Problem definition: We analyzed the value of response time information in supply chain bargaining and how the transparency of response times affects bargaining dynamics and outcomes. Academic/practical relevance: The research on supply chain bargaining has focused on agents’ choices, whereas the value of process data, such as response times, has received limited attention. The process data underlying a decision can contain valuable information about the agents’ preference. Methodology: We conducted two laboratory experiments with multiround bargaining between a supplier and a retailer, where the supplier had private information about production costs. The retailer proposed wholesale prices to the supplier, and the supplier decided whether to reject or accept them. The experiments were composed of treatments with response time information (RT-Treatments) and those without response time information (noRT-Treatments). Suppliers’ response times were transparent to retailers in the RT-Treatment but were not transparent to those in the noRT-Treatment. Results: We found that suppliers’ response times could indicate their preference strengths regarding retailers’ proposals. In the RT-Treatment, retailers could use suppliers’ response times to their advantage. Compared with those in the noRT-Treatment, retailers in the RT-Treatment made lower initial proposals. The final wholesale prices in agreements were also lower in this treatment, resulting in higher average retailer and channel profits but lower supplier profits. Managerial implications: We demonstrated that response time information in supply chain bargaining revealed bargainers’ preferences and affected bargaining dynamics and outcomes. Bargainers could use their partners’ response times to improve their bargaining outcomes.
{"title":"The Value of Response Time Information in Supply Chain Bargaining","authors":"Fadong Chen, Yingshuai Zhao, U. W. Thonemann","doi":"10.1287/msom.2022.1138","DOIUrl":"https://doi.org/10.1287/msom.2022.1138","url":null,"abstract":"Problem definition: We analyzed the value of response time information in supply chain bargaining and how the transparency of response times affects bargaining dynamics and outcomes. Academic/practical relevance: The research on supply chain bargaining has focused on agents’ choices, whereas the value of process data, such as response times, has received limited attention. The process data underlying a decision can contain valuable information about the agents’ preference. Methodology: We conducted two laboratory experiments with multiround bargaining between a supplier and a retailer, where the supplier had private information about production costs. The retailer proposed wholesale prices to the supplier, and the supplier decided whether to reject or accept them. The experiments were composed of treatments with response time information (RT-Treatments) and those without response time information (noRT-Treatments). Suppliers’ response times were transparent to retailers in the RT-Treatment but were not transparent to those in the noRT-Treatment. Results: We found that suppliers’ response times could indicate their preference strengths regarding retailers’ proposals. In the RT-Treatment, retailers could use suppliers’ response times to their advantage. Compared with those in the noRT-Treatment, retailers in the RT-Treatment made lower initial proposals. The final wholesale prices in agreements were also lower in this treatment, resulting in higher average retailer and channel profits but lower supplier profits. Managerial implications: We demonstrated that response time information in supply chain bargaining revealed bargainers’ preferences and affected bargaining dynamics and outcomes. Bargainers could use their partners’ response times to improve their bargaining outcomes.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"5 1","pages":"19-35"},"PeriodicalIF":0.0,"publicationDate":"2022-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86103695","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}
{"title":"Introduction to the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management","authors":"Serguei Netessine, Christopher S. Tang, M. Toffel","doi":"10.1287/msom.2022.1155","DOIUrl":"https://doi.org/10.1287/msom.2022.1155","url":null,"abstract":"","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"3 1","pages":"2797-2798"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86079062","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: With increasing concerns about the quality and safety of agricultural products, many agricultural cooperatives (co-ops) have begun to specify quality provisions in contracts with farmers. Correspondingly, they are pooling products to quality-differentiated markets and offering quality-differentiated prices to farmers in multiple stages. Methodology/results: We propose a two-stage stochastic program to study the quality coordination problem in a setting where a co-op specifies a quality standard and offers a multistage payment scheme in its contract with multiple farmers who can exert quality-related effort and also show preference toward prompt payment timing. We first analyze a commonly adopted payment scheme, the pooling payment scheme, and then propose an improved payment scheme, the upfront incentive (UI) payment scheme. We find that the pooling payment scheme is able to coordinate the supply chain only when farmers’ time preference is higher than a threshold; otherwise, the scheme leads to the problem of over-motivation with respect to effort. However, the UI payment scheme can coordinate the supply chain unconditionally and is also robust to farmers heterogeneous in farm size. We further conduct two extensions, including farmers heterogeneous in farm size and dynamic market size. Managerial implications: The results provide guidance on a co-op’s contract design, including quality provision and payment mechanisms in multiple periods.
