4.7 Article

A two-period model of product cannibalization in an atypical Closed-loop Supply Chain with endogenous returns: The case of DellReconnect

Journal

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 262, Issue 3, Pages 1009-1027

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2017.03.080

Keywords

Game theory; DellReconnect project; Cannibalization; Product returns; Product resale value

Ask authors/readers for more resources

In this paper we develop a two-period model of an atypical Closed-loop Supply Chain (CLSC) consistent with the DellReconnect project. In our setting, a manufacturer (Dell) sells new products in the first period and faces the threat of cannibalization in the second period from a Goodwill agency, which collects and refurbishes the manufacturer's goods and sells them as used products. Surprisingly, and unlike the findings from the marketing literature, cannibalization does-not lower the manufacturer's sales in both periods; however, it does negatively impact the manufacturer's profits and positively affect the Goodwill agency's profits. We demonstrate that in an atypical CLSC, a reduction in the price of new products is never sufficient to counter the negative effect of cannibalization. We then introduce an advertising strategy, through which the manufacturer complements its pricing strategy, endogenizes the returns, and positively affects both the new and used product demands. Although the advertising strategy positively influences the product returns, it continues to be insufficient to counter the negative effect of cannibalization. Interestingly, we now find that cannibalization is detrimental even for the Goodwill agency, whose profits decrease when the cannibalization level exceeds a certain threshold. Finally, we show that when a product resale value option exists, the manufacturer can convert the cannibalization threat into a business opportunity and increase its profits, independent of an advertising strategy. Thus, the manufacturer should always collect through a Goodwill agency when sufficiently large resale value options exist. (C) 2017 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Engineering, Industrial

Closed-loop supply chain models with coopetition options

Hamed Jalali, Amir Ansaripoor, Vinay Ramani, Pietro De Giovanni

Summary: This study introduces a game-theoretic model of a closed-loop supply chain involving an Original Equipment Manufacturer (OEM) and a social collector. The research shows that while the social collector is indifferent between coopetition and competition, the OEM strictly prefers coopetition.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2022)

Article Operations Research & Management Science

A selective survey of game-theoretic models of closed-loop supply chains

Pietro De Giovanni, Georges Zaccour

Summary: This paper surveys two crucial issues in Closed-loop Supply Chain (CLSC) research: return functions and coordination mechanisms. Return functions determine the rules for returning end-of-life/use products to a collector, while coordination mechanisms align the objectives of closed-loop supply chain members through the adoption of specific mechanisms, such as contracts. The paper describes the latest developments in these two major CLSC-related fields and suggests future research directions.

ANNALS OF OPERATIONS RESEARCH (2022)

Article Management

Technology and service investments in the presence of feature fatigue and word-of-mouth

Sara Rezaee Vessal, Pietro De Giovanni, Alborz Hassanzadeh

Summary: In the digital age, firms strive to meet the needs of sophisticated consumers by offering leading technologies and superior quality products. However, the complexity of these high-tech products can lead to feature fatigue, which generates frustration among consumers. This study examines the impact of feature fatigue on a manufacturing firm's product-service portfolio design and finds that it drives manufacturers to under invest in quality and change pricing policies. The study also shows that after-sales service cannot fully alleviate the detrimental effect of feature fatigue on a manufacturer's profits.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2022)

Article Business

Responsible digitalization through digital technologies and green practices

Pier Giacomo Cardinali, Pietro De Giovanni

Summary: This research examines how firms can achieve responsible digitalization by combining digital technologies and green practices to fulfill corporate social responsibility goals. It identifies key factors for responsible digitalization.

CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT (2022)

Article Management

Traceability vs. sustainability in supply chains: The implications of blockchain

Debajyoti Biswas, Hamed Jalali, Amir H. Ansaripoor, Pietro De Giovanni

Summary: This research proposes a game theory model to analyze the trade-offs between traceability and sustainability in the adoption of blockchain technology in global supply chains. The study finds that high distrust levels discourage firms from implementing blockchain, while low distrust levels make it an economically suitable technology with minimal environmental damages. The study also highlights the importance of consumer sensitivity to price and quality in determining the adoption of blockchain technology.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2023)

Review Management

A survey of dynamic models of product quality

Pietro De Giovanni, Georges Zaccour

Summary: This article reviews dynamic quality models in both single-agent setup and competitive frameworks. The objectives are to provide the reader with the latest developments in this field, identify the boundaries between different quality concepts, and outline a research agenda. The article is not only relevant to active researchers in the field but also to scholars and practitioners in operations management, marketing, industrial engineering, and operations research who are interested in quality dynamics.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2023)

Article Economics

Offshoring motivations driven by sustainability factors

Daniele Morganti, Pietro De Giovanni

Summary: This research examines firms' motivations for offshoring and finds that sustainable initiatives reduce the motivation for offshoring in most cases. Corporate Social Responsibility performance discourages offshoring related to labor cost benefits, energy savings, and host governments' sustainable programs. Domestic governments' sustainable initiatives can support firms that forfeit potential benefits, while suppliers' sustainable initiatives push firms towards offshoring.

RESEARCH IN TRANSPORTATION ECONOMICS (2022)

Article Green & Sustainable Science & Technology

Green practices and operational performance: The moderating role of agility

Lorenzo Salandri, Giovanni Luca Cascio Rizzo, Alessandra Cozzolino, Pietro De Giovanni

Summary: This research paper investigates the impact of agility on the relationship between green practices and operational performance. The study finds that agility can improve the impact of green practices on operational performance. Specifically, focusing on green practices related to the circular economy, such as recycling, recovery, and reuse, can enhance operational performance. On the other hand, eco-materials and green packaging do not significantly affect operational performance. Moreover, the study suggests that agility can completely reverse the impact of green practices on operational performance. When agility plays a moderating role, recycling, recovery, and reuse have no significant impact, while eco-materials and green packaging have a positive influence on operational performance.

