Pub Date : 2024-05-09DOI: 10.1177/10591478241256644
George P. Ball, Hessam Bavafa, Christian C. Blanco, Hyunwoo Park, Kaitlin D. Wowak
Consumers taking prescription drugs have limited ability to ascertain drug quality before taking the drug. After drug use, however, consumers frequently report their personal experiences with prescription drugs on one of the world’s largest medical websites: WebMD. Drug reviews on WebMD are a potentially rich source of free-form text that can be utilized to inform firms, consumers, researchers, and the Food and Drug Administration (FDA) about the quality and safety of prescription drugs. Additionally, because men and women communicate in starkly different ways, the gender of the reviewer may play a key role in drug reviews signaling drug quality problems. We examine if drug review textual sentiment is associated with the hazard of a serious drug recall and whether this relationship varies depending on the gender of the reviewer. We analyze textual sentiment on drug reviews from WebMD along with 13 years of drug recall data using several hazard models. We find that the more negative the drug review sentiment, the greater the hazard of a serious recall on that drug. This relationship is completely explained by drug reviews written by females; reviews written by males have no explanatory power. Our findings are confirmed by numerous robustness checks. In post-hoc analysis, we explore possible mechanisms by comparing female and male adverse events on the recalled drugs in our study. Our contributions to gender diversity and drug quality literature leads to implications for the FDA, WebMD, and firms that manufacture prescription drugs.
{"title":"EXPRESS: Gender and Serious Drug Recalls: a Textual Sentiment Analysis of Drug Reviews on WebMD","authors":"George P. Ball, Hessam Bavafa, Christian C. Blanco, Hyunwoo Park, Kaitlin D. Wowak","doi":"10.1177/10591478241256644","DOIUrl":"https://doi.org/10.1177/10591478241256644","url":null,"abstract":"Consumers taking prescription drugs have limited ability to ascertain drug quality before taking the drug. After drug use, however, consumers frequently report their personal experiences with prescription drugs on one of the world’s largest medical websites: WebMD. Drug reviews on WebMD are a potentially rich source of free-form text that can be utilized to inform firms, consumers, researchers, and the Food and Drug Administration (FDA) about the quality and safety of prescription drugs. Additionally, because men and women communicate in starkly different ways, the gender of the reviewer may play a key role in drug reviews signaling drug quality problems. We examine if drug review textual sentiment is associated with the hazard of a serious drug recall and whether this relationship varies depending on the gender of the reviewer. We analyze textual sentiment on drug reviews from WebMD along with 13 years of drug recall data using several hazard models. We find that the more negative the drug review sentiment, the greater the hazard of a serious recall on that drug. This relationship is completely explained by drug reviews written by females; reviews written by males have no explanatory power. Our findings are confirmed by numerous robustness checks. In post-hoc analysis, we explore possible mechanisms by comparing female and male adverse events on the recalled drugs in our study. Our contributions to gender diversity and drug quality literature leads to implications for the FDA, WebMD, and firms that manufacture prescription drugs.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140994377","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}
Pub Date : 2024-05-09DOI: 10.1177/10591478241256167
As businesses increasingly move into digital domains, digital piracy has become more prevalent and more costly. Pre-release piracy, where pirated versions of digital products are distributed before legitimate ones, remains particularly damaging to digital product developers. Although workers’ social norms may play a critical role, limited research exists on the behavioral factors that intentionally or unintentionally contribute to pre-release piracy, particularly when considering multinational nuances (e.g., national cultures) and workers’ experience (e.g., organizational tenure). To address this gap, we develop and test an empirical model of how national culture and organizational tenure jointly predict the likelihood of pre-release piracy. Our empirical analyses employ a dataset compiled from more than twenty distinct sources and capture the electronic video game industry’s PC-based products from 2000 through 2019. For national culture, we focus on two forms of collectivism – institutional and in-group – finding that institutional collectivism is associated with a reduced likelihood of pre-release piracy, while in-group collectivism increases it. We also find that the likelihood of pre-release piracy reduces with a product development team’s organizational tenure, but that this relationship is distinctively moderated by each of collectivism’s two forms. Specifically, the benefits of increased organizational tenure are amplified in the presence of stronger institutional collectivism but muted in the presence of stronger in-group collectivism. We link our findings to research streams on national culture, digital piracy, and organizational tenure, and specify contributions to each.
