Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal

Abstract Mobile payments are the future as we move towards a cashless society. In some markets, cash is already being replaced by digital transactions, but consumers of many developing countries are slower in transition towards digital payments. This study aims to identify major determinants of consumer mobile payment adoption in India the country with second largest mobile subscribers in the world. Existing mobile payments adoption studies have predominantly utilised Technology Acceptance Model (TAM), which was primarily developed in organisational context and criticised for having deterministic approach without much consideration for users’ individual characteristics. Therefore, this study adapted meta-UTAUT model with individual difference variable attitude as core construct and extended the model with consumer related constructs such as personal innovativeness, anxiety, trust, and grievance redressal. Empirical examination of the model among 491 Indian consumers revealed performance expectancy, intention to use, and grievance redressal as significant positive predictor of consumer use behaviour towards mobile payment. Moreover, intention to use was significantly influenced by attitude, social influence, and facilitating conditions. The major contribution of this study includes re-affirming the central role of attitude in consumer adoption studies and examining usage behaviour in contrast to most existing studies, which examine only behavioural intention.

[1]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[2]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[3]  Khaled A. Alshare,et al.  Predicting Student-Perceived Learning Outcomes and Satisfaction in ERP Courses: An Empirical Investigation , 2011, Commun. Assoc. Inf. Syst..

[4]  Laurence Brooks,et al.  E-government implementation in Zambia: contributing factors , 2007, Electron. Gov. an Int. J..

[5]  W. Aslam,et al.  Consumer Behavioral Intentions towards Mobile Payment Services: An Empirical Analysis in Pakistan , 2017 .

[6]  Anisa Stefi,et al.  Do Developers Make Unbiased Decisions? - The Effect of Mindfulness and Not-Invented-Here Bias on the Adoption of Software Components , 2015, ECIS.

[7]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[8]  T. Garry,et al.  Value co-creation: The role of actor competence , 2017 .

[9]  Yogesh Kumar Dwivedi,et al.  A Systematic Review of Citations of UTAUT2 Article and Its Usage Trends , 2017, I3E.

[10]  Yogesh Kumar Dwivedi,et al.  Adoption of online public grievance redressal system in India: Toward developing a unified view , 2016, Comput. Hum. Behav..

[11]  Simon Fong,et al.  User Acceptance Testing of Mobile Payment in Various Scenarios , 2008, 2008 IEEE International Conference on e-Business Engineering.

[12]  Aspasia Togia,et al.  Computer anxiety and attitudes among undergraduate students in Greece , 2010, Comput. Hum. Behav..

[13]  D. Whetten What Constitutes a Theoretical Contribution , 1989 .

[14]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[15]  Ikram Dastan,et al.  Factors Affecting the Adoption of Mobile Payment Systems: An Empirical Analysis , 2016 .

[16]  Matthew K. O. Lee,et al.  Self-disclosure in mobile payment applications: Common and differential effects of personal and proxy control enhancing mechanisms , 2020, Int. J. Inf. Manag..

[17]  Yogesh Kumar Dwivedi,et al.  Innovation adoption attributes: a review and synthesis of research findings , 2014 .

[18]  Magid Igbaria,et al.  End-user computing effectiveness: A structural equation model , 1990 .

[19]  Charles J. Kacmar,et al.  Developing and Validating Trust Measures for e-Commerce: An Integrative Typology , 2002, Inf. Syst. Res..

[20]  Harsh Vardhan Samalia,et al.  Extending unified theory of acceptance and use of technology with perceived monetary value for smartphone adoption at the bottom of the pyramid , 2020, Int. J. Inf. Manag..

[21]  Yogesh Kumar Dwivedi,et al.  Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust , 2017, Int. J. Inf. Manag..

[22]  Alain Yee-Loong Chong,et al.  A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption , 2013, Expert Syst. Appl..

[23]  Pedro Monge-Lozano,et al.  Factors that Influence the Perceived Advantages and Relevance of Facebook as a Learning Tool: An Extension of the UTAUT. , 2014 .

[24]  Norman Shaw The mediating influence of trust in the adoption of the mobile wallet , 2014 .

[25]  J. Hair Multivariate data analysis : a global perspective , 2010 .

[26]  Tao Zhou,et al.  An empirical examination of continuance intention of mobile payment services , 2013, Decis. Support Syst..

[27]  A. Palmer,et al.  Enjoyment and social influence: predicting mobile payment adoption , 2015 .

[28]  Wassan A.A. Al-Khowaiter,et al.  Digital payment and banking adoption research in Gulf countries: A systematic literature review , 2020, Int. J. Inf. Manag..

