while the latter to what the world should look like. Mapped onto methods, this analytical distinction differentiates between specific methodological practices (e.g., one should design measures that fit the core constructs, one should gather informed consent) and the broader social and practical implications of research (e.g., the goals of science to innovate, educate or emancipate). We emphasize that this is an “analytical” distinction because, in practice, these aspects of ethics are deeply intertwined, and we distinguish them primarily to show how they spill into each other. Actions should be prescribed, at least in part, for the worlds they contribute to making, although in the fog of situated practice, we are often unaware of, or unable to, clearly link our actions to those future worlds.

From this distinction, it is easy to differentiate heuristically between ethics in research methods, that is, the ethical norms and practices internal to research design and execution, and the ethics of research methods, that is, whether those methods should be used in the broader evaluative sense. In many cases, these ethical levels align, with ethical practices working toward an evaluatively desirable world. Gathering informed consent is important because it is desirable to promote a world of autonomous choice (e.g., Hansson, 2006 ). Hypothesizing after the results are known is problematic because promoting false positive statistical results reduces replicability and thus scientific certainty about the world (Kerr, 1998 ). To take the previous example, however, some have argued that “HARK”ing is less ethically problematic when research is transparently exploratory (Hollenbeck & Wright, 2017 ); in this case, what is ethically problematic is not the practice per se, but the lack of transparency between a given practice and its exploratory (rather than confirmatory) intent. As for informed consent, in cases where a signed form substitutes for, rather than expresses, true participant autonomy (cf., Dubois et al, 2012 ), it can obscure rather than clarify the ethics of a research project. To begin with, the presentation of a priori formulated protocols for consent presumes that the identified participant is the only stakeholder in the research who is affected by the research in a manner that would require their consent. Moreover, this protocol may preclude collaborative models in which participants actively construct research protocols with researchers (Hansson, 2006 ). In both of these examples, a practice is justified on the basis of a deeper evaluative motive, but the mapping between the two is imperfect and situation-dependent.

Tensions may appear between prescriptive and evaluative dimensions of research methods, giving rise to ethical polemics or dilemmas. To give one example, we have had recent debates around the ethics of online data crowdsourcing from platforms such as Amazon MTurk (e.g., Newman et al., 2021 ). Much discussion has been given to best practice in terms of construct validity and similar “internal” considerations of research design as well as issues such as “bots” or fraudulent respondent activity that affect validity. However, broader considerations in terms of labour exploitation on online platforms (e.g., Shank, 2016 ) bridge internal and external research ethics, given internal norms for participant autonomy and external considerations of the public good. Less discussed are the systematic effects of widespread use of online data collection for disembodying researchers from participant communities, entrenching economies of digital labour and surveillance, and reifying a context-free individual as the object of social scientific study. These, we would argue, are methodological outcomes that may contribute to undesirable worlds, and thus are materially relevant for ethical consideration.

Other examples illustrate the opposite tension between prescriptive and evaluative research ethics. In a provocative article, Roulet et al. ( 2017 ) describe the potentials of “covert” research, where normally unacceptable practices of researcher concealment are weighed against laudable goals such as revealing workplace abuse or unethical organizational practices. In such cases, practices that are prescriptively problematic (e.g., collecting data without consent, concealing researcher identity) are defended on the grounds that the ethical goods, in terms of creating a better world, legitimate such practices. While the example of online platforms seems more defensible at the level of practice but questionable at the level of broad systemic implications, that of covert research seems more problematic at the level of practices while (possibly) defensible in terms of its ethical purposes.

More than simply a conflict between means and ends, however, such tensions reveal discrepancies between ends that are “localized” as specific practices (e.g., the goal of conducting a valid study according to current norms) and the more broad-based ends of research (e.g., creating a better world through socially reflexive knowledge production). Our challenge at the Journal of Business Ethics as editors, and our counsel to authors, reviewers and editors is to reflexively seek equilibrium between the practical ethics of research design and execution and the broader promotion of the public good that is the ultimate end of science.

Guiding Ethical Research in Business Ethics

Situating research ethics within the relationship between concrete ethical practices and evaluative goals of social improvement adds complexity to ethical decisions, forcing researchers, reviewers and editors to confront real ethical dilemmas that cannot be dissolved in mere compliance practices. We think the recognition of this complexity is salutary. It emphasizes that the review process is one moment in the broader network of evaluative practices that includes—but is not limited to—institutional ethics approval processes prior to submission, ethical and legal considerations of publishing houses and scholarly societies that administer academic production, and reception of research after publication. Each of these moments bring into light different ethical stakes, and we see our editorial role as an important but not exhaustive evaluative moment. From our perspective, our role is not to present a hurdle over which only the most flawless research can pass, but to curate a conversation with the greatest potential for scholarly generativity and progress. This makes our goal a collective one, and we judge research for its ability to promote the field, by being rigorous, by being interesting, by being reflexive, or by some combination of these epistemic virtues. From the research ethics we have outlined we derive certain guiding principles for evaluation.

Showing Links Between Methodological Design and the Broader Purpose of the Study

Business ethics scholarship should clarify its purpose through clearly articulated research questions and hypotheses, while explaining in its methods why specific research practices are important for a broader purpose, and why that purpose is itself ethically relevant. Specifically, the methods discussion should reflect how the ethics-related purpose of the study is consistent with the methodological approach adopted, both in terms of the broad design and specific practices. In short, integration of methods with the wider purpose of the study, and alignment between the two, is a mark of ethically sensitive research.

In their recent study of child labour in Indian cottonseed oil farms, D’Cruz et al. ( 2022 ) demonstrate an exemplary integration of methods and purpose to explore a topic that is notoriously difficult to study methodologically. Drawing on analyses of children’s drawings, together with detailed conversational extracts, the authors paint a powerful picture of the experience of violence in a population of working children. Rather than staying only at the level of lived experiences, however, the authors use those experiences to understand how processes of embedding and disembedding labour within society are manifested at the micro level. Thus, their visual and discursive methods become powerful tools to link everyday suffering with macro processes of economy and society.

Acknowledging the Web of Relationships Within Which Research Methods are Embedded

Each aspect of the research process, from protocol design to data collection to peer review, involves multiple actors who collectively construct the meaning of scholarship (Greenwood, 2016 ). While it may not be possible to make this network entirely visible, the ability to do so increases the transparency and value of a scholarly inquiry.

In his study of external funding on research freedom, Goduscheit ( 2022 ) uses qualitative interviews, program materials and observations to understand how funding bodies shape research outcomes. He shows how expectations from funding bodies can shape the types of topics studied, the ways in which research questions are answered and the forms of research output that are produced. Rather than simply deeming such influences to be unethical, he analyses the positive and negative features of the evolving relationships between researchers and funding bodies and their implications for developing scholarship.

Similarly acknowledging relationships but on a very different topic, Allen et al. ( 2019 ) describe the role of reflexivity in sustainability research, where ecological responsibility can result from acknowledging the multiple relationships between humans and the environment. Promoting an “ecocentric radical-reflexivity”, they point to how methods such as participatory action research and arts-based methods can help identify organizational actors as embedded in ecological relationships. In this example, as in the previous one, research is recognized as more than simply the execution of accepted standards. Rather, ethical research depends on developing sensibilities towards the complex economic and ecological relationships in which scholarship is situated.

Complementing Compliance with Purpose

Ethics should be explicitly discussed as an aspect of methodology, but this is best done when a focus on compliance with standards is complemented by a consideration of core ethical issues and a transparent discussion of how decisions were made in response to those issues. Doing so reveals those decisions as tailor-made for the case at hand and not imposed upon the case without regard for its specificities (Greenwood, 2016 ). In other words, compliance is not a sufficient criterion for ethical research methods, and a methodological approach focused exclusively on ethical compliance criteria may miss the “bigger picture” of the role of the methods in the broader scientific and social goals of the study.

Nielsen’s ( 2016 ) paper on ethical praxis and action research elaborates on how research involves ethical decision making and situated, pragmatic choices that go beyond simply ticking the correct ethical boxes. Describing these from an Aristotelian perspective, he elaborates how researcher-participant interactions give rise to emergent research concerns that are both knowledge-related problems and problems for practice. The ethics of action research in this context is about facing unique problems that cut across the researcher-practitioner divide and can draw upon but are not limited to pre-existing ethics templates.

Adopting an Explanatory Versus a Justificatory Orientation

Methodological descriptions of ethics often have the tone of justification claims legitimizing authorial choices in terms of sample, data collection or analysis. Such justifications are warranted, and are good practice, but we believe that value is added when authors are more forthright about their ethical difficulties and dilemmas. Specifically, we value their attempts to work out those dilemmas transparently for a scholarly audience, that is thereby given access into the workings of scientific decision-making process and not simply presented with a black box labeled “method”. There is more value in showing the path taken to an ethical judgement than simply defending that the end decision was a good one. This also implies that wrong turns, changes of track, and similar ethical revisions should be described and contribute to the value of a paper.

Litz’s and Turner’s ( 2013 ) study of unethical practices in inherited family firms provides an interesting case of how researchers can productively describe the dilemmas they face methodologically. Given the difficulty of gathering data about the unethical practices of family members, they candidly ask “how does one approach a question so laced with shame and stigma?”(p.303). Rather than presenting their method in terms of templates used to justify their choices, they recruit the readers directly into their dilemma and walk them through their choices, which involved confronting participants with dramatic scenarios that allowed them to disclose intimately held views more safely. Ultimately building this technique into a validation exercise and a quantitative analysis, the latter are given credibility by their grounding in the initial researcher dilemma that led to the methodological approach.

Transparency and Reflexivity in Writing and Link Between Methods and Results Sections

Because transparent and reflexive description of methods integrates theoretical considerations within the methods itself, such description allows the method to operate more organically within the broader argument of the paper. Doing so allows authors to establish links between the methods and discussion sections, to describe what went right or wrong, what the limitations and possibilities of the method were, and how future research could remedy possible shortcomings or harms of the given method.

For example, Bontempi et al. ( 2021 ) study of CSR reporting inspired by the case of the Ethiopian Gibe III dam is exemplary of how methods can be used to reflexively and transparently link methods and results. Engaging in a “counter reporting”, the study draws upon conceptual literature, archival and theoretical research, and activist on-the-ground engagement to build an alternative view of reported social engagement around hydroelectric dams. Alternating between inductive and deductive approaches, these authors were particularly reflexive and deeply transparent in their methodological description, including detailed and publicly available information from their codebook in the article’s supplementary materials. The result went beyond the standard critique of CSR discourses to actively create a counter-discourse that was both scholarly and activist in orientation. The resulting discursive struggle continued onto the blogosphere, with methodological debate between the authors and the company itself over methods. Footnote 1 We see such interaction and engagement as key to the social relevance of research.

Purpose, Care and Reflexivity

Research ethics have conventionally been concerned with the procedural aspects of scholarship, in particular the methods. Gold standard in this regard has been to not merely treat ethical standards as hurdles but as aspirations. In this sense an ethical researcher is one who does not only comply but who also cares. We suggest that care requires researcher to actively reflect on and take responsibility for their ethical practices and their research goals, and to situate their practices reflexively within a broader collective process of scholarly inquiry. Thus, we extend the notion of care to embrace the reflexivity of the researcher with regard to their own positionality (and privilege) and with regard to the purpose of research, treating ethics as central to the entire research endeavor. Complementing ethical theorizing that draws data from orthodox empirical methods, we encourage scholars to take up new forms of ethical empirical research in which connections between the conduct of the research and the motivation of the research are deeply and actively formed. The guiding principles we outline in this editorial are aimed at integrating organic, particularized and reflective narratives about the ethical conduct and goals of research in the methods section and throughout the manuscript. Editors, reviewers and authors can all contribute to treating research ethics more centrally in business ethics research.

https://www.business-humanrights.org/es/%C3%BAltimas-noticias/rejoinder-to-webuilds-response/

Allen, S., Cunliffe, A. L., & Easterby-Smith, M. (2019). Understanding sustainability through the lens of ecocentric radical-reflexivity: Implications for management education. Journal of Business Ethics, 154 (3), 781–795.

Article   Google Scholar  

Bontempi, A., Del Bene, D., & Di Felice, L. J. (2021). Counter-reporting sustainability from the bottom up: The case of the construction company WeBuild and dam-related conflicts. Journal of Business Ethics, 2021 , 1–26.

Google Scholar  

D’Cruz, P., Noronha, E., Banday, M. U. L., & Chakraborty, S. (2022). Place matters:(Dis) embeddedness and child labourers’ experiences of depersonalized bullying in Indian Bt cottonseed global production networks. Journal of Business Ethics, 176 (2), 241–263.

DuBois, J. M., Beskow, L., Campbell, J., Dugosh, K., Festinger, D., Hartz, S., & Lidz, C. (2012). Restoring balance: A consensus statement on the protection of vulnerable research participants. American Journal of Public Health, 102 (12), 2220–2225.

Goduscheit, R. C. (2022). No strings attached? Potential effects of external funding on freedom of research. Journal of Business Ethics, 176 (1), 1–15.

Greenwood, M. (2016). Approving or improving research ethics in management journals. Journal of Business Ethics, 137 (3), 507–520.

Islam, G., & Greenwood, M. (2021). Reconnecting to the social in business ethics. Journal of Business Ethics, 170 (1), 1–4.

Hansson, S. O. (2006). Informed consent out of context. Journal of Business Ethics, 63 (2), 149–154.

Hollenbeck, J. R., & Wright, P. M. (2017). Harking, sharking, and tharking: Making the case for post hoc analysis of scientific data. Journal of Management, 43 (1), 5–18.

Kerr, N. L. (1998). HARKing: Hypothesizing after the results are known. Personality & Social Psychology Review, 2 , 196.

Litz, R. A., & Turner, N. (2013). Sins of the father’s firm: Exploring responses to inherited ethical dilemmas in family business. Journal of Business Ethics, 113 (2), 297–315.

Newman, A., Bavik, Y. L., Mount, M., & Shao, B. (2021). Data collection via online platforms: Challenges and recommendations for future research. Applied Psychology, 70 (3), 1380–1402.

Nielsen, R. P. (2016). Action research as an ethics praxis method. Journal of Business Ethics, 135 (3), 419–428.

Roulet, T. J., Gill, M. J., Stenger, S., & Gill, D. J. (2017). Reconsidering the value of covert research: The role of ambiguous consent in participant observation. Organizational Research Methods, 20 (3), 487–517.

Shank, D. B. (2016). Using crowdsourcing websites for sociological research: The case of Amazon Mechanical Turk. American Sociologist, 47 (1), 47–55.

Williams, B. (1985). Ethics and the limits of philosophy . Harvard University Press.

Download references

Author information

Authors and affiliations.

Grenoble Ecole de Management and IREGE, Grenoble, France

Faculty of Business and Economics, Monash University, Melbourne, VIC, Australia

Michelle Greenwood

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Gazi Islam .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Islam, G., Greenwood, M. Ethical Research in Business Ethics. J Bus Ethics 182 , 1–5 (2023). https://doi.org/10.1007/s10551-022-05301-z

Download citation

Published : 29 November 2022

Issue Date : January 2023

DOI : https://doi.org/10.1007/s10551-022-05301-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Research ethics
  • Reflexivity
  • Research purpose
  • Methodology
  • Research integrity
  • Social impact
  • Beyond compliance

Advertisement

  • Find a journal
  • Publish with us
  • Track your research
  • Harvard Business School →
  • Faculty & Research →

Publications

  • Global Research Centers
  • Case Development
  • Initiatives & Projects
  • Research Services
  • Seminars & Conferences
  • Publications →

Show Results For

  • All HBS Web  (114,585)
  • Faculty Publications  (57,713)

WorkingPapers →

No results found in faculty publications.

  • Were any results found in one of the other content buckets on the left?
  • Try removing some search filters.
  • Use different search filters.

35 years of research on business intelligence process: a synthesis of a fragmented literature

Management Research Review

ISSN : 2040-8269

Article publication date: 7 December 2020

Issue publication date: 7 May 2021

The business intelligence (BI) research witnessed a proliferation of contributions during the past three decades, yet the knowledge about the interdependencies between the BI process and organizational context is scant. This has resulted in a proliferation of fragmented literature duplicating identical endeavors. Although such pluralism expands the understanding of the idiosyncrasies of BI conceptualizations, attributes and characteristics, it cannot cumulate existing contributions to better advance the BI body of knowledge. In response, this study aims to provide an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones.

Design/methodology/approach

This paper reviews 120 articles spanning the course of 35 years of research on BI process, antecedents and outcomes published in top tier ABS ranked journals.

Building on a process framework, this review identifies major patterns and contradictions across eight dimensions, namely, environmental antecedents; organizational antecedents; managerial and individual antecedents; BI process; strategic outcomes; firm performance outcomes; decision-making; and organizational intelligence. Finally, the review pinpoints to gaps in linkages across the BI process, its antecedents and outcomes for future researchers to build upon.

Practical implications

This review carries some implications for practitioners and particularly the role they ought to play should they seek actionable intelligence as an outcome of the BI process. Across the studies this review examined, managerial reluctance to open their intelligence practices to close examination was omnipresent. Although their apathy is understandable, due to their frustration regarding the lack of measurability of intelligence constructs, managers manifestly share a significant amount of responsibility in turning out explorative and descriptive studies partly due to their defensive managerial participation. Interestingly, managers would rather keep an ineffective BI unit confidential than open it for assessment in fear of competition or bad publicity. Therefore, this review highlights the value open participation of managers in longitudinal studies could bring to the BI research and by extent the new open intelligence culture across their organizations where knowledge is overt, intelligence is participative, not selective and where double loop learning alongside scholars is continuous. Their commitment to open participation and longitudinal studies will help generate new research that better integrates the BI process within its context and fosters new measures for intelligence performance.

Originality/value

This study provides an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones. By so doing, the developed framework sets the ground for scholars to further develop insights within each dimension and across their interrelationships.

  • Business intelligence
  • Literature review
  • Antecedents

Talaoui, Y. and Kohtamäki, M. (2021), "35 years of research on business intelligence process: a synthesis of a fragmented literature", Management Research Review , Vol. 44 No. 5, pp. 677-717. https://doi.org/10.1108/MRR-07-2020-0386

Emerald Publishing Limited

Copyright © 2020, Yassine Talaoui and Marko Kohtamaki.

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

The business intelligence (BI) process research has grown exponentially during the past three decades into a fragmented state drawing from a diverse set of studies with widely different contributions ( Talaoui and Kohtamäki, 2020 ). Although this pluralism is necessary for the BI process research to generate momentum from insightful findings, it can yield a disjointed theoretical progress if it lacks proper literature reviews that uncover what is already known and set a direction for the way ahead (Hart, 1998 ; Rowe, 2014). Unfortunately, extant reviews of the BI process research still focus on the scheme that BI follows to provide actionable intelligence for organizations to act upon (Jourdan et al. , 2008 ) rather than the context where this process occurs and guide organizations (Bingham and Eisenhardt, 2011 ; Loock and Hinnen, 2015 ). For instance, the stock of previous reviews on BI research focused on its attributes and conceptualization (Ekbia et al. , 2015 ), its methodologies and research strategies (Jourdan et al. , 2008 ), its application to operations models (Roden et al. , 2017 ), its contribution to business value (Trieu, 2017 ) or decision-making (Mora et al. , 2005 ), its dimensions and taxonomy (Holsapple et al. , 2014 ), its usage (Watson and Wixom, 2007 ), its field development (Arnott and Pervan , 2005, 2014 ; Toit, 2015 ), its attitudes (Rouach and Santi, 2001 ), its characteristics and applications (Chen et al. , 2012 ; Eom and Kim, 2006 ; Moro et al. , 2015 ), its technologies and challenges (Shim et al. , 2002 ; Sivarajah et al. , 2017 ) and its trends (Watson, 2009 ).

