This paper aims to investigate the influence of customer–organization identification from a customer–employee relationship perspective. Specifically, this paper examines the mediating effects of the customer–employee identification and customer–employee trust between the relationship between customer–organization identification and customer citizenship behavior. Based on social identity theory, this paper builds a research framework that is empirically tested using a sample of 465 patients or their families from one of the largest high-level hospitals in China. Structural equation modeling and a bootstrapping method were adopted to test the model and the mediation effects. Results of data analysis reveal that customer–organization identification has a direct positive influence on customer citizenship behavior, and customer–employee identification and customer–employee trust have positive mediation effects between customer–organization identification and customer citizenship behavior. Funding: This study was supported by the National Natural Science Foundation of China [Grant 71772186 to L. Xie and Grant 71802052 to X. Guan].
本文旨在从顾客-员工关系的角度研究顾客-组织认同的影响。具体而言，本文考察了顾客-员工认同和顾客-员工信任在顾客-组织认同与顾客公民行为关系中的中介作用。基于社会认同理论，本文构建了一个研究框架，并以中国最大的一家高水平医院的465名患者或家属为样本进行了实证检验。采用结构方程模型和自举方法对模型和中介效应进行检验。数据分析结果表明，顾客-组织认同对顾客公民行为具有直接的正向影响，顾客-员工认同和顾客-员工信任在顾客-组织认同与顾客公民行为之间具有正向中介作用。基金资助:本研究由国家自然科学基金资助[基金资助:71772186 to L. Xie;基金资助:71802052 to X. Guan]。
{"title":"Exploring Customer Citizenship Behavior Through Customer–Organization Identification","authors":"Lishan Xie, Wenxuan Zhang, Xinhua Guan, T. Huan","doi":"10.1287/serv.2021.0051","DOIUrl":"https://doi.org/10.1287/serv.2021.0051","url":null,"abstract":"This paper aims to investigate the influence of customer–organization identification from a customer–employee relationship perspective. Specifically, this paper examines the mediating effects of the customer–employee identification and customer–employee trust between the relationship between customer–organization identification and customer citizenship behavior. Based on social identity theory, this paper builds a research framework that is empirically tested using a sample of 465 patients or their families from one of the largest high-level hospitals in China. Structural equation modeling and a bootstrapping method were adopted to test the model and the mediation effects. Results of data analysis reveal that customer–organization identification has a direct positive influence on customer citizenship behavior, and customer–employee identification and customer–employee trust have positive mediation effects between customer–organization identification and customer citizenship behavior. Funding: This study was supported by the National Natural Science Foundation of China [Grant 71772186 to L. Xie and Grant 71802052 to X. Guan].","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75707491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Revenue management (RM) is the application of analytical methodologies and tools that predict consumer behavior and optimize product availability and prices to maximize a firm’s revenue or profit. In the last decade, data has been playing an increasingly crucial role in business decision making. As firms rely more on collected or acquired data to make business decisions, it brings opportunities and challenges to the RM research community. In this review paper, we systematically categorize the related literature by how a study is “driven” by data and focus on studies that explore the interplay between two or three of the elements: data, model, and decisions, in which the data element must be present. Specifically, we cover five data-driven RM research areas, including inference (data to model), predict then optimize (data to model to decisions), online learning (data to model to decisions to new data in a loop), end-to-end decision making (data directly to decisions), and experimental design (decisions to data to model). Finally, we point out future research directions. Funding: The research of N. Chen is partly supported by Natural Sciences and Engineering Research Council of Canada Discovery [Grant RGPIN-2020-04038]. The research of M. Hu is in part supported by Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2021-04295].
