Skip to main content

Structural Implications of Destination Value System Networks

  • Conference paper
  • First Online:
Information and Communication Technologies in Tourism 2017

Abstract

This study establishes the foundation for a system-level model for understanding destination value creation—the Destination Value System (DVS)—by empirically testing the relationships between destination network structures and total value created within a destination. Volunteered geographic information from 4.3 million geotagged Flickr photos and Florida tax records were used to describe the quarterly network structures and quarterly travel-related spending for 43 Florida destinations between 2007 and 2015. Econometric analysis of the panel data indicates that DVS network structures and seasonal effects have significant relationships with the total tourism-related sales of a destination. Density, out-degree centralization, and global clustering coefficient are found to have negative effects on destination value creation, while in-degree centralization, betweenness centralization, and subcommunity count are found to have positive effects. These results indicate strategic management of the destination network is an important activity of any destination management organization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Aggarwal, C. C. (Ed.). (2011). Social network data analysis. New York: Springer Science + Business Media LLC.

    Google Scholar 

  • Angus, E., & Thelwall, M. (2010). Motivations for image publishing and tagging on flickr. Paper Presented at the 14th International Conference on Electronic Publishing, Helsinki, Finland.

    Google Scholar 

  • Baggio, R., Scott, N., & Cooper, C. (2010). Network science: A review focused on tourism. Annals of Tourism Research, 37(3), 802–827.

    Article  Google Scholar 

  • Baltagi, B. (2013). Econometric analysis of panel data (5th ed.). West Sussex, UK: John Wiley & Sons.

    Google Scholar 

  • Beritelli, P., Bieger, T., & Laesser, C. (2013). The new frontiers of destination management: Applying Variable Geometry as a Function-Based Approach. Journal of Travel Research.

    Google Scholar 

  • Bhat, S. S., & Milne, S. (2008). Network effects on cooperation in destination website development. Tourism Management, 29(6), 1131–1140.

    Article  Google Scholar 

  • Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008.

    Article  Google Scholar 

  • Borgatti, S. P., & Halgin, D. S. (2011). On network theory. Organization Science, 22(5), 1168–1181.

    Article  Google Scholar 

  • Carlile, P. R. (2002). A pragmatic view of knowledge and boundaries: Boundary Objects in New Product Development. Organization Science, 442–455.

    Google Scholar 

  • Easterby-Smith, M., Lyles, M. A., & Tsang, E. W. K. (2008). Inter-organizational knowledge transfer: Current Themes and Future Prospects. Journal of Management Studies, 45(4), 677–690.

    Article  Google Scholar 

  • Florida Department of Revenue. (2015). Validated florida sales tax return receipts (Forms 9 & 10). Retrieved from http://dor.myflorida.com/taxes/pages/colls_from_7_2003.aspx.

  • Freeman, L. C. (2011). the development of social network analysis—with an emphasis on recent events. In J. Scott & P. J. Carrington (Eds.), The sage handbook of social network analysis (pp. 26–54). London: SAGE Publications Ltd.

    Google Scholar 

  • Hargadon, A., & Sutton, R. I. (1997). Technology brokering and innovation in a product development firm. Administrative Science Quarterly, 42(4), 716–749.

    Article  Google Scholar 

  • Haugland, S. A., Ness, H., Grønseth, B.-O., & Aarstad, J. (2011). Development of tourism destinations. Annals of Tourism Research, 38(1), 268–290.

    Article  Google Scholar 

  • Hui, T.-K., & Yuen, C. C. (2002). A study in the seasonal variation of japanese tourist arrivals in singapore. Tourism Management, 23(2002), 127–131.

    Article  Google Scholar 

  • Jackson, M. O. (2010). Social and economic networks. Princeton: Princeton University Press.

    Google Scholar 

  • Koc, E., & Altinay, G. (2007). An analysis of seasonality in monthly per person tourist spending in turkish inbound tourism from a market segmentation perspective. Tourism Management, 28(1), 227–237.

    Article  Google Scholar 

  • Li, G., Wong, K. K. F., Song, H., & Witt, S. F. (2006). Tourism demand forecasting: A Time Varying Parameter Error Correction Model. Journal of Travel Research, 45(2), 175–185.

    Article  Google Scholar 

  • McGlohon, M., Akoglu, L., & Faloutsos, C. (2011). Statistical properties of social networks. In C. C. Aggarwal (Ed.), Social network data analytics (pp. 17–42). New York: Springer.

    Chapter  Google Scholar 

  • McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in Social Networks. Annual Review of Sociology, 27(1), 415–444.

    Article  Google Scholar 

  • Murray, S. (2008). Digital images, photo-sharing, and our shifting notions of everyday aesthetics. Journal of Visual Culture, 7(2), 147–163.