To this date, no literature review has examined the BI process and its interrelationships with the organizational context. To address this gap, our paper synthesizes the body of knowledge of the BI process to discern patterns of the interrelated relationships of its characteristics, and its context, i.e. antecedents and outcomes (Hutzschenreuter and Kleindienst, 2006 ; Rajagopalan et al. , 1993 ; Van De Ven, 1992 ). We follow other scholars’ conceptualization of BI process as an integrative sequence that encompasses the collection, transformation and usage (Chen et al. , 2012 ; Davenport and Paul Barth, 2012 ; Trieu, 2017 ) that occurs in an organizational context, exerts an influence upon it and is shaped by its antecedents (Bingham and Eisenhardt, 2011 ; Loock and Hinnen, 2015 ).

To capture the BI process within its context, we follow the process framework of Hutzschenreuter and Kleindienst (2006) , Rajagopalan et al. (1993) and Van De Ven (1992) for it allows to position the BI process within its organizational context and explore their interrelated linkages. In this vein, we purposefully follow Levy and Ellis (2006) and Webster and Watson (2002) ’s “effective methodology” of conducting systematic reviews in cross-disciplinary research such as the BI process body of knowledge and adheres to its processual scheme to select 120 articles published in top tier ABS ranked journals that we synthesize and integrate drawing from the process view framework that emphasizes the role of organizational context (Hutzschenreuter and Kleindienst, 2006 ; Rajagopalan et al. , 1993 ; Fischer et al. , 2016 ; Vaara and Lamberg, 2014 ). By so doing, we seek to synthesize the contributions of prior studies on the BI process and its organizational context and pinpoint to gaps in linkages across the BI process, its antecedents and outcomes for future researchers to build upon. The paper begins with a detailed explanation of our systematic method, then presents our synthetic review and concludes with research gaps for further studies.

Methodology

It addresses the peculiar and cross-disciplinary nature of the IS research in general and the BI body of knowledge in particular.

It follows a process protocol of literature reviews that fits our process perspective of integrating the BI body of knowledge.

Following Levy and Ellis (2006) , a high-quality input yields a high-quality output if it adheres to comprehensiveness, quality and relevance inclusion criteria. To ensure comprehensiveness, we go beyond the IT contributions on BI and extend our search scope beyond one database to capture all fruitful work regardless of its inherent discipline (Levy and Ellis, 2006 ). We, therefore, use four scientific databases, reputable among scholars of management, marketing and information management fields, namely, ABI/Inform, EBSCO academic search elite, EBSCO business premier, Emerald journals (Levy and Ellis, 2006 ; Webster and Watson, 2002 ). We conducted a pilot search of keywords in the aforementioned databases with two keywords, namely, BI and competitive intelligence. The intention of this trial was to gather all keywords related to both concepts. In total, 26 keywords were deemed appropriate for this review. Boolean operators (“AND” and “OR”) and the asterisk “*” wildcard were used to concatenate the keywords set to generate multiple query strings that returned 11,745 hits across the four databases from 1985 through 2020 as Table 1 depicts. We selected 1990 as a starting year of our search as it represents the inception of BI (Chen et al. , 2012 ; Davenport et al. , 2001 ). A first scrutiny of the hits sought the elimination of duplicates shrinking the set of papers to 780 including conference papers, which we excluded because their research rigor is inferior to top journals and are not subjected to a rigorous peer review process (Culnan, 1978 ; Levy and Ellis, 2006 ; Webster and Watson, 2002 ). Besides, the high quality input criterion Levy and Ellis (2006) and Webster and Watson (2002) impose limits our sample to articles published in high quality peer reviewed journals of a reputable ranking because they are likely to contain the major contributions we ought to deal with to ensure rigor and leading theoretical discussions on BI (Levy and Ellis, 2006 ; Vogel, 2012 ; Webster and Watson, 2002 ). Therefore, we chose the ABS journal ranking because it offers an extensive cross-disciplinary list that is corroborated by a documented hybrid and iterative ranking process based upon peer reviews, peers’ consensus and citations (Mingers and Willcocks, 2017 ; Morris et al. , 2009 ), which, in turn, offers us a credible guide that we can gauge papers against with confidence (Levy and Ellis, 2006 ; Morris et al. , 2009 ; Webster and Watson, 2002 ). This high-quality criterion reduced our sample to 290 articles whose abstracts we read and evaluated against our relevance criterion that, based on the research gap and motivation, deems only articles addressing BI process, antecedents or outcomes relevant to the review at hand. This step reduced the sample to 113 articles that contain one or several linkages to the BI process, antecedents or outcomes. To verify the comprehensiveness of our sample and prevent the exclusion of any older and relevant contribution, we conducted a backward search that consists of reviewing the reference lists in our final set of papers to identify any work that our time frame criterion might have excluded and/or that our databases search might not have revealed (Bandara et al. , 2015 ; Levy and Ellis, 2006 ; Müller and Jensen, 2017 ; Thennakoon et al. , 2018 ; Webster and Watson, 2002 ). Our backward search analyzed each title in the reference lists of the 113 articles and identified 7 seminal works published prior to 1990 such as El Sawy (1985) and Ghoshal and Kim (1986) , which, in turn, extended our final sample to 120 articles. We gauged the census of this review complete when no new concepts or relationships were identified in the literature set (Levy and Ellis, 2006 ; Webster and Watson, 2002 ).

A synthetic framework of the business intelligence process

According to Levy and Ellis (2006) and Webster and Watson (2002) , a good literature review offers a complete census of its synthesis and follows an analytical framework to structure the body of knowledge it deals with. As a corollary, we followed the process linkage exploring framework of Hutzschenreuter and Kleindienst (2006) and Rajagopalan et al. (1993) because it emphasizes the role of organizational context (Vaara and Lamberg, 2014 ) and the mediating mechanisms that reveal the causality between antecedents and outcomes (Fischer et al. , 2016 ). We coded all articles using a two-digit key (01–120) that we plotted in Table 2 to provide summaries of the studies. Our thorough review of the 120 articles revealed shared patterns along which three streams were discernable, namely, antecedents, BI process and outcomes. In addition, our analysis revealed that each article focused on different interrelationships across the organizational context of the BI process. For the sake of comprehensiveness and in-depth analysis, we marked each article with a linkage code composed of a letter designating the contextual domain [(1) antecedents; (2) BI process; and (3) outcome] and a number that refers to the factor responsible of the relationship between contextual domains:

Antecedents . Similar to biological organisms, firms’ actions are often constrained by their external environments (Brownlie, 1994 ). This implies that organizations should constantly monitor their respective environments to ensure the detection of plausible alterations susceptible of jeopardizing their competitive advantage. Their BI processes are, hence, influenced by environmental factors (A-I) such as uncertainty ( Hubert and Daft, 1987 ), complexity ( Child, 1972 ), rate of change ( Daft et al. , 1988 ), importance ( Aaker, 1983 ; Pfeffer and Salancik, 1978 ), culture (Leidner et al. , 1999 ) and competitive pressures ( Zhu and Kraemer, 2005 ). Further influence on the BI process can be attributed to the organizational context (A-II). This may include organizational factors such as size (Yasai-Ardekani and Nystrom, 1996 ), institutional isomorphism ( DiMaggio and Powell, 1983 ), core technologies (Thompson, 1967), structural flux (Maltz and Kohli, 1996 ), market orientation ( Narver and Slater, 1990 ) and IT sophistication ( Armstrong and Sambamurthy, 1999 ). Finally, managerial and individual attitudes (A-III) affects the BI process through managerial heterogeneity (Cho, 2006 ), experience ( Thomas et al. , 1991 ), managerial attitude (Qiu, 2008 ; Pryor et al. , 2019 ), absorptive capacity (Elbashir et al. , 2011 ) and decision roles ( Mintzberg, 1973 ).

BI process. While alterations in the aforementioned antecedents are believed to impact the BI process, characteristics of this latter are also crucial for understanding the different patterns of the BI process literature. At the outset, the intelligence collection phase (B-I) is pictured as the first link between a firm and its environment, whereby it can comprehend the happenings and remain vigilant to changes ( Hambrick, 1981 ; Lönnqvist and Pirttimäki, 2006 ; Turban et al. , 2010 ). Traditionally, the collection phase was fed through open and human sources. However, with the advent of the internet, it faced the challenge of information overload (Chen et al. , 2002 ). The abundance of data created a lack of executives’ attention, and called for a more tailored intelligence transformation phase (B-II) to support managerial action ( Fabbe-Costes et al. , 2014 ; Christen et al. , 2009 ). In response, the BI analysts used computerized decision support systems to prepare the requested intelligence for executives (Leidner and Elam, 1993 ). Such decision aids stimulated, eventually, the design of the executive information system with the purpose of retrieving the information related to internal operations and the business environment ( Turban and Schaeffer, 1987 ; Turban et al. , 2010 ). A further scrutiny of the transformation phase (B-II) reveals that both structured and unstructured data are extracted from operational and external sources, then prepared and loaded into the data warehouse, for a later clustering into Data Marts. This process is usually performed through the extract-transform-load (ETL) application. On the one hand, the data warehouse usually deploys a relational database management system (RDBMS) to store data and rapidly execute queries across a wide range of data. On the other hand, the data warehouse is corroborated by an online analytic processing (OLAP) server in charge of filtering, and drawing thorough analysis (slicing and dicing, drill down…) of the data, which, in turn, is communicated to the user interface (dashboards, spreadsheets…) that yields the way to the Usage phase (B-III) (Chaudhuri et al. , 2011 ; Sen and Sinha, 2005 ; Singh et al. , 2002 ). This last phase of the BI process offers the required capability to conduct predictive analysis, streamline intelligence content and ensure an effective practice of the BI process and its alignment across organizational culture, analytical capabilities and the human capital propensity for BI (Holsapple et al. , 2014 ; Viaene and Bunder, 2011 ; Chaudhuri et al. , 2011 ; Sen and Sinha, 2005 ; Singh et al. , 2002 ).

Outcomes . The BI process was found related to certain outcomes (C): of a strategic order (C-I) such as strategic management process (Hofer, 1978 ) and managerial representations of competitive advantage ( Porac and Thomas, 1990 ); at a firm performance level (C-II) such as share of wallet ( Zeithaml, 1988 ), customer perceived value (Hughes et al. , 2013 ), product development (Lynn, 1998) and superior sales growth (Slater and Narver, 2000 ); related to decision-making (C-III) including decision-making speed (Leidner and Elam, 1995 ), problem identification speed (Leidner and Elam, 1995 ) and extent of analysis ( Miller and Friesen, 1980 ); and under the umbrella of organizational intelligence (C-IV) encompassing perceived intelligence quality (Popovič et al. , 2012 ), perceived information availability (Leidner and Elam, 1995 ), intelligence use (Maltz and Kohli, 1996 ), receiver’s trust ( Moorman et al. , 1992 ) and insight generation speed (Heinrichs and Lim, 2003 ).

After plotting the linkages of each study in Table 2 , we sought to allow for a visual display of the linkages explored, and the ones overlooked, therefore we juxtaposed the elements of the BI process (BI-II-III), antecedents (AI-II-III) and outcomes (CI-II-III) in a review matrix, exhibited in Figure 1 , where rows represent the independent variables, and columns represent the dependent variables, and each coded study (01–120) is allocated into its appropriate linkage cell. Finally, we synthesized and depicted the aforementioned interrelationships in the form of an integrative framework we present in Figure 2 . The framework displays three clusters of antecedents (A), namely, environmental factors (A-I), organizational factors (A-II) and managerial and individual attitudes (A-III); three characteristics of the BI process (B), namely, collection (B-I), transformation (B-II), usage (B-III); and four sets of outcomes (C), namely, strategic (C-I), firm performance (C-II), decision-making (C-III) and organizational intelligence (C-IV). Research within the framework falls into four categories, namely, the first one explores the influence of the antecedents on the BI process (A-I-II-III – B-I-II-III); the second explores the BI phases separately, describing the state of affairs and prescribing optimal processes (B-I-II-III); the third set of studies examines the linkages between the BI process and its ensuing outcomes (B-I-II-III – C-I-II-III-IV); and the fourth set of studies examines the moderating role of antecedents on the relationship between the BI process and outcomes (A-I-II-III – B-I-II-III – C-I-II-III-IV).

Literature synthesis

Stream 1: the influence of antecedents on the bi process (links a-i-ii-iii – b-i-ii-iii).

The environmental influence on the BI process motivated multiple studies that shaped the first cluster of this stream, although the nature of this linkage is still equivocal. This is due to inconsistent views of environmental heterogeneity and uncertainty, and the partial accounts of the BI process. These treatments, rooted in management, bifurcate into two strands. First, a constellation of studies that focus on the frequency and scope of BI collection (Boyd and Fulk, 1996 ; Daft et al. , 1988 ; Ebrahimi, 2000 ; Elenkov, 1997 ; Maltz and Kohli, 1996 ; May et al. , 2000 ; Sawyerr, 1993 ). Their findings are at best exploratory and piecemeal as they adopt a “one rule fits all” approach to different environmental layers (e.g. political, customer, direct and remote) let alone country-level contexts (e.g. developed vs developing). By so doing, they overlook the peculiarities of developing economies where other informal pressures and singularities (cultural, institutional and cognitive) moderate the relationship between the environment and BI collection. The second thread of studies examine executives’ goal orientations (Pryor et al. , 2019 ), strategic priorities (Opait et al. , 2016 ) quality of information source (El Sawy, 1985 ; Jones and McLeod, 1986 ; Robinson and Simmons, 2017 ), experience and educational background (Cho, 2006 ), entrepreneurial attitude (Qiu, 2008 ), intuitive judgments (Constantiou et al. , 2019 ) and boundary spanners’ intelligence effort (Le Bon and Merunka, 2006 ; Mariadoss et al. , 2014 ), customer orientation (Hughes et al. , 2013 ). Unfortunately, these studies overlook to consider the collection activity as a formal unit within the organization, and explore the informal BI collection and source selection of boundary spanners and executives despite previous evidence of their bounded rationality (Cyert and March, 1963 ). Besides, we still know little about the upper management’s cognitive and managerial characteristics, which implicitly determine their BI collection, not to mention the need to verify, which leadership approach serves best this activity. Credit is given to Elbashir et al. (2011) , being the only scholars of this stream who examined the influence of the absorptive capacity of managers on BI assimilation. Similar studies must follow this line to explore the influence of absorptive capacity on the entirety of the BI process. To this date, all we know, in this context, is the positive influence of the absorptive capacity of managers on organizations’ BI assimilation (Elbashir et al. , 2011 ). Further, studies examining boundary spanners collecting and gathering of intelligence like their engagement to their desire for upward mobility and recognition. Therefore, boundary spanners’ involvement in BI collection is a variable of managerial stimulation, and hence, more studies are needed to examine the moderating effect of management appraisal on the linkage between BI collection and boundary spanners’ scope and frequency of BI collection.

The significant focus of management scholars on the environment and the managerial and individual factors as the primary antecedents of the BI process came at the expense of overlooking the organizational factors susceptible of influencing the BI process. Conversely, studies, rooted in marketing and decision support, shed light on the ability of the organizational context to alter the BI process, particularly the collection phase and its linkage to decentralized organizational culture (Babbar and Rai, 1993), size and core technologies (Yasai-Ardekani and Nystrom, 1996), inter-functional distance and structural flux (Maltz and Kohli, 1996 ), organizational market orientation (Qiu, 2008 ), resource scarcity (Christen et al. , 2009 ), institutional isomorphism (Ramakrishnan et al. , 2012 ), analytical culture (Holsapple et al. , 2014 ; Popovič et al. , 2012 ); IT infrastructure (Elbashir et al. , 2011 ), organizational culture ( Leidner and Elam, 1995 , 1999 ) and organizational beliefs (Reinmoeller and Ansari, 2016 ). Although harmonious in its uniformity, this line of research was limited to the BI collection phase except for two studies that extended their focus to BI support and its linkage to organizational orientation and culture (Lin and Kunnathur, 2019 ) and organizational tensions (Kowalczyk and Buxmann, 2015 ).

Stream 2: the business intelligence process (links B-I-II-III)

The review of the literature illustrates a shared conceptual meaning, across marketing and management scholars, regarding the nature of BI collection as an activity that seeks to proactively monitor a dynamic environment and that ends once data has been collected (Babbar and Rai, 1993 ; Bernhardt, 1994 ; Calof and Wright, 2008 ; Slater and Narver, 2000 ). Unfortunately, the literature within this stream was considerably explorative of the BI collection activities and practices ( Taylor, 1992 ; Vedder et al. , 1999 ; Dishman and Calof, 2008 ; Wright et al. , 2009 ). While some marketing scholars emphasized the use of Bayes’ theorem to determine when more collection becomes cost (Michaeli and Simon, 2008 ), other explored information sources companies use (Fleisher et al. , 2008 ; Lasserre, 1993 ; Peyrot et al. , 1996 ) or developed indices to evaluate the adaptability of firm capabilities to BI collection of boundary spanners (Hallin et al. , 2017 ) or to collect BI from disaggregated data (Kumar et al. , 2020 ). While a stream of scholars examined trust in BI collection quality (Robinson and Simmons, 2017 ), others investigated the type and source of the collected intelligence (Peyrot et al. , 1996 ) or the capabilities to decode each type of intelligence be it soft (Lasserre, 1993 ) or web-based (Fleisher, 2008 ; Pawar and Sharda, 1997 ). On the other hand, an apparent discussion within this stream involves the collection approach, i.e. the comprehensive vs the project-based model. A priori, the comprehensive mode seems a better fit to broad strategic decisions, while the ad-hoc approach is more project-oriented. The narrowed focus of the project-based approach is believed to generate more accurate intelligence compared to the holistic model (Prescott and Smith, 1987 ). Nonetheless, this paradox shifts the debate to the culture and the core business of organizations. For some scholars, organizations might choose to participate in the environment rather than passively observing it (Brownlie, 1994 ). By so doing, the underpinning motive of such an activity swings from BI collection to sense giving (Gioia and Chittipeddi, 1991 ), from informing to influencing, from a mere passive to proactive BI collection (Brownlie, 1994 ). Other scholars suggest that ambidexterity arises as a reasonable option whereby the firm can develop two cultures, namely, one for sensing peripheral patterns; the other is core business-oriented (Brown, 2004 ; O’Reilley and Tushman, 2002 ; Ghosal and Westney, 1991 ; Gilad et al. , 1993 ).

Conversely, literature with scaffolding in information systems and decision support, fueled by the desire of bridging the gap between the business user and BI transformation and usage, criticized the firms’ focus on collection over analysis despite the challenge of information overload and gave significant attention to testing in-house acquisition techniques of BI collection to curb the exorbitant price of third-party sources by proposing Limited Information NBD/Dirichlet (LIND) models to infer key competitive measures based on site-centric data (Zheng et al. , 2012 ) or two level conditional random fields (CRF) models to extract comparative relation features from entities and words (Xu et al. , 2011 ) or event detection (NEED) applications that perform events detection based on properties extracted from news stories (Wei and Lee, 2004 ) or proposed 80/20 rule-based models for reduction of cycle time (Kohavi et al. , 2002 ; Liu and Wang, 2008 ) or suggested data slicing and dicing technologies, which index and analyze documents collected from websites matching users’ interest (Chen et al. , 2002 ) or grant rapid access displays of data ( Walters et al. , 2003 ). One commonality within this research stream is the evaluation of the proposed tool against the commercial engines (Chen et al. , 2002 ; Zheng et al. , 2012 ; Xu et al. , 2011 ).

