Customers' Intention to Use Digital Services in Retail Banking - An Information Processing Perspective

Service digitization increasingly impacts work and life. A frequent example is Internet banking. While customers act independently from time and space constraints, banks benefit from significantly lower transaction costs compared to branches. However, customers use online channels for distinct transactions and favor physical interactions with bank advisors for others. To understand the underlying drivers for the intention to use digital banking services, we derive a research model that is theoretically grounded in the Information Processing View. It is validated in a quantitative study with 338 evaluations among retail banking customers. The results indicate that customers’ information requirements and process risk negatively impact intended digital process use. In contrast, process experience positively impacts the intended digital process use. This paper is, to our best knowledge, the first to explore the role of information requirements and process-specific characteristics in detail. It guides practitioners in establishing more effective and efficient digital banking services.

[1]  Paul A. Pavlou,et al.  Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective , 2007, MIS Q..

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

[3]  R. Brislin The wording and translation of research instruments. , 1986 .

[4]  Chao-Min Chiu,et al.  Internet self-efficacy and electronic service acceptance , 2004, Decis. Support Syst..

[5]  Hock-Hai Teo,et al.  Conceptualizing and Testing a Social Cognitive Model of the Digital Divide , 2011, Inf. Syst. Res..

[6]  Carol Stoak Saunders,et al.  Information Processing View of Organizations: An Exploratory Examination of Fit in the Context of Interorganizational Relationships , 2005, J. Manag. Inf. Syst..

[7]  Daniel J. Veit,et al.  Which Processes Do Users Not Want Online? Extending Process Virtualization Theory , 2011, ICIS.

[8]  S. Isaacs Consumer's information needs: results of a national survey. , 1996, Health affairs.

[9]  Krista Neykova Customer Loyalty in Retail Banking , 2019, Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series.

[10]  Andrew B. Whinston,et al.  Successfully Governing Business Process Outsourcing Relationships , 2006, MIS Q. Executive.

[11]  Omar El Sawy,et al.  Leveraging Standard Electronic Business Interfaces to Enable Adaptive Supply Chain Partnerships , 2007, Inf. Syst. Res..

[12]  Marilyn M. Helms,et al.  Consumer internet purchasing patterns: a congruence of product attributes and technology , 2006 .

[13]  D. Gefen,et al.  E-commerce: the role of familiarity and trust , 2000 .

[14]  Carla Ruiz-Mafé,et al.  Key drivers of internet banking services use , 2009, Online Inf. Rev..

[15]  Enid Mumford,et al.  Reengineering the Corporation: A Manifesto for Business Revolution , 1995 .

[16]  Richard L. Daft,et al.  Message Equivocality, Media Selection, and Manager Performance: Implications for Information Systems , 1987, MIS Q..

[17]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[18]  S. Neslin,et al.  Multichannel customer management: Understanding the research-shopper phenomenon , 2007 .

[19]  Glenn B. Voss,et al.  Determinants of online channel use and overall satisfaction with a relational, multichannel service provider , 2003 .

[20]  Michael L. Tushman,et al.  Information Processing as an Integrating Concept in Organizational Design. , 1978 .

[21]  Geoffrey Randall Principles of Marketing , 1993 .

[22]  K. Jöreskog,et al.  Intraclass Reliability Estimates: Testing Structural Assumptions , 1974 .

[23]  Nils Urbach,et al.  Structural Equation Modeling in Information Systems Research Using Partial Least Squares , 2010 .

[24]  D. Straub,et al.  Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly , 2012 .

[25]  R. Daft,et al.  A Tentative Exploration into the Amount and Equivocality of Information Processing in Organizational Work Units. , 1981 .

[26]  Henry H. Bi,et al.  The Impact of Process Mapping on Transparency , 2008 .

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

[28]  Chechen Liao,et al.  Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model , 2011, Electron. Commer. Res. Appl..

[29]  Sandra Slaughter,et al.  Research Commentary - The Design, Use, and Consequences of Virtual Processes , 2010, Inf. Syst. Res..

[30]  H. Winklhofer,et al.  Applying the technology acceptance model to the online retailing of financial services , 2006 .

[31]  Marios Koufaris,et al.  Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior , 2002, Inf. Syst. Res..

[32]  Tommi Laukkanen,et al.  The role of information in mobile banking resistance , 2010 .

[33]  Izak Benbasat,et al.  Addressing the What and How of Online Services: Positioning Supporting-Services Functionality and Service Quality for Business-to-Consumer Success , 2008, Inf. Syst. Res..

[34]  S. Geisser A predictive approach to the random effect model , 1974 .

[35]  Paul A. Pavlou,et al.  Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior , 2006, MIS Q..

[36]  Janni Nielsen,et al.  European Conference on Information Systems (ECIS) , 2008 .

[37]  Kai Wang,et al.  Business–IT fit in e‐procurement systems: evidence from high‐technology firms in China , 2008, Inf. Syst. J..

[38]  Christoph Rosenkranz,et al.  Why People Reject or Use Virtual Processes: A Test of Process Virtualization Theory , 2013, AMCIS.

[39]  Detmar W. Straub,et al.  Validation in Information Systems Research: A State-of-the-Art Assessment , 2001, MIS Q..

[40]  Rajeev Sharma,et al.  The Contingent Effects of Training, Technical Complexity, and Task Interdependence on Successful Information Systems Implementation , 2007, MIS Q..