随着企业越来越多地进入数字领域，数字盗版变得越来越普遍，代价也越来越高。发行前盗版，即盗版数字产品先于正版数字产品发行，对数字产品开发商的危害尤为严重。尽管工人的社会规范可能起着关键作用，但有关有意或无意造成发行前盗版的行为因素的研究却很有限，尤其是在考虑到跨国细微差别（如国家文化）和工人经验（如组织任期）的情况下。为了弥补这一不足，我们建立并测试了一个实证模型，以研究国家文化和组织任期如何共同预测发行前盗版的可能性。我们的实证分析采用了二十多个不同来源的数据集，涵盖了电子视频游戏行业从 2000 年到 2019 年基于 PC 的产品。在民族文化方面，我们关注两种形式的集体主义--制度集体主义和群体内集体主义--发现制度集体主义与发行前盗版可能性的降低相关，而群体内集体主义则会增加发行前盗版的可能性。我们还发现，产品开发团队的组织任期越长，发布前盗版的可能性就越小，但这种关系会受到集体主义两种形式的不同影响。具体来说，组织任期增加的益处在机构集体主义较强的情况下会放大，但在群体内集体主义较强的情况下会减弱。我们将研究结果与有关民族文化、数字盗版和组织任期的研究流联系起来，并具体说明了对这些研究流的贡献。
{"title":"EXPRESS: The Effects of Collectivism and Organizational Tenure on the Emergence of Pre-Release Digital Piracy","authors":"","doi":"10.1177/10591478241256167","DOIUrl":"https://doi.org/10.1177/10591478241256167","url":null,"abstract":"As businesses increasingly move into digital domains, digital piracy has become more prevalent and more costly. Pre-release piracy, where pirated versions of digital products are distributed before legitimate ones, remains particularly damaging to digital product developers. Although workers’ social norms may play a critical role, limited research exists on the behavioral factors that intentionally or unintentionally contribute to pre-release piracy, particularly when considering multinational nuances (e.g., national cultures) and workers’ experience (e.g., organizational tenure). To address this gap, we develop and test an empirical model of how national culture and organizational tenure jointly predict the likelihood of pre-release piracy. Our empirical analyses employ a dataset compiled from more than twenty distinct sources and capture the electronic video game industry’s PC-based products from 2000 through 2019. For national culture, we focus on two forms of collectivism – institutional and in-group – finding that institutional collectivism is associated with a reduced likelihood of pre-release piracy, while in-group collectivism increases it. We also find that the likelihood of pre-release piracy reduces with a product development team’s organizational tenure, but that this relationship is distinctively moderated by each of collectivism’s two forms. Specifically, the benefits of increased organizational tenure are amplified in the presence of stronger institutional collectivism but muted in the presence of stronger in-group collectivism. We link our findings to research streams on national culture, digital piracy, and organizational tenure, and specify contributions to each.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140995304","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}
Pub Date : 2024-05-09DOI: 10.1177/10591478241256383
Long He, Tu Ni
Digital platforms have improved the effciency and quality of smart city operations by soliciting more customer inputs, for example, in the form of suggestions. One innovative option in urban transportation is the shared shuttle service, which lies between traditional public transportation and ride-hailing services. Platforms that offer these services can gather customer suggestions in a crowd-starting" manner, which provides valuable insights into customer needs. However, this also presents a challenge in balancing service coverage and quality to meet customer needs implied by their suggestions. To address this issue, we introduce an optimization framework designed to maximize expected profit by leveraging customer response models which characterize how customers will respond to different service attributes and how their suggestions inform these responses. When estimating these response models, we present methods involving isotonic penalty and shrinkage tailored for handling small datasets. To demonstrate the practical implications, we apply our model to a shared shuttle service case study and discuss practical considerations, such as the value of information, the effectiveness of our estimation approaches, and the benefits of involving customers in the service design process.