The coming of the WEB 2.0, digitization, the internet of things and Big Data further challenged the BI process by technical issues in regard to (a) the time consuming process of transforming and storing structured and unstructured data into the data warehouse, (b) the lack of techniques capable of, simultaneously, alleviating data heterogeneity and integrating slice, dice, roll-up and drill-down dimensions for data evaluation, (c) the multidimensional view of data through OLAP, which needs continuous performance improvement; (d) the rising volume of data, which challenges the capacity of the RDBMSs to query and store data, (e) the pressure on ETL to filter, cluster and integrate current operational data, for real time decision-making support and (d) detect hidden patterns in terabytes of data (Chaudhuri et al. , 2011 ). This ushered most empirical studies in this stream to shift their attention to what Chen et al. (2012) refer to as BI 3.0 or mobile BI and accordingly update BI technologies and develop new applications that can detect patterns in terabytes of data, diminish further information overload, and merge structured with unstructured data (Chen et al. , 2012 ; Srivastava and Cooley, 2003 ; Chung et al. , 2005 ; Chau et al. , 2007 ; Cheng et al. , 2009 ; Lin et al. , 2009 ) or decipher frameworks for evaluation BI process based on users’ feedback ( Brichni et al. , 2017 ) or modeling its best practice approach for less challenges ( Vidgen et al. , 2017 ; Wang et al. , 2018a ; 2018b ). However, this might not be enough to ensure an effective usage of BI as this latter hinges on the alignment across organizational culture, analytical capabilities and the human capital propensity for BI (Holsapple et al. , 2014 ; Viaene and Bunder, 2011 ). No empirical studies have yet to investigate this triadic relationship and its moderating variables for better BI usage.

Stream 3: the influence of the business intelligence process on outcomes (links B-I-II-III – C-I-II-III-IV)

Drawing from marketing research, scholars explored the influence of BI collection and managerial representation of competitive advantage (Qiu, 2008 ), managerial belief in formulating and implementing strategies (Vedder et al. , 1999 ) improvement of marketing strategies (Fleisher et al. , 2008 ). Other scholars suggested that BI collection translates to share of wallet and profit margin (Hughes et al. , 2013 ) and sales performance (Mariadoss et al. , 2014 ), product innovation and competitive pricing strategies (Trim and Lee, 2008 ), price optimization, expanding product lines and service improvements (Peyrot et al. , 1996 ), superior sales growth, customer satisfaction (Slater and Narver, 2000 ), innovation (Tanev and Bailetti, 2008 ) and profitability and revenues increase (Wright et al. , 2009 ). Although these studies might pinpoint to the relationship between BI collection and strategic outcomes, the question of whether or not this step of the BI process contributes to strategy formulation or implementation remains ambiguous.

Furthermore, the available evidence, drawing from management, demonstrates two stocks of research: one that indicates a clear relation between BI support and productivity enhancement, and information distribution cost savings (Belcher and Watson, 1993 ), price competition (Abramson et al. , 2005 ), firm performance (Akter et al. , 2016 ; Gupta and George, 2016 ), business value (Côrte-Real et al. , 2020 ; Seddon et al. , 2016 ; Wang et al. , 2018a ; 2018b ), innovation (Ghasemaghaei and Calic, 2020 ); another that suggests BI support adds value to the organizational intelligence in at least two interrelated ways, namely, workforce learning (Cheung and Li, 2012 ), information access quality (Popovič et al. , 2012 ), data security (Gordon and Loeb, 2001 ; McCrohan, 1998 ; Sheng et al. , 2005 ; Vedder et al. , 1999 ) and intelligence use (Maltz and Kohli, 1996 ) and organizational knowledge management (Côrte-Real et al. , 2017 ; Shollo and Galliers, 2015 ).

The research strand, rooted in information systems, was limited to providing benchmarks of their BI support technologies to which they ascribe a linkage to the decision-making process. Scholars presented their prototypes and evaluated their success for mergers and acquisitions (Lau et al. , 2012 ), and banking and financial decisions (Moro et al. , 2015 ). Besides, information systems scholars had a penchant for solving tactical issues because of their straightforward evaluation or to scholars’ approach to BI, as a set of separate technologies rather than a holistic decisional paradigm. Therefore, their contributions integrate BI technologies such as data warehouse and data mining into BI support and address its ability to improve firm performance indicators. Studies examined and demonstrated the positive impact of BI support on crafting personalized customer strategies (Li et al. , 2008 ), decision-making (Aversa et al. , 2018 ), strengthen innovation capability (Mikalef et al. , 2019 ), business value (Sharma et al. , 2014 ), identify sales ordering patterns (Cheung and Li, 2012 ), business model insight (Heinrichs and Lim, 2003 ). Research, herein, seems obsessed with solving tactical issues because of their straightforward evaluation or to scholars’ approach to BI as a set of separate technologies rather than a holistic decisional paradigm.

Studies rooted in decision support empirically examined the linkage between BI support and the speed of problem identification, decision-making speed and the extent of analysis (Leidner et al. , 1999 ; Leidner and Elam, 1993 ; Leidner and Elam, 1995 ; Belcher and Watson, 1993 ; Arnott et al. , 2017 ). Still little is known about how BI collection influences decision-making. While it is true that explorative studies reveal the utility of BI collection for organizational decision-making (Ghosal and Westney, 1991 ; Vedder et al. , 1999 ), no empirical evidence has yet examined this belief. The outcome of BI collection on decision-making might be, as well negative than positive, at least for competitor analysis blind spots in the case of capacity expansion, new business entry and acquisition (Zajac and Bazerman, 1991 ). One might keep wonder about the contexts and the extent to which BI can bring value to the decision-making if scholars’ attention does not shift from explorative, inductive studies to more cross functional longitudinal ones to further delve into the relation between BI and the decision-making process.

Stream 4: the moderating effects of antecedents on the relationship between the business intelligence process and outcomes (links A-I-II-III – B-I-II-III–C-I-II-III-IV)

This stream of research is threefold, namely, research at the individual level, organizational level and environment level. At the individual level, scholars, with scaffolding in marketing research, investigated the moderating role of boundary spanners adaptive skills on BI collection sales performance outcomes (Hughes et al. , 2013 ; Mariadoss et al. , 2014 ; Ahearne et al. , 2013 ), the moderating role of the relationship between intelligence officers and strategists on boosting product innovation and generating competitive pricing strategies (Trim and Lee, 2008 ), the moderating effect of the relationship between district managers centrality and district BI quality diversity on salespersons’ performance (Ahearne et al. , 2013 ). Unfortunately, studies rooted in management and information systems or decision support overlooked the moderating role of antecedents at the individual level on the relationship between BI process and outcomes.

At the organizational level, management scholars explored the moderating role of the alignment between business strategy and IT on the relationship between BI usage and business value (Côrte-Real et al. , 2019 ; Urbinati et al. , 2019 ), the moderating role of the relationship between the alignment of business strategy and BI analytics on BI usage and firm performance (Akter et al. , 2016 ), the moderating role of deep organizational structure on the relationship between BI usage and strategy outcomes (Audzeyeva and Hudson, 2015 ), the moderating role of organizational learning and ambidextrous organizational culture on the relationship between BI usage and business value (Bordeleau et al. , 2020 ) and BI usage and organizational learning (Fink et al. , 2016 ) and the mediating role of dynamic capabilities on the relationship of BI usage and firm performance (Wamba et al. , 2017 ). In like fashion, marketing scholars investigated the moderating effects of the relationships between organizational antecedents such as structural flux and perceived intelligence quality on BI usage (Maltz and Kohli, 1996 ), the curvilinear relationship between organizational size and BI use, as well as between marketing departments size and BI usage (Peyrot et al. , 2002 ). On the other hand, decision support scholars shed light on the moderating role of decision-making culture on the relation between the BI content quality and the BI usage (Popovič et al. , 2012 ), the moderating role of the relationship between organizational readiness and design factors on the relationship between BI usage and business value (Popovič et al. , 2012 ) and the moderating role of the information system BI infrastructure investment on the relationship between BI usage and value targets (Grover et al. , 2018 ).

At the environmental level, marketing scholars showcased the moderating role of the relationship between perceived competitiveness of the environment and the perceived value of BI quality on BI usage and organizational outcomes (Maltz and Kohli, 1996 ; Peyrot et al. , 2002 ). On the other hand, one study, rooted in information systems, explored the moderating role of the environment dynamism on the influence of the BI usage on value creation (Chen et al. , 2015 ).

Future research

35 years of BI process research seemed fragmented and scattered around similar areas, with scant initiatives to weave strands of lookalike contributions into one unifying paradigm. Research spawned a considerable number of articles partly prescriptive, partly explorative, revealing discrepancies between theory and practice across the BI process, antecedents and outcomes. Figure 3 displays the covered and underexplored areas in each of the aforementioned streams. Antecedents exploring studies focused on the supply side of the market to formulate viable strategies for an existing industry. These contributions unanimously adopted an outside in perspective, examining the external environmental influence on the frequency and mode of BI collection. They adopted the same structuralist approach to different business environments and neglected the influence of cultural factors and institutional pressures on the BI process. Another limitation of this stream is the exclusiveness of collection activity to executives, rather than the organization as a whole, following a top-down approach in an apparent discontinuity from the literature on bounded rationality that grant executives limited capacity to fathom the dynamism of the environment.

The significant focus on the environment as the primary antecedent of BI collection marginalized discussions on organizational factors susceptible of influencing the BI process. For instance, the ramifications of one single event on the BI use of multinational corporations in different settings. In this vein, managerial heterogeneity seems a potential frontier for research through which scholars shall compare heterogeneous teams to homogeneous groups of executives’ vis-a-vis their uncertainty perception and use of the BI process. Additionally, researchers still need to investigate, which structure represents an environment ripe for effective BI use: organic or mechanistic structure. Similarly, the causation link between strategic orientation and BI process is still vague, despite some studies suggest a one-way association from strategic orientation to BI collection. Moreover, contrary to the trend line of recommendation positing the BI process at the outset of the decision-making or the strategic management process, the authors of the article at hand personally encountered situations, in monopolistic economies, where the BI process was regarded more as legitimacy tools that solidify an already taken decisional or strategic choice. As a corollary, it might be crucial to incorporate the singularity of the decision-making process in developing countries, when hypothesizing coming empirical studies. Another trend line across studies examining BI use is the focus on the receiver’s trust in regard to the intelligence sender. Nonetheless, this latter’s willingness to share intelligence was treated as a given, while it is far from being the case. Particularly, in developing countries where information is shared among individuals pertaining to the same interest groups. It becomes, hence, evident to account for the sender’s trust and influence on the BI dissemination and use, in future research.

In addition, cognitive factors of managers and boundary spanners were rarely on the scholars’ agenda. After all, the environmental uncertainty is a matter of interpretation, which, in turn, is framed by intrinsic factors rooted in the person’s background. More studies, in this respect, should incorporate elements such as age, gender and personality traits. Moreover, the rationale behind decision-makers’ BI collection behavior still appears ambiguous, for there seems to be no evidence regarding the value it adds to their mental models. Another overlooked matter by scholars, caught in an everlasting development of new ways of codifying structured and unstructured data, is the ability of the BI process to acquire and communicate tacit knowledge. Another gap worth mentioning is the scarcity of studies comparing BI practices of multinational corporations in the western world to emerging countries, in a world where anything might happen any second, where new technologies disrupt the status quo of businesses, economies and political regimes. The Covid-19 epidemic, political upheavals or data privacy issues present an opportunity for researchers to examine the linkage between the BI process and strategic agility let alone employees’ and organizations’ privacy and readiness for disruption.

Finally, a myriad of research methods was adopted by scholars, to delve into issues related to the BI process phases ranging from bibliometric studies, surveys and case studies. Some were conceptual papers, whereas others field tested their hypotheses or settled for laboratory experiments. Except for qualitative exploration examining linkage between BI transformation to decision-making success, benchmarking data mining or data warehousing applications against commercial products marked most BI transformation studies, let alone the quantitative exploratory and conceptual articles representing a common trend across studies tackling BI collection. The absence of comparative studies urges researchers to invest time and money probing differences across industries, not in an exploratory superficial manner, but more as a longitudinal thorough analysis depicting whether or not the industry type is a contributing factor to the BI process. Longitudinal studies were, surprisingly, absent, notwithstanding their presence in multiple scholars’ future directions. Another advantage longitudinal studies shall have is related to the evaluation of prototypes and technologies in an accurate manner, encompassing the residual value of such applications on the organizational learning. Longitudinal studies might also enable scholars to tap into cognitive changes prior and after BI collection and usage and track front line managers intelligence use as they assume high level positions. With that said, studies shall alter to a more dynamic view of the environment capable of capturing all the various interactions among its constantly shifting elements.

Nowadays, confidential strategies and tactics are swiftly replicated; the sustainability of the competitive advantage is no longer a result of a secret recipe. Managers shall recognize that room for intuition is shrinking as the need for a rational predictability is rising. Therefore, it seems wiser and beneficial for managers to tear down their walls, and engage in double loop learning with scholars, should they want a better real time decision-making and strategic agility. This review carries some implications for practitioners and particularly the role they ought to play should they seek actionable intelligence as an outcome of the BI process. Across the studies this review examined, managerial reluctance to open their intelligence practices to close examination was omnipresent. Although their apathy is understandable, due to their frustration regarding the lack of measurability of intelligence constructs, managers manifestly share a significant amount of responsibility in turning out explorative and descriptive studies partly due to their defensive managerial participation. Interestingly, managers would rather keep an ineffective BI unit confidential than open it for assessment in fear of competition or bad publicity. Therefore, this review highlights the value open participation of managers in longitudinal studies could bring to the BI research and by extent the new open intelligence culture across their organizations where knowledge is overt, intelligence is participative, not selective and where double loop learning alongside scholars is continuous. Their commitment to open participation and longitudinal studies will help generate new research that better integrates the BI process within its context and fosters new measures for intelligence performance.

Although far from completeness, this systematic review strived to synthesize the BI process body of knowledge via an integrative process framework that pinpoints to areas of redundancies and research gaps where scholars’ attention should be directed. It is hoped that this article will encourage researchers to change perspective and adopt a more comprehensive view of the BI process aimed at contributing to its organizational context and focus its attention on the interrelationships across the BI process, antecedents and outcomes. Drawing from Levy and Ellis (2006) and Webster and Watson (2002) , we sought comprehensiveness from four databases and quality from the ABS ranking list. Therefore, this paper excludes conference papers and book chapters. A caveat regarding the 26 keywords of this study is worth mentioning, as there might surely be some articles that the query strings failed to retrieve; let alone in-press- publications, not yet available when the database search took place. Notwithstanding, a backward search of references allowed the verification of this review’s comprehensiveness, gauged near completion when no new concepts were identified in the literature set (Webster and Watson, 2002 ). However, the material upon which this scrutiny is based epitomizes an open invitation for other researchers, to compare and test whether or not the results herein stand up to close examination. After all, this is the ultimate way to expand and enrich the body of knowledge probing BI process research.

research papers on business

Linkage-exploring review matrix

research papers on business

BI process: an integrative framework

research papers on business

Synthesis of the covered and remaining areas of the literature

Systematic selection process of the articles

Aaker , D.A. ( 1983 ), “ Organizing a strategic information scanning system ”, California Management Review , Vol. 25 No. 2 , pp. 76 - 83 .

Abramson , C. , Currim , I.S. and Sarin , R. ( 2005 ), “ An experimental investigation of the impact of information on competitive decision making ”, Management Science , Vol. 51 No. 2 , pp. 195 - 207 .

Ahearne , M. , Lam , S.K. , Hayati , B. and Kraus , F. ( 2013 ), “ Intrafunctional competitive intelligence and sales performance: a social network perspective ”, Journal of Marketing , Vol. 77 No. 5 , pp. 37 - 56 .

Akter , S. , Wamba , S.F. , Gunasekaran , A. , Dubey , R. and Childe , S.J. ( 2016 ), “ How to improve firm performance using big data analytics capability and business strategy alignment? ”, International Journal of Production Economics , Vol. 182 , pp. 113 - 131 , doi: 10.1016/j.ijpe.2016.08.018 .

Armstrong , C.P. and Sambamurthy , V. ( 1999 ), “ Information technology assimilation in firms: the influence of senior leadership and IT infrastructures ”, Information Systems Research , Vol. 10 No. 4 , pp. 304 - 327 .

Arnott , D. and Pervan , G. ( 2005 ), “ A critical analysis of decision support systems research ”, Journal of Information Technology , Vol. 20 No. 2 , pp. 67 - 87 , doi: 10.1057/palgrave.jit.2000035 .

Arnott , D. and Pervan , G. ( 2014 ), “ A critical analysis of decision support systems research revisited: the rise of design science ”, Journal of Information Technology , Vol. 29 No. 4 , pp. 269 - 293 , doi: 10.1057/jit.2014.16 .

Arnott , D. , Lizama , F. and Song , Y. ( 2017 ), “ Patterns of business intelligence systems use in organizations ”, Decision Support Systems , Vol. 97 , pp. 58 - 68 .

Audzeyeva , A. and Hudson , R. ( 2015 ), “ How to get the most from a business intelligence application during the post implementation phase? Deep structure transformation at a U.K. retail bank ”, European Journal of Information Systems , Vol. 25 No. 1 , pp. 1 - 18 , doi: 10.1057/ejis.2014.44 .

Aversa , P. , Cabantous , L. and Haefliger , S. ( 2018 ), “ When decision support systems fail: insights for strategic information systems from Formula 1 ”, The Journal of Strategic Information Systems , Vol. 27 No. 3 , pp. 221 - 236 , doi: 10.1016/j.jsis.2018.03.002 .

Babbar , S. and Rai , A. ( 1993 ), “ Competitive intelligence for international business ”, Long Range Planning , Vol. 26 No. 3 , pp. 103 - 113 .

Bandara , W. , Furtmueller , E. , Beekhuyzen , J. , Gorbacheva , E. and Miskon , S. ( 2015 ), “ Achieving rigour in literature reviews: insights from qualitative data analysis and tool-support ”, Communications of the Association for Information Systems , Vol. 34 No. 8 , pp. 154 - 204 .

Belcher , L. and Watson , H. ( 1993 ), “ Assessing the value of Conoco’s EIS ”, MIS Quarterly , Vol. 17 No. 3 , pp. 239 - 269 .

Bernhardt , D.C. ( 1994 ), “ I want it fast, factual, actionable-tailoring competitive intelligence to executives’ needs ”, Long Range Planning , Vol. 27 No. 1 , pp. 12 - 24 .

Bingham , C.B. and Eisenhardt , K.M. ( 2011 ), “ Rational heuristics: the ‘simple rules’ that strategists learn from process experience ”, Strategic Management Journal , Vol. 1464 , pp. 1 - 43 , doi: 10.1002/smj .

Bordeleau , F.E. , Mosconi , E. and de Santa-Eulalia , L.A. ( 2020 ), “ Business intelligence and analytics value creation in industry 4.0: a multiple case study in manufacturing medium enterprises ”, Production Planning and Control , Vol. 31 Nos 2/3 , pp. 173 - 185 , doi: 10.1080/09537287.2019.1631458 .

Boyd , B. and Fulk , J. ( 1996 ), “ Executive scanning and perceived uncertainty: a multidimensional model ”, Journal of Management , Vol. 22 No. 1 , pp. 1 - 21 .

