Why do customers use self-service information technologies in retail? The mediating effect of perceived service quality

To ensure a high level of service quality (SQ), retailers think about offering self-service information technologies (SSIT) at the point of sale. However, the explanatory value of the SQ for SSIT adoption is barely researched. Thus, the present study examines the mediation effect of SQ within the technology acceptance model. Building on data from a laboratory experiment using a fully functional application for Tablet PCs, the partial least squares approach is applied. The findings reveal that the perceived SQ partially mediates the effect of the attitude towards using on the intention to reuse. Therefore, retailers have to emphasize the service-related value of SSITs.

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

[2]  Rosalind C. Paige,et al.  An Exploratory Study on Consumer Perceptions of Service Quality in Technology-Based Self-Service , 2006 .

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

[4]  Hyun-Joo Lee,et al.  Interpersonal service quality, self-service technology (SST) service quality, and retail patronage , 2013 .

[5]  Dhruv Grewal,et al.  Internet retailing: enablers, limiters and market consequences , 2004 .

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

[7]  Nick Lee,et al.  Revolution in Sales: The Impact of Social Media and Related Technology on the Selling Environment , 2012 .

[8]  Eleonora Pantano,et al.  New technologies and retailing: Trends and directions , 2010 .

[9]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[10]  Mary Jo Bitner,et al.  Services Marketing: Integrating Customer Focus Across the Firm , 1996 .

[11]  J. J. Cronin,et al.  Removing the contextual lens: A multinational, multi-setting comparison of service evaluation models , 2005 .

[12]  João F. Proença,et al.  A comparison of users and non‐users of banking self‐service technology in Portugal , 2011 .

[13]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[14]  A. Parasuraman,et al.  The Behavioral Consequences of Service Quality , 1996 .

[15]  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..

[16]  B. Weijters,et al.  Determinants and Outcomes of Customers' Use of Self-Service Technology in a Retail Setting , 2007 .

[17]  Terry L. Childers,et al.  HEDONIC AND UTILITARIAN MOTIVATIONS FOR ONLINE RETAIL SHOPPING BEHAVIOR , 2001 .

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

[19]  J. J. Cronin,et al.  Some New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach , 2001 .

[20]  Mark Snyder,et al.  Personality and social behavior , 1985 .

[21]  Youjae Yi,et al.  The impact of other customers on customer citizenship behavior , 2013 .

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

[23]  Brian I. Spaid,et al.  Service failure and recovery in using technology-based self-service: effects on user attributions and satisfaction , 2012 .

[24]  N. Malhotra,et al.  Positive and Negative Affectivity as Mediators of Volunteerism and Service-Oriented Citizenship Behavior and Customer Loyalty , 2012 .

[25]  A. Parasuraman,et al.  A Conceptual Model of Service Quality and Its Implications for Future Research , 1985 .

[26]  J. Nunnally.  Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .

[27]  Mary Jo Bitner,et al.  The influence of technology anxiety on consumer use and experiences with self-service technologies , 2003 .

[28]  Kerstin Liehr-Gobbers,et al.  Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach , 2010 .

[29]  P. A. Dabholkar.  Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality , 1996 .

[30]  Gian Luca Marzocchi,et al.  Self-scanning technologies in retail: Determinants of adoption , 2006 .

[31]  Vinit Parida,et al.  Antecedents of Technology-Based Self-Service Acceptance: A Proposed Model , 2012 .

[32]  M. Meuter,et al.  Self‐service technology adoption: comparing three technologies , 2005 .

[33]  Kristopher J Preacher,et al.  SPSS and SAS procedures for estimating indirect effects in simple mediation models , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[34]  Uolevi Lehtinen,et al.  Two Approaches to Service Quality Dimensions , 1991 .

[35]  Tim Hughes,et al.  Adopting self-service technology to do more with less , 2013 .

[36]  Cees J. Gelderman,et al.  Choosing self-service technologies or interpersonal services—The impact of situational factors and technology-related attitudes , 2011 .

[37]  Cheryl Burke Jarvis,et al.  A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research , 2003 .

