Problem definition: Scan based trading (SBT) represents a type of replenishment system in which the supplier retains title until the product is scanned through checkout at the retail store by the consumer. Although SBT carries potential benefits for both parties in the supplier-retailer dyad, it may also yield asymmetric gains to these parties, particularly because SBT can impose greater inventory costs to suppliers through shrink. We document the financial benefits in terms of supply chain profit creation and allocation based on the differences in bargaining power between parties in a vertical channel under SBT vis-à-vis the more traditional vendor-managed inventory (VMI) contracts. Academic/practical relevance: Although prior literature has examined inventory benefits and drawbacks from VMI and SBT contracts in retailer-supplier dyads, it has failed to offer a systematic evaluation of the relative impact of these contract forms on bargaining power and profits in these dyads. We address this knowledge gap. Methodology: To that end, we use a methodological approach that incorporates an empirical Nash-in-Nash bargaining model, a supplementary regression, and a counterfactual simulation. Results: We find that retailer bargaining power is higher under SBT relative to VMI contracts. Moreover, the direct effects of a retailer switching from VMI to SBT regimes generate an average increase of 25% in total supply chain profit, allowing the retailer and its supplier to increase their profit by 20% and 29%, respectively. However, although the retailer’s profit share decreases by approximately 3.5%, the supplier’s increases by about 3.3%. We attribute the decrease in the retailer’s share to a stronger bargaining position on the supplier side based on higher supplier shrink costs. Managerial implications: Our findings provide managers with more transparent information regarding the set of outcomes they can expect should they choose to enter into SBT contracts. Importantly, we show how an outcome that has significantly hindered the adoption of SBT contracts (i.e., shrink costs) can enter into the negotiation between retailers and suppliers to optimally split the dyadic surplus of the contracts between these parties.
{"title":"Scan Based Trading and Bargaining Equilibrium: A Structural Estimation of Supply Chain Profit","authors":"S. Lim, T. Richards, E. Rabinovich, Min Choi","doi":"10.1287/msom.2022.1087","DOIUrl":"https://doi.org/10.1287/msom.2022.1087","url":null,"abstract":"Problem definition: Scan based trading (SBT) represents a type of replenishment system in which the supplier retains title until the product is scanned through checkout at the retail store by the consumer. Although SBT carries potential benefits for both parties in the supplier-retailer dyad, it may also yield asymmetric gains to these parties, particularly because SBT can impose greater inventory costs to suppliers through shrink. We document the financial benefits in terms of supply chain profit creation and allocation based on the differences in bargaining power between parties in a vertical channel under SBT vis-à-vis the more traditional vendor-managed inventory (VMI) contracts. Academic/practical relevance: Although prior literature has examined inventory benefits and drawbacks from VMI and SBT contracts in retailer-supplier dyads, it has failed to offer a systematic evaluation of the relative impact of these contract forms on bargaining power and profits in these dyads. We address this knowledge gap. Methodology: To that end, we use a methodological approach that incorporates an empirical Nash-in-Nash bargaining model, a supplementary regression, and a counterfactual simulation. Results: We find that retailer bargaining power is higher under SBT relative to VMI contracts. Moreover, the direct effects of a retailer switching from VMI to SBT regimes generate an average increase of 25% in total supply chain profit, allowing the retailer and its supplier to increase their profit by 20% and 29%, respectively. However, although the retailer’s profit share decreases by approximately 3.5%, the supplier’s increases by about 3.3%. We attribute the decrease in the retailer’s share to a stronger bargaining position on the supplier side based on higher supplier shrink costs. Managerial implications: Our findings provide managers with more transparent information regarding the set of outcomes they can expect should they choose to enter into SBT contracts. Importantly, we show how an outcome that has significantly hindered the adoption of SBT contracts (i.e., shrink costs) can enter into the negotiation between retailers and suppliers to optimally split the dyadic surplus of the contracts between these parties.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"33 1","pages":"2328-2348"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78543294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: Agile project management, in particular Scrum, is enjoying increased use in practice despite only scant scientific validation. This article explores how agile project management impacts project performance and execution. We compare the effects of agile sprints—short-term project phases characterized by time-boxed progression from one sprint to the next and self-imposed, phase-specific output goals—with those of traditional project management. Methodology/results: We decompose the two sprint elements of time-boxed progression and self-imposed, phase-specific output goals as factors in a 2 × 2 experimental design. We then conceptualize project execution as a simple real-effort task and conduct a controlled laboratory study. For a given duration, participants perform better with time-boxed progression as, without it, that is, with flexible progression, they spend too much time on early project phases at the expense of later ones. We refer to this effect as “progression fallacy” and show how it differs from well-known behavioral effects that cause project delays. Introducing self-imposed, phase-specific output goals in combination with time-boxed progression, as proposed by Scrum, does not significantly improve performance when compared with time-boxed progression alone. However, the combination of self-imposed, phase-specific output goals and flexible progression, as is common in traditional project management, amplifies the progression fallacy with the result that goal-setting has a negative performance effect. In two control treatments, we show that the progression fallacy is robust to planning and progression prompts despite some mitigation. Managerial implications: This study contributes evidence of higher project performance when working in agile sprints, which mitigate behavioral flaws present in traditional project management. Not only do these behavioral insights apply to project management; they are also relevant in the broader context of task completion.
