Knowledge that Transforms

The relationship between emissions reduction and firm financial performance has been studied with mixed results. We consider potential sources of this ambiguity by examining announcements of voluntary emissions reduction (VER) from 1990 to 2009. We measure the stock market reaction associated with VER announcements to estimate the effects of time, emissions type, and whether the reduction was announced ex ante or ex post . We find that the market reaction to VER significantly decreased over time. The changing nature of the market reaction to VER over time highlights the importance of evaluating the financial impact of any VER in the current context rather than relying on past findings. We also find that the market reaction is more positive if the reduction is for greenhouse gas (GHG) rather than other emissions types. In light of the increasing concern with GHGs, this finding should be welcome news for managers. Last, we find a more positive market reaction for VER announcements that are pledges or statements of intent rather than realized achievements of VER. Managers contemplating VER might find benefit (and at least no harm) in announcing their intent to reduce emissions rather than waiting until they have achieved the reduction.

It is common for a firm to make use of multiple suppliers of different delivery lead times, reliabilities, and costs. In this study, we are concerned with the joint pricing and inventory control problem for such a firm that has a quick‐response supplier and a regular supplier that both suffer random disruptions, and faces price‐sensitive random demands. We aim at characterizing the optimal ordering and pricing policies in each period over a planning horizon, and analyzing the impacts of supply source diversification. We show that, when both suppliers are unreliable, the optimal inventory policy in each period is a reorder point policy and the optimal price is decreasing in the starting inventory level in that period. In addition, we show that having supply source diversification or higher supplier reliability increases the firm's optimal profit and lowers the optimal selling price. We also demonstrate that, with the selling price as a decision, a supplier may receive even more orders from the firm after an additional supplier is introduced. For the special case where the quick‐response supplier is perfectly reliable, we further show that the optimal inventory policy is of a base‐stock type and the optimal pricing policy is a list‐price policy with markdowns.

Gray markets, also known as parallel imports, have created fierce competition for manufacturers in many industries. We analyze the impact of parallel importation on a price‐setting manufacturer that serves two markets with uncertain demand, and characterize her policy against parallel importation. We show that ignoring demand uncertainty can take a significant toll on the manufacturer's profit, highlighting the value of making price and quantity decisions jointly. We find that adjusting prices is more effective in controlling gray market activity than reducing product availability, and that parallel importation forces the manufacturer to reduce her price gap while demand uncertainty forces her to lower prices. Furthermore, we explore the impact of market conditions (such as market base, price sensitivity, and demand uncertainty) and product characteristics (“fashion” vs. “commodity”) on the manufacturer's policy towards parallel importation. We also provide managerial insights about the value of strategic decision‐making by comparing the optimal policy to the uniform pricing policy that has been adopted by some companies to eliminate gray markets entirely. The comparison indicates that the value of making price and quantity decisions strategically is highest for moderately different market conditions and non‐commodity products.

We consider a decentralized two‐period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it through a retailer facing a price‐dependent demand. The manufacturer's second‐period production cost declines linearly in the first‐period production, but with a random learning rate. The manufacturer may or may not have the inventory carryover option. We formulate the resulting problems as two‐period Stackelberg games and obtain their feedback equilibrium solutions explicitly. We then examine the impact of mean learning rate and learning rate variability on the pricing strategies of the channel members, on the manufacturer's production decisions, and on the retailer's procurement decisions. We show that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We obtain revenue sharing contracts that can coordinate the dynamic supply chain. In particular, when the manufacturer may hold inventory, we identify two major drivers for inventory carryover: market growth and learning rate variability. Finally, we demonstrate the robustness of our results by examining a model in which cost learning takes place continuously.

Based on a serial supply chain model with two periods and price‐sensitive demand, we present the first experimental test of the effect of strategic inventories on supply chain performance. In theory, if holding costs are sufficiently low, the buyer builds up a strategic inventory (even if no operational reasons for stock‐holding exist) to limit the supplier's market power, and to increase the own profit share. As it turns out, this enhances the overall supply chain performance. The supplier anticipates the effect of the strategic inventory and differentiates prices to capture a part of the increased supply chain profits. Our results show that the positive effects of strategic inventories are even more pronounced than theoretically predicted, because strategic inventories empower buyers by shifting the perception of the fair split. Overall, strategic inventories have a double positive effect, a strategic and a behavioral, both reducing the average wholesale prices and dampening the double marginalization effect. The latter effect leads to more equitable payoffs.

