Latest Research Publications

Estimating the hazard function of customer patience time has become a necessary component of effective operational planning such as workforce staffing and scheduling in call centers. When customers get served, their patience times are right-censored. In addition, the exact event times in call centers are sometimes unobserved and naturally binned into time intervals, due to the design of data collection systems. We develop a TunT (Transform-unTransform) estimator that turns the difficult problem of nonparametric hazard function estimation into a regression problem on binned and right-censored data. Our approach starts with binning event times and transforming event count data with a mean-matching transformation, which enables a simpler characterization of the heteroscedastic variance function. A nonparametric regression technique is then applied to the transformed data. Finally, the estimated regression function is back-transformed to yield an estimator for the original hazard function. The proposed estimation procedure is illustrated using call center data to reveal interesting customer patience behavior, and health insurance plan trial data to compare the effect between treatment and control groups. The numerical study shows that our approach yields more accurate estimates and better staffing decisions than existing methods.

We analyze optimal auction mechanisms when bidders base costly entry decisions on their valuations, and bidders pay with a fixed royalty rate plus cash. With sufficient valuation uncertainty relative to entry costs, the optimal mechanism features asymmetry so that bidders enter with strictly positive but different (ex-ante) probabilities. When bidders are ex-ante identical, higher royalty rates—which tie payments more closely to bidder valuations—increase the optimal degree of asymmetry in auction design, further raising revenues. When bidders differ ex-ante in entry costs, the seller favors the low cost entrant; whereas when bidders have different valuation distributions, the seller favors the weaker bidder if entry costs are low, but not if they are high. Higher royalty rates cause the seller to favor the weaker bidder by less, and the strong bidder by more.

Given the positive bias toward attractive people in society, online sellers are justifiably apprehensive about perceptions of their profile pictures. Although the existing literature emphasizes the “beauty premium” and the “ugliness penalty,” the current studies of seller profile pictures on customer-to-customer e-commerce platforms find a U-shaped relationship between facial attractiveness and product sales (i.e., both beauty and ugliness premiums and, thus, a “plainness penalty”). By analyzing two large data sets, the authors find that both attractive and unattractive people sell significantly more than plain-looking people. Two online experiments reveal that attractive sellers enjoy greater source credibility due to perceived sociability and competence, whereas unattractive sellers are considered more believable on the basis of their perceived competence. While a beauty premium is apparent for appearance-relevant products, an ugliness premium is more pronounced for expertise-relevant products and for female consumers evaluating male sellers. These findings highlight the influence of facial appearance as a key vehicle for impression formation in online platforms and its complex effects in e-commerce and marketing.

We propose a functional censored quantile regression model to describe the time-varying relationship between time-to-event outcomes and corresponding functional covariates. The time-varying effect is modeled as an unspecified function that is approximated via B-splines. A generalized approximate cross-validation method is developed to select the number of knots by minimizing the expected loss. We establish asymptotic properties of the method and the knot selection procedure. Furthermore, we conduct extensive simulation studies to evaluate the finite sample performance of our method. Finally, we analyze the functional relationship between ambulatory blood pressure trajectories and clinical outcome in stroke patients. The results reinforce the importance of the morning blood pressure surge phenomenon, whose effect has caught attention but remains controversial in the medical literature. Supplementary materials for this article are available online.

We show that installing stronger risk management into financial institutions—a proposal widely discussed following the 2008 financial crisis—is insufficient to constrain institutions’ exposure to investment with lurking risk, such as asset-backed securities (ABS). Regulations affect the functioning of risk management: risk management constrains institutions’ exposure to risky ABS when they face mark-to-market reporting combined with capital requirements; however, this role is considerably weaker when capital requirements are combined with historical cost accounting. We find suggestive evidence that financial regulations affect risk management functions through promoting risk managers’ efforts in uncovering ABS risk and curbing executives’ incentives to take excessive risk.

Efforts to engage customers in cocreating new products have garnered much research attention from studies documenting customer cocreation’s (CC’s) positive impact on firm innovation and performance. Less research, however, has counterbalanced the bright side with the potential dark side of CC, especially as a strategy for multinational corporations (MNCs) operating in foreign markets. This study examines how MNC subsidiaries’ CC affects new product innovativeness and knowledge leakage to competitors. Adopting a broader agency perspective to recognize that subsidiaries often do not perform up to headquarters’ expectations due to both self-serving opportunism and honest incompetence, this study explores how CC effects are contingent on MNCs’ global management mechanisms. Using a dyadic managerial survey of 238 MNC subsidiaries, the authors find that MNCs can control knowledge leakage by implementing proper global integration and local adaptation mechanisms. However, CC may not improve new product innovativeness, except when the subsidiary has low local research-and-development staff influence. This study contributes to the CC literature by showing its benefits, challenges, and boundary conditions as a growing MNC innovation strategy.

Trust is key to relationship marketing. Although trust is bilateral, studies on the dispersion of trust among exchange parties remain limited, leaving the antecedents and outcomes of trust asymmetry largely underexplored. To fill the gaps, this study empirically examines the effects of different types of trust asymmetry on exchange performance and then investigates the institutional origins of trust asymmetry in international interfirm exchanges. Drawing on a survey of 134 international buyer–supplier relationships in China, the study finds that both calculative trust asymmetry and relational trust asymmetry have negative influences on exchange performance. The study also finds that formal institutional distance constrains calculative trust asymmetry and informal institutional distance increases relational trust asymmetry. Moreover, prior interactions and expectations of continuity significantly moderate the effects of formal and informal institutional distance. This study advances trust studies in cross-border settings.

Many people face problems of emotional distress. Early detection of high-risk individuals is the key to prevent suicidal behavior. There is increasing evidence that the Internet and social media provide clues of people’s emotional distress. In particular, some people leave messages showing emotional distress or even suicide notes on the Internet. Identifying emotionally distressed people and examining their posts on the Internet are important steps for health and social work professionals to provide assistance, but the process is very time-consuming and ineffective if conducted manually using standard search engines. Following the design science approach, we present the design of a system called KAREN, which identifies individuals who blog about their emotional distress in the Chinese language, using a combination of machine learning classification and rule-based classification with rules obtained from experts. A controlled experiment and a user study were conducted to evaluate system performance in searching and analyzing blogs written by people who might be emotionally distressed. The results show that the proposed system achieved better classification performance than the benchmark methods and that professionals perceived the system to be more useful and effective for identifying bloggers with emotional distress than benchmark approaches.

Firms often attribute their service employees’ competent performance to either dedicated effort or natural talent. However, it is unclear how such practices affect customer evaluations of service employees and customer outcomes. Moreover, prior work has primarily examined attributions of one’s own performance, providing little insight on the impact of attributions of others’ performance. Drawing on research regarding the warmth–competence framework and performance attributions, the current research proposes and finds that consumers expect a more communal-oriented and less exchange-oriented relationship when a service employee’s competent performance is attributed to dedicated effort rather than natural talent, as effort (vs. talent) attribution leads consumers to perceive the employee as warmer. The authors further propose customer helping behaviors as downstream consequences of relationship expectations, finding that effort (vs. talent) attribution is more likely to induce customers’ word-of-mouth and idea provision behaviors. The findings enrich existing literature by identifying performance attributions as a managerially meaningful antecedent of relationship expectations and offer practical guidance on how marketers can influence consumers’ relationship expectations and helping behaviors.