{"title":"Should We All Work in Sprints? How Agile Project Management Improves Performance","authors":"Tobias Lieberum, S. Schiffels, R. Kolisch","doi":"10.1287/msom.2022.1091","DOIUrl":"https://doi.org/10.1287/msom.2022.1091","url":null,"abstract":"Problem definition: Agile project management, in particular Scrum, is enjoying increased use in practice despite only scant scientific validation. This article explores how agile project management impacts project performance and execution. We compare the effects of agile sprints—short-term project phases characterized by time-boxed progression from one sprint to the next and self-imposed, phase-specific output goals—with those of traditional project management. Methodology/results: We decompose the two sprint elements of time-boxed progression and self-imposed, phase-specific output goals as factors in a 2 × 2 experimental design. We then conceptualize project execution as a simple real-effort task and conduct a controlled laboratory study. For a given duration, participants perform better with time-boxed progression as, without it, that is, with flexible progression, they spend too much time on early project phases at the expense of later ones. We refer to this effect as “progression fallacy” and show how it differs from well-known behavioral effects that cause project delays. Introducing self-imposed, phase-specific output goals in combination with time-boxed progression, as proposed by Scrum, does not significantly improve performance when compared with time-boxed progression alone. However, the combination of self-imposed, phase-specific output goals and flexible progression, as is common in traditional project management, amplifies the progression fallacy with the result that goal-setting has a negative performance effect. In two control treatments, we show that the progression fallacy is robust to planning and progression prompts despite some mitigation. Managerial implications: This study contributes evidence of higher project performance when working in agile sprints, which mitigate behavioral flaws present in traditional project management. Not only do these behavioral insights apply to project management; they are also relevant in the broader context of task completion.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"91 1","pages":"2293-2309"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79011243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: Our objective is to design a defibrillator-enabled drone network that augments the existing emergency medical services (EMS) system to rapidly respond to out-of-hospital cardiac arrest (OHCA). Academic/practical relevance: OHCA claims more than 400,000 lives each year in North America and is one of the most time-sensitive medical emergencies. Drone-delivered automated external defibrillators (AEDs) have the potential to be a transformative innovation in the provision of emergency care for OHCA. Methodology: We develop an integrated location-queuing model that incorporates existing EMS response times and is based on the p-median architecture, where each base constitutes an explicit [Formula: see text] queue (i.e., Erlang loss). We then develop a reformulation technique that exploits the existing EMS response times, allowing us to solve real-world instances to optimality using an off-the-shelf solver. We evaluate our solutions using a tactical simulation model that accounts for the effects of congestion and dispatching, and we use a machine-learning model to translate our response-time reductions into survival estimates. Results: Using real data from an area covering 26,000 square kilometers around Toronto, Canada, we find that a modest number of drones are required to significantly reduce response times in all regions. An objective function that minimizes average response time results in drone resources concentrated in cities, with little impact on the tail of the distribution. In contrast, optimizing for the tail of the response-time distribution produces larger and more geographically dispersed drone networks that improve response-time equity across the regions. We estimate that the response-time reductions achieved by the drone network are associated with between a 42% and 76% higher survival rate and up to 144 additional lives saved each year across the geographical region we consider. Managerial implications: Overall, this paper provides a realistic framework that can be leveraged by system designers and/or EMS personnel seeking to investigate design questions associated with a drone network. An objective function focused on improving the tail of the response-time distribution is well-suited for use in practice because the model provides equitable solutions that reduce the entire response-time distribution and corresponds to the real-world metrics, on which EMS systems are most commonly evaluated.