{"title":"Frontiers in Service Science: Data-Driven Revenue Management: The Interplay of Data, Model, and Decisions","authors":"Ningyuan Chen, Ming Hu","doi":"10.1287/serv.2023.0322","DOIUrl":"https://doi.org/10.1287/serv.2023.0322","url":null,"abstract":"Revenue management (RM) is the application of analytical methodologies and tools that predict consumer behavior and optimize product availability and prices to maximize a firm’s revenue or profit. In the last decade, data has been playing an increasingly crucial role in business decision making. As firms rely more on collected or acquired data to make business decisions, it brings opportunities and challenges to the RM research community. In this review paper, we systematically categorize the related literature by how a study is “driven” by data and focus on studies that explore the interplay between two or three of the elements: data, model, and decisions, in which the data element must be present. Specifically, we cover five data-driven RM research areas, including inference (data to model), predict then optimize (data to model to decisions), online learning (data to model to decisions to new data in a loop), end-to-end decision making (data directly to decisions), and experimental design (decisions to data to model). Finally, we point out future research directions. Funding: The research of N. Chen is partly supported by Natural Sciences and Engineering Research Council of Canada Discovery [Grant RGPIN-2020-04038]. The research of M. Hu is in part supported by Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2021-04295].","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135006081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How should digital service firms design and bundle their offering to capture a large market while seeking differentiation from competition? To answer this question, we consider the most generic model of competition, namely, two symmetric firms competing on price with regard to two (independent or complementary) components with an arbitrary distribution of valuations, without restrictions on their product offering. We show that three outcomes emerge in equilibrium, namely, a full-mixed bundling monopoly, a full-mixed bundling competitive duopoly leading to a price war, and a pure or partial-mixed bundling differentiated duopoly yielding positive profits for both firms. The latter equilibrium is the most plausible because it is the only one that is both trembling-hand perfect and not payoff dominated. We demonstrate the benefits of bundling under competition, thereby explaining the online platforms’ motivation for and success in expanding their offering horizontally. Yet not all products may be offered in equilibrium to avoid direct or indirect competition; hence, competition may lead to a narrower range of products available than a monopoly. Is bundling anticompetitive? It is a double-edged sword. On the one hand, it softens price competition by allowing firms to differentiate their offering. On the other hand, it stimulates competition by creating some product overlap.
{"title":"Competitive Bundling and Offer Design in a Symmetric Bertrand Duopoly","authors":"G. Roels, Araz Khodabakhshian, U. Karmarkar","doi":"10.1287/serv.2023.0325","DOIUrl":"https://doi.org/10.1287/serv.2023.0325","url":null,"abstract":"How should digital service firms design and bundle their offering to capture a large market while seeking differentiation from competition? To answer this question, we consider the most generic model of competition, namely, two symmetric firms competing on price with regard to two (independent or complementary) components with an arbitrary distribution of valuations, without restrictions on their product offering. We show that three outcomes emerge in equilibrium, namely, a full-mixed bundling monopoly, a full-mixed bundling competitive duopoly leading to a price war, and a pure or partial-mixed bundling differentiated duopoly yielding positive profits for both firms. The latter equilibrium is the most plausible because it is the only one that is both trembling-hand perfect and not payoff dominated. We demonstrate the benefits of bundling under competition, thereby explaining the online platforms’ motivation for and success in expanding their offering horizontally. Yet not all products may be offered in equilibrium to avoid direct or indirect competition; hence, competition may lead to a narrower range of products available than a monopoly. Is bundling anticompetitive? It is a double-edged sword. On the one hand, it softens price competition by allowing firms to differentiate their offering. On the other hand, it stimulates competition by creating some product overlap.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85985406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yiting Deng, Christopher S. Tang, Wei Wang, Onesun Steve Yoo
Because of the informational advantage of online marketplaces (i.e., platforms), it is a common belief that a platform’s market entry will be detrimental to third-party sellers who sell similar products on the platform. To examine the validity of this belief, we conduct an exploratory analysis using the sales data for a single product category provided by JD.com for the month of March 2018. Our analysis reveals an unexpected result. Upon the platform’s entry, third-party sellers who sell similar products can afford to charge a higher price, obtain a higher demand, and earn a higher profit. To provide a plausible explanation for this unexpected exploratory result, we develop a duopoly model that incorporates the changing competitive dynamic before and after the platform’s entry. Specifically, before entry, the platform earns a commission (based on the seller’s revenue), whereas the seller sets its retail price as a monopoly. After entry, the platform earns a profit generated by its direct sales in addition to the commission from the seller. In addition, the seller and the platform operate in a duopoly and engage in a sequential game. By examining the equilibrium outcomes associated with this sequential game, we identify conditions under which the platform’s entry can create a win-win situation for both parties. Specifically, these conditions hold when the platform’s market potential is moderate and when the platform’s entry creates a sufficiently high spillover effect on the seller, providing a plausible explanation for our empirical finding that the seller can benefit from a platform’s entry. Funding: W. Wang acknowledges the financial support from the National Natural Science Foundation of China [Grant 72173019], the Beijing Social Science Foundation [Grant 20JJA004], the Chinese Ministry of Education Research Funds on Humanities and Social Sciences [Grant 21YJA790056], and the Excellent Young Scholar Funds of UIBE [Grant 19YQ17].
{"title":"Can Third-Party Sellers Benefit from a Platform’s Entry to the Market?","authors":"Yiting Deng, Christopher S. Tang, Wei Wang, Onesun Steve Yoo","doi":"10.1287/serv.2023.0324","DOIUrl":"https://doi.org/10.1287/serv.2023.0324","url":null,"abstract":"Because of the informational advantage of online marketplaces (i.e., platforms), it is a common belief that a platform’s market entry will be detrimental to third-party sellers who sell similar products on the platform. To examine the validity of this belief, we conduct an exploratory analysis using the sales data for a single product category provided by JD.com for the month of March 2018. Our analysis reveals an unexpected result. Upon the platform’s entry, third-party sellers who sell similar products can afford to charge a higher price, obtain a higher demand, and earn a higher profit. To provide a plausible explanation for this unexpected exploratory result, we develop a duopoly model that incorporates the changing competitive dynamic before and after the platform’s entry. Specifically, before entry, the platform earns a commission (based on the seller’s revenue), whereas the seller sets its retail price as a monopoly. After entry, the platform earns a profit generated by its direct sales in addition to the commission from the seller. In addition, the seller and the platform operate in a duopoly and engage in a sequential game. By examining the equilibrium outcomes associated with this sequential game, we identify conditions under which the platform’s entry can create a win-win situation for both parties. Specifically, these conditions hold when the platform’s market potential is moderate and when the platform’s entry creates a sufficiently high spillover effect on the seller, providing a plausible explanation for our empirical finding that the seller can benefit from a platform’s entry. Funding: W. Wang acknowledges the financial support from the National Natural Science Foundation of China [Grant 72173019], the Beijing Social Science Foundation [Grant 20JJA004], the Chinese Ministry of Education Research Funds on Humanities and Social Sciences [Grant 21YJA790056], and the Excellent Young Scholar Funds of UIBE [Grant 19YQ17].","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136091195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Healthcare providers often implement quality improvement (QI) practices to improve clinical quality, which may be measured as the extent to which healthcare workers (HCWs) comply with standardized procedures designed for ensuring patient safety. Unfortunately, the effectiveness of QI practices to improve clinical quality varies from facility to facility because of healthcare delivery complexity. In this paper, we consider the contextual complexity and the provider complexity arising from healthcare delivery processes, and we propose an exploratory study based on discrete choice experiments to examine their roles in the relationship between QI practices and clinical quality. By collecting and analyzing data from 320 HCWs at a university hospital in Taiwan, we found that healthcare delivery complexity significantly moderated the effectiveness of QI practices and how they improved clinical quality. We found that the contextual complexity influenced the level of effectiveness of the QI practices, whereas the provider complexity influenced whether a QI practice may be effective or not. We also studied the effect of implementing multiple QI practices simultaneously to counter the provider complexity. We found that implementing more QI practices does not necessarily lead to better outcomes, but implementing the right ones would. Our findings provide healthcare facilities with ex ante insights for designing QI practices to improve clinical quality. Funding: W. Chen was supported by the National Natural Science Foundation of China [Grant 71902017], and C.-L. Tseng was supported by the University of New South Wales UNOVA Knowledge Hub. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0323 .
{"title":"The Impact of Healthcare Delivery Complexity on Practices for Clinical Quality Improvement: A Case of Healthcare Workers’ Hand Hygiene Compliance","authors":"Wenlin Chen, C. Tseng, Cynthia Tseng","doi":"10.1287/serv.2023.0323","DOIUrl":"https://doi.org/10.1287/serv.2023.0323","url":null,"abstract":"Healthcare providers often implement quality improvement (QI) practices to improve clinical quality, which may be measured as the extent to which healthcare workers (HCWs) comply with standardized procedures designed for ensuring patient safety. Unfortunately, the effectiveness of QI practices to improve clinical quality varies from facility to facility because of healthcare delivery complexity. In this paper, we consider the contextual complexity and the provider complexity arising from healthcare delivery processes, and we propose an exploratory study based on discrete choice experiments to examine their roles in the relationship between QI practices and clinical quality. By collecting and analyzing data from 320 HCWs at a university hospital in Taiwan, we found that healthcare delivery complexity significantly moderated the effectiveness of QI practices and how they improved clinical quality. We found that the contextual complexity influenced the level of effectiveness of the QI practices, whereas the provider complexity influenced whether a QI practice may be effective or not. We also studied the effect of implementing multiple QI practices simultaneously to counter the provider complexity. We found that implementing more QI practices does not necessarily lead to better outcomes, but implementing the right ones would. Our findings provide healthcare facilities with ex ante insights for designing QI practices to improve clinical quality. Funding: W. Chen was supported by the National Natural Science Foundation of China [Grant 71902017], and C.