IDEAS home Printed from https://ideas.repec.org/a/eee/anture/v69y2018icp31-41.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160738317301627
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.annals.2017.12.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. Farmaki, Anna, 2017. "The tourism and peace nexus," Tourism Management, Elsevier, vol. 59(C), pages 528-540.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoyi Shi & Xiaoxia Huang & Huifang Liu, 2022. "Research on the Structural Features and Influence Mechanism of the Low-Carbon Technology Cooperation Network Based on Temporal Exponential Random Graph Model," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    2. Ladan Ghahramani & Jalayer Khalilzadeh & Birendra KC, 2018. "Tour guides’ communication ecosystems: an inferential social network analysis approach," Information Technology & Tourism, Springer, vol. 20(1), pages 103-130, December.
    3. Raisi, Hossein & Baggio, Rodolfo & Barratt-Pugh, Llandis & Willson, Gregory, 2020. "A network perspective of knowledge transfer in tourism," Annals of Tourism Research, Elsevier, vol. 80(C).
    4. Chang Won Park & Ji-Yeon Lee & Bong-Seok Kim, 2023. "Sustainable Exchange and Cooperation Process in Exhibition and Convention: Applications for the Korean Peninsula From the Leipzig Trade Fair in Germany," SAGE Open, , vol. 13(4), pages 21582440231, October.
    5. Ruggieri, Giovanni & Iannolino, Salvatore & Baggio, Rodolfo, 2022. "Tourism destination brokers: A network analytic approach," Annals of Tourism Research, Elsevier, vol. 97(C).
    6. Kádár, Bálint & Gede, Mátyás, 2021. "Tourism flows in large-scale destination systems," Annals of Tourism Research, Elsevier, vol. 87(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kádár, Bálint & Gede, Mátyás, 2021. "Tourism flows in large-scale destination systems," Annals of Tourism Research, Elsevier, vol. 87(C).
    2. Ahn, Sang-Jin & Yi, Seung-Kyu, 2021. "Methodological framework for analyzing peace engineering: Focusing on Kaesong Industrial Complex and North Korean innovators in South Korea," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. De Nicola, Giacomo & Fritz, Cornelius & Mehrl, Marius & Kauermann, Göran, 2023. "Dependence matters: Statistical models to identify the drivers of tie formation in economic networks," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 351-363.
    4. Chang Won Park & Ji-Yeon Lee & Bong-Seok Kim, 2023. "Sustainable Exchange and Cooperation Process in Exhibition and Convention: Applications for the Korean Peninsula From the Leipzig Trade Fair in Germany," SAGE Open, , vol. 13(4), pages 21582440231, October.
    5. Huanhuan Hua & Amare Wondirad, 2020. "Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review," Sustainability, MDPI, vol. 13(1), pages 1-16, December.
    6. Dang-Pham, Duy & Pittayachawan, Siddhi & Bruno, Vince, 2016. "Impacts of security climate on employees’ sharing of security advice and troubleshooting: Empirical networks," Business Horizons, Elsevier, vol. 59(6), pages 571-584.
    7. Kai Wang & Menghan Wang & Chang Gan & Qinchang Chen & Mihai Voda, 2021. "Tourism Economic Network Structural Characteristics of National Parks in the Central Region of China," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    8. Duxbury, Scott W, 2019. "Mediation and Moderation in Statistical Network Models," SocArXiv 9bs4u, Center for Open Science.
    9. Goodreau, Steven M. & Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Morris, Martina, 2008. "A statnet Tutorial," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i09).
    10. repec:jss:jstsof:24:i09 is not listed on IDEAS
    11. Christine A. Bevc & Jessica H. Retrum & Danielle M. Varda, 2015. "Patterns in PARTNERing across Public Health Collaboratives," IJERPH, MDPI, vol. 12(10), pages 1-14, October.
    12. Aliakbar Akbaritabar & Vincent Antonio Traag & Alberto Caimo & Flaminio Squazzoni, 2020. "Italian sociologists: a community of disconnected groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2361-2382, September.
    13. Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2013. "ergm.userterms: A Template Package for Extending statnet," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i02).
    14. Alex Stivala & Garry Robins & Alessandro Lomi, 2020. "Exponential random graph model parameter estimation for very large directed networks," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-21, January.
    15. Yonghong Ma & Xiaomeng Yang & Sen Qu & Lingkai Kong, 2022. "Research on the formation mechanism of big data technology cooperation networks: empirical evidence from China," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1273-1294, March.
    16. Per Åsberg & Henrik Uggla, 2019. "Introducing multi-dimensional brand architecture: taking structure, market orientation and stakeholder alignment into account," Journal of Brand Management, Palgrave Macmillan, vol. 26(5), pages 483-496, September.
    17. Philipp Wassler & Giacomo Del Chiappa & Thi Hong Hai Nguyen & Giancarlo Fedeli & Nigel L. Williams, 2022. "Increasing vaccination intention in pandemic times: a social marketing perspective," Italian Journal of Marketing, Springer, vol. 2022(1), pages 37-58, March.
    18. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    19. repec:dau:papers:123456789/1758 is not listed on IDEAS
    20. Hugo Padrón-Ávila & Raúl Hernández-Martín, 2019. "Preventing Overtourism by Identifying the Determinants of Tourists’ Choice of Attractions," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    21. Pradeep Kumar Ponnamma Divakaran & Jie Xiong, 2022. "Eliciting brand association networks: A new method using online community data," Post-Print hal-03700393, HAL.
    22. Krivitsky, Pavel N., 2017. "Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 149-161.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:anture:v:69:y:2018:i:c:p:31-41. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/annals-of-tourism-research/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.