{"title":"Contractual Coordination of Agricultural Marketing Cooperatives With Quality Provisions","authors":"Xiaoyan Qian, T. Olsen","doi":"10.1287/msom.2022.1151","DOIUrl":"https://doi.org/10.1287/msom.2022.1151","url":null,"abstract":"Problem Definition: With increasing concerns about the quality and safety of agricultural products, many agricultural cooperatives (co-ops) have begun to specify quality provisions in contracts with farmers. Correspondingly, they are pooling products to quality-differentiated markets and offering quality-differentiated prices to farmers in multiple stages. Methodology/results: We propose a two-stage stochastic program to study the quality coordination problem in a setting where a co-op specifies a quality standard and offers a multistage payment scheme in its contract with multiple farmers who can exert quality-related effort and also show preference toward prompt payment timing. We first analyze a commonly adopted payment scheme, the pooling payment scheme, and then propose an improved payment scheme, the upfront incentive (UI) payment scheme. We find that the pooling payment scheme is able to coordinate the supply chain only when farmers’ time preference is higher than a threshold; otherwise, the scheme leads to the problem of over-motivation with respect to effort. However, the UI payment scheme can coordinate the supply chain unconditionally and is also robust to farmers heterogeneous in farm size. We further conduct two extensions, including farmers heterogeneous in farm size and dynamic market size. Managerial implications: The results provide guidance on a co-op’s contract design, including quality provision and payment mechanisms in multiple periods.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"24 1","pages":"3269-3282"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81870566","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}
Yixuan Liu, Xiaofang Wang, S. Gilbert, Guoming Lai
Problem definition: We investigate the participation, competition, and welfare at platforms that focus on customer-intensive discretionary services, such as healthcare, legal, and business consulting. Academic/practical relevance: Such platforms have recently emerged in practice to provide a venue for independent professionals and service seekers to match online. Methodology: We develop a strategic queueing model, where the platform sets the commission rate, upon which service providers decide participation, service quality, and price, and consumers make service acquisition. Results: First, our study reveals that with heterogeneous consumers, the participating service providers may engage in both price and service competitions if the number of them is either small or large. They compete for attractive consumers in the former and for market share in the latter. In these regions, more service providers joining the platform can result in a lower service price and a higher service quality. Whereas, if the number of participating service providers is intermediate, only service competition arises, so that a higher service quality is associated with a higher service price. Second, we find that in our main model, the platform may set the commission rate sufficiently high to limit the number of participating service providers, so as to prevent intense price competition. In contrast, if the platform also controls the service price, it may set a higher service price and a lower commission rate, which boosts the participation of service providers and improves their service quality. As a result, platform price intervention may not only benefit the platform and the service providers, but also the consumers. Managerial implications: These insights not only complement prior literature, but are also useful for understanding and the design of such service platforms in practice.
{"title":"On the Participation, Competition and Welfare at Customer-Intensive Discretionary Service Platforms","authors":"Yixuan Liu, Xiaofang Wang, S. Gilbert, Guoming Lai","doi":"10.1287/msom.2022.1152","DOIUrl":"https://doi.org/10.1287/msom.2022.1152","url":null,"abstract":"Problem definition: We investigate the participation, competition, and welfare at platforms that focus on customer-intensive discretionary services, such as healthcare, legal, and business consulting. Academic/practical relevance: Such platforms have recently emerged in practice to provide a venue for independent professionals and service seekers to match online. Methodology: We develop a strategic queueing model, where the platform sets the commission rate, upon which service providers decide participation, service quality, and price, and consumers make service acquisition. Results: First, our study reveals that with heterogeneous consumers, the participating service providers may engage in both price and service competitions if the number of them is either small or large. They compete for attractive consumers in the former and for market share in the latter. In these regions, more service providers joining the platform can result in a lower service price and a higher service quality. Whereas, if the number of participating service providers is intermediate, only service competition arises, so that a higher service quality is associated with a higher service price. Second, we find that in our main model, the platform may set the commission rate sufficiently high to limit the number of participating service providers, so as to prevent intense price competition. In contrast, if the platform also controls the service price, it may set a higher service price and a lower commission rate, which boosts the participation of service providers and improves their service quality. As a result, platform price intervention may not only benefit the platform and the service providers, but also the consumers. Managerial implications: These insights not only complement prior literature, but are also useful for understanding and the design of such service platforms in practice.