Service mobile apps: a millennial generation perspective
Tóm tắt
Từ khóa
Tài liệu tham khảo
1999, Are individual differences germane to the acceptance of new information technologies?, Decision Sciences, 30, 361, 10.1111/j.1540-5915.1999.tb01614.x
1991, The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 179, 10.1016/0749-5978(91)90020-T
2014, Customer experience from a self-service system perspective, Journal of Service Management, 25, 677, 10.1108/JOSM-01-2013-0016
2007, Extending the technology acceptance model for SMS banking: analyzing the gender gap among students, International Journal of Business and Society, 8, 15
2014, The application of the technology acceptance model under different cultural contexts: the case of online shopping adoption, Journal of International Marketing, 22, 68, 10.1509/jim.14.0065
1977, Self-efficacy: toward a unifying theory of behavioral change, Psychological Review, 84, 191, 10.1037/0033-295X.84.2.191
1986, Social Foundations of Thought and Action: A Social Cognitive Theory
BEA (2018), “BEA industry facts: private services-producing industries”, available at: www.bea.gov/industry/factsheet/factsheet.cfm (accessed April 8, 2018).
2008, Gender differences and intra-gender differences amongst management information systems students, Journal of Information Systems Education, 19, 301
2016, Gen Y customer loyalty in online shopping: an integrated model of trust, user experience and branding, Computers in Human Behavior, 61, 103, 10.1016/j.chb.2016.03.014
1984, Empirical validation of affect, behavior, and cognition as distinct components of attitude, Journal of Personality and Social Psychology, 47, 1191, 10.1037/0022-3514.47.6.1191
2005, Gender and information and communication technologies (IT) anxiety: male self-assurance and female hesitation, Cyber Psychology and Behaviour, 8, 21, 10.1089/cpb.2005.8.21
2003, An empirical investigation of the determinants of user acceptance of internet banking, Journal of Organizational Computing and Electronic Commerce, 13, 123, 10.1207/S15327744JOCE1302_3
2009, Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model, Behavior and Information Technology, 28, 335, 10.1080/01449290701850111
2017, Determinants of behavioral intention to use the personalized location-based mobile tourism application: an empirical study by integrating TAM with ISSM, Future Generation Computer Systems
Chin, W.W. (1998), “The partial least squares approach to structural equation modeling”, in Marcoulides, G.A. (Ed.), Modern Methods for Business Research, Lawrence Erlbaum Associates, Mahwah, NJ, pp. 295-358.
2010, How to Write Up and Report PLS Analyses, 655
2014, Determinants of adoption of smartphone health apps among college students, American Journal of Health Behavior, 38, 860, 10.5993/AJHB.38.6.8
2013, Assessing the impact of quality determinants and user characteristics on successful enterprise resource planning project implementation, Journal of Manufacturing Systems, 32, 792, 10.1016/j.jmsy.2013.04.014
1995, Computer self-efficacy: development of a measure and initial test, MIS Quarterly, 19, 189, 10.2307/249688
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, 184, 10.1177/0092070302303001
1989, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 319, 10.2307/249008
1993, User acceptance of information technology: system characteristics, user perceptions and behavioral impacts, International Journal Man-Machine Studies, 38, 475, 10.1006/imms.1993.1022
1989, User acceptance of computer technology: a comparison of two theoretical models, Management Science, 35, 982, 10.1287/mnsc.35.8.982
1992, Information systems success: the quest for the dependent variable, Information Systems Research, 3, 60, 10.1287/isre.3.1.60
2003, The DeLone and McLean model of information systems success: a ten-year update, Journal of Management Information Systems, 19, 9, 10.1080/07421222.2003.11045748
2014, Comparison of the middle-aged and older users’ adoption of mobile health services in China, International Journal of Medical Informatics, 83, 210, 10.1016/j.ijmedinf.2013.12.002
2018, Lift-share using mobile apps in tourism: the role of trust, sense of community and existing lift-share practices, Transportation Research Part D: Transport and Environment, 61, 397, 10.1016/j.trd.2017.11.004
2015, Emotions and continued usage of mobile applications, Industrial Management and Data Systems, 115, 833, 10.1108/IMDS-11-2014-0338
2013, Key quality factors affecting users’ perception of social networking websites, Journal of Retailing and Consumer Services, 20, 120, 10.1016/j.jretconser.2012.10.013
2016, An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: does gender matter?, Journal of Retailing and Consumer Services, 30, 140, 10.1016/j.jretconser.2016.01.016
2015, Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective, Journal of Retailing and Consumer Services, 22, 37, 10.1016/j.jretconser.2014.09.006
1975, Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research
2017, How locus of control shapes intention to reuse mobile apps for making hotel reservations: evidence from Chinese consumers, Tourism Management, 61, 331, 10.1016/j.tourman.2017.03.002
1981, Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 39, 10.1177/002224378101800104
1997, Gender differences in the perception and use of e-mail: an extension to the technology acceptance model, MIS Quarterly, 21, 389, 10.2307/249720
2014, Exploring gender differences in Islamic mobile banking acceptance, Electronic Commerce Research, 14, 435, 10.1007/s10660-014-9150-7
2014, Designing mobile business applications for different age groups, Technological Forecasting and Social Change, 88, 177, 10.1016/j.techfore.2014.06.020
2006, Multivariate Data Analysis, 6th ed.
