Jessica L. Darby, D. Ketchen, George P. Ball, U. Mukherjee
Problem definition: Firms often delay the decision to recall faulty medical devices long after they become aware of a defect, thereby putting public safety at heightened risk. However, the factors contributing to these delays are not well-understood. To help address this gap, we examine whether and how CEO stock ownership influences the speed with which faulty medical devices are recalled and whether this influence varies with recall severity. We then examine whether the stock market penalizes firms differently based on recall decision-making speed and whether this penalty also varies with recall severity. Methodology/results: We collect data on 2,144 medical device recalls across 50 public medical device firms from 2002 to 2015. We use accelerated failure time models to test the effects of CEO stock ownership on the time-to-recall and event study methodology to examine how the time-to-recall influences stock market returns. Supplementary analyses shed further light on underlying mechanisms. Robustness checks demonstrate consistent results, including coarsened exact matching, reverse causality tests, Cox proportional hazard models, generalized linear regression models, and a mediation analysis. Firms whose CEOs possess greater ownership stakes recall medical devices more slowly, and this recall-slowing effect is accentuated for high-severity recalls. Delaying recalls magnifies the stock market penalty attributable to the recall, particularly for high-severity recalls. Managerial implications: Our study highlights an ownership characteristic of firms that are more likely to delay recalling faulty medical devices. Boards of directors can use insights from our study as they oversee product-quality decisions and determine the level and form of CEO compensation, and the FDA can use our findings to identify firms that might warrant extra scrutiny and better allocate its limited monitoring resources. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0175 .
{"title":"CEO Stock Ownership, Recall Timing, and Stock Market Penalties","authors":"Jessica L. Darby, D. Ketchen, George P. Ball, U. Mukherjee","doi":"10.1287/msom.2021.0175","DOIUrl":"https://doi.org/10.1287/msom.2021.0175","url":null,"abstract":"Problem definition: Firms often delay the decision to recall faulty medical devices long after they become aware of a defect, thereby putting public safety at heightened risk. However, the factors contributing to these delays are not well-understood. To help address this gap, we examine whether and how CEO stock ownership influences the speed with which faulty medical devices are recalled and whether this influence varies with recall severity. We then examine whether the stock market penalizes firms differently based on recall decision-making speed and whether this penalty also varies with recall severity. Methodology/results: We collect data on 2,144 medical device recalls across 50 public medical device firms from 2002 to 2015. We use accelerated failure time models to test the effects of CEO stock ownership on the time-to-recall and event study methodology to examine how the time-to-recall influences stock market returns. Supplementary analyses shed further light on underlying mechanisms. Robustness checks demonstrate consistent results, including coarsened exact matching, reverse causality tests, Cox proportional hazard models, generalized linear regression models, and a mediation analysis. Firms whose CEOs possess greater ownership stakes recall medical devices more slowly, and this recall-slowing effect is accentuated for high-severity recalls. Delaying recalls magnifies the stock market penalty attributable to the recall, particularly for high-severity recalls. Managerial implications: Our study highlights an ownership characteristic of firms that are more likely to delay recalling faulty medical devices. Boards of directors can use insights from our study as they oversee product-quality decisions and determine the level and form of CEO compensation, and the FDA can use our findings to identify firms that might warrant extra scrutiny and better allocate its limited monitoring resources. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0175 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115831691","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: In an environment where consumers’ rising valuation of Instagrammable memories drives their spending from products to experiences, retailers offer experiences to attract consumers back to their stores. Yet, it is not obvious under which settings consumers can benefit from these experiences and raise retailers’ profits. Methodology/results: We use a random utility model for consumer choice in both monopoly and duopoly settings. For the latter, we pose a game-theoretic model to analyze the equilibrium prices, profits, and consumer welfare for various problem cases. We show that medium-quality experiences can lower the product sales and store traffic below the level when no experience is offered. Sufficiently low- or high-quality experiences overcome this issue, making the consumers better off. Yet, the former presents the only profitable option when a single retailer in the market offers an experience. In contrast, when both retailers adopt experiences, low-quality experiences may not be profitable, and the retailers would need to adopt even higher-quality experiences, which lead to a “win-win-win” outcome for the two retailers and consumers. A fee structure for the experience elevates retailer profits but can turn stores into outlets where consumers visit to purchase experiences and not products. When experiential retailing is the common practice in the market, it enables “win-win-win” outcomes when free experiences fail. Managerial implications: Being the first to study this new retail format, our results contribute to the ongoing debate on the settings under which experiential offerings are beneficial for the retailers and consumers and highlight that there is no one-size-fits-all strategy. Our results show that experiences affect main product sales in nonobvious ways, especially in competitive markets. In a (post-)pandemic world where retailers try to attract consumers back to stores, we offer insights that can guide retailers in the process. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0339 .