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"12 1","pages":"218-234"},"PeriodicalIF":0.0,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84275159","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: Electric vertical-takeoff-and-landing (eVTOL) vehicles enable urban aerial mobility (UAM). This paper optimizes the number, locations, and capacities of vertiports in UAM systems while capturing interdependencies between strategic vertiport deployment, tactical operations, and passenger demand. Academic/practical relevance: The model includes a “tractable part” (based on mixed-integer second-order conic optimization) and also a nonconvex demand function. Methodology: We develop an exact algorithm that approximates nonconvex functions with piecewise constant segments, iterating between a conservative model (which yields a feasible solution) and a relaxed model (which yields a solution guarantee). We propose an adaptive discretization scheme that converges to a global optimum—because of the relaxed model. Results: Our algorithm converges to a 1% optimality gap, dominating static discretization benchmarks in terms of solution quality, runtimes, and solution guarantee. Managerial implications: We find that the most attractive structure for UAM is one that uses a few high-capacity vertiports, consolidating operations primarily to serve long-distance trips. Moreover, UAM profitability is highly sensitive to network planning optimization and to customer expectations, perhaps even more so than to vehicle specifications. Therefore, the success of UAM operations requires not only mature eVTOL technologies but also tailored analytics-based capabilities to optimize strategic planning and market-based efforts to drive customer demand.
{"title":"Vertiport Planning for Urban Aerial Mobility: An Adaptive Discretization Approach","authors":"Kai Wang, A. Jacquillat, Vikrant Vaze","doi":"10.1287/msom.2022.1148","DOIUrl":"https://doi.org/10.1287/msom.2022.1148","url":null,"abstract":"Problem definition: Electric vertical-takeoff-and-landing (eVTOL) vehicles enable urban aerial mobility (UAM). This paper optimizes the number, locations, and capacities of vertiports in UAM systems while capturing interdependencies between strategic vertiport deployment, tactical operations, and passenger demand. Academic/practical relevance: The model includes a “tractable part” (based on mixed-integer second-order conic optimization) and also a nonconvex demand function. Methodology: We develop an exact algorithm that approximates nonconvex functions with piecewise constant segments, iterating between a conservative model (which yields a feasible solution) and a relaxed model (which yields a solution guarantee). We propose an adaptive discretization scheme that converges to a global optimum—because of the relaxed model. Results: Our algorithm converges to a 1% optimality gap, dominating static discretization benchmarks in terms of solution quality, runtimes, and solution guarantee. Managerial implications: We find that the most attractive structure for UAM is one that uses a few high-capacity vertiports, consolidating operations primarily to serve long-distance trips. Moreover, UAM profitability is highly sensitive to network planning optimization and to customer expectations, perhaps even more so than to vehicle specifications. Therefore, the success of UAM operations requires not only mature eVTOL technologies but also tailored analytics-based capabilities to optimize strategic planning and market-based efforts to drive customer demand.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"95 1","pages":"3215-3235"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88550729","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: Unexpected failures of equipment can have severe consequences and costs. Such unexpected failures can be prevented by performing preventive replacement based on real-time degradation data. We study a component that degrades according to a compound Poisson process and fails when the degradation exceeds the failure threshold. An online sensor measures the degradation in real time, but interventions are only possible during planned downtime. Academic/practical relevance: We characterize the optimal replacement policy that integrates real-time learning from the online sensor. We demonstrate the effectiveness in practice with a case study on interventional x-ray machines. The data set of this case study is available in the online companion. As such, it can serve as a benchmark data set for future studies on stochastically deteriorating systems. Methodology: The degradation parameters vary from one component to the next but cannot be observed directly; the component population is heterogeneous. These parameters must therefore be inferred by observing the real-time degradation signal. We model this situation as a partially observable Markov decision process (POMDP) so that decision making and learning are integrated. We collapse the information state space of this POMDP to three dimensions so that optimal policies can be analyzed and computed tractably. Results: The optimal policy is a state dependent control limit. The control limit increases with age but may decrease as a result of other information in the degradation signal. Numerical case study analyses reveal that integration of learning and decision making leads to cost reductions of 10.50% relative to approaches that do not learn from the real-time signal and 4.28% relative to approaches that separate learning and decision making. Managerial implications: Real-time sensor information can reduce the cost of maintenance and unplanned downtime by a considerable amount. The integration of learning and decision making is tractably possible for industrial systems with our state space collapse. Finally, the benefit of our model increases with the amount of data available for initial model calibration, whereas additional data are much less valuable for approaches that ignore population heterogeneity.
