Performance evaluation of Taiwanese international tourist hotels: evidence from a modified NDEA model with ICA technique
Abstract
The motivation for this study is to assess the managerial performance in Taiwanese international tourist hotels based on the two-stage NDEA performance mechanism with ICA technique for enhancing the discriminatory power of performance evaluation model. The two-stage managerial performance structure is applied, incorporating the service production and service operation stages, as a reduced form to introduce the relatively complex business environment of modern enterprise. However, we have need to be considerable of dimensionality curse problem in NDEA performance model. A modified NDEA-based evaluation model, therefore, is proposed to integrate the network slacks-based measure (NSBM) with a dimensional reduction technique, the independent component analysis (ICA). The results indicate that the performance of the profit dimension significantly hampers operational performance, and that both regulators and managers must adjust their market orientation business strategy. Moreover, compared with the NSBM model, this modified ICA-NSBM performance model has a high discriminatory ability to measure the relative performance of the selected hotels.
Keyword : Taiwanese international tourist hotels, two-stage NDEA model, independent component analysis, network slacks-based measure, DEA, performance evaluation
How to Cite
Chiu, S.-H., & Lin, T.-Y. (2018). Performance evaluation of Taiwanese international tourist hotels: evidence from a modified NDEA model with ICA technique. Technological and Economic Development of Economy, 24(4), 1560-1580. https://doi.org/10.3846/tede.2018.3116
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Adler, N., & Golany, B. (2001). Evaluation of deregulation airline networks using data envelopment analysis combined with principle component analysis with an application to Western Europe. European Journal of Operational Research, 132(6), 18-31.
Adler, N., & Golany, B. (2002). Including principle component weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 53(9), 985-991. https://doi.org/10.1057/palgrave.jors.2601400
Adler, N., & Yazhemsky, E. (2010). Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction. European Journal of Operational Research, 202(1), 273-284. https://doi.org/10.1016/j.ejor.2009.03.050
Afsharinia, A., Bagherpour, M., & Farahmand, K. (2013). Efficiency measurement of clinical units using integrated independent component analysis-DEA model under Fuzzy conditions. International Journal of Hospital Research, 2(3), 109-118.
Assaf, A., & 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
Avkiran, N. K. (2009). Opening the black box of efficiency analysis: an illustration with UAE banks. Omega-International Journal of Management Science, 37(4), 930-941. https://doi.org/10.1016/j.omega.2008.08.001
Back, A. D., & Weigend, A. S. (1997). A first application of independent component analysis to extracting structure from stock returns. International Journal of Neural Systems, 8(4): 473-484. https://doi.org/10.1142/S0129065797000458
Ban, O. I., Tara, I. G., Bogdan, V., Tuşe, D., & Bologa, S. G. (2016). Evaluation of hotel quality attribute importance through fuzzy correlation coefficient. Technological and Economic Development of Economy, 22(4), 471-492. https://doi.org/10.3846/20294913.2016.1144657
Barros, C. P., Managi, S., & Matousek, R. (2012). The technical efficiency of the Japanese banks: nonradial directional performance measurement with undesirable output. Omega-International Journal of Management Science, 40(1), 1-8. https://doi.org/10.1016/j.omega.2011.02.005
Bian, Y. (2012). A Gram-Schmidt process based approach for improving DEA discrimination in the presence of large dimensionality of data set. Expert Systems with Applications, 39(3), 3793-3799. https://doi.org/10.1016/j.eswa.2011.09.080
Castelli, L., Pesenti, R., & Ukovich, W. (2010). A classification of DEA models when the international structure of the Decision Making Units in considered. Annals of Operations Research, 173(1), 207-235. https://doi.org/10.1007/s10479-008-0414-2
Chen, T. H. (2009). Performance measurement of an enterprise and business units with an application to a Taiwanese hotel chain. International Journal of Hospitality Management, 28(3), 415-422. https://doi.org/10.1016/j.ijhm.2008.10.010
Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Science, 34(1), 35-49. https://doi.org/10.1016/S0038-0121(99)00012-9
Galagedera, D. U. A., Watson, J., Premachandra, I. M., & Chen, Y. (2016). Modelling leakage in twostage DEA models: an application to US mutual fund families. Omega-International Journal of Management Science, 61, 62-77. https://doi.org/10.1016/j.omega.2015.07.007
García-Ferrer, A., González-Prieto, E., & Peña, D. (2012). A conditionally heteroskedastic independent factor model with an application to financial stock returns. International Journal of Forecasting, 28(1), 70-93. https://doi.org/10.1016/j.ijforecast.2011.02.010
Hadad, Y., Friedman, L., & Israeli, A. A. (2005). Evaluating hotel advertisements efficiency using data envelopment analysis. Journal of Business Economics and Management, 6(3), 145-153.