JOURNAL OF CLEANER PRODUCTION (2022)

Article Green & Sustainable Science & Technology

Circular Economy Guidelines for the Textile Industry

Rocco Furferi, Yary Volpe, Franco Mantellassi

Summary: Textile production has a significant impact on the environment. Developing a circular economy policy can transform used textiles into valuable resources and reduce waste generation.

SUSTAINABILITY (2022)

Article Green & Sustainable Science & Technology

The Impact of Digital Technologies on Company Restoration Time Following the COVID-19 Pandemic

Giorgia Sammarco, Daniel Ruzza, Behzad Maleki Vishkaei, Pietro De Giovanni

Summary: This study investigates the implications of COVID-19 on companies and explores how they can achieve resilience through performance robustness and digital technology adoption. The findings suggest that the robustness of Sales is particularly important in contributing to restoration time. Additionally, the deployment of technologies such as Blockchain, 3D Printing, and Artificial Intelligence has a positive impact on firms' resilience during the outbreak.

SUSTAINABILITY (2022)

Article Management

Portfolios of sustainable practices for packaging in the circular economy: an analysis of Italian firms

Alessandra Cozzolino, Pietro De Giovanni

Summary: This study examines sustainable practices adopted by Italian firms to enhance packaging circularity and assesses their impact on environmental performance indicators. The findings indicate that firms tend to focus on individual sustainable practices rather than portfolios, with raw material saving and logistics optimization being the most frequently adopted practices. The reuse of packaging contributes to reductions in CO2 emissions, energy usage, and water consumption.

INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT (2023)

Article Green & Sustainable Science & Technology

Sustainability of the Metaverse: A Transition to Industry 5.0

Pietro De Giovanni

Summary: This study examines the sustainability of metaverse technology and its responsible adoption to drive the transition to Industry 5.0. It addresses the potential side effects of digital technologies, such as energy consumption, job displacement, and continuous payments, by providing frameworks to analyze the metaverse from a triple bottom line or ESG perspective, and linking it to business strategies or sustainable development goals. These tools enable responsible implementation, adoption, and management of the metaverse, allowing businesses to address and mitigate any negative impacts.

SUSTAINABILITY (2023)

Article Business

Rescheduling Multiproduct Delivery Planning With Digital Technologies for Smart Mobility and Sustainability Goals

Behzad Maleki Vishkaei, Pietro De Giovanni

Summary: In this article, the Load-Dependent Vehicle Routing Problem (LDVRP) is studied to develop an optimal delivery plan for vehicles carrying different types of products. The model takes into account various factors such as customer demands, rejection rates of products, time windows, and speed limits. Digital technologies are used to support decision-making due to the dynamic nature of the system. The proposed model is mathematically discussed and solved using a Genetic Algorithm, leading to sustainable solutions balancing environmental, social, and economic aspects.

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT (2023)

Article Management

The Impact of Digital Technologies and Sustainable Practices on Circular Supply Chain Management

Sara Romagnoli, Claudia Tarabu', Behzad Maleki Vishkaei, Pietro De Giovanni

Summary: This study investigates how firms can enhance their circular supply chains (CSCs) by adopting sustainable practices and digital technologies. The results show that green suppliers and environmental regulations, as well as transportation management systems (TMS) and the internet of things (IoT), are effective in promoting CSCs. Machine learning (ML) is effective in making green decisions and 3D printing extends product life.

LOGISTICS-BASEL (2023)

Article Business

The Selection of Industry 4.0 Technologies Through Bayesian Networks: An Operational Perspective

Pietro De Giovanni, Valeria Belvedere, Alberto Grando

Summary: This article examines the impact of Industry 4.0 technologies on operational performance in manufacturing firms. It analyzes the relationships between the technologies, constructs portfolios based on operational targets, and identifies possible operational improvements. The use of Bayesian network and machine-learning algorithms helps guide investment decisions in these technologies.

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT (2022)

Review Management

Survey of optimization models for power system operation and expansion planning with demand response

Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau

Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

R-SALSA: A branch, bound, and remember algorithm for the workload smoothing problem on simple assembly lines

Philipp Schulze, Armin Scholl, Rico Walter

Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Adaptive scheduling in service systems: A Dynamic programming approach

Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor

Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Discrete scheduling and critical utilization

Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang

Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Review Management

Supply chain network design with financial considerations: A comprehensive review

Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi

Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

A branch-and-cut algorithm for the connected max- k-cut problem

Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka

Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Estimating production functions through additive models based on regression splines

Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve

Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Time-flexible min completion time variance in a single machine by quadratic programming

Stefano Nasini, Rabia Nessah

Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Convex support vector regression

Zhiqiang Liao, Sheng Dai, Timo Kuosmanen

Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

A simulation evacuation framework for effective disaster preparedness strategies and response decision making

Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin

Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

An effective hybrid evolutionary algorithm for the clustered orienteering problem

Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu

Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Improving uplift model evaluation on randomized controlled trial data

Bjorn Bokelmann, Stefan Lessmann

Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Newsvendor conditional value-at-risk minimisation: A feature-based approach under adaptive data selection

Congzheng Liu, Wenqi Zhu

Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Right-left asymmetry of the eigenvector method: A simulation study

Laszlo Csato

Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)

Article Management

Compete or cooperate? Effects of channel relationships on government policies for sustainability

Guowei Dou, Tsan-Ming Choi

Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2024)