{"title":"Real-Time Integrated Learning and Decision Making for Cumulative Shock Degradation","authors":"Collin Drent, M. Drent, J. Arts, S. Kapodistria","doi":"10.1287/msom.2022.1149","DOIUrl":"https://doi.org/10.1287/msom.2022.1149","url":null,"abstract":"Problem definition: Unexpected failures of equipment can have severe consequences and costs. Such unexpected failures can be prevented by performing preventive replacement based on real-time degradation data. We study a component that degrades according to a compound Poisson process and fails when the degradation exceeds the failure threshold. An online sensor measures the degradation in real time, but interventions are only possible during planned downtime. Academic/practical relevance: We characterize the optimal replacement policy that integrates real-time learning from the online sensor. We demonstrate the effectiveness in practice with a case study on interventional x-ray machines. The data set of this case study is available in the online companion. As such, it can serve as a benchmark data set for future studies on stochastically deteriorating systems. Methodology: The degradation parameters vary from one component to the next but cannot be observed directly; the component population is heterogeneous. These parameters must therefore be inferred by observing the real-time degradation signal. We model this situation as a partially observable Markov decision process (POMDP) so that decision making and learning are integrated. We collapse the information state space of this POMDP to three dimensions so that optimal policies can be analyzed and computed tractably. Results: The optimal policy is a state dependent control limit. The control limit increases with age but may decrease as a result of other information in the degradation signal. Numerical case study analyses reveal that integration of learning and decision making leads to cost reductions of 10.50% relative to approaches that do not learn from the real-time signal and 4.28% relative to approaches that separate learning and decision making. Managerial implications: Real-time sensor information can reduce the cost of maintenance and unplanned downtime by a considerable amount. The integration of learning and decision making is tractably possible for industrial systems with our state space collapse. Finally, the benefit of our model increases with the amount of data available for initial model calibration, whereas additional data are much less valuable for approaches that ignore population heterogeneity.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"5 1","pages":"235-253"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81117382","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}
Balaraman Rajan, Arvind Sainathan, Saligrama R. Agnihothri, Leon Cui
Problem definition: Rapid innovations in technology have created opportunities for different modes of healthcare delivery including digital services provided via mobile applications (mHealth). mHealth technology has the potential to provide efficient, effective, and patient-centered healthcare to manage chronic conditions. However, the economics associated with the adoption and integration of mHealth into the care delivery process is not well understood. In a chronic care clinical practice setting, we investigate fee-for-service (FFS) and capitation payment systems, and explore their performance in a traditional office-visit mode and in a mHealth-adopted mode. We identify conditions under which it is preferable to switch to an mHealth-based practice from an office visit-based practice. Methodology/results: We use an analytical model to track the progression of a chronic disease and formulate an optimization problem in which the clinic decides the time between scheduled visits and patient panel size. We consider many patient-doctor interaction factors including the risk-index of patients, the cost of being sick, and the effectiveness of treatment. We measure the performance based on four different criteria: physician net revenue, physician panel size, total patient utility, and payor net revenue. Although patients may find mHealth mode to be very beneficial, physicians under an FFS system may only adopt mHealth for moderately risky patients but for neither low-risk nor high-risk patients. Capitation clinics are likely to adopt mHealth (higher net revenue) even if the technology is moderately effective. Importantly, mHealth is preferred by patients (higher total utility) and policy makers (greater coverage) when the clinic serves moderate-risk or high-risk patients. Managerial implications: Chronic conditions need continuous care management and use of mHealth has been very promising. However, adoption of mHealth by healthcare providers has been very slow. Our research explores payment systems, physician incentives, and optimal conditions for mHealth to achieve its full potential.