2010, Are men more technology-oriented than women? The role of gender on the development of general computer self-efficacy of college students, Journal of Information Systems Education, 21, 203
Henderson, S. (2016), “Spending habits by generation”, The US Department of Labor, available at: https://blog.dol.gov/2016/11/03/spending-habits-by-generation (accessed August 4, 2017).
Henseler, J. (2007), “A new and simple approach to multi-group analysis in partial least squares path modeling”, in Martens, H. and Næs, T. (Eds), Causalities Explored by Indirect Observation: Proceedings of the 5th International Symposium on PLS and Related Methods (PLS’07), Oslo, pp. 104-107.
2009, The use of partial least squares path modeling in international marketing, Advances in International Marketing, 20, 277, 10.1108/S1474-7979(2009)0000020014
2015, What catalyses mobile apps usage intention: an empirical analysis, Industrial Management and Data Systems, 115, 1269, 10.1108/IMDS-01-2015-0028
2015, Mobile application usability: conceptualization and instrument development, MIS Quarterly, 39, 435, 10.25300/MISQ/2015/39.2.08
2009, Millennials Rising: The Next Great Generation
2015, Assessing ERP post-implementation success at the individual level: revisiting the role of service quality, Information & Management, 52, 925, 10.1016/j.im.2015.06.009
2007, Factors affecting Internet shopping behavior in Singapore: gender and educational issues, International Journal of Consumer Studies, 31, 310, 10.1111/j.1470-6431.2006.00554.x
2017, Understanding usage intention in innovative mobile app service: comparison between millennial and mature consumers, 73, 353
IDC (2016), “Worldwide mobile applications forecast 2016–2020: mobile app revenue outlook remains healthy despite slowing download volumes and smartphone growth”, available at: www.idc.com/getdoc.jsp?containerId=prUS41240816 (accessed October 20, 2016).
1976, Managerial response to an information system, 877
Juniper Research (2016), “Mobile banking users to reach 2 billion by 2020: representing more than 1 in 3 of global adult population”, available at: www.juniperresearch.com/press/press-releases/mobile-banking-users-to-reach-2-billion-by-2020 (accessed October 21, 2016).
1999, The psychological origins of perceived usefulness and ease-of-use, Information and Management, 35, 237, 10.1016/S0378-7206(98)00096-2
2010, An empirical examination of factors influencing the intention to use mobile payment, Computers in Human Behavior, 26, 310, 10.1016/j.chb.2009.10.013
2004, A comparison of online trust building factors between potential customers and repeat customers, Journal of the Association for Information Systems, 5, 392, 10.17705/1jais.00056
2015, Marketing Management, 15th ed.