Brichni , M. , Dupuy-Chessa , S. , Gzara , L. , Mandran , N. and Jeannet , C. ( 2017 ), “ BI4BI: a continuous evaluation system for business intelligence systems ”, Expert Systems with Applications , Vol. 76 , pp. 97 - 112 .

Brown , J.S. ( 2004 ), “ Minding and mining the periphery ”, Long Range Planning , Vol. 37 No. 2 , pp. 143 - 151 , doi: 10.1016/j.lrp.2004.01.001 .

Brownlie , D. ( 1994 ), “ Organizing for environmental scanning: orthodoxies and reformations ”, Journal of Marketing Management , Vol. 10 No. 8 , pp. 703 - 723 .

Calof , J.L. and Wright , S. ( 2008 ), “ Competitive intelligence: a practitioner, academic and inter-disciplinary perspective ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 717 - 730 .

Chau , M. , Shiu , B. , Chan , I. and Chen , H. ( 2007 ), “ Redips: backlink search and analysis on the web for business intelligence analysis ”, Journal of the American Society for Information Science and Technology , Vol. 14 No. 4 , pp. 90 - 103 .

Chaudhuri , S. , Dayal , U. and Narasayya , V. ( 2011 ), “ An overview of business intelligence technology ”, Communications of the ACM , Vol. 54 No. 8 , pp. 88 - 98 .

Chen , D.Q. , Preston , D.S. and Swink , M. ( 2015 ), “ How the use of big data analytics affects value creation in supply chain management ”, Journal of Management Information Systems , Vol. 32 No. 4 , pp. 4 - 39 , doi: 10.1080/07421222.2015.1138364 .

Chen , H. , Chau , M. and Zeng , D. ( 2002 ), “ CI spider: a tool for competitive intelligence on the web ”, Decision Support Systems , Vol. 34 No. 1 , pp. 1 - 17 .

Chen , H. , Chiang , R. and Storey , V. ( 2012 ), “ Business intelligence and analytics: from big data to big impact ”, MIS Quarterly , Vol. 36 , pp. 1165 - 1188 .

Cheng , H. , Lu , Y.-C. and Sheu , C. ( 2009 ), “ An ontology-based business intelligence application in a financial knowledge management system ”, Expert Systems with Applications , Vol. 36 No. 2 , pp. 3614 - 3622 .

Cheung , C. and Li , F. ( 2012 ), “ A quantitative correlation coefficient mining method for business intelligence in small and medium enterprises of trading business ”, Expert Systems with Applications , Vol. 39 No. 7 , pp. 6279 - 6291 .

Child , J. ( 1972 ), “ Organizational structure, environment and performance: the role of strategic choice ”, Sociology , Vol. 6 No. 1 , pp. 1 - 22 .

Cho , T.S. ( 2006 ), “ The effects of executive turnover on top management team’s environmental scanning behavior after an environmental change ”, Journal of Business Research , Vol. 59 Nos 10/11 , pp. 1142 - 1150 .

Christen , M. , Boulding , W. and Staelin , R. ( 2009 ), “ Optimal market intelligence strategy when management attention is scarce ”, Management Science , Vol. 55 No. 4 , doi: 10.1287/mnsc.1080.0988 .

Chung , W. , Chen , H. and Nunamaker , J.F.J. ( 2005 ), “ A visual framework for knowledge discovery on the web: an empirical study of business intelligence exploration ”, Journal of Management Information Systems , Vol. 21 No. 4 , pp. 57 - 84 .

Constantiou , I. , Shollo , A. and Vendelø , M.T. ( 2019 ), “ Mobilizing intuitive judgement during organizational decision making: when business intelligence is not the only thing that matters ”, Decision Support Systems , Vol. 121 , pp. 51 - 61 , doi: 10.1016/j.dss.2019.04.004 .

Côrte-Real , N. , Oliveira , T. and Ruivo , P. ( 2017 ), “ Assessing business value of big data analytics in European firms ”, Journal of Business Research , Vol. 70 , pp. 379 - 390 , doi: 10.1016/j.jbusres.2016.08.011 .

Côrte-Real , N. , Ruivo , P. and Oliveira , T. ( 2020 ), “ Leveraging internet of things and big data analytics initiatives in European and American firms: is data quality a way to extract business value? ”, Information and Management , Vol. 57 No. 1 , p. 103141 , doi: 10.1016/j.im.2019.01.003 .

Côrte-Real , N. , Ruivo , P. , Oliveira , T. and Popovič , A. ( 2019 ), “ Unlocking the drivers of big data analytics value in firms ”, Journal of Business Research , Vol. 97 , pp. 160 - 173 , doi: 10.1016/j.jbusres.2018.12.072 .

Culnan , M.J. ( 1978 ), “ An analysis of the information usage patterns of academics and practitioners in the computer field: a citation analysis of a national conference proceedings ”, Information Processing and Management , Vol. 14 No. 6 , pp. 395 - 404 , doi: 10.1016/0306-4573(78)90004-3 .

Cyert , R.M. and March , J.G. ( 1963 ), A Behavioral Theory of the Firm , Prentice-H , Englewood Cliffs, NJ .

Daft , R.R.L.R. , Sormunen , J. and Parks , D. ( 1988 ), “ Chief executive scanning, environmental characteristics, and company performance: an empirical study ”, Strategic Management Journal , Vol. 9 No. 2 , pp. 123 - 139 .

Davenport , T. and Paul Barth , R.B. ( 2012 ), “ How ‘big data’ is different ”, MIT Sloan Management Review , Vol. 54 No. 1 , pp. 43 - 46 , available at: http://sloanreview.mit.edu/article/how-big-data-is-different/#article-authors

Davenport , T.H. , Harris , J.G. , De Long , D.W. and Jacobson , A.L. ( 2001 ), “ Data to knowledge to results ”, California Management Review , Vol. 43 No. 2 , p. 117 , available at: http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=4372997&site=ehost-live

DiMaggio , P.J. and Powell , W. ( 1983 ), “ The iron cage revisited” institutional isomorphism and collective rationality in organizational fields ”, American Sociological Review , Vol. 48 No. 2 , pp. 147 - 160 .

Dishman , P.L. and Calof , J.L. ( 2008 ), “ Competitive intelligence: a multiphasic precedent to marketing strategy ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 766 - 785 .

Ebrahimi , B.P.B. ( 2000 ), “ Environmental complexity, importance, variability and scanning behavior of Hong Kong executives ”, Journal of Business Research , Vol. 49 No. 1 , pp. 67 - 77 .

Ekbia , H. , Mattioli , M. , Kouper , I. , Arave , G. , Ghazinejad , A. , Bowman , T. , Suri , V.R. , Tsou , A. , Weingart , S. and Sugimoto , C.R. ( 2015 ), “ Big data, bigger dilemmas: a critical review ”, Journal of the Association for Information Science and Technology , Vol. 66 No. 8 , pp. 1523 - 1545 , doi: 10.1002/asi .

El Sawy , O.A. ( 1985 ), “ Personal information systems for strategic scanning in turbulent environments: can the CEO go on-line? ”, MIS Quarterly , Vol. 9 No. 1 , pp. 53 - 60 .

Elbashir , M. , Collier , P. and Sutton , S. ( 2011 ), “ The role of organizational absorptive capacity in strategic use of business intelligence to support integrated management control systems ”, The Accounting Review , Vol. 86 No. 1 , pp. 155 - 184 .

Elenkov , D. ( 1997 ), “ Strategic uncertainty and environmental scanning: the case for institutional influences on scanning behavior ”, Strategic Management Journal , Vol. 18 No. 4 , pp. 287 - 302 .

Eom , S. and Kim , E. ( 2006 ), “ A survey of decision support system applications (1995-2001) ”, Journal of the Operational Research Society , Vol. 57 No. 11 , pp. 1264 - 1278 , doi: 10.1057/palgrave.jors.2602140 .

Fabbe-Costes , N. , Christine , R. , Margaret , T. and Taylor , A. ( 2014 ), “ Sustainable supply chains: a framework for environmental scanning practices ”, International Journal of Operations and Production Management , Vol. 34 No. 5 , pp. 664 - 694 .

Fink , L. , Yogev , N. and Even , A. ( 2016 ), “ Business intelligence and organizational learning: an empirical investigation of value creation processes ”, Information and Management , Vol. 54 No. 1 , pp. 38 - 56 , doi: 10.1016/j.im.2016.03.009 .

Fischer , T. , Dietz , J. and Antonakis , J. ( 2016 ), “ Leadership process models: a review and synthesis ”, Journal of Management , Vol. 43 No. 6 , pp. 1726 - 1753 , doi: 10.1177/0149206316682830 .

Fleisher , C.S. ( 2008 ), “ Using open source data in developing competitive and marketing intelligence ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 852 - 866 .

Fleisher , C.S. , Wright , S. and Allard , H.T. ( 2008 ), “ The role of insight teams in integrating diverse marketing information management techniques ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 836 - 851 .

Ghasemaghaei , M. and Calic , G. ( 2020 ), “ Assessing the impact of big data on firm innovation performance: big data is not always better data ”, Journal of Business Research , Vol. 108 , pp. 147 - 162 , doi: 10.1016/j.jbusres.2019.09.062 .

Ghosal , S. and Westney , D.E. ( 1991 ), “ Organizing competitor analysis systems ”, Strategic Management Journal , Vol. 12 , pp. 17 - 31 .

Ghoshal , S. and Kim , S.K.S.K. ( 1986 ), “ Building effective intelligence systems for competitive advantage ”, Sloan Management Review , Vol. 28 No. 1 , pp. 49 - 58 .

Gilad , B. , Gordon , G. , Sudit , E. , Gordon , G. and Sudit , E. ( 1993 ), “ Identifying gaps and blind spots in competitive intelligence ”, Long Range Planning , Vol. 26 No. 6 , pp. 107 - 113 , doi: 10.1016/0024-6301(93)90212-X .

Gioia , D. and Chittipeddi , K. ( 1991 ), “ Sense making and sense giving in strategic change initiation ”, Strategic Management Journal , Vol. 12 No. 6 , pp. 433 - 444 .

Gordon , L.A. and Loeb , M.P. ( 2001 ), “ Using information security as a response to competitor analaysis systems ”, Communications of the ACM , Vol. 44 No. 9 , pp. 70 - 75 .

Grover , V. , Chiang , R.H.L. , Liang , T.P. and Zhang , D. ( 2018 ), “ Creating strategic business value from big data analytics: a research framework ”, Journal of Management Information Systems , Vol. 35 No. 2 , pp. 388 - 423 , doi: 10.1080/07421222.2018.1451951 .

Gupta , M. and George , J.F. ( 2016 ), “ Toward the development of a big data analytics capability ”, Information and Management , Vol. 53 No. 8 , pp. 1049 - 1064 , doi: 10.1016/j.im.2016.07.004 .

Haeckel , S.H. ( 2004 ), “ Peripheral vision: Sensing and acting on weak signals making meaning out of apparent noise: the need for a new managerial framework ”, Long Range Planning , Vol. 37 No. 2 , pp. 181 - 189 .

Hallin , C.A. , Andersen , T.J. and Tveterås , S. ( 2017 ), “ Harnessing the frontline employee sensing of capabilities for decision support ”, Decision Support Systems , Vol. 97 , pp. 104 - 112 , doi: 10.1016/j.dss.2017.03.009 .

Hambrick , D.C. ( 1981 ), “ Environment, strategy, and power within top management teams ”, Administrative Science Quarterly , Vol. 26 No. 2 , pp. 253 - 276 .

Hart , C. ( 1998 ), Doing a Literature Review: Releasing the Social Science Research Imagination , Sage , London .

Heinrichs , J.H. and Lim , J. ( 2003 ), “ Integrating web-based data mining tools with business models for knowledge management ”, Decision Support Systems , Vol. 35 No. 1 , pp. 103 - 112 .

Hofer , C.W. ( 1978 ), Strategic Management: A Casebook in Policy and Planning , West Publishing , St. Paul, MN .

Holsapple , C. , Lee-Post , A. and Pakath , R. ( 2014 ), “ A unified foundation for business analytics ”, Decision Support Systems , Vol. 64 , pp. 130 - 141 .

Huber , G.P. and Daft , R.L. ( 1987 ), “ The information environment of organizations ”, Handbook of Organizational Communication: An Interdisciplinary Perspective , Sage Publi , Newbury Park, CA , pp. 130 - 164 .

Hughes , D. , Le Bon , J. and Rapp , A. ( 2013 ), “ Gaining and leveraging customer-based competitive intelligence: the pivotal role of social capital and salesperson adaptive selling skills ”, Journal of the Academy of Marketing Science , Vol. 41 No. 1 , pp. 91 - 110 .

Hutzschenreuter , T. and Kleindienst , I. ( 2006 ), “ Strategy-process research: what have we learned and what is still to be explored ”, Journal of Management , Vol. 32 No. 5 , pp. 673 - 720 , doi: 10.1177/0149206306291485 .

Jones , J.W. and McLeod , R.J. ( 1986 ), “ The structure of executive information systems: an exploratory analysis ”, Decision Sciences , Vol. 17 No. 2 , pp. 220 - 249 .

Jourdan , Z. , Rainer , R.K. and Marshall , T.E. ( 2008 ), “ Business intelligence: an analysis of the literature ”, Information Systems Management , Vol. 25 No. 2 , pp. 121 - 131 , doi: 10.1080/10580530801941512 .

Kohavi , R. , Rothleder , N. and Simoudis , E. ( 2002 ), “ Emerging trends in business analytics ”, Communications of the ACM , Vol. 45 No. 8 , pp. 45 - 48 .

Kowalczyk , M. and Buxmann , P. ( 2015 ), “ An ambidextrous perspective on business intelligence and analytics support in decision processes: insights from a multiple case study ”, Decision Support Systems , Vol. 80 , pp. 1 - 13 , doi: 10.1016/j.dss.2015.08.010 .

Kumar , V. , Saboo , A.R. , Agarwal , A. and Kumar , B. ( 2020 ), “ Generating competitive intelligence with limited information: a case of the multimedia industry ”, Production and Operations Management , Vol. 29 No. 1 , pp. 192 - 213 , doi: 10.1111/poms.13095 .

Lasserre , P. ( 1993 ), “ Gathering and interpreting strategic intelligence in Asia Pacific ”, Long Range Planning , Vol. 26 No. 3 , pp. 56 - 66 .

Lau , R.Y. , Liao , S.S.Y. , Wong , K. and Chiu , D.K.W. ( 2012 ), “ Web 2.0 environmental scanning and adaptive decision support for business mergers and acquisitions ”, MIS Quarterly , Vol. 36 No. 2 , pp. 1239 - 1268 .

Le Bon , J. and Merunka , D. ( 2006 ), “ The impact of individual and managerial factors on salespeople’s contribution to marketing intelligence activities ”, International Journal of Research in Marketing , Vol. 23 No. 4 , pp. 395 - 408 .

Leidner , D. and Elam , J. ( 1993 ), “ Executive information systems: their impact on executive decision making ”, Journal of Management Information Systems , Vol. 10 No. 3 , pp. 139 - 155 .

Leidner , D. and Elam , J. ( 1995 ), “ The impact of executive information systems on organizational design, intelligence, and decision making ”, Organization Science , Vol. 6 No. 6 , pp. 645 - 665 .

Leidner , D.E. , Carlsson , S. , Elam , J. and Corrales , M. ( 1999 ), “ Mexican and Swedish managers’ perceptions of the impact of EIS on organizational intelligence, decision making, and structure ”, Decision Sciences , Vol. 30 No. 3 , pp. 632 - 658 .

Lenz , R.T. and Engledow , J.L. ( 1986a ), “ Environmental analysis units and strategic decision-making: a field study of selected ’leading-edge’corporations ”, Strategic Management Journal , Vol. 7 No. 1 , pp. 69 - 89 .

Lenz , R.T. and Engledow , J.L. ( 1986b ), “ Environmental analysis: the applicability of current theory ”, Strategic Management Journal , Vol. 7 No. 4 , pp. 329 - 346 .

Levy , Y. and Ellis , T. ( 2006 ), “ A systems approach to conduct an effective literature review in support of information systems research ”, Informing Science Journal , Vol. 9 , pp. 181 - 212 , doi: 10.1109/IEEM.2012.6837801

Li , S.T.S. , Shue , L.L.Y.L. and Lee , S.F.S. ( 2008 ), “ Business intelligence approach to supporting strategy-making of ISP service management ”, Expert Systems with Applications , Vol. 35 No. 3 , pp. 739 - 754 .

Lin , C. and Kunnathur , A. ( 2019 ), “ Strategic orientations, developmental culture, and big data capability ”, Journal of Business Research , Vol. 105 , pp. 49 - 60 , doi: 10.1016/j.jbusres.2019.07.016 .

Lin , Y.-H. , Tsai , K.-M. , Shiang , W.-J. , Kuo , T.-C. and Tsai , C.-H. ( 2009 ), “ Research on using ANP to establish a performance assessment model for business intelligence systems ”, Expert Systems with Applications , Vol. 36 No. 2 , pp. 4135 - 4146 .

Liu , C.-H. and Wang , C. ( 2008 ), “ Forecast competitor service strategy with service taxonomy and CI data ”, European Journal of Marketing , Vol. 428 No. 7 , pp. 746 - 765 .

Lönnqvist , A. and Pirttimäki , V. ( 2006 ), “ Measurement of business intelligence: forthcoming in information systems management ”, Information Systems Management , Vol. 23 No. 1 .

Loock , M. and Hinnen , G. ( 2015 ), “ Heuristics in organizations: a review and a research agenda ”, Journal of Business Research , Vol. 68 No. 9 , pp. 2027 - 2036 , doi: 10.1016/j.jbusres.2015.02.016 .

McCrohan , K.F. ( 1998 ), “ Competitive intelligence: preparing for the information war ”, Long Range Planning , Vol. 31 No. 4 , pp. 586 - 593 .

Maltz , E. and Kohli , A.A.K. ( 1996 ), “ Market intelligence dissemination across functional boundaries ”, Journal of Marketing Research , Vol. 33 No. 1 , pp. 47 - 47 .

March , S. and Hevner , A. ( 2007 ), “ Integrated decision support systems: a data warehousing perspective ”, Decision Support Systems , Vol. 43 No. 3 , pp. 1031 - 1043 .

Mariadoss , B.J. , Milewicz , C. , Lee , S. and Sahaym , A. ( 2014 ), “ Salesperson competitive intelligence and performance: the role of product knowledge and sales force automation usage ”, Industrial Marketing Management , Vol. 43 No. 1 , pp. 136 - 145 .

May , R. , Stewart , W. and Sweo , R. ( 2000 ), “ Environmental scanning behavior in a transitional economy: evidence from Russia ”, Academy of Management Journal , Vol. 43 , pp. 403 - 427 .

Michaeli , R. and Simon , L. ( 2008 ), “ An illustration of Bayes’ theorem and its use as a decision-making aid for competitive intelligence and marketing analysts ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 804 - 813 .

Mikalef , P. , Boura , M. , Lekakos , G. and Krogstie , J. ( 2019 ), “ Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment ”, British Journal of Management , Vol. 30 No. 2 , pp. 272 - 298 , doi: 10.1111/1467-8551.12343 .

Miller , D. and Friesen , P. ( 1980 ), “ Momentum and revolution in organizational adaptation ”, Academy of Management Journal , Vol. 23 No. 4 , pp. 591 - 615 .

Mingers , J. and Willcocks , L. ( 2017 ), “ An integrative semiotic methodology for is research ”, Information and Organization , Vol. 27 No. 1 , pp. 17 - 36 , doi: 10.1016/j.infoandorg.2016.12.001 .

Mintzberg , H. ( 1973 ), The Nature of Managerial Work , Harper and Row , New York, NY .