{"title":"The Promise of mHealth for Chronic Disease Management Under Different Payment Systems","authors":"Balaraman Rajan, Arvind Sainathan, Saligrama R. Agnihothri, Leon Cui","doi":"10.1287/msom.2022.1143","DOIUrl":"https://doi.org/10.1287/msom.2022.1143","url":null,"abstract":"Problem definition: Rapid innovations in technology have created opportunities for different modes of healthcare delivery including digital services provided via mobile applications (mHealth). mHealth technology has the potential to provide efficient, effective, and patient-centered healthcare to manage chronic conditions. However, the economics associated with the adoption and integration of mHealth into the care delivery process is not well understood. In a chronic care clinical practice setting, we investigate fee-for-service (FFS) and capitation payment systems, and explore their performance in a traditional office-visit mode and in a mHealth-adopted mode. We identify conditions under which it is preferable to switch to an mHealth-based practice from an office visit-based practice. Methodology/results: We use an analytical model to track the progression of a chronic disease and formulate an optimization problem in which the clinic decides the time between scheduled visits and patient panel size. We consider many patient-doctor interaction factors including the risk-index of patients, the cost of being sick, and the effectiveness of treatment. We measure the performance based on four different criteria: physician net revenue, physician panel size, total patient utility, and payor net revenue. Although patients may find mHealth mode to be very beneficial, physicians under an FFS system may only adopt mHealth for moderately risky patients but for neither low-risk nor high-risk patients. Capitation clinics are likely to adopt mHealth (higher net revenue) even if the technology is moderately effective. Importantly, mHealth is preferred by patients (higher total utility) and policy makers (greater coverage) when the clinic serves moderate-risk or high-risk patients. Managerial implications: Chronic conditions need continuous care management and use of mHealth has been very promising. However, adoption of mHealth by healthcare providers has been very slow. Our research explores payment systems, physician incentives, and optimal conditions for mHealth to achieve its full potential.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"64 2","pages":"3158-3176"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91416391","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}
H. M. Yayla-Küllü, Omkar D. Palsule-Desai, S. Gavirneni
Problem definition: Onion is an indispensable ingredient of the Indian diet, and plays a vital role in Indian economy, society, and politics. The ever-lasting volatility in its prices leads to significant social unrest. In this paper, we are interested in helping decision makers to rigorously evaluate a recent policy proposal to make dehydrated onion widely available to remedy the situation. Methodology/results: Using a stylized analytical model, we look for conditions under which it is optimal to introduce a processed substitute and whether it should be managed by nonprofit or for-profit firms. We find that the solution is identified by threshold-based policies and outcomes are far better under the nonprofit management. We also find that a nonprofit processing firm may purposefully choose a strategy where consumers do not purchase its offering for a certain medium range of raw onion deterioration levels. In addition, we find that a for-profit firm would always choose to be the lower-quality substitute in the market unless the raw onion deterioration is high. We also find that when supply capacity is constrained, sales of the processed substitute might decrease with increased supply availability. Managerial implications: This is the first paper that takes perishability and consumer welfare into account in a two-period vertically differentiated market model and compares various scenarios of competition when there is consumer prejudice for the processed substitute. For India’s policymakers, we find ample evidence to work toward implementing the processed substitute policy. We go deep and discuss tailored insights for certain regions in India. We find that although improved consumer perception is favorable in general, policymakers should be careful about some unintended consequences such as increased prices and lower availability.
