Knowledge that Transforms

The literature in sustainability has emphasized external pressures as a main driver of firms’ environmental responsibility. However, under similar external pressures, some firms search for environmental technology, while others do not. By focusing on information and communication technology (ICT) firms, we try to answer the question of when firms are motivated to search for renewable energy technology. Drawing on the framework of the behavioral theory of the firm, we propose that a mismatch between ICT firms’ CO 2 emissions performance and their aspiration to a certain level of emissions induce firms to evaluate their environmental performance status—whether they are aligned well with environmental requirements and their peer firms—and their technology status—whether they possess sufficient technologies to reduce emissions—which in turn affects their search for renewable energy technology. We corroborate our hypotheses using data on CO 2 emissions and renewable energy patents of U.S. ICT firms from 2010 to 2018. When we compare two groups of firms—one group whose emissions performance is poor and the other group whose emissions performance is good compared to their own past emissions—we find that the former is more likely to search for renewable energy technology compared to the latter. When we focus on each of the two groups, we find that firms decrease their search for renewable energy technology as the degree of poor emissions performance exacerbates (firms’ emissions increase above aspiration) or the degree of good emissions performance increases (firms’ emissions decrease below aspiration). Our findings have implications for public policy as well as firms’ environmentally sustainable operations.

Two empirical observations motivate the focus of this article. First, stemming from the increased demand for electronics, there is a significant change in the number of substitute product offerings. For example, within a product category, Eaton and Dell both offer remanufactured/refurbished products and new products to consumers. Second, to better manage expenses for e-waste, social planners levy fees on producers or consumers of electronic products. Integrating these two aspects, the key issue addressed is whether the social planner should levy a fee on the producer or consumer and whether such a fee should target one or both products. Through a rigorous analysis of the social planner’s fee decision, insights into differences between alternative policy choices are discussed. As expected, if the producer or consumer fee is levied on the same set of products, there are no differences in the impact on all stakeholders. Thus, the social planner would be indifferent in choosing whether to levy a fee on the producer or the consumer. On the other hand, analyzing current policies (e.g., Connecticut collects e-waste management fees from producers based on new product sales while California collects the fees from consumers purchasing new and refurbished/remanufactured products), we find significant differences for all stakeholders. Analytically, we show that pass-through fee effects of each policy are different. Through extensive numerical experiments, we find that the policy of a consumer fee on purchases of both products offers a greater chance of alignment between social planner and producer objectives; there are regions defined by parameters associated with remanufacturing activities where there exists a trade-off between the benefits to producers versus those for consumers; and there exist regions where the optimum policy for the social planner is aligned with the original equipment manufacturer’s preferred policy choice.

The sponsorship of sports or entertainment events is a long-established marketing promotion technique. The goals of sponsoring these events are to generate exposure and to transfer brand equity. A more assertive type of sponsored competition is when the competition is built around the products and brands of the sponsoring firm. The number of firms using sponsored product-based competitions (SPCs) is rising. Firms invest in these competitions to create content that highlights the capabilities of their products and build committed fan bases. However, evaluating the economic value of this type of sponsorship activity is challenging due to the absence of a direct link between event viewing and subsequent product consumption. We present an empirical approach to investigate the impacts of SPC on customer engagement using esports viewing and video game consumption data. We find that sponsored competitions provide firms with substantial benefits. Specifically, the results suggest that viewing an SPC event (i.e., esports competition) reduces consumers’ time between game plays by 3.2% (i.e., increased visit frequency), increases per-visit duration by 3.5%, and boosts the paid content purchase rate by 26%. These findings are corroborated using an alternate dataset from a second esports event from the game publisher. We find that the effect of an SPC event viewing is a nonlinear function of consumer expertise and is more pronounced among customers less familiar with the video game product category. In a supplementary analysis, we also identify an educational role of SPC that may explain the observed incremental consumption. The analyses reveal that esports audiences tend to choose frequently featured game characters with superior performance during the event. In addition, we find that when event viewers play the game with these characters, their performance improves. The results have substantial implications for event sponsorship management and follow-up product promotions.

