Understanding the effects of physical experience and information integration on consumer use of online to offline commerce
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Lesley Pek Wee Land | Yeming Gong | Thomas Chesney | Yongqing Yang | Y. Gong | T. Chesney | L. Land | Yongqing Yang
[1] David F. Midgley,et al. Formative versus reflective measurement models: two applications of formative measurement | NOVA. The University of Newcastle's Digital Repository , 2008 .
[2] Tao Zhou,et al. An empirical examination of continuance intention of mobile payment services , 2013, Decis. Support Syst..
[3] Shian-Yang Tzeng,et al. An empirical research of consumer adoption behavior on catering transformation to mobile O2O , 2015 .
[4] Yogesh Kumar Dwivedi,et al. RFID systems in libraries: An empirical examination of factors affecting system use and user satisfaction , 2013, Int. J. Inf. Manag..
[5] Yong Liu,et al. Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China , 2011, Comput. Hum. Behav..
[6] Francisco J. Molina-Castillo,et al. Customer Knowledge Management and E-commerce: The role of customer perceived risk , 2008, Int. J. Inf. Manag..
[7] Sumeet Gupta,et al. Value-based Adoption of Mobile Internet: An empirical investigation , 2007, Decis. Support Syst..
[8] Viswanath Venkatesh,et al. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..
[9] Yi-Shun Wang,et al. The stickiness intention of group-buying websites: The integration of the commitment-trust theory and e-commerce success model , 2016, Inf. Manag..
[10] Min Zhang,et al. The impact of channel integration on consumer responses in omni-channel retailing: The mediating effect of consumer empowerment , 2018, Electron. Commer. Res. Appl..
[11] Shan Liu,et al. Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks , 2017, Eur. J. Oper. Res..
[12] Tao Zhou,et al. Exploring Chinese users' acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory , 2009, Comput. Hum. Behav..
[13] Lin Xiao,et al. Exploring the moderators and causal process of trust transfer in online-to-offline commerce , 2019, Journal of Business Research.
[14] Lu Hsiao,et al. Returns Policy and Quality Risk in E-Business , 2010 .
[15] I. Ajzen,et al. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .
[16] Eunil Park,et al. An Integrated Adoption Model of Mobile Cloud Services: Exploration of Key Determinants and Extension of Technology Acceptance Model , 2014, Telematics Informatics.
[17] Changsu Kim,et al. An empirical investigation of factors affecting ubiquitous computing use and U-business value , 2009, Int. J. Inf. Manag..
[18] Jee-Won Kang,et al. The information quality and source credibility matter in customers’ evaluation toward food O2O commerce , 2019, International Journal of Hospitality Management.
[19] Jiayin Qi,et al. An extension of technology acceptance model: Analysis of the adoption of mobile data services in China , 2009 .
[20] Yogesh Kumar Dwivedi,et al. Citizens’ adoption of an electronic government system: towards a unified view , 2015, Information Systems Frontiers.
[21] Yogesh Kumar Dwivedi,et al. An empirical validation of a unified model of electronic government adoption (UMEGA) , 2017, Gov. Inf. Q..
[22] Yong Liu,et al. Understanding perceived risks in mobile payment acceptance , 2015, Ind. Manag. Data Syst..
[23] Dennis Herhausen,et al. Integrating Bricks with Clicks: Retailer-Level and Channel-Level Outcomes of Online–Offline Channel Integration , 2015 .
[24] Dong-Hee Shin,et al. Modeling the Interaction of Users and Mobile Payment System: Conceptual Framework , 2010, Int. J. Hum. Comput. Interact..
[25] Tao Zhou,et al. Industrial Management & Data Systems Understanding continuance usage of mobile sites , 2016 .
[26] Tze-Hsien Liao,et al. Online shopping post-payment dissonance: Dissonance reduction strategy using online consumer social experiences , 2017, Int. J. Inf. Manag..
[27] E. Rogers. Diffusion of Innovations , 1962 .
