Mobile applications in the personal development sector increasingly integrate goal-enabling technology features (GETFs), which allow users to define a service-related end goal, set implementation strategies through subgoals, and monitor progress. Little is known, however, about how the difficulty of goals chosen during GETF adoption affects subsequent app behaviors. This study examines whether customers who set more versus less difficult end goals and subgoals show greater engagement and retention, and whether firms can nudge customers toward goal-difficulty levels conducive to sustained engagement. Using behavioral data from an investment app that introduced GETFs, the authors employ hierarchical modeling with staggered synthetic control and instrumental variable regression to address self-selection and endogeneity. Results reveal substantial heterogeneity: Many adopters show no or negative engagement changes, whereas those selecting moderately challenging goals and subgoals significantly increase in-app investment actions, though not sign-ins. Higher engagement postadoption predicts improved retention after one year. A field experiment confirms that subgoal difficulty causally drives in-app actions. These findings suggest that personalized guidance during GETF adoption can enhance sustained engagement. Marketing managers are advised to tailor goal-setting features to individual needs, providing expert-like support. This research provides novel empirical evidence on goal-difficulty levels that most effectively promote app engagement.

We uncover the underlying factors that influence perceived trade-offs between sustainability and financial returns and risks, and the resulting real-world investment behaviour of micro-investors. Given the direct-to-consumer nature of new age investment platforms, the context for our study is framed within a consumer-centric context. Through a survey and conjoint experiment (383 investors), and analysis of actual investment decisions (for 89,744 micro-investors), we show that individual motives—specifically sustainability values and feelings of empowerment—are key drivers for sustainable investments, influencing willingness to forgo financial returns and the duration of investment. We provide practical implications for fostering sustainable investments through micro-investing platforms.

We examine the impact of social investing on charitable donations using a unique data set consisting of investment behaviors and donation transactions for more than 10,000 customers of an investment app platform. We find that investors switching to a recently introduced social fund reduced their donations, mainly in charities supporting causes similar to those of the social fund. However, 79% of the investors that switched to the social fund did not donate before switching, so the social fund attracted more people to fund social causes. Still, because of the substitution effect, we estimate social funds have a positive effect on society only if their annual contributions to social causes are greater than 3.2% of the balance invested. This paper was accepted by David Simchi-Levi, finance. Funding: This work was supported by the Henry Crown Institute of Business Research and the Jeremy Coller Foundation. Supplemental Material: Data files are available at https://doi.org/10.1287/mnsc.2022.4339 .

A theory-first paradigm tends to be the dominant approach in much academic marketing research. In this approach, a theory is borrowed, refined, or developed and then tested empirically. In this challenging-the-boundaries article, the authors make a case for an empirics-first approach. “Empirics-first” refers to research that (1) is grounded in (originates from) a real-world marketing phenomenon, problem, or observation, (2) involves obtaining and analyzing data, and (3) produces valid marketing-relevant insights without necessarily developing or testing theory. The empirics-first approach is not antagonistic to theory but rather can serve as a stepping-stone to theory. The approach lends itself well to today’s data-rich environment, which can reveal novel research questions untethered to theory. The present article describes the underlying principles of an empirics-first approach, which consists of exploring a domain purposefully without preconceptions. Using a rich set of published examples, the authors offer guidance on how to implement empirics-first research and how it can lead to valuable knowledge development. Advice is also offered to scholars on how to report empirics-first research and to reviewers and to editorial teams on how to evaluate it. The ultimate objective is to pave a way for the empirics-first approach to enter the mainstream of academic marketing research.

Predicting consumers’ purchasing behaviors is critical for targeted advertisement and sales promotion in e-commerce. Human faces are an invaluable source of information for gaining insights into consumer personality and behavioral traits. However, consumer’s faces are largely unexplored in previous research, and the existing face-related studies focus on high-level features such as personality traits while neglecting the business significance of learning from facial data. We propose to predict consumers’ purchases based on their facial features and purchasing histories. We design a semi-supervised model based on a hierarchical embedding network to extract high-level features of consumers and to predict the top- N purchase destinations of a consumer. Our experimental results on a real-world dataset demonstrate the positive effect of incorporating facial information in predicting consumers’ purchasing behaviors.

