Would You Recommend This Product? A Topic Modeling Approach to Understanding Review Behaviors

Online shopping platforms often highlight reviews to aid consumers’ decision-making process. The current research proposes that highlighted review should match between the reviewers’ and the browsing consumers’ purchasing goals (profiles). Using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method for topic modeling, we uncovered the hidden profiles that show a reviewer’s original purchasing goal, whether utility-oriented or hedonic-oriented. Subsequent analysis revealed that utility- and hedonic-oriented reviewers differ in certain review-writing and rating behaviors. The paper contributes to the literature by suggesting a new way to understand reviewers’ profiles from text data and resulting review behaviors. We also make a practical recommendation for shopping platforms in highlighting more relevant reviews

Why Did You Buy It? A Text Mining Approach to Understanding Purchasing Goals and Review Behaviors

Online reviews play a fundamental role in supporting purchase decisions and driving sales, but the sheer quantity and varying quality pose challenges for consumers to navigate. Using an unsupervised machine learning approach to extract latent topics from review texts, our paper demonstrates that shopping platforms can extract reviewers\u27 original purchasing goals (profiles) varying in the degree of utility and hedonic orientations. These profiles significantly alter their review behaviors in terms of effort, complexity, sentiment, and rating decision. A follow-up experiment finds early evidence that future consumers perceive reviews that match their shopping orientation more favorably in terms of both argument quality and review helpfulness. The paper contributes a new approach to understanding reviewer behaviors and makes a practical recommendation to online shopping platforms to match reviewer and consumer purchasing orientations

An Examination of Digital Nudging Scarcity Effect in E-Commerce

With the onset of the pandemic, online shopping applications have seen a rise in consumer traffic in the past two years. E-commerce sales has grown by 35% year over year, with online penetration remaining 30% higher than pre-Covid levels (McKinsey & Company., 2021). Given the ubiquitous use of e-commerce applications, it becomes increasingly important for e-retailers to optimize the design of their web stores in order to attract consumers and gain competitive advantages. In particular, many e-commerce applications have incorporated digital nudging techniques to subtly change consumers’ online choice environments and influence their purchase decisions. One of the commonly used digital nudging techniques is associating scarcity with an online product offering or promotion. Research suggests that in an offline setting, a person’s desirability of a product option tends to increase, as the perceived availability of the option decreases (Cialdini, 1993). Nevertheless, because peoples’ behaviors in an offline setting can be different from those in an online setting (Schneider et. al., 2018), it remains largely unclear the extent to which digital nudging through scarcity would elicit comparable effects among online shoppers. Furthermore, previous studies indicate that time-related and quantity-related scarcity message can have different effects on consumers’ purchase intentions (Aggarwal et al., 2011). Yet, little is known how consumers would respond to these two forms of scarcity differently when they are induced through digital nudging. In this research, we suggest that scarcity-related digital nudges can influence an online consumer’s choice architecture through multiple processes, each of which can produce different effects on the consumer’s valuation and intention to purchase a product online. Drawn on the Elaboration Likelihood Model (Petty & Cacioppo, 1986 & Wagner & Petty, 2022), we posit that the influence of the two forms of scarcity-related digital nudging (i.e., limited time vs. limited quantity) can vary at different points along the elaboration continuum. When consumers are unable or unmotivated to assess the core merits of an online product offering, both forms of digital nudging can institute a “scarce-is-good” heuristic and enhance product valuation and purchase intention (Cialdini, 1993). When elaboration is unconstrained to be high or low, the two forms of digital nudging can motivate consumers to scrutinize the reasons of the scarcity. Lastly, when elaboration is high, we suggest that the two forms of digital nudging can serve as a validation of consumers’ own valuation of the scarce product option. As compared to digital nudging through limited time, nudging through limited quantity is more likely to be construed as a result of high demand rather than limited supply (Aggarwal et al., 2011). Thus, we suggest that the latter is likely to induce more favorable responses among online consumers than the former. To test the effects of the two scarcity-related digital nudges on consumers’ product valuation and purchase intentions, we plan to conduct vignette-based randomized laboratory experiments as well as an online field experiment. Our research adds to the extant literature on digital nudging. Our findings can help to shed light on how and when scarcity-related digital nudging can influence consumers’ purchase decisions in a digital environment. By highlighting the difference in nudging through time-based and quantity-based scarcity, the present research can also help to inform interface designers of why a specific form of scarcity-related nudge would be appropriate for an intended online environment

The Effects of Digitally Delivered Nudges in a Corporate Wellness Program

We investigate how two digitally delivered nudges, namely light social support (non-verbal cues such as kudos or likes) and motivational messaging, affect employees’ self-reported physical activity in an online, corporate wellness program. Within this unique field setting with data over several years, we find evidence that both types of nudges provide benefits beyond the effect of cash incentives. However, the effects vary by individuals, depending on whether the employee is active in exercising, and by time, depending on how long the employee has been in the wellness program. While light social support is found to be less effective over time, motivational messages are more effective with the duration in the program and generally more effective for inactive users. Our findings have implications for the design of wellness systems, suggesting different approaches depending on an employee’s current activity level and tenure with the program