Abstract Our research investigates a joint inventory replenishment and pricing problem, where a seller controls the price of a leading product while restocking for all the products. We demonstrate that the seller's expected value functions present an structure, recommending an optimal order‐up‐to inventory‐level and list‐price policy. Our findings reveal divergent economic relationships between products from the seller's and customer's perspectives, suggesting managers broaden their strategies beyond customer viewpoints. We extend the pricing and inventory analysis to scenarios involving three substitute products under both price and inventory control. In these situations, we further reveal that sellers and customers uniformly view product inventories as substitutes, and the corresponding value functions are submodular and mutually diagonally dominant.
{"title":"Complementarity analysis of a multi‐item inventory model with leading product pricing","authors":"Sangjo Kim, Youyi Feng, Jianjun Xu","doi":"10.1111/poms.14084","DOIUrl":"https://doi.org/10.1111/poms.14084","url":null,"abstract":"Abstract Our research investigates a joint inventory replenishment and pricing problem, where a seller controls the price of a leading product while restocking for all the products. We demonstrate that the seller's expected value functions present an structure, recommending an optimal order‐up‐to inventory‐level and list‐price policy. Our findings reveal divergent economic relationships between products from the seller's and customer's perspectives, suggesting managers broaden their strategies beyond customer viewpoints. We extend the pricing and inventory analysis to scenarios involving three substitute products under both price and inventory control. In these situations, we further reveal that sellers and customers uniformly view product inventories as substitutes, and the corresponding value functions are submodular and mutually diagonally dominant.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135945127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract While global supply chains provide firms with a buffer against local shocks, they expose firms to multiregional risks. The COVID‐19 pandemic and its differential impact on different regions in the world offer an opportunity to explore these effects. We investigate the multiregional supply chain risk by focusing on credit risk measured by abnormal credit default swaps (CDS) spreads and US–China supply chain networks. Our evidence shows that local risks propagate through global supply chains to other regions. Using a matched sample, we find that abnormal CDS spreads for firms with Chinese supply chain partners increase by 12% to 13% relative to the average raw CDS spreads due to supply chain disruptions during the economic shutdown in China, and the abnormal CDS spreads decrease by 9% to 13% relative to the average raw CDS spreads when the supply chain activities resume in China. We also find that having a more global customer base can mitigate the effects of local household demand shocks. Lastly, we discover that firm size, supply chain network centrality, cash holdings, inventory, strong credit ratings, capital redeployability, and the number of segments increase resilience to global supply chain shocks, while financial leverage, operational leverage, and market competition weaken supply chain resilience.
{"title":"The impact of COVID‐19 on supply chain credit risk","authors":"Şenay Ağca, John R. Birge, Zi'ang Wang, Jing Wu","doi":"10.1111/poms.14079","DOIUrl":"https://doi.org/10.1111/poms.14079","url":null,"abstract":"Abstract While global supply chains provide firms with a buffer against local shocks, they expose firms to multiregional risks. The COVID‐19 pandemic and its differential impact on different regions in the world offer an opportunity to explore these effects. We investigate the multiregional supply chain risk by focusing on credit risk measured by abnormal credit default swaps (CDS) spreads and US–China supply chain networks. Our evidence shows that local risks propagate through global supply chains to other regions. Using a matched sample, we find that abnormal CDS spreads for firms with Chinese supply chain partners increase by 12% to 13% relative to the average raw CDS spreads due to supply chain disruptions during the economic shutdown in China, and the abnormal CDS spreads decrease by 9% to 13% relative to the average raw CDS spreads when the supply chain activities resume in China. We also find that having a more global customer base can mitigate the effects of local household demand shocks. Lastly, we discover that firm size, supply chain network centrality, cash holdings, inventory, strong credit ratings, capital redeployability, and the number of segments increase resilience to global supply chain shocks, while financial leverage, operational leverage, and market competition weaken supply chain resilience.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136078401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simon J. Blanchard, Theodore J. Noseworthy, Ethan Pancer, Maxwell Poole