[29]  Tao Zhou,et al.  Examining mobile banking user adoption from the perspectives of trust and flow experience , 2012, Inf. Technol. Manag..

[30]  Yogesh Kumar Dwivedi,et al.  Social media research in the context of emerging markets , 2018 .

[31]  J. Yeon,et al.  The Adoption of Mobile Payment Services for "Fintech" , 2016 .

[32]  Yijun Huang,et al.  The impact of privacy concern on users' usage intention of mobile payment , 2012, 2012 International Conference on Information Management, Innovation Management and Industrial Engineering.

[33]  Arpan Kumar Kar,et al.  Quality in Mobile Payment Service in India , 2017, I3E.

[34]  Yogesh Kumar Dwivedi,et al.  Evaluating alternative theoretical models for examining citizen centric adoption of e‐government , 2013 .

[35]  Jonas Hedman,et al.  Value Added Services and Adoption of Mobile Payments , 2014, ICEC '14.

[36]  Yogesh Kumar Dwivedi,et al.  The unified theory of acceptance and use of technology (UTAUT): a literature review , 2015, J. Enterp. Inf. Manag..

[37]  C. Robb,et al.  Adoption of Mobile Payment Technology by Consumers , 2014 .

[38]  Joel R. Evans,et al.  The value of online surveys , 2005, Internet Res..

[39]  Marjan Hericko,et al.  An Empirical Study of Virtual Learning Environment Adoption Using UTAUT , 2010, 2010 Second International Conference on Mobile, Hybrid, and On-Line Learning.

[40]  Francesca Valsesia ASSOCIATION FOR CONSUMER RESEARCH , 2015 .

[41]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[42]  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 .

[43]  Tiago Oliveira,et al.  Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators , 2015, Comput. Hum. Behav..

[44]  David Graham Wastell,et al.  Diffusion - or delusion? Challenging an IS research tradition , 2005, Inf. Technol. People.

[45]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[46]  Yogesh Kumar Dwivedi,et al.  Demographic influence on UK citizens' e-government adoption , 2008, Electron. Gov. an Int. J..

[47]  U. Goel,et al.  Factors influencing adoption of payments banks by Indian customers: extending UTAUT with perceived credibility , 2019, Journal of Asia Business Studies.

[48]  Niels J. Blunch,et al.  Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS , 2012 .

[49]  Shuiqing Yang,et al.  Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective , 2011, Inf. Manag..

[50]  Ying Kong,et al.  Exploring Culture Factors Affecting the Adoption of Mobile Payment , 2011, 2011 10th International Conference on Mobile Business.

[51]  E. Hirschman Innovativeness, Novelty Seeking, and Consumer Creativity , 1980 .

[52]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[53]  Lei-da Chen,et al.  Determinants of Mobile Payments: An Empirical Analysis , 2008, Journal of International Technology and Information Management.

[54]  Judith C. Forney,et al.  The Moderating Role of Consumer Technology Anxiety in Mobile Shopping Adoption: Differential Effects of Facilitating Conditions and Social Influences , 2013 .

[55]  Tao Zhou,et al.  Understanding the determinants of mobile payment continuance usage , 2014, Ind. Manag. Data Syst..

[56]  Daniel Brantes Ferreira,et al.  The effects of trust transference, mobile attributes and enjoyment on mobile trust , 2015 .

[57]  Emad Abu-Shanab,et al.  Drivers of mobile payment acceptance: The impact of network externalities , 2015, Information Systems Frontiers.

[58]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[59]  Yogesh Kumar Dwivedi,et al.  Citizens’ adoption of an electronic government system: towards a unified view , 2015, Information Systems Frontiers.

[60]  O. Alaeddin,et al.  FROM PHYSICAL TO DIGITAL: INVESTIGATING CONSUMER BEHAVIOUR OF SWITCHING TO MOBILE WALLET , 2018, Polish Journal of Management Studies.

[61]  M. Nilashi,et al.  Academic researchers’ behavioural intention to use academic social networking sites: A case of Malaysian research universities , 2019 .

[62]  Yogesh Kumar Dwivedi,et al.  Exploring the Role of 'Price Value' for Understanding Consumer Adoption of Technology: A Review and Meta-analysis of UTAUT2 based Empirical Studies , 2018, PACIS.

[63]  Giovanni Mattia,et al.  The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical application to public transport , 2015 .

[64]  Lihua Huang,et al.  Exploring User Acceptance of Innovative Mobile Payment Service in Emerging Market: the Moderating effect of diffusion stages of WeChat Payment in China , 2016, PACIS.

[65]  Yogesh Kumar Dwivedi,et al.  Consumer adoption and usage of broadband in Bangladesh , 2007, Electron. Gov. an Int. J..

