Effects of Random Yield in Remanufacturing with Price‐Sensitive Supply and Demand

In this study, we investigate the effects of recovery yield rate on pricing decisions in reverse supply chains. Motivated by the automotive parts remanufacturing industry, we consider an end‐of‐life product from which a particular part can be recovered and remanufactured for reuse, and the remainder of the product can be recycled for material recovery. Both the supply of end‐of‐life products and demand for remanufactured parts are price‐sensitive. Yield of the recovery process is random and depends on the acquisition price offered for the end‐of‐life products. In this setting, we develop models to determine the optimal acquisition price for the end‐of‐life products and the selling price for remanufactured parts. We also analyze the effects of yield variation to the profitability of remanufacturing, benefits of delaying pricing decisions until after yield realization, and value of perfect yield rate information.     

Shelf Space Management When Demand Depends on the Inventory Level

Two factors that their influence on the demand has been investigated in many papers are (i) the shelf space allocated to a product and to its complement or supplement products and (ii) the instantaneous inventory level seen by customers. Here we analyze the joint shelf space allocation and inventory decisions for multiple items with demand that depends on both factors. The traditional approach to solve inventory models with a state‐dependent demand rate uses a time domain approach. However, this approach often does not lead to closed‐form expressions for the profit rate with both dependencies. We analyze the problem in the inventory domain via level crossing theory. This approach leads to closed‐form expressions for a large set of demand rate functions exhibiting both dependencies. These closed‐form expressions substantially simplify the search for optimal solutions; thus we use them to solve the joint inventory control and shelf space allocation problem. We consider examples with two products to investigate the significance of capturing both demand dependencies. We show that in some settings it is important to capture both dependencies. We consider two heuristics, each one of them ignores one of the two dependencies. Using these heuristics it seems that ignoring the dependency on the shelf space might be less harmful than ignoring the dependency on the inventory level, which, based on computational results, can lead to profit losses of more than 6%. We demonstrate that retailers should use their operational control, e.g., reorder point, to promote higher demand products.     

Take‐Back Legislation: Consequences for Remanufacturing and Environment

In the last two decades, many countries have enacted product take‐back legislation that holds manufacturers responsible for the collection and environmentally sound treatment of end‐of‐use products. In an industry regulated by such legislation, we consider a manufacturer that also sells remanufactured products under its brand name. Using a stylized model, we consider three levels of legislation: no take‐back legislation, legislation with collection targets, and legislation with collection and reuse targets. We characterize the optimal solution for the manufacturer and analyze how various levels of legislation affect manufacturing, remanufacturing, and collection decisions. First, we explore whether legislation with only collection targets causes an increase in remanufacturing levels, which is argued to be an environmentally friendlier option for end‐of‐use treatment than other options such as recycling. While increased remanufacturing alone is usually perceived as a favorable environmental outcome, if one considers the overall environmental impact of new and remanufactured products, this might not be the case. To study this issue, we model the environmental impact of the product following a life cycle analysis–based approach. We characterize the conditions under which increased remanufacturing due to take‐back legislation causes an increase in total environmental impact. Finally, we model the impact of legislation on consumer surplus and manufacturer profits and identify when total welfare goes down because of legislation.     

The comparison between trade-in and leasing of a product with technology innovations

Companies can adopt trade-in and/or leasing to shorten consumers׳ upgrade cycle and gain control over secondary markets. In this paper, we consider a monopolistic manufacturer who offers a technology product to a market consisting of heterogeneous consumers. We focus on an exogenous, stochastic innovation process that determines the availability of new technology and consequently, residual value of the current product. We derive the optimal pricing strategy of trade-in and leasing, respectively, examine its impact on the manufacturer׳s expected profit, and compare the performance of the two strategies. Trade-in protects the manufacturer against residual value risk and allows the flexibility of offering the option at different innovation states separately. Leasing, on the other hand, provides the manufacturer an opportunity to circumvent low new product prices and thus increases expected profit when product reuse profitability is high. The interplay between the two forces, product reuse profitability and new product price, determines the preference between trade-in and leasing. Our findings provide monopolistic manufacturers guidance on how to optimally employ the trade-in and leasing strategies.     

