Knowledge that Transforms

Motivated by several industry examples, we study the interaction between a technology provider introducing a new technology and downstream manufacturers adopting the new technology into their products. The manufacturers, once decided on their adoption timing, both cooperate in making demand‐boosting investments to promote the technology and compete in price in the product market. Our main objective is to explore the important question of how the technology provider manipulates manufacturers’ adoption timing. We develop a stylized continuous‐time multi‐stage game‐theoretic model with one technology provider and two downstream manufacturers, and derive pure‐strategy equilibria for the manufacturers and the technology provider. We find that in the absence of the technology provider's intervention, in equilibrium there is simultaneous adoption when the market competition is relatively mild, and sequential adoption otherwise. In particular, under the sequential‐adoption equilibrium, the second manufacturer strategically postpones adoption in order to freeride on the first manufacturer's demand‐boosting investment. We show that manufacturers’ equilibrium adoption timing is not always in line with the technology provider's interest. To align these different preferences, we suggest that when the competition is in a relatively mild region, the technology provider can make an initial investment to incentivize both manufacturers to adopt the technology early, whereas when the competition is relatively intense, an exclusive period should instead be offered to one manufacturer to keep the other from adopting the technology early. Interestingly, these self‐interested interventions often improve the efficiency of the system. Finally, we show that our main findings remain robust when we assume that the effect of manufacturers’ demand‐boosting investments decreases over time, or when we allow the technology provider to optimize over the technology's licensing fee.

The past decade has witnessed the explosive implementation of corporate social tools and technologies such as corporate internal online communities. However, there is little empirical evidence on whether and to what extent the implementation of an internal online community affects individual job performance in the geographically dispersed organization. In this study, we investigate this question with a quasi‐natural experiment: A large manufacturer (i.e., the company) introduced an internal online community for its sales representatives across geographically dispersed subunits. The unique data set from the company's different departments enables us to observe detailed information about each representative's community usage, sales performance, and demographics. Our difference‐in‐differences design and instrumental‐variable analysis jointly demonstrate a positive relationship between community usage and individual sales performance. In addition, we find that the online community has heterogeneous effects: It is significantly more beneficial for representatives with fewer offline opportunities to observe and learn from their colleagues' activities (i.e., representatives from subunits with fewer employees and lower average job performance). Finally, sales performance is more positively associated with reading posts from nonlocal subunits (vs. posts from the local subunit) and posts that summarize multiple selling events (vs. posts that describe a single selling event). Our study has implications for managers regarding the benefits of corporate online communities, especially for the geographically dispersed organization.

Recent advancements in Information Technology have provided an opportunity to significantly improve the effectiveness of inventory systems. The use of in‐cycle demand information enables faster reaction to demand fluctuations. In particular, for the newsvendor (NV) system, we exploit the newly available data to perform an additional review (AR) of inventory at an endogenously determined, a priori set time during the sales period, and perform an additional replenishment if necessary. We implemented our innovative model at a market‐leading media group. The results of the initial pilot were dramatic, indicating that the proposed model achieves an increase of 4%–24% in profits compared to the policy before implementation. As a result, the company started following the proposed model for all their printed magazines and observed a significant reduction in operational costs. In a generalized setting, we provide a tractable search‐based optimization algorithm, based on the problem's structural properties, for determining the optimal initial quantity, AR timing, and quantity to restock at that time. Based on these theoretical results, we propose a simple heuristic that can be used for many practical situations including our implementation at Yedioth. Through a computational experiment, we show that our algorithm finds the optimal solution quickly and that the proposed heuristic performs well. We also provide additional insights into the problem—for instance, that our system exhibits properties similar to inventory pooling, provided that the demand rate is large enough.

This commentary provides my remarks on “Network Structure and Its Impact on Commodity Markets” by John Birge.

We study a special class of cooperative games with transferable utility (TU), called <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> ‐ attribute games . Every player in an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> ‐attribute game is endowed with a vector of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> attributes that can be combined in an additive fashion; that is, if players form a coalition, the attribute vector of this coalition is obtained by adding the attributes of its members. Another fundamental feature of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> ‐attribute games is that their characteristic function is defined by a continuous attribute function <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>π</mml:mi> <mml:annotation encoding="">π</mml:annotation> </mml:semantics> </mml:math> —the value of a coalition depends only on evaluation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>π</mml:mi> <mml:annotation encoding="">π</mml:annotation> </mml:semantics> </mml:math> on the attribute vector possessed by the coalition, and not on the identity of coalition members. This class of games encompasses many well‐known examples, such as queueing games and economic lot‐sizing games. We believe that by studying attribute function <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>π</mml:mi> <mml:annotation encoding="">π</mml:annotation> </mml:semantics> </mml:math> and its properties, instead of specific examples of games, we are able to develop a common platform for studying different situations and obtain more general results with wider applicability. In this paper, we first show the relationship between nonemptiness of the core and identification of attribute prices that can be used to calculate core allocations. We then derive necessary and sufficient conditions under which every <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> ‐attribute game embedded in attribute function <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>π</mml:mi> <mml:annotation encoding="">π</mml:annotation> </mml:semantics> </mml:math> has a nonempty core, and a set of necessary and sufficient conditions that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>π</mml:mi> <mml:annotation encoding="">π</mml:annotation> </mml:semantics> </mml:math> should satisfy for the embedded game to be convex. We also develop several sufficient conditions for nonemptiness of the core of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation> </mml:semantics> </mml:math> ‐attribute games, which are easier to check, and show how to find a core allocation when these conditions hold. Finally, we establish natural connections between TU games and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:semantics definitionURL="" encoding=""> <mml:mi>m</mml:mi> <mml:annotation encoding="">m</mml:annotation>