Hsieh, L. F., & Lin, L. H. (2010). A performance evaluation model for international tourist hotels in Taiwan – an application of the rational network DEA. International Journal of Hospitality Management, 29(1), 14-24. https://doi.org/10.1016/j.ijhm.2009.04.004
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
Huang, C. W. (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. W., Ho, F. N., & Chiu, Y. H. (2014). Measurement of tourist hotels’ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan. Omega-The International Journal of Management Science, 48, 49-59. https://doi.org/10.1016/j.omega.2014.02.005
Hwang, S. N., & Chang, T. Y. (2003). Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan. Tourism Management, 24(4), 357-369. https://doi.org/10.1016/S0261-5177(02)00112-7
Hyvärinen, A., Karhunen, J., & Oja, E. (2001). Independent component analysis. New York: John Wiley & Sons. https://doi.org/10.1002/0471221317
Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4-5), 411-430. https://doi.org/10.1016/S0893-6080(00)00026-5
Jenkins, L., & Anderson, M. (2003). A multivariate statistical approach to reducing the number of variables in data envelopment analysis. European Journal of Operational Research, 147(1), 51-61. https://doi.org/10.1016/S0377-2217(02)00243-6
Kao, H. Y., Wu, D. J., & Huang, C. H. (2017). Evaluation of cloud service industry with dynamic and network DEA models. Applied Mathematics and Computation, 315, 188-202. https://doi.org/10.1016/j.amc.2017.07.059
Kao, L. J., Lu, C. J., & Chiu, C. C. (2011). Efficiency measurement using independent component analysis and data envelopment analysis. European Journal of Operational Research, 210(2), 310-317. https://doi.org/10.1016/j.ejor.2010.09.016
Lewis, H. F., & Sexton, T. R. (2004). Network DEA: efficiency analysis of organizations with complex internal structure. Computers & Operations Research, 31(9), 1365-1410. https://doi.org/10.1016/S0305-0548(03)00095-9
Liang, L., Li, Y., & Li, S. (2009). Increasing the discriminatory power of DEA in the presence of the undesirable outputs and large dimensionality of data sets with PCA. Expert Systems with Applications, 36(3), 5895-5899. https://doi.org/10.1016/j.eswa.2008.07.022
Lin, T. Y., & Chiu, S. H. (2013). Using independent component analysis and network DEA to improve bank performance evaluation. Economic Modelling, 32(5), 608-616. https://doi.org/10.1016/j.econmod.2013.03.003
Mahlberg, B., & Sahoo, B. K. (2011). Radial and non-radial decomposition of Luenberger productivity indicator with an illustrative application. International Journal of Production Economics, 131(2), 721-726. https://doi.org/10.1016/j.ijpe.2011.02.021
Marchetti, D., & Wanke, P. (2017). Brazil’s rail freight transport: efficiency analysis using two-stage DEA and cluster-driven public policies. Socio-Economic Planning Sciences, 59, 26-42. https://doi.org/10.1016/j.seps.2016.10.005
Nataraja, N. R., & Johnson, A. L. (2011). Guidelines for using variable selection techniques in data envelopment analysis. European Journal of Operational Research, 215(3), 662-669. https://doi.org/10.1016/j.ejor.2011.06.045
