References
- Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24 (4), 665–694. http://dx.doi.org/10.2307/3250951
- Agarwal, R., & Prasad, J. (1998). The antecedents and consequents of user perceptions in information technology adoption. Decision Support Systems, 22 (1), 15–29. http://dx.doi.org/10.1016/S0167-9236(97)00006-7
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179–211. http://dx.doi.org/10.1016/0749-5978(91)90020-T
- Aladwani, A. M. (2013). A cross-cultural comparison of Kuwaiti and British citizens’ views of e-government interface quality. Government Information Quarterly, 30(1), 74–86. https://doi.org/10.1016/j.giq.2012.08.003
- Animesh, A., Pinsonneault, A., Yang, S. B., & Oh, W. (2011). An odyssey into virtual worlds: Exploring the impacts of technological and spatial environments on intention to purchase virtual products. MIS Quarterly, 35 (3), 789–810. https://www.jstor.org/stable/23042809
- Ashraf, A. R., Thongpapanl, N., & Auh, S. (2014). The application of the technology acceptance model under different cultural contexts: The case of online shopping adoption. Journal of International Marketing, 22 (3), 68–93. http://dx.doi.org/10.1509/jim.14.0065
- Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 3. http://aisel.aisnet.org/jais/vol8/iss4/3
- Balaji, M. S., & Roy, S. K. (2017). Value co-creation with Internet of things technology in the retail industry. Journal of Marketing Management, 33 (1–2), 7–31. https://doi.org/10.1080/0267257X.2016.1217914
- Balram, S. (2019). Offline retailers use technology to attract younger consumers. https://economictimes.indiatimes.com/industry/services/retail/offline-retailers-use-technology-to-attract-younger-consumers/articleshow/68434671.cms?from=mdr
- Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Inc.
- Bansal, H. S., Taylor, S. F., & James, Y. S. (2005). “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors. Journal of the Academy of Marketing Science, 33 (1), 96–115. http://dx.doi.org/10.1177/0092070304267928
- Bell, D. E. (1982). Regret in decision making under uncertainty. Operations Research, 30 (5), 961–981. http://dx.doi.org/10.1287/opre.30.5.961
- Berry, L. L., Bolton, R. N., Bridges, C. H., Meyer, J., Parasuraman, A., & Seiders, K. (2010). Opportunities for innovation in the delivery of interactive retail services. Journal of Interactive Marketing, 24 (2), 155–167. http://dx.doi.org/10.1016/j.intmar.2010.02.001
- Besbes, A., Legohérel, P., Kucukusta, D., & Law, R. (2016). A cross-cultural validation of the tourism web acceptance model (T-WAM) in different cultural contexts. Journal of International Consumer Marketing, 28 (3), 211–226. https://doi.org/10.1080/08961530.2016.1152524
- Borrero, J. D., Yousafzai, S. Y., Javed, U., & Page, K. L. (2014). Expressive participation in Internet social movements: Testing the moderating effect of technology readiness and sex on student SNS use. Computers in Human Behavior, 30 (January), 39–49. http://dx.doi.org/10.1016/j.chb.2013.07.032
- Brown, S. (2016). Get smart: Add value with smart retail technology. https://itpeernetwork.intel.com/get-smart-add-value-with-smart-retail-technology/
- Casler, K., Bickel, L., & Hackett, E. (2013). Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Computers in Human Behavior, 29 (6), 2156–2160. http://dx.doi.org/10.1016/j.chb.2013.05.009
- Chang, I., Liu, C. C., & Chen, K. (2014). The push, pull and mooring effects in virtual migration for social networking sites. Information Systems Journal, 24 (4), 323–346. http://dx.doi.org/10.1111/isj.12030
- Clark, B. H., Abela, A. V., & Ambler, T. (2005). Organizational motivation, opportunity and ability to measure marketing performance. Journal of Strategic Marketing, 13 (4), 241–259. http://dx.doi.org/10.1080/09652540500338014
- Collier, J. E., Moore, R. S., Horky, A., & Moore, M. L. (2015). Why the little things matter: Exploring situational influences on customers’ self-service technology decisions. Journal of Business Research, 68 (3), 703–710. http://dx.doi.org/10.1016/j.jbusres.2014.08.001
- Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19 (2), 189–211. https://www.jstor.org/stable/249688
- Curran, J. M., & Meuter, M. L. (2007). Encouraging existing customers to switch to self-service technologies: Put a little fun in their lives. Journal of Marketing Theory and Practice, 15(4), 283–298.
- Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science, 30 (3), 184–201. http://dx.doi.org/10.1177/0092070302303001
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319–340. http://doi.org/10.2307/249008
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982–1003. http://doi.org/10.1287/mnsc.35.8.982
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22 (14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
- Davis, K., & Songer, A. D. (2008). Resistance to IT change in the AEC industry: An individual assessment tool. Construction Management Faculty Publications and Presentations. Semantic Scholar. http://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=1000&context=construct_facpubs
- De Mooij, M., & Hofstede, G. (2011). Cross-cultural consumer behavior: A review of research findings. Journal of International Consumer Marketing, 23 (3–4), 181–192. https://doi.org/10.1080/08961530.2011.578057
- Electronicsforu.com. (2017). Engineering of smart retail stores for India should begin now. https://electronicsforu.com/india-corner/innovations-innovators/engineering-smart-retail-stores-india/2
- Evanschitzky, H., Emrich, O., Sangtani, V., Ackfeldt, A. L., Reynolds, K. E., & Arnold, M. J. (2014). Hedonic shopping motivations in collectivistic and individualistic consumer cultures. International Journal of Research in Marketing, 31 (3), 335–338. http://dx.doi.org/10.1016/j.ijresmar.2014.03.001
- Evanschitzky, H., Iyer, G. R., Pillai, K. G., Kenning, P., & Schütte, R. (2015). Consumer trial, continuous use, and economic benefits of a retail service innovation: The case of the personal shopping assistant. Journal of Product Innovation Management, 32 (3), 459–475. http://dx.doi.org/10.1111/jpim.12241
- Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
- Fan, A., Wu, L., Miao, L., & Mattila, A. S. (2020). When does technology anthropomorphism help alleviate customer dissatisfaction after a service failure?–The moderating role of consumer technology self-efficacy and interdependent self-construal. Journal of Hospitality Marketing & Management, 29 (3), 269–290. https://doi.org/10.1080/19368623.2019.1639095
- Farh, J. L., Hackett, R. D., & Liang, J. (2007). Individual-level cultural values as moderators of perceived organizational support–employee outcome relationships in China: Comparing the effects of power distance and traditionality. Academy of Management Journal, 50(3), 715–729. https://doi.org/10.5465/amj.2007.25530866
- Fornell, C., & Cha, J. (1994). Partial least squares. In R. Bagozzi (Ed.), Advanced Methods of Marketing Research, (pp. 52–78). Blackwell Publishing.
- Foroudi, P., Gupta, S., Sivarajah, U., & Broderick, A. (2018). Investigating the effects of smart technology on customer dynamics and customer experience. Computers in Human Behavior, 80 (March), 271–282. https://doi.org/10.1016/j.chb.2017.11.014
- Fu, J. R., & Chen, J. H. (2015). Career commitment of information technology professionals: The investment model perspective. Information & Management, 52 (5), 537–549. https://doi.org/10.1016/j.im.2015.03.005
- Ganesh, S., & Paramasivam Ganesh, M. (2014). Effects of masculinity-femininity on quality of work life: Understanding the moderating roles of gender and social support. Gender in Management: An International Journal, 29 (4), 229–253. https://doi.org/10.1108/GM-07-2013-0085
- Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26 (2), 211–231. http://dx.doi.org/10.1108/APJML-06-2013-0061
- Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, 115 (9), 1704–1723. http://dx.doi.org/10.1108/IMDS-03-2015-0087
- Garaus, M., Wolfsteiner, E., & Wagner, U. (2016). Shoppers’ acceptance and perceptions of electronic shelf labels. Journal of Business Research, 69 (9), 3687–3692. http://dx.doi.org/10.1016/j.jbusres.2016.03.030
- Goncalo, J. A., & Staw, B. M. (2006). Individualism–collectivism and group creativity. Organizational Behavior and Human Decision Processes, 100(1), 96–109. https://doi.org/10.1016/j.obhdp.2005.11.003
- Grewal, G., Noble, S. M., Roggeveen, A. L., & Nordfalt, J. (2020). The future of in-store technology. Journal of the Academy of Marketing Science, 48 (1), 96–113. https://link.springer.com/article/10.1007/s11747-019-00697-z
- Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2005). How e-communities extend the concept of exchange in marketing: An application of the motivation, opportunity, ability (MOA) theory. Marketing Theory, 5 (1), 33–49. https://doi.org/10.1177/1470593105049600
- Ha, Y., & Im, H. (2014). Determinants of mobile coupon service adoption: Assessment of gender difference. International Journal of Retail & Distribution Management, 42 (5), 441–459. http://dx.doi.org/10.1108/IJRDM-08-2012-0074
- Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40 (3), 414–433. http://dx.doi.org/10.1007/s11747-011-0261-6
- Harrison, J. K., Chadwick, M., & Scales, M. (1996). The relationship between cross-cultural adjustment and the personality variables of self-efficacy and self-monitoring. International Journal of Intercultural Relations, 20 (2), 167–188. https://doi.org/10.1016/0147-1767(95)00039-9
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43 (1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
- Hofstede, G. (1983). National cultures in four dimensions: A research-based theory of cultural differences among nations. International Studies of Management & Organization, 13(1–2), 46–74. https://doi.org/10.1080/00208825.1983.11656358
- Hogg, G., Laing, A., & Winkelman, D. (2003). The professional service encounter in the age of the Internet: An exploratory study. Journal of Services Marketing, 17 (5), 476–494. https://doi.org/10.1108/08876040310486276
- Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853–868. https://doi.org/10.1016/j.im.2003.08.014
- Hsu, M. H., & Chiu, C. M. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38 (3), 369–381. http://dx.doi.org/10.1016/j.dss.2003.08.001
- Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information & Management, 48(1), 1–8. https://doi.org/10.1016/j.im.2010.09.001
- Jung, T. H., Lee, H., Chung, N., & Tom Dieck, M. C. (2018). Cross-cultural differences in adopting mobile augmented reality at cultural heritage tourism sites. International Journal of Contemporary Hospitality Management, 30 (3), 1621–1645. https://doi.org/10.1108/IJCHM-02-2017-0084
- Kallweit, K., Spreer, P., & Toporowski, W. (2014). Why do customers use self-service information technologies in retail? The mediating effect of perceived service quality. Journal of Retailing and Consumer Services, 21 (3), 268–276. http://dx.doi.org/10.1016/j.jretconser.2014.02.002
- Kang, J. W., Lee, H., & Namkung, Y. (2018). The impact of restaurant patrons’ flow experience on SNS satisfaction and offline purchase intentions. International Journal of Contemporary Hospitality Management, 30 (2), 797–816. https://doi.org/10.1108/IJCHM-09-2016-0537
- Kang, L., Wang, X., Tan, C. H., & Zhao, J. L. (2015). Understanding the antecedents and consequences of live chat use in electronic markets. Journal of Organizational Computing and Electronic Commerce, 25 (2), 117–139. https://doi.org/10.1080/10919392.2015.1033935
- Karatepe, O. M. (2015). Do personal resources mediate the effect of perceived organizational support on emotional exhaustion and job outcomes? International Journal of Contemporary Hospitality Management, 27 (1), 4–26. http://dx.doi.org/10.1108/IJCHM-09-2013-0417
- Khan, M. S. L., Li, H., & Ur Réhman, S. (2016). Gaze perception and awareness in smart devices. International Journal of Human-Computer Studies, 92–93, 55–65. https://doi.org/10.1016/j.ijhcs.2016.05.002
- Kitayama, S., Markus, H. R., Matsumoto, H., & Norasakkunkit, V. (1997). Individual and collective processes in the construction of the self: Self-enhancement in the United States and self-criticism in Japan. Journal of Personality and Social Psychology, 72 (6), 1245–1267. https://doi.org/10.1037/0022-3514.72.6.1245
- Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13 (2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
- Kucukusta, D., Heung, V. C., & Hui, S. (2014). Deploying self-service technology in luxury hotel brands: Perceptions of business travelers. Journal of Travel & Tourism Marketing, 31 (1), 55–70. https://doi.org/10.1080/10548408.2014.861707
- Lee, H. Y., Lee, Y. K., & Kwon, D. (2005). The intention to use computerized reservation systems: The moderating effects of organizational support and supplier incentive. Journal of Business Research, 58 (11), 1552–1561. http://dx.doi.org/10.1016/j.jbusres.2004.07.008