{"title":"Drone Network Design for Cardiac Arrest Response","authors":"J. Boutilier, Timothy C. Y. Chan","doi":"10.1287/msom.2022.1092","DOIUrl":"https://doi.org/10.1287/msom.2022.1092","url":null,"abstract":"Problem definition: Our objective is to design a defibrillator-enabled drone network that augments the existing emergency medical services (EMS) system to rapidly respond to out-of-hospital cardiac arrest (OHCA). Academic/practical relevance: OHCA claims more than 400,000 lives each year in North America and is one of the most time-sensitive medical emergencies. Drone-delivered automated external defibrillators (AEDs) have the potential to be a transformative innovation in the provision of emergency care for OHCA. Methodology: We develop an integrated location-queuing model that incorporates existing EMS response times and is based on the p-median architecture, where each base constitutes an explicit [Formula: see text] queue (i.e., Erlang loss). We then develop a reformulation technique that exploits the existing EMS response times, allowing us to solve real-world instances to optimality using an off-the-shelf solver. We evaluate our solutions using a tactical simulation model that accounts for the effects of congestion and dispatching, and we use a machine-learning model to translate our response-time reductions into survival estimates. Results: Using real data from an area covering 26,000 square kilometers around Toronto, Canada, we find that a modest number of drones are required to significantly reduce response times in all regions. An objective function that minimizes average response time results in drone resources concentrated in cities, with little impact on the tail of the distribution. In contrast, optimizing for the tail of the response-time distribution produces larger and more geographically dispersed drone networks that improve response-time equity across the regions. We estimate that the response-time reductions achieved by the drone network are associated with between a 42% and 76% higher survival rate and up to 144 additional lives saved each year across the geographical region we consider. Managerial implications: Overall, this paper provides a realistic framework that can be leveraged by system designers and/or EMS personnel seeking to investigate design questions associated with a drone network. An objective function focused on improving the tail of the response-time distribution is well-suited for use in practice because the model provides equitable solutions that reduce the entire response-time distribution and corresponds to the real-world metrics, on which EMS systems are most commonly evaluated.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"123 1","pages":"2407-2424"},"PeriodicalIF":0.0,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83336321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: Bargaining situations are ubiquitous in economics and management. We consider the problem of bargaining for a fair ex ante distribution of random profits arising from a cooperative effort of a fixed set of risk-averse agents. Our approach integrates optimal managerial decision making into bargaining situations with random outcomes and explicitly models the impact of risk aversion. The proposed solution rests on a firm axiomatic foundation and yet allows to compute concrete bargaining solutions for a wide range of practically relevant problems. Methodology/results: We model risk preferences using coherent acceptability functionals and base our bargaining solution on a set of axioms that can be considered a natural extension of Nash bargaining to our setting. We show that the proposed axioms fully characterize a bargaining solution, which can be efficiently computed by solving a stochastic optimization problem. We characterize special cases where random payoffs of players are simple functions of overall project profit. In particular, we show that, for players with distortion risk functionals, the optimal bargaining solution can be represented by an exchange of standard options contracts with the project profit as the underlying asset. We illustrate the concepts in the paper with a detailed example of risk-averse households that jointly invest into a solar plant. Managerial implications: We demonstrate that there is no conflict of interest between players about management decisions and that risk aversion facilitates cooperation. Furthermore, our results on the structure of optimal contracts as a basket of option contracts provides valuable guidance for negotiators.