[66]  Agnes L. DeFranco,et al.  It's about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels , 2016 .

[67]  Rui Zhang,et al.  Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits , 2012, Comput. Hum. Behav..

[68]  Nuri Wulandari Cashless Payment in Tourism. An Application of Technology Acceptance Model , 2017, Journal of Environmental Management and Tourism.

[69]  Nripendra P. Rana,et al.  Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model , 2019, Int. J. Inf. Manag..

[70]  Niina Mallat,et al.  Exploring consumer adoption of mobile payments - A qualitative study , 2007, J. Strateg. Inf. Syst..

[71]  Robert D. Smith,et al.  Computer anxiety in management: myth or reality? , 1986, CACM.

[72]  Iryna Pentina,et al.  Mobile payments adoption by US consumers: an extended TAM , 2017 .

[73]  Lihua Huang,et al.  Consumer acceptance of mobile payment across time: Antecedents and moderating role of diffusion stages , 2017, Ind. Manag. Data Syst..

[74]  N. Michaelidou,et al.  Are innovative consumers emotional and prestigiously sensitive to price? , 2014 .

[75]  Heikki Karjaluoto,et al.  How Relevant Are Risk Perceptions, Effort, and Performance Expectancy in Mobile Banking Adoption? , 2018, Int. J. E Bus. Res..

[76]  D. Whetten An Examination of the Interface between Context and Theory Applied to the Study of Chinese Organizations , 2009, Management and Organization Review.

[77]  Juan Sánchez-Fernández,et al.  The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN) , 2014, Int. J. Inf. Manag..

[78]  Yu Tian,et al.  An analysis of key factors affecting user acceptance of mobile payment , 2013, 2013 Second International Conference on Informatics & Applications (ICIA).

[79]  Bernd W. Wirtz,et al.  Understanding consumer acceptance of mobile payment services: An empirical analysis , 2010, Electron. Commer. Res. Appl..

[80]  Mala Srivastava,et al.  Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India , 2014, Internet Res..

[81]  Shalini Chandra,et al.  of the Association , 2018 .

[82]  Norman L. Chervany,et al.  What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology , 2001, Int. J. Electron. Commer..

[83]  Biplab Datta,et al.  Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective , 2018 .

[84]  D. Iacobucci Everything You Always Wanted to Know About SEM (Structural Equations Modeling) But Were Afraid to Ask , 2009 .

[85]  Ritu Agarwal,et al.  Are Individual Differences Germane to the Acceptance of New Information Technologies , 1999 .

[86]  Heikki Karjaluoto,et al.  How perceived value drives the use of mobile financial services apps , 2019, Int. J. Inf. Manag..

[87]  Yung-Hsiang Cheng,et al.  High speed rail passengers’ mobile ticketing adoption , 2013 .

[88]  Garry Wei-Han Tan,et al.  NFC mobile credit card: The next frontier of mobile payment? , 2014, Telematics Informatics.

[89]  Juan Sánchez-Fernández,et al.  Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied , 2019, Technological Forecasting and Social Change.

[90]  Nripendra P. Rana,et al.  A meta-analysis based modified unified theory of acceptance and use of technology (meta-UTAUT): a review of emerging literature. , 2020, Current opinion in psychology.

[91]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[92]  Brijesh Sivathanu Adoption of digital payment systems in the era of demonetization in India , 2018, Journal of Science and Technology Policy Management.

[93]  A. Ozturk,et al.  Role of risk, self-efficacy, and innovativeness on behavioral intentions for mobile payment systems in the restaurant industry , 2016 .

[94]  Habib Ullah Khan,et al.  Factors influence consumers' adoption of mobile payment devices in Qatar , 2015, Int. J. Mob. Commun..

[95]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[96]  Yogesh Kumar Dwivedi,et al.  Devising a research model to examine adoption of mobile payments: An extension of UTAUT2 , 2014 .

[97]  Nathalie T. M. Demoulin,et al.  Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers? , 2016 .

[98]  Tao Zhou,et al.  Integrating TTF and UTAUT to explain mobile banking user adoption , 2010, Comput. Hum. Behav..

[99]  Wynne W. Chin,et al.  On the use, usefulness, and ease of use of structural equation modeling in MIS research: a note of caution , 1995 .

[100]  I. Ajzen The theory of planned behavior , 1991 .

[101]  Dong-Hee Shin,et al.  Modeling the Interaction of Users and Mobile Payment System: Conceptual Framework , 2010, Int. J. Hum. Comput. Interact..