Refurbishing of used products is increasingly being recognized as a value recovery strategy in sustainable operations. Hence, manufacturers, retailers, as well as third‐party firms, engage in refurbishing. Manufacturers, to some extent, can deter other players from refurbishing through various means such as product design, intellectual property, and restricting access to spare parts and diagnostic tools. While previous research has extensively examined the question of whether a manufacturer should allow an independent third‐party player to refurbish used products, the question of whether a manufacturer should allow his retailer to refurbish them, to our knowledge, remains unanswered. In this study, we examine whether a manufacturer should refurbish used products himself or allow his retailer to refurbish them. We compare two closed‐loop supply chain structures: Model‐M, where the manufacturer refurbishes used products; and Model‐R, where the retailer refurbishes. In a two‐period setting, new products are sold in both periods and some of the first‐period products are refurbishable in the second period. We show that when either (i) the refurbishability of used products is low and the attractiveness of refurbishing (value of the refurbished product as compared to the refurbishing cost) is either moderate or sufficiently high, or (ii) the refurbishability is high and the attractiveness of refurbishing is moderate, the manufacturer, despite forgoing profits and facing competition from refurbished products, is better off with letting the retailer refurbish used products (Model‐R) than with refurbishing them himself (Model‐M). Identifying a novel mechanism through which the manufacturer benefits in Model‐R is our key theoretical contribution to the closed‐loop supply chain literature. Moreover, we provide some useful and interesting insights to policymakers related to customer welfare and the environment. We also analyze the performances of these models (Model‐M and Model‐R) in terms of supply chain efficiency. In addition, we discuss how some of our key results change if a third‐party refurbisher coexists with the manufacturer and the retailer. Our results not only support some of the current policies and practices but also shed some light on their limitations and suggest some avenues for improvement.

As more customers purchase pre‐owned apparel, firms are increasingly adopting resale based business models. These models typically operate as either (i) a trade‐in and resale program, wherein a firm offers a trade‐in discount on a new product and resells the traded‐in products, or (ii) a P2P resale marketplace where customers can buy and sell used products to each other. Since different firms choose different resale strategies, it is not clear which strategy is more profitable. Furthermore, although firms that adopt each resale model also promote their environmental benefits, there are concerns that these firms are greenwashing, that is, misrepresenting the environmental benefits of their business models. Hence, we investigate the profitability and environmental impacts of these resale marketplace models and find that the trade‐in model may be more profitable despite the lower reverse logistics cost in the P2P model, and the P2P resale marketplace may be more profitable despite the trade‐in program having direct control over the supply and demand of used products. Furthermore, both models can be better for the environment depending on the product characteristics and perceived quality difference between the used products sold in these programs. We further identify when each model is better for profitability and environment concurrently and when there is misalignment. Other results and managerial insights include comparative pricing of new and used products, market coverage, total sales, and resales, and the impact of product durability on pricing. The insights presented in this study provide useful guidelines for firms, non‐governmental organizations, and environmental advocacy groups.

Human decision making in the newsvendor context has been analyzed intensively in laboratory experiments, where various decision biases have been identified. However, it is unclear whether the biases also exist in practice. We analyze the ordering decisions of a manufacturer who faces a multiproduct newsvendor problem with an aggregate service‐level constraint. We find that the manufacturer broadly exhibits the same biases as subjects in the laboratory and is prone to another bias that has not been identified before, that is, group aggregation. The bias can be attributed to the multi‐product problem of the manufacturer, and refers to the observation that the service levels are not optimized for individual products, but rather for product groups. Our data allow us to analyze the performance of a manufacturer in detail and we find that target service levels are achieved effectively, but not efficiently. We provide rationales for the manufacturer's ordering behavior, discuss managerial implications, and quantify the financial benefits of debiasing ordering decisions.

Understanding the patterns of demand evolution for a new category is important for firms to effectively manage capacity planning, market and service operations, and research and development. Our objective is to analyze how marketing at the industry level affects the evolution of primary demand in different stages of the product life cycle. We characterize the aggregate marketing activities in two constructs: marketing breadth and competitive spread. The first construct reflects the spread of spending across different marketing instruments at the industry level, and the second construct reflects the spread of spending across different firms . Though both constructs are related to the spread of spending within a category, we find that they have qualitatively different effects on category growth. An econometric model making use of the hierarchical nature of time observations within countries is estimated for each category. First, we find that high degrees of spending breadth impede market growth when the number of competitors is small (the category is young) but accelerate market growth when the number of competitors is higher (the category is maturing). Second, we find that high levels of competitive spread decrease category growth when spending levels are relatively low. However, as spending levels increase, the negative effect of competitive spread on demand growth all but evaporates.

Annapoornima M. Subramanian, Moren Lévesque, and Vareska Van De Vrande were recognized as a runner up for the 2020 Ralph Gomory Best Industry Studies Paper Award.