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Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
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Hsu, L., & Jang, S. (2009), Effects of Restaurant Franchising: Does an optimal franchise proportion exist?

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This is the presentation file I created for an HTM 681 class discussion. …

This is the presentation file I created for an HTM 681 class discussion.
The contents are based on an Li-Tzang (Jane) Hsu and SooCheong (Shawn) Jang's article, Effects of Restaurant Franchising: Does an optimal franchise proportion exist?
in International Journal of Hospitality Management Volume 28, Issue 2, June 2009, Pages 204-211.

Published in: Economy & Finance, Business
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  • 1. Effects of Restaurant Franchising: Does an optimal franchise proportion exist?<br />January 22<br />Suh-hee Choi<br />HTM 681 2nd Article<br />Spring 2009<br />Hsu, L.,&amp; Jang, S. (in press)<br />
  • 2. Spinelli et al., 2003; Aliouche and Schlentrich, 2005<br />Research<br />Questions<br />Alon et al., 2004<br />Does franchise influence a restaurant firm’s performance? <br />franchise<br />Vs. <br />non-franchise<br />profitability <br />intangible value <br />Research based on<br />the empirical evidence<br />Does optimal franchise proportion exist? <br />• reduces investment cost / risk <br />• disadvantages <br />Other things being equal<br />Bradach, 1997<br />“marginal costs<br />= marginal benefits”<br />Organizational learning theory (Sorenson &amp; Sorenson, 2001)<br />Resource scarcity theory (Hunt, 1973; Norton, 1988; Oxenfeldt &amp; Thompson, 1968, Oxenfeldt &amp; Kelly, 1969)<br />Theories<br />Agency theory (Rubin, 1978)<br />
  • 3. Methodology<br />
  • 4.
  • 5.
  • 6. Methodology<br /> Dependent variables <br />ROA<br />ROE<br />Tobin’s Q<br />
  • 7. Methodology (cont.)<br />Independent variables<br />franchise proportion<br />Controlled variables<br />leverage<br />firm size (economy of scale) <br />advertising <br />profitability (in Tobin’s Q model)<br />
  • 8. Methodology<br />T-test<br />compare the means between <br /> franchise / non-franchise <br /> ROA(ROE, Tobin’s Q<br />Regression analysis <br />
  • 9. Methodology<br />Regression analysis <br />• normality  natural log transformation<br />• multicollinearity • heteroskedasticity<br />
  • 10. Resultsdescriptive information<br />
  • 11. Results franchise vs. non-franchise<br />profitability and intangible values are significantly higher in franchise firms than non-franchise firms<br />
  • 12. Results franchise vs. non-franchise<br />H1: Franchise restaurant firms have higher profitability and create more intangible value than non-franchise restaurant firms. <br />
  • 13. Results effects of franchise proportion<br />H2: There is non-linear relationship between franchise proportion and profitability and intangible value. <br />
  • 14. Results effects of franchise proportion<br />maximum ROA (ROE, Tobin’s Q)? <br /> shaped<br />
  • 15. Results geography matters<br />not significant<br />sq% coefficient:<br />negative linear <br />relationship<br /><ul><li>less dispersed </li></ul>max: 35% 36%<br />
  • 16. Results geography matters<br /><ul><li>dispersed hard to monitor  more franchising </li></ul>max: 52% 55% 43%<br />
  • 17. Conclusions<br />Franchising betters financial performance / intangible value.<br />Optimal proportions of franchising can be found (to maximize financial performance / intangible value).<br />other factors of optimal proportions might be significant : geographical dispersion was tested. <br />
  • 18. limitations <br />Didn’t include positioning and marketing concepts.<br />Focused only on restaurant industry. <br />Limited data available (what about small franchisors?) <br />
  • 19. Further studies <br />Develop methodologies to find optimal points that consider both maximizing profits and reducing risks at the same time (e.g. Agency Theory (Rubin, 1978)) <br />What happens if OTHER THINGS ARE NOT EQUAL?<br />Other benefits of franchising?<br />social values<br />sustainable relationships between the firms<br />
  • 20. appendix: White&amp;apos;s test<br />Assumption: V(ui) = s 2 + g(E(Yi))2<br />i.e. the variance of u depends on the expected value of Y (and hence on at least one of the x variables). <br /> V(ui) = s2 + g(b1 + b2x2 + ... + bkxk)2<br />H0: g = 0  homoscedasticity<br /> otherwise heteroscedasticity. <br />Regress e2 on x22, x32, etc and x2x3, x3x4, etc. <br />Obtain nR2 ~ c2(k-1) as an LM statistic. <br />www.sussex.ac.uk/economics/documents/lecture_4.ppt <br />

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