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The franchising business model: an entrepreneurial growth alternative

  • Published: 25 May 2010
  • Volume 8 , pages 75–98, ( 2012 )

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  • William Gillis 1 &
  • Gary J. Castrogiovanni 2  

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The franchising business model is widely and increasingly used by entrepreneurs seeking growth through geographic expansion. Thus, continued research efforts are needed to help entrepreneurs make wise choices as to whether the franchising business model is appropriate for them. To help promote such research, we reviewed the literature on reasons for franchising and outcomes of franchising. Based on that review, we drew conclusions as to future research directions likely to be fruitful. Specifically, we recommend that researchers (a) continue adding theoretical diversity to franchising research, (b) build large-scale, longitudinal databases, (c) test or control for implicit and explicit assumptions, (d) pay more attention to micro-level considerations within franchise networks, and (e) compare franchising with alternative business models suitable for geographic expansion.

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Department of Management, Mitchell College of Business, University of South Alabama, Mobile, AL, 36688-0002, USA

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Gillis, W., Castrogiovanni, G.J. The franchising business model: an entrepreneurial growth alternative. Int Entrep Manag J 8 , 75–98 (2012). https://doi.org/10.1007/s11365-010-0158-8

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Published : 25 May 2010

Issue Date : March 2012

DOI : https://doi.org/10.1007/s11365-010-0158-8

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Abstract: In this work, we tackle the challenge of enhancing the realism and expressiveness in talking head video generation by focusing on the dynamic and nuanced relationship between audio cues and facial movements. We identify the limitations of traditional techniques that often fail to capture the full spectrum of human expressions and the uniqueness of individual facial styles. To address these issues, we propose EMO, a novel framework that utilizes a direct audio-to-video synthesis approach, bypassing the need for intermediate 3D models or facial landmarks. Our method ensures seamless frame transitions and consistent identity preservation throughout the video, resulting in highly expressive and lifelike animations. Experimental results demonsrate that EMO is able to produce not only convincing speaking videos but also singing videos in various styles, significantly outperforming existing state-of-the-art methodologies in terms of expressiveness and realism.

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