- Lee, S. G., Trimi, S., & Kim, C. (2013). The impact of cultural differences on technology adoption. Journal of World Business, 48 (1), 20–29. http://dx.doi.org/10.1016/j.jwb.2012.06.003
- Lee, Y., Lee, J., & Hwang, Y. (2015). Relating motivation to information and communication technology acceptance: Self-determination theory perspective. Computers in Human Behavior, 51 (Part A), 418–428. http://dx.doi.org/10.1016/j.chb.2015.05.021
- Leung, X. Y., & Bai, B. (2013). How motivation, opportunity, and ability impact travelers’ social media involvement and revisit intention. Journal of Travel & Tourism Marketing, 30 (1–2), 58–77. https://doi.org/10.1080/10548408.2013.751211
- Lin, H. C. (2014). An investigation of the effects of cultural differences on physicians’ perceptions of information technology acceptance as they relate to knowledge management systems. Computers in Human Behavior, 38 (September), 368–380. https://doi.org/10.1016/j.chb.2014.05.001
- Lin, J. S. C., & Chang, H. C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21 (4), 424–444. https://doi.org/10.1108/09604521111146289
- Lin, J. S. C., & Hsieh, P. L. (2012). Refinement of the technology readiness index scale: A replication and cross-validation in the self-service technology context. Journal of Service Management, 23 (1), 34–53. https://doi.org/10.1108/09564231211208961
- Liu, B. S. C., Furrer, O., & Sudharshan, D. (2001). The relationships between culture and behavioral intentions toward services. Journal of Service Research, 4 (2), 118–129. https://doi.org/10.1177/109467050142004
- MacInnis, D. J., Moorman, C., & Jaworski, B. J. (1991). Enhancing and measuring consumers’ motivation, opportunity, and ability to process brand information from ads. Journal of Marketing, 55 (4), 32–53. https://doi.org/10.2307/1251955
- Markets and Markets. (2015). Internet of Things (IoT) in retail market worth 35.64 billion USD by 2020. http://www.marketsandmarkets.com/PressReleases/retail-iot.asp
- Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of Consumer Research, 31 (2), 324–332. https://doi.org/10.1086/422111
- Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. Journal of Marketing, 69 (2), 61–83. https://doi.org/10.1509/jmkg.69.2.61.60759
- Moore, K. (2017). Why 2017 is Australia’s retail tipping point. http://www.smartcompany.com.au/industries/retail/why-2017-is-australias-retail-tipping-point/
- Nunnally, J. (1994). Psychometric methods. McGraw-Hill.
- Ordanini, A., Parasuraman, A., & Rubera, G. (2013). When the recipe is more important than the ingredients a qualitative comparative analysis (QCA) of service innovation configurations. Journal of Service Research, 17 (4), 134–149. https://doi.org/10.1177/1094670513513337
- Pallant, J. (2018). What’s really driving the future of retail? The conversation. https://theconversation.com/whats-really-driving-the-future-of-retail-100518
- Pantano, E., & Timmermans, H. (2014). What is smart for retailing? Procedia Environmental Sciences, 22, 101–107. http://dx.doi.org/10.1016/j.proenv.2014.11.010
- Pantano, E., & Viassone, M. (2014). Demand pull and technology push perspective in technology-based innovations for the points of sale: The retailers evaluation. Journal of Retailing and Consumer Services, 21 (1), 43–47. http://dx.doi.org/10.1016/j.jretconser.2013.06.007
- Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2 (4), 307–320. https://doi.org/10.1177/109467050024001
- Park, N., Rhoads, M., Hou, J., & Lee, K. M. (2014). Understanding the acceptance of teleconferencing systems among employees: An extension of the technology acceptance model. Computers in Human Behavior, 39 (October), 118–127. http://dx.doi.org/10.1016/j.chb.2014.05.048
- Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88 (5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
- Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers’ expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77 (December), 374–381. https://doi.org/10.1016/j.chb.2017.01.058
