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

International Journal of Information Management - Tập 44 - Trang 65-75 - 2019
Sujeet Kumar Sharma1, Manisha Sharma2
1MIS Area, Indian Institute of Management Tiruchirappalli, India
2School of Management, Gautam Buddha University, Greater Noida, UP, India

Tóm tắt

Từ khóa


Tài liệu tham khảo

Ahmad, 2017, The adoption of M-government services from the user’s perspectives: Empirical evidence from the United Arab Emirates, International Journal of Information Management, 37, 367, 10.1016/j.ijinfomgt.2017.03.008

Akter, 2013, Development and validation of an instrument to measure user perceived service quality of mHealth, Information & Management, 50, 181, 10.1016/j.im.2013.03.001

Alalwan, 2018, Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceivedenjoyment, innovativeness and trust, Technology in Society, 10.1016/j.techsoc.2018.06.007

Alalwan, 2016, Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy, Journal of Enterprise Information Management, 29, 118, 10.1108/JEIM-04-2015-0035

Alalwan, 2017, Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust, International Journal of Information Management, 37, 99, 10.1016/j.ijinfomgt.2017.01.002

Al-Somali, 2009, An investigation into the acceptance of online banking in Saudi Arabia, Technovation, 29, 130, 10.1016/j.technovation.2008.07.004

Au, 2008, Extending the understanding of end user information systems satisfaction formation: An equitable needs fulfillment model approach, MIS Quarterly, 32, 43, 10.2307/25148828

Baptista, 2015, Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators, Computers in Human Behavior, 50, 418, 10.1016/j.chb.2015.04.024

Belwal, 2009, Mobile phone usage behavior of university students in Oman, International Conference on New Trends in Information and Service Science, 954, 10.1109/NISS.2009.65

Bhattacherjee, 2001, Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, 25, 351, 10.2307/3250921

Boateng, 2016, Assessing the determinants of internet banking adoption intentions: A social cognitive theory perspective, Computers in Human Behavior, 65, 468, 10.1016/j.chb.2016.09.017

Chan, 2012, A SEM–neural network approach for understanding determinants of interorganizational system standard adoption and performances, Decision Support Systems, 54, 621, 10.1016/j.dss.2012.08.009

Chandra, 2010, Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis, Communications of the Association for Information Systems, 27, 561, 10.17705/1CAIS.02729

Chatterjee, 2018, Success of IoT in Smart Cities of India: An empirical analysis, Government Information Quarterly, 35, 349, 10.1016/j.giq.2018.05.002

Chen, 2009, Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model, Behaviour & Information Technology, 28, 335, 10.1080/01449290701850111

Chiang, 2006, Predicting and explaining patronage behavior toward web and traditional stores using neural networks: A comparative analysis with logistic regression, Decision Support Systems, 41, 514, 10.1016/j.dss.2004.08.016

Chong, 2013, A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption, Expert Systems With Applications, 40, 1240, 10.1016/j.eswa.2012.08.067

Chong, 2015, Predicting RFID adoption in healthcare supply chain from the perspectives of users, International Journal of Production Economics, 159, 66, 10.1016/j.ijpe.2014.09.034

Davis, 1989, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 319, 10.2307/249008

De Kerviler, 2016, Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers?, Journal of Retailing and Consumer Services, 31, 334, 10.1016/j.jretconser.2016.04.011

de Ruyter, 2000, The impact of perceived listening behavior in voice-to-voice service encounters, Journal of Service Research, 2, 276, 10.1177/109467050023005

DeLone, 1992, Information systems success: The quest for the dependent variable, Information Systems Research, 3, 60, 10.1287/isre.3.1.60

DeLone, 2002, Information systems success: The quest for the dependent variable, Information Systems Research, 3, 60, 10.1287/isre.3.1.60

DeLone, 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

Dwivedi, 2016, A generalised adoption model for services: A cross-country comparison of mobile health (m-health), Government Information Quarterly, 33, 174, 10.1016/j.giq.2015.06.003

Dwivedi, 2017

Dwivedi, 2013, RFID systems in libraries: An empirical examination of factors affecting system use and user satisfaction, International Journal of Information Management, 33, 367, 10.1016/j.ijinfomgt.2012.10.008

Elman, 1993, Learning and development in neural networks: The importance of starting small, Cognition, 48, 71, 10.1016/0010-0277(93)90058-4

Gao, 2014, An empirical study on continuance intention of mobile social networking services: Integrating IS success model, network externalities and flow theory, Asia Pacific Journal of Marketing and Logistics, 26, 168, 10.1108/APJML-07-2013-0086