Moorman , C. , Zaltman , G. and Deshpandé , R. ( 1992 ), “ Relationships between providers and users of market research: the dynamics of trust within and between organizations ”, Journal of Marketing Research , Vol. 29 No. 3 , pp. 314 - 329 .

Mora , M. , Forgionne , G. , Gupta , J. , Cervantes , F. and Gelman , O. ( 2005 ), “ A strategic research agenda ”, Journal of Decision Systems , Vol. 14 Nos 1/2 , pp. 179 - 196 , doi: 10.3166/jds.14.179-196 .

Moro , S.S. , Cortez , P. and Rita , P. ( 2015 ), “ Business intelligence in banking: a literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation ”, Expert Systems with Applications , Vol. 42 No. 3 , pp. 1314 - 1324 , doi: 10.1016/j.eswa.2014.09.024 .

Morris , H. , Harvey , C. and Kelly , A. ( 2009 ), “ Journal rankings and the ABS journal quality guide ”, Management Decision , Vol. 47 No. 9 , pp. 1441 - 1451 , doi: 10.1108/00251740910995648 .

Müller , S.D. and Jensen , P. ( 2017 ), “ Big data in the Danish industry: application and value creation ”, Business Process Management Journal , Vol. 23 No. 3 , pp. 645 - 670 , doi: 10.1108/BPMJ-01-2016-0017 .

Narver , J.C. and Slater , S.F. ( 1990 ), “ The effect of a market orientation on business profitability ”, Journal of Marketing , Vol. 54 No. 4 , pp. 20 - 34 .

O’Reilley , C. and Tushman , M. ( 2002 ), Winning through Innovation: A Practical Guide to Leading Organizational Change and Renewal , Harvard Business School Press , Cambridge, MA .

Opait , G. , Bleoju , G. , Nistor , R. and Capatina , A. ( 2016 ), “ The influences of competitive intelligence budgets on informational energy dynamics ”, Journal of Business Research , Vol. 69 No. 5 , pp. 1682 - 1689 , doi: 10.1016/j.jbusres.2015.10.038 .

Pawar , B.S. and Sharda , R. ( 1997 ), “ Obtaining business intelligence on the internet ”, Long Range Planning , Vol. 30 No. 1 , pp. 110 - 121 .

Peyrot , M. , Childs , N. , Van Doren , D. and Allen , K. ( 2002 ), “ An empirically based model of competitor intelligence use ”, Journal of Business Research , Vol. 55 No. 9 , pp. 747 - 758 .

Peyrot , M. , Van Doren , D. , Allen , K. and Childs , N. ( 1996 ), “ Competitor intelligence among industrial wholesalers: an exploratory study ”, Journal of Marketing Management , Vol. 6 , pp. 46 - 60 .

Pfeffer , J. and Salancik , G.R. ( 1978 ), The External Control of Organizations: A Resource Dependence Perspective , Harper and Row , New York, NY .

Popovič , A. , Hackney , R. , Coelho , P.S. and Jaklič , J. ( 2012 ), “ Towards business intelligence systems success: effects of maturity and culture on analytical decision making ”, Decision Support Systems , Vol. 54 No. 1 , pp. 729 - 739 .

Porac , J.F. and Thomas , H. ( 1990 ), “ Taxonomic mental models in competitor definition ”, Academy of Management Review , Vol. 15 No. 2 , pp. 224 - 240 .

Prescott , J. and Smith , D. ( 1987 ), “ A project‐based approach to competitive analysis ”, Strategic Management Journal , Vol. 8 No. 5 , pp. 411 - 423 .

Pryor , C. , Holmes , R.M. , Webb , J.W. and Liguori , E.W. ( 2019 ), “ Top executive goal orientations’ effects on environmental scanning and performance: differences between founders and nonfounders ”, Journal of Management , Vol. 45 No. 5 , pp. 1958 - 1986 , doi: 10.1177/0149206317737354 .

Qiu , T. ( 2008 ), “ Scanning for competitive intelligence: a managerial perspective ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 814 - 835 .

Rajagopalan , N. , Rasheed , A.M.A. and Datta , D.K. ( 1993 ), “ Strategic decision processes: critical review and future directions ”, Journal of Management , Vol. 19 No. 2 , pp. 349 - 384 , doi: 10.1177/014920639301900207 .

Ramakrishnan , T. , Jones , M.C. and Sidorova , A. ( 2012 ), “ Factors influencing business intelligence (BI) data collection strategies: an empirical investigation ”, Decision Support Systems , Vol. 52 No. 2 , pp. 486 - 496 .

Reinmoeller , P. and Ansari , S. ( 2016 ), “ The persistence of a stigmatized practice: a study of competitive intelligence ”, British Journal of Management , Vol. 27 No. 1 , pp. 116 - 142 , doi: 10.1111/1467-8551.12106 .

Robinson , C.V. and Simmons , J.E.L. ( 2017 ), “ Organising environmental scanning: exploring information source, mode and the impact of firm size ”, Long Range Planning , Vol. 51 No. 4 , doi: 10.1016/j.lrp.2017.10.004 .

Roden , S. , Nucciarelli , A. , Li , F. and Graham , G. ( 2017 ), “ Big data and the transformation of operations models: a framework and a new research agenda ”, Production Planning and Control , Vol. 28 Nos 11/12 , pp. 929 - 944 , doi: 10.1080/09537287.2017.1336792 .

Rouach , D. and Santi , P. ( 2001 ), “ Competitive intelligence adds value: five intelligence attitudes ”, European Management Journal , Vol. 19 No. 5 , pp. 552 - 559 , doi: 10.1016/S0263-2373(01)00069-X .

Sawyerr , O. ( 1993 ), “ Environmental uncertainty and environmental scanning activities of Nigerian manufacturing executives: a comparative analysis ”, Strategic Management Journal , Vol. 14 No. 4 , pp. 287 - 299 .

Seddon , P.B. , Constantinidis , D. , Tamm , T. and Dod , H. ( 2016 ), “ How does business analytics contribute to business value? ”, Information Systems Journal , Vol. 27 No. 3 , pp. 237 - 269 , doi: 10.1111/isj.12101 .

Sen , A. and Sinha , A.P. ( 2005 ), “ A comparison of data warehousing methodologies ”, Communications of the Acm , Vol. 48 No. 3 , pp. 79 - 84 .

Sharma , R. , Mithas , S. and Kankanhalli , A. ( 2014 ), “ Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations ”, European Journal of Information Systems , Vol. 23 No. 4 , pp. 433 - 441 .

Sheng , Y.P. , Mykytyn , P.P.J. and Litecky , C.R. ( 2005 ), “ Competitor analysis and its defenses in the e-marketplace ”, Communications of the ACM , Vol. 48 No. 8 , pp. 107 - 112 .

Shim , J.P. , Warkentin , M. , Courtney , J.F. , Power , D.J. , Sharda , R. and Carlsson , C. ( 2002 ), “ Past, present, and future of decision support technology ”, Decision Support Systems , Vol. 33 No. 2 , pp. 111 - 126 , doi: 10.1016/S0167-9236(01)00139-7 .

Shollo , A. and Galliers , R.D. ( 2015 ), “ Towards an understanding of the role of business intelligence systems in organisational knowing ”, Information Systems Journal , Vol. 26 No. 4 , pp. 339 - 367 , doi: 10.1111/isj.12071 .

Singh , S.K. , Watson , H. and Watson , R. ( 2002 ), “ EIS support for the strategic management process ”, Decision Support Systems , Vol. 33 No. 1 , pp. 71 - 85 .

Sivarajah , U. , Kamal , M.M. , Irani , Z. and Weerakkody , V. ( 2017 ), “ Critical analysis of big data challenges and analytical methods ”, Journal of Business Research , Vol. 70 , pp. 263 - 286 , doi: 10.1016/j.jbusres.2016.08.001 .

Slater , S. and Narver , J. ( 2000 ), “ Intelligence generation and superior customer value ”, Journal of the Academy of Marketing Science , Vol. 28 No. 1 , pp. 120 - 127 .

Srivastava , J. and Cooley , R. ( 2003 ), “ Web business intelligence: mining the web for actionable knowledge ”, INFORMS Journal on Computing , Vol. 15 No. 2 , pp. 191 - 207 .

Talaoui , Y. and Kohtamäki , M. ( 2020 ), “ Of BI research: a tale of two communities ”, Management Research Review , Vol. 43 No. 11 , pp. 1371 - 1394 .

Tanev , S. and Bailetti , T. ( 2008 ), “ Competitive intelligence information and innovation in small Canadian firms ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 786 - 803 .

Taylor , J.W. ( 1992 ), “ Competitive intelligence: a status report on US business practices ”, Journal of Marketing Management , Vol. 8 No. 2 , pp. 117 - 125 .

Thennakoon , D. , Bandara , W. , French , E. and Mathiesen , P. ( 2018 ), “ What do we know about business process management training? Current status of related research and a way forward ”, Business Process Management Journal , Vol. 24 No. 2 , pp. 478 - 500 , doi: 10.1108/BPMJ-09-2016-0180 .

Thomas , A. , Litschert , R. and Ramaswamy , K. ( 1991 ), “ The performance impact of strategy manager coalignment: an empirical examination ”, Strategic Management Journal , Vol. 12 No. 7 , pp. 509 - 522 .

Toit , A.S.A. ( 2015 ), “ Competitive intelligence research: an investigation of trends in the literature ”, Journal of Intelligence Studies in Business , Vol. 5 No. 2 , pp. 14 - 21 .

Trieu , V.H. ( 2017 ), “ Getting value from business intelligence systems: a review and research agenda ”, Decision Support Systems , Vol. 93 , pp. 111 - 124 , doi: 10.1016/j.dss.2016.09.019 .

Trim , R.J. and Lee , P.Y.I. ( 2008 ), “ A strategic marketing intelligence and multi-organisational resilience framework ”, European Journal of Marketing , Vol. 42 Nos 7/8 , pp. 731 - 745 .

Turban , E. and Schaeffer , D. ( 1987 ), “ A comparative study of executive information systems ”, DSS 87 Transactions , pp. 139 - 148 .

Turban , E. , King , D. , and Lang , J. ( 2010 ), Introduction to Electronic Commerce , Prentice Hall , New York, NY .

Urbinati , A. , Bogers , M. , Chiesa , V. and Frattini , F. ( 2019 ), “ Creating and capturing value from big data: a multiple-case study analysis of provider companies ”, Technovation , Vol. 84-85 , pp. 21 - 36 , doi: 10.1016/j.technovation.2018.07.004 .

Vaara , E. and Lamberg , J.A. ( 2014 ), “ Academy of management review ”, Taking Historical Embeddedness Seriously: Three Historical Approaches to Advance Strategy Process and Practice Research EERO .

Van De Ven , A.H. ( 1992 ), “ Suggestions for studying strategy process: a research note Andrew ”, Strategic Management Journal , Vol. 13 , pp. 169 - 188 , doi: 10.1080/02566702.1990.9648237 .

Vedder , R.G. , Vanecek , M.T. , Guynes , S.C. and Cappel , J.J. ( 1999 ), “ CEO and CIO perspectives on competitive intelligence ”, Communications of the ACM , Vol. 42 No. 8 , pp. 108 - 116 .

Viaene , S. , Bunder , A. and Van den , ( 2011 ), “ The secrets to managing business analytics projects ”, MIT Sloan Management Review , Vol. 53 No. 1 , pp. 65 - 69 .

Vidgen , R. , Shaw , S. and Grant , D.B. ( 2017 ), “ Management challenges in creating value from business analytics ”, European Journal of Operational Research , Vol. 261 No. 2 , pp. 626 - 639 .

Vogel , R. ( 2012 ), “ The visible colleges of management and organization studies: a bibliometric analysis of academic journals ”, Organization Studies , Vol. 33 No. 8 , pp. 1015 - 1043 .

Walters , B.A. , Jiang , J.J. and Klein , G. ( 2003 ), “ Strategic information and strategic decision making: the EIS/CEO interface in smaller manufacturing companies ”, Information and Management , Vol. 40 No. 6 , pp. 487 - 495 .

Wamba , S.F. , Gunasekaran , A. , Akter , S. , Fan Ren , S.J. , Dubey , R. and Childe , S.J. ( 2017 ), “ Big data analytics and firm performance: effects of dynamic capabilities ”, Journal of Business Research , Vol. 70 , pp. 356 - 365 , doi: 10.1016/j.jbusres.2016.08.009 .

Wang , C.H. , Cheng , H.Y. and Deng , Y.T. ( 2018b ), “ Using Bayesian belief network and time-series model to conduct prescriptive and predictive analytics for computer industries ”, Computers and Industrial Engineering , Vol. 115 , pp. 486 - 494 .

Wang , Y. , Kung , L.A. , Wang , W.Y.C. and Cegielski , C.G. ( 2018a ), “ An integrated big data analytics-enabled transformation model: application to health care ”, Information and Management , Vol. 55 No. 1 , pp. 64 - 79 , doi: 10.1016/j.im.2017.04.001 .

Watson , H.J. ( 2009 ), “ Tutorial: business intelligence – past, present, and future ”, Communications of the Association for Information Systems , Vol. 25 , pp. 487 - 510 , available at: http://aisel.aisnet.org/cais/vol25/iss1/39/

Watson , H.J. and Wixom , B. ( 2007 ), “ The current state of business intelligence in academia ”, Computer , Vol. 40 No. 9 , pp. 299 - 312 , doi: 10.1109/MC.2007.331 .

Webster , J. and Watson , R.T. ( 2002 ), “ Analyzing the past to prepare for the future: writing a literature review ”, MIS Quarterly , Vol. 26 No. 2 , pp. 13 - 23 .

Wei , C. and Lee , Y. ( 2004 ), “ Event detection from online news documents for supporting environmental scanning ”, Decision Support Systems , Vol. 36 No. 4 , pp. 385 - 401 .

Wright , S. , Eid , E. and Fleisher , C. ( 2009 ), “ Competitive intelligence in practice: empirical evidence from the UK retail banking sector ”, Journal of Marketing Management , Vol. 25 Nos 9/10 , pp. 941 - 964 .

Xu , K. , Liao , S.S. , Li , J. and Song , Y. ( 2011 ), “ Mining comparative opinions from customer reviews for competitive intelligence ”, Decision Support Systems , Vol. 50 No. 4 , pp. 743 - 754 .

Yasai-Ardekani , M. and Nystrom , P. ( 1996 ), “ Designs for environmental scanning systems: tests of a contingency theory ”, Management Science , Vol. 42 No. 2 , pp. 187 - 207 .

Zajac , E.J. and Bazerman , M.H. ( 1991 ), “ Blind spots in industry and competitor analysis: implications of interfirm (mis)perceptions for strategic decisions ”, Academy of Management Review , Vol. 16 No. 1 , doi: 10.5465/AMR.1991.4278990 .

Zeithaml , V.A. ( 1988 ), “ Consumer perception of price, quality, and value: a means–end model and synthesis of evidence ”, Journal of Marketing , Vol. 52 No. 3 , pp. 2 - 22 .

Zheng , Z.E. , Fader , P. and Padmanabhan , B. ( 2012 ), “ From business intelligence to competitive intelligence: inferring competitive measures using augmented site- centric data ”, Information Systems Research Publication , Vol. 23 , pp. 698 - 720 .

Zhu , K. and Kraemer , K.L. ( 2005 ), “ Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry ”, Information Systems Research , Vol. 16 No. 1 , pp. 61 - 84 .

Corresponding author

About the authors.

Yassine Talaoui is a researcher at the School of Management at the University of Vasa, where he teaches business models and strategic management theories. His research interests focus on delineating relationships between materiality, digitization and management and organization studies. He is the recipient of the 2018 SAP Interest Group Division Pushing The Boundary Award at the Academy of Management.

Marko Kohtamäki (PhD) is a Professor of Strategy at the University of Vaasa, and a visiting professor at the University of South-Eastern Norway, USN Business School and Luleå University of Technology. Kohtamäki takes special interest in strategic practices, strategic agility and business intelligence. Kohtamäki has published in distinguished international journals such as Strategic Management Journal, International Journal of Operations and Production Management, Industrial Marketing Management, Long Range Planning, Strategic Entrepreneurship Journal, International Journal of Production Economics, Technovation, Journal of Business Research , amongst others.

Related articles

We’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • Elsevier - PMC COVID-19 Collection

Logo of pheelsevier

Effects of COVID-19 on business and research

The COVID-19 outbreak is a sharp reminder that pandemics, like other rarely occurring catastrophes, have happened in the past and will continue to happen in the future. Even if we cannot prevent dangerous viruses from emerging, we should prepare to dampen their effects on society. The current outbreak has had severe economic consequences across the globe, and it does not look like any country will be unaffected. This not only has consequences for the economy; all of society is affected, which has led to dramatic changes in how businesses act and consumers behave. This special issue is a global effort to address some of the pandemic-related issues affecting society. In total, there are 13 papers that cover different industry sectors (e.g., tourism, retail, higher education), changes in consumer behavior and businesses, ethical issues, and aspects related to employees and leadership.

1. Introduction

There has been a long history of fear of pandemic outbreaks. The discussion has not focused on whether there will be an outbreak, but when new outbreaks will happen ( Stöhr & Esveld, 2004 ). The events leading to influenza pandemics are recurring biological phenomena and cannot realistically be prevented. Pandemics seem to occur at 10–50-year intervals as a result of the emergence of new virus subtypes from virus re-assortment ( Potter, 2001 ). As the global population increases and we need to live closer to animals, it is likely that the transfer of new viruses to the human population will occur even more frequently. All our society can do is take preventive measures so that we are able to act quickly once we suspect an outbreak. We should also make an effort to learn from the consequences of pandemic outbreaks to prepare our societies for if—and, more likely, when—this happens again.

As we are in the middle of a pandemic outbreak, it is very difficult to estimate its long-term effects. Although society has been hit by several pandemics in the past, it is difficult to estimate the long-term economic, behavioral, or societal consequences as these aspects have not been studied to a great extent in the past. The limited studies that do exist indicate that the major historical pandemics of the last millennium have typically been associated with subsequent low returns on assets ( Jorda, Singh, & Taylor, 2020 ). For a period after a pandemic, we tend to become less interested in investing and more interested in saving our capital, resulting in reduced economic growth. Given the current situation, in which saving capital means negative returns, it is not at all certain that we will be as conservative as we have been in the past. Behavioral changes related to pandemic outbreaks seem to be connected with personal protection ( Funk, Gilad, Watkins, & Jansen, 2009 ), such as the use of face masks, rather than general behavior changes. Our lives, as humans in a modern society, seem to be more centered around convenience than around worrying about what might happen in the future.

On a societal level, we seem to be completely unprepared for large-scale of outbreaks. Our societies are more open than ever; we rely on the importing of important products, such as food, energy, and medical equipment, rather than sourcing them from close to where they are needed; and there are limited efforts to prepare for pandemic outbreaks. The guiding principle of our society seems to be efficiency and economic gain rather than safety. This may change after the current outbreak. It is also important to point out that the principles (eg. openness and global trade) on which society is based have lifted a large number of countries around the globe out of poverty and produced well-developed economies. It is not unlikely that our societies will back-off some of them leading to more poverty in the world.

The COVID-19 pandemic outbreak has forced many businesses to close, leading to an unprecedented disruption of commerce in most industry sectors. Retailers and brands face many short-term challenges, such as those related to health and safety, the supply chain, the workforce, cash flow, consumer demand, sales, and marketing. However, successfully navigating these challenges will not guarantee a promising future, or any future at all. This is because once we get through this pandemic, we will emerge in a very different world compared to the one before the outbreak. Many markets, especially in the fields of tourism and hospitality, no longer exist. All organizational functions are intended to prioritize and optimize spending or postpone tasks that will not bring value in the current environment. Companies, especially start-ups, have implemented an indefinite hiring freeze. At the same time, online communication, online entertainment, and online shopping are seeing unprecedented growth.

