Benchmarking bed and breakfast industry in a sharing economy: a frontier-based technology forecasting approach

References

• Ahikiriza, E., Van Meensel, J., Gellynck, X., & Lauwers, L. (2021). Heterogeneity in frontier analysis: Does it matter for benchmarking farms? Journal of Productivity Analysis, 56(2–3), 69–84. https://doi.org/10.1007/s11123-021-00608-x
   Web of Science ®Google Scholar
• An, Q., Tao, X., & Xiong, B. (2021). Benchmarking with data envelopment analysis: An agency perspective. Omega, 101, 102235. https://doi.org/10.1016/j.omega.2020.102235
   Web of Science ®Google Scholar
• Aparicio, J., Ruiz, J. L., & Sirvent, I. (2007). Closest targets and minimum distance to the Pareto-efficient frontier in DEA. Journal of Productivity Analysis, 28(3), 209–218. https://doi.org/10.1007/s11123-007-0039-5
   Web of Science ®Google Scholar
• Assaf, A. G., & Barros, C. (2011). Performance analysis of the Gulf hotel industry: A Malmquist index with bias correction. International Journal of Hospitality Management, 30(4), 819–826. https://doi.org/10.1016/j.ijhm.2011.01.002
   Web of Science ®Google Scholar
• Assaf, A. G., & Magnini, V. (2012). Accounting for customer satisfaction in measuring hotel efficiency: Evidence from the US hotel industry. International Journal of Hospitality Management, 31(3), 642–647. https://doi.org/10.1016/j.ijhm.2011.08.008
   Web of Science ®Google Scholar
• Assaf, A. G., & Tsionas, M. (2018). The estimation and decomposition of tourism productivity. Tourism Management, 65, 131–142. https://doi.org/10.1016/j.tourman.2017.09.004
   Web of Science ®Google Scholar
• Assaf, A. G., Deery, M., & Jago, L. (2011). Evaluating the performance and scale characteristics of the Australian restaurant industry. Journal of Hospitality & Tourism Research, 35(4), 419–436. https://doi.org/10.1177/1096348010380598
   Web of Science ®Google Scholar
• Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
   Web of Science ®Google Scholar
• Barros, C. P. (2005). Measuring efficiency in the hotel sector. Annals of Tourism Research, 32(2), 456–477. https://doi.org/10.1016/j.annals.2004.07.011
   Web of Science ®Google Scholar
• Bell, R. A., & Morey, R. C. (1995). Increasing the efficiency of corporate travel management through macro benchmarking. Journal of Travel Research, 33(3), 11–20. https://doi.org/10.1177/004728759503300303
   Google Scholar
• Bernini, C., & Guizzardi, A. (2010). Internal and locational factors affecting hotel industry efficiency: Evidence from Italian business corporations. Tourism Economics, 16(4), 883–913. https://doi.org/10.5367/te.2010.0008
   Web of Science ®Google Scholar
• Bogetoft, P. (2013). Performance benchmarking: Measuring and managing performance. Springer Science & Business Media.