{"title":"Offering Memories to Sell Goods? Pricing and Welfare Implications of Experiential Retail","authors":"Nevin Mutlu, H. El-Amine, Ozge Sahin","doi":"10.1287/msom.2021.0339","DOIUrl":"https://doi.org/10.1287/msom.2021.0339","url":null,"abstract":"Problem definition: In an environment where consumers’ rising valuation of Instagrammable memories drives their spending from products to experiences, retailers offer experiences to attract consumers back to their stores. Yet, it is not obvious under which settings consumers can benefit from these experiences and raise retailers’ profits. Methodology/results: We use a random utility model for consumer choice in both monopoly and duopoly settings. For the latter, we pose a game-theoretic model to analyze the equilibrium prices, profits, and consumer welfare for various problem cases. We show that medium-quality experiences can lower the product sales and store traffic below the level when no experience is offered. Sufficiently low- or high-quality experiences overcome this issue, making the consumers better off. Yet, the former presents the only profitable option when a single retailer in the market offers an experience. In contrast, when both retailers adopt experiences, low-quality experiences may not be profitable, and the retailers would need to adopt even higher-quality experiences, which lead to a “win-win-win” outcome for the two retailers and consumers. A fee structure for the experience elevates retailer profits but can turn stores into outlets where consumers visit to purchase experiences and not products. When experiential retailing is the common practice in the market, it enables “win-win-win” outcomes when free experiences fail. Managerial implications: Being the first to study this new retail format, our results contribute to the ongoing debate on the settings under which experiential offerings are beneficial for the retailers and consumers and highlight that there is no one-size-fits-all strategy. Our results show that experiences affect main product sales in nonobvious ways, especially in competitive markets. In a (post-)pandemic world where retailers try to attract consumers back to stores, we offer insights that can guide retailers in the process. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0339 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126191876","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}
Fan Zou, Yan Dong, Sin-Geun Song, M. Rungtusanatham
Problem definition: Suppliers are increasingly involved in innovation activities that contribute to a firm’s product quality and introduce risks to firms’ quality control, leading to quality failures and recalls. This quality trade-off suggests the possibility of a nonlinear relationship between supplier innovation and product recalls, which is the focus of this research. Recall literature focuses on firms’ internal drivers of recalls, whereas anecdotal evidence increasingly points to the role of external drivers, such as suppliers. We contribute to the literature by examining supplier innovation as an external driver leading to recalls via quality and risk spillovers. Methodology/results: We collect and assemble a unique panel data set of consumer product recalls from firms and their supply bases (i.e., first tier suppliers). We estimate econometric models to examine the nonlinear relationship between supply base innovation, measured by research and development (R&D) intensity of the supply bases, and the likelihood of product recalls. We find a quadratic (i.e., U-shaped) relationship between the probability of recalls and supply base R&D intensity. We also find that this nonlinear relationship is critically related to three specific sources of risk: radicalness of supplier innovation, technological distance between firms and their suppliers, and complexity of supply base. Managerial implications: Our findings suggest that firms should be mindful of the quality trade-offs in encouraging supplier innovation to reduce product recalls. Further, to minimize recall risks, firms should better evaluate and manage the risks associated with external supplier knowledge that is novel and different and closely work with global suppliers to reduce coordination challenges in knowledge transfer and integration. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1213 .