2. Interesting research themes

As research indicates that pandemics are reoccurring events, it is very likely that we will see another outbreak in our lifetime. It is apparent to anyone that the current pandemic has had enormous—but hopefully short-term—effects on all our lives. Countries have closed their borders, limited the movement of their citizens, and even confined citizens in quarantine within their homes for weeks. This is a rather unique occurrence, as we are used to freedom of movement, but in the midst of the pandemic outbreak, people have been fined just for being outside. Although our societies seem to be very accepting of these limitations and condemn people that do not follow the rules, but we need to ask ourselves how this will affect the views of our society (e.g., views regarding freedom, healthcare, government intervention). We should also be aware that infrastructure and routines to monitor citizens in order to limit the spread of the virus have been rolled out, and so we should ask ourselves how accepting we will be of monitoring in the future. We must realize that once these systems are in place, it is highly unlikely that they will be rolled back. Furthermore, in some countries, the ruling politicians have taken advantage of this situation and increased their control over the state, suppressing opposing opinions and thus jeopardizing democratic systems. Some of the worst examples are Turkmenistan, which has banned the use of the word “corona,” and Hungary, which is letting Viktor Orbán rule by decree indefinitely.

As previously mentioned, people have been confined to their homes. There has also been a constant stream of news on this invisible external threat from which we cannot protect ourselves. We have been occupied trying to figure out how best to protect ourselves and our loved ones. On top of that, many feel pressure due to losing their jobs or due to working in close proximity to potentially infected people, as society depends on them fulfilling their duty. The consequences of the pandemic outbreak have hit various sectors of society in different ways. People that are working in sectors connected to healthcare must endure endless tasks and very long working days. Additionally, people are losing their jobs at rates we have not seen since the Great Depression of the 1930s. The sectors that have seen the largest increases in unemployment are those that are hedonic in nature and require the physical presence of the customer (e.g., hospitality, tourism, and entertainment), as demand for these services has ceased to exist. The employees in these sectors tend to be younger and female. Past experience also indicates that once someone is outside the job market, it is very difficult to get back in as they will face more competition that may be more competent.

All countries that can are trying to stimulate their economies to keep as much as possible of their necessary infrastructure intact and to keep citizens productive or ready to become productive once the pandemic has been overcome. In order to keep society from deteriorating, people not only need jobs or a way to support themselves but also need access to what they view as necessary products and services. If this infrastructure does not exist, people start to behave in what is considered uncivil behavior (e.g., hording or looting). Countries around the globe have adopted very different approaches to handle the current stress on the job markets and infrastructure. Some countries have chosen to support businesses in order to help them keep the workforce intact, but others with less financial strength cannot do the same. Countries also have directly supported their citizens in various ways. There is an enormous body of rich information that researchers can collect to determine the best approaches for when when and if a major disaster happens in the future.

3. Consumer behavior during COVID-19

Around the globe, societies are in lockdown, and citizens are asked to respect social distance and stay at home. As we are social beings, isolation may be harmful for us ( Cacioppo & Hawkley, 2009 ). Feelings of loneliness have, among other things, been connected to poorer cognitive performance, negativity, depression, and sensitivity to social threats. There are indications that this is happening during the current pandemic, as there has been an increase in domestic violence, quarrels among neighbors, and an increase in the sales of firearms ( Campbell, 2020 ). However, we have also seen an increase in other, more positive types of behavior caused by social distancing that have not been researched. People have started to nest, develop new skills, and take better care of where they live. For instance, they may learn how to bake, try to get fit, do a puzzle, or read more. There has also been an increase in purchases of cleaning products, and more trash is being recycled. At the same time, we are eating more junk food and cleaning ourselves less. People are also stockpiling essentials, panic buying, and escaping to rural areas. This is an indication that what is happening to us and our behaviors is complex, and it would be interesting to study this phenomenon further.

Another consequence of the lockdowns is the extreme increase in the usage of Internet and social media. Previous research has indicated that humans who feel lonely tend to use social media more and, in some cases, even prefer social media over physical interaction ( Nowland, Necka, & Cacioppo, 2018 ). Social media also may bring out the worst in us through trolling or sharing of fake news. This is, to some degree, not as damaging as the “real life” is lived in the physical world and the Internet is an “add on” with, in most cases, limited impact on the physical world. By this, we are able to compartmentalize and distinguish what matters and what does not matter. However, the current situation has made social media the main mode of contacting or socializing with others. In many cases, the Internet is at present also the main way to get essential supplies and receive essential services, like seeing a doctor. The question, then, is what happens to us when the “real life” is lived online and becomes a way to escape the physical world?

As humans, we rely to a large degree on our senses; we are built to use them in all situations of life. Thus, we rely on them heavily when making decisions. However, the current isolation is depriving us of our senses, as we are not exposed to as many stimuli as normal situation. Thus, we are, in a sense, being deprived of stimulation. We are also being told by authorities not to use our senses; we should not touch anything, wear a mask, or get close to other humans. Thus, what happens once our societies open up? How long will this fear of using our senses linger, and will we be over-cautious for a while or may we try to compensate as we have to some degree been deprived of using them? These are just some aspects of consumer behavior; many more are covered by this special issue.

4. Markets during COVID-19

The COVID-19 outbreak is likely to cause bankruptcy for many well-known brands in many industries as consumers stay at home and economies are shut down ( Tucker, 2020 ). In the US, famous companies such as Sears, JCPenney, Neiman Marcus, Hertz, and J. Crew are under enormous financial pressure. The travel industry is deeply affected; 80% of hotel rooms are empty ( Asmelash & Cooper, 2020 ), airlines cut their workforce by 90%, and tourism destinations are likely to see no profits in 2020. Furthermore, expos, conferences, sporting events, and other large gatherings as well as cultural establishments such as galleries and museums have been abruptly called off. Consulting in general and personal services, like hairdressers, gyms, and taxis, have also come to a standstill due to lockdowns. Finally, important industries like the car, truck, and electronics industries have abruptly closed (although they started to open up two months after their closure). There are an endless number of questions we could ask ourselves in connection to this rather abrupt close-down. For instance, how do we take care of employees in such situations? Why are companies not better prepared to handle such situations (e.g., putting aside earnings or thinking of alternative sources of income)? How are the companies and even countries using the current situation to enhance their competitive situation? One of the countries that seem to be using the situation is China that is buying European based infrastructure and technology ( Rapoza, 2020 ).

While some businesses are struggling, some businesses are thriving. This is true for a number of Internet-based businesses, such as those related to online entertainment, food delivery, online shopping, online education, and solutions for remote work. People have also changed their consumption patterns, increasing the demand for takeout, snacks, and alcohol as well as cleaning products as we spend more time in our homes. Other industries that are doing well are those related to healthcare and medication as well as herbs and vitamins. Typically, when studying markets, it is assumed that they are static, a natural conclusion since they tend to change slowly. However, if there is one thing the COVID-19 outbreak has shown us, it is that markets are dynamic ( Jaworski, Kohli, & Sahay, 2000 ) and can move rapidly. Furthermore, a market is not just a firm; it is a network of actors (i.e., firms, customers, public organizations) acting in accordance with a set of norms. These systems are sometimes referred to as dynamic ecosystems that exist to generate value ( Vargo & Lusch, 2011 ). The COVID-19 outbreak poses a unique opportunity to study how markets are created and how they disappear within a very limited time span. It would also be interesting to explore whether the disappearance of one solution for a market may be replaced by another (e.g., combustion engines for electric or physical teaching for online teaching).

5. Predicted lasting effects

Based on past experiences, we have become more conservative and protective after a pandemic outbreak. We save resources in order to be prepared if the unthinkable happens again. Countries are starting to stockpile things like food, equipment, and medicine or prepare to produce them locally. It is also essential for larger global firms to have reliable supply chains that do not break. Consequently, it is very likely that this pandemic will make these firms rethink their supply chains and, probably, move supply chains closer to where they are needed in order to avoid stopping production in the future. Furthermore, authorities have implied that other humans from other countries are dangerous as they may carry the virus. A closed border implies that the threat is from the outside. In addition, international flights are not likely to be an option for many in the coming years. Together, these circumstances mean that countries may become more nationalistic and less globalized. This may be a dangerous development, as long-term protection from the consequences of a pandemic outbreak is likely to require global effort and sharing of resources. Such cooperation is also key to tackle other global challenges that we may face in the future.

6. This special issue

In this special issue, we have invited scholars from different areas of business and management to write brief papers on various aspects of the effects of the COVID-19 pandemic. In total, there are 12 articles in the special issue, which are summarized below.

The first contribution, by Jagdish Sheth, is titled “Impact of COVID-19 on Consumer Behavior: Will the Old Habits Return or Die?” It explores how the current pandemic has affected several aspects of consumers’ lives, ranging from personal mobility to retail shopping, attendance at major life events like marriage ceremonies, having children, and relocation. The author investigates four contexts of construed consumer behavior, namely social context, technology, coworking spaces, and natural disasters. Additionally, the author foresees eight immediate effects of the pandemic on consumer behavior and consumption. Hoarding—the mad scramble observed at the start of the COVID-19 outbreak—applies not only to consumers but also to unauthorized middlemen who buy products in excess to sell at increased prices.

Consumers learn to adapt quickly and take an improvised approach to overcome constraints that have been imposed by governments. Pent-up demand may lead to a significant rebound in sales of durable products, like automobiles, houses, and large appliances, and some of the realities of COVID-19 will put consumers in a buying mood soon.

Embracement of digital technology, either through online services or information-sharing platforms like Zoom, has kept people connected around the world. Digital savviness will become a necessity, rather than an alternative, for schools, businesses, and healthcare providers. With the onset of lockdowns in many countries, online shopping, including grocery shopping, has become more prevalent.

The desire to do everything in-home has impacted consumers’ impulse buying habits. Slowly but surely, work–life boundaries will be blurred when both tasks are carried out from home. There should be efforts to compartmentalize the two tasks to make this a more efficient way of life.

Reunions with friends and family are now restricted to digital interactions, especially for people who work and live away from their families. We can expect a dramatic change in consumers’ behavior because of sophisticated technology. In addition, consumers may discover new talents as they spend less time on the road and more at home. They may experiment with cooking, learn new skills, and, soon, become producers with commercial possibilities. In the end, most consumer’s habits will return to normal, while some habits may die due to adaptation to the new norm.

The second contribution, “Interventions as Experiments: Connecting the Dots in Forecasting and Overcoming Pandemics, Global Warming, Corruption, Civil Rights Violations, Misogyny, Income Inequality, and Guns,” written by Arch G. Woodside, discusses whether there is an association between public health interventions, national and state/provincial governments interventions, and improved control of the COVID-19 outbreak in certain countries. The paper suggests “ultimate broadening of the concept of marketing” in order to design and implement interventions in public laws and policy, national and local regulations, and the everyday lives of individuals. It also lays out effective mitigating strategies by examining designs, implementations, and outcomes of COVID-19 interventions by examining deaths as a natural experiment.

While COVID-19 eradication intervention tests are being run for promising vaccines, these are considered true experiments, and analyzing the data from these interventions may involve examination of the success of each vaccine for different demographic subgroups in treatment and placebo groups in randomized control trials. Comparing the designs and impact of the current COVID-19 mitigation interventions across nations and states within the U.S. provides useful information for improving these interventions, even though they are not “true experiments.”

The third contribution, “Employee Adjustment and Well-Being in the Era of COVID-19: Implications for Human Resource Management” is written by Joel B. Carnevale and Isabella Hatak. They claim that COVID-19 is becoming the accelerator for one of the most drastic workplace transformations in recent years. How we work, socialize, shop, learn, communicate, and, of course, where we work will be changed forever. Person–environment (P-E) fit theories highlight that employee–environment value congruence is important because values influence outcomes through motivation. However, given the current environment, in which the fulfillment of needs and desires like greater satisfaction, higher engagement, and overall well-being is drastically altered, there is an increased likelihood of misfits working in organizations.

In response to this, organizations need to use virtual forms of recruitment, training, and socialization in lieu of face-to-face interactions. Increasing job autonomy will alleviate the family-related challenges that may arise within remote work environments by providing employees with the right resources to manage conflicting work and family demands. Human resource leaders within the organization must enhance relationship-oriented human resources systems in order to combat the risk of unforeseen and prolonged isolation among single, independent employees and to better prepare them for situations like the current crisis. The field of entrepreneurship can offer insights that can be adapted by organizations coping with the pandemic. Entrepreneurs’ struggles are largely caused by the lack of work-related social support in comparison to salaried employees. Nevertheless, some entrepreneurs are known to overcome these limitations by leveraging alternative, domain-specific sources of social support, such as positive feedback from customers, which ultimately enhances their well-being. Recycling such approaches to identify overlooked or untapped sources of social support is likely to be beneficial for employees given the current work environment dynamic.

The fourth contribution, written by Hongwei He and Lloyd C. Harris, is titled “The Impact of Covid-19 Pandemic on Corporate Social Responsibility and Marketing Philosophy.” The worldwide demand for hand sanitizers, gloves, and other hygiene products has risen because of the COVID-19 pandemic. And, in some countries, there has been a surge in complaints about profiteering and opportunism. As doctors combat the virus, prosecutors are pursuing the opportunistic profiteers who prey on the fearful. Many large corporations have a social purpose and set of values that indicate how much they appreciate their customers, employees, and stakeholders. This is the time for these corporations to make good on that commitment. Some organizations strive to set great examples. For example, Jack Ma, the co-founder of Alibaba, donated coronavirus test kits and other medical supplies to many countries around the world through the Jack Ma Foundation and Alibaba Foundation. Large corporations have often written off the costs of product failures, restructuring, or acquisitions. When writing off losses due to the coronavirus pandemic, it is understandable to pursue the bond established between the brand and consumer. This gesture can turn out to be more meaningful and lasting than when implemented during “normal” times.

On the bright side, the COVID-19 pandemic offers great opportunities for companies to actively engage with their corporate social responsibility (CSR) strategies and agenda. The post-COVID-19 marketplace is going to be irrecoverably different. Organizations will need to re-evaluate their visions, missions, and objectives to account for changes to their customers and competitors, amongst other shifts. A key facet of this is the exponential increase in digital communications and change.

Professors T. Y. Leung, Piyush Sharma, Pattarin Adithipyangkul, and Peter Hosie wrote “Gender Diversity and Public Health Outcomes: The COVID-19 Experience.” Public health is an interdisciplinary subject that involves the social sciences, public policy, public education, economics, and management. Failure to implement a proper public health policy may not only lead to a huge loss of human lives but also shatter the economy; expose the incompetence of public bodies, including governments and political leaders; and weaken the confidence of the general public. We are used to hearing that women are more other-directed and emotionally intelligent, but it has been proven that women are just as good, if not better, in terms of what we think of as male qualities, like being decisive and making tough calls, during a crisis. Prevalent issues like under-representation of women in leadership positions, mismanagement of public health systems, and inaccurate or inconsistent reporting of public health outcomes in the context of the recent pandemic need to be addressed by involving women at all stages of public health management, including planning, decision-making, and emergency response systems. This is important not only for a quick economic recovery in the aftermath of the COVID-19 crisis but also to prevent and manage such disasters in future.

The sixth paper in the special issue, “Managing Uncertainty during a Global Pandemic: An International Business Perspective,” was written by Piyush Sharma, T. Y. Leung, Russel P. J. Kingshott, Nebojsa S. Davcik, and Silvio Cardinali. Pandemics like that caused by COVID-19 are not just passing tragedies of sickness and death. The ubiquity of such a threat, and the uncertainty and fear that accompany it, lead to new consumer trends and norms. People become both more suspicious and less susceptible. The crisis also shines a light on the importance of international business research, which has been overlooked in the years leading up to this crisis. Social and informational uncertainty are likely to have economic repercussions.

As pointed out by the author, successful outcomes of social distancing and other restrictions are highly dependent upon societal acceptance and following through with restrictions. Social uncertainty and unrest among consumers due to being under lockdown for months could lead to a huge stifled demand for the products they missed. In this context, Samsung, a South Korean giant in consumer electronics and home appliances, may be a great case study during the ongoing COVID-19 crisis. Samsung established a huge manufacturing network over the years, with factories in multiple locations. This was done due to foresight of the risk of single sourcing, the need to fulfill large production demand, and the desire to reduce its dependence on China. This strategy has helped Samsung shift its production from one location to another during the ongoing COVID-19 crisis, thereby facing just a slowdown and not a complete shutdown of production. Similarly, to compensate for the closure of retail stores, Samsung has leveraged its contracts with mobile phone retailers and Benow (a payment and EMI technology firm) to create an e-commerce platform so that its retail business can continue to sell and deliver products directly to customers.

The seventh contribution, “Competing During a Pandemic? Retailers Ups and Downs During the COVID-19 Outbreak,” was written by Eleonora Pantano, Gabriele Pizzi, Daniele Scarpi, and Charles Dennis. The authors note that retailers who were not quick to adapt and factor COVID-19 into their operations are currently facing an existential crisis. The authors also highlight that retailers can minimize current and future business impacts by addressing four major emergencies.

First, retailers can identify and execute controllable activities. They must identify, optimize, and re-access existing technologies and business models. Specifically, they must understand how their stakeholders operate and interact to reduce response time and optimize communication channels. Second, all retailers, but especially grocery stores, are revisiting their business continuity plans to reassure customers that their needs will be met and manage the inevitable supply chain constraints and highs and lows caused by volatile demand. These retailers are prioritizing critical business activities and creating contingency plans for disruption. Third, retailers need to have an understanding of their financial needs as well as the essential role they play in their communities. For some regular customers, an open and well-stocked supermarket will reassure them that they are being cared for. Fourth, messages that retailers spread online during emergencies need to include information about products’ availability on the shelves and at digital outlets; control panic buying by restricting the quantity that customers can purchase; devise and implement protection plans for consumers and employees; contribute to overall public health; and use surveillance measures to limit the spread of the virus. To these ends, retailers need to improve their customer relationship management systems and promote safe interactions with customers (e.g., through online chats with employees) to provide real-time customer assistance.

In Fabian Eggers’ contribution, “Masters of Disasters? Challenges and Opportunities for SMEs in Times of Crisis,” he identifies small- to medium-sized businesses with low or unstable cashflow as particularly vulnerable during crises, as they are currently struggling for profitability. Studies reveal the interconnectedness between finance and strategy, particularly entrepreneurial orientation and market orientation in strategies. The paper highlights that a combination of entrepreneurial orientation and market orientation can lead to lean and flexible marketing efforts, which are particularly valuable in times of crisis. In addition, entrepreneurial orientation and market orientation can be combined into an entrepreneurial marketing post-disaster business recovery framework that highlights that seeking opportunities, organizing resources, creating customer value, and accepting risk are markedly different in a post-disaster context.