Abstract Researchers have increasingly turned to crowdfunding platforms to gain insights into entrepreneurial activity and dynamics. While previous studies have explored various factors influencing crowdfunding success, such as technology, communication, and marketing strategies, the role of visual elements that can be automatically extracted from images has received less attention. This is surprising, considering that crowdfunding platforms emphasize the importance of attention‐grabbing and high‐resolution images, and previous research has shown that image characteristics can significantly impact product evaluations. Indeed, a comprehensive review of empirical articles ( n = 202) utilized Kickstarter data, focusing on the incorporation of visual information in their analyses. Our findings reveal that only 29.70% controlled for the number of images, and less than 12% considered any image details. In this manuscript, we contribute to the existing literature by emphasizing the significance of visual characteristics as essential variables in empirical investigations of crowdfunding success. We review the literature on image processing and its relevance to the business domain, highlighting two types of visual variables: visual counts (number of pictures and number of videos) and image details. Building upon previous work that discussed the role of color, composition, and figure–ground relationships, we introduce visual scene elements that have not yet been explored in crowdfunding, including the number of faces, the number of concepts depicted, and the ease of identifying those concepts. To demonstrate the predictive value of visual counts and image details, we analyze Kickstarter data using flexible machine learning models (Lasso, Ridge, Bayesian additive regression trees, and eXtreme Gradient Boosting). Our results highlight that visual count features are two of the top three predictors of success and highlight the ease at which researchers can incorporate some information about visual information. Our results also show that simple image detail features such as color matter a lot, and our proposed measures of visual scene elements can also be useful. By supplementing our article with R and Python codes that help authors extract image details ( https://osf.io/ujnzp/ ), we hope to stimulate scholars in various disciplines to consider visual information data in their empirical research and enhance the impact of visual cues on crowdfunding success.
{"title":"Extraction of visual information to predict crowdfunding success","authors":"Simon J. Blanchard, Theodore J. Noseworthy, Ethan Pancer, Maxwell Poole","doi":"10.1111/poms.14083","DOIUrl":"https://doi.org/10.1111/poms.14083","url":null,"abstract":"Abstract Researchers have increasingly turned to crowdfunding platforms to gain insights into entrepreneurial activity and dynamics. While previous studies have explored various factors influencing crowdfunding success, such as technology, communication, and marketing strategies, the role of visual elements that can be automatically extracted from images has received less attention. This is surprising, considering that crowdfunding platforms emphasize the importance of attention‐grabbing and high‐resolution images, and previous research has shown that image characteristics can significantly impact product evaluations. Indeed, a comprehensive review of empirical articles ( n = 202) utilized Kickstarter data, focusing on the incorporation of visual information in their analyses. Our findings reveal that only 29.70% controlled for the number of images, and less than 12% considered any image details. In this manuscript, we contribute to the existing literature by emphasizing the significance of visual characteristics as essential variables in empirical investigations of crowdfunding success. We review the literature on image processing and its relevance to the business domain, highlighting two types of visual variables: visual counts (number of pictures and number of videos) and image details. Building upon previous work that discussed the role of color, composition, and figure–ground relationships, we introduce visual scene elements that have not yet been explored in crowdfunding, including the number of faces, the number of concepts depicted, and the ease of identifying those concepts. To demonstrate the predictive value of visual counts and image details, we analyze Kickstarter data using flexible machine learning models (Lasso, Ridge, Bayesian additive regression trees, and eXtreme Gradient Boosting). Our results highlight that visual count features are two of the top three predictors of success and highlight the ease at which researchers can incorporate some information about visual information. Our results also show that simple image detail features such as color matter a lot, and our proposed measures of visual scene elements can also be useful. By supplementing our article with R and Python codes that help authors extract image details ( https://osf.io/ujnzp/ ), we hope to stimulate scholars in various disciplines to consider visual information data in their empirical research and enhance the impact of visual cues on crowdfunding success.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gary J. Young, E. David Zepeda, Stephen Flaherty, Md Mahmudul Hasan