2007, Toward a unified theory of consumer acceptance technology, Psychology and Marketing, 24, 1059, 10.1002/mar.20196
2015, Traveler acceptance of an app-based mobile tour guide, Journal of Hospitality and Tourism Research, 39, 401, 10.1177/1096348013491596
2015, Perspective: older adults’ adoption of technology: an integrated approach to identifying determinants and barriers, Journal of Product Innovation Management, 32, 747, 10.1111/jpim.12176
2015, The relationship between attitude toward using and customer satisfaction with mobile application services: an empirical study from the life insurance industry, Journal of Enterprise Information Management, 28, 680, 10.1108/JEIM-07-2014-0077
2003, The technology acceptance model: past, present, and future, Communications of the Association for Information Systems, 12, 752
2012, A unified perspective on the factors influencing usage intention toward mobile financial services, Journal of Business Research, 65, 1590, 10.1016/j.jbusres.2011.02.044
2003, Why do people use information technology? a critical review of the technology acceptance model, Information Management, 40, 191, 10.1016/S0378-7206(01)00143-4
2013, Modeling the stimulators of the behavioral intention to use mobile entertainment: does gender really matter?, Computers in Human Behavior, 29, 2109, 10.1016/j.chb.2013.04.004
2013, Generational differences in content generation in social media: the roles of the gratifications sought and of narcissism, Computers in Human Behavior, 29, 997, 10.1016/j.chb.2012.12.028
2014, Gender and mobile access method differences of millennials in social media evaluation and usage: an empirical test, Marketing Management Journal, 24, 124
2010, Examining e-travel sites: an empirical study in Taiwan, Online Information Review, 34, 205, 10.1108/14684521011036954
2006, Determinants of success for online communities: an empirical study, Behaviour and Information Technology, 25, 479, 10.1080/01449290500330422
2000, Towards an understanding of the behavioural intention to use a web site, International Journal of Information Management, 20, 197, 10.1016/S0268-4012(00)00005-0
2017, Gender differences in information quality of virtual communities: a study from an expectation-perception perspective, Personality and Individual Differences, 104, 224, 10.1016/j.paid.2016.08.011
1978, Empirical evidence for a descriptive model of implementation, MIS Quarterly, 2, 27, 10.2307/248939
Masnick, G. (2012), “Defining the generations”, Joint Center for Housing Studies of Harvard University, available at: http://housingperspectives.blogspot.co.id/2012/11/defining-generations.html (accessed December 6, 2017).
2000, Self-service technologies: understanding customer satisfaction with technology-based service encounters, Journal of Marketing, 64, 50, 10.1509/jmkg.64.3.50.18024
2000, Academic insights: an application of multiple-group causal models in assessing cross-cultural measurement equivalence, Journal of International Marketing, 8, 108, 10.1509/jimk.8.4.108.19790
Nielsen (2014), “Millennials: technology = social connection”, available at: www.nielsen.com/us/en/insights/news/2014/millennials-technology-social-connection.html (accessed December 12, 2017).
2015, Mobile health services: a new paradigm for health care systems, International Journal of Asian Business and Information Management, 6, 1, 10.4018/IJABIM.2015010101
2016, An analysis of the relationship between quality and user acceptance in smartphone apps, Information Systems and e-Business Management, 14, 273, 10.1007/s10257-015-0283-6
1978, Psychometric Theory, 2nd ed.
2003, Web retailing adoption: exploring the nature of internet users web retailing behavior, Journal of Retailing and Consumer Services, 10, 81, 10.1016/S0969-6989(02)00004-8
Olson, M.A. and Kendrick, R.V. (2008), “Origins of attitudes, book: attitudes and attitude change”, in Crano, W.D. and Prislin, R. (Eds), Attitudes and Attitude Change, Psychology Press, New York, NY.
2009, Cognitive control in media multitaskers, 15583
2015, Factors impacting the acceptance of mobile data services – a systematic literature review, Computers in Human Behavior, 53, 24, 10.1016/j.chb.2015.06.013
2007, An empirical investigation of consumer control factors on adoption intention selected self-service technologies, International Journal of Service Industry Management, 18, 287, 10.1108/09564230710751497
2016, What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience, International Journal of Information Management, 36, 1350, 10.1016/j.ijinfomgt.2016.04.005
2007, Acceptance and adoption of the innovative use of smartphone, Industrial Management and Data Systems, 107, 1349, 10.1108/02635570710834009
1979, Reliability: a review of psychometric basics and recent marketing practices, Journal of Marketing Research, 16, 6, 10.1177/002224377901600102
Pew Research Center (2011), “The generation gap and the 2012 election”, available at: www.people-press.org/2011/11/03/the-generation-gap-and-the-2012-election-3/ (accessed February 12, 2016).