{"title":"Product Recalls and Supply Base Innovation","authors":"Fan Zou, Yan Dong, Sin-Geun Song, M. Rungtusanatham","doi":"10.1287/msom.2023.1213","DOIUrl":"https://doi.org/10.1287/msom.2023.1213","url":null,"abstract":"Problem definition: Suppliers are increasingly involved in innovation activities that contribute to a firm’s product quality and introduce risks to firms’ quality control, leading to quality failures and recalls. This quality trade-off suggests the possibility of a nonlinear relationship between supplier innovation and product recalls, which is the focus of this research. Recall literature focuses on firms’ internal drivers of recalls, whereas anecdotal evidence increasingly points to the role of external drivers, such as suppliers. We contribute to the literature by examining supplier innovation as an external driver leading to recalls via quality and risk spillovers. Methodology/results: We collect and assemble a unique panel data set of consumer product recalls from firms and their supply bases (i.e., first tier suppliers). We estimate econometric models to examine the nonlinear relationship between supply base innovation, measured by research and development (R&D) intensity of the supply bases, and the likelihood of product recalls. We find a quadratic (i.e., U-shaped) relationship between the probability of recalls and supply base R&D intensity. We also find that this nonlinear relationship is critically related to three specific sources of risk: radicalness of supplier innovation, technological distance between firms and their suppliers, and complexity of supply base. Managerial implications: Our findings suggest that firms should be mindful of the quality trade-offs in encouraging supplier innovation to reduce product recalls. Further, to minimize recall risks, firms should better evaluate and manage the risks associated with external supplier knowledge that is novel and different and closely work with global suppliers to reduce coordination challenges in knowledge transfer and integration. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1213 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116491730","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}
Yangzi Jiang, Hossein Abouee Mehrizi, Jan A. Van Mieghem
Problem definition: Patient-level data from 72 magnetic resonance imaging (MRI) hospitals in Ontario, Canada from 2013 to 2017 show that over 60% of patients exceeded their wait time targets. We conduct a data-driven analysis to quantify the reduction in the patient fraction exceeding (FET) target for MRI services through geographic virtual resource-sharing while limiting incremental driving time. We present a data-driven method to solve the geographic pooling problem of partitioning 72 hospitals with heterogeneous patients with different wait time targets located in a two-dimensional region into a set of clusters. Methodology/results: We propose an “augmented-priority rule,” which is a sequencing rule that balances the patient’s initial priority class and the number of days until her wait time target. We then use neural networks to predict patient arrival and service times. We combine this predicted information and the sequencing rule to implement “advance scheduling,” which informs the patient of her treatment day and location when requesting an MRI scan. We then optimize the number of geographic resource pools among the 72 hospitals using genetic algorithms. Our resource-pooling model lowers the FET from 66% to 36% while constraining the average incremental travel time below three hours. In addition, our model shows that only 10 additional scanners are needed to achieve 10% FET, whereas 50 additional scanners would be needed without resource sharing. Over 70% of the hospitals are not worse off financially. Each individual hospital, measured over at least two weeks, achieves a higher machine utilization and a lower FET. Managerial implications: Our paper provides a practical, data-driven geographical resource-sharing model that hospitals can readily implement. Our method achieves a near-optimal solution with low computational complexity. Using smart data-driven scheduling, a little extra capacity placed at the right location is all we need to achieve the desired FET under geographic resource-sharing. Funding: This paper is supported by the following grant: Canadian Institutes of Health Research (CIHR) [Grant CIHR-950-231935]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1225 .