{"title":"EXPRESS: Crowd-starting a Shared (Shuttle) Service with Customer Suggestions","authors":"Long He, Tu Ni","doi":"10.1177/10591478241256383","DOIUrl":"https://doi.org/10.1177/10591478241256383","url":null,"abstract":"Digital platforms have improved the effciency and quality of smart city operations by soliciting more customer inputs, for example, in the form of suggestions. One innovative option in urban transportation is the shared shuttle service, which lies between traditional public transportation and ride-hailing services. Platforms that offer these services can gather customer suggestions in a crowd-starting\" manner, which provides valuable insights into customer needs. However, this also presents a challenge in balancing service coverage and quality to meet customer needs implied by their suggestions. To address this issue, we introduce an optimization framework designed to maximize expected profit by leveraging customer response models which characterize how customers will respond to different service attributes and how their suggestions inform these responses. When estimating these response models, we present methods involving isotonic penalty and shrinkage tailored for handling small datasets. To demonstrate the practical implications, we apply our model to a shared shuttle service case study and discuss practical considerations, such as the value of information, the effectiveness of our estimation approaches, and the benefits of involving customers in the service design process.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997961","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}
Pub Date : 2024-05-06DOI: 10.1177/10591478241255066
Opher Baron, A. Ciré, Sinem Savaser
We consider an order fulfillment problem of an omni-channel retailer that ships online orders from its distribution center (DC) and brick-and-mortar stores. Stores use their local information, not observed by the retailer, that can lead them to accept or reject fulfillment requests of items in an online order. We investigate the problem of sequencing requests to stores and inventory rationing decisions at the DC to minimize expected costs under uncertain store acceptance behavior and when items are indistinguishable in terms of shipping. First, under the scenario that stores are used only when the DC has insufficient inventory, we propose a Markov Decision Process formulation and analyze the performance of myopic policies that are preferable because of their interpretability. We show that the performance rate of a myopic approach that orders stores by cost only depends on the number of items in an order, which is small in practice. We also determine conditions for the range of acceptance probabilities for the myopic policy to be optimal for small-sized orders. Using optimality conditions for a special case of the problem, we develop an adaptive variant of the myopic policy, and propose a new degree-based strategy that balances shipping costs and acceptance probabilities. Numerical testing suggests that the best-performing sequencing policy is within 1% of optimality on average. Moreover, using two years of data from a large omni-channel retailer in North America, we observe that adaptive policies, albeit more complex, are beneficial in reducing costs and split deliveries if acceptance rates can be estimated accurately. Second, we determine when the retailer should ship from stores or ration the inventory at the DC. We show that for single-item orders, the optimal policy has a threshold structure, where, remarkably, the highest priority region is also subject to rationing. We then consider the novel multi-unit-single-item rationing problem, and leverage the structure of the single-unit model to develop a heuristic. We numerically establish the efficacy of rationing models and our heuristic.