Abstract Much interest exists in physicians’ ability and willingness to adapt their practice styles, as research demonstrates that many physicians practice in ways that are not aligned with the best available scientific evidence. We exploit migration patterns of primary care physicians in Massachusetts over a span of 8 years by tracking physician migrations to practice sites comprised of new peers who shared actual physical working space. We examined whether a patient's likelihood of receiving an inappropriate referral for diagnostic imaging, specifically a magnetic resonance imaging (MRI), was associated with a change in the work environment of the referring physician. Study results indicate that migrating physicians changed their practice style for imaging relatively soon after migration in conformance with the average practice style of their new peer group regardless of whether or not the practice style was aligned with evidence‐based standards for diagnostic imaging. To place our results in context, a 1 percentage point difference in average inappropriate MRI referral rates between a migrating physician's new and previous work environment was associated with approximately a 14% change in the probability that a patient received an inappropriate MRI referral. The effect diminished with greater variability in inappropriate MRI referral rates within the new peer group. The results show that physician practice style may deviate from evidence‐based standards and vary markedly among physicians within a work environment. At the same time, physician practice style is also malleable in either direction—more or less likely to deviate from evidence‐based standards in conformance with the average practice style of their new peer group. These results imply that healthcare managers can employ various institutional‐level interventions to influence physician behavior in the direction of evidence‐based practice by including strategies directed towards developing strong peer influence in physicians’ work environments.
{"title":"Physician Practice Migration and Changes in Practice Style: An Empirical Analysis of Inappropriate Diagnostic Imaging in Primary Care","authors":"Gary J. Young, E. David Zepeda, Stephen Flaherty, Md Mahmudul Hasan","doi":"10.1111/poms.14074","DOIUrl":"https://doi.org/10.1111/poms.14074","url":null,"abstract":"Abstract Much interest exists in physicians’ ability and willingness to adapt their practice styles, as research demonstrates that many physicians practice in ways that are not aligned with the best available scientific evidence. We exploit migration patterns of primary care physicians in Massachusetts over a span of 8 years by tracking physician migrations to practice sites comprised of new peers who shared actual physical working space. We examined whether a patient's likelihood of receiving an inappropriate referral for diagnostic imaging, specifically a magnetic resonance imaging (MRI), was associated with a change in the work environment of the referring physician. Study results indicate that migrating physicians changed their practice style for imaging relatively soon after migration in conformance with the average practice style of their new peer group regardless of whether or not the practice style was aligned with evidence‐based standards for diagnostic imaging. To place our results in context, a 1 percentage point difference in average inappropriate MRI referral rates between a migrating physician's new and previous work environment was associated with approximately a 14% change in the probability that a patient received an inappropriate MRI referral. The effect diminished with greater variability in inappropriate MRI referral rates within the new peer group. The results show that physician practice style may deviate from evidence‐based standards and vary markedly among physicians within a work environment. At the same time, physician practice style is also malleable in either direction—more or less likely to deviate from evidence‐based standards in conformance with the average practice style of their new peer group. These results imply that healthcare managers can employ various institutional‐level interventions to influence physician behavior in the direction of evidence‐based practice by including strategies directed towards developing strong peer influence in physicians’ work environments.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136057782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Companies have increasingly used supply chain financing instead of bank financing when engaging with financially constrained suppliers. We investigate the effectiveness of different financing mechanisms at supporting supply chain responsibility. We consider a decentralized supply chain where a buyer sources from a financially constrained supplier who borrows from either a bank or the buyer to finance his production. The buyer audits the supplier for responsibility compliance and will refuse to accept and pay for the order if the supplier fails the audit. We find that under conventional bank financing, the bank is concerned with the supplier's audit failure and will raise the interest rate. This not only hinders the supplier's compliance effort but also hurts the profitability of every stakeholder. In contrast, under buyer financing, the buyer may offer the supplier a low interest rate to motivate him to be more compliant when the supplier's collateral is of low value. However, if the supplier's collateral is of high value, the buyer may be tempted to set a high interest rate to exploit the supplier—leading to a reduction in supplier's compliance and supply chain profitability. Thus, we conclude that buyer (bank) financing is more preferable for encouraging responsibility when the supplier has low (high) collateral. Our findings suggest that buyer financing may not always be an effective approach for encouraging supply chain responsibility. As such, we propose an alternative mechanism under which the buyer offers a reward to the supplier if he passes the audit while the supplier continues to borrow from a bank. We prove that this combination of bank financing and buyer reward always improves the compliance level and in most cases increases the total supply chain profit. It is even more effective than buyer financing in encouraging responsibility especially when the supplier's collateral is of low value.
