Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry

This study aims to provide an integrated model that examines the determinants of near-field communication (NFC) based mobile payment (MP) technology acceptance in the restaurant industry. The proposed model, which combines the unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM), was tested via structural equation modeling (SEM) by using data collected from 412 restaurant customers. The study results indicated that the proposed model provides approximately 20% greater explanatory power and predictive accuracy than the original UTAUT model and demonstrates strong evidence of the effects of risk, security, and trust on customers' intentions to use NFC-based MP technology in restaurant settings. In addition, considering the total effect, attitude, security, and risk have the most substantial impact on customers behavioral intentions. The study results further demonstrate that risk, security, and trust are also important determinants, with direct and indirect impacts, of other critical constructs (i.e., effort expectancy, hedonic and utilitarian performance expectancy, attitude, and intention). The empirical findings provide valuable theoretical contributions for researchers and practical implications for restaurant operators and technology vendors by explaining the reasons as to why the NFC-based MP is not popular in North American restaurants. Facilitating conditions have no impact on intention to use NFC-based MP.Social readiness positively influences the NFC-based MP use in restaurants.Users consider NFC-based MP as fun when they perceive it useful.Attitude, security, and risk are the most influential factors in NFC-based MP usage.

[1]  Namho Chung,et al.  The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea , 2011 .

[2]  Helaiel Almutairi,et al.  Validating the unified theory of acceptance and use of technology in Kuwaiti ministries: a structural equation modelling approach , 2009, Int. J. Inf. Syst. Chang. Manag..

[3]  Il Im,et al.  The effects of perceived risk and technology type on users' acceptance of technologies , 2008, Inf. Manag..

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

[5]  E. Carvajal-Trujillo,et al.  Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model , 2014 .

[6]  H. Marsh,et al.  Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups. , 1985 .

[7]  Michael R. Mullen,et al.  Structural equation modelling: guidelines for determining model fit , 2008 .

[8]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[9]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[10]  Nena Lim,et al.  Consumers' perceived risk: sources versus consequences , 2003, Electron. Commer. Res. Appl..

[11]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[12]  Hossein Mohammadi,et al.  Investigating users' perspectives on e-learning: An integration of TAM and IS success model , 2015, Comput. Hum. Behav..

[13]  HewTeck-Soon,et al.  NFC mobile credit card , 2014 .

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

[15]  William R. Darden,et al.  Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value , 1994 .

[16]  Panagiotis G. Ipeirotis,et al.  Running Experiments on Amazon Mechanical Turk , 2010, Judgment and Decision Making.

[17]  Carlos Flavián,et al.  Consumer trust, perceived security and privacy policy: Three basic elements of loyalty to a web site , 2006, Ind. Manag. Data Syst..

[18]  Claude Sicotte,et al.  Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT , 2015, Int. J. Medical Informatics.

[19]  Abdulwahab Lawan,et al.  Unified Theory of Acceptance and Use of Technology , 2012, Encyclopedia of Education and Information Technologies.

[20]  Tao Zhou,et al.  User Adoption of Location-based Services , 2011, Ind. Manag. Data Syst..

[21]  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.

[22]  C. Ruiz-Mafé,et al.  The role of consumer innovativeness and perceived risk in online banking usage , 2009 .

[23]  Kiseol Yang Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services , 2010 .

[24]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[25]  Tao Zhou,et al.  An Empirical Examination of Initial Trust in Mobile Banking , 2011, Internet Res..

[26]  Charles D. Barrett Understanding Attitudes and Predicting Social Behavior , 1980 .

[27]  Martin Wetzels,et al.  A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects , 2007, Inf. Manag..

[28]  Yu-Lung Wu,et al.  The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users , 2008 .

[29]  Harold W. Thimbleby,et al.  Validating the unified theory of acceptance and use of technology (UTAUT) tool cross-culturally , 2007, BCS HCI.

[30]  Paul A. Pavlou,et al.  Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..

[31]  Scott B. MacKenzie,et al.  Working memory: theories, models, and controversies. , 2012, Annual review of psychology.

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

[33]  R. P. McDonald,et al.  Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size , 1988 .

[34]  Il Im,et al.  An international comparison of technology adoption: Testing the UTAUT model , 2011, Inf. Manag..

[35]  José Manuel Ortega Egea,et al.  Explaining physicians' acceptance of EHCR systems: An extension of TAM with trust and risk factors , 2011, Comput. Hum. Behav..

[36]  Carla Ruiz-Mafé,et al.  Exploring individual personality factors as drivers of M-shopping acceptance , 2009, Ind. Manag. Data Syst..

[37]  Garry Wei-Han Tan,et al.  Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach , 2013, Expert Syst. Appl..

[38]  V. Venkatesh,et al.  Unified Theory of Acceptance and Use of Technology: U.S. Vs. China , 2010 .

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

[40]  Peter M. Bentler,et al.  Treatments of Missing Data: A Monte Carlo Comparison of RBHDI, Iterative Stochastic Regression Imputation, and Expectation-Maximization , 2000 .

[41]  Dong-Hee Shin,et al.  Towards an understanding of the consumer acceptance of mobile wallet , 2009, Comput. Hum. Behav..

[42]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[43]  J. Hair Multivariate data analysis , 1972 .

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

[45]  William David Salisbury,et al.  Perceived security and World Wide Web purchase intention , 2001, Ind. Manag. Data Syst..

[46]  Varun Gauria,et al.  Organizational Behavior and Human Decision Processes , 2019 .

[47]  D. DavisFred,et al.  User Acceptance of Computer Technology , 1989 .

[48]  F. Chen Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance , 2007 .

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

[50]  Sirkka L. Jarvenpaa,et al.  Consumer Trust in an Internet Store: A Cross-Cultural Validation , 2006, J. Comput. Mediat. Commun..

[51]  C. Cobanoglu,et al.  Are Consumers Ready for Mobile Payment? An Examination of Consumer Acceptance of Mobile Payment Technology in Restaurant Industry , 2015 .

[52]  Fred D. Davis,et al.  Disentangling behavioral intention and behavioral expectation , 1985 .

[53]  Harold Thimbleby,et al.  Validating the unified theory of acceptance and use of technology (UTAUT) tool cross-culturally , 2007 .

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

[55]  E. Carvajal-Trujillo,et al.  Online drivers of consumer purchase of website airline tickets , 2013 .

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

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

[58]  E. Bast Exploring technology acceptance aspects of an NFC enabled mobile shopping system: perceptions of German grocery consumers , 2011 .

[59]  C. Jayawardhena,et al.  e-Consumer Behaviour , 2009 .

[60]  Qingfei Min,et al.  Mobile commerce user acceptance study in China: A revised UTAUT model , 2008 .

[61]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .