All Publications
Users generate tremendous amounts of data on the Internet every day. This so-called user-generated content (UGC) is valuable input for organizations since it may include individual experiences, opinions, and desires with respect to the products and services they offer. To automatically process UGC, automated techniques, typically referred to as Needmining, have been developed. Existing Needmining approaches extract customer needs from UGC by binarily classifying unstructured textual data into need-content and no-need content. However, they are not able to extract the specific needs. We address this research gap by developing a decision support artifact that re-conceptualizes Needmining from a binary classification problem to a token-classification problem to extract specific needs from informative content. To achieve this, we break down customer needs into components, i.e. attributes and characteristics and develop a token classification artifact. The artifact accurately identifies the need-components and, therefore, can identify specific customer needs in user-generated content. We organize and discuss the value of the artifact's output and further enrich the model with sentiment data to distinguish relevant needs. If applied, the artifact can realize efficiency gains for decisionmakers in the field of product development as it automatically and quickly identifies relevant consumer needs.
In recent years, the emergence of highly successful digital multi-brand retailers has facilitated an omnichannel distribution strategy to become the norm for brands. Rather than relying solely on these multi-brand retailers, it is necessary for companies’ omnichannel strategy to establish strong brand-owned direct-to-consumer (D2C) webstores. To help D2C brands make decisions regarding distribution channel choices, this paper investigates the circumstances under which customers prefer brands’ D2C webstores over digital multi-brand retailers and how these circumstances vary across phases of the customer journey. The results from an extensive experimental study demonstrate that, depending on the customer journey, brands’ D2C webstores can compete with digital multi-brand retailers, particularly in product categories characterized by deep assortments, the need for extensive product information, exclusive products, or a high degree of personalization.
In recent years, service providers have identified the proactive postsales service (PPS) as a viable measure for preempting service failures and their negative consequences. Due to the high costs associated with PPSs, companies are looking for ways to increase their efficiency. To understand how companies can increase their revenues and lower their costs, this study investigates how cross-selling activities and different media types affect the impact of a PPS on inbound service calls and customer churn. Based on a large-scale field experiment in the telecommunications industry, as well as a controlled lab experiment, the results demonstrate the overall effectiveness of the PPS and indicate two mediating effects. While the effect of cross-selling on customer churn and service calls is mediated by the customers’ uncertainty regarding the company’s motives, it is the customers’ perception of privacy invasion that mediates the influence of the contact medium on the effectiveness of the PPS. Our finding that PPS contacts have to be clear in their message and should not be perceived as invasive is an indication of the importance of service-(post)sales ambidexterity.
In recent years, many industries have experienced the rise of digital platforms (e.g., eBay, Uber, or Takeaway.com). A common characteristic of these concepts is that they focus on fragmented markets populated by many small firms, which often show a high fluctuation. However, established diffusion models based on Bass (1969) do not account for fluctuation in the market potential, although the exit of adopters and the entry of new firms could change the diffusion curve significantly. Thus, we propose an extension of the Bass Model to account for the exit and entry of (potential) adopters and empirically test this framework in a real-world setting. Using two decades of adopter data of leading digital platforms and information on the complete market potential, we employ agent-based models to analyze the effects of fluctuation on the platform diffusion. Initial results confirm the existence of high fluctuation and indicate relevant impacts on the diffusion curve.
In recent years, many industries have experienced the rise of digital platforms (e.g., eBay, Uber, or Takeaway.com). A common characteristic of these concepts is that they focus on fragmented markets populated by many small firms, which often show a high fluctuation. However, established diffusion models based on Bass (1969) do not account for fluctuation in the market potential, although the exit of adopters and the entry of new firms could change the diffusion curve significantly. Thus, we propose an extension of the Bass Model to account for the exit and entry of (potential) adopters and empirically test this framework in a real-world setting. Using two decades of adopter data of leading digital platforms and information on the complete market potential, we employ agent-based models to analyze the effects of fluctuation on the platform diffusion. Initial results confirm the existence of high fluctuation and indicate relevant impacts on the diffusion curve.