{"title":"Risk-Averse Bargaining in a Stochastic Optimization Context","authors":"W. Gutjahr, Raimund M. Kovacevic, D. Wozabal","doi":"10.1287/msom.2021.1076","DOIUrl":"https://doi.org/10.1287/msom.2021.1076","url":null,"abstract":"Problem definition: Bargaining situations are ubiquitous in economics and management. We consider the problem of bargaining for a fair ex ante distribution of random profits arising from a cooperative effort of a fixed set of risk-averse agents. Our approach integrates optimal managerial decision making into bargaining situations with random outcomes and explicitly models the impact of risk aversion. The proposed solution rests on a firm axiomatic foundation and yet allows to compute concrete bargaining solutions for a wide range of practically relevant problems. Methodology/results: We model risk preferences using coherent acceptability functionals and base our bargaining solution on a set of axioms that can be considered a natural extension of Nash bargaining to our setting. We show that the proposed axioms fully characterize a bargaining solution, which can be efficiently computed by solving a stochastic optimization problem. We characterize special cases where random payoffs of players are simple functions of overall project profit. In particular, we show that, for players with distortion risk functionals, the optimal bargaining solution can be represented by an exchange of standard options contracts with the project profit as the underlying asset. We illustrate the concepts in the paper with a detailed example of risk-averse households that jointly invest into a solar plant. Managerial implications: We demonstrate that there is no conflict of interest between players about management decisions and that risk aversion facilitates cooperation. Furthermore, our results on the structure of optimal contracts as a basket of option contracts provides valuable guidance for negotiators.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"4 1","pages":"323-340"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73201993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Telesilla O. Kotsi, Owen Q. Wu, Alfonso J. Pedraza Martinez
Problem definition: Six million refugees have been living in camps in 2021 due to multiple armed conflicts worldwide. Regulations often impede refugees’ integration into host countries; thus, refugees have to seek help from humanitarian organizations (HOs). HOs traditionally provide in-kind (e.g., food) assistance and now offer cash (monetary assistance) that refugees can spend at local retail stores. However, cash assistance can be exploited by local retailers’ market power, which challenges HOs’ mission of helping refugees while doing no harm to host communities. Practical relevance: Completely informed by field research in three refugee camps in northwestern Greece, we analyze the trade-off between in-kind and cash assistance from the perspective of an HO. We propose two cash assistance policies, implementable by a partnership between the HO and the local government, to curb the retailer’s market power and ensure that the refugees, the local residents, and the retailer are better off than if only in-kind assistance is provided. Methodology: We use field research to define our research setting and support our main modeling assumptions and parameters. Then, we use a game-theoretical model to analyze the interactions among multiple stakeholders in an ecosystem consisting of an HO, refugees, a monopolistic retailer, local residents, and a local government. Results: We demonstrate the effectiveness of our proposed cash assistance policies that benefit refugees and local residents while ensuring the retailer’s profitability. In particular, a price-dependent cash assistance (PDCA) policy aligns the incentives between the retailer and the HO-government partnership. This new policy for cash assistance acts as a lever for the retailer to voluntarily set desirable prices, which benefit both refugees and their host community. Managerial implications: We provide tools and implementable policies that guide HOs to improve their budget allocation between in-kind and cash assistance for refugees living in areas where local market power exists. Moreover, we clearly outline the roles of HOs and the local government in a partnership for cash assistance to refugees.
{"title":"Donations for Refugee Crises: In-kind vs. Cash Assistance","authors":"Telesilla O. Kotsi, Owen Q. Wu, Alfonso J. Pedraza Martinez","doi":"10.1287/msom.2021.1073","DOIUrl":"https://doi.org/10.1287/msom.2021.1073","url":null,"abstract":"Problem definition: Six million refugees have been living in camps in 2021 due to multiple armed conflicts worldwide. Regulations often impede refugees’ integration into host countries; thus, refugees have to seek help from humanitarian organizations (HOs). HOs traditionally provide in-kind (e.g., food) assistance and now offer cash (monetary assistance) that refugees can spend at local retail stores. However, cash assistance can be exploited by local retailers’ market power, which challenges HOs’ mission of helping refugees while doing no harm to host communities. Practical relevance: Completely informed by field research in three refugee camps in northwestern Greece, we analyze the trade-off between in-kind and cash assistance from the perspective of an HO. We propose two cash assistance policies, implementable by a partnership between the HO and the local government, to curb the retailer’s market power and ensure that the refugees, the local residents, and the retailer are better off than if only in-kind assistance is provided. Methodology: We use field research to define our research setting and support our main modeling assumptions and parameters. Then, we use a game-theoretical model to analyze the interactions among multiple stakeholders in an ecosystem consisting of an HO, refugees, a monopolistic retailer, local residents, and a local government. Results: We demonstrate the effectiveness of our proposed cash assistance policies that benefit refugees and local residents while ensuring the retailer’s profitability. In particular, a price-dependent cash assistance (PDCA) policy aligns the incentives between the retailer and the HO-government partnership. This new policy for cash assistance acts as a lever for the retailer to voluntarily set desirable prices, which benefit both refugees and their host community. Managerial implications: We provide tools and implementable policies that guide HOs to improve their budget allocation between in-kind and cash assistance for refugees living in areas where local market power exists. Moreover, we clearly outline the roles of HOs and the local government in a partnership for cash assistance to refugees.