   Google Scholar
• Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50(6), 1393–1414. https://doi.org/10.2307/1913388
   Web of Science ®Google Scholar
• Charnes, A., Cooper, W. W., & Rhodes, E. (1979). Measuring the efficiency of decision-making units. European Journal of Operational Research, 3(4), 339–338. https://doi.org/10.1016/0377-2217(79)90229-7
   Web of Science ®Google Scholar
• Chen, L., & Ray, S. C. (2013). Cost efficiency and scale economies in general dental practices in the US: A non-parametric and parametric analysis of Colorado data. Journal of the Operational Research Society, 64(5), 762–774. https://doi.org/10.1057/jors.2011.109
   Web of Science ®Google Scholar
• Chen, L. C., Lin, S. P., & Kuo, C. M. (2013). Rural tourism: Marketing strategies for the bed and breakfast industry in Taiwan. International Journal of Hospitality Management, 32, 278–286. https://doi.org/10.1016/j.ijhm.2012.07.005
   Web of Science ®Google Scholar
• Chen, T. Y. (2002). A comparison of chance-constrained DEA and stochastic frontier analysis: Bank efficiency in Taiwan. Journal of the Operational Research Society, 53(5), 492–500. https://doi.org/10.1057/palgrave.jors.2601318
   Web of Science ®Google Scholar
• Chiu, C. N. (2018). How can managerial efficiency be improved? Evidence from the bed and breakfast industry. Tourism Management Perspectives, 27, 111–124. https://doi.org/10.1016/j.tmp.2018.06.002
   Web of Science ®Google Scholar
• Chiu, C. N. (2019). Taiwanese bed and breakfast business performance: A geographic region perspective. Growth and Change, 50(3), 1102–1114. https://doi.org/10.1111/grow.12313
   Web of Science ®Google Scholar
• Cook, W. D., Ruiz, J. L., Sirvent, I., & Zhu, J. (2017). Within-group common benchmarking using DEA. European Journal of Operational Research, 256(3), 901–910. https://doi.org/10.1016/j.ejor.2016.06.074
   Web of Science ®Google Scholar
• Cordeiro, J. J., Sarkis, J., Vazquez-Brust, D., Frater, L., & Dijkshoorn, J. (2012). An evaluation of technical efficiency and managerial correlates of solid waste management by Welsh SMEs using parametric and non-parametric techniques. Journal of the Operational Research Society, 63(5), 653–664. https://doi.org/10.1057/jors.2011.22
   Web of Science ®Google Scholar
• Dwyer, L., & Kim, C. (2003). Destination competitiveness: Determinants and indicators. Current Issues in Tourism, 6(5), 369–414. https://doi.org/10.1080/13683500308667962
   Google Scholar
• Dyson, R. G., & Shale, E. A. (2010). Data envelopment analysis, operational research and uncertainty. Journal of the Operational Research Society, 61(1), 25–34. https://doi.org/10.1057/jors.2009.145
   Web of Science ®Google Scholar
• Fang, B., Ye, Q., & Law, R. (2016). Effect of sharing economy on tourism industry employment. Annals of Tourism Research, 57, 264–267. https://doi.org/10.1016/j.annals.2015.11.018
   Web of Science ®Google Scholar
• Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83.
   Web of Science ®Google Scholar
• Frochot, I. (2005). A benefit segmentation of tourists in rural areas: A Scottish perspective. Tourism Management, 26(3), 335–346. https://doi.org/10.1016/j.tourman.2003.11.016
   Web of Science ®Google Scholar
• Ghahraman, A., & Prior, D. (2016). A learning ladder toward efficiency: Proposing network-based stepwise benchmark selection. Omega, 63, 83–93. https://doi.org/10.1016/j.omega.2015.10.004
   Web of Science ®Google Scholar
• Heo, Y. (2016). Sharing economy and prospects in tourism research. Annals of Tourism Research, 58, 166–170. https://doi.org/10.1016/j.annals.2016.02.002
   Web of Science ®Google Scholar
• Hjalager, A. M. (1996). Agricultural diversification into tourism: Evidence of a European Community development programme. Tourism Management, 17(2), 103–111. https://doi.org/10.1016/0261-5177(95)00113-1
   Web of Science ®Google Scholar
• Hu, J. L., Chiu, C. N., Shieh, H. S., & Huang, C. H. (2010). A stochastic cost efficiency analysis of international tourist hotels in Taiwan. International Journal of Hospitality Management, 29(1), 99–107. https://doi.org/10.1016/j.ijhm.2009.06.005
   Web of Science ®Google Scholar
• Ikkala, T., Lampinen, A. (2015). Monetizing network hospitality: Hospitality and sociability in the context of Airbnb. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 1033–1044).