{"title":"EXPRESS: Decentralized Online Order Fulfillment in Omni-Channel Retailers","authors":"Opher Baron, A. Ciré, Sinem Savaser","doi":"10.1177/10591478241255066","DOIUrl":"https://doi.org/10.1177/10591478241255066","url":null,"abstract":"We consider an order fulfillment problem of an omni-channel retailer that ships online orders from its distribution center (DC) and brick-and-mortar stores. Stores use their local information, not observed by the retailer, that can lead them to accept or reject fulfillment requests of items in an online order. We investigate the problem of sequencing requests to stores and inventory rationing decisions at the DC to minimize expected costs under uncertain store acceptance behavior and when items are indistinguishable in terms of shipping. First, under the scenario that stores are used only when the DC has insufficient inventory, we propose a Markov Decision Process formulation and analyze the performance of myopic policies that are preferable because of their interpretability. We show that the performance rate of a myopic approach that orders stores by cost only depends on the number of items in an order, which is small in practice. We also determine conditions for the range of acceptance probabilities for the myopic policy to be optimal for small-sized orders. Using optimality conditions for a special case of the problem, we develop an adaptive variant of the myopic policy, and propose a new degree-based strategy that balances shipping costs and acceptance probabilities. Numerical testing suggests that the best-performing sequencing policy is within 1% of optimality on average. Moreover, using two years of data from a large omni-channel retailer in North America, we observe that adaptive policies, albeit more complex, are beneficial in reducing costs and split deliveries if acceptance rates can be estimated accurately. Second, we determine when the retailer should ship from stores or ration the inventory at the DC. We show that for single-item orders, the optimal policy has a threshold structure, where, remarkably, the highest priority region is also subject to rationing. We then consider the novel multi-unit-single-item rationing problem, and leverage the structure of the single-unit model to develop a heuristic. We numerically establish the efficacy of rationing models and our heuristic.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141009317","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}
Pub Date : 2024-05-06DOI: 10.1177/10591478241255667
Bahriye Cesaret, A. Bayram
Keeping up with competitors’ prices is one of the top operational challenges in pricing. However, competitive interactions in revenue management have not received much research attention in the past due to their complexity. We conduct a series of laboratory experiments to investigate the dynamic pricing behavior of two capacity-constrained firms under competition. Our experiments initially control for strategic interactions between the sellers and then allow for them. To gain a broader understanding, we also manipulate demand uncertainty and the expected market size. Our results confirm the dependency of dynamic pricing decisions on the competitor’s behavior. We find that the theory is much more forgiving—in the sense that it predicts a lower level of competition among the sellers—than what we actually observe in the laboratory. The modeling literature indicates that the seller with the lower capacity has a competitive advantage, but our results reveal the opposite. Further, there is potential for high-capacity sellers to benefit from competition. Sellers tend to underprice (resp., overprice) their units at the beginning (resp., end) of a selling season. Also, competition lasts longer than the theory predicts, and customers benefit from the biases of the competing sellers. The higher-capacity seller following the best-response policy is not harmed due to the biases of the competitor. However, the lower-capacity seller’s performance is greatly influenced by the competitor's degree of rationality.
{"title":"EXPRESS: Competitive Dynamic Pricing under Capacity Constraints: an Experimental Study","authors":"Bahriye Cesaret, A. Bayram","doi":"10.1177/10591478241255667","DOIUrl":"https://doi.org/10.1177/10591478241255667","url":null,"abstract":"Keeping up with competitors’ prices is one of the top operational challenges in pricing. However, competitive interactions in revenue management have not received much research attention in the past due to their complexity. We conduct a series of laboratory experiments to investigate the dynamic pricing behavior of two capacity-constrained firms under competition. Our experiments initially control for strategic interactions between the sellers and then allow for them. To gain a broader understanding, we also manipulate demand uncertainty and the expected market size. Our results confirm the dependency of dynamic pricing decisions on the competitor’s behavior. We find that the theory is much more forgiving—in the sense that it predicts a lower level of competition among the sellers—than what we actually observe in the laboratory. The modeling literature indicates that the seller with the lower capacity has a competitive advantage, but our results reveal the opposite. Further, there is potential for high-capacity sellers to benefit from competition. Sellers tend to underprice (resp., overprice) their units at the beginning (resp., end) of a selling season. Also, competition lasts longer than the theory predicts, and customers benefit from the biases of the competing sellers. The higher-capacity seller following the best-response policy is not harmed due to the biases of the competitor. However, the lower-capacity seller’s performance is greatly influenced by the competitor's degree of rationality.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141011382","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}