{"title":"Supply chain short‐term financing for responsible production at small and medium‐sized enterprises","authors":"Xiaole Chen, Vernon N. Hsu, Guoming Lai, Yang Li","doi":"10.1111/poms.14082","DOIUrl":"https://doi.org/10.1111/poms.14082","url":null,"abstract":"Abstract Companies have increasingly used supply chain financing instead of bank financing when engaging with financially constrained suppliers. We investigate the effectiveness of different financing mechanisms at supporting supply chain responsibility. We consider a decentralized supply chain where a buyer sources from a financially constrained supplier who borrows from either a bank or the buyer to finance his production. The buyer audits the supplier for responsibility compliance and will refuse to accept and pay for the order if the supplier fails the audit. We find that under conventional bank financing, the bank is concerned with the supplier's audit failure and will raise the interest rate. This not only hinders the supplier's compliance effort but also hurts the profitability of every stakeholder. In contrast, under buyer financing, the buyer may offer the supplier a low interest rate to motivate him to be more compliant when the supplier's collateral is of low value. However, if the supplier's collateral is of high value, the buyer may be tempted to set a high interest rate to exploit the supplier—leading to a reduction in supplier's compliance and supply chain profitability. Thus, we conclude that buyer (bank) financing is more preferable for encouraging responsibility when the supplier has low (high) collateral. Our findings suggest that buyer financing may not always be an effective approach for encouraging supply chain responsibility. As such, we propose an alternative mechanism under which the buyer offers a reward to the supplier if he passes the audit while the supplier continues to borrow from a bank. We prove that this combination of bank financing and buyer reward always improves the compliance level and in most cases increases the total supply chain profit. It is even more effective than buyer financing in encouraging responsibility especially when the supplier's collateral is of low value.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract We address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per‐unit‐time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex separately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it. This article is protected by copyright. All rights reserved
{"title":"Economic Production with Poisson Demand, Lost Sales, a Constant Setup Time, and Fixed‐rate Discrete Replenishment","authors":"Thomas Schmitt, Bruce Faaland","doi":"10.1111/poms.14072","DOIUrl":"https://doi.org/10.1111/poms.14072","url":null,"abstract":"Abstract We address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per‐unit‐time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex separately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it. This article is protected by copyright. All rights reserved","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135146143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yinshi (Agnes) Gao, Saurabh Bansal, V. Daniel R. Guide, None Jr
Abstract Customers of many original equipment manufacturers (OEMs) in business‐to‐business markets today demand product servicizing in which instead of buying the product from the OEM they buy the use of a product during a lease. During the lease, (i) the customer uses the product and returns it to the OEM after the use reaches a specific level, (ii) the OEM remanufactures the product in a costly process and sends it back to the customer, and this usecycle is repeated multiple times. The lease terms typically involve a use‐based payment. While a greater product use by a customer brings a larger revenue to the OEM, it also increases the remanufacturing cost incurred by the OEM. We investigate this trade‐off using an analytical model for a contract that is used extensively in industry. For the case of homogeneous customers with a common use rate of the product, we optimize lease payment terms and identify market and product‐remanufacturing characteristics for which the OEM should servicize the product instead of selling it. We show that an OEM should not servicize a product when the customers' use rate exceeds a threshold. This is because, beyond this threshold, the remanufacturing cost increases disproportionably, exceeding the higher usage‐based revenue. Subsequently, we consider a market with two segments with different use rates. We consider two servicizing modes: (i) servicize both market segments or (ii) selectively servicize only one segment and sell the product to the other segment, and the default mode of selling in both segments. We develop optimal lease payment terms for these use‐based servicizing modes, identify thresholds of product and market characteristics for the optimality of these modes. Finally, we extend the results to a market with more than two segments and compare the environmental impacts of the servicizing or sell decision. Numerical results informed by empirical data show that the OEM's loss of profit from choosing a suboptimal servicizing/sell decision can be significant.
