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.     

MATERIALS PRICES AND PRODUCTIVITY

There is substantial within‐industry variation in the prices that plants pay for their material inputs. Using plant‐level data from the US Census Bureau, I explore the consequences and sources of this variation in materials prices. For a sample of industries with relatively homogeneous products, the standard deviation of plant‐level productivity would be 7% smaller if all plants faced the same materials prices. Moreover, plant‐level materials prices are persistent, spatially correlated, and positively associated with the probability of exit. The contribution of entry and exit to aggregate productivity growth is smaller for productivity measures that are purged of materials price variation. After documenting these patterns, I discuss three potential sources of materials price variation: geography, differences in suppliers' marginal costs, and within‐supplier markup differences. Together, these variables explain 15% of the variation of materials prices.     

Efficient Take‐Back Legislation

Product and waste take‐back is becoming more regulated by countries to protect the environment. Such regulation puts an economic burden on firms, while creating fairness concerns and potentially even missing its primary target: environmental benefits. This research discusses the economic and environmental impacts of extended producer responsibility type of legislation and identifies efficiency conditions. It is shown that the right policy would (i) make producers responsible for their own waste to avoid fairness concerns and (ii) favor eco‐design producers to create stronger environmental benefits. Furthermore, the efficiency of take‐back systems is also driven by environmental classification of products, industry structure, and end‐user willingness to participate in take‐back programs.     

Extended Producer Responsibility for E‐Waste: Individual or Collective Producer Responsibility?

We investigate the implications of collective and individual producer responsibility (CPR and IPR, respectively) models of product take‐back laws for e‐waste on manufacturers’ design for product recovery (DfR) choices and profits, and on consumer surplus in the presence of product competition. We show that IPR offers superior DfR incentives as compared to CPR, and provides a level competitive ground. CPR may distort competition and allow free‐riding on DfR efforts to reduce product recovery costs. Thus, manufacturer preferences for IPR or CPR may differ because of the free‐riding implications under CPR, with even high‐end manufacturers having incentives to free‐ride under certain competitive conditions. The policy choice between IPR and CPR is not clear cut from an economic welfare perspective. This choice involves a comparison between the effects of superior recovery cost reduction through improved DfR under IPR and the operational cost‐efficiency under CPR.     

How Collection Cost Structure Drives a Manufacturer's Reverse Channel Choice

This note discusses the impact of collection cost structure on the optimal reverse channel choice of manufacturers who remanufacture their own products. Using collection cost functions that capture collection rate and collection volume dependency, we show that the optimal reverse channel choice (retailer‐ vs. manufacturer‐managed collection) is driven by how the cost structure moderates the manufacturer's ability to shape the retailer's sales and collection quantity decisions.     

Circular success and failure runs in a sequence of exchangeable binary trials

Let X₁,…,X_n be an exchangeable sequence of binary trials arranged on a circle with possible values “1” (success) or “0” (failure). In an exchangeable sequence, the joint distribution of X₁,X₂,…,X_n is invariant under the permutation of its arguments. For the circular sequence, general expressions for the joint distributions of run statistics based on the joint distribution of success and failure run lengths are obtained. As a special case, we present our results for Bernoulli trials. The results presented consist of combinatorial terms and therefore provide easier calculations. For illustration purposes, some numerical examples are given and the reliability of the circular combined k-out-of-n:G and consecutive k_c-out-of-n:G system under stress–strength setup is evaluated.     

Profust reliability of linear and circular type F and G systems having two failure criteria under Markov dependency

In this study, the profust reliabilities of (n, f, k): F(G) and < n, f, k > : F(G) systems for Markov dependent components are investigated. Having two failure criteria are the common features of these four systems. The usage of both fuzzy approach and two failure criteria in the same system provides us more realistic approach to evaluate the reliability of more complex systems. The component configurations are examined for both linear and circular sequences and the working principle of systems are studied for both F and G systems. Under all these assumptions, the profust reliabilities of (n, f, k): F(G) and < n, f, k > : F(G) systems are obtained using the distribution of run statistics. Also a new membership function different from the linear membership function which is generally used in the literature is proposed. Some numerical results which allow the comparison of the systems from various perspectives and various figures for both linear and circular type systems are presented. Some special cases (between Markov – iid assumption, conventional – profust reliability) are also considered.     

The effect of retirement on home production: evidence from Australia

Review of Economics of the Household - This paper examines the effect of retirement on individuals’ time spent on home production activities. Using rich longitudinal data from Australia and...     

Stakeholder Perspectives on E‐Waste Take‐Back Legislation

In this study, we compare two common forms of product take‐back legislation implementation: (i) manufacturer‐operated systems, where the state imposes certain take‐back objectives on manufacturers, and (ii) state‐operated systems, where manufacturers or consumers finance take‐back through recovery fees. We show that their impacts on different stakeholders, that is, social welfare, manufacturers, consumers, and the environment, can be significantly different and stakeholder preferences for these models vary depending on the operating environments (e.g., production and take‐back costs, and environmental externalities). We also consider the impact of operational externalities such as operating and monitoring costs, and show how they affect stakeholder preferences.