Taking Stock of Customization Research: A Computational Review and Interdisciplinary Research Agenda

A considerable body of literature has studied the idea of producing and marketing customized goods and services according to individual customer needs, addressing the growing importance of strategies like mass customization or personalization in business practice. However, customization research is characterized by scattered discussions along several unconnected streams of research in marketing, operations management, and information systems. With this study, we seek to outline the developments and hidden structures within 1,273 scholarly articles on customization to develop recommendations for future research. Applying recent advances in text mining, namely the Latent Dirichlet Allocation algorithm for topic modeling, allowed us to extract 60 topics and their corresponding terms and to map the temporal development trajectory of each topic. Furthermore, we evaluated the roles of research disciplines in shaping these topics. Based on this understanding, we empirically derive recommendations that will help scholars to address the interdisciplinary potentials and requirements of customization research.