在当今的企业对企业市场中，许多原始设备制造商(OEM)的客户需要产品服务，而不是从OEM购买产品，他们在租赁期间购买产品的使用权。在租赁期间，(i)客户使用产品并在使用达到特定水平后将其退还给OEM， (ii) OEM在昂贵的过程中重新制造产品并将其送回给客户，这种使用循环多次重复。租赁条款通常包括基于使用的付款。客户对产品的使用越多，给OEM带来的收益越大，同时也增加了OEM的再制造成本。我们使用工业中广泛使用的合同分析模型来研究这种权衡。对于产品使用率相同的同质客户，我们优化租赁付款条款，并确定市场和产品再制造特征，OEM应该为产品提供服务，而不是销售产品。我们表明，当客户的使用率超过阈值时，OEM不应该为产品提供服务。这是因为，超过这个阈值，再制造成本会不成比例地增加，超过更高的基于使用的收入。随后，我们考虑一个具有不同使用率的两个细分市场。我们考虑了两种服务模式:(i)为两个细分市场提供服务或(ii)有选择地只服务一个细分市场并向另一个细分市场销售产品，以及在两个细分市场销售的默认模式。我们为这些基于使用的服务模式制定了最优的租赁付款条款，确定了这些模式最优性的产品和市场特征的阈值。最后，我们将结果扩展到两个以上细分市场，并比较服务或销售决策的环境影响。根据经验数据得出的数值结果表明，主机厂选择次优维修/销售决策所造成的利润损失可能是显著的。
{"title":"OEM‐Servicizing with a Multi‐usecycle Product: Model analysis and insights","authors":"Yinshi (Agnes) Gao, Saurabh Bansal, V. Daniel R. Guide, None Jr","doi":"10.1111/poms.14076","DOIUrl":"https://doi.org/10.1111/poms.14076","url":null,"abstract":"Abstract Customers of many original equipment manufacturers (OEMs) in business‐to‐business markets today demand product servicizing in which instead of buying the product from the OEM they buy the use of a product during a lease. During the lease, (i) the customer uses the product and returns it to the OEM after the use reaches a specific level, (ii) the OEM remanufactures the product in a costly process and sends it back to the customer, and this usecycle is repeated multiple times. The lease terms typically involve a use‐based payment. While a greater product use by a customer brings a larger revenue to the OEM, it also increases the remanufacturing cost incurred by the OEM. We investigate this trade‐off using an analytical model for a contract that is used extensively in industry. For the case of homogeneous customers with a common use rate of the product, we optimize lease payment terms and identify market and product‐remanufacturing characteristics for which the OEM should servicize the product instead of selling it. We show that an OEM should not servicize a product when the customers' use rate exceeds a threshold. This is because, beyond this threshold, the remanufacturing cost increases disproportionably, exceeding the higher usage‐based revenue. Subsequently, we consider a market with two segments with different use rates. We consider two servicizing modes: (i) servicize both market segments or (ii) selectively servicize only one segment and sell the product to the other segment, and the default mode of selling in both segments. We develop optimal lease payment terms for these use‐based servicizing modes, identify thresholds of product and market characteristics for the optimality of these modes. Finally, we extend the results to a market with more than two segments and compare the environmental impacts of the servicizing or sell decision. Numerical results informed by empirical data show that the OEM's loss of profit from choosing a suboptimal servicizing/sell decision can be significant.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Auto‐delivery is a subscription model widely employed in supply chains, whereby a supplier delivers products to a buyer (or multiple buyers) according to the buyer's choice of a constant shipping quantity to be delivered at prescheduled dates. The buyer enjoys a discount for the auto‐delivery orders and other benefits, including free subscription and cancellation. Because these benefits seem to all accrue to the buyer at the supplier's expense, the rationale for the supplier's decision to offer auto‐delivery and its impact on the profitability of both parties is an intriguing concern. We first develop a model that consists of a supplier and a single buyer, whereby the supplier offers a discount for the auto‐delivery orders and the buyer chooses the auto‐delivery quantity with the flexibility of cancelling the subscription. We derive the two parties' operating characteristics of their inventory systems and examine their optimal decisions. Our analysis shows that buyers benefit from the auto‐delivery discount; the supplier benefits from the demand‐expansion effect and the inventory‐reduction effect, a potential discount on the cost of the auto‐delivery units; and the supply chain benefits from reducing the