[41]  Russel L. Thompson,et al.  A Meta-Analysis of Response Rates in Web- or Internet-Based Surveys , 2000 .

[42]  Eric Overby,et al.  Process Virtualization Theory and the Impact of Information Technology , 2008, Organ. Sci..

[43]  Andrew B. Whinston,et al.  An Empirical Analysis of the Impact of Information Capabilities Design on Business Process Outsourcing Performance , 2010, MIS Q..

[44]  Paul A. Pavlou,et al.  Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model , 2003, Int. J. Electron. Commer..

[45]  S. Sills,et al.  Innovations in Survey Research , 2002 .

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

[47]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[48]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[49]  Izak Benbasat,et al.  Information Security Policy Compliance: An Empirical Study of Rationality-Based Beliefs and Information Security Awareness , 2010, MIS Q..

[50]  Bilal Balci The Impact of Perceived Process Characteristics on Process Virtualizability , 2014, ECIS.

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

[52]  Shuiwang Ji,et al.  Partial Least Squares , 2016 .

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

[54]  O. John,et al.  Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German , 2007 .

[55]  J. Webster,et al.  Making Connections: Complementary Influences on Communication Media Choices, Attitudes, and Use , 2000 .

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

[57]  Wolfgang E. Ebbers,et al.  Electronic government: Rethinking channel management strategies , 2008, Gov. Inf. Q..

[58]  Varun Grover,et al.  Examining the Relational Benefits of Improved Interfirm Information Processing Capability in Buyer-Supplier Dyads , 2013, MIS Q..

[59]  P. K. Kannan,et al.  E-service: a new paradigm for business in the electronic environment , 2003, CACM.

[60]  P. Trott,et al.  Exploring the adoption of a service innovation: A study of Internet banking adopters and non-adopters , 2009 .

[61]  Steve Howard,et al.  Putting Yourself in the Picture: An Evaluation of Virtual Model Technology as an Online Shopping Tool , 2011, Inf. Syst. Res..

[62]  Ting Li,et al.  Information capability and value creation strategy: advancing revenue management through mobile ticketing technologies , 2009, Eur. J. Inf. Syst..

[63]  Kate E. Stewart,et al.  The Diffusion of Online Banking , 2003 .

[64]  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..

[65]  Richard L. Daft,et al.  Organizational information requirements, media richness and structural design , 1986 .

[66]  N. J. Black,et al.  Modelling consumer choice of distribution channels: an illustration from financial services , 2002 .

[67]  Heikki Karjaluoto,et al.  Consumer acceptance of online banking: an extension of the technology acceptance model , 2004, Internet Res..

[68]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .

[69]  S. Kale,et al.  Consumer perceptions of Internet banking in Finland: The moderating role of familiarity , 2008 .

[70]  Rikard Larsson,et al.  Organization and Customer: Managing Design and Coordination of Services , 1989 .

[71]  Jason Kuruzovich,et al.  Marketspace or Marketplace? Online Information Search and Channel Outcomes in Auto Retailing , 2008, Inf. Syst. Res..

[72]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

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

[74]  William Lewis,et al.  Does PLS Have Advantages for Small Sample Size or Non-Normal Data? , 2012, MIS Q..

[75]  Margaret Tan,et al.  Factors Influencing the Adoption of Internet Banking , 2000, J. Assoc. Inf. Syst..

[76]  Paul A. Pavlou,et al.  Psychological Contract Violation in Online Marketplaces: Antecedents, Consequences, and Moderating Role , 2005, Inf. Syst. Res..

[77]  Jung-Kuei Hsieh,et al.  The challenge for multichannel services: Cross-channel free-riding behavior , 2011, Electron. Commer. Res. Appl..

[78]  France Bélanger,et al.  Trust and Risk in eGovernment Adoption , 2008, AMCIS.

[79]  Chao-Min Chiu,et al.  A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior , 2006, Int. J. Hum. Comput. Stud..

[80]  France Bélanger,et al.  The utilization of e‐government services: citizen trust, innovation and acceptance factors * , 2005, Inf. Syst. J..

[81]  S. Sills,et al.  Innovations in Survey Research , 2002 .

[82]  Viswanath Venkatesh,et al.  European Conference on Information Systems ( ECIS ) 5-15-2012 DEVELOPMENT AND VALIDATION OF AN INSTRUMENT TO MEASURE THE SERVICE-CHANNEL FIT OF ELECTRONIC BANKING SERVICES , 2017 .

[83]  Gaby Odekerken-Schröder,et al.  Using PLS path modeling for assessing hierarchial construct models: guidelines and impirical illustration , 2009 .

[84]  D. Reibstein What attracts customers to online stores, and what keeps them coming back? , 2002 .

[85]  M. Stone Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[86]  Sonja Grabner-Kräuter,et al.  Consumer acceptance of internet banking: the influence of internet trust , 2008 .

[87]  Toni M. Somers,et al.  Impact of Environmental Uncertainty and Task Characteristics on User Satisfaction with Data , 2004, Inf. Syst. Res..

[88]  Wesley Shu,et al.  How to improve consumer attitudes toward using credit cards online: An experimental study , 2012, Electron. Commer. Res. Appl..

[89]  Michel Tenenhaus,et al.  PLS path modeling , 2005, Comput. Stat. Data Anal..