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Articles

The influence of the internet on catering and accommodation industry efficiency

, , , &
Pages 949-970 | Received 12 Oct 2020, Accepted 29 Jun 2021, Published online: 02 Aug 2021

References

  • Ang, S., Chen, M., & Yang, F. (2018). Group cross-efficiency evaluation in data envelopment analysis: An application to Taiwan hotels. Computers & Industrial Engineering, 125, 190–199. https://doi.org/10.1016/j.cie.2018.08.028
  • Ashrafi, A., Seow, H. V., Lee, L. S., & Lee, C. G. (2013). The efficiency of the hotel industry in Singapore. Tourism Management, 37, 31–34. https://doi.org/10.1016/j.tourman.2012.12.003
  • Bánáti, D., & Lakner, Z. (2012). Managerial attitudes, acceptance and efficiency of HACCP systems in Hungarian catering. Food Control., 25(2), 484–492. https://doi.org/10.1016/j.foodcont.2011.10.054
  • 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
  • Barros, C. P., Managi, S., & Matousek, R. (2012). The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output. Omega, 40(1), 1–8. https://doi.org/10.1016/j.omega.2011.02.005
  • Bogetoft, P., Christensen, D. L., Damgård, I., Geisler, M., Jakobsen, T. P., Krøigaard, M., & Schwartzbach, M. I. (2008). Multiparty computation goes live. IACR Cryptology ePrint Archive, 68
  • Chaabouni, S. (2019). China’s regional tourism efficiency: A two-stage double bootstrap data envelopment analysis. Journal of Destination Marketing & Management, 11, 183–191. https://doi.org/10.1016/j.jdmm.2017.09.002
  • Chang, H., Choy, H. L., Cooper, W. W., & Ruefli, T. W. (2009). Using Malmquist indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes. Omega, 37(5), 951–960. https://doi.org/10.1016/j.omega.2008.08.004
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Chen, C.-M. (2009). A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks. European Journal of Operational Research, 194(3), 687–699. https://doi.org/10.1016/j.ejor.2007.12.025
  • Chiu, C.-R., Liou, J.-L., Wu, P.-I., & Fang, C.-L. (2012). Decomposition of the environmental inefficiency of the meta-frontier with undesirable output. Energy Economics, 34(5), 1392–1399. https://doi.org/10.1016/j.eneco.2012.06.003
  • Chung, Y. H., Färe, R., & Grosskopf, S. (1997). Productivity and undesirable outputs: A directional distance function approach. Journal of Environmental Management, 51(3), 229–240. https://doi.org/10.1006/jema.1997.0146
  • Färe, R., & Grosskopf, S. (1996). Productivity and intermediate products: A frontier approach. Economics Letters, 50(1), 65–70. https://doi.org/10.1016/0165-1765(95)00729-6
  • Färe, R., & Grosskopf, S. (2010). Directional distance functions and slacks-based measures of efficiency. European Journal of Operational Research, 200(1), 320–322. https://doi.org/10.1016/j.ejor.2009.01.031
  • Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84(1), 66–83.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253–281. https://doi.org/10.2307/2343100
  • Fusi, A., Guidetti, R., & Azapagic, A. (2016). Evaluation of environmental impacts in the catering industry: the case of pasta. Journal of Cleaner Production, 132, 146–160. https://doi.org/10.1016/j.jclepro.2015.07.074
  • Hu, J. H., & Wang, S. C. (2006). Total-factor energy efficiency of regions in China. Energy Policy, 34(17), 3206–3217. https://doi.org/10.1016/j.enpol.2005.06.015
  • Huang, C. (2018). Assessing the performance of tourism supply chains by using the hybrid network data envelopment analysis model. Tourism Management, 65, 303–316. https://doi.org/10.1016/j.tourman.2017.10.013
  • Huang, C., Ho, F. N., & Chiu, Y. (2014). Measurement of tourist hotels׳ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan. Omega-International Journal of Management Science, 48, 49–59. https://doi.org/10.1016/j.omega.2014.02.005
  • Huang, Y., Mesak, H. I., Hsu, M. K., & Qu, H. (2012). Dynamic efficiency assessment of the Chinese hotel industry. Journal of Business Research, 65(1), 59–67. https://doi.org/10.1016/j.jbusres.2011.07.015
  • Kao, C. (2008). Network data envelopment analysis: current development and future research. In Asia-Pacific Productivity Conference (APPC) (pp. 10–15).
  • Labanauskaitė, D., Fiore, M., & Stašys, R. (2020). Use of E-marketing tools as communication management in the tourism industry. Tourism Management Perspectives, 34, 100652. https://doi.org/10.1016/j.tmp.2020.100652