{"title":"Reining in Onion Prices by Introducing a Vertically Differentiated Substitute: Models, Analysis, and Insights","authors":"H. M. Yayla-Küllü, Omkar D. Palsule-Desai, S. Gavirneni","doi":"10.1287/msom.2022.1145","DOIUrl":"https://doi.org/10.1287/msom.2022.1145","url":null,"abstract":"Problem definition: Onion is an indispensable ingredient of the Indian diet, and plays a vital role in Indian economy, society, and politics. The ever-lasting volatility in its prices leads to significant social unrest. In this paper, we are interested in helping decision makers to rigorously evaluate a recent policy proposal to make dehydrated onion widely available to remedy the situation. Methodology/results: Using a stylized analytical model, we look for conditions under which it is optimal to introduce a processed substitute and whether it should be managed by nonprofit or for-profit firms. We find that the solution is identified by threshold-based policies and outcomes are far better under the nonprofit management. We also find that a nonprofit processing firm may purposefully choose a strategy where consumers do not purchase its offering for a certain medium range of raw onion deterioration levels. In addition, we find that a for-profit firm would always choose to be the lower-quality substitute in the market unless the raw onion deterioration is high. We also find that when supply capacity is constrained, sales of the processed substitute might decrease with increased supply availability. Managerial implications: This is the first paper that takes perishability and consumer welfare into account in a two-period vertically differentiated market model and compares various scenarios of competition when there is consumer prejudice for the processed substitute. For India’s policymakers, we find ample evidence to work toward implementing the processed substitute policy. We go deep and discuss tailored insights for certain regions in India. We find that although improved consumer perception is favorable in general, policymakers should be careful about some unintended consequences such as increased prices and lower availability.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"9 1","pages":"3283-3305"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90418515","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 consider the problem of resolving ad hoc unpredictable congestion in environments where customers have private time valuations. We investigate the design of fair, efficient, budget-balanced, and implementable bidding mechanisms for observable queues. Academic/practical relevance: Our primary motivation comes from merging in algorithmic traffic, i.e., a driver wishing to merge in a relatively dense platoon of vehicles in a coordinated and efficient way, using intervehicle communication and micropayments, akin to an arriving customer trading for position in a single-server observable queue. Methodology: We analyze the performance of a mechanism where the queue joiner makes sequential take-it-or-leave-it bids from tail to head (T2H) of a platoon, with the condition that the vehicle can advance to the next position only if it wins the bid. This mechanism is designed so that it is implementable, balances the budget, and imposes no negative externalities. Results: We compared this mechanism with head to tail (H2T) bidding, which favors the merging driver but potentially causes uncompensated externalities. Assuming i.i.d. time valuations, we obtain the optimal bids, value functions, and expected social welfare in closed form in both mechanisms. Moreover, if the time valuation of the merging driver is not high, we show that the expected social welfare of T2H is close to a partial information social optimum and that the expected social welfare of H2T is lower than that of T2H as long as the platoon is not too short. Managerial implications: Our findings suggest that mechanisms based on sequential take-it-or-leave-it bids from T2H of an observable queue have good social welfare performance, even if the corresponding bids are not chosen optimally, as long as the time valuation of the arriving customer is not high. Nevertheless, the tension between individual incentives and social welfare seems hard to resolve, highlighting the role of platforms to enforce the cooperation of involved parties.
{"title":"Sequential Bidding for Merging in Algorithmic Traffic","authors":"Mihalis G. Markakis, K. Talluri, D. Tikhonenko","doi":"10.1287/msom.2022.1144","DOIUrl":"https://doi.org/10.1287/msom.2022.1144","url":null,"abstract":"Problem definition: We consider the problem of resolving ad hoc unpredictable congestion in environments where customers have private time valuations. We investigate the design of fair, efficient, budget-balanced, and implementable bidding mechanisms for observable queues. Academic/practical relevance: Our primary motivation comes from merging in algorithmic traffic, i.e., a driver wishing to merge in a relatively dense platoon of vehicles in a coordinated and efficient way, using intervehicle communication and micropayments, akin to an arriving customer trading for position in a single-server observable queue. Methodology: We analyze the performance of a mechanism where the queue joiner makes sequential take-it-or-leave-it bids from tail to head (T2H) of a platoon, with the condition that the vehicle can advance to the next position only if it wins the bid. This mechanism is designed so that it is implementable, balances the budget, and imposes no negative externalities. Results: We compared this mechanism with head to tail (H2T) bidding, which favors the merging driver but potentially causes uncompensated externalities. Assuming i.i.d. time valuations, we obtain the optimal bids, value functions, and expected social welfare in closed form in both mechanisms. Moreover, if the time valuation of the merging driver is not high, we show that the expected social welfare of T2H is close to a partial information social optimum and that the expected social welfare of H2T is lower than that of T2H as long as the platoon is not too short. Managerial implications: Our findings suggest that mechanisms based on sequential take-it-or-leave-it bids from T2H of an observable queue have good social welfare performance, even if the corresponding bids are not chosen optimally, as long as the time valuation of the arriving customer is not high. Nevertheless, the tension between individual incentives and social welfare seems hard to resolve, highlighting the role of platforms to enforce the cooperation of involved parties.","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"34 1","pages":"168-181"},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72839387","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}
{"title":"Introduction to the Special Section on Smart City Operations","authors":"Sameer Hasija, C. Teo","doi":"10.1287/msom.2022.1133","DOIUrl":"https://doi.org/10.1287/msom.2022.1133","url":null,"abstract":"","PeriodicalId":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"8 1","pages":"2387-2388"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87099881","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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