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"1 1","pages":"3001-3018"},"PeriodicalIF":0.0,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77237102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: We present a data-driven pricing problem motivated from our collaboration with a satellite service provider. In particular, we study a variant of the two-part tariff pricing scheme. The firm offers a set of data plans consisting of a bundle of data at a fixed price plus additional data at a variable price. Most literature on two-part tariff problems focuses on models that assume full information. However, little attention has been devoted to this problem from a data-driven perspective without full information. One of the main challenges when working with data comes from missing data. Methodology/results: First, we develop a new method to address the missing data problem, which comes from different sources: (i) the number of unobserved customers, (ii) customers’ willingness to pay (WTP), and (iii) demand from unobserved customers. We introduce an iteration procedure to maximize the likelihood by combining the expectation maximization algorithm with a gradient ascent method. We also formulate the pricing optimization problem as a dynamic program (DP) using a discretized set of prices. From applying Sample Average Approximation, the DP obtains a solution within 3.8% of the optimal solution of the sampled instances, on average, and within 18% with 95% confidence from the optimal solution of the exact problem. By extending the DP formulation, we show that it is better to optimize on prices rather than bundles, obtaining revenues close to optimizing jointly on both. Managerial implications: The sensitivity analysis of the problem parameters is key for decision makers to understand the risks of their pricing decisions. Indeed, assuming a higher variability of customers’ WTP induces higher revenue risks. In addition, revenues are barely (highly) sensitive to the customers’ assumed WTP variability when considering a high (low) number of unobserved customers. Finally, we extend the model to incorporate price-dependent consumption.
{"title":"On a Variation of Two-Part Tariff Pricing of Services: A Data-Driven Approach","authors":"G. Perakis, Charles Thraves","doi":"10.1287/msom.2021.1069","DOIUrl":"https://doi.org/10.1287/msom.2021.1069","url":null,"abstract":"Problem definition: We present a data-driven pricing problem motivated from our collaboration with a satellite service provider. In particular, we study a variant of the two-part tariff pricing scheme. The firm offers a set of data plans consisting of a bundle of data at a fixed price plus additional data at a variable price. Most literature on two-part tariff problems focuses on models that assume full information. However, little attention has been devoted to this problem from a data-driven perspective without full information. One of the main challenges when working with data comes from missing data. Methodology/results: First, we develop a new method to address the missing data problem, which comes from different sources: (i) the number of unobserved customers, (ii) customers’ willingness to pay (WTP), and (iii) demand from unobserved customers. We introduce an iteration procedure to maximize the likelihood by combining the expectation maximization algorithm with a gradient ascent method. We also formulate the pricing optimization problem as a dynamic program (DP) using a discretized set of prices. From applying Sample Average Approximation, the DP obtains a solution within 3.8% of the optimal solution of the sampled instances, on average, and within 18% with 95% confidence from the optimal solution of the exact problem. By extending the DP formulation, we show that it is better to optimize on prices rather than bundles, obtaining revenues close to optimizing jointly on both. Managerial implications: The sensitivity analysis of the problem parameters is key for decision makers to understand the risks of their pricing decisions. Indeed, assuming a higher variability of customers’ WTP induces higher revenue risks. In addition, revenues are barely (highly) sensitive to the customers’ assumed WTP variability when considering a high (low) number of unobserved customers. Finally, we extend the model to incorporate price-dependent consumption.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"14 1","pages":"1369-1387"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73197370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: We study profit allocation for a sourcing network, in which a buyer sources from a set of differentiated suppliers with limited capacity under uncertain demand for the final product. Whereas the buyer takes the lead in forming the sourcing network and designing the contract mechanism, due to their substantial bargaining power, the suppliers take the lead in determining the terms of the contract. Academic/practical relevance: We identify contracting mechanisms that will ensure the stability of the sourcing network in the long term, where a stable sourcing network requires an effective profit-allocation scheme that motivates all members to join and stay in the network. Methodology: We apply methods from game theory to model the network and analyze the Nash equilibrium of a noncooperative game under a proposed contracting mechanism. We then use a cooperative game model to study the stability of the resulting equilibrium. Results: We show that the optimal network profit, as a set function of the set of suppliers, is submodular, which allows us to demonstrate that the core of the cooperative game is not empty. We also establish a set of conditions that are equivalent to, but much simpler than, the original conditions for the core. We use these results to demonstrate that the proposed fixed-fee contracting mechanism can implement a stable network in the competitive setting by achieving a profit allocation that is in the core of the cooperative game. We also demonstrate that the grand coalition is stable in a farsighted sense under the Shapley value allocation. Managerial implications: Under the fixed-fee mechanism, the buyer’s decisions maximize the network profit, and each supplier earns a profit equal to its marginal contribution. When the aggregate capacity of the supplier network is high relative to demand, or demand is more likely to be small, the fixed-fee mechanism is likely to outperform the Shapley value allocation from the perspective of the buyer.