“Cloud Kitchens” are delivery-only facilities that house multiple restaurants. Food-delivery platforms operate such kitchens to exploit two advantages: (a) Location advantage, arising due to a cloud-kitchen’s central location—this enables lower delivery times to customers. (b) Consolidation advantage, which accrues when multiple restaurants choose to co-locate at the cloud kitchen—this enables the platform to use a common pool of delivery drivers, thereby reducing costs. However, a cloud-kitchen’s eventual impacts on both the restaurants and the platform are intricately connected through their respective decisions—namely, the restaurants’ location decisions and the platform’s delivery capacity and delivery time. We examine conditions under which a cloud kitchen simultaneously benefits the primary stakeholders: delivery platform, restaurants, and customers. Our game-theoretic analysis considers two restaurants and a delivery platform. The restaurants simultaneously decide whether to stay at their initial (extreme) locations or relocate to a centrally located cloud kitchen. The platform decides the driver headcount and the delivery times for customers. In line with industry trends, we show that as population density increases beyond a threshold, the restaurants co-locating at the cloud kitchen is first a Pareto-dominant equilibrium and then the unique equilibrium. The platform and customers also prefer this equilibrium, leading to a win-win-win for the stakeholders. A cloud-kitchen’s benefit to the platform further increases as the drivers’ operational environment becomes more constrained, i.e. drivers’ carry-limit and speed decrease, and driver cost increases.

We document trends and patterns in the key attributes of the 24 top journals during 2001–2021 using data from the Web of Science. These trends include growth by disciplines and journals represented among selected journals in terms of growth in publications, relative publication share of disciplines, number of unique authors, attributes of prolific authors, and the extent of interdisciplinary contributions. We compare and contrast our findings with prior studies and offer a few conjectures on similarities and differences in the findings. We hope that our descriptive findings will spur further research on the production function of science and help identify the determinants of research productivity in top journals.

We consider an order fulfillment problem of an omni-channel retailer that ships online orders from its distribution center (DC) and brick-and-mortar stores. Stores use their local information, not observed by the retailer, that can lead them to accept or reject fulfillment requests of items in an online order. We investigate the problem of sequencing requests to stores and inventory rationing decisions at the DC to minimize expected costs under uncertain store acceptance behavior and when items are indistinguishable in terms of shipping. First, under the scenario that stores are used only when the DC has insufficient inventory, we propose a Markov Decision Process formulation and analyze the performance of myopic policies that are preferable because of their interpretability. We show that the performance rate of a myopic approach that orders stores by cost only depends on the number of items in an order, which is small in practice. We also determine conditions for the range of acceptance probabilities for the myopic policy to be optimal for small-sized orders. Using optimality conditions for a special case of the problem, we develop an adaptive variant of the myopic policy, and propose a new degree-based strategy that balances shipping costs and acceptance probabilities. Numerical testing suggests that the best-performing sequencing policy is within 1% of optimality on average. Moreover, using two years of data from a large omni-channel retailer in North America, we observe that adaptive policies, albeit more complex, are beneficial in reducing costs and split deliveries if acceptance rates can be estimated accurately. Second, we determine when the retailer should ship from stores or ration the inventory at the DC. We show that for single-item orders, the optimal policy has a threshold structure, where, remarkably, the highest priority region is also subject to rationing. We then consider the novel multi-unit-single-item rationing problem, and leverage the structure of the single-unit model to develop a heuristic. We numerically establish the efficacy of rationing models and our heuristic.

We examine the causal effects of nearby terrorist attacks on supplier–customer relationships. We find that for supplier firms located near terrorist attacks, the probability of relationship termination with their major customers increases by 2.9 percentage points within two years following the attacks. The major customers’ intensified perceptions of supply chain risk largely drive the relationship termination. Further analyses show that major customers tend to switch to suppliers with lower terrorism risks after they end their relationships with the suppliers near attacks. This study provides new insights into the consequences of terrorism by extending the focus to the response of a key stakeholder group (i.e., trade partners) instead of the attack-afflicted firms per se.