Gao, 2017, Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation, Information System Frontiers, 19, 525, 10.1007/s10796-015-9611-0

Gefen, 2002, Reflections on the dimensions of trust and trustworthiness among online consumers, ACM SIGMIS Database, 33, 38, 10.1145/569905.569910

GSMA, 2016

Hair, 2010

Hanafizadeh, 2014, Mobile banking adoption by Iranian bank clients, Telematics and Informatics, 31, 62, 10.1016/j.tele.2012.11.001

Haykin, 2001

Hossain, 2014, What improves citizens’ privacy perceptions toward RFID technology? A cross-country investigation using mixed method approach, International Journal of Information Management, 34, 711, 10.1016/j.ijinfomgt.2014.07.002

Hsu, 2014, Determinants of repurchase intention in online group-buying: The perspectives of DeLone & McLean IS success model and trust, Computers in Human Behavior, 36, 234, 10.1016/j.chb.2014.03.065

ICT sustainable development report. (2015). Retrieved from www.oman.om/wps/wcm/…/ICT+Sustainable+Development+Report+2015.

Iman, 2018, Is mobile payment still relevant in the fintech era?, Electronic Commerce Research and Applications, 30, 72, 10.1016/j.elerap.2018.05.009

Johnson, 1989, When choice models fail: Compensatory models in negatively correlated environments, Journal of Marketing Research, 26, 255, 10.2307/3172899

Johnson, 2018, Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services, Computers in Human Behavior, 79, 111, 10.1016/j.chb.2017.10.035

Jung, 2009, Consumer adoption of mobile TV: Examining psychological flow and media content, Computers in Human Behavior, 25, 123, 10.1016/j.chb.2008.07.011

Kim, 2007, Value-based adoption of mobile internet: An empirical investigation, Decision Support Systems, 43, 111, 10.1016/j.dss.2005.05.009

Kim, 2009, Understanding dynamics between initial trust and usage intentions of mobile banking, Information Systems Journal, 19, 283, 10.1111/j.1365-2575.2007.00269.x

Kim, 2009, Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration, Information Systems Research, 20, 237, 10.1287/isre.1080.0188

KPMG Analysis (2015). Mobile Banking 2015. Retrieved from https://home.kpmg.com/content/dam/kpmg/pdf/2015/…/mobile-banking-report-2015.

Kuo, 2009, The relationships among service quality, perceived value, customer satisfaction and post-purchase intention in mobile value-added services, Computers in Human Behavior, 25, 887, 10.1016/j.chb.2009.03.003

Kuo, 2012, A study of the relationship between customer relationship management contents and benefits in hospitals: An application of fuzzy set theory, African Journal of Business Management, 6, 4835

Laukkanen, 2016, Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking, Journal of Business Research, 69, 2432, 10.1016/j.jbusres.2016.01.013

Lee, 2009, Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective, Interacting With Computers, 21, 385, 10.1016/j.intcom.2009.06.004

Lee, 2015, Provision of mobile banking services from an actor-network perspective: Implications for convergence and standardization, Technological Forecasting and Social Change, 90, 551, 10.1016/j.techfore.2014.02.007

Leong, 2013, Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach, Expert Systems With Applications, 40, 5604, 10.1016/j.eswa.2013.04.018

Liebana-Cabanillas, 2017, A SEM-neural network approach for predicting antecedents of m-commerce acceptance, International Journal of Information Management, 37, 14, 10.1016/j.ijinfomgt.2016.10.008

Liebana-Cabanillas, 2014, Role of gender on acceptance of mobile payment, Industrial Management & Data Systems, 114, 220, 10.1108/IMDS-03-2013-0137

Lin, 2013, Determining the relative importance of mobile banking quality factors, Computer Standards & Interfaces, 35, 195, 10.1016/j.csi.2012.07.003

Liu, 2011, The effects of relationship quality and switching barrierson customer loyalty, International Journal of Information Management, 31, 71, 10.1016/j.ijinfomgt.2010.05.008

Luo, 2010, Examining multi-dimensional trust andmultifaceted risk in initial acceptance of emerging technologies: An empirical study of Mobile banking services, Decision Support Systems, 49, 222, 10.1016/j.dss.2010.02.008

Mallat, 2007, Exploring consumer adoption of mobile payments- a qualitative study, The Journal of Strategic Information Systems, 16, 413, 10.1016/j.jsis.2007.08.001

Mazurowski, 2008, Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance, Neural Networks, 21, 427, 10.1016/j.neunet.2007.12.031

McCoy, 2007, Applying TAM across cultures: The need for caution, European Journal of Information Systems, 16, 81, 10.1057/palgrave.ejis.3000659