[38]  Geoffrey S. Hubona,et al.  The mediation of external variables in the technology acceptance model , 2006, Inf. Manag..

[39]  Anne L. Roggeveen,et al.  Understanding the co-creation effect: when does collaborating with customers provide a lift to service recovery? , 2012 .

[40]  A. Fairhurst,et al.  The influence of consumer traits and demographics on intention to use retail self‐service checkouts , 2010 .

[41]  Mary Jo Bitner,et al.  Self-Service Technologies: Understanding Customer Satisfaction with Technology-Based Service Encounters , 2000 .

[42]  Izak Benbasat,et al.  Quo vadis TAM? , 2007, J. Assoc. Inf. Syst..

[43]  Mary Jo Bitner,et al.  Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies , 2005 .

[44]  Wolfgang Maass,et al.  In-store consumer behavior: How mobile recommendation agents influence usage intentions, product purchases, and store preferences , 2010, Comput. Hum. Behav..

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

[46]  Mary Jo Bitner,et al.  Servicescapes: The Impact of Physical Surroundings on Customers and Employees: , 1992 .

[47]  Hans van der Heijden.  Mobile decision support for in-store purchase decisions , 2006, Decis. Support Syst..

[48]  A. Kara,et al.  Supermarket self-checkout service quality, customer satisfaction, and loyalty: Empirical evidence from an emerging market , 2014 .

[49]  Pratibha A. Dabholkar,et al.  Technology-based service delivery: A classification scheme for developing marketing strategies , 1994 .

[50]  Neeru Malhotra,et al.  Antecedents and consequences of service quality in consumer evaluation of self-service internet technologies , 2008 .

[51]  Viswanath Venkatesh,et al.  Where To Go From Here? Thoughts on Future Directions for Research on Individual-Level Technology Adoption with a Focus on Decision Making , 2006, Decis. Sci..

[52]  V. Zeithaml,et al.  A Dynamic Process Model of Service Quality: From Expectations to Behavioral Intentions , 1993 .

[53]  Jan Marco Leimeister,et al.  Do Point of Sale RFID-Based Information Services Make a Difference? Analyzing Consumer Perceptions for Designing Smart Product Information Services in Retail Business , 2008, Electron. Mark..

[54]  A. Parasuraman,et al.  The nature and determinants of customer expectations of service , 1993 .

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

[56]  Ann Fairhurst,et al.  The importance of self‐service kiosks in developing consumers' retail patronage intentions , 2009 .

[57]  Gary Chamberlain,et al.  Longitudinal Analysis of Labor Market Data: Heterogeneity, omitted variable bias, and duration dependence , 1985 .

[58]  M. Sobel.  Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[59]  E. Pantano,et al.  Demand pull and technology push perspective in technology-based innovations for the points of sale: the retailers evaluation , 2014 .

[60]  A. Fairhurst,et al.  Gender differences in consumer evaluations of service quality: self-service kiosks in retail , 2013 .

[61]  Eleonora Pantano,et al.  The Design of an Advanced Virtual Shopping Assistant for Improving Consumer Experience , 2011 .

[62]  R. Bagozzi,et al.  An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors , 2002 .

[63]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[64]  Eun-Ju Lee,et al.  Understanding consumer motivation and behavior related to self‐scanning in retailing , 2003 .

[65]  Zheng Zhou,et al.  Development and validation of an instrument to measure user perceived service quality of information presenting Web portals , 2005, Inf. Manag..

[66]  Rudolf R. Sinkovics,et al.  The Use of Partial Least Squares Path Modeling in International Marketing , 2009 .

[67]  Arjun Chaudhuri,et al.  A Macro Analysis of the Relationship of Product Involvement and Information Search: The Role of Risk , 2000 .

[68]  James H. Gerlach,et al.  Consumer views of self-service technologies , 2008 .

[69]  Steven J Sherman,et al.  Parallals between attitudes and traits as predictors of behavior. , 1983, Journal of personality.

[70]  Michael Chih-Hung Wang,et al.  Determinants and consequences of consumer satisfaction with self‐service technology in a retail setting , 2012 .