{"title":"Geographic Virtual Pooling of Hospital Resources: Data-Driven Trade-off Between Waiting and Traveling","authors":"Yangzi Jiang, Hossein Abouee Mehrizi, Jan A. Van Mieghem","doi":"10.1287/msom.2023.1225","DOIUrl":"https://doi.org/10.1287/msom.2023.1225","url":null,"abstract":"Problem definition: Patient-level data from 72 magnetic resonance imaging (MRI) hospitals in Ontario, Canada from 2013 to 2017 show that over 60% of patients exceeded their wait time targets. We conduct a data-driven analysis to quantify the reduction in the patient fraction exceeding (FET) target for MRI services through geographic virtual resource-sharing while limiting incremental driving time. We present a data-driven method to solve the geographic pooling problem of partitioning 72 hospitals with heterogeneous patients with different wait time targets located in a two-dimensional region into a set of clusters. Methodology/results: We propose an “augmented-priority rule,” which is a sequencing rule that balances the patient’s initial priority class and the number of days until her wait time target. We then use neural networks to predict patient arrival and service times. We combine this predicted information and the sequencing rule to implement “advance scheduling,” which informs the patient of her treatment day and location when requesting an MRI scan. We then optimize the number of geographic resource pools among the 72 hospitals using genetic algorithms. Our resource-pooling model lowers the FET from 66% to 36% while constraining the average incremental travel time below three hours. In addition, our model shows that only 10 additional scanners are needed to achieve 10% FET, whereas 50 additional scanners would be needed without resource sharing. Over 70% of the hospitals are not worse off financially. Each individual hospital, measured over at least two weeks, achieves a higher machine utilization and a lower FET. Managerial implications: Our paper provides a practical, data-driven geographical resource-sharing model that hospitals can readily implement. Our method achieves a near-optimal solution with low computational complexity. Using smart data-driven scheduling, a little extra capacity placed at the right location is all we need to achieve the desired FET under geographic resource-sharing. Funding: This paper is supported by the following grant: Canadian Institutes of Health Research (CIHR) [Grant CIHR-950-231935]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1225 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"59 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134020999","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: “Long tail” products with intermittent demand often tie up valuable warehouse space and capital investment for many companies. Furthermore, the paucity of demand data poses additional challenges for model estimation and performance evaluation. Traditional inventory solutions are not designed for products with intermittent demand. In this paper, we propose a new framework to optimize the choice of “replenishment timing” and “replenishment quantity” for managing the inventory metrics of long tail products, when evaluated over a finite horizon. Methodology/results: Our analysis is motivated by a recent interesting observation that the gambler’s fallacy phenomenon actually holds in a finite number of coin tosses. We use this phenomenon to analyze the inventory problem for intermittent demand to demonstrate that classical inventory models using KPIs such as fill rate, average cost per cycle, or average cost per unit, etc., must necessarily “bias” the underlying demand distribution to account for the finite horizon effect. We provide the exact closed-form expressions of the biased distribution to account for this effect in performance evaluation. The results show that the choice of replenishment timing and replenishment quantity is essential to superior performance on several key inventory metrics. Managerial implications: For long tail products, the belief that it is less likely for another demand to arrive shortly after a preceding one (the gambler’s fallacy), turns out to be true when performance is tabulated over a finite horizon, even if demands across time are independent. So it pays to delay the replenishment of depleted stocks to save on holding cost and warehouse space. Managers can optimize the replenishment timing, besides choosing the replenishment quantity, to optimize the performance metrics of several classes of inventory problems. This is especially useful for companies managing a large number of long tail products. Funding: This work was supported in part by the National Natural Science Foundation of China [Grant 72192832] and the 2019 Academic Research Fund Tier 3 of the Ministry of Education-Singapore [Grant MOE-2019-T3-1-010]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1217 .
{"title":"Taming the Long Tail: The Gambler’s Fallacy in Intermittent Demand Management","authors":"S. Bi, Long He, C. Teo","doi":"10.1287/msom.2023.1217","DOIUrl":"https://doi.org/10.1287/msom.2023.1217","url":null,"abstract":"Problem definition: “Long tail” products with intermittent demand often tie up valuable warehouse space and capital investment for many companies. Furthermore, the paucity of demand data poses additional challenges for model estimation and performance evaluation. Traditional inventory solutions are not designed for products with intermittent demand. In this paper, we propose a new framework to optimize the choice of “replenishment timing” and “replenishment quantity” for managing the inventory metrics of long tail products, when evaluated over a finite horizon. Methodology/results: Our analysis is motivated by a recent interesting observation that the