2003, Common method biases in behavioral research: a critical review of the literature and recommended remedies, Journal of Applied Psychology, 88, 879, 10.1037/0021-9010.88.5.879
Ringle, C.M., Wende, S. and Becker, J.M. (2015), “SmartPLS 3”, SmartPLS GmbH, Boenningstedt, available at: www.smartpls.com
2010, The moderating effect of gender in the adoption of mobile banking adoption, International Journal of Bank Marketing, 28, 328, 10.1108/02652321011064872
2003, A gender and e-commerce: an exploratory study, Journal of Advertising Research, 43, 322, 10.2501/JAR-43-3-322-329
2016, Mobile app usage and its implications for service management – empirical findings from German public transport, 230
SITA (2016), “Air transport industry insights: the airline it trends survey”, available at: www.sita.aero/airline-survey-2016 (accessed June 3, 2016).
2002, Effect of trust on customer acceptance of internet banking, Electronic Commerce Research and Applications, 1, 247
2017, Flight ticket booking app on mobile devices: examining the determinants of individual intention to use, Journal of Air Transport Management, 62, 146, 10.1016/j.jairtraman.2017.04.003
2016, Determinants of continuance intention to use the smartphone banking services: an extension to the expectation-confirmation model, Industrial Management & Data Systems, 116, 508, 10.1108/IMDS-05-2015-0195
2006, Millennial Behaviors and Demographics
2016, Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective, Computers in Human Behavior, 61, 233, 10.1016/j.chb.2016.03.016
2016, Behavioural intention to adopt mobile banking among the millennial generation, Young Consumers, 17, 18, 10.1108/YC-07-2015-00537
2015, The moderating role of technology readiness, gender, and sex in consumer acceptance and actual use of technology-based services, Journal of High Technology Management Research, 26, 124, 10.1016/j.hitech.2015.09.003
2009, Customer self-efficacy in technology-based self-service: assessing between-and within-person differences, Journal of Service Research, 11, 407, 10.1177/1094670509333237
2000, Determinants of perceived ease of use: integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model, Information Systems Research, 11, 342, 10.1287/isre.11.4.342.11872
2008, Technology acceptance model 3 and a research agenda on interventions, Decision Sciences, 39, 273, 10.1111/j.1540-5915.2008.00192.x
1996, A model of the antecedents of perceived ease of use: development and test, Decision Sciences, 27, 451, 10.1111/j.1540-5915.1996.tb01822.x
2000, A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science, 46, 186, 10.1287/mnsc.46.2.186.11926
2000, Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior, MIS Quarterly, 24, 115, 10.2307/3250981
2012, Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Quarterly, 36, 157, 10.2307/41410412
2003, User acceptance of information technology: toward a unified view, MIS Quarterly, 27, 425, 10.2307/30036540
2006, Mobile computing: a user study on hedonic/utilitarian mobile device usage, European Journal of Information Systems, 15, 292, 10.1057/palgrave.ejis.3000619
2010, Predicting mobile hotel reservation adoption: insight from a perceived value standpoint, International Journal of Hospitality Management, 29, 598, 10.1016/j.ijhm.2009.11.001
2015, Service supply chain management: a review of operational models, European Journal of Operational Research, 247, 685, 10.1016/j.ejor.2015.05.053
2016, The Millennial Generation: Implications for the Intelligence and Policy Communities
2011, The adoption of mobile healthcare by hospital’s professionals: an integrative perspective, Decision Support Systems, 51, 587, 10.1016/j.dss.2011.03.003
2007, Mobile computing acceptance factors in the healthcare industry: a structural equation model, International Journal of Medical Informatics, 76, 66, 10.1016/j.ijmedinf.2006.06.006
2013, Bon appétit for apps: young American consumers’ acceptance of mobile applications, The Journal of Computer Information Systems, 53, 85, 10.1080/08874417.2013.11645635
2005, Exploring factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics, 22, 257, 10.1016/j.tele.2004.11.003
2012, Using the technology acceptance model to evaluate user attitude and intention of use for online games, Total Quality Management, 23, 965