{"title":"Contracting Mechanisms for Stable Sourcing Networks","authors":"J. Ryan, Lusheng Shao, Daewon Sun","doi":"10.1287/msom.2021.1066","DOIUrl":"https://doi.org/10.1287/msom.2021.1066","url":null,"abstract":"Problem definition: We study profit allocation for a sourcing network, in which a buyer sources from a set of differentiated suppliers with limited capacity under uncertain demand for the final product. Whereas the buyer takes the lead in forming the sourcing network and designing the contract mechanism, due to their substantial bargaining power, the suppliers take the lead in determining the terms of the contract. Academic/practical relevance: We identify contracting mechanisms that will ensure the stability of the sourcing network in the long term, where a stable sourcing network requires an effective profit-allocation scheme that motivates all members to join and stay in the network. Methodology: We apply methods from game theory to model the network and analyze the Nash equilibrium of a noncooperative game under a proposed contracting mechanism. We then use a cooperative game model to study the stability of the resulting equilibrium. Results: We show that the optimal network profit, as a set function of the set of suppliers, is submodular, which allows us to demonstrate that the core of the cooperative game is not empty. We also establish a set of conditions that are equivalent to, but much simpler than, the original conditions for the core. We use these results to demonstrate that the proposed fixed-fee contracting mechanism can implement a stable network in the competitive setting by achieving a profit allocation that is in the core of the cooperative game. We also demonstrate that the grand coalition is stable in a farsighted sense under the Shapley value allocation. Managerial implications: Under the fixed-fee mechanism, the buyer’s decisions maximize the network profit, and each supplier earns a profit equal to its marginal contribution. When the aggregate capacity of the supplier network is high relative to demand, or demand is more likely to be small, the fixed-fee mechanism is likely to outperform the Shapley value allocation from the perspective of the buyer.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"75 1","pages":"2558-2576"},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86392172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Problem definition: Despite the widespread adoption of environmental management systems (EMS), their relationship with energy efficiency remains unclear. This study investigates whether and how EMS adoption lowers energy efficiency and, if so, how to mitigate the impact. Academic/practical relevance: Understanding the relationship between EMS and energy efficiency is important because any decrease in energy efficiency may eventually lead to undesired environmental outputs (e.g., CO2), potentially contributing to climate change. This study sheds light on energy as a necessary input required for environmental management, thereby elucidating the issue of environmental trade-offs in sustainable operations. Methodology: Using novel panel data on energy efficiency and EMS standards obtained from 2,690 South Korean plants operating between 2001 and 2014, this study empirically investigates the impact of EMS on energy efficiency at the plant level. Results: We provide evidence of a trade-off relationship between environmental performance and energy efficiency in relation to EMS adoption. We find that the adoption of ISO 14001, the representative EMS standard, results in approximately 6%–12% lower energy efficiency compared with nonadoption although it effectively reduces air, water, and waste pollution. More importantly, our results show that the trade-off, an unintended consequence of EMS implementation, can be moderated through quality management capability. Managerial implications: We suggest that sustainability managers take balancing actions to reduce trade-offs between environmental performance and energy efficiency. Specifically, when implementing EMS, managers are advised to (1) actively incorporate energy management activities, (2) employ more comprehensive measurements for energy efficiency, and (3) redesign incentive schemes to facilitate improvements in energy efficiency.