bullwhip effect. We also find that channel coordination requires the supplier to pass the inventory‐related savings to the buyer through the auto‐delivery discount, which depends on the ratio of the two parties' holding cost rates. Moreover, we examine a model extension whereby the supplier announces a discount that is available for multiple buyers, we show that the supplier's optimal auto‐delivery discount under exponential demand can be determined based on the aggregate‐level demand information from all buyers. Finally, we discuss another model extension whereby the lead time of the supplier's recurring orders for auto‐delivery is longer than that of the regular orders and present a full analysis of the case when the lead time differential is one time period.
{"title":"Inventory and supply chain management with auto‐delivery subscription","authors":"Shi Chen, Junfei Lei, Kamran Moinzadeh","doi":"10.1111/poms.14078","DOIUrl":"https://doi.org/10.1111/poms.14078","url":null,"abstract":"Abstract Auto‐delivery is a subscription model widely employed in supply chains, whereby a supplier delivers products to a buyer (or multiple buyers) according to the buyer's choice of a constant shipping quantity to be delivered at prescheduled dates. The buyer enjoys a discount for the auto‐delivery orders and other benefits, including free subscription and cancellation. Because these benefits seem to all accrue to the buyer at the supplier's expense, the rationale for the supplier's decision to offer auto‐delivery and its impact on the profitability of both parties is an intriguing concern. We first develop a model that consists of a supplier and a single buyer, whereby the supplier offers a discount for the auto‐delivery orders and the buyer chooses the auto‐delivery quantity with the flexibility of cancelling the subscription. We derive the two parties' operating characteristics of their inventory systems and examine their optimal decisions. Our analysis shows that buyers benefit from the auto‐delivery discount; the supplier benefits from the demand‐expansion effect and the inventory‐reduction effect, a potential discount on the cost of the auto‐delivery units; and the supply chain benefits from reducing the bullwhip effect. We also find that channel coordination requires the supplier to pass the inventory‐related savings to the buyer through the auto‐delivery discount, which depends on the ratio of the two parties' holding cost rates. Moreover, we examine a model extension whereby the supplier announces a discount that is available for multiple buyers, we show that the supplier's optimal auto‐delivery discount under exponential demand can be determined based on the aggregate‐level demand information from all buyers. Finally, we discuss another model extension whereby the lead time of the supplier's recurring orders for auto‐delivery is longer than that of the regular orders and present a full analysis of the case when the lead time differential is one time period.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Product evaluation is an essential business process, and digital innovation has made it possible for companies to immediately process available information. We develop a model where a company continuously assesses information that follows a doubly stochastic Poisson process with a mean‐reverting and stochastic intensity. Accordingly, the company faces a two‐dimensional optimal stopping problem in which the company continues to evaluate the product if and only if the product reputation and information intensity remain in a continuation set. We employ a probabilistic approach to prove that the continuation set takes the form of an open interval for any fixed information arrival intensity. Given the complicated nature of the optimal solutions, we develop an asymptotic expansive solution, and numerical studies show that our solution performs well. We also analyze a heuristic solution where the company substitutes the dynamic intensity with a constant intensity. Interestingly, we find that this heuristic company does not necessarily benefit from having a higher product reputation.