A Theory of Optimal Inheritance Taxation

This paper derives optimal inheritance tax formulas that capture the key equity‐efficiency trade‐off, are expressed in terms of estimable sufficient statistics, and are robust to the underlying structure of preferences. We consider dynamic stochastic models with general and heterogeneous bequest tastes and labor productivities. We limit ourselves to simple but realistic linear or two‐bracket tax structures to obtain tractable formulas. We show that long‐run optimal inheritance tax rates can always be expressed in terms of aggregate earnings and bequest elasticities with respect to tax rates, distributional parameters, and social preferences for redistribution. Those results carry over with tractable modifications to (a) the case with social discounting (instead of steady‐state welfare maximization), (b) the case with partly accidental bequests, (c) the standard Barro–Becker dynastic model. The optimal tax rate is positive and quantitatively large if the elasticity of bequests to the tax rate is low, bequest concentration is high, and society cares mostly about those receiving little inheritance. We propose a calibration using micro‐data for France and the United States. We find that, for realistic parameters, the optimal inheritance tax rate might be as large as 50%–60%—or even higher for top bequests, in line with historical experience.     

MANAGING PRODUCT RETURNS FOR REMANUFACTURING

Firms are often encouraged to offer environmentally friendly products as a demonstration of corporate citizenship. However, this may prove to be an unrealistic expectation since a rational firm will only engage in profitable ventures; those that increase shareholder wealth. We develop a framework for analyzing the profitability of reuse activities and show how the management of product returns influences operational requirements. We show that the acquisition of used products may be used as the control lever for the management and profitability of reuse activities. These activities, termed product acquisition management, affect several important business decisions. First, if a firm is to pursue reuse activities, these reuse activities must be value‐creating. Second, if a firm is to compete by offering remanufactured products, then we show how product returns management influences the overall profitability of such activities via a trial and error EVA approach. Third, we show how operational issues are strongly affected by the approach used to manage product returns. There is a need for future research specifying the mathematical relationship between acquisition price and the nominal quality of the returned product.     

Sharing Responsibility for Product Recovery Across the Supply Chain

Extended producer responsibility (EPR) programs typically hold the producer—a single actor defined by the regulator—responsible for the environmental impacts of end‐of‐life products. This is despite emphasis on the need to involve all actors in the supply chain in order to best achieve the aims of EPR. In this paper, we examine the economic and environmental implications of product recovery mandates and shared responsibility within a supply chain. We use a two‐echelon model consisting of a supplier and a manufacturer to determine the impacts of product collection and recycling mandates on the incentive to recycle and resulting profits in the integrated and decentralized supply chains. For the decentralized supply chain, we demonstrate how the sharing of responsibility for product recovery between the echelons can improve total supply chain profit and suggest a contract menu that can Pareto‐improve profits. To examine both the economic and environmental performance associated with responsibility sharing, we propose a social welfare construct that includes supply chain profit, consumer surplus, and the externalities associated with virgin material extraction, product consumption, and disposal of nonrecycled products. Using a numerical example, we discuss how responsibility sharing may or may not improve social welfare. The results of this paper are of value to firms either anticipating or subject to product recovery legislation, and to social planners that attempt to balance economic and environmental impacts and ensure fairness of such legislation.     

Inventory Models with Continuous and Poisson Demands and Discounted and Average Costs

We develop a new, unified approach to treating continuous‐time stochastic inventory problems with both the average and discounted cost criteria. The approach involves the development of an adjusted discounted cycle cost formula, which has an appealing intuitive interpretation. We show for the first time that an (s, S) policy is optimal in the case of demand having a compound Poisson component as well as a constant rate component. Our demand structure simultaneously generalizes the classical EOQ model and the inventory models with Poisson demand, and we indicate the reasons why this task has been a difficult one. We do not require the surplus cost function to be convex or quasi‐convex as has been assumed in the literature. Finally, we show that the optimal s is unique, but we do not know if optimal S is unique.     

Optimal Acquisition and Sorting Policies for Remanufacturing

The condition of the used items acquired by remanufacturers is often highly variable, and sorting is an important aspect of remanufacturing operations. Sorting policies—the rules specifying which used products should be remanufactured and which should be scrapped—have received limited attention in the literature. In this paper, we examine the case of a remanufacturer who acquires unsorted used products as needed from third party brokers. As more used items are acquired for a given demand, the remanufacturer can be more selective when sorting. Thus, two related decisions are made: how many used items to acquire, and how selective to be during the sorting process. We derive optimal acquisition and sorting policies in the presence of used product condition variability for a remanufacturer facing both deterministic and uncertain demand. We show the existence of a single optimal acquisition and sorting policy with a simple structure and show that this policy is independent of production amount when acquisition costs are linear.     

