An Individual Differences Approach in Adaptive Waving of User Checkout Process in Retail eCommerce

Developing a usable checkout process is pivotal for e-business success. However, recent research has shown that users frequently abandon their shopping carts and lacking a clear direction through the process. In this context, aiming to improve the usability and overall user experience of checkout processes in ecommerce Web-sites, this paper reports on a study, primarily inspired by concepts driven from theories of individual differences in cognitive processing, and considers content presentation and navigability as a measure of checkout usability and task quality. Concurrent think-aloud, short interviews and questionnaires were conducted with a convenient sample of 15 users to understand the preference of a particular type of checkout process, and users’ task completion time while interacting with ecommerce Web-sites for a set of different checkout scenarios. Preliminary results revealed that cognitive styles have an effect on users’ task completion and checkout process preference.

[1]  Jaewon Kang,et al.  Online Shopping Hesitation , 2006, Cyberpsychology Behav. Soc. Netw..

[2]  K. Reynolds,et al.  Hedonic shopping motivations , 2003 .

[3]  Panagiotis Germanakos,et al.  Modeling users on the World Wide Web based on cognitive factors, navigation behavior and clustering techniques , 2013, J. Syst. Softw..

[4]  Eileen Bridges,et al.  Hedonic and utilitarian shopping goals: The online experience , 2008 .

[5]  Angeline C. Scheinbaum,et al.  Beyond Buying: Motivations Behind Consumers’ Online Shopping Cart Use , 2009 .

[6]  Rian van der Merwe,et al.  A framework and methodology for evaluating e-commerce Web sites , 2003, Internet Res..

[7]  C. A. Moore,et al.  Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications , 1977 .

[8]  L. W. Webb,et al.  Students' methods of studying a certain subject--psychology. , 1920 .

[9]  Dirk Van den Poel,et al.  Predicting online-purchasing behaviour , 2005, Eur. J. Oper. Res..

[10]  Panagiotis Germanakos,et al.  Realizing Comprehensive User Profile as the Core Element of Adaptive and Personalized Communication Environments and Systems , 2009, Comput. J..

[11]  Corrado lo Storto,et al.  Evaluating ecommerce websites cognitive efficiency: an integrative framework based on data envelopment analysis. , 2013, Applied ergonomics.

[12]  Wendy W. Moe,et al.  Capturing evolving visit behavior in clickstream data , 2004 .

[13]  Shane W. Mathews,et al.  An Exploration of Online Shopping Cart Abandonment Syndrome–A Matter of Risk and Reputation , 2006 .

[14]  Andrew Boyd The goals, questions, indicators, measures (GQIM) approach to the measurement of customer satisfaction with e-commerce Web sites , 2002, Aslib Proc..

[15]  Ping Zhang,et al.  Satisfiers and dissatisfiers: a two-factor model for website design and evaluation , 2000 .

[16]  Ting Li,et al.  Examining the impact of rich media on consumer willingness to pay in online stores , 2013, Electron. Commer. Res. Appl..

[17]  Muhammad Muazzem Hossain,et al.  Why do shoppers abandon shopping cart? Perceived waiting time, risk, and transaction inconvenience , 2009 .

[18]  Xiaohui Liu,et al.  An Integrated Approach for Modeling Learning Patterns of Students in Web-Based Instruction: A Cognitive Style Perspective , 2008, TCHI.

[19]  R. Riding,et al.  Cognitive Styles—an overview and integration , 1991 .

[20]  Monika Kukar-Kinney,et al.  The determinants of consumers’ online shopping cart abandonment , 2010 .

[21]  Sriram Thirumalai,et al.  Customization of the online purchase process in electronic retailing and customer satisfaction: An online field study , 2011 .

[22]  Ian J. Deary,et al.  A new measure of Verbal–Imagery Cognitive Style: VICS , 2005 .

[23]  R. Bucklin,et al.  Modeling Purchase Behavior at an E-Commerce Web Site: A Task-Completion Approach , 2004 .