   Google Scholar
• Jahanshahloo, G. R., Amirteimoori, A. R., & Kordrostami, S. (2004). Multi-component performance, progress and regress measurement and shared inputs and outputs in DEA for panel data: An application in commercial bank branches. Applied Mathematics and Computation, 151(1), 1–16. https://doi.org/10.1016/S0096-3003(03)00318-7
   Web of Science ®Google Scholar
• Kozak, M., & Rimmington, M. (1999). Measuring tourist destination competitiveness: Conceptual considerations and empirical findings. International Journal of Hospitality Management, 18(3), 273–283. https://doi.org/10.1016/S0278-4319(99)00034-1
   Google Scholar
• Lim, D. J., Jahromi, S. R., Anderson, T. R., & Tudorie, A. A. (2015). Comparing technological advancement of hybrid electric vehicles (HEV) in different market segments. Technological Forecasting and Social Change, 97, 140–153. https://doi.org/10.1016/j.techfore.2014.05.008
   Web of Science ®Google Scholar
• Liu, A., & Wu, D. C. (2019). Tourism productivity and economic growth. Annals of Tourism Research, 76, 253–265. https://doi.org/10.1016/j.annals.2019.04.005
   Web of Science ®Google Scholar
• Lynch, P. A. (1994). Demand for training by bed and breakfast operators. International Journal of Contemporary Hospitality Management, 6(4), 25–31. https://doi.org/10.1108/09596119410060892
   Google Scholar
• Milman, A., & Pizam, A. (1995). The role of awareness and familiarity with a destination: The central Florida case. Journal of Travel Research, 33(3), 21–27. https://doi.org/10.1177/004728759503300304
   Google Scholar
• Nuntsu, N., Tassiopoulos, D., & Haydam, N. (2004). The bed and breakfast market of Buffalo City (BC), South Africa: Present status, constraints and success factors. Tourism Management, 25(4), 515–522. https://doi.org/10.1016/S0261-5177(03)00125-0
   Web of Science ®Google Scholar
• Nurmatov, R., Lopez, X. L. F., & Millan, P. P. C. (2021). Tourism, hospitality, and DEA: Where do we come from and where do we go? International Journal of Hospitality Management, 95, 102883. https://doi.org/10.1016/j.ijhm.2021.102883
   Web of Science ®Google Scholar
• O’Donnell, C. J., Rao, D. P., & Battese, G. E. (2008). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics, 34(2), 231–255. https://doi.org/10.1007/s00181-007-0119-4
   Web of Science ®Google Scholar
• Özer, B. (1996). An investment analysis model for small hospitality operations. International Journal of Contemporary Hospitality Management, 8(5), 20–24. https://doi.org/10.1108/09596119610126112
   Google Scholar
• Pastor, J. T., & Lovell, C. K. (2005). A global Malmquist productivity index. Economics Letters, 88(2), 266–271. https://doi.org/10.1016/j.econlet.2005.02.013
   Web of Science ®Google Scholar
• Peng, H., Zhang, J., Zhong, S., & Li, P. (2021). Corporate governance, technical efficiency and financial performance: Evidence from Chinese listed tourism firms. Journal of Hospitality and Tourism Management, 48, 163–173. https://doi.org/10.1016/j.jhtm.2021.06.005
   Web of Science ®Google Scholar
• Pérez-Granja, U., & Inchausti-Sintes, F. (2023). On the analysis of efficiency in the hotel sector: Does tourism specialization matter? Tourism Economics, 29(1), 92–115. https://doi.org/10.1177/13548166211039301
   Web of Science ®Google Scholar
• Pham, T. D. (2020). Tourism productivity theory and measurement for policy implications: The case of Australia. Journal of Travel Research, 59(2), 247–266. https://doi.org/10.1177/0047287519835972
   Web of Science ®Google Scholar
• Piot-Lepetit, I., Perrigot, R., & Cliquet, G. (2014). Impact of the industry on franchise chain efficiency: A meta-DEA and context-dependent DEA approach. Journal of the Operational Research Society, 65(11), 1692–1699. https://doi.org/10.1057/jors.2013.140
   Web of Science ®Google Scholar
• Puschmann, T., & Alt, R. (2016). Sharing economy. Business & Information Systems Engineering, 58(1), 93–99. https://doi.org/10.1007/s12599-015-0420-2