McKnight, 2002, The impact of initial consumer trust on intentions to transact with a website: A trust building model, The Journal of Strategic Information Systems, 11, 297, 10.1016/S0963-8687(02)00020-3

Meola, 2016

Moon, 2001, Extending the TAM for a world-wide-Web context, Information & Management, 38, 217, 10.1016/S0378-7206(00)00061-6

Negnevitsky, 2011

Oliveira, 2014, Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM, International Journal of Information Management, 34, 689, 10.1016/j.ijinfomgt.2014.06.004

Oliver, 1980, A cognitive model of the antecedents and consequences of satisfaction decisions, Journal of Marketing Research, 17, 460, 10.2307/3150499

Oman Economic Review (2017). Retrieved from http://oeronline.com/economy/9459.html.

Petter, 2008, Measuring information systems success: Models, dimensions, measures, and interrelationships, European Journal of Information Systems, 17, 236, 10.1057/ejis.2008.15

Petter, 2013, Information systems success: The quest for the independent variables, Journal of Management Information Systems, 29, 7, 10.2753/MIS0742-1222290401

Pitt, 1995, Service quality: A measure of information systems effectiveness, MIS Quarterly, 19, 173, 10.2307/249687

Rana, 2017, Citizens’ adoption of an electronic government system: Towards a unified view, Information Systems Frontiers, 19, 549, 10.1007/s10796-015-9613-y

Rana, 2016, Adoption of online public grievance redressal system in India: Toward developing a unified view, Computers in Human Behavior, 59, 265, 10.1016/j.chb.2016.02.019

Riffai, 2012, Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman, International Journal of Information Management, 32, 239, 10.1016/j.ijinfomgt.2011.11.007

Saunders, 2007

Shaibany, 2017

Shareef, 2018, Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages, Journal of Retailing and Consumer Services, 43, 54, 10.1016/j.jretconser.2018.03.003

Sharma, 2017, Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling, Information Systems Frontiers, 1, 1

Sharma, 2017, Structural equation model (SEM)-neural network (NN) model for predicting quality determinants of e-learning management systems, Behaviour & Information Technology, 36, 1053, 10.1080/0144929X.2017.1340973

Sim, 2014, Understanding and predicting the motivators of mobile music acceptance- A multi stage MRA-Artificial neural network approach, Telematics and Informatics, 31, 569, 10.1016/j.tele.2013.11.005

Slade, 2013, Mobile payment Adoption: Classification and review of existant literature, The Marketing Review, 13, 103, 10.1362/146934713X13699019904687

Slade, 2015, Modeling consumers’ adoption intentions of remote mobile payments in the UK: Extending UTAUT with innovativeness, risk and trust, Psychology & Marketing, 32, 860, 10.1002/mar.20823

Slade, 2015, Exploring consumer adoption of proximity mobile payments, Journal of Strategic Marketing, 23, 209, 10.1080/0965254X.2014.914075

Statista. (2018). Retrieved from https://www.statista.com/topics/779/mobile-internet/.

Straub, 2004, Validation guidelines for IS positivist research, Communications of the Association for Information Systems, 13, 380

Tam, 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

Tan, 2014, Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach, Computers in Human Behavior, 36, 198, 10.1016/j.chb.2014.03.052

Urbach, 2010, An empirical investigation of employee portal success, The Journal of Strategic Information Systems, 19, 184, 10.1016/j.jsis.2010.06.002

Veeramootoo, 2018, What determines success of an e government service? Validation of an integrative model of E-Filing continuance usage, Government Information Quarterly, 35, 161, 10.1016/j.giq.2018.03.004

Wixom, 2005, A Theoretical integration of user satisfaction and technology acceptance, Information Systems Research, 16, 85, 10.1287/isre.1050.0042

Wu, 2006, Measuring KMS success: a respecification of the DeLone and McLean’s model, Information & Management, 43, 728, 10.1016/j.im.2006.05.002

Wu, 2014, Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective, Journal of Business Research, 67, 2768, 10.1016/j.jbusres.2012.09.007

Yiu, 2007, Factors affecting the adoption of Internet Banking in Hong Kong—Implications for the banking sector, International Journal of Information Management, 27, 336, 10.1016/j.ijinfomgt.2007.03.002

Zhou, 2013, An empirical examination of continuance intention of mobile payment services, Decision Support Systems, 54, 1085, 10.1016/j.dss.2012.10.034

Zhou, 2014, An empirical examination of initial trust in mobile payment, Wireless Personal Communications, 77, 1519, 10.1007/s11277-013-1596-8