Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation

[1]  R. Oliver A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[2]  Sanjoy Ghose,et al.  When Choice Models Fail: Compensatory Models in Negatively Correlated Environments , 1989 .

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

[4]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[5]  J. Elman Learning and development in neural networks: the importance of starting small , 1993, Cognition.

[6]  Richard T. Watson,et al.  Service Quality: A Measure of Information System Effectiveness , 1995, MIS Q..

[7]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[8]  Ko de Ruyter,et al.  The Impact of Perceived Listening Behavior in Voice-to-Voice Service Encounters , 2000 .

[9]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[10]  Michael Negnevitsky,et al.  Artificial Intelligence: A Guide to Intelligent Systems , 2001 .

[11]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[12]  Charles J. Kacmar,et al.  The impact of initial consumer trust on intentions to transact with a web site: a trust building model , 2002, J. Strateg. Inf. Syst..

[13]  David Gefen,et al.  Reflections on the dimensions of trust and trustworthiness among online consumers , 2002, Data Base.

[14]  Detmar W. Straub,et al.  Validation Guidelines for IS Positivist Research , 2004, Commun. Assoc. Inf. Syst..

[15]  Barbara H Wixom,et al.  A Theoretical Integration of User Satisfaction and Technology Acceptance , 2005, Inf. Syst. Res..

[16]  T. C. Edwin Cheng,et al.  Extending the Understanding of End User Information Systems Satisfaction Formation: An Equitable Needs Fulfillment Model Approach , 2008, MIS Q..

[17]  Jen-Her Wu,et al.  An organizational memory information systems success model: an extension of DeLone and McLean's I/S success model , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[18]  Dongsong Zhang,et al.  Predicting and explaining patronage behavior toward web and traditional stores using neural networks: a comparative analysis with logistic regression , 2006, Decis. Support Syst..

[19]  Philip E. T. Lewis,et al.  Research Methods for Business Students , 2006 .

[20]  Sumeet Gupta,et al.  Value-based Adoption of Mobile Internet: An empirical investigation , 2007, Decis. Support Syst..

[21]  Kevin Grant,et al.  Factors affecting the adoption of Internet Banking in Hong Kong - implications for the banking sector , 2007, Int. J. Inf. Manag..

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

[23]  Dennis F. Galletta,et al.  Applying TAM across cultures: the need for caution , 2007, Eur. J. Inf. Syst..

[24]  Jacek M. Zurada,et al.  Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance , 2008, Neural Networks.

[25]  Ephraim R. McLean,et al.  Measuring information systems success: models, dimensions, measures, and interrelationships , 2008, Eur. J. Inf. Syst..

[26]  Gi Mun Kim,et al.  Understanding dynamics between initial trust and usage intentions of mobile banking , 2009, Inf. Syst. J..

[27]  B. Clegg,et al.  An investigation into the acceptance of online banking in Saudi Arabia , 2009 .

[28]  Kun Chang Lee,et al.  Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean's model perspective , 2009, Interact. Comput..

[29]  Sonja Wiley-Patton,et al.  Consumer adoption of mobile TV: Examining psychological flow and media content , 2009, Comput. Hum. Behav..

[30]  Wei-Jaw Deng,et al.  The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services , 2009, Comput. Hum. Behav..

[31]  Chien-Wen David Chen,et al.  Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model , 2009, Behav. Inf. Technol..

[32]  H. Raghav Rao,et al.  Trust and Satisfaction, Two Stepping Stones for Successful E-Commerce Relationships: A Longitudinal Exploration , 2009, Inf. Syst. Res..

[33]  Rakesh Belwal,et al.  Mobile Phone Usage Behavior of University Students in Oman , 2009, 2009 International Conference on New Trends in Information and Service Science.

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

[35]  Xin Luo,et al.  Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services , 2010, Decis. Support Syst..

[36]  Gerold Riempp,et al.  An empirical investigation of employee portal success , 2010, J. Strateg. Inf. Syst..

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

[38]  Chung-Tzer Liu,et al.  he effects of relationship quality and switching barriers on customer loyalty , 2010 .

[39]  Kevin Grant,et al.  Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman , 2012, Int. J. Inf. Manag..

[40]  Alain Yee-Loong Chong,et al.  A SEM-neural network approach for understanding determinants of interorganizational system standard adoption and performances , 2012, Decis. Support Syst..

[41]  Wann‐Yih Wu,et al.  A study of the relationship between customer relationship management contents and benefits in hospitals: An application of fuzzy set theory , 2012 .