gambler’s fallacy phenomenon actually holds in a finite number of coin tosses. We use this phenomenon to analyze the inventory problem for intermittent demand to demonstrate that classical inventory models using KPIs such as fill rate, average cost per cycle, or average cost per unit, etc., must necessarily “bias” the underlying demand distribution to account for the finite horizon effect. We provide the exact closed-form expressions of the biased distribution to account for this effect in performance evaluation. The results show that the choice of replenishment timing and replenishment quantity is essential to superior performance on several key inventory metrics. Managerial implications: For long tail products, the belief that it is less likely for another demand to arrive shortly after a preceding one (the gambler’s fallacy), turns out to be true when performance is tabulated over a finite horizon, even if demands across time are independent. So it pays to delay the replenishment of depleted stocks to save on holding cost and warehouse space. Managers can optimize the replenishment timing, besides choosing the replenishment quantity, to optimize the performance metrics of several classes of inventory problems. This is especially useful for companies managing a large number of long tail products. Funding: This work was supported in part by the National Natural Science Foundation of China [Grant 72192832] and the 2019 Academic Research Fund Tier 3 of the Ministry of Education-Singapore [Grant MOE-2019-T3-1-010]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1217 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130759484","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 Special Section on Data-Driven Research Challenge","authors":"Gad Allon","doi":"10.1287/msom.2023.1209","DOIUrl":"https://doi.org/10.1287/msom.2023.1209","url":null,"abstract":"","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130366698","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":"Acknowledgments to Editors and Reviewers (2022)","authors":"","doi":"10.1287/msom.2023.1222","DOIUrl":"https://doi.org/10.1287/msom.2023.1222","url":null,"abstract":"","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"18 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113977168","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}
Sindy De La Torre Pacheco, Mahyar Eftekhar, Chao Wu
Problem definition: Although in-kind donations contribute to charity’s triple bottom line (i.e., generating additional revenue for the charity, contributing to social welfare, and reducing environmental waste through rechanneling used items), inappropriate material donations impose additional costs to sort, process, or discard them. Minimizing the amount of undesired in-kind donations, however, is a challenge given charities’ sensitive relationship with their donors. This paper examines the effectiveness of behavioral interventions on improving the quality of in-kind donations gifted by individuals. Methodology/results: We conducted a field experiment to implement interventions motivated by two well-established behavioral mechanisms: information disclosure and social norm. We studied the reaction of 763 donors who were scheduled to make an in-kind donation at a local charity between October 31 and November 11, 2020. Our results show that using the social norm intervention effectively improved the quality of in-kind donations, whereas information disclosure, which is commonly used in practice as the industry standard intervention, was ineffective. We also conducted two postexperiment analyses. First, we collected additional data on 1,301 in-kind donations whose donors had received the social norm intervention during February 2021. Results show that the impact of the social norm intervention is stable over different time periods. Second, we studied the spillover effect of these interventions for a period of 12 months and did not find a negative long-term impact on in-kind donations. Managerial implications: A conservative estimation shows that implementing the social norm intervention reduced the junk donations received by 50% without having a negative spillover effect on donors’ in-kind donations or imposing any direct operating cost. Consequently, this field evidence provides an effective, cost-efficient, and scalable solution for charities to address the quality problem of in-kind donations. In addition, our results challenge the industry conventional practice of incorporating information disclosure in their communications with donors. Funding: This work was supported by Virginia G. Piper Charitable Trust [Grant: 2020 Initiative].
问题定义:虽然实物捐赠有助于慈善机构的三重底线(即为慈善机构带来额外收入，为社会福利做出贡献，并通过重新分配废旧物品减少环境浪费)，但不适当的物质捐赠会增加分类，处理或丢弃的额外成本。然而，考虑到慈善机构与捐赠者之间的敏感关系，将不受欢迎的实物捐赠数量降至最低是一项挑战。本文考察了行为干预对提高个人捐赠实物质量的有效性。方法/结果:我们进行了实地实验，以实施信息披露和社会规范两种完善的行为机制驱动的干预措施。我们研究了763名捐赠者的反应，他们计划在2020年10月31日至11月11日期间向当地一家慈善机构进行实物捐赠。研究结果表明，社会规范干预有效地提高了实物捐赠的质量，而实践中常用的行业标准干预——信息披露则效果不佳。我们还进行了两次实验后分析。首先，我们收集了2021年2月期间接受社会规范干预的1301笔实物捐赠的额外数据。结果表明，社会规范干预在不同时期的影响是稳定的。其次，我们对这些干预措施的溢出效应进行了为期12个月的研究，并没有发现对实物捐赠有负面的长期影响。管理启示:保守估计，实施社会规范干预可以使垃圾捐赠减少50%，而不会对捐赠者的实物捐赠产生负面溢出效应，也不会增加任何直接运营成本。因此，这一现场证据为慈善机构解决实物捐赠的质量问题提供了一个有效、经济、可扩展的解决方案。此外，我们的研究结果挑战了将信息披露纳入其与捐助者沟通的行业传统做法。资助:本研究由Virginia G. Piper Charitable Trust [Grant: 2020 Initiative]资助。
{"title":"Improving the Quality of In-Kind Donations: A Field Experiment","authors":"Sindy De La Torre Pacheco, Mahyar Eftekhar, Chao Wu","doi":"10.1287/msom.2023.1214","DOIUrl":"https://doi.org/10.1287/msom.2023.1214","url":null,"abstract":"Problem definition: Although in-kind donations contribute to charity’s triple bottom line (i.e., generating additional revenue for the charity, contributing to social welfare, and reducing environmental waste through rechanneling used items), inappropriate material donations impose additional costs to sort, process, or discard them. Minimizing the amount of undesired in-kind donations, however, is a challenge given charities’ sensitive relationship with their donors. This paper examines the effectiveness of behavioral interventions on improving the quality of in-kind donations gifted by individuals. Methodology/results: We conducted a field experiment to implement interventions motivated by two well-established behavioral mechanisms: information disclosure and social norm. We studied the reaction of 763 donors who were scheduled to make an in-kind donation at a local charity between October 31 and November 11, 2020. Our results show that using the social norm intervention effectively improved the quality of in-kind donations, whereas information disclosure, which is commonly used in practice as the industry standard intervention, was ineffective. We also conducted two postexperiment analyses. First, we collected additional data on 1,301 in-kind donations whose donors had received the social norm intervention during February 2021. Results show that the impact of the social norm intervention is stable over different time periods. Second, we studied the spillover effect of these interventions for a period of 12 months and did not find a negative long-term impact on in-kind donations. Managerial implications: A conservative estimation shows that implementing the social norm intervention reduced the junk donations received by 50% without having a negative spillover effect on donors’ in-kind donations or imposing any direct operating cost. Consequently, this field evidence provides an effective, cost-efficient, and scalable solution for charities to address the quality problem of in-kind donations. In addition, our results challenge the industry conventional practice of incorporating information disclosure in their communications with donors. Funding: This work was supported by Virginia G. Piper Charitable Trust [Grant: 2020 Initiative].","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"6 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114044423","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: This paper studies the deceased-donor liver allocation policies in the United States. In the transplant community, broader organ sharing is believed to mitigate geographic inequity (intergeographic variation in transplant rates, patient survival rates, waiting times, and offers) in organ access, and recent policies are moving in that direction in principle. The liver-allocation policy has gone through two major modifications in the last 10 years. Despite these overhauls, geographic inequity persists. Methodology/results: In this study, we develop a patient’s dynamic choice model to analyze the patient’s strategic response to a policy change. We use this to evaluate several (existing and proposed) organ-allocation policies. On historical data, we show that our model’s predictions are more precise than the existing liver simulated allocation model. It more accurately captures (1) a patient’s change in organ offer acceptance probability (with their sickness level) and (2) the behavioral change of a patient in terms of organ offer acceptance probability with a change in policy. Next, we study the current acuity circles policy (a one-size-fits-all variant of broader sharing) and conclude that it results in lower efficiency (more offer refusals and a lower transplant benefit) than the previous share 35 policy and performs similarly on geographic equity measures. Finally, we show that broader sharing in its current form may not be the best strategy to balance geographic equity and efficiency. The intuition is that, by indiscriminately enlarging the pool of supply locations from where patients can receive offers, they tend to become more selective, resulting in more offer rejections and less efficiency. We illustrate that a policy that equalizes the supply (deceased donors)-to-demand (waiting list patients) ratios across geographies is better than acuity circles in achieving geographic equity at the lowest trade-off on efficiency metrics. Managerial implications: The key message to policymakers is that they should move away from the one-size-fits-all approach and focus on matching supply and demand to develop organ-allocation policies that score well in terms of efficiency and geographic equity. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1211 .
