In today's increasingly complex and disruptive marketplace, retailers face mounting pressures from rising costs, shifting consumer expectations, and heightened regulatory scrutiny. Given these challenges, one might question whether this is the right time to focus on responsible retailing. However, this perspective often stems from a narrow and misguided view of responsible retailing as merely an added cost rather than a strategic imperative. Responsible retailing is not a short-term financial burden but a multifaceted framework that fosters long-term benefits for both businesses and society. Rather than postponing responsible retailing for more favorable economic conditions, the need for its adoption is more pressing than ever. Understanding how and why responsible retailing works is critical to ensuring its effective implementation in today's retail landscape.

To further this understanding, I have invited the founding scholars of the Center for Responsible Retailing at Maastricht University's School of Business and Economics to offer their insights. As pioneers in the field, they provide a comprehensive perspective on the concept, its impact, and its relevance in both academic research and retail practice. Their contributions in this guest editorial not only clarify misconceptions but also serve as a catalyst for further scholarly exploration, equipping retailers with the knowledge needed to integrate responsible retailing into their business models effectively.

Faced by increasing emphasis on health, manufacturers try to persuade consumers by using nutrition claims on their packaging. Although experimental research suggests that such claims influence consumer behavior in different ways, it remains unknown whether and to what extent they have an effect in actual grocery situations with large amounts of information to process. In this study, the authors investigate the effect of presence (stressing the presence of a healthy ingredient) and absence nutrition claims (stressing the absence of an unhealthy ingredient) on consumer purchase behavior using UK household scanner purchase data from 17 product categories during the years 2009–2012. They find that presence nutrition claims increase choice while absence nutrition claims decrease choice. Both types of nutrition claims do not influence the quantity purchased. Importantly, a nutrition claim’s effectiveness depends on SKU and category characteristics. Presence nutrition claims are more effective in healthy categories, and absence nutrition claims for SKUs with fewer promotions. At the same time, both nutrition claims are less effective for higher priced SKUs and more effective for brands with higher advertising spending. Absence nutrition claims are more effective when fewer SKUs in the category have the same type of nutrition claim, but presence nutrition claims benefit when more SKUs have the same type of nutrition claim

Manufacturers in the retailing sector extensively use online sales points of their own, known as online direct channels. This form of manufacturer encroachment offers consumers the possibility to purchase directly from the manufacturer and hence may cannibalize retailer sales. However, it may also create synergy effects by increasing brand awareness, which may create additional retailer sales. In this research, we investigate the cannibalistic versus synergetic nature of the relationship between an established online direct channel and the retail network and assess whether retailer characteristics related to competitive strength impact this relationship. Using unique sales data from the toy industry and vector autoregressive modeling, we find that the short-term cross-channel price elasticity of online direct channels on retailer sales is negative and significant, indicating a synergetic relationship on average. However, the impact is heterogenous across retailers. Our analysis reveals that acquisition utility components of competitive strength, such as price and innovativeness, especially for large items, can enhance synergetic effects and mitigate the risk of cannibalization. Transaction utility components, such as online presence or the number of physical stores, do not play a moderating role. 

With the help of more than 700 reviewers, we assess the reproducibility of nearly 500 articles published in the journal Management Science before and after the introduction of a new Data and Code Disclosure policy in 2019. When considering only articles for which data accessibility and hardware and software requirements were not an obstacle for reviewers, the results of more than 95% of articles under the new disclosure policy could be fully or largely computationally reproduced. However, for 29% of articles, at least part of the data set was not accessible to the reviewer. Considering all articles in our sample reduces the share of reproduced articles to 68%. These figures represent a significant increase compared with the period before the introduction of the disclosure policy, where only 12% of articles voluntarily provided replication materials, of which 55% could be (largely) reproduced. Substantial heterogeneity in reproducibility rates across different fields is mainly driven by differences in data set accessibility. Other reasons for unsuccessful reproduction attempts include missing code, unresolvable code errors, weak or missing documentation, and software and hardware requirements and code complexity. Our findings highlight the importance of journal code and data disclosure policies and suggest potential avenues for enhancing their effectiveness. 

Improving the healthiness of diets can be realized by replacing unhealthy with healthier product alternatives when shopping for groceries. For this strategy to be effective, shoppers need to consistently make healthier choices. However, shoppers may end up balancing the healthiness of their choices throughout the shopping trip, (partly) offsetting the benefits of a healthy product choice (e.g., low-fat milk) by an unhealthy subsequent choice (e.g., sugary cornflakes). Across two studies, one study with purchase data from a brick-and-mortar supermarket and one online experimental study, we empirically demonstrate that the relative healthiness of an initial product choice is indeed inversely related to the relative healthiness of the subsequent choice, regardless of the category of both products. That means: a relatively healthy choice is followed by a relatively unhealthier choice, and vice versa. Furthermore, the strength of this balancing effect differs depending on the nature of the product category; the dynamic effect is less pronounced when subsequently choosing within a vice (vs. virtue) product category. In the brick-and-mortar supermarket, the dynamics also become less pronounced as the shopping trip progresses. These findings contribute to literature on in-store decision-making and within-trip dynamics, and underscore the need for retailers to have a thorough understanding of these healthy shopping dynamics in order to effectively promote healthier baskets in support of the growing demand for healthy diets. 

Firms operating in non-contractual settings apply customer reactivation initiatives such as email messages to stimulate customers who have become inactive temporarily or permanently to resume their transaction activities. Thus, firms need to know which customers are inactive, and when a customer becomes inactive. Existing approaches struggle to distinguish active from inactive customers and do not provide time-scale estimates of when to send reactivation mails. To address these shortcomings, we develop an approach to target and time the sending of reactivation mails. Building on control chart methods, we introduce a gamma–gamma control chart, modelling the average customer interpurchase time and the variation therein to determine activity boundaries. Crossing these boundaries signals a potential change in a customer’s purchasing activity, providing a signal to initiate customer reactivation. A field experiment in the greetings and gifts industry, supported by several additional analyses, illustrates the improved performance of our approach when it comes to signaling customer activity against a wide range of competing models. The improved performance of our method occurs particularly in settings where customers vary strongly in purchase and inactivity patterns.

For customer-centric firms, churn prediction plays a central role in churn management programs. Methodological advances have emphasized the use of customer panel data to model the dynamic evolution of a customer base to improve churn predictions. However, pressure from policy makers and the public geared to reducing the storage of customer data has led to firms' ‘self-policing’ by limiting data storage, rendering panel data methods infeasible. We remedy these problems by developing a method that captures the dynamic evolution of a customer base without relying on the availability past data. Instead, using a recursively updated model our approach requires only knowledge of past model parameters. This generalized mixture of Kalman filters model maintains the accuracy of churn predictions compared to existing panel data methods when data from the past is available. In the absence of past data, applications in the insurance and telecommunications industry establish superior predictive performance compared to simpler benchmarks. These improvements arise because the proposed method captures the same dynamics and unobserved heterogeneity present in customer databases as advanced methods, while achieving privacy preserving data minimization and data anonymization. We therefore conclude that privacy preservation does not have to come at the cost of analytical operations.