{"title":"Evaluation timing with Dynamic Information: Optimization and heuristic","authors":"Meng Li, Lijun Bo, Tingting Zhang","doi":"10.1111/poms.14070","DOIUrl":"https://doi.org/10.1111/poms.14070","url":null,"abstract":"Abstract Product evaluation is an essential business process, and digital innovation has made it possible for companies to immediately process available information. We develop a model where a company continuously assesses information that follows a doubly stochastic Poisson process with a mean‐reverting and stochastic intensity. Accordingly, the company faces a two‐dimensional optimal stopping problem in which the company continues to evaluate the product if and only if the product reputation and information intensity remain in a continuation set. We employ a probabilistic approach to prove that the continuation set takes the form of an open interval for any fixed information arrival intensity. Given the complicated nature of the optimal solutions, we develop an asymptotic expansive solution, and numerical studies show that our solution performs well. We also analyze a heuristic solution where the company substitutes the dynamic intensity with a constant intensity. Interestingly, we find that this heuristic company does not necessarily benefit from having a higher product reputation.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Social media platforms like Facebook and Twitter have emerged as effective channels for advertising that enable consumer targeting based on demographics, interests, and user behavior. Social media marketers have utilized information spillover within these platforms to reach a larger customer base. This information spillover also exists across groups of users within the platform and enhances returns from social media advertising. Thus, this information spillover can be utilized to strategically sequence targeted advertising to amplify the returns from social media ads. In this paper, we present a theoretical model for information retention and show that the sequential advertising strategy is effective in targeting groups of users on a social media platform. In addition, we provide empirical evidence through two series of randomized field experiments. From experiments for a health services organization, we find that sequential advertising campaigns provide 23% more clicks when compared to campaigns that target groups simultaneously, which translates to a saving of 18.7% in the advertising budget to achieve similar results as simultaneous advertising. Additionally, we found that sequential advertising campaigns targeting a smaller group first followed by a larger group provide 10.7% additional clicks when compared to targeting a larger group first followed by a smaller group. These results were consistent for consumer packaged goods that were advertised on Facebook and Twitter. These results provide implications for social media advertising research and practice.
{"title":"Strategic social media marketing: An empirical analysis of sequential advertising","authors":"Parshuram Hotkar, Rajiv Garg, Kristen Sussman","doi":"10.1111/poms.14075","DOIUrl":"https://doi.org/10.1111/poms.14075","url":null,"abstract":"Abstract Social media platforms like Facebook and Twitter have emerged as effective channels for advertising that enable consumer targeting based on demographics, interests, and user behavior. Social media marketers have utilized information spillover within these platforms to reach a larger customer base. This information spillover also exists across groups of users within the platform and enhances returns from social media advertising. Thus, this information spillover can be utilized to strategically sequence targeted advertising to amplify the returns from social media ads. In this paper, we present a theoretical model for information retention and show that the sequential advertising strategy is effective in targeting groups of users on a social media platform. In addition, we provide empirical evidence through two series of randomized field experiments. From experiments for a health services organization, we find that sequential advertising campaigns provide 23% more clicks when compared to campaigns that target groups simultaneously, which translates to a saving of 18.7% in the advertising budget to achieve similar results as simultaneous advertising. Additionally, we found that sequential advertising campaigns targeting a smaller group first followed by a larger group provide 10.7% additional clicks when compared to targeting a larger group first followed by a smaller group. These results were consistent for consumer packaged goods that were advertised on Facebook and Twitter. These results provide implications for social media advertising research and practice.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：