CAPACITATED REMANUFACTURING WITH SERVICE LEVEL CONSTRAINTS*

This research examines production planning and control for a remanufacturer that can sell returned items on a graded as‐is basis or remanufacture the returned items. Using a GI/G/1 queuing network, we model the firms decision to remanufacture an optimal product mix over the long run that maximizes profits while maintaining a desired service level. We further use simulation to explore dispatching heuristics that can be used at the shop‐floor level to achieve the desired optimal product mix, while meeting the service level constraint. Our research is grounded in actual practice and the results provide key insights into the decision‐making process required to maximize profits and minimize average flow times for remanufactured products.     

The permutation flow shop problem with just in time production considerations

This research presents a variation to the permutation flow shop problem where Just In Time (JIT) production requirements are taken into account. The model developed in this research employs dual objectives. In addition to the traditional objective of minimizing the production makespan, minimization of Miltenburg's material usage rate is also incorporated. In this model, multiple units of any product are permitted in the production sequence. However, the minimization of material usage rates attempts to prevent batch scheduling of products and allows unit flow of products as required in demand flow manufacturing. A solution method is proposed for determining an optimal production sequence via an efficient frontier approach and Simulated Annealing (SA). Test problems and specific performance criteria are used to assess the solutions generated by the proposed method. Experimental results presented in this paper show that the use of the efficient frontier and SA provide solutions that approach the optimal solution for the performance measures used in this research.     

Behavioral Modeling of Adversaries with Multiple Objectives in Counterterrorism

Attacker/defender models have primarily assumed that each decisionmaker optimizes the cost of the damage inflicted and its economic repercussions from their own perspective. Two streams of recent research have sought to extend such models. One stream suggests that it is more realistic to consider attackers with multiple objectives, but this research has not included the adaption of the terrorist with multiple objectives to defender actions. The other stream builds off experimental studies that show that decisionmakers deviate from optimal rational behavior. In this article, we extend attacker/defender models to incorporate multiple objectives that a terrorist might consider in planning an attack. This includes the tradeoffs that a terrorist might consider and their adaption to defender actions. However, we must also consider experimental evidence of deviations from the rationality assumed in the commonly used expected utility model in determining such adaption. Thus, we model the attacker's behavior using multiattribute prospect theory to account for the attacker's multiple objectives and deviations from rationality. We evaluate our approach by considering an attacker with multiple objectives who wishes to smuggle radioactive material into the United States and a defender who has the option to implement a screening process to hinder the attacker. We discuss the problems with implementing such an approach, but argue that research in this area must continue to avoid misrepresenting terrorist behavior in determining optimal defensive actions.     

Mixed Hitting‐Time Models

We study mixed hitting‐time models that specify durations as the first time a Lévy process—a continuous‐time process with stationary and independent increments—crosses a heterogeneous threshold. Such models are of substantial interest because they can be deduced from optimal‐stopping models with heterogeneous agents that do not naturally produce a mixed proportional hazards structure. We show how strategies for analyzing the identifiability of the mixed proportional hazards model can be adapted to prove identifiability of a hitting‐time model with observed covariates and unobserved heterogeneity. We discuss inference from censored data and give examples of structural applications. We conclude by discussing the relative merits of both models as complementary frameworks for econometric duration analysis.     

Managing Technology Selection and Development Risk in Competitive Environments

Managing development decisions for new products based on dynamically evolving technologies is a complex task, especially in highly competitive industries. Product managers often have to choose between introducing an incrementally better, safe new product early and a superior, yet highly risky, product later. Recommendations for managing such performance vs. time‐to‐market trade‐offs often ignore competitive reactions to development decisions. In this paper, we study how a firm could incorporate the presence of a strategic competitor in making technology selection and investment decisions regarding new products. We consider a model in which an innovating firm and its rival can introduce a new product immediately or pursue a more advanced product for later launch. Further, the firm can reduce the uncertainty surrounding product development by dedicating more resources; the effectiveness of this investment depends on the firm's innovative capacity. Our model generates two sets of insights. First, in highly competitive industries, firms can adopt different technologies and effectively use introduction timing to mitigate the effects of price competition. More importantly, the firm could strategically invest in the advanced product to influence its rival's technology choice. We characterize equilibrium development and investment decisions of the firms, and derive innovative capacity hurdles that govern a firm's choice between the risky and safe alternatives. The effects of development flexibility—where firms might have the option to revert to the safe product if the advanced product fails—are also considered.     

