Customers do not always prefer personalised products: The role of personalized options range in personalization

초록

Existing research on personalization has verified that customers perceive personalized products more highly than standard alternatives. Although many business practitioners are apparently convinced that providing various assortments or personalizing options is inevitably superior to standardization in securing market share, the empirical result of this paper suggests that personalization is not necessarily the optimal strategy. This research argues that customers prefer standard products over personalized alternatives when the range of personalization is perceived as excessive. That is, customers are more likely to select standard products over personalized alternatives when faced with inordinately complex decision-making. This study tests four hypotheses: (1) As the range of personalizing options steadily increases beyond a customer-perceived optimal point, attitudes toward personalized products will increasingly assume the form of an inverted U (i.e., inverted bell curve); (2) As the range of personalizing options steadily increases beyond a customer-perceived optimal point, purchase intention for personalized products will increasingly assume the form of an inverted U; (3) Customers will demonstrate a more positive attitude for standard products over personalized products with a higher level of personalizing options beyond a customerperceived optimal point; (4) Customers will demonstrate a higher purchase intention for standard products over personalized products having a higher level of personalizing options beyond a customer-perceived optimal point. Results indicate that, given the condition of overcomplexity, product attitude and purchase intentions regarding personalization will be characterized by an inverted U-shape pattern. In addition, the results reveal that customers prefer standard products over personalized alternatives when the range of personalizing options exceeds a customer-perceived optimal point.

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