Systematic Literature Review of Switching Behavior in Service Industry
DOI:
https://doi.org/10.21512/bbr.v13i1.7618Keywords:
Systematic Literature Review, switching behavior, service industryAbstract
Although many studies have focused on consumer behavior, a summary of constructs specialized in switching behavior is unexplored. The research aimed to enlarge an extensive and updated overview of customer switching behavior in the service industry. The Systematic Literature Review (SLR) technique evaluated 35 scientific papers released from 2011 to 2021 to analyze drivers, mediating factors, moderating factors, and outcomes related to customer switching behavior. The results improve the understanding and outcome of the drivers to retain consumers. First, the drivers (independent variables) consist of social factors, firm factors, customer behavior, and cost. Second, mediating factors include switching cost, experiential psychological states, inertia, emotion, and consumer perception. Third, moderating constructs have mooring factors, satisfaction, and inertia. Surprisingly, inertia appears in both mediating and moderating variables. The difference depends on service context. Last, outcomes consist of customers’ responses, low satisfaction, and low loyalty. The research contributes to theoretical and managerial implications for sustainable planning by making an overview of several service models. In addition, it includes the drivers of switching behavior in the service industry. Furthermore, the framework offers possibilities and issues for future research and moves the focus from the conventional service domain to social networking that refers to the online platform.
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References
Al-Mashraie, M., Chung, S. H., & Jeon, H. W. (2020). Customer switching behavior analysis in the telecommunication industry via push-pull-mooring framework: A machine learning approach. Computers and Industrial Engineering, 144(June), 1‒14. https://doi.org/10.1016/j.cie.2020.106476
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184‒206. https://doi.org/10.1177/0092070399272005
Bazi, S., Filieri, R., & Gorton, M. (2020). Customers’ motivation to engage with luxury brands on social media. Journal of Business Research, 112(May), 223‒235. https://doi.org/10.1016/j.jbusres.2020.02.032
Belanche, D., Flavián, M., & Pérez-Rueda, A. (2020). Mobile apps use and WOM in the food delivery sector: The role of planned behavior, perceived security and customer lifestyle compatibility. Sustainability, 12(10), 1‒21. https://doi.org/10.3390/su12104275
Blut, M., Evanschitzky, H., Backhaus, C., Rudd, J., & Marck, M. (2016). Securing business-to-business relationships: The impact of switching costs. Industrial Marketing Management, 52(January), 82‒90. https://doi.org/10.1016/j.indmarman.2015.05.010
Bölen, M. C. (2020). From traditional wristwatch to smartwatch: Understanding the relationship between innovation attributes, switching costs and consumers' switching intention. Technology in Society, 63(November), 1‒11. https://doi.org/10.1016/j.techsoc.2020.101439
Cai, R., Lu, L., & Gursoy, D. (2018). Effect of disruptive customer behaviors on others' overall service experience: An appraisal theory perspective. Tourism Management, 69(December), 330‒344. https://doi.org/10.1016/j.tourman.2018.06.013
Calvo-Porral, C., Faíña-Medín, A., & Nieto-Mengotti, M. (2017). Satisfaction and switching intention in mobile services: Comparing lock-in and free contracts in the Spanish market. Telematics and Informatics, 34(5), 717‒729. https://doi.org/10.1016/j.tele.2016.08.022
Chang, H. H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24(July–August), 50‒67. https://doi.org/10.1016/j.elerap.2017.06.002
Cheng, S., Lee, S. J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 92(March), 198‒215. https://doi.org/10.1016/j.chb.2018.10.035
Chou, S. Y., Shen, G. C., Chiu, H. C., & Chou, Y. T. (2016). Multichannel service providers’ strategy: Understanding customers’ switching and free-riding behavior. Journal of Business Research, 69(6), 2226‒2232. https://doi.org/10.1016/j.jbusres.2015.12.034
Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591‒621. https://doi.org/10.1146/annurev.psych.55.090902.142015
Górska-Warsewicz, H., & Kulykovets, O. (2020). Hotel brand loyalty—A systematic literature review. Sustainability, 12(12), 1‒34. https://doi.org/10.3390/SU12124810
Gryaznov, A. N., Gruzkova, S. U., Sharafiev, E. S., Cheverikina, E. A., Muhametzyanova, L. Y., Kamaleeva, A. R., & Gilmeeva, R. K. (2016). Psycho-pedagogical research of emotional and estimative mental states of students who are prone to addictions. International Journal of Environmental and Science Education, 11(15), 8343‒8349.