[42]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Independent Variables , 2013, J. Manag. Inf. Syst..

[43]  Slade Emma Mobile payment adoption: Classification and review of the extant literature , 2013 .

[44]  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..

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

[46]  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..

[47]  Christine Hallier Willi,et al.  Virtual brand-communities using blogs as communication platforms and their impact on the two-step communication process : a research agenda , 2013 .

[48]  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..

[49]  Hsiu-Fen Lin,et al.  Determining the relative importance of mobile banking quality factors , 2013, Comput. Stand. Interfaces.

[50]  Shahriar Akter,et al.  Development and validation of an instrument to measure user perceived service quality of mHealth , 2013, Inf. Manag..

[51]  Garry Wei-Han Tan,et al.  Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach , 2014, Comput. Hum. Behav..

[52]  Juan Sánchez-Fernández,et al.  Role of gender on acceptance of mobile payment , 2014, Ind. Manag. Data Syst..

[53]  Chun-Ming Chang,et al.  Determinants of repurchase intention in online group-buying: The perspectives of DeLone & McLean IS success model and trust , 2014, Comput. Hum. Behav..

[54]  Garry Wei-Han Tan,et al.  Understanding and predicting the motivators of mobile music acceptance - A multi-stage MRA-artificial neural network approach , 2014, Telematics Informatics.

[55]  Po-yuan Chen,et al.  Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective , 2014 .

[56]  Yogesh Kumar Dwivedi,et al.  What improves citizens' privacy perceptions toward RFID technology? A cross-country investigation using mixed method approach , 2014, Int. J. Inf. Manag..

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

[58]  Lingling Gao,et al.  An empirical study on continuance intention of mobile social networking services: Integrating the IS success model, network externalities and flow theory , 2014 .

[59]  Payam Hanafizadeh,et al.  Mobile-banking adoption by Iranian bank clients , 2014, Telematics Informatics.

[60]  Tiago Oliveira,et al.  International Journal of Information Management , 2014 .

[61]  Martin J. Liu,et al.  Predicting RFID adoption in healthcare supply chain from the perspectives of users , 2015 .

[62]  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 .

[63]  Heejin Lee,et al.  Provision of mobile banking services from an actor–network perspective: Implications for convergence and standardization , 2015 .

[64]  Yogesh Kumar Dwivedi,et al.  Cronfa - Swansea University Open Access Repository , 2017 .

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

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

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

[68]  Tiago Oliveira,et al.  Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective , 2016, Comput. Hum. Behav..

[69]  Tommi Laukkanen Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking , 2016 .

[70]  Abednego Feehi Okoe,et al.  Assessing the determinants of internet banking adoption intentions: A social cognitive theory perspective , 2016, Comput. Hum. Behav..

[71]  Yogesh Kumar Dwivedi,et al.  A generalised adoption model for services: A cross-country comparison of mobile health (m-health) , 2016, Gov. Inf. Q..

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

[73]  Khalizani Khalid,et al.  The adoption of M-government services from the user's perspectives: Empirical evidence from the United Arab Emirates , 2017, Int. J. Inf. Manag..

[74]  Sujeet Kumar Sharma,et al.  Structural equation model (SEM)-neural network (NN) model for predicting quality determinants of e-learning management systems , 2017, Behav. Inf. Technol..

[75]  Zoran Kalinic,et al.  International Journal of Information Management , 2016 .

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

[77]  Lingling Gao,et al.  Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation , 2015, Information Systems Frontiers.

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

[79]  Yogesh Kumar Dwivedi,et al.  Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages , 2018, Journal of Retailing and Consumer Services.

[80]  Nofie Iman,et al.  Is mobile payment still relevant in the fintech era? , 2018, Electron. Commer. Res. Appl..

[81]  Yogesh Kumar Dwivedi,et al.  Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust , 2018, Technology in Society.

[82]  Yogesh Kumar Dwivedi,et al.  What determines success of an e-government service? Validation of an integrative model of e-filing continuance usage , 2018, Gov. Inf. Q..

[83]  Vess Johnson,et al.  Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services , 2018, Comput. Hum. Behav..

[84]  Arpan Kumar Kar,et al.  Success of IoT in Smart Cities of India: An empirical analysis , 2018, Gov. Inf. Q..

[85]  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.

[86]  Sujeet Kumar Sharma,et al.  Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling , 2017, Information Systems Frontiers.