Selected Publications
A Model of Brand Architecture Choice: A House of Brands vs. A Branded House
( Yu, Jungju )MARKETING SCIENCE2021-01
Abstract
Some firms that operate in multiple product markets use the same brand in different markets, whereas others use different brands in different markets. This research investigates in which product markets a firm should use the same or different brands and how this decision depends on the relatedness of product markets. To answer this question, I propose a framework of market relatedness that characterizes the relationships among distinct product markets from the supply side (e.g., shared production technology) and demand side (e.g., correlated customer preferences). This framework is applied to a model of reputation in which a multiproduct firm's product quality is jointly determined by its hidden capability type (i.e., adverse selection) and hidden choice of effort level (i.e., moral hazard) in each product market. Consumers obtain noisy information about the firm by observing its track record, that is, product quality produced in the past. Umbrella branding allows consumers to pool the firm's track record across different product markets and form expectations about the product quality based on market relatedness. The analysis shows that umbrella branding is optimal if supply-side relatedness is high and demand-side relatedness is not too high. However, if the product markets are closely related in both dimensions, then independent branding may be optimal because, as an umbrella brand, the firm faces a temptation to exploit positive information spillover across product markets through its shared brand name. By using different brand names, a firm can credibly commit to investing in all product markets and thereby earn higher profits. Finally, this paper provides implications for an umbrella brand's customer relationship management strategy whether to serve the same or distinct customer segments with its products.
Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach
( Shin, Donghyuk | He, Shu | Lee, Gene Moo | Whinston, Andrew B. | Cetintas, Suleyman | Lee, Kuang-Chih )MIS Quarterly2020-12
Abstract
This research methods article proposes a visual data analytics framework to enhance social media research using deep learning models. Drawing on the literature of information systems and marketing, complemented with data-driven methods, we propose a number of visual and textual content features including complexity, similarity, and consistency measures that can play important roles in the persuasiveness of social media content. We then employ state-of-the-art machine learning approaches such as deep learning and text mining to operationalize these new content features in a scalable and systematic manner. For the newly developed features, we validate them against human coders on Amazon Mechanical Turk. Furthermore, we conduct two case studies with a large social media dataset from Tumblr to show the effectiveness of the proposed content features. The first case study demonstrates that both theoretically motivated and data-driven features significantly improve the model's power to predict the popularity of a post, and the second one highlights the relationships between content features and consumer evaluations of the corresponding posts. The proposed research framework illustrates how deep learning methods can enhance the analysis of unstructured visual and textual data for social media research.
How Does the Mobile Channel Reshape the Sales Distribution in E-Commerce?
( Park, Yongjin | Bang, Youngsok | Ahn, Jae-Hyeon )INFORMATION SYSTEMS RESEARCH2020-12
Abstract
Despite the prolitcratiun of studies on sales distributions in e-commerce, little is known about how such a distribution in online markets is affected by the presence of mobile channels, which have become a significant conduit for e-commerce. Using a large transaction data set from a leading e-marketplace in South Korea, this study empirically investigates (1) how the sales distribution in the mobile commerce channel is different from the sales distribution in the traditional personal computer (PC) channel and (2) how mobile commerce channel adoption (as a search and purchase channel) affects e-market users' search intensity and their aggregate sales distribution. Our analysis in comparing the sales distributions between the PC and mobile channels shows that transactions in the mobile channel are more concentrated on "head" products compared with PC channel sales. The subsequent user-level analysis, based on a difference-in-differences approach, reveals that mobile channel adopters search more but are less (more) likely to choose "tail" (head) products. This finding is contrary to our previous belief that more search activities lead to more tail product sales. The relationship between search intensity and head (tail) product sales, however, largely depends on the product categories. In the case of preference goods such as books, CDs, toys, and fashion items, adoption increased e-market users' search activities and resulted in more tail product sales. For quality goods such as PCs, phones, cameras, and digital appliances, however, adoption intensified the search activities but resulted in more head product sales. Finally, for convenience goods such as home supplies and processed foods, adoption discouraged search activities and decreased the choice of tail products. We discuss the theoretical implications of our findings.
Creating Mutual Gains to Leverage a Racially Diverse Workforce: The Effects of Firm-Level Racial Diversity on Financial and Workforce Outcomes Under the Use of Broad-Based Stock Options
( Han, Joo Hun | Shin, DuckJung | Castellano, William G. | Konrad, Alison M. | Kruse, Douglas L. | Blasi, Joseph R. )ORGANIZATION SCIENCE2020-11
Abstract
Despite substantial scholarly attention to workforce demographic diversity, existing research is limited in understanding whether or in what contexts firm-level racial diversity relates to performance and workforce outcomes of the firm. Drawing on social interdependence theory along with insights from social exchange and psychological ownership theories, we propose that the use of broad-based stock options granted to at least half the workforce creates the conditions supporting a positive relationship between workforce racial diversity and firm outcomes. We examine this proposition by analyzing panel data from 155 companies that applied for the "100 Best Companies to Work For" competition with responses from 109,314 employees over the five-year period from 2006 to 2010 (354 company-year observations). Findings revealed that racial diversity was positively related to subsequent firm financial performance and individual affective commitment and was not significantly associated with subsequent voluntary turnover rates, when accompanied by a firm's adoption of broad-based stock options. However, under the nonuse of broad-based stock options, racial diversity was significantly related to higher voluntary turnover rates and lower employee affective commitment, with no financial performance gains. By documenting the beneficial effects of financial incentives in diverse workplaces, this paper extends theory asserting the value of incentives for performance.
When Loyalty Goes Mobile: Effects of Mobile Loyalty Apps on Purchase, Redemption, and Competition
( Son, Yoonseock | Oh, Wonseok | Han, Sang Pil | Park, Sungho )INFORMATION SYSTEMS RESEARCH2020-09
Abstract
Avenues for the delivery of loyalty programs have rapidly shifted from plastic card schemes to mobile app-based initiatives, yet our understanding of the economic value presented by the latter (i.e., loyalty apps) has not kept pace with this development. We examine the effects of loyalty app adoption on customers' offline purchase patterns, reward redemption, and deal-prone behaviors as well as store-level competition in a multivendor loyalty program (MVLP) context, where multiple offline brands collaborate in the operation of point-sharing initiatives. Mobile-driven loyalty apps substantially lower consumer search costs, thereby enhancing on-demand information accessibility and facilitating the monitoring of reward points. Based on a unique data set that comprises information on customers' loyalty app adoption status, loyalty point redemption patterns, and purchase behaviors in MVLP environments, we investigate how the transition from plastic-based programs to loyalty apps influences the out-of-pocket spending and point redemption patterns of consumers. Our findings reveal that the adoption of loyalty apps is associated with an increase in purchases and the predilection for point redemption. Despite these positive outcomes, however, potential adverse consequences may arise in the form of deal-susceptible behaviors and reduced store-specific loyalty. Loyalty app adopters tend to be more vulnerable to deals, with these customers selectively buying highly discounted products of low margin. Additionally, loyalty app consumers visit more stores but spend less in a focal store, thereby diminishing loyalty to this specific store. These results have managerial implications on optimal mobile-based loyalty program designs and implementation, reward-driven platform strategies, and risk management initiatives in an MVLP setting.