Sandeep Krishnamurthy contributed with “The Future of Business Education: A Commentary in the Shadow of the Covid-19 Pandemic.” The paper highlights that social distancing is prompting educational institutions to rethink how they are connecting with their student bodies. Spatial interaction is becoming the new norm, and the blurring of physical and virtual communication is likely to continue until the pandemic is overcome. Globally, the higher education system will undergo a decade of radical technology-led transformation, according to the author. The author identified five trends that will revolutionize how we educate after COVID-19:

  • 1. The Algorithm as Professor – Rather than taking a traditional route and learning from a human professor in classrooms, students will learn remotely from an algorithm. The AI-enabled algorithm will provide customized personal learning experiences. Students will be able to quickly master rudimentary and routinized tasks. Then, the algorithm will prepare them for an in-person experience, where a “warm body” will engage them in Socratic dialogue.
  • 2. The University as a Service – Traditionally, we have followed a linear formulation of society. Students go through K-12 education, some get an undergraduate degree, and some go on to further studies. However, the current and future environment is too volatile to sustain this educational structure. Students will need to learn what they need when they need it. Personalized, continuing education will become the norm.
  • 3. The University as Assessment Powerhouse – In a world characterized by AI and automation, learning can come from many sources. Students will learn from each other, algorithmic systems, and public information. However, universities will continue to have a powerful place as assessors of learning. Students will come to universities to gain objective credentials based on powerful assessments of learning.
  • 4. Learning Personalization to Support Diversity – Students of the future will have access to multiple pathways to learn the same content. For example, a course may be available through algorithmic engagement, animation/video/augmented reality, face-to-face instruction, or any mixture thereof. Using assessment data, the university of the future will be able to pinpoint the learning needs of each student and provide a personalized experience.
  • 5. Problem Solving Through Ethical Inquiry - As the influence of artificial intelligence and automation grow exponentially in our lives, there will be a great need for students to become problem solvers through ethical inquiry. Clearly, the future will not simply be about what the answers are; it will be about which problems we wish to solve, given what we know. Students will need to become more comfortable with the need to evaluate AI algorithms based on their efficacy and their ethical foundation.

Contribution number ten, “Consumer Reacting, Coping and Adapting Behaviors in the COVID-19 Pandemic,” is written by Colleen P. Kirk and Laura S. Rifkin. In it, the authors explore numerous consumer insights during a major pandemic outbreak. Mainly, they examine consumer behaviors across three phases: reacting (e.g., hoarding and rejecting), coping (e.g., maintaining social connectedness, do-it-yourself behaviors, and changing views of brands), and longer-term adapting (e.g., potentially transformative changes in consumption and individual and social identity). The authors also identify a number of negative aspects of the pandemic that will likely impact consumer behavior. As they state, given the mandatory close quarters people must keep due to stay-at-home requirements, domestic abuse may be on the rise. In addition, throughout history, pandemics provide an excuse for increased racial and anti-immigrant biases.

In “How Firms in China Innovate in COVID-19 Crisis? An Exploratory Study of Marketing Innovation Strategies,” written by Yonggui Wang, Aoran Hong, Xia Li, and Jia Gao, the authors explore how firms in China worked to make their marketing strategies a success. They do so by identifying the typology of firms’ marketing innovations based on two dimensions: the motivation for innovations and the level of collaboration in innovations.

The authors outline four innovative strategies to combat crises for businesses. The responsive strategy works predominantly for firms that involve physical contact, but it can easily be transferred from offline marketing channels to online channels. A collective strategy can be implemented by firms that are highly affected by the crisis, which need to develop new business by collaborating with other firms during the crisis. A proactive strategy is for firms that are less affected by the COVID-19 crisis (mostly online businesses) to develop new businesses to meet the special demands of existing customers during the COVID-19 crisis. Firms that are less affected during the COVID-19 crisis can take an alternative approach: a partnership strategy. Firms should usually develop new offerings through collaboration with other firms.

Professors Amalesh Sharma, Anirban Adhikary, and Sourav Bikash Borah contributed with “Covid-19 Impact on Supply Chain Decisions: Strategic Insights for NASDAQ 100 Firms using Twitter Data.” During black swan events like the COVID-19 pandemic, which may have severe long-term consequences, a deep understanding of business risks can help organizations establish the right plan. In this article, the authors identified supply chain challenges faced by companies using their Twitter data. To develop insights from the findings, the authors constructed unigrams, bigrams, and trigrams that revealed the supply-chain-related aspects that gain attention on Twitter.

A topic analysis was performed to identify keywords used in discussions about COVID-19. The obtained insights show that the greatest challenge for the organizations was accessing realistic customer demands. A pandemic may increase or decrease demand for specific products, making estimation of realistic final customer demand more difficult and more urgent to address. Some user accounts suggested that organizations are still lacking in terms of technological readiness and that companies are looking to gain visibility across value chains. There are growing discussions about building supply chain resilience by identifying risks. Many organizations are not only focusing on social sustainability but also turning their attention toward environmental sustainability. To deal with the challenges brought on by unprecedented times, the leaders of organizations must reimagine and redesign the supply chain; rely on technology such as artificial intelligence, the Internet of Things, and blockchain in their supply chain designs; and focus on sustainable supply chain.

Finally, Marianna Sigala wrote “Tourism and COVID-19: Impacts and Implications for Advancing and Resetting Industry and Research.” Tourism is experiencing a rapid and steep drop in demand during the COVID-19 pandemic. Despite the tourism industry’s proven resilience in other unprecedented times, the impact of the current pandemic will likely last longer for international tourism than for other affected industries. However, the tourism industry should not only recover but also reimagine and reform the next normal economic order. Currently, there is a lack of research on how crises can alter the industry, how the industry adapts to changes with innovative techniques, and how research that can establish the next norms can be conducted. To study the needs and gaps in research work, the author reviews past and emerging literature to capture its impacts and impart some ideas from different research fields that will allow tourism to grow and evolve.

Biographies

Naveen Donthu is a Distinguished University Professor at Georgia State University. He holds the title of Vanchel Pennebaker Eminent Scholar Chair and is the Kenneth Bernhardt Distinguished Department Chair of the Marketing Department. His research has appeared in journals such as Marketing Science , Management Science , Journal of Marketing , Journal of Marketing Research , and Journal of Consumer Research. He is the current editor-in-chief for the Journal of Business Research .

Anders Gustafsson is a Professor of Marketing at the Norwegian Business School. Dr Gustafsson is also a Distinguished Professorial Fellow at the University of Manchester’s Alliance Manchester Business School, and he is part of Center for Services Leadership Global Faculty at the W. P. Carey School of Business, Arizona State University. Dr. Gustafsson has published articles in journals such as the Journal of Marketing , Journal of Marketing Research , Journal of Consumer Research , Journal of Service Research , and Journal of Product Innovation Management . He is the current editor-in-chief for the Journal of Business Research and an area editor for the Journal of Service Research . Recently, he received the Christopher Lovelock Career Contributions to the Services Discipline Award. He is the current president of AMA’s Academic Council (2019/2020).

  • Asmelash L., Cooper A. CNN; 2020. Nearly 80% of hotel rooms in the US are empty, according to new data. https://edition.cnn.com/2020/04/08/us/hotel-rooms-industry-coronavirus-trnd/index.htm [ Google Scholar ]
  • Cacioppo J.T., Hawkley L.C. Perceived social isolation and cognition. Trends in Cognitive Sciences. 2009; 13 (10):447–454. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • Campbell A.M. An increasing risk of family violence during the Covid-19 pandemic: Strengthening community collaborations to save lives. Forensic Science International: Reports. 2020:100089. [ Google Scholar ]
  • Funk S., Gilad E., Watkins C., Jansen V.A. The spread of awareness and its impact on epidemic outbreaks. Proceedings of the National Academy of Sciences. 2009; 106 (16):6872–6877. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • Jaworski B., Kohli A.K., Sahay A. Market-driven versus driving markets. Journal of the Academy of Marketing Science. 2000; 28 (1):45–54. [ Google Scholar ]
  • Jorda O., Singh S.R., Taylor A.M. National Bureau of Economic Research; 2020. Longer-run economic consequences of pandemics. (Report no. w26934) [ Google Scholar ]
  • Nowland R., Necka E.A., Cacioppo J.T. Loneliness and social internet use: Pathways to reconnection in a digital world? Perspectives on Psychological Science. 2018; 13 (1):70–87. [ PubMed ] [ Google Scholar ]
  • Potter C.W. A history of influenza. Journal of Applied Microbiology. 2001; 91 (4):572–579. [ PubMed ] [ Google Scholar ]
  • Rapoza K. Forbes; 2020. Watch out for china buying spree, NATO warns. https://www.forbes.com/sites/kenrapoza/2020/04/18/watch-out-for-china-buying-spree-nato-warns/#623eada31758 [ Google Scholar ]
  • Stöhr K., Esveld M. Will vaccines be available for the next influenza pandemic? Science. 2004; 306 :2195–2196. [ PubMed ] [ Google Scholar ]
  • Tucker H. Forbes; 2020. Coronavirus bankruptcy tracker: These major companies are failing amid the shutdown. https://www.forbes.com/sites/hanktucker/2020/05/03/coronavirus-bankruptcy-tracker-these-major-companies-are-failing-amid-the-shutdown/#5649f95d3425 [ Google Scholar ]
  • Vargo S.L.…Lusch R.F. It’s all B2B… and beyond: Toward a systems perspective of the market. Industrial Marketing Management. 2011; 40 (2):181–187. [ Google Scholar ]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • View all journals

Business and management articles from across Nature Portfolio

Latest research and reviews.

research papers on business

Modeling the intention to consume and willingness to pay premium price for 3D-printed food in an emerging economy

  • Marvello Yang
  • Mohammad Enamul Hoque

research papers on business

Factors influencing continuance intention to use mobile banking: an extended expectation-confirmation model with moderating role of trust

  • Giang-Do Nguyen
  • Thu-Hien Thi Dao

research papers on business

Hybrid organizations: a classification within economic sectors

  • Alisher Mansurov

research papers on business

Individual entrepreneurial orientation for entrepreneurial readiness

  • Adeshina Olushola Adeniyi
  • Vangeli Gamede
  • Evelyn Derera

research papers on business

Exploring the appeal of villainous characters in film-induced tourism: perceived charismatic leadership and justice sensitivity

research papers on business

A contingent value of bricolage strategy on SMEs’ organizational resilience: lessons from the COVID-19 pandemic

  • Ji-Hoon Park

Advertisement

News and Comment

research papers on business

Post-pandemic acceleration of demand for interpersonal skills

Aggregate demand for interpersonal skills in the Australian labour market has accelerated since the onset of the COVID-19 pandemic. Further, there has been a high degree of complementarity between remote work and demand for interpersonal skills during this period.

research papers on business

A challenge for the law and artificial intelligence

Borrowing the format of public competitions from engineering and computer science, a new type of challenge in 2023 tested real-world AI applications with legal assessments based on the EU AI Act.

  • Thomas Burri

research papers on business

Workplaces must respond better to the bullied boss

Bullying comes in many forms, including when subordinates bully a manager. Sara Branch argues that workplaces should implement policies to combat all types of bullying.

  • Sara Branch

research papers on business

Forced labour in US food supply chains

A risk assessment of land-based food supply in the United States reveals a high risk of forced labour in domestic production and processing.

  • Amy V. Benstead

From science to business: translating live biotherapeutic products to the clinic

At Pulmobiotics, we engineer bacteria for the treatment of respiratory diseases. Here, we outline how we designed MycoChassis — an attenuated bacterium strain obtained by genome engineering of Mycoplasma pneumoniae (a human lung pathogen) — and discuss the challenges on the road to its clinical translation.

  • Maria Lluch-Senar

research papers on business

Gordon Moore (1929–2023)

Co-founder of Intel, creator of Moore’s law and philanthropist.

  • James S. Clarke

Quick links

  • Explore articles by subject
  • Guide to authors
  • Editorial policies

research papers on business

  • Browse All Articles
  • Newsletter Sign-Up

SmallBusiness →

No results found in working knowledge.

  • Were any results found in one of the other content buckets on the left?
  • Try removing some search filters.
  • Use different search filters.

business analyst Recently Published Documents

Total documents.

  • Latest Documents
  • Most Cited Documents
  • Contributed Authors
  • Related Sources
  • Related Keywords

ANEC: Artificial Named Entity Classifier based on BI-LSTM for an AI-based Business Analyst

Business users across enterprises today rely on reports and dashboards created by IT organizations to understand the dynamics of their business better and get insights into the data. In many cases, these users are underserved and do not possess the technical skillset to query the data source to get the information they need. There is a need for users to access information in the most natural way possible. AI-based Business Analysts are going to change the future of business analytics and business intelligence by providing a natural language interface between the user and data. This natural language interface can understand ambiguous questions from users, the intent and convert the same into a database query. One of the important elements of an AI-based business analyst is to interpret a natural language question. It also requires identification of key business entities within the question and relationship between them to generate insights. The Artificial Named Entity Classifier (ANEC) helps us take a huge step forward in that direction by not only identifying but also classifying entities with the help of the sequence recognising prowess of BiLSTMs.

Customer Segmentation using RFM Model and K-Means Clustering

Today as the competition among marketing companies, retail stores, banks to attract newer customers and maintain the old ones is in its peak, every company is trying to have the customer segmentation approach in order to have upper hand in competition. So Our project is based on such customer clustering method where we have collected, analyzed, processed and visualized the customer’s data and build a data science model which will help in forming clusters or segments of customers using the k-means clustering algorithm and RFM model (Recency Frequency Monetary) for already existing customers. The input dataset we used is UK’s E-commerce dataset from UCI repository for Machine Learning which is based on customer’s purchasing behavioral. At the very simple the customer clusters would be like super customer, intermediate customers, customers on the verge of churning out based on RFM score .Along with this we also have created a web model where an e-commerce startup or e-commerce business analyst can analyze their own customers based on model we created .So using this it will be easy to target customers accordingly and achieve business strength by maintaining good relationship with the customers .

A mathematical model to evaluate return on investment in higher education

Subject. The article assesses the effectiveness of investments in higher education. Objectives. The aim is to assess the performance of investments in higher education for a Master’s student at the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty. Methods. The methodology, presented in the study, includes three stages. The first assesses the demand for skills, the second assesses how the supply of skills match the demand, and the third – the effectiveness of investments in higher education, based on the developed mathematical model, scenario analysis, and decision tree. Results. We revealed that for a business analyst, the most important categories of skills are project management, decision-making, organizational competencies, communication, and knowledge of corporate software. The most required skills in these categories are the knowledge of business processes, project documentation, systems thinking, teamwork, communication, and well-bred speech. The analysis of correspondence between the competencies required by employers and those acquired in the training process showed that Master’s graduates meet the demand for the position of a business analyst in the labor market by 69%. Conclusions. The evaluation of the effectiveness of investment in higher education for a Master’s student of the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty, shows that it is more profitable for a Bachelor graduate to continue studying for a Master's degree, rather than go straight to work.

Business intelligence as a decision support system tool

The relevance of the topic considered in the article is to solve the problems of designing management decision support systems for enterprises based on business analytics technology. The research purpose is to analyze the applied methodologies during the design stage of the enterprise information system, to develop principles for using management decision support systems based on business intelligence. The problem statement is to analyze the technologies available on the market, which deal with business analyst systems, their potential use for decision support systems, and to identify the main stages of business analyst for enterprises. Business intelligence (BI) is information that can be obtained from data contained in the operational systems of a firm, enterprise, corporation, or from external sources. The BI can help the management of a company make the best decision in the chosen sphere of human activity faster, and, consequently, win the competition in the market for goods and services. A decision support system (DSS) which uses business intelligence, is an automated structure designed to assist professionals in making decisions in a complex environment and to objectively analyze a subject area. The decision support system is the result of the integration of management information systems and database management systems (DBMS). The internal development of BI is more cost-effective. The methods used are Structured Analysis and Design Technique and Object-oriented methods. The results of the research: the analysis of the possibilities was conducted and recommendations relating to the use of BI within DSS were given. Competition between BI software in business analysts reduces the cost of products created making them accessible to end-users – producers, traders and corporations.

A Literature Review and Overview of Performance Management: A Guide to the Field

The underlining presupposition and the supposition of performance management as a study field have been controversial or have a non-defined concept ever since the field was introduced to the mainstream economy. The paper covers the concept of performance management as a business analyst, scrum master, archeologist, and leader. The research delves into the founding history of performance management and analyzes critical performance management tools. Our findings show that performance management should be seen, managed, and played as an infinite game while creating incentives for the players who will, in turn, drive productivity in any industry.

PECULIARITIES OF USING BUSINESS ANALYSIS TECHNIQUES IN ADMINISTRATIVE MANAGEMENT DURING THE COVID PANDEMIC-19

The current state of motor transport enterprises, which is characterized by negative dynamics of development in all sectors of the transport sector, is studied. The research of scientific works determined the direction of the article and the object of research was business processes in administrative management. That is, it is impossible not to agree with the authors to solve the crisis of modern enterprises. It should be noted that all of them are solved through the mechanisms of the administrative management system. Therefore, it became necessary to form conceptual features of the use of business analyst in administrative management during the Covid pandemic 19. Modern approaches to administrative management are considered, providing reliable administrative management of the motor transport enterprise. Management of business processes in motor transport enterprises of business provides their constant improvement and optimization therefore the most important tools of process management are approaches and methods of improvement of business processes managed by administrative management systems. The researched approaches are aimed at identifying duplication of functions, bottlenecks, cost centers, quality of individual operations, missing information, the possibility of automation and quality management. The main directions and software products for automation of business processes in the system of administrative management are established. It is proved that the holistic application of approaches and elements of business analyst in the administrative management of the enterprise will lead to great chances of maintaining the competitiveness of motor transport enterprises and ways out of the post-crisis crisis. The measures of administrative management concerning improvement of activity of the motor transport enterprises are offered. Therefore, in order for trucking companies to develop and differ from their competitors in the level of services provided and the level of comfort, in the critical conditions of the COVID-19 pandemic it is necessary to radically change the methods of administrative management, ie reengineer business processes.

Business Analyst Tasks for Requirement Elicitation

Dealing with the challenge of business analyst skills mismatch in the fourth industrial revolution, features of the application of game theory in the economic activity of economic entities.

Today, there are a huge number of different tools that help reduce risks, but the problem is that they rely on classical probability theory, statistics, etc. These methods can be effective, but they do not take into account the interaction of market participants, psychological characteristics. These problems entail an increase in risks and, as a result, a drop in income and other difficulties. Often, to solve such problems, a business analyst turns to such a branch of mathematics as game theory. Game theory refers to a mathematical method that looks for optimal strategies in the course of a game, and a game refers to a situation in which there are two or more participants who are fighting to defend their interests. A special advantage of game theory is to take into account the struggle of interests of each party, this helps to better understand the current situation and find the optimal solution plan for the real processes taking place in the economy of an economic entity.

Development of a BI application. Moving from a business idea to formulation of the problem

Development of BI applications and, in general, Business Intelligence are no longer new concepts for the market. Nevertheless, there is practically no literature of practical significance. This article is aimed at analyzing the author’s practical experience with the generation of conclusions and specific advice for a novice business analyst to use in his work. Inexperienced professionals just starting their careers in BI can face a variety of challenges, especially when dealing with business customers and developers. Therefore, the article pays special attention to the description of research objects and their correct interaction with each other. It also provides a detailed analysis of the initial stages: from the customer’s need to develop an application to setting clear detailed requirements for the contractor. The result of this work was the proposed methodology for step-by-step work and analysis of the difficulties that may be encountered on the way of the “newly minted” business analyst.

Export Citation Format

Share document.

research papers on business

Government-funded R&D produces long-term productivity gains

February 13, 2024

Economists and policymakers have been broadly concerned about slowing U.S. productivity growth in recent decades, particularly since the late 1960s.

Productivity growth occurs when more economic output is produced without using more inputs to production, such as workers or machinery. Economists interpret productivity growth as reflecting technological progress and greater know-how.

Examining several measures of U.S. productivity, we find that increases in nondefense government research and development (R&D) appear to spur sustained growth in long-term productivity.