The relationship between product variety and sales has been extensively researched, but almost exclusively from the perspective of a new goods retail firm. Closed-loop supply chains for used goods, such as automobiles, offer unique challenges in terms of using reverse flows to create product variety at the retail location. Firms in used goods industries are unable to define their product mix a priori and may not even know which goods will be available to add to their sellable inventory. In this article, we use data from a used automobile retailer to explore these issues. A better understanding of the relationship between variety and sales can help used automobile retailers improve how they define and structure product variety at retail locations. Improved management of used automobile sales has obvious financial implications, but it also has important environmental implications, given the large contribution of passenger vehicles to overall emissions. This study implements a cluster analysis using consumer-facing variables to understand how customers view product variety for used automobiles. Our results show that three distinct classes of inventory exist, primarily driven by a key characteristic—body type—which differs from the traditional definition of product variety for new vehicles in the existing literature. A two-way fixed effects regression is then used to understand the relationship between product variety at the firm's retail locations and sales. The results demonstrate a nonlinear relationship between product variety and sales and, intriguingly, suggest that increasing product variety in some classes can be used to drive sales in others. Our findings yield important contributions for managers in used automobile firms and extend the broader literature on closed-loop supply chains. Specifically, our research demonstrates important differences in how product variety should be managed with used goods relative to new goods by a firm seeking to maximize sales.

Much of the responsibility for advancing the circular economy has been directed towards firms, yet many reuse opportunities can only be achieved through environmentally compliant, household-level recycling behaviors. In response, policymakers and recycling organizations are using a range of feedback mechanisms to promote household recycling that meets local quality standards. However, the effectiveness of these tactics remains unclear, and stakeholders are divided on the appropriateness of their use. In this research, we examine the role of two popular feedback mechanisms—information-only and information-plus-penalty—in correcting households’ curbside recycling behaviors. With information-only feedback, households are provided with best practices for recycling and are not penalized for their errors. With information-plus-penalty feedback, households also receive information, but temporarily forfeit their recycling services. While previous studies have explored the use of information and penalties as feedback mechanisms to guide behavioral changes, there is mixed evidence of their effectiveness, particularly in the recycling context. We address this research gap by analyzing unique data collected from a 2019 curbside auditing effort that occurred in a large, Mid-Western city. Our analysis leverages econometric methods, and recycling feedback and performance data from 25,359 audits across 11,899 households and 15 recycling routes. We find that information-only feedback mechanisms, while preferred by some stakeholders, are not associated with improvements in recycling quality (measured using household contamination rates). By contrast, our results indicate that punitive mechanisms (i.e., information-plus-penalty) involving cart refusals are associated with significant reductions in contamination rates: that is, households that receive punitive feedback reduce their contamination rate severity by 59%, and are 75% less likely to commit a violation in the future. More importantly, we do not find evidence that punitive feedback mechanisms generally discourage households’ participation in recycling programs (measured using future set out rates). Our study informs sustainable operations management literature by investigating how curbside feedback mechanisms, with differing levels of severity, influence critical dimensions of households’ recycling performance (i.e., recycling quality and participation). We also inform policymakers on how curbside feedback mechanisms can be more effectively leveraged to enhance opportunities for material reuse.

Live streaming has significantly transformed the landscape of both offline and online retail operations. This article explores the optimal timing and circumstances under which a firm with a specific product should launch a live streaming channel, and if so, whether it should use third-party streaming, self-run streaming, or a combination of both. We demonstrate that no single channel structure is universally superior to the others: the firm's optimal channel strategy depends on the third-party streamer's popularity and bargaining power, the investment and broadcasting effort cost for the live streaming channel, consumer's channel preference and extra cost for watching live streaming, cross-channel spillover, as well as the price sensitivity of a product. In general, live streaming is most beneficial for firms selling products that aren't highly price sensitive, where traditional pricing tool is less important for attracting consumers. Start-ups should collaborate with either highly popular streamers or those with a small but dedicated following, avoiding those with intermediate popularity. In contrast, established firms should partner with streamers who have a moderate level of popularity. An established firm considering leveraging two or more channels concurrently should additionally take into consideration the cross-channel spillover, channel encroachment cost, and channel competition. Our research reveals that, contrary to expectation, price in live streaming channels may not always be lower than those in traditional channels. Furthermore, highly popular streamers do not always demand higher revenue-sharing ratios and slotting fees. This research sheds light on the key decisions for firms considering live streaming commerce: whether to adopt it, when to integrate it into their strategy, and how to effectively implement it.