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Demonstration of exponential random graph models in tourism studies: Is tourism a means of global peace or the bottom line?

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  • Khalilzadeh, Jalayer

Abstract

Most social network analyses conducted in hospitality and tourism studies are merely descriptive. Despite the recent popularity of exponential-family of random graph models (ERGMs) in various scientific investigations, no studies have utilized these inferential methods of network analysis in hospitality and tourism studies. In some contexts, the power of these methods is undeniably superior to those of conventional statistical tests. Accordingly, in the current study, by using the controversial subject of tourism-peace, I demonstrated how ERGMs can be used in hypotheses testing and statistical modeling in hospitality and tourism context. The results of this study suggest that a change of perspective in tourism-peace discourse from tourism as a peacemaker to tourism as a peacekeeper can be a valid approach concerning the long-lasting debates on the relationship between tourism and peace.

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  • Khalilzadeh, Jalayer, 2018. "Demonstration of exponential random graph models in tourism studies: Is tourism a means of global peace or the bottom line?," Annals of Tourism Research, Elsevier, vol. 69(C), pages 31-41.
  • Handle: RePEc:eee:anture:v:69:y:2018:i:c:p:31-41
    DOI: 10.1016/j.annals.2017.12.007
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    1. Sommer, Robert & Aitkens, Susan, 1982. "Mental Mapping of Two Supermarkets," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 211-215, September.
    2. Liu, Bing & Huang, Songshan (Sam) & Fu, Hui, 2017. "An application of network analysis on tourist attractions: The case of Xinjiang, China," Tourism Management, Elsevier, vol. 58(C), pages 132-141.
    3. van Winsen, Frankwin & de Mey, Yann & Lauwers, Ludwig & Van Passel, Steven & Vancauteren, Mark & Wauters, Erwin, 2013. "Cognitive mapping: A method to elucidate and present farmers’ risk perception," Agricultural Systems, Elsevier, vol. 122(C), pages 42-52.
    4. Khalilzadeh, Jalayer & Tasci, Asli D.A., 2017. "Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research," Tourism Management, Elsevier, vol. 62(C), pages 89-96.
    5. Cai, Haiyan, 2017. "A note on jointly modeling edges and node attributes of a network," Statistics & Probability Letters, Elsevier, vol. 121(C), pages 54-60.
    6. Morris, Martina & Handcock, Mark S. & Hunter, David R., 2008. "Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i04).
    7. Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i01).
    8. Narang, Ritu, 2016. "Understanding purchase intention towards Chinese products: Role of ethnocentrism, animosity, status and self-esteem," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 253-261.
    9. Henderson, Geraldine R. & Iacobucci, Dawn & Calder, Bobby J., 1998. "Brand diagnostics: Mapping branding effects using consumer associative networks," European Journal of Operational Research, Elsevier, vol. 111(2), pages 306-327, December.
    10. Farmaki, Anna, 2017. "The tourism and peace nexus," Tourism Management, Elsevier, vol. 59(C), pages 528-540.
    11. Becken, Susanne & Carmignani, Fabrizio, 2016. "Does tourism lead to peace?," Annals of Tourism Research, Elsevier, vol. 61(C), pages 63-79.
    12. Stienmetz, Jason L. & Fesenmaier, Daniel R., 2015. "Estimating value in Baltimore, Maryland: An attractions network analysis," Tourism Management, Elsevier, vol. 50(C), pages 238-252.
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