Productivity gains improve economic well-being

Broadly speaking, productivity growth is what fuels long-run increases in living standards. When workers are more productive—meaning they can produce more from an hour of labor—their wages should rise to reflect as much. Slower U.S. productivity growth, in turn, means wages and living standards don’t rise as quickly.

While the deceleration in U.S. productivity growth is evident in the data, there is less agreement about why productivity has been slowing. Economists Simon Johnson and Jonathan Gruber offer a potential explanation in their book, Jump-Starting America: How Breakthrough Science Can Revive Economic Growth and the American Dream . They say government-funded R&D is key to productivity growth, and the nation previously invested more in such efforts.

“A declining public sector role in R&D has coincided with a slowdown in productivity growth and a stagnating standard of living for most Americans,” they write.

Government R&D broadens our knowledge

While the slowdown in U.S. productivity growth since the late 1960s coincides with a relative decline in government R&D spending, the causality underlying this relationship is far from clear. Higher growth in public infrastructure or R&D spending by businesses could also have driven faster productivity growth in the early post-World War II era.

Why might government-funded R&D be particularly important for productivity growth?

Broadly speaking, the private sector invests more heavily in the development part of R&D, that is, bringing goods to market and creating work that can be patented. The government, conversely, tends to invest relatively more in basic and applied research, work that expands our fundamental knowledge and efforts that can generate big spillovers but can be hard to patent.

Think physics research conducted with particle accelerators at the National Laboratories or DNA sequencing for the Human Genome Project, R&D funded by the Department of Energy and National Institutes of Health. Other government-funded R&D is conducted at universities or contracted out to private firms. Much of this focuses on basic research, which the private sector underfunds because it can be difficult to monetize the results.

New paper explores R&D appropriations shocks

In our new Federal Reserve Bank of Dallas working paper, “ The Returns to Government R&D: Evidence from U.S. Appropriations Shocks ,” we use a novel empirical strategy to contribute causal evidence on the effects of government-funded R&D on U.S. productivity growth and other measures of innovation.

We first analyze the post-war history of congressional appropriations for the R&D activities of five major federal agencies that account for the lion’s share of federal R&D investments: the Department of Defense, Department of Energy, National Aeronautics and Space Administration, National Institutes of Health and National Science Foundation.

Our analysis identifies large, relatively unanticipated changes (shocks) in the R&D appropriations for these agencies that were not motivated by short-run macroeconomic conditions. We use these R&D appropriations shocks to estimate the dynamic causal effects of government-funded R&D on productivity growth and other measures of innovation.

We find that shocks to nondefense R&D appropriations lead to significant increases in various measures of productivity and scientific innovation, but only with a delay—consistent with implementation lags and a gradual diffusion of new knowledge.

R&D appropriations shocks boost total factor productivity

Our preferred measure of productivity is utilization-adjusted total factor productivity. It reflects all residual growth in business-sector output less all measurable inputs, adjusted for short-run business cycle fluctuations that can affect the use of available inputs such as labor (hence, utilization-adjusted). In our analysis, we use data the Federal Reserve Bank of San Francisco constructs on total factor productivity for the U.S. business sector.

Chart 3

Downloadable chart | Chart data

After about eight years, productivity starts to significantly and steadily increase. It continues rising and remains persistently elevated for at least 15 years after the increase in R&D appropriations. Put differently, greater nondefense government R&D appears to spur gains in long-term productivity, thus increasing living standards.

Similarly, we find that increases in nondefense government R&D boost business-sector labor productivity (output per hour worked) and potential output (noninflationary levels of output reflecting productivity growth), again with a lag and then a highly persistent effect.

We also find evidence that nondefense R&D appropriations shocks increase innovative inputs and outputs, such as the number of scientific researchers employed, the number of science and engineering doctoral recipients and the flow of new, innovative patents. These effects also only materialize after a lag.

For instance, the number of newly minted PhDs in science, technology, engineering and mathematics (commonly known as STEM) fields rises only after about seven or eight years, roughly the time it takes a professor to secure a federal research grant, recruit a student to join the lab and then see the student through to a degree.

No clear evidence defense R&D provides similar productivity gains’

On the other hand, we find no evidence of an economically or statistically significant increase in productivity or other measures of private sector innovation in response to R&D for national defense functions, at least not over the 15-year horizons we consider.

But why would nondefense R&D have a different effect than defense R&D?

For starters, military know-how is often classified to maintain military superiority, deliberately impeding knowledge spillovers. The military also invests relatively more in the development of weapons systems and less in basic and applied research than the nondefense agencies—the National Aeronautics and Space Administration, National Institutes of Health, National Science Foundation and the Department of Energy (excluding its R&D for nuclear weapons).

Defense R&D activities surely contribute to our national security, but they do not appear to drive economic growth the same way as nondefense R&D, at least not within a similar time frame.

Diminished public investment, gains since 1960s

We use the nondefense R&D appropriations shocks to estimate how responsive productivity growth is to changes in the government R&D capital stock. Then we apply those estimates to the actual growth in government R&D capital to quantify its contribution to productivity growth.

Chart 2 shows our preferred measure of total factor productivity growth (black line), along with our estimates of the contribution of government R&D capital (blue) and public infrastructure capital (red) to that productivity growth.

Chart 2

U.S. productivity growth has slowed markedly since the late 1960s—apart from the information technology revolution near the start of the century—and government-funded R&D heavily contributed to the faster postwar rates of productivity growth.

Our estimates indicate that government-funded R&D accounts for roughly one quarter of all business sector productivity growth since World War II, including one quarter of the deceleration in productivity growth since the late 1960s.

Correlation does not imply causation in general, but our new causal evidence lends support to the thesis of Gruber and Johnson about the important relationship between government-funded R&D and U.S. productivity growth.

About the authors

Andrew J. Fieldhouse

Andrew J. Fieldhouse is a visiting assistant professor at the Mays Business School at Texas A&M University.

Karel Mertens

Karel Mertens is a senior economic policy advisor in the Research Department at the Federal Reserve Bank of Dallas.

The views expressed are those of the authors and should not be attributed to the Federal Reserve Bank of Dallas or the Federal Reserve System.

Related Articles

paper

Making a Song and Dance About It: The Effectiveness of Teaching Children Vocabulary with Animated Music Videos

Programs that engage young children in movement and song to help them learn are popular but experimental evidence on their impact is sparse. We use an RCT to evaluate the effectiveness of Big Word Club (BWC), a classroom program that uses music and dance videos for 3-5 minutes per day to increase vocabulary. We conducted a field experiment with 818 preschool and kindergarten students in 47 schools in three U.S. states. We find that treated students scored higher on a test of words targeted by the program (0.30 SD) after four months of use and this effect persisted for two months.

This work was supported by J-PAL. This study was registered on the AEA RCT Registry (AEARCTR-0002631) and received approval from the Social and Behavioral Sciences IRB from the University of Chicago (IRB17-1609). We are grateful to the staff at the Behavioral Insights and Parenting Lab, led by Michelle Park Michelini, for invaluable effort in implementing this intervention, and Harkirat Kaur for excellent research assistance. We are grateful to Shane DeRolf for his efforts not only in developing the Big Word Club but also in enthusiastically embracing the evaluation process. We also thank participants at the Advances with Field Experiments and AEFP conferences for helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

Download Citation Data

  • randomized controlled trials registry entry

More from NBER

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

15th Annual Feldstein Lecture, Mario Draghi, "The Next Flight of the Bumblebee: The Path to Common Fiscal Policy in the Eurozone cover slide

  • Skip to Guides Search
  • Skip to breadcrumb
  • Skip to main content
  • Skip to footer
  • Skip to chat link
  • Report accessibility issues and get help
  • Go to Penn Libraries Home
  • Go to Franklin catalog

Critical Writing Program: Decision Making - Spring 2024: Researching the White Paper

  • Getting started
  • News and Opinion Sites
  • Academic Sources
  • Grey Literature
  • Substantive News Sources
  • What to Do When You Are Stuck
  • Understanding a citation
  • Examples of Quotation
  • Examples of Paraphrase
  • Chicago Manual of Style: Citing Images
  • Researching the Op-Ed
  • Researching Prospective Employers
  • Resume Resources
  • Cover Letter Resources

Research the White Paper

Researching the White Paper:

The process of researching and composing a white paper shares some similarities with the kind of research and writing one does for a high school or college research paper. What’s important for writers of white papers to grasp, however, is how much this genre differs from a research paper.  First, the author of a white paper already recognizes that there is a problem to be solved, a decision to be made, and the job of the author is to provide readers with substantive information to help them make some kind of decision--which may include a decision to do more research because major gaps remain. 

Thus, a white paper author would not “brainstorm” a topic. Instead, the white paper author would get busy figuring out how the problem is defined by those who are experiencing it as a problem. Typically that research begins in popular culture--social media, surveys, interviews, newspapers. Once the author has a handle on how the problem is being defined and experienced, its history and its impact, what people in the trenches believe might be the best or worst ways of addressing it, the author then will turn to academic scholarship as well as “grey” literature (more about that later).  Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position.  Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting, and overlapping perspectives. When people research out of a genuine desire to understand and solve a problem, they listen to every source that may offer helpful information. They will thus have to do much more analysis, synthesis, and sorting of that information, which will often not fall neatly into a “pro” or “con” camp:  Solution A may, for example, solve one part of the problem but exacerbate another part of the problem. Solution C may sound like what everyone wants, but what if it’s built on a set of data that have been criticized by another reliable source?  And so it goes. 

For example, if you are trying to write a white paper on the opioid crisis, you may focus on the value of  providing free, sterilized needles--which do indeed reduce disease, and also provide an opportunity for the health care provider distributing them to offer addiction treatment to the user. However, the free needles are sometimes discarded on the ground, posing a danger to others; or they may be shared; or they may encourage more drug usage. All of those things can be true at once; a reader will want to know about all of these considerations in order to make an informed decision. That is the challenging job of the white paper author.     
 The research you do for your white paper will require that you identify a specific problem, seek popular culture sources to help define the problem, its history, its significance and impact for people affected by it.  You will then delve into academic and grey literature to learn about the way scholars and others with professional expertise answer these same questions. In this way, you will create creating a layered, complex portrait that provides readers with a substantive exploration useful for deliberating and decision-making. You will also likely need to find or create images, including tables, figures, illustrations or photographs, and you will document all of your sources. 

Business & Research Support Services Librarian

Profile Photo

Connect to a Librarian Live Chat or "Ask a Question"

  • Librarians staff live chat from 9-5 Monday through Friday . You can also text to chat: 215-543-7674
  • You can submit a question 24 hours a day and we aim to respond within 24 hours 
  • You can click the "Schedule Appointment" button above in librarian's profile box (to the left), to schedule a consultation with her in person or by video conference.  
  • You can also make an appointment with a  Librarian by subject specialization . 
  • Connect by email with a subject librarian

Find more easy contacts at our Quick Start Guide

  • Next: Getting started >>
  • Last Updated: Feb 15, 2024 12:28 PM
  • URL: https://guides.library.upenn.edu/spring2024/decision-making

IMAGES

  1. 😀 Business research sample. Research Paper Example. 2019-03-01

    research papers on business

  2. 32+ Research Paper Samples

    research papers on business

  3. How to Write a Research Paper in English

    research papers on business

  4. 38+ Research Paper Samples

    research papers on business

  5. Research Paper Apa Style

    research papers on business

  6. 💄 Business research paper format. Formatting a Research Paper. 2022-11-02

    research papers on business

VIDEO

  1. How to critically review research papers in 4 steps #academicwriting #studytips #thesis

  2. Secret To Writing A Research Paper

  3. Key Points on Why homework is good for students

  4. Websites for research papers #philippines #research #thesis #studytips #rrl #presentation

  5. Write a research paper in a WEEK (what no one tells you)

  6. Business administration for css and pms

COMMENTS

  1. Journal of Business Research

    Business-to-Business Research Corporate Social Responsibility & Business Ethics Sales Research Stacey Robinson Advertising and Marketing Communications Marketing Retailing and Multichannel Management Beyond these tracks, JBR regularly highlights important emerging topics in its special issues.

  2. PDF The Impact of Covid-19 on Small Business Owners: National Bureau of

    1. Introduction The widespread closing of stores and businesses in the United States and around the world due to the coronavirus is unprecedented. Stores, factories and many other businesses have closed by policy mandate or downward demand shifts.

  3. Business & Management

    First published Jan 29, 2021 Sample Selection in Systematic Literature Reviews of Management Research Martin R. W. Hiebl Organizational Research Methods Open Access Article commentary First published Jun 21, 2023 The Now, New, and Next of Digital Leadership: How Artificial Intelligence (AI) Will Take Over and Change Leadership as We Know It

  4. Business or Company Management: Articles, Research, & Case Studies on

    New research on business or company management from Harvard Business School faculty on issues including the relationship between corporate purpose and financial performance, the downsides of self-interest on businesses, government, and the economy, and advice for new CEOs. Page 1 of 17 Results 02 Jan 2024 What Do You Think?

  5. HBR's Most-Read Research Articles of 2021

    December 29, 2021 fotosipsak/Getty Images Summary. What will it take to make work better? Over the past year, HBR has published a wide array of research-backed articles that explore topics...

  6. 94062 PDFs

    Explore the latest full-text research PDFs, articles, conference papers, preprints and more on BUSINESS MANAGEMENT. Find methods information, sources, references or conduct a literature...

  7. Digital transformation in business and management research: An overview

    This study is divided into two parts: (1) mapping the thematic evolution of the DT research in the areas of business and management by focusing on papers that were published in the Chartered Association of Business Schools' (ABS) ≥ 2-star journals during the period 2010-2020; (2) based on the findings of the first part, proposing a ...

  8. 15845 PDFs

    Jan 2024 Joseph Vincent Anthony Lawrence Paul Joseph Oluwaseyi Park Thaichon Explore the latest full-text research PDFs, articles, conference papers, preprints and more on BUSINESS RESEARCH....

  9. Full article: What do we know about business and economics research

    2.1. Data selection strategy. For selecting the data, we relied on the Scopus database. It is the largest multidisciplinary database in social sciences, economics, finance and business studies and is widely used for conducting bibliometric studies (Baker et al., Citation 2021; Donthu et al., Citation 2020).Scopus is considered a middle choice in terms of the rigorousness of vetting research ...

  10. Ethical Research in Business Ethics

    In this editorial essay, we argue that business ethics research should be aware of the ethical implications of its own methodological choices, and that these implications include, but go beyond, mere compliance with standardized ethical norms. Methodological choices should be made specifically with reference to their effects on the world, both within and outside the academy. Awareness of these ...

  11. 12399 PDFs

    Explore the latest full-text research PDFs, articles, conference papers, preprints and more on BUSINESS ANALYTICS. Find methods information, sources, references or conduct a literature review...

  12. Working Papers

    Page 1 of 1,936 Results → 2024 Working Paper Principles and Content for Downstream Emissions Disclosures By: Robert S. Kaplan and Karthik Ramanna In a previous paper, we proposed the E-liability carbon accounting algorithm for companies to measure and subsequently reduce their own and their suppliers' emissions.

  13. 35 years of research on business intelligence process: a synthesis of a

    35 years of research on business intelligence process: a synthesis of a fragmented literature Yassine Talaoui, Marko Kohtamäki Management Research Review ISSN: 2040-8269 Article publication date: 7 December 2020 Issue publication date: 7 May 2021 Downloads 9232 pdf (679 KB) Abstract Introduction Methodology

  14. Effects of COVID-19 on business and research

    In total, there are 13 papers that cover different industry sectors (e.g., tourism, retail, higher education), changes in consumer behavior and businesses, ethical issues, and aspects related to employees and leadership. Go to: 1. Introduction There has been a long history of fear of pandemic outbreaks.

  15. Full article: Business analytics and firm performance: role of

    Therefore, based on this perceived research gap, this research paper seeks to help bridge the research divide, and propose a comprehensive theoretical framework that informs on the relationship between business analytics and performance. ... With respect to business analytics research, the correlation between business analytics and performance ...

  16. The development of business model research: A bibliometric review

    The development of business model research: A bibliometric review Every business since the dawn of commerce has followed a business model (BM) ( ). A BM articulates how a business creates, delivers and captures value ( Osterwalder and Pigneur, 2010 ).

  17. Business and management

    Forced labour in US food supply chains. A risk assessment of land-based food supply in the United States reveals a high risk of forced labour in domestic production and processing. Amy V. Benstead ...

  18. Small Business: Articles, Research, & Case Studies

    18 Apr 2020 Working Paper Summaries How Are Small Businesses Adjusting to COVID-19? Early Evidence From a Survey by Alexander Bartik, Marianne Bertrand, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, and Christopher Stanton

  19. The Implications of Big Data Analytics on Business Intelligence ...

    This paper is a qualitative study on how big data analytics has helped shaped business intelligence and drive the success of many companies. The findings reveal that big data analytics has facilitated the extraction of information from the vast amounts of data generated by businesses every second.

  20. business analyst Latest Research Papers

    The paper covers the concept of performance management as a business analyst, scrum master, archeologist, and leader. The research delves into the founding history of performance management and analyzes critical performance management tools. Our findings show that performance management should be seen, managed, and played as an infinite game ...

  21. The Welfare Effects of Selling Leads in a Two-Sided Marketplace

    USC Marshall School of Business Research Paper Series. Subscribe to this free journal for more curated articles on this topic FOLLOWERS. 5,050. PAPERS. 911. This Journal is curated by: Gerard J. Tellis at University of Southern California - Marshall School of Business, Department of Marketing. Marketing Science eJournal ...

  22. 30 Emerging Technologies That Will Guide Your Business Decisions

    This theme focuses on making the right business and ethical choices in the adoption of AI and using AI design principles that will benefit people and society.. Human-centered AI (HCAI) is a common AI design principle that calls for AI to continuously benefit from human input. Behavioral analytics refers to session-tracking capabilities that monitor user interactions with a protected service to ...

  23. The Perception of Ethics in Business: Analysis of Research Results

    Abstract. Ethics in business is of key importance in the existence of companies in numerous countries and regions. If a company wishes to be perceived as a reliable partner in business, it should implement the elements of this concept, or indeed this concept itself. Taking into account the aforementioned circumstances, the goal of our paper is ...

  24. Government-funded R&D produces long-term productivity gains

    New paper explores R&D appropriations shocks. In our new Federal Reserve Bank of Dallas working paper, "The Returns to Government R&D: Evidence from U.S. Appropriations Shocks," we use a novel empirical strategy to contribute causal evidence on the effects of government-funded R&D on U.S. productivity growth and other measures of innovation.

  25. Making a Song and Dance About It: The Effectiveness of Teaching

    Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, and business professionals.

  26. (Pdf) Business and Management Research

    Business research comes within the purview of social science research. Social science research refers to research conducted by social scientists (primarily within sociology and social...

  27. Best-Performing Cities 2024: Focus on Sustainable Growth and Resilience

    The Best-Performing Cities (BPC) 2024 rankings evaluate the performance of 403 metropolitan areas across the US based on 13 indicators that cover labor market conditions, high-tech impact, and access to economic opportunities. As the post-pandemic economy reaches a new status quo, metropolitan areas remain at the heart of the nation's growth.

  28. Researching the White Paper

    Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position. Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting ...

  29. Research Guides: PEMBA & Executive MBA for Healthcare Leadership

    Deloitte University Press publishes original articles, reports, and periodicals that provide insights for businesses and the public sector to draw upon research and experience from throughout the professional services organization, and that of coauthors in academia and business, to advance the conversation on a broad spectrum of topics of ...