[102]  Won-jun Lee,et al.  The Effects Of Technology Readiness And Technology Acceptance On Nfc Mobile Payment Services In Korea , 2014 .

[103]  Sonia San Martín Gutiérrez,et al.  Mobile Shoppers: Types, Drivers, and Impediments , 2013, J. Organ. Comput. Electron. Commer..

[104]  Tao Zhou,et al.  An Empirical Examination of Initial Trust in Mobile Payment , 2014, Wireless Personal Communications.

[105]  Khaled A. Alshare,et al.  The Moderating effect of Espoused Cultural Dimensions on Consumer's Intention to Use Mobile Payment Devices , 2014, ICIS.

[106]  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.

[107]  Nripendra P. Rana,et al.  Consumer Acceptance and Use of Information Technology: A Meta-Analytic Evaluation of UTAUT2 , 2020, Information Systems Frontiers.

[108]  Yogesh Kumar Dwivedi,et al.  A Meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT) , 2011, Governance and Sustainability in Information Systems.

[109]  C. Sellitto,et al.  User Intentions to Adopt Mobile Payment Services: A Study of Early Adopters in Thailand , 2015 .

[110]  Juan Sánchez-Fernández,et al.  Antecedents of the adoption of the new mobile payment systems: The moderating effect of age , 2014, Comput. Hum. Behav..

[111]  Yogesh Kumar Dwivedi,et al.  Exploring consumer adoption of proximity mobile payments , 2014, Journal of Strategic Marketing.

[112]  Neena Sinha,et al.  Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence , 2020, Int. J. Inf. Manag..

[113]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[114]  Arpan Kumar Kar,et al.  Review of Technology Adoption frameworks in Mobile Commerce , 2017, ITQM.

[115]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[116]  Eze Uchenna Cyril,et al.  Modelling User Trust and Mobile Payment Adoption: A Conceptual Framework , 2008 .

[117]  Yogesh Kumar Dwivedi,et al.  Open data and its usability: an empirical view from the Citizen’s perspective , 2016, Information Systems Frontiers.

[118]  N. Charness,et al.  Factors Predicting the Use of Technology: Findings From the Center for Research and Education on Aging and Technology Enhancement (CREATE) , 2006 .

[119]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[120]  Michael R. Simonson,et al.  Development of a Standardized Test of Computer Literacy and a Computer Anxiety Index , 1987 .

[121]  Nava Pliskin,et al.  Drivers and Inhibitors of Mobile-Payment Adoption by Smartphone Users , 2012, Int. J. E Bus. Res..

[122]  H. Celik Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework , 2016 .

[123]  Manoj A. Thomas,et al.  Mobile Payment , 2013, Springer Fachmedien Wiesbaden.

[124]  Amandeep Dhir,et al.  Exploring Consumer Adoption of Mobile Payments in China , 2013, MindTrek.

[125]  Kiseol Yang Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior , 2012 .

[126]  Rolph E. Anderson,et al.  Multivariate Data Analysis with Readings , 1979 .

[127]  Yogesh Kumar Dwivedi,et al.  Digital Payments Adoption: An Analysis of Literature , 2017, I3E.

[128]  Naresh K. Malhotra,et al.  Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research , 2006, Manag. Sci..

[129]  Xianhao Xu,et al.  Drivers and barriers in the acceptance of mobile payment in China , 2011, 2011 International Conference on E-Business and E-Government (ICEE).

[130]  M. Seligman,et al.  Learned helplessness in humans: critique and reformulation. , 1978, Journal of abnormal psychology.

[131]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[132]  Marc Rysman,et al.  Mobile Payments at the Retail Point of Sale in the United States: Prospects for Adoption , 2010 .

[133]  Understanding Consumers' Intention to Use Mobile Payment Services: The Perspective of University Students in Northern Jiangsu Area , 2012, 2012 Second International Conference on Business Computing and Global Informatization.

[134]  Kampan Mukherjee,et al.  The effect of perceived security and grievance redressal on continuance intention to use M-wallets in a developing country , 2018, International Journal of Bank Marketing.

[135]  In Lee,et al.  An empirical examination of factors influencing the intention to use mobile payment , 2010, Comput. Hum. Behav..

[136]  Manisha Sharma,et al.  Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation , 2019, Int. J. Inf. Manag..

[137]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[138]  Arpan Kumar Kar,et al.  m-commerce technology adoption , 2018, The Bottom Line.

[139]  Yogesh K. Dwivedi,et al.  Implementing e-government in Sri Lanka: Lessons from the UK , 2009 .

[140]  Hongwei Du,et al.  Toward a better understanding of behavioral intention and system usage constructs , 2012, Eur. J. Inf. Syst..