The Economics of Public Beta Testing

A growing number of software firms now rely on public beta testing to improve the quality of their products before commercial release. While the benefits resulting from improved software reliability are well recognized, some important market‐related benefits have not been studied. Through word‐of‐mouth, public beta testers can accelerate the diffusion of a software product after its release. Additionally, because of network effects, public beta testers can increase users’ valuation of a product. In this study, we consider both reliability‐related and market‐related benefits, and develop models to determine the optimal number of public beta testers and the optimal duration of testing. Our analyses show that public beta testing can be profitable even if word‐of‐mouth and network effects are the only benefits. Furthermore, when both benefits are considered, there is significant “economies of scope”—the net profit increases at a faster rate when both word‐of‐mouth and network effects are significant than when only one benefit is present. Finally, our sensitivity analyses demonstrate that public beta testing remains highly valuable to software firms over a wide range of testing and market conditions. In particular, firms will realize greater profits when recruiting public beta testers who are interested in the software but unable to afford it.     

Supply Chain Strategies for Perishable Products: The Case of Fresh Produce

This paper examines supply chain design strategies for a specific type of perishable product—fresh produce—using melons and sweet corn as examples. Melons and other types of produce reach their peak value at the time of harvest; product value deteriorates exponentially post‐harvest until the product is cooled to dampen the deterioration. Using the product's marginal value of time (MVT), the rate at which the product loses value over time in the supply chain, we show that the appropriate model to minimize lost value in the supply chain is a hybrid of a responsive model from post‐harvest to cooling, followed by an efficient model in the remainder of the chain. We also show that these two segments of the supply chain are only loosely linked, implying that little coordination is required across the chain to achieve value maximization. The models we develop also provide insights into the use of a product's MVT to develop supply chain strategies for other perishable products.     

A Single‐Period Assortment Optimization Model

This paper studies a single‐period assortment optimization problem with unequal cost parameters. The consumer choice process is characterized by a Multinomial Logit (MNL) model. When the store traffic is a continuous random variable, we explicitly derive the structure of the optimal assortment. Our approach is to use a comprehensive measure–profit rate to evaluate the profitability of each variant and then determine which product should be offered. We demonstrate that the optimal assortment contains the few items that have the highest profit rate. When the store traffic is discrete, the optimal solution is difficult to obtain. We propose a “profit rate” heuristic, which is inspired by the result for the case of continuous store traffic. In a special case with equal cost parameters and normal demand distribution, the profit rate heuristic is indeed optimal. Using randomly generated data, we test the effectiveness of the heuristic and find that the average percentage error is less than 0.1% and that the hit rate is above 90%. Our research provides managerial insights on assortment planning and accentuates the importance of measuring the profitability of each product when the demand is random and cannibalization among different products exists.     

An Empirical Agent‐Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large‐scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision‐making process. Based on the social amplification of risk framework, our agent‐based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the “risk publics” model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community‐level parameters—including social groups, relationships, and communication variables, also from survey data—are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks.     

How Does Product Recovery Affect Quality Choice?

We study the impact of product recovery on a firm's product quality choice, where quality is defined as an observable performance measure that increases a consumer's valuation for the product. We consider three general forms of product recovery: (i) when product recovery reuses (after reprocessing) quality inducing components or material (e.g., remanufacturing), (ii) when product recovery does not reuse quality inducing components or material but it is overall profitable (e.g., cell phone recycling), and (iii) when product recovery is costly (but mandated by legislation, e.g., recycling of small appliances in the European Union). Using a stylized economic model, we show that the form of product recovery, recovery cost structure, and the presence of product take‐back legislation play an important role in quality choice. Generally speaking, product recovery increases the firm's quality choice, except for some instances of recovery form (ii). In addition, we find that product take‐back legislation can lead to higher quality choice as opposed to voluntary take‐back. We further demonstrate that both the firm and the consumers benefit from recovery form (ii), while both are worse off with recovery form (iii). However, environmental implications of the three recovery modes differ from their impact on consumer surplus and firm profit. While recovery forms (i) and (iii) reduce consumption and increase environmental benefits, the same is not true with recovery form (ii), which can increase consumption, potentially resulting in higher environmental impact.     

Searching for innovation: Product,process, and business model innovations and search behavior in established firms

Prior research indicates that search practices are an important part of the innovation process. But where established firms search for different innovation types is not clear. Drawing on knowledge-based theory of innovation and using state-of-the-art statistical techniques (copula with Bayesian inference), we find that established firms predominantly rely on several external sources (broad external search) when introducing new business models, on internal and external sources with high intensity (deep search) when innovating processes, and on broad and deep external search when innovating products. We explain that broad external search is important for business model innovation (BMI) because increased exploration is needed when introducing new business models that rely on general rather than specialized technical or tacit business knowledge. We contribute to the innovation and business model literatures by nuancing the differences between innovation types (BMI, product, and process innovation) and the associated search behavior. It is important to consider these differences because they give us clues to understand how established firms can explore unfamiliar territories through BMI.