Limited version, time‐locked, and hybrid are three software free trial strategies employed by software firms to exploit increased installed base and/or reduction of consumers' uncertainty about software quality. We develop an analytical model to examine these three software free trial strategies. We find that the hybrid strategy weakly dominates the limited and time‐locked versions, and the intensity of the network effects is a key factor determining which strategy is optimal.

Management‐by‐walking‐around (MBWA) is a widely adopted technique in hospitals that involves senior managers directly observing frontline work. However, few studies have rigorously examined its impact on organizational outcomes. This study examines an improvement program based on MBWA in which senior managers observe frontline employees, solicit ideas about improvement opportunities, and work with staff to resolve the issues. We randomly selected hospitals to implement the 18‐month‐long, MBWA‐based improvement program; 56 work areas participated. We find that the program, on average, had a negative impact on performance. To explain this surprising finding, we use mixed methods to examine the impact of the work area's problem‐solving approach. Results suggest that prioritizing easy‐to‐solve problems was associated with improved performance. We believe this was because it resulted in greater action‐taking. A different approach was characterized by prioritizing high‐value problems, which was not successful in our study. We also find that assigning to senior managers responsibility for ensuring that identified problems get resolved resulted in better performance. Overall, our study suggests that senior managers' physical presence in their organizations' front lines was not helpful unless it enabled active problem solving.

Class‐based storage is widely studied in the literature and applied in practice. It divides all stored items into a number of classes according to their turnover. A class of items with higher turnover is allocated to a region closer to the warehouse depot. In the literature, it has been shown that the use of more storage classes leads to a shorter travel time for storing and retrieving items. A basic assumption in this literature is that the required storage space for all items equals their average inventory level , which is valid only if an infinite number of items can be stored in each storage region. This study revisits class‐based storage by considering each storage space to contain only a finite number of items. We develop a travel time model and an algorithm that can be used for determining the optimal number and boundaries of storage classes in warehouses. Different from the conventional research, our findings illustrate that commonly a small number of classes is optimal. In addition, we find the travel time is fairly insensitive to the number of storage classes in a wide range around the optimum. This suggests that a manager can select a near‐optimal number of storage classes in an easy way and need not be worried about the impact of storage‐class reconfigurations. We validate our findings for various cases, including different ABC‐demand curves, space‐sharing factors, number of items, storage rack shapes, discrete storage locations, and stochastic item demand.

This study examines the peer‐to‐Peer interactions among farmers when both knowledge learning and sharing are available. We construct a stylized model in which heterogeneous farmers are endowed with their initial production capabilities and can post questions in the platform for help. A representative expert regularly monitors the forum and provides answers to the farmers’ questions, but may be non‐responsive sometimes due to the limited capacity. A knowledgeable core user (farmer) can choose to be silent or responsive, and is allowed to strategically determine the informativeness of her answers. The farmers face the minimum quantity restriction for attracting the buyers, and must make production before the time of sales. We show that in equilibrium the core user never provides answers that are more informative than the expert's, irrespective of her ex ante knowledge level. Redesigning or restructuring the platform does not help eliminate this inefficient knowledge provision. We also find that hiring more staff to frequently monitor the forum turns out to be detrimental for the peer‐to‐peer interactions. Moreover, the competition on knowledge sharing between the platform expert and the core user features strategic complementarity sometimes but strategic substitution at other times. Third, charging for the platform usage may discourage uninformative answers, but it could also discourage the core user from sharing knowledge with other farmers.

Product take‐back regulation, under which firms finance the collection and treatment of their end‐of‐life products, is a widely used environmental program. One of the most common compliance schemes is collectively with cost allocation by market share. As an alternative, individual compliance scheme is considered. Assuming that firms can choose their compliance scheme, we compare these two schemes with respect to the costs they impose on firms and environmental benefits. We show that high collection targets and large market shares among firms in a collective compliance scheme make it more cost‐effective. From an environmental benefits perspective, the prevailing intuition is that collection rates will be higher under collective schemes but individual compliance will provide more incentive for higher recyclability levels. Our results challenge both of these premises. We identify conditions under which collection rates are higher when firms comply individually and recyclability levels are higher when firms comply collectively and allocate costs with respect to market shares.