   Web of Science ®Google Scholar
• Ruan, W., Li, Y., Zhang, S., & Liu, C. H. (2019). Evaluation and drive mechanism of tourism ecological security based on the DPSIR-DEA model. Tourism Management, 75, 609–625. https://doi.org/10.1016/j.tourman.2019.06.021
   Web of Science ®Google Scholar
• Ruiz, J. L., & Sirvent, I. (2019). Performance evaluation through DEA benchmarking adjusted to goals. Omega, 87, 150–157. https://doi.org/10.1016/j.omega.2018.08.014
   Web of Science ®Google Scholar
• Sharpley, R. (2002). Rural tourism and the challenge of tourism diversification: The case of Cyprus. Tourism Management, 23(3), 233–244. https://doi.org/10.1016/S0261-5177(01)00078-4
   Web of Science ®Google Scholar
• Sigala, M., Airey, D., Jones, P., & Lockwood, A. (2004). ICT paradox lost? A stepwise DEA methodology to evaluate technology investments in tourism settings. Journal of Travel Research, 43(2), 180–192. https://doi.org/10.1177/0047287504268247
   Google Scholar
• Stringer, P. F. (1981). Hosts and guests the bed-and-breakfast phenomenon. Annals of Tourism Research, 8(3), 357–376. https://doi.org/10.1016/0160-7383(81)90004-9
   Google Scholar
• Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5
   Web of Science ®Google Scholar
• Tulkens, H., & Eeckaut, P. V. (1995). Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects. European Journal of Operational Research, 80(3), 474–499. https://doi.org/10.1016/0377-2217(94)00132-V
   Web of Science ®Google Scholar
• Tussyadiah, I. P. (2016). Factors of satisfaction and intention to use peer-to-peer accommodation. International Journal of Hospitality Management, 55, 70–80. https://doi.org/10.1016/j.ijhm.2016.03.005
   Web of Science ®Google Scholar
• Vaninsky, A. (2006). Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis. Energy Economics, 28(3), 326–338. https://doi.org/10.1016/j.eneco.2006.02.007
   Web of Science ®Google Scholar
• Vojtko, V., Štumpf, P., Rašovská, I., McGrath, R., & Ryglová, K. (2022). Removing uncontrollable factors in benchmarking tourism destination satisfaction. Journal of Travel Research, 61(1), 136–149. https://doi.org/10.1177/0047287520971047
   Web of Science ®Google Scholar
• Walheer, B. (2023). Meta-frontier and technology switchers: A nonparametric approach. European Journal of Operational Research, 305(1), 463–474. https://doi.org/10.1016/j.ejor.2022.05.038
   Web of Science ®Google Scholar
• Wu, J., Cheng, X., & Liao, S. S. (2020). Tourism forecast combination using the stochastic frontier analysis technique. Tourism Economics, 26(7), 1086–1107. https://doi.org/10.1177/1354816619868089
   Web of Science ®Google Scholar
• Wu, W. C., & Yang, C. Y. (2010). An empirical study on the impact of differences in bed and breakfast service quality attributes on customers’ revisiting desires. International Journal of Organizational Innovation (Online), 2(4), 223.
   Google Scholar
• Yang, Z., & Soltani, N. (2021). A new SBM-based global Malmquist productivity index and target setting. Computers & Industrial Engineering, 158, 107411. https://doi.org/10.1016/j.cie.2021.107411
   Web of Science ®Google Scholar
• Yu, M. M., & Lee, B. C. (2009). Efficiency and effectiveness of service business: Evidence from international tourist hotels in Taiwan. Tourism Management, 30(4), 571–580. https://doi.org/10.1016/j.tourman.2008.09.005
   Web of Science ®Google Scholar
• Zekan, B., Önder, I., & Gunter, U. (2019). Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities? Tourism Economics, 25(7), 1029–1046. https://doi.org/10.1177/1354816618814349
   Web of Science ®Google Scholar
• Zhang, D., Tu, J., Zhou, L., & Yu, Z. (2020). Higher tourism specialization, better hotel industry efficiency? International Journal of Hospitality Management, 87, 102509. https://doi.org/10.1016/j.ijhm.2020.102509
   PubMed Web of Science ®Google Scholar