Gu, J., Wang, X., & Lu, T. (2020). I like my app but I wanna try yours: Exploring user switching from a learning perspective. Internet Research, 30(2), 611‒630. https://doi.org/10.1108/INTR-07-2018-0310
Gvili, Y., & Levy, S. (2021). Consumer engagement in sharing brand-related information on social commerce: the roles of culture and experience. Journal of Marketing Communications, 27(1), 53‒68. https://doi.org/10.1080/13527266.2019.1633552
Habib, T. (2020). Maxim hingga Anterin, Ini 7 ojek online terbaru pesaing Gojek dan Grab. Retrieved from https://akurat.co/maxim-hingga-anterin-ini-7-ojek-online-terbaru-pesaing-gojek-dan-grab
Hakim, C. (2021). Upaya memperbaiki kembali dunia penerbangan pasca pandemi Covid-19. Retrieved from https://money.kompas.com/read/2021/02/15/051000426/upaya-memperbaiki-kembali-dunia-penerbangan-pasca-pandemi-covid-19?page=all
Hirata, E. (2019). Service characteristics and customer satisfaction in the container liner shipping industry. The Asian Journal of Shipping and Logistics, 35(1), 24‒29. https://doi.org/10.1016/j.ajsl.2019.03.004
Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push–pull–mooring framework. Computers in Human Behavior, 28(5), 1912‒1920. https://doi.org/10.1016/j.chb.2012.05.010
Hsu, J. S. C. (2014). Understanding the role of satisfaction in the formation of perceived switching value. Decision Support Systems, 59(March), 152‒162. https://doi.org/10.1016/j.dss.2013.11.003
Huang, D., Markovitch, D. G., & Ying, Y. (2017). Social learning and network externalities in decision making. European Journal of Marketing, 51(1), 157‒176. https://doi.org/10.1108/EJM-10-2015-0703
Jawa Pos. (2021). Tren belanja online meningkat, jasa pengiriman barang laris manis. Retrieved from https://www.jawapos.com/ekonomi/21/02/2021/tren-belanja-online-meningkat-jasa-pengiriman-barang-laris-manis/
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of Retailing, 76(2), 259‒274. https://doi.org/10.1016/S0022-4359(00)00024-5
Jung, J., Han, H., & Oh, M. (2017). Travelers’ switching behavior in the airline industry from the perspective of the push-pull-mooring framework. Tourism Management, 59(April), 139‒153. https://doi.org/10.1016/j.tourman.2016.07.018
Kamolsook, A., Badir, Y. F., & Frank, B. (2019). Consumers’ switching to disruptive technology products: The roles of comparative economic value and technology type. Technological Forecasting and Social Change, 140(March), 328‒340. https://doi.org/10.1016/j.techfore.2018.12.023
Khalilzadeh, J., Ghahramani, L., & Tabari, S. (2017). From “hypercritics” to “happy campers”: Who complains the most in fine dining restaurants? Journal of Hospitality Marketing & Management, 26(5), 451‒473. https://doi.org/10.1080/19368623.2017.1256802
Koo, B., Yu, J., & Han, H. (2020). The role of loyalty programs in boosting hotel guest loyalty: Impact of switching barriers. International Journal of Hospitality Management, 84(January), 1-10. https://doi.org/10.1016/j.ijhm.2019.102328
Kreibig, S. D., Gendolla, G. H. E., & Scherer, K. R. (2012). Goal relevance and goal conduciveness appraisals lead to differential autonomic reactivity in emotional responding to performance feedback. Biological Psychology, 91(3), 365‒375. https://doi.org/10.1016/j.biopsycho.2012.08.007