National Development Council (NDC). (2016). Taiwan macro-economic insight 2016. Retrieved from http://www.ey.gov.tw/state/News_Content3.aspx?n=3F00F60B9FC304D7&s=2FE35E5B857F7A92
Oukil, A., Channouf, N., & AL-Zaidi, A. (2016). Performance evaluation of the hotel industry in an emerging tourism destination: the case of Oman. Journal of Hospitality and Tourism Management, 29, 60-68. https://doi.org/10.1016/j.jhtm.2016.05.003
Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management Science, 45(9), 1270-1288. https://doi.org/10.1287/mnsc.45.9.1270
Taiwan Tourism Bureau. (2017). Tourism Statistics Database. Retrieved from http://admin.taiwan.net.tw/statistics/year_en.aspx?no=15
Tone, K., & Tsutsui, M. (2009). Network DEA: a slacks-based measure approach. European Journal of Operational Research, 197(1), 243-252. https://doi.org/10.1016/j.ejor.2008.05.027
Vaz, C. B., Camanho, A. S., & Guimarães, R. C. (2010). The assessment of retailing efficiency using network data envelopment analysis. Annals of Operations Research, 173(1), 5-24. https://doi.org/10.1007/s10479-008-0397-z
Xu, X., & Cui. Q. (2017). Evaluating airline energy efficiency: an integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure. Energy, 122, 274-286. https://doi.org/10.1016/j.energy.2017.01.100
Yang, C., & Liu, H. M. (2012). Managerial efficiency in Taiwan bank branches: a network DEA. Economic Modelling, 29(2), 450-461. https://doi.org/10.1016/j.econmod.2011.12.004
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
Yu, M. M. (2010). Assessment of airport performance using the SBM-NDEA model. Omega-International Journal of Management Science, 38(6), 440-452. https://doi.org/10.1016/j.omega.2009.11.003
Yu, M. M., & Lee, C. Y. (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
Yu, M. M., & Lin, T. J. (2008). Efficiency and effectiveness in railway performance using a multi-activity network DEA model. Omega-International Journal of Management Science, 36(6), 1005-1017. https://doi.org/10.1016/j.omega.2007.06.003
Zha, Y., Liang, N., Wu, M., & Bian, Y. (2016). Efficiency evaluation of banks in China: a dynamic twostage slacks-based measure approach. Omega-The International Journal of Management Science, 60, 60-72. https://doi.org/10.1016/j.omega.2014.12.008
Zhang, G. P. (2001). An investigation of neural networks for linear time-series forecasting. Computers & Operations Research, 28(12), 1183-1202. https://doi.org/10.1016/S0305-0548(00)00033-2
Adler, N., & Golany, B. (2002). Including principle component weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 53(9), 985-991. https://doi.org/10.1057/palgrave.jors.2601400
Adler, N., & Yazhemsky, E. (2010). Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction. European Journal of Operational Research, 202(1), 273-284. https://doi.org/10.1016/j.ejor.2009.03.050
Afsharinia, A., Bagherpour, M., & Farahmand, K. (2013). Efficiency measurement of clinical units using integrated independent component analysis-DEA model under Fuzzy conditions. International Journal of Hospital Research, 2(3), 109-118.