- Privette, G., & Brundrick, C. M. (1991). Peak experience, peak performance, and flow: Correspondence of personal descriptions and theoretical constructs. Journal of Social Behavior and Personality, 6 (5), 169. https://bit.ly/2HUaSOc
- Rese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2016). How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological Forecasting and Social Change, 124 (November), 306–319. http://dx.doi.org/10.1016/j.techfore.2016.10.010
- Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. SmartPLS GmbH. http://www.smartpls.com
- Robertson, N. L., & Shaw, R. (2009). Predicting the likelihood of voiced complaints in the self-service technology context. Journal of Service Research, 12 (1), 100–116. http://doi.org/10.1177/1094670509333789
- Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
- Rojas-Méndez, J. I., Parasuraman, A., & Papadopoulos, N. (2017). Demographics, attitudes, and technology readiness: A cross-cultural analysis and model validation. Marketing Intelligence & Planning, 35 (1), 18–39. https://doi.org/10.1108/MIP-08-2015-0163
- Rosenbaum, M. S., & Wong, I. A. (2015). If you install it, will they use it? Understanding why hospitality customers take “technological pauses” from self-service technology. Journal of Business Research, 68 (9), 1862–1868. http://dx.doi.org/10.1016/j.jbusres.2015.01.014
- Roy, S. K., Balaji, M. S., Sadeque, S., Nguyen, B., & Melewar, T. C. (2017). Constituents and consequences of smart customer experience in retailing. Technological Forecasting and Social Change, 124, 257–270. http://dx.doi.org/10.1016/j.techfore.2016.09.022
- Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55 (1), 68–78. http://dx.doi.org/10.1037/0003-066X.55.1.68
- Sääksjärvi, M., & Samiee, S. (2011). Assessing multifunctional innovation adoption via an integrative model. Journal of the Academy of Marketing Science, 39 (5), 717–735. http://dx.doi.org/10.1007/s11747-010-0231-4
- Sabnis, G., Chatterjee, S. C., Grewal, R., & Lilien, G. L. (2013). The sales lead black hole: On sales reps’ follow-up of marketing leads. Journal of Marketing, 77 (1), 52–67. http://dx.doi.org/10.1509/jm.10.0047
- Sánchez-Franco, M. J., & Roldán, J. L. (2005). Web acceptance and usage model: A comparison between goal-directed and experiential web users. Internet Research, 15 (1), 21–48. http://dx.doi.org/10.1108/10662240510577059
- Sarstedt, M., Henseler, J., & Christian, M. (2011). Multigroup analysis in Partial Least Squares (PLS) path modeling: Alternative methods and empirical results. In M. Sarstedt, M. Schwaiger and C. R. Taylor (Eds), Measurement and research methods in international marketing (pp. 195–218). Emerald Group Publishing Limited.
- Sharafi, P., Hedman, L., & Montgomery, H. (2006). Using information technology: Engagement modes, flow experience, and personality orientations. Computers in Human Behavior, 22 (5), 899–916. https://doi.org/10.1016/j.chb.2004.03.022
- Shiau, W. L., & Luo, M. M. (2013). Continuance intention of blog users: The impact of perceived enjoyment, habit, user involvement and blogging time. Behaviour & Information Technology, 32 (6), 570–583. https://doi.org/10.1080/0144929X.2012.671851
- Singelis, T. M. (1994). The measurement of independent and interdependent self-construals. Personality and Social Psychology Bulletin, 20 (5), 580–591. https://doi.org/10.1177/0146167294205014
- Smith, R., Deitz, G., Royne, M. B., Hansen, J. D., Grünhagen, M., & Witte, C. (2013). Cross-cultural examination of online shopping behavior: A comparison of Norway, Germany, and the United States. Journal of Business Research, 66 (3), 328–335. https://doi.org/10.1016/j.jbusres.2011.08.013
- Son, M., & Han, K. (2011). Beyond the technology adoption: Technology readiness effects on post-adoption behavior. Journal of Business Research, 64 (11), 1178–1182. http://dx.doi.org/10.1016/j.jbusres.2011.06.019
- Su, Y. S., Chiang, W. L., Lee, C. T. J., & Chang, H. C. (2016). The effect of flow experience on player loyalty in mobile game application. Computers in Human Behavior, 63 (October), 240–248. https://doi.org/10.1016/j.chb.2016.05.049
- Triandis, H. C. (2004). The many dimensions of culture. The Academy of Management Executive, 18 (1), 88–93. https://doi.org/10.5465/ame.2004.12689599