Ethical leadership has so far mainly been featured in the organizational behavior domain and, as such, treated as an intra-organizational phenomenon. The present study seeks to highlight the relevance of ethical leadership for extra-organizational phenomena by combining the organizational behavior perspective on ethical leadership with a classical marketing approach. In particular, we demonstrate that customers may use perceived ethical leadership cues as additional reference points when forming purchasing intentions. In two experimental studies (N = 601 and N = 336), we find that ethical leadership positively affects purchasing intentions because of customers’ concerns for moral self-congruence. We show this by means of both mediation and moderation analyses. Interestingly, the effect of perceived ethical leadership on purchasing intentions holds over and above the ethical advertising claims (e.g., cause-related marketing) that are commonly used in marketing. We conclude by discussing the possible ramifications of ethical leadership beyond its effects on immediate employees.
Rewarding existing customers for the recruitment of new ones has become an increasingly popular acquisition tool for companies. However, when a company rewards the recruitment of a new customer, managers are unaware of whether the rewarded referral was actually necessary or whether “reward-scrounging” has occurred because the referral receiver would have converted anyway. As a consequence, companies risk overestimating the effectiveness of their referral programs, which is why gaining insights into how and when reward-scrounging occurs is crucial. In this study, we employ a large data set from the telecommunications industry to analyze the drivers of reward-scrounging. The results indicate that reward-scrounging reduces the effectiveness of referral reward programs over time and that its likelihood depends on both the referral sender's network position and the company's marketing activities. The findings are used to develop managerial means to alleviate the negative effects of reward-scrounging.
Geographic proximity has become increasingly relevant due to the growing number of marketing services that use consumers’ geographic locations, thus increasing the importance of gaining insights from this information. In five studies (both field and experimental), the authors analyze the effect of geographic proximity on social influence and demonstrate that not only social proximity but also perceived homophily can trigger social influence. They find that this effect holds under alternative representations of geographic distance and is confirmed for a range of different services and even for physical goods. Furthermore, the authors show that geographic proximity has a relative effect because the social influence of a closer sender is stronger than that of a more distant sender, regardless of the absolute distances. They present managerially relevant conditions under which the influence of geographic proximity not only is comparable to other types of information such as age or gender but also provides sufficient informational value for customers to offset differences among alternatives (e.g., due to higher prices) in trade-off decisions.
This paper critically examines the prevailing practice in empirical studies of social networks to define edges in communication networks as undirected. This approach is based on the assumption that communication is inherently reciprocal and, thus, directionality can be ignored. In contrast, we argue that this assumption of reciprocity does not hold true for regular communication channels, such as telephone or instant massaging. The present study uses large-scale observational data on communication in networks across four distinct channels to investigate the (im-)balance of dyads and its causes. We show that dyads with a dominant direction can make up to 73 % of all edges in a communication network. When analyzing potential causes for imbalanced communication patterns, we find that gender is a key driver for observed asymmetric relationships as females reveal significantly higher outbound shares, whereas high degrees of clustering counteract the phenomenon of imbalance.
In recent years, social media have become a popular channel through which customers and companies can interact. However, companies struggle to assess whether their investments in establishing and maintaining brand pages in social media actually meet their high expectations with respect to developing and retaining customers. Based on three empirical studies, the authors explore the role of interactions through corporate social media channels, such as Facebook brand pages, in customer relationship management. The results indicate that social media interactions indeed ease the upselling efforts and reduce the risk of churn. These positive effects offset the observed increases with regard to the number of service requests and the higher overall service cost. Thus, we ultimately find customers who interact with the brand on social media to be more profitable.
Referral programs have become a popular tool to use the customer base for new customer acquisition. We replicate the work of Schmitt et al. (2011) who find that referred customers are more loyal and valuable than customers acquired through other channels. While our results confirm that rewarded referrals indeed reduce the risk of customer churn, we do not find that referred customers are necessarily more valuable. Analysis of the relationship between senders and receivers of referrals demonstrates that demographic similarity drives the referred customer value.
Book pricing is problematic for two main reasons. First, because legal restrictions make pricing decisions irreversible. Second, because publishers must set prices for many books every year. Therefore, a sound knowledge of consumer reaction to price is essential for good pricing decisions. Our research examines consumer reactions to prices, provides price elasticities based on a large sample of fiction books, and creates a comprehensive set of quality measures and control variables. Our results show that once price endogeneity is considered, consumers are price elastic. Moreover, we find that the price elasticity for hardcover books is substantially smaller than for paperbacks.