Assaf, A., & 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
Avkiran, N. K. (2009). Opening the black box of efficiency analysis: an illustration with UAE banks. Omega-International Journal of Management Science, 37(4), 930-941. https://doi.org/10.1016/j.omega.2008.08.001
Back, A. D., & Weigend, A. S. (1997). A first application of independent component analysis to extracting structure from stock returns. International Journal of Neural Systems, 8(4): 473-484. https://doi.org/10.1142/S0129065797000458
Ban, O. I., Tara, I. G., Bogdan, V., Tuşe, D., & Bologa, S. G. (2016). Evaluation of hotel quality attribute importance through fuzzy correlation coefficient. Technological and Economic Development of Economy, 22(4), 471-492. https://doi.org/10.3846/20294913.2016.1144657
Barros, C. P., Managi, S., & Matousek, R. (2012). The technical efficiency of the Japanese banks: nonradial directional performance measurement with undesirable output. Omega-International Journal of Management Science, 40(1), 1-8. https://doi.org/10.1016/j.omega.2011.02.005
Bian, Y. (2012). A Gram-Schmidt process based approach for improving DEA discrimination in the presence of large dimensionality of data set. Expert Systems with Applications, 39(3), 3793-3799. https://doi.org/10.1016/j.eswa.2011.09.080
Castelli, L., Pesenti, R., & Ukovich, W. (2010). A classification of DEA models when the international structure of the Decision Making Units in considered. Annals of Operations Research, 173(1), 207-235. https://doi.org/10.1007/s10479-008-0414-2
Chen, T. H. (2009). Performance measurement of an enterprise and business units with an application to a Taiwanese hotel chain. International Journal of Hospitality Management, 28(3), 415-422. https://doi.org/10.1016/j.ijhm.2008.10.010
Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Science, 34(1), 35-49. https://doi.org/10.1016/S0038-0121(99)00012-9
Galagedera, D. U. A., Watson, J., Premachandra, I. M., & Chen, Y. (2016). Modelling leakage in twostage DEA models: an application to US mutual fund families. Omega-International Journal of Management Science, 61, 62-77. https://doi.org/10.1016/j.omega.2015.07.007
García-Ferrer, A., González-Prieto, E., & Peña, D. (2012). A conditionally heteroskedastic independent factor model with an application to financial stock returns. International Journal of Forecasting, 28(1), 70-93. https://doi.org/10.1016/j.ijforecast.2011.02.010
Hadad, Y., Friedman, L., & Israeli, A. A. (2005). Evaluating hotel advertisements efficiency using data envelopment analysis. Journal of Business Economics and Management, 6(3), 145-153.
Hsieh, L. F., & Lin, L. H. (2010). A performance evaluation model for international tourist hotels in Taiwan – an application of the rational network DEA. International Journal of Hospitality Management, 29(1), 14-24. https://doi.org/10.1016/j.ijhm.2009.04.004
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
Huang, C. W. (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. W., Ho, F. N., & Chiu, Y. H. (2014). Measurement of tourist hotels’ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan. Omega-The International Journal of Management Science, 48, 49-59. https://doi.org/10.1016/j.omega.2014.02.005
Hwang, S. N., & Chang, T. Y. (2003). Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan. Tourism Management, 24(4), 357-369. https://doi.org/10.1016/S0261-5177(02)00112-7
Hyvärinen, A., Karhunen, J., & Oja, E. (2001). Independent component analysis. New York: John Wiley & Sons. https://doi.org/10.1002/0471221317
Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4-5), 411-430. https://doi.org/10.1016/S0893-6080(00)00026-5
Jenkins, L., & Anderson, M. (2003). A multivariate statistical approach to reducing the number of variables in data envelopment analysis. European Journal of Operational Research, 147(1), 51-61. https://doi.org/10.1016/S0377-2217(02)00243-6
Kao, H. Y., Wu, D. J., & Huang, C. H. (2017). Evaluation of cloud service industry with dynamic and network DEA models. Applied Mathematics and Computation, 315, 188-202. https://doi.org/10.1016/j.amc.2017.07.059