Despite the importance of social capital (e.g. external network ties, social interaction, and relationship quality) and entrepreneurial orientation (e.g. proactiveness, innovativeness, and risk taking) for firm performance, little is known about the mechanisms that benefit firms from the interplay among these factors. It has also been unclear which entrepreneurial processes or activities assist in transforming social capital into positive performance outcomes. In this study, we clarify how and why entrepreneurial orientation assists in transforming social capital into firm performance. A survey of 198 entrepreneurs in Vietnam shows that entrepreneurial firms need both bridging and bonding capital (i.e. external network ties and social interaction) for enhanced relationship quality. While proactiveness mediates the impact of relationship quality on firm performance, findings show no support for the mediating role of innovativeness and risk taking. In other words, proactiveness converts relationship quality into enhanced firm performance, while innovativeness and risk taking do not.

Most current studies on survey analysis and risk tolerance modelling lack professional knowledge and domain-specific models. Given the effectiveness of generative adversarial learning in cross-domain information, we design an Asymmetric cross-Domain Generative Adversarial Network (ADGAN) for domain scale inequality. ADGAN utilizes the information-sufficient domain to provide extra information to improve the representation learning on the information-insufficient domain via domain alignment. We provide data analysis and user model on two data sources: Consumer Consumption Information and Survey Information. We further test ADGAN on a real-world dataset with view embedding structures and show ADGAN can better deal with the class imbalance and unqualified data space than state-of-the-art, demonstrating the effectiveness of leveraging asymmetrical domain information.

Prior research in charitable giving and prosocial behavior has identified that demographic and psychological factors can influence consumer intentions to donate. However, such research has mostly examined the net effects of such factors. The current research aims to address this important issue by employing fuzzy-set qualitative comparative analysis (fsQCA) and exploring different combinations of moral emotion, moral judgment, moral identity, and demographic factors that lead to higher customer intentions to donate time and money. In doing so, this research provides concrete managerial implications by highlighting the importance of personalized and targeted marketing strategies.

Firms typically utilize loyalty programs to encourage repeat purchases. In particular, frequency reward programs and customer tier programs are the two predominant loyalty program structures. However, there is little insight on the conditions under which these loyalty program structures can be more effective. This research investigates how different, discrete positive emotions such as pride and happiness can leverage the effectiveness of these loyalty program structures. Findings from four studies show that while pride and happiness can similarly increase repurchase intentions following a frequency reward program, only pride (vs. happiness) differentially increases repurchase intentions following a customer tier program. Further, the effects of these emotions are mediated by two distinct paths: the intensity of positive affect (for frequency reward programs) and signaling motives (for customer tier programs). These findings have beneficial implications for marketers and firms in employing appropriate positive emotion appeals to promote their loyalty programs.

Purpose Despite the fact that prosocial motivation is related to word of mouth (WOM), few studies have been conducted to investigate the psychological and behavioral processes that mediate the two constructs. This study aims to explore customers’ relational interactions, specifically customer-to-employee interaction (via customer participation), customer-to-customer interaction and customer-to-brand interaction (via brand commitment), as mediators of the prosocial motivation–WOM linkage. Specifically, this paper examines the serial mediation model, in which prosocial motivation increases customer participation and customer-to-customer interaction, which in turn increase brand commitment and WOM sequentially. Design/methodology/approach This study collected survey data from two different samples, including higher degree research education and fitness gym services (highly interactive, people-processing service contexts), and used partial least square method to analyze the multiple serial mediations. Findings The results of this study show two serial mediating processes through which prosocial motivation influences WOM: 1. prosocial motivation → customer participation → brand commitment → WOM; and 2. prosocial motivation → customer-to-customer interaction → brand commitment → WOM. Practical implications The findings provide managerial insights into how marketers can foster a more interactive service environment to encourage prosocial customers to engage in WOM more effectively. Originality/value This study contributes to the literature on services WOM by illustrating the behavioral and psychological processes that underlie the effect of prosocial motivation on WOM.

Drawing upon signaling theory and social identity theory, we developed a theoretical model that illuminates the role of brand credibility as an important basis on which customers form and signal their brand-related self and social identities via positive word-of-mouth (WOM). The proposed model was empirically tested using time-lagged data from a sample of 249 students of a top university in a metropolitan city. The findings show that the credibility of a brand is of paramount importance for the customer in developing a sense of oneness with the brand as well as a sense of affinity with other users of the brand. Our study also offers the new insight that brands serve as symbolic devices that customers use in their evolving thought processes that create a link between personal identity and social identity. In addition, brand–social connection is essential in spreading positive WOM. Finally, our findings support a sequential mediation model in which brand credibility is positively related to brand–self connection and brand–social connection, which in turn are positively associated with positive WOM.