Pub Date : 2024-05-02DOI: 10.1177/10591478241254853
Mohammad Hashemi Joo, Yuka Nishikawa, K. Dandapani, Vaidyanathan Jayaraman
We investigate how language, an essential part of culture, affects manufacturing firms’ supply chain operations management practices, including the cash conversion cycle and its components. Based on the Sapir–Whorf hypothesis, which theorizes that a language’s structure may affect how its speakers think, prior studies have established that using the future tense to describe future events increases one’s mental distance from the future, reducing a person’s concern about it. Building upon this foundation, we hypothesize that firms in weak future-time reference countries are likely to be better prepared for future volatility in demand for their products and therefore carry higher inventory to avoid potential stockouts. We also hypothesize that firms in weak future-time reference countries are more apprehensive about long-term relationships with their customers and hence extend longer credit terms to them. Finally, we hypothesize that firms in weak future-time reference countries have longer operating and cash conversion cycles due to carrying higher levels of inventory and extending longer credit terms to customers. The empirical results using a large global sample of 193,625 firm-year observations from 45 countries support our hypotheses. In terms of economic significance, on average, the cash conversion cycle of firms in weak future-time reference countries is approximately 11 percent longer than that of firms in strong future-time reference countries. We also find that the effect of language is dominant over the influence of traditional cultural dimensions. Together, the results suggest that time encoding in the language of a firm is a determining factor in its supply chain operations.
{"title":"EXPRESS: Unlocking the Role of Language and National Culture: Effects on Supply Chain Operations in a Global Context","authors":"Mohammad Hashemi Joo, Yuka Nishikawa, K. Dandapani, Vaidyanathan Jayaraman","doi":"10.1177/10591478241254853","DOIUrl":"https://doi.org/10.1177/10591478241254853","url":null,"abstract":"We investigate how language, an essential part of culture, affects manufacturing firms’ supply chain operations management practices, including the cash conversion cycle and its components. Based on the Sapir–Whorf hypothesis, which theorizes that a language’s structure may affect how its speakers think, prior studies have established that using the future tense to describe future events increases one’s mental distance from the future, reducing a person’s concern about it. Building upon this foundation, we hypothesize that firms in weak future-time reference countries are likely to be better prepared for future volatility in demand for their products and therefore carry higher inventory to avoid potential stockouts. We also hypothesize that firms in weak future-time reference countries are more apprehensive about long-term relationships with their customers and hence extend longer credit terms to them. Finally, we hypothesize that firms in weak future-time reference countries have longer operating and cash conversion cycles due to carrying higher levels of inventory and extending longer credit terms to customers. The empirical results using a large global sample of 193,625 firm-year observations from 45 countries support our hypotheses. In terms of economic significance, on average, the cash conversion cycle of firms in weak future-time reference countries is approximately 11 percent longer than that of firms in strong future-time reference countries. We also find that the effect of language is dominant over the influence of traditional cultural dimensions. Together, the results suggest that time encoding in the language of a firm is a determining factor in its supply chain operations.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141020022","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}
Pub Date : 2024-05-02DOI: 10.1177/10591478241254857
Yash Babar, Jason Chan, Ben Choi
Exercise-tracking apps are digital tools for delivering personalized behavioral interventions. Despite the growing usage of exercise applications, the efficacy of in-exercise app features in driving usage and athletic outcomes remains poorly understood. To remain competitive, sports organizations now need to leverage tracking tools to efficiently allocate resources and streamline training regimens and interventions for their core assets (i.e., athletes). In response to these operational needs, we examine two specific forms of such in-exercise interventions, namely performance feedback and social feedback. We conducted an 18-month-long field study with 1,037 uniformed group servicemen to assess the effect of these feedback types on running and usage outcomes. Results from the field study provided evidence that these two app features improved the servicemen’s running times and frequency of application usage, on average. Contrary to the common belief that more features are better, the joint usage of two feedback features does not produce additive effects. Tests at more granular levels suggest that users who received both feedback types in exercise episodes exhibit overconfidence behavior by participating in fewer subsequent exercises. The receipt of both feedback may be redundant and can cause user annoyance. Heterogeneity tests revealed that while performance feedback benefited most runners, social features were effective only for already stronger runners. Also, only positive social feedback had a significant impact on running performance. The results further indicate that performance feedback generated a slow but sustained increase in usage frequency, while social feedback spurred quick initial growth in usage but dwindled in effectiveness over time. Implications for theory and practice, as well as directions for further research, are discussed.