Kuo, R. Z. (2020). Why do people switch mobile payment service platforms? An empirical study in Taiwan. Technology in Society, 62(August), 1‒16. https://doi.org/10.1016/j.techsoc.2020.101312
Kuo, Y. W., Hsieh, C. H., & Hung, Y. C. (2021). Non-linear characteristics in switching intention to use a docked bike-sharing system. Transportation, 48, 1459‒1479. https://doi.org/10.1007/s11116-020-10102-2
Li, C. Y., & Ku, Y. C. (2018). The power of a thumbs-up: Will e-commerce switch to social commerce? Information & Management, 55(3), 340‒357. https://doi.org/10.1016/j.im.2017.09.001
Lim, M., & Yang, Y. (2015). Effects of users’ envy and shame on social comparison that occurs on social network services. Computers in Human Behavior, 51, 300‒311. https://doi.org/10.1016/j.chb.2015.05.013
Line, N. D., Hanks, L., & Kim, W. G. (2016). Hedonic adaptation and satiation: Understanding switching behavior in the restaurant industry. International Journal of Hospitality Management, 52(January), 143‒153. https://doi.org/10.1016/j.ijhm.2015.10.005
Lu, L., Cai, R., & King, C. (2020). Building trust through a personal touch: Consumer response to service failure and recovery of home-sharing. Journal of Business Research, 117(September), 99‒111. https://doi.org/10.1016/j.jbusres.2020.05.049
Lunn, P. D., & Lyons, S. (2018). Consumer switching intentions for telecoms services: Evidence from Ireland. Heliyon, 4(5), 1‒32. https://doi.org/10.1016/j.heliyon.2018.e00618
Maier, E. (2016). Supply and demand on crowdlending platforms: Connecting small and medium-sized enterprise borrowers and consumer investors. Journal of Retailing and Consumer Services, 33(November), 143‒153. https://doi.org/10.1016/j.jretconser.2016.08.004
McColl-Kennedy, J. R., Patterson, P. G., Smith, A. K., & Brady, M. K. (2009). Customer rage episodes: Emotions, expressions and behaviors. Journal of Retailing, 85(2), 222‒237. https://doi.org/10.1016/j.jretai.2009.04.002
Merz, M. A., He, Y., & Vargo, S. L. (2009). The evolving brand logic: A service-dominant logic perspective. Journal of the Academy of Marketing Science, 37, 328‒344. https://doi.org/10.1007/s11747-009-0143-3
Mou, J., & Benyoucef, M. (2021). Consumer behavior in social commerce: Results from a meta-analysis. Technological Forecasting and Social Change, 167(June), 1‒13. https://doi.org/10.1016/j.techfore.2021.120734
Myers, D. G. (2010). Social psychology. McGraw-Hill.
Park, J. Y., & Jang, S. C. (2014). Why do customers switch? More satiated or less satisfied. International Journal of Hospitality Management, 37(February), 159‒170. https://doi.org/10.1016/j.ijhm.2013.11.007
Pizzi, G., Scarpi, D., Pichierri, M., & Vannucci, V. (2019). Virtual reality, real reactions?: Comparing consumers’ perceptions and shopping orientation across physical and virtual-reality retail stores. Computers in Human Behavior, 96(July), 1‒12. https://doi.org/10.1016/j.chb.2019.02.008
Pookulangara, S., Hawley, J., & Xiao, G. (2011). Explaining consumers’ channel-switching behavior using the theory of planned behavior. Journal of Retailing and Consumer Services, 18(4), 311‒321. https://doi.org/10.1016/j.jretconser.2011.02.005
Prasad, K. (2016). A conceptual paper on the determinants of consumer buying behaviour. International Journal of Engineering Science and Computing, 6(7), 1820‒1824.