  • Lado-Sestayo, R., & Fernández-Castro, Á. S. (2019). The impact of tourist destination on hotel efficiency: A data envelopment analysis approach. European Journal of Operational Research, 272(2), 674–686. https://doi.org/10.1016/j.ejor.2018.06.043
  • Li, K. X., Jin, M., & Shi, W. (2018). Tourism as an important impetus to promoting economic growth: A critical review. Tourism Management Perspectives, 26, 135–142. https://doi.org/10.1016/j.tmp.2017.10.002
  • Luenberger, D. G. (1992). Benefit functions and duality. Journal of Mathematical Economics, 21(5), 461–481. https://doi.org/10.1016/0304-4068(92)90035-6
  • Mariani, M. M., & Visani, F. (2019). Embedding eWOM into efficiency DEA modelling: An application to the hospitality industry. International Journal of Hospitality Management, 80, 1–12. https://doi.org/10.1016/j.ijhm.2019.01.002
  • Matias, J. C., de, O., Fonseca, J. M. J., Barata, I. G., & Brojo, F. M. R. P. (2013). HACCP and OHS: Can each one help improve the other in the catering industry? Food Control., 30(1), 240–250. https://doi.org/10.1016/j.foodcont.2012.06.030
  • Mudie, S., & Vadhati, M. (2017). Low energy catering strategy: insights from a novel carbon-energy calculator. Energy Procedia., 123, 212–219. https://doi.org/10.1016/j.egypro.2017.07.244
  • Nemoto, J., & Goto, M. (1999). Dynamic Data Envelopment Analysis: Modeling Intertemporal Behavior of a Frim in the Presence of Productive Inefficiencies. Economics Letters, 64(1), 51–56. https://doi.org/10.1016/S0165-1765(99)00070-1
  • Nemoto, J., & Goto, M. (2003). Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis. Journal of Productivity Analysis, 19(2/3), 191–210. https://doi.org/10.1023/A:1022805500570
  • Oneţiu, A. N., & Predonu, A.-M. (2013). Economic and Social Efficiency of Tourism. Procedia - Social and Behavioral Sciences, 92, 648–651. https://doi.org/10.1016/j.sbspro.2013.08.732
  • Sellers-Rubio, R., & Casado-Díaz, A. B. (2018). Analyzing hotel efficiency from a regional perspective: The role of environmental determinants. International Journal of Hospitality Management, 75, 75–85. https://doi.org/10.1016/j.ijhm.2018.03.015
  • Shephard, R. W. (1970). Theory of cost and production functions. Princeton University Press.
  • Song, M., & Li, H. (2019). Estimating the efficiency of a sustainable Chinese tourism industry using bootstrap technology rectification. Technological Forecasting and Social Change, 143, 45–54. https://doi.org/10.1016/j.techfore.2019.03.008
  • Sun, Y. Y. (2016). Decomposition of tourism greenhouse gas emissions: Revealing the dynamics between tourism economic growth, technological efficiency, and carbon emissions. Tourism Management, 55, 326–336. https://doi.org/10.1016/j.tourman.2016.02.014
  • The Ministry of Culture and Tourism. (2021). Tourism report in 2020. Available from: http://zwgk.mct.gov.cn/zfxxgkml/tjxx/202102/t20210218_921658.html
  • 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
  • Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145–156. https://doi.org/10.1016/j.omega.2009.07.003
  • Wang, Y. S., Tseng, T. H., Wang, W. T., Shih, Y. W., & Chan, P. Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002
  • Yang, Y., Park, S., & Hu, X. (2018). Electronic word of mouth and hotel performance: A meta-analysis. Tourism Management, 67, 248–260. https://doi.org/10.1016/j.tourman.2018.01.015
  • Yang, Z., Xia, L., & Cheng, Z. (2017). Performance of Chinese hotel segment markets: Efficiencies measure based on both endogenous and exogenous factors. Journal of Hospitality and Tourism Management, 32, 12–23. https://doi.org/10.1016/j.jhtm.2017.04.007
  • Zhang, G., & Lin, B. (2018). Impact of structure on unified efficiency for Chinese service industry—A two-stage analysis. Applied Energy, 231, 876–886. https://doi.org/10.1016/j.apenergy.2018.09.033
  • Zhang, N., & Choi, Y. (2013). Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis. Energy Economics, 40, 549–559. https://doi.org/10.1016/j.eneco.2013.08.012
  • Zhao, C. Q. (2011). On the theory of scientific management and the development of Chongqing’s catering chain industry. Procedia Engineering, 15, 5420–5424.
  • Zhou, P., Ang, B. W., & Wang, H. (2012). Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach. European Journal of Operational Research, 221(3), 625–635. https://doi.org/10.1016/j.ejor.2012.04.022