{"title":"EXPRESS: “Run Forrest Run!”: Measuring the Impact of App-Enabled Performance and Social Feedback on Athletic and Usage Outcomes","authors":"Yash Babar, Jason Chan, Ben Choi","doi":"10.1177/10591478241254857","DOIUrl":"https://doi.org/10.1177/10591478241254857","url":null,"abstract":"Exercise-tracking apps are digital tools for delivering personalized behavioral interventions. Despite the growing usage of exercise applications, the efficacy of in-exercise app features in driving usage and athletic outcomes remains poorly understood. To remain competitive, sports organizations now need to leverage tracking tools to efficiently allocate resources and streamline training regimens and interventions for their core assets (i.e., athletes). In response to these operational needs, we examine two specific forms of such in-exercise interventions, namely performance feedback and social feedback. We conducted an 18-month-long field study with 1,037 uniformed group servicemen to assess the effect of these feedback types on running and usage outcomes. Results from the field study provided evidence that these two app features improved the servicemen’s running times and frequency of application usage, on average. Contrary to the common belief that more features are better, the joint usage of two feedback features does not produce additive effects. Tests at more granular levels suggest that users who received both feedback types in exercise episodes exhibit overconfidence behavior by participating in fewer subsequent exercises. The receipt of both feedback may be redundant and can cause user annoyance. Heterogeneity tests revealed that while performance feedback benefited most runners, social features were effective only for already stronger runners. Also, only positive social feedback had a significant impact on running performance. The results further indicate that performance feedback generated a slow but sustained increase in usage frequency, while social feedback spurred quick initial growth in usage but dwindled in effectiveness over time. Implications for theory and practice, as well as directions for further research, are discussed.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141022168","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}
Pub Date : 2024-05-02DOI: 10.1177/10591478241254855
Wei Liu, Vidyadhar G. Kulkarni
We study a multi-server queueing system where a customer is satisfied (and generates a unit revenue) if their queueing time is at most a given constant. If the queueing time of the admitted customer exceeds this constant, the customer gets served, but is unsatisfied and generates no revenue. Such queueing systems arise in the context of modeling service systems where excessive delays are of concern. A key challenge is how to design an admission control policy to maximize the number of satisfied customers per unit time in the long run, assuming that we can observe the number of customers in the system at any time. We call this the binary reward structure system and show that a threshold-type admission policy is optimal. The optimal threshold policy has to be computed numerically. Hence we propose a square-root admission policy to approximate the optimal admission control policy, and compare the performance of these two policies. We derive an analytical upper bound on the performance of optimal admission control policy by deriving an optimal admission policy assuming we have full information over the queueing time of the admitted customers. This is equivalent to a queueing system where customers abandon the queue (i.e., leave without service) if their queueing time exceeds the given constant. We demonstrate that the optimal policy that includes customer abandonment, or alternatively, the optimal policy under full information, the optimal threshold policy, and the square-root admission policy, all exhibit identical performance in the asymptotic regions of the parameter space. Our numerical results indicate that the worst optimality gap of the square-root admission policy is within 3.9% of the optimal revenue, and implementing the square-root admission policy in the observable queueing system leads to a revenue loss that is at most 5.6% of the maximum possible revenue rate in the full information system. We also compare the binary reward structure with the more common linear reward structure where the system incurs holding cost per unit queueing time per customer. In addition, we also show that the analysis based on queueing time is applicable to the system time as well.