    Article  Google Scholar 

  • Ness, H., Aarstad, J., Haugland, S. A., & Gronseth, B. O. (2013). Destination development: The Role of Interdestination Bridge Ties. Journal of Travel Research, 53(2), 183–195.

    Article  Google Scholar 

  • Nunnally, J. C. (1967). Psychometric Theory. New York: McGraw-Hill.

    Google Scholar 

  • Pavlovich, K. (2003). The evolution and transformation of a tourism destination network: The Waitomo Caves. New Zealand Tourism Management, 24(2), 203–216.

    Article  Google Scholar 

  • Poon, A. (1993). Tourism, technology, and competitive strategies. Oxon, UK: CAB Publishing.

    Google Scholar 

  • Porter, M. E. (1985). Competitive advantage: Creating and Sustaining Superior Performance. New York: The Free Press.

    Google Scholar 

  • Prebensen, N. K., Vittersø, J., & Dahl, T. I. (2013). Value co-creation significance of tourist resources. Annals of Tourism Research, 42, 240–261.

    Article  Google Scholar 

  • Purves, R., & Hollenstein, L. (2010). Exploring place through user-generated content: Using Flickr to Describe City Cores. Journal of Spatial Information Science(1).

    Google Scholar 

  • Scott, N., Baggio, R., & Cooper, C. (2008). Network Analysis and Tourism: From Theory to Practice. Tonawanda, NY: Channel View Books.

    Google Scholar 

  • Sfandla, C., & Björk, P. (2013). Tourism experience network: Co-Creation of Experiences in Interactive Processes. International Journal of Tourism Research, 15(5), 495–506.

    Article  Google Scholar 

  • Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, translations’ and boundary objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907–39. Social Studies of Science, 19(3), 387–420.

    Article  Google Scholar 

  • Stienmetz, J. L., & Fesenmaier, D. R. (2013). Traveling the network: A Proposal for Destination Performance Metrics. International Journal of Tourism Sciences, 13(2), 57–75.

    Article  Google Scholar 

  • Stienmetz, J. L., & Fesenmaier, D. R. (2015a). Estimating value in baltimore, maryland: An Attractions Network Analysis. Tourism Management, 50, 238–252.

    Article  Google Scholar 

  • Stienmetz, J. L., & Fesenmaier, D. R. (2015b). Measuring intra-regional tourist behavior: Towards modeling visitor expenditure dynamics. Paper Presented at the 4th International Conference on Sub National Measurement and Economic Anlaysis of Tourism, Puerto Rico.

    Google Scholar 

  • Stienmetz, J. L., & Fesenmaier, D. R. (2016). Validating volunteered geographic information: Can we reliably trace visitors’ digital footprints? Paper Presented at the 2016 International Travel and Tourism Research Association Conference. Colorado: Vail.

    Google Scholar 

  • Tax, S. S., McCutcheon, D., & Wilkinson, I. F. (2013). The service delivery network (Sdn): A Customer-Centric Perspective of the Customer Journey. Journal of Service Research, 16(4), 454–470.

    Article  Google Scholar 

  • Tham, A. (2015). From tourism supply chains to tourism value ecology. Journal of New Business Ideas & Trends, 13(1), 47–65.

    Google Scholar 

  • Uysal, M., Fesenmaier, D. R., & O’Leary, J. T. (1994). Geographic and seasonal variation in the concentration of travel in the United States. Journal of Travel Research, 32(3), 61–64.

    Article  Google Scholar 

  • Van Wijk, R., Jansen, J. J. P., & Lyles, M. A. (2008). Inter—and intra-organizational knowledge transfer: A Meta-Analytic Review and Assessment of Its Antecedents and Consequences. Journal of Management Studies, 45(4), 830–853.

    Article  Google Scholar 

  • Vrotsou, K., Andrienko, N., Andrienko, G., & Jankowski, P. (2011). Exploring city structure from georeferenced photos using graph centrality measures. In D. Gunopulos, T. Hofmann, D. Malerba, & M. Vazirgiannis (Eds.), Machine learning and knowledge discovery in databases. Berlin/Heidelberg: Springer.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and Applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT press.

    Google Scholar 

  • Yabuta, M., & Scott, N. (2011). Dynamic property of a tourism destination network. Tourism Analysis, 16(4), 493–498.

    Article  Google Scholar 

  • Zach, F., & Gretzel, U. (2011). Tourist-activated networks: Implications for dynamic bundling and en route recommendations. Information Technology & Tourism, 13(3), 229–238.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jason L. Stienmetz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Stienmetz, J.L., Fesenmaier, D.R. (2017). Structural Implications of Destination Value System Networks. In: Schegg, R., Stangl, B. (eds) Information and Communication Technologies in Tourism 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-51168-9_12

Download citation

Publish with us

Policies and ethics