[28] Bernd W. Wirtz,et al. Understanding consumer acceptance of mobile payment services: An empirical analysis , 2010, Electron. Commer. Res. Appl..
[29] K. Ruyter,et al. An assessment of value creation in mobile service delivery and the moderating role of time consciousness , 2007 .
[30] Jung-Kuei Hsieh,et al. The role of customers in co-creating m-services in the O2O model , 2017 .
[31] T. C. Edwin Cheng,et al. Evolutionary location and pricing strategies for service merchants in competitive O2O markets , 2016, Eur. J. Oper. Res..
[32] C. Fornell,et al. Evaluating structural equation models with unobservable variables and measurement error. , 1981 .
[33] C. Shapiro,et al. Network Externalities, Competition, and Compatibility , 1985 .
[34] J. H. Gilmore,et al. Welcome to the experience economy. , 1998, Harvard business review.
[35] Neil Gandal. Hedonic Price Indexes for Spreadsheets and an Empirical Test for Network Externalities , 1994 .
[36] Icek Ajzen,et al. From Intentions to Actions: A Theory of Planned Behavior , 1985 .
[37] Byoungsoo Kim,et al. The difference of determinants of acceptance and continuance of mobile data services: A value perspective , 2011, Expert Syst. Appl..
[38] Huilin Wang,et al. Investigation of Chinese students' O2O shopping through multiple devices , 2017, Comput. Hum. Behav..
[39] Sonja Wiley-Patton,et al. Consumer adoption of mobile TV: Examining psychological flow and media content , 2009, Comput. Hum. Behav..
[40] Marko Sarstedt,et al. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .
[41] Shinyi Lin,et al. Perceived Innovation and Quick Response Codes in an Online-to-Offline E-Commerce Service Model , 2017, Int. J. E Adopt..
[42] Jungjoo Jahng,et al. Effects of interaction richness on consumer attitudes and behavioral intentions in e-commerce: some experimental results , 2007, Eur. J. Inf. Syst..
[43] Gordon B. Davis,et al. User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..
[44] A. Keramati,et al. A combinative model of behavioural and technical factors affecting ‘Mobile’-payment services adoption: an empirical study , 2012 .
[45] Yan Peng,et al. An O2O E-Commerce Acceptance Model in Local Life Service , 2018, FSDM.
[46] Lu Lu,et al. Consumers acceptance of artificially intelligent (AI) device use in service delivery , 2019, Int. J. Inf. Manag..
[47] Seongcheol Kim,et al. Does mIM experience affect satisfaction with and loyalty toward O2O services? , 2018, Comput. Hum. Behav..
[48] Fred D. Davis. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..
[49] Charles M. Wood,et al. Incorporating Perceived Risk Into Models of Consumer Deal Assessment and Purchase Intent , 1996 .
[50] Neil Gandal. Hedonic price indexes for spreadsheets and an empirical test of the network externalities hypothesis , 1992 .
[51] Clay M. Voorhees,et al. Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies , 2016 .
[52] N. Kock. Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach , 2015, Int. J. e Collab..
[53] Yogesh Kumar Dwivedi,et al. Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model , 2017, Information Systems Frontiers.
[54] You Wu,et al. Exploring short-form video application addiction: Socio-technical and attachment perspectives , 2019, Telematics Informatics.
[55] John D'Ambra,et al. Benefit-based O2O commerce segmentation: a means-end chain approach , 2018, Electronic Commerce Research.
[56] V. Mitchell. Consumer perceived risk: conceptualisations and models , 1999 .
[57] Peter A. Todd,et al. Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..
[58] A. Tversky,et al. Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .
[59] H. Raghav Rao,et al. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents , 2008, Decis. Support Syst..
[60] Yogesh Kumar Dwivedi,et al. A generalised adoption model for services: A cross-country comparison of mobile health (m-health) , 2016, Gov. Inf. Q..
[61] H. Teo,et al. The effects of retail channel integration through the use of information technologies on firm performance , 2012 .
[62] J. Hair. Multivariate data analysis , 1972 .