{"title":"EXPRESS: Admission Control in Multi-server Systems under Binary Reward Structure","authors":"Wei Liu, Vidyadhar G. Kulkarni","doi":"10.1177/10591478241254855","DOIUrl":"https://doi.org/10.1177/10591478241254855","url":null,"abstract":"We study a multi-server queueing system where a customer is satisfied (and generates a unit revenue) if their queueing time is at most a given constant. If the queueing time of the admitted customer exceeds this constant, the customer gets served, but is unsatisfied and generates no revenue. Such queueing systems arise in the context of modeling service systems where excessive delays are of concern. A key challenge is how to design an admission control policy to maximize the number of satisfied customers per unit time in the long run, assuming that we can observe the number of customers in the system at any time. We call this the binary reward structure system and show that a threshold-type admission policy is optimal. The optimal threshold policy has to be computed numerically. Hence we propose a square-root admission policy to approximate the optimal admission control policy, and compare the performance of these two policies. We derive an analytical upper bound on the performance of optimal admission control policy by deriving an optimal admission policy assuming we have full information over the queueing time of the admitted customers. This is equivalent to a queueing system where customers abandon the queue (i.e., leave without service) if their queueing time exceeds the given constant. We demonstrate that the optimal policy that includes customer abandonment, or alternatively, the optimal policy under full information, the optimal threshold policy, and the square-root admission policy, all exhibit identical performance in the asymptotic regions of the parameter space. Our numerical results indicate that the worst optimality gap of the square-root admission policy is within 3.9% of the optimal revenue, and implementing the square-root admission policy in the observable queueing system leads to a revenue loss that is at most 5.6% of the maximum possible revenue rate in the full information system. We also compare the binary reward structure with the more common linear reward structure where the system incurs holding cost per unit queueing time per customer. In addition, we also show that the analysis based on queueing time is applicable to the system time as well.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141018861","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}
Pub Date : 2024-05-02DOI: 10.1177/10591478241254854
Buhui Qiu, Fangming Xu, Andy C. L. Yeung, Cheng (Colin) Zeng
Although risk management is widely regarded as an important topic within supply chain (SC) management, little research studies the contagious effect of risk factors along SC networks. By using stock price crashes as an indicator of risk factors, our study reveals that stock price crash risk can be transmitted from major customers to suppliers with a delay of up to two weeks. We show that the information opacity of suppliers is a factor that potentially contributes to the delayed crash contagion. We also find that the contagion effect becomes more pronounced as the importance of customers increases. Moreover, customer operational incidents have a more pronounced contagion effect on suppliers compared to customer financial incidents. Additionally, we find that suppliers tend to take strategic measures following the stock price crashes of their major customers, including diversifying their customer base, enhancing operational efficiency, and improving product quality. However, among these actions, only the improvement of operational efficiency effectively mitigates the adverse impact of customer stock price crashes on suppliers. Overall, our findings provide new insight into the distribution of risk factors across SC networks, highlighting the critical role of operational improvements in bolstering the resilience of firms to SC risks.
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Pub Date : 2024-04-23DOI: 10.1177/10591478241252357
Xiting Gong, Suting Liu
In this paper, we consider hybrid manufacturing/remanufacturing inventory systems that produce a single product to satisfy demands over a finite planning horizon. In each period, the firm receives random demand and returns of end-of-life products. A serviceable product can be manufactured from ample raw materials or remanufactured from a returned product. The two operations possess random dedicated capacities. The firm’s objective is to minimize the expected total discounted cost over the planning horizon. We partially characterize the firm’s optimal inventory policy when the two capacities are positively dependent and completely characterize it when only one capacity is random. When there is ample manufacturing capacity, we connect the model with an auxiliary dual-sourcing inventory model and derive a more detailed structure of the optimal policy. Finally, our numerical study provides actionable insights into the effects of random capacities. Among others, we find that approximating a slightly/moderately variable remanufacturing capacity as its deterministic mean capacity or ignoring the correlation between two random capacities under a multi-period setting incurs a limited cost to the firm.
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