- Van Beuningen, J., de Ruyter, K., Wetzels, M., & Streukens, S. (2009). Customer self-efficacy in technology-based self-service assessing between-and within-person differences. Journal of Service Research, 11 (4), 407–428. https://doi.org/10.1177/1094670509333237
- Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28 (4), 695–704. https://www.jstor.org/stable/25148660
- Vatavu, R. D. (2017). Smart-pockets: Body-deictic gestures for fast access to personal data during ambient interactions. International Journal of Human-Computer Studies, 103 (July), 1–21. https://doi.org/10.1016/j.ijhcs.2017.01.005
- Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11 (4), 342–365. http://dx.doi.org/10.1287/isre.11.4.342.11872
- Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36 (1), 157–178. https://www.jstor.org/stable/41410412
- Wang, C., Harris, J., & Patterson, P. (2013). The roles of habit, self-efficacy, and satisfaction in driving continued use of self-service technologies a longitudinal study. Journal of Service Research, 16 (3), 400–414. https://doi.org/10.1177/1094670512473200
- Wang, K. (2015). Determinants of mobile value-added service continuance: The mediating role of service experience. Information & Management, 52 (3), 261–274. http://dx.doi.org/10.1016/j.im.2014.11.005
- Wang, Y., So, K. K. F., & Sparks, B. A. (2016). Technology readiness and customer satisfaction with travel technologies. A cross-country investigation. Journal of Travel Research, 56 (5), 563–577. https://doi.org/10.1177/0047287516657891
- Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33 (1), 177–195. https://www.jstor.org/stable/20650284
- Willems, K., Smolders, A., Brengman, M., Luyten, K., & Schöning, J. (2016). The path-to-purchase is paved with digital opportunities: An inventory of shopper-oriented retail technologies. Technological Forecasting and Social Change, 124 (November). http://dx.doi.org/10.1016/j.techfore.2016.10.066.
- Wirtz, J., Xiao, P., Chiang, J., & Malhotra, N. (2014). Contrasting the drivers of switching intent and switching behavior in contractual service settings. Journal of Retailing, 90 (4), 463–480. http://dx.doi.org/10.1016/j.jretai.2014.07.002
- Xu, J., Benbasat, I., & Cenfetelli, R. T. (2014). Research note-the influences of online service technologies and task complexity on efficiency and personalization. Information Systems Research, 25 (2), 420–436. http://dx.doi.org/10.1287/isre.2013.0503
- Xu, S., Zhu, K., & Gibbs, J. (2004). Global technology, local adoption: A cross-country investigation of internet adoption by companies in the United States and China. Electronic Markets, 14 (1), 13–24. https://doi.org/10.1080/1019678042000175261
- Yang, K., & Forney, J. C. (2013). The moderating role of consumer technology anxiety in mobile shopping adoption: Differential effects of facilitating conditions and social influences. Journal of Electronic Commerce Research, 14 (44), 334–347. http://ojs.jecr.org/jecr/sites/default/files/14_4_p04.pdf
- Yim, C. K. B., Chan, K. W., & Hung, K. (2007). Multiple reference effects in service evaluations: Roles of alternative attractiveness and self-image congruity. Journal of Retailing, 83 (1), 147–157. http://dx.doi.org/10.1016/j.jretai.2006.10.011
- Zhang, K. Z., Lee, M. K., Cheung, C. M., & Chen, H. (2009). Understanding the role of gender in bloggers’ switching behavior. Decision Support Systems, 47 (4), 540–546. https://doi.org/10.1016/j.dss.2009.05.013
- Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28 (5), 1902–1911. http://dx.doi.org/10.1016/j.chb.2012.05.008
- Zhang, X., De Pablos, P. O., Wang, X., Wang, W., Sun, Y., & She, J. (2014). Understanding the users’ continuous adoption of 3D social virtual world in China: A comparative case study. Computers in Human Behavior, 35 (June), 578–585. http://dx.doi.org/10.1016/j.chb.2014.02.034
- Zhou, T. (2013). Understanding the effect of flow on user adoption of mobile games. Personal and Ubiquitous Computing, 17 (4), 741–748. http://dx.doi.org/10.1007/s00779-012-0613-3
- Zhu, Z., Nakata, C., Sivakumar, K., & Grewal, D. (2007). Self-service technology effectiveness: The role of design features and individual traits. Journal of the Academy of Marketing Science, 35(4), 492–506. http://dx.doi.org/10.1007/s11747-007-0019-3