[63] C. Ruiz-Mafé,et al. The role of consumer innovativeness and perceived risk in online banking usage , 2009 .
[64] Diane M. Strong,et al. Extending the technology acceptance model with task-technology fit constructs , 1999, Inf. Manag..
[65] Jinlong Zhang,et al. Hybrid Influences of Social Subsystem and Technical Subsystem Risks in the Crowdsourcing Marketplace , 2019, IEEE Transactions on Engineering Management.
[66] Harry Bouwman,et al. An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models , 2008, Inf. Manag..
[67] Yogesh Kumar Dwivedi,et al. Adoption of online public grievance redressal system in India: Toward developing a unified view , 2016, Comput. Hum. Behav..
[68] M.H.P. Kleijnen,et al. Consumer adoption of wireless services: Discovering the rules, while playing the game , 2004 .
[69] E. McKinney,et al. Extending the Technology Acceptance Model Extending the Technology Acceptance Model and the Task and the Task-Technology Fit Model to Technology Fit Model to Consumer E Consumer E- -Commerce Commerce , 2004 .
[70] Chin-Lung Hsu,et al. Examining Social Networking O2O Apps User Loyalty , 2018, J. Comput. Inf. Syst..
[71] Namho Chung,et al. The role of technology readiness in consumers' adoption of mobile internet services between South Korea and China , 2014, Int. J. Mob. Commun..
[72] In Lee,et al. An empirical examination of factors influencing the intention to use mobile payment , 2010, Comput. Hum. Behav..
[73] Fred D. Davis,et al. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.
[74] Edward E. Rigdon,et al. Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. , 2001 .
[75] Jen-Her Wu,et al. What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..
[76] Minjung Roh,et al. Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation , 2019, Int. J. Inf. Manag..
[77] Ali Abdallah Alalwan,et al. Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse , 2020, Int. J. Inf. Manag..
[78] Lin Xiao,et al. Examining Consumers’ Behavioral Intention in O2O Commerce from a Relational Perspective: an Exploratory Study , 2017, Information Systems Frontiers.
[79] Yi Li,et al. The Impacts of User Experience on User Loyalty Based on O2O Innovation Platform , 2019, J. Electron. Commer. Organ..
[80] Tibert Verhagen,et al. Online purchase intentions: A multi-channel store image perspective , 2009, Inf. Manag..
[81] Jung-Kuei Hsieh,et al. The challenge for multichannel services: Cross-channel free-riding behavior , 2011, Electron. Commer. Res. Appl..
[82] Yu-Wei Chang,et al. Integration of online and offline channels: a view of O2O commerce , 2018, Internet Res..
[83] Chia-Chen Chen,et al. Understanding usage transfer behavior of two way O2O services , 2019, Comput. Hum. Behav..
[84] Lin Xiao,et al. Understanding consumer repurchase intention on O2O platforms: an integrated model of network externalities and trust transfer theory , 2018 .
[85] Stephen L. Vargo,et al. Evolving to a New Dominant Logic for Marketing , 2004 .
[86] Eric T. G. Wang,et al. Understanding customers' repeat purchase intentions in B2C e‐commerce: the roles of utilitarian value, hedonic value and perceived risk , 2014, Inf. Syst. J..
[87] Yogesh Kumar Dwivedi,et al. Modeling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust , 2015 .
[88] Hamed Qahri Saremi,et al. Factors affecting adoption of online banking: A meta-analytic structural equation modeling study , 2015, Inf. Manag..
[89] Ronald T. Cenfetelli,et al. Interpretation of Formative Measurement in Information Systems Research , 2009, MIS Q..
[90] Ming-Chi Lee,et al. Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit , 2009, Electron. Commer. Res. Appl..
[91] Paul A. Pavlou,et al. Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..
[92] Yogesh Kumar Dwivedi,et al. Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust , 2017, Int. J. Inf. Manag..
[93] Hui Li,et al. Local Market Characteristics and Online-to-Offline Commerce: An Empirical Analysis of Groupon , 2016 .