Past research in operations management and marketing on inventory levels and product variety has predominantly focused on their effects on brand performance indicators, such as sales and market share, while overlooking the influence on consumers’ perceptions of brands. Brand perceptions, encompassing reputation, quality, credibility, and emotional associations, go beyond typical revenue metrics and offer foresight into a brand’s future performance. Hence, understanding the effects of inventory and product variety on brand perceptions is crucial, and that constitutes the main contribution of this paper.

This article examines the role of Generative Artificial Intelligence (GenAI) in the context of marketing education, highlighting its substantial impact on the field. The study is based on an analysis of how GenAI, particularly through the use of Large Language Models (LLMs), functions. We detail the operational mechanisms of LLMs, their training methods, performance across various metrics, and the techniques for engaging with them via prompt engineering.

Private labels (PL), also known as store brands or private brands, account for hundreds of billions of dollars in consumer packaged goods sales every year. PLs build store loyalty, improve margins and have been a key factor in changing the balance of power between retailers and national brand (NB) manufacturers. Thus, retailers around the world have a stake in pushing their own store brands. Yet, while PLs enjoy great success in Western, and increasingly Central, Europe, their performance is much more muted in the world's largest market, the United States, and in emerging markets. Why is that the case?

In the sales process in business markets, customers often are assisted by two types of sales reps: customer-focused reps (CSRs) and operations-focused reps (OSRs), who work together to ensure smooth buying experiences. Because these reps work jointly, selling firms often evaluate reps’ performance according to overall output, without assessing or quantifying their respective individual contributions to customer buying decisions. The authors of this study propose using value-added metrics that pertain to three drivers of value: (1) CSRs, (2) OSRs, and (3) the interface between CSRs and OSRs. This approach leverages variations in CSR–OSR combinations and produces both individual CSR–OSR and dyadic or interface value-added metrics. To address the empirical challenges (i.e., limited variations in CSR–OSR combinations), they use empirical Bayes random effect estimation to produce best linear unbiased prediction.

We examine the intersection of two major trends at online retail platforms: the emergence of retail media, which allows sellers to advertise on retail platforms alongside selling their products, and the platforms' switch away from reselling towards marketplace formats. We study whether and when a retail platform benefits from introducing sponsored advertising, and how the effects change with the platform's selling format. We consider two sellers with different qualities selling through a retail platform. We find that counter to our intuitions, offering sponsored advertising may not always benefit the platform, depending on its selling format.

Co-brands are strategically advantageous partnerships which can also involve risk. For example, Papa John’s gained access to the largest television audience in the US by sponsoring the National Football League (NFL), but later blamed stagnant sales on how the NFL’s handled players’ well-publicized protests of inequitable policing. What implications did Papa John’s prioritization of sales over fairness have for NFL consumption? To answer this question, the current research tests for changes in Sunday watch party rituals (SWPR), when U.S. consumers gather to socialize while watching live NFL games.

When a business model innovation (BMI) appears, incumbent firms experience great uncertainty about its potential ramifications and their capacity to assimilate the new business model. To resolve such uncertainty, incumbents seek to learn from industry peers, which can spark organizational herding. Organizational herding in BMI contexts is distinct, relative to product/technology adoption contexts, because in addition to peer behaviors, incumbents actively attempt to evaluate peer outcomes, and the importance of peer behaviors and outcomes likely vary, both over time and across types of peers.

Although the level of power held by the marketing department can determine key organizational outcomes, including firm performance, we show that this power has been decreasing since 2007. To address this apparent disconnect, we propose that the board of directors is a critical but overlooked antecedent of marketing department power. In particular, we demonstrate that directors’ exposure through board service at other firms (i.e., board-interlocked firms) affects the marketing department’s power in the firms on whose boards they also serve (i.e., focal firms).

In business markets, marketing and sales functions often conflict over customer acquisition. Marketers are seen to complain that sales representatives disregard the leads they generate, while sales representatives question the revenue potential of these leads. How should firms resolve such conflicts? We investigate these questions using relatively novel sequential principal-agent models with risk averse agents where asymmetry of information exists regarding leads’ revenue potentials.