A Classification of Internet Retail Stores

This article describes an empirical method for classifying Internet retail sites for electronic commerce. The technique used 35 observable Internet retail site attributes and features of online stores as the raw data to classify the online stores into meaningful groups. This paper presents a classification of online retail stores based upon an August 1996 convenience sample of 137 Internet retail stores. Descriptive statistics for 44 variables provide a snapshot of key attributes and features of online stores. Subsequent cluster and factor analysis identified five distinct Web catalog interface categories: superstores, promotional stores, plain sales stores, one-page stores, and product listings. Online stores differ primarily on the three dimensions: size, service offerings, and interface quality. A preponderance of the stores in the study had limited product selection, few service features, and poor interfaces. This categorization provides a better understanding of the strategies pursued in Internet-based marketing and will be helpful for Internet retail store designers as well as for researchers to structure and target further analyses in this domain.

[1]  Ronald M. Lee,et al.  InterShop: Enhancing the Vendor/Customer Dialectic in Electronic Shopping , 1995, J. Manag. Inf. Syst..

[2]  Neff Walker,et al.  A classification of visual representations , 1994, CACM.

[3]  G. W. Milligan,et al.  A Review Of Monte Carlo Tests Of Cluster Analysis. , 1981, Multivariate behavioral research.

[4]  James J. Cappel,et al.  World Wide Web Uses for Electronic Commerce:Toward a Classification Scheme , 1996 .

[5]  Jonathan Grudin,et al.  Human Computer Interaction: The Year 2000 and Beyond , 1995, HCI.

[6]  T. Oum,et al.  Determinant Attributes in Retail Patronage: Seasonal, Temporal, Regional, and International Comparisons , 1983 .

[7]  Ben Shneiderman,et al.  Designing the user interface (videotape) , 1987 .

[8]  J. Louviere,et al.  Shopping-center patronage models: Fashioning a consideration set segmentation solution , 1990 .

[9]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[10]  Stephen J. Arnold,et al.  A Comparative Analysis of Determinant Attributes in Retail Store Selection , 1978 .

[11]  Avijit Ghosh,et al.  Hierarchical Models of Store Choice , 1989 .

[12]  P. English-Zemke Using color in online marketing tools , 1988 .

[13]  Girish N. Punj,et al.  Cluster Analysis in Marketing Research: Review and Suggestions for Application , 1983 .

[14]  Ben Shneiderman,et al.  Designing The User Interface , 2013 .

[15]  H. Miller Consumer Search and Retail Analysis , 1993 .

[16]  Patrali Chatterjee,et al.  Commercial Scenarios for the Web: Opportunities and Challenges , 1997, J. Comput. Mediat. Commun..

[17]  Jakob Nielsen,et al.  Chapter 4 – The Usability Engineering Lifecycle , 1993 .

[18]  Aaron Marcus Principles of effective visual communication for graphical user interface design , 1995 .

[19]  Jonathan Grudin,et al.  The case against user interface consistency , 1989, CACM.

[20]  Gerald M. Murch,et al.  Colour Graphics—Blessing or Ballyhoo? , 1985, Comput. Graph. Forum.

[21]  Murphy A. Sewall,et al.  A Choice Sets Model of Retail Selection , 1987 .

[22]  Peter A. Todd,et al.  Consumer Reactions to Electronic Shopping on the World Wide Web , 1996, Int. J. Electron. Commer..

[23]  George S. Day,et al.  Using Cluster Analysis to Improve Marketing Experiments , 1971 .