Kao, L. J., Lu, C. J., & Chiu, C. C. (2011). Efficiency measurement using independent component analysis and data envelopment analysis. European Journal of Operational Research, 210(2), 310-317. https://doi.org/10.1016/j.ejor.2010.09.016
Lewis, H. F., & Sexton, T. R. (2004). Network DEA: efficiency analysis of organizations with complex internal structure. Computers & Operations Research, 31(9), 1365-1410. https://doi.org/10.1016/S0305-0548(03)00095-9
Liang, L., Li, Y., & Li, S. (2009). Increasing the discriminatory power of DEA in the presence of the undesirable outputs and large dimensionality of data sets with PCA. Expert Systems with Applications, 36(3), 5895-5899. https://doi.org/10.1016/j.eswa.2008.07.022
Lin, T. Y., & Chiu, S. H. (2013). Using independent component analysis and network DEA to improve bank performance evaluation. Economic Modelling, 32(5), 608-616. https://doi.org/10.1016/j.econmod.2013.03.003
Mahlberg, B., & Sahoo, B. K. (2011). Radial and non-radial decomposition of Luenberger productivity indicator with an illustrative application. International Journal of Production Economics, 131(2), 721-726. https://doi.org/10.1016/j.ijpe.2011.02.021
Marchetti, D., & Wanke, P. (2017). Brazil’s rail freight transport: efficiency analysis using two-stage DEA and cluster-driven public policies. Socio-Economic Planning Sciences, 59, 26-42. https://doi.org/10.1016/j.seps.2016.10.005
Nataraja, N. R., & Johnson, A. L. (2011). Guidelines for using variable selection techniques in data envelopment analysis. European Journal of Operational Research, 215(3), 662-669. https://doi.org/10.1016/j.ejor.2011.06.045
National Development Council (NDC). (2016). Taiwan macro-economic insight 2016. Retrieved from http://www.ey.gov.tw/state/News_Content3.aspx?n=3F00F60B9FC304D7&s=2FE35E5B857F7A92
Oukil, A., Channouf, N., & AL-Zaidi, A. (2016). Performance evaluation of the hotel industry in an emerging tourism destination: the case of Oman. Journal of Hospitality and Tourism Management, 29, 60-68. https://doi.org/10.1016/j.jhtm.2016.05.003
Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management Science, 45(9), 1270-1288. https://doi.org/10.1287/mnsc.45.9.1270
Taiwan Tourism Bureau. (2017). Tourism Statistics Database. Retrieved from http://admin.taiwan.net.tw/statistics/year_en.aspx?no=15
Tone, K., & Tsutsui, M. (2009). Network DEA: a slacks-based measure approach. European Journal of Operational Research, 197(1), 243-252. https://doi.org/10.1016/j.ejor.2008.05.027
Vaz, C. B., Camanho, A. S., & Guimarães, R. C. (2010). The assessment of retailing efficiency using network data envelopment analysis. Annals of Operations Research, 173(1), 5-24. https://doi.org/10.1007/s10479-008-0397-z
Xu, X., & Cui. Q. (2017). Evaluating airline energy efficiency: an integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure. Energy, 122, 274-286. https://doi.org/10.1016/j.energy.2017.01.100
Yang, C., & Liu, H. M. (2012). Managerial efficiency in Taiwan bank branches: a network DEA. Economic Modelling, 29(2), 450-461. https://doi.org/10.1016/j.econmod.2011.12.004
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
Yu, M. M. (2010). Assessment of airport performance using the SBM-NDEA model. Omega-International Journal of Management Science, 38(6), 440-452. https://doi.org/10.1016/j.omega.2009.11.003
Yu, M. M., & Lee, C. Y. (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
Yu, M. M., & Lin, T. J. (2008). Efficiency and effectiveness in railway performance using a multi-activity network DEA model. Omega-International Journal of Management Science, 36(6), 1005-1017. https://doi.org/10.1016/j.omega.2007.06.003
Zha, Y., Liang, N., Wu, M., & Bian, Y. (2016). Efficiency evaluation of banks in China: a dynamic twostage slacks-based measure approach. Omega-The International Journal of Management Science, 60, 60-72. https://doi.org/10.1016/j.omega.2014.12.008
Zhang, G. P. (2001). An investigation of neural networks for linear time-series forecasting. Computers & Operations Research, 28(12), 1183-1202. https://doi.org/10.1016/S0305-0548(00)00033-2