Putri, C. A. (2021). Sektor hotel hingga pariwisata RI masih berdarah-darah. Retrieved from https://www.cnbcindonesia.com/news/20210415122522-4-238093/sektor-hotel-hingga-pariwisata-ri-masih-berdarah-darah
Qiu, H., Ye, B. H., Bai, B., & Wang, W. H. (2015). Do the roles of switching barriers on customer loyalty vary for different types of hotels? International Journal of Hospitality Management, 46(April), 89‒98. https://doi.org/10.1016/j.ijhm.2015.01.015
Singh, R., & Rosengren, S. (2020). Why do online grocery shoppers switch? An empirical investigation of drivers of switching in online grocery. Journal of Retailing and Consumer Services, 53(March), 1‒11. https://doi.org/10.1016/j.jretconser.2019.101962
Steinberg, J. R., Marthey, D., Xie, L., & Boudreaux, M. (2021). Contraceptive method type and satisfaction, confidence in use, and switching intentions. Contraception, 104(2), 176‒182. https://doi.org/10.1016/j.contraception.2021.02.010
Stephanie, C. (2020). Transaksi di aplikasi Gojek diklaim tumbuh 10 persen selama pandemi. Retrieved from https://tekno.kompas.com/read/2020/11/12/20000007/transaksi-di-aplikasi-gojek-diklaim-tumbuh-10-persen-selama-pandemi
Sun, J. (2014). How risky are services? An empirical investigation on the antecedents and consequences of perceived risk for hotel service. International Journal of Hospitality Management, 37(February), 171‒179. https://doi.org/10.1016/j.ijhm.2013.11.008
Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users’ switching behavior of mobile instant messaging applications: An empirical study from the perspective of push-pull-mooring framework. Computers in Human Behavior, 75(October), 727‒738. https://doi.org/10.1016/j.chb.2017.06.014
Tang, Z., & Chen, L. (2020). An empirical study of brand microblog users’ unfollowing motivations: The perspective of push-pull-mooring model. International Journal of Information Management, 52(June), 1‒11. https://doi.org/10.1016/j.ijinfomgt.2020.102066
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186‒204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425‒478. https://doi.org/10.2307/30036540
Verhagen, T., Nauta, A., & Felberg, F. (2013). Negative online word-of-mouth: Behavioral indicator or emotional release? Computers in Human Behavior, 29(4), 1430‒1440. https://doi.org/10.1016/j.chb.2013.01.043
Wang, L., Luo, X., Yang, X., & Qiao, Z. (2019). Easy come or easy go? Empirical evidence on switching behaviors in mobile payment applications. Information & Management, 56(7), 1‒13. https://doi.org/10.1016/j.im.2019.02.005
Wu, H. C., Ai, C. H., & Cheng, C. C. (2019). Experiential quality, experiential psychological states and experiential outcomes in an unmanned convenience store. Journal of Retailing and Consumer Services, 51(November), 409‒420. https://doi.org/10.1016/j.jretconser.2019.07.003
Wu, K., Vassileva, J., & Zhao, Y. (2017). Understanding users’ intention to switch personal cloud storage services: Evidence from the Chinese market. Computers in Human Behavior, 68(March), 300‒314. https://doi.org/10.1016/j.chb.2016.11.039
Wu, Y. L., Tao, Y. H., Li, C. P., Wang, S. Y., & Chiu, C. Y. (2014). User-switching behavior in social network sites: A model perspective with drill-down analyses. Computers in Human Behavior, 33(April), 92‒103. https://doi.org/10.1016/j.chb.2013.12.030
Zhang, J., Luximon, Y., & Song, Y. (2019). The role of consumers’ perceived security, perceived control, interface design features, and conscientiousness in continuous use of mobile payment services. Sustainability, 11(23), 1‒16. https://doi.org/10.3390/su11236843
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883‒889. https://doi.org/10.1016/j.chb.2010.11.013
Zhu, H., & Huberman, B. A. (2014). To switch or not to switch: Understanding social influence in online choices. American Behavioral Scientist, 58(10), 1329‒1344. https://doi.org/10.1177/0002764214527089
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