{"title":"Environment and Energy? The Impact of Environmental Management Systems on Energy Efficiency","authors":"Seong-Bae Jeong, Jaeseok Lee","doi":"10.1287/msom.2021.1057","DOIUrl":"https://doi.org/10.1287/msom.2021.1057","url":null,"abstract":"Problem definition: Despite the widespread adoption of environmental management systems (EMS), their relationship with energy efficiency remains unclear. This study investigates whether and how EMS adoption lowers energy efficiency and, if so, how to mitigate the impact. Academic/practical relevance: Understanding the relationship between EMS and energy efficiency is important because any decrease in energy efficiency may eventually lead to undesired environmental outputs (e.g., CO2), potentially contributing to climate change. This study sheds light on energy as a necessary input required for environmental management, thereby elucidating the issue of environmental trade-offs in sustainable operations. Methodology: Using novel panel data on energy efficiency and EMS standards obtained from 2,690 South Korean plants operating between 2001 and 2014, this study empirically investigates the impact of EMS on energy efficiency at the plant level. Results: We provide evidence of a trade-off relationship between environmental performance and energy efficiency in relation to EMS adoption. We find that the adoption of ISO 14001, the representative EMS standard, results in approximately 6%–12% lower energy efficiency compared with nonadoption although it effectively reduces air, water, and waste pollution. More importantly, our results show that the trade-off, an unintended consequence of EMS implementation, can be moderated through quality management capability. Managerial implications: We suggest that sustainability managers take balancing actions to reduce trade-offs between environmental performance and energy efficiency. Specifically, when implementing EMS, managers are advised to (1) actively incorporate energy management activities, (2) employ more comprehensive measurements for energy efficiency, and (3) redesign incentive schemes to facilitate improvements in energy efficiency.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"26 1","pages":"1311-1328"},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81749199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brian Rongqing Han, Tianshu Sun, Leon Yang Chu, Lixia Wu
Problem definition: This paper investigates the impact of COVID-19 on e-commerce sales and the underlying operational driver. Academic/practical relevance: As COVID-19 continues to disrupt offline retail, anecdotal evidence suggests a rapid growth of e-commerce. However, the pandemic may also significantly decrease offline logistics capacity, which in turn decreases e-commerce sales. Then, how does e-commerce respond to COVID-19, and what are the corresponding opportunities and challenges? Methodology: We leverage e-commerce sales data from Alibaba and construct a city-day panel across three years, representing sales for all buyers and sellers on the platform across 339 cities in mainland China. We develop three identification strategies to estimate the overall impact of COVID-19 (based on a year-on-year comparison), the impact of COVID-19 intensity (based on the different number of cases across cities), and the impact of corresponding containment measures (leveraging policy changes of checkpoint, partial shutdown, and complete shutdown measures across cities). Results: We provide two key findings. First, across different identification strategies, we observe a common drop and recovery pattern, which illustrates the digital resilience of e-commerce during the pandemic. For example, we estimate an overall decrease of 22% in e-commerce sales during the period of the Wuhan shutdown (January 23–April 7, 2020). However, it recovers in most cities within five weeks. Second, we identify a key operational driver—logistics capacity—that significantly explains the decline and recovery of e-commerce sales during and after the outbreak. Managerial implications: We provide important evidence on how e-commerce responds to and recovers from COVID-19, contrary to the common perception. The evidence in the recovery phase can also inform platforms and policymakers to design digital strategies and invest in logistics infrastructure.