{"title":"Improving Broader Sharing to Address Geographic Inequity in Liver Transplantation","authors":"Shubham Akshat, Liye Ma, S. Raghavan","doi":"10.1287/msom.2023.1211","DOIUrl":"https://doi.org/10.1287/msom.2023.1211","url":null,"abstract":"Problem definition: This paper studies the deceased-donor liver allocation policies in the United States. In the transplant community, broader organ sharing is believed to mitigate geographic inequity (intergeographic variation in transplant rates, patient survival rates, waiting times, and offers) in organ access, and recent policies are moving in that direction in principle. The liver-allocation policy has gone through two major modifications in the last 10 years. Despite these overhauls, geographic inequity persists. Methodology/results: In this study, we develop a patient’s dynamic choice model to analyze the patient’s strategic response to a policy change. We use this to evaluate several (existing and proposed) organ-allocation policies. On historical data, we show that our model’s predictions are more precise than the existing liver simulated allocation model. It more accurately captures (1) a patient’s change in organ offer acceptance probability (with their sickness level) and (2) the behavioral change of a patient in terms of organ offer acceptance probability with a change in policy. Next, we study the current acuity circles policy (a one-size-fits-all variant of broader sharing) and conclude that it results in lower efficiency (more offer refusals and a lower transplant benefit) than the previous share 35 policy and performs similarly on geographic equity measures. Finally, we show that broader sharing in its current form may not be the best strategy to balance geographic equity and efficiency. The intuition is that, by indiscriminately enlarging the pool of supply locations from where patients can receive offers, they tend to become more selective, resulting in more offer rejections and less efficiency. We illustrate that a policy that equalizes the supply (deceased donors)-to-demand (waiting list patients) ratios across geographies is better than acuity circles in achieving geographic equity at the lowest trade-off on efficiency metrics. Managerial implications: The key message to policymakers is that they should move away from the one-size-fits-all approach and focus on matching supply and demand to develop organ-allocation policies that score well in terms of efficiency and geographic equity. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1211 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116381611","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 a repeated interaction between a manufacturer and a retailer, where the retailer may share with the manufacturer past sales information. In our model, such information cannot improve the latter’s predictive capabilities of future demand, but it does allow him to infer past demand. Academic/practical relevance: Our main research questions are under what conditions the retailer and the manufacturer benefit from sharing such past sales information and how dynamic interaction and past sales information affect the efficiency of the distribution channel. Methodology: We model a repeated relationship between a manufacturer and a retailer, where demand fluctuates in an independent and identically distributed manner between periods. In each period, the retailer privately observes the current demand, and the manufacturer offers a menu of contracts to elicit the retailer to reveal its private information. The manufacturer may observe sales information that reveals past demand at the end of each period if the retailer chooses to share such information. Results: We find that even without sharing sales information, repeated interaction by itself enhances efficiency and profits for both firms. Past sales information further improves the channels’ efficiency and increases the manufacturer’s expected profit. Yet, past sales information increases (decreases) the retailer’s per-period expected profit when the retailer places a low (high) value on its future profits. Managerial implications: Our results provide a new strategic reasoning for sharing past sales information—as a way to increase trust in repeated vertical relationships. Furthermore, when the retailer can share a noisy signal regarding past demand, this may facilitate the exchange of sales information. We also consider the case of a financially constrained retailer and demonstrate that financial constraints may benefit the retailer as they limit the market power of the manufacturer. In contrast, the manufacturer and the channel’s efficiency are always worse off when the retailer is financially constrained. Funding: The authors acknowledge financial support from the Coller Foundation, the Eli Hurvitz Institute, and the Henry Crown Institute. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1208 .
{"title":"Sales Information Transparency and Trust in Repeated Vertical Relationships","authors":"Noam Shamir, Y. Yehezkel","doi":"10.1287/msom.2023.1208","DOIUrl":"https://doi.org/10.1287/msom.2023.1208","url":null,"abstract":"Problem definition: We study a repeated interaction between a manufacturer and a retailer, where the retailer may share with the manufacturer past sales information. In our model, such information cannot improve the latter’s predictive capabilities of future demand, but it does allow him to infer past demand. Academic/practical relevance: Our main research questions are under what conditions the retailer and the manufacturer benefit from sharing such past sales information and how dynamic interaction and past sales information affect the efficiency of the distribution channel. Methodology: We model a repeated relationship between a manufacturer and a retailer, where demand fluctuates in an independent and identically distributed manner between periods. In each period, the retailer privately observes the current demand, and the manufacturer offers a menu of contracts to elicit the retailer to reveal its private information. The manufacturer may observe sales information that reveals past demand at the end of each period if the retailer chooses to share such information. Results: We find that even without sharing sales information, repeated interaction by itself enhances efficiency and profits for both firms. Past sales information further improves the channels’ efficiency and increases the manufacturer’s expected profit. Yet, past sales information increases (decreases) the retailer’s per-period expected profit when the retailer places a low (high) value on its future profits. Managerial implications: Our results provide a new strategic reasoning for sharing past sales information—as a way to increase trust in repeated vertical relationships. Furthermore, when the retailer can share a noisy signal regarding past demand, this may facilitate the exchange of sales information. We also consider the case of a financially constrained retailer and demonstrate that financial constraints may benefit the retailer as they limit the market power of the manufacturer. In contrast, the manufacturer and the channel’s efficiency are always worse off when the retailer is financially constrained. Funding: The authors acknowledge financial support from the Coller Foundation, the Eli Hurvitz Institute, and the Henry Crown Institute. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1208 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":"73 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114042823","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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