{"title":"COVID-19 and E-commerce Operations: Evidence from Alibaba","authors":"Brian Rongqing Han, Tianshu Sun, Leon Yang Chu, Lixia Wu","doi":"10.1287/msom.2021.1075","DOIUrl":"https://doi.org/10.1287/msom.2021.1075","url":null,"abstract":"Problem definition: This paper investigates the impact of COVID-19 on e-commerce sales and the underlying operational driver. Academic/practical relevance: As COVID-19 continues to disrupt offline retail, anecdotal evidence suggests a rapid growth of e-commerce. However, the pandemic may also significantly decrease offline logistics capacity, which in turn decreases e-commerce sales. Then, how does e-commerce respond to COVID-19, and what are the corresponding opportunities and challenges? Methodology: We leverage e-commerce sales data from Alibaba and construct a city-day panel across three years, representing sales for all buyers and sellers on the platform across 339 cities in mainland China. We develop three identification strategies to estimate the overall impact of COVID-19 (based on a year-on-year comparison), the impact of COVID-19 intensity (based on the different number of cases across cities), and the impact of corresponding containment measures (leveraging policy changes of checkpoint, partial shutdown, and complete shutdown measures across cities). Results: We provide two key findings. First, across different identification strategies, we observe a common drop and recovery pattern, which illustrates the digital resilience of e-commerce during the pandemic. For example, we estimate an overall decrease of 22% in e-commerce sales during the period of the Wuhan shutdown (January 23–April 7, 2020). However, it recovers in most cities within five weeks. Second, we identify a key operational driver—logistics capacity—that significantly explains the decline and recovery of e-commerce sales during and after the outbreak. Managerial implications: We provide important evidence on how e-commerce responds to and recovers from COVID-19, contrary to the common perception. The evidence in the recovery phase can also inform platforms and policymakers to design digital strategies and invest in logistics infrastructure.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"21 1","pages":"1388-1405"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80577571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David A. Wuttke, Ankit Upadhyay, Enno Siemsen, A. Wuttke-Linnemann
Problem definition: Firms increasingly use augmented reality (AR) devices to improve their production ramp-up processes. These devices appear useful, yet little is known about their broader impact on worker productivity and behavior. Academic/practical relevance: Efficient production ramp-ups are particularly important when product life cycles are short. An ongoing debate among academics and practitioners pertains to how Industry 4.0, and AR devices in particular, can accelerate the ramp-up. The current study provides empirical evidence related to AR in the production ramp-up context, examines the strengths and weaknesses of AR, and tests four hypotheses, leading to a more nuanced view of AR use in the manufacturing ramp-up. Methodology: A framed field experiment in a manufacturing plant provides a test of how quickly workers can perform new tasks with and without AR support and how the use of AR affects their ability to suggest process improvements. Results: When faced with a new task, workers instructed by AR smart glasses use 43.8% less time to complete the task compared with a control group that relies on paper-based instructions. However, workers that use AR glasses consistently use 23% more time than the control group when both groups repeat the task without either AR or paper-based instructions. Task difficulty moderates this relationship; workers assigned to a more difficult task benefit the most from AR instructions. After the devices are removed, workers instructed based on paper improve their productivity faster through learning than those instructed by AR. In addition, the former group suggests better process improvements than the latter one. Managerial implications: Although these results indicate substantially higher productivity resulting from AR devices, they also support the view that, once instructed through AR devices, workers come to rely on this new technology without fully internalizing the task. This failure to internalize their task then leads workers to suggest less useful process improvements.
{"title":"Seeing the Bigger Picture? Ramping up Production with the Use of Augmented Reality","authors":"David A. Wuttke, Ankit Upadhyay, Enno Siemsen, A. Wuttke-Linnemann","doi":"10.1287/msom.2021.1070","DOIUrl":"https://doi.org/10.1287/msom.2021.1070","url":null,"abstract":"Problem definition: Firms increasingly use augmented reality (AR) devices to improve their production ramp-up processes. These devices appear useful, yet little is known about their broader impact on worker productivity and behavior. Academic/practical relevance: Efficient production ramp-ups are particularly important when product life cycles are short. An ongoing debate among academics and practitioners pertains to how Industry 4.0, and AR devices in particular, can accelerate the ramp-up. The current study provides empirical evidence related to AR in the production ramp-up context, examines the strengths and weaknesses of AR, and tests four hypotheses, leading to a more nuanced view of AR use in the manufacturing ramp-up. Methodology: A framed field experiment in a manufacturing plant provides a test of how quickly workers can perform new tasks with and without AR support and how the use of AR affects their ability to suggest process improvements. Results: When faced with a new task, workers instructed by AR smart glasses use 43.8% less time to complete the task compared with a control group that relies on paper-based instructions. However, workers that use AR glasses consistently use 23% more time than the control group when both groups repeat the task without either AR or paper-based instructions. Task difficulty moderates this relationship; workers assigned to a more difficult task benefit the most from AR instructions. After the devices are removed, workers instructed based on paper improve their productivity faster through learning than those instructed by AR. In addition, the former group suggests better process improvements than the latter one. Managerial implications: Although these results indicate substantially higher productivity resulting from AR devices, they also support the view that, once instructed through AR devices, workers come to rely on this new technology without fully internalizing the task. This failure to internalize their task then leads workers to suggest less useful process improvements.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"49 5 1","pages":"2349-2366"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89069667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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