-L. Tseng was supported by the University of New South Wales UNOVA Knowledge Hub. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0323 .","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85708137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lockdown policies, such as stay-at-home orders, are known to be effective in controlling the spread of the novel coronavirus disease 2019. However, concerns over economic burdens of these policies rapidly propelled U.S. states to move toward reopening in the early stage of the pandemic. Decision making in most states has been challenging, especially because of a dearth of quantitative evidence on health gains versus economic burdens of different policies. To assist decision makers, we study the health and economic impacts of various lockdown policies across U.S. states and shed light on policies that are most effective. To this end, we make use of detailed data from 50 U.S. states plus the District of Columbia on various factors, including number of tests, positive and negative results, hospitalizations, ICU beds and ventilators used, residents’ mobility obtained from cellphone data, and deaths. Our analyses allow quantifying the total cost versus the total quality-adjusted life year (QALY) associated with various lockdown policies. We utilize a compartmental model with Markov chain Monte Carlo simulation to estimate the spread of disease. To calibrate our model separately for each U.S. state, we make use of empirical data on the intensity of intervention policies, age, ratio of Black/Hispanic populations, per capita income, residents’ mobility, and number of daily tests and feed them to a longitudinal mixed-effect model. Finally, we utilize a microsimulation model to estimate the total cost and total QALY for each state and perform cost-effectiveness analysis to identify policies that would have worked best. Our results show that, compared with no intervention during March–June 2020, the policies undertaken across the United States saved, on average, about 41,284.51 years’ worth of QALY (per 100K capita), incurring $164.01 million (per 100K capita). Had the states undertaken more strict policies during the same time frame than those they adopted, these values would be 44,909.41 years and $117.28 million, respectively. By quantifying the impact of various lockdown policies separately for each state, our results allow federal and state authorities to avoid following a “one size fits all” strategy and instead enact policies that are better suited for each state. Specifically, by studying the trade-offs between health gains and economic impacts, we identify the particular states that would have benefited from implementing more restrictive policies. Finally, in addition to shedding light on the impact of lockdown policies during our study period (March–June 2020), our results have important implications on curbing future fast-spreading variants of the coronavirus or other related potential epidemics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0321 .
{"title":"Health and Economic Impacts of Lockdown Policies in the Early Stage of COVID-19 in the United States","authors":"Alireza Boloori, S. Saghafian","doi":"10.1287/serv.2023.0321","DOIUrl":"https://doi.org/10.1287/serv.2023.0321","url":null,"abstract":"Lockdown policies, such as stay-at-home orders, are known to be effective in controlling the spread of the novel coronavirus disease 2019. However, concerns over economic burdens of these policies rapidly propelled U.S. states to move toward reopening in the early stage of the pandemic. Decision making in most states has been challenging, especially because of a dearth of quantitative evidence on health gains versus economic burdens of different policies. To assist decision makers, we study the health and economic impacts of various lockdown policies across U.S. states and shed light on policies that are most effective. To this end, we make use of detailed data from 50 U.S. states plus the District of Columbia on various factors, including number of tests, positive and negative results, hospitalizations, ICU beds and ventilators used, residents’ mobility obtained from cellphone data, and deaths. Our analyses allow quantifying the total cost versus the total quality-adjusted life year (QALY) associated with various lockdown policies. We utilize a compartmental model with Markov chain Monte Carlo simulation to estimate the spread of disease. To calibrate our model separately for each U.S. state, we make use of empirical data on the intensity of intervention policies, age, ratio of Black/Hispanic populations, per capita income, residents’ mobility, and number of daily tests and feed them to a longitudinal mixed-effect model. Finally, we utilize a microsimulation model to estimate the total cost and total QALY for each state and perform cost-effectiveness analysis to identify policies that would have worked best. Our results show that, compared with no intervention during March–June 2020, the policies undertaken across the United States saved, on average, about 41,284.51 years’ worth of QALY (per 100K capita), incurring $164.01 million (per 100K capita). Had the states undertaken more strict policies during the same time frame than those they adopted, these values would be 44,909.41 years and $117.28 million, respectively. By quantifying the impact of various lockdown policies separately for each state, our results allow federal and state authorities to avoid following a “one size fits all” strategy and instead enact policies that are better suited for each state. Specifically, by studying the trade-offs between health gains and economic impacts, we identify the particular states that would have benefited from implementing more restrictive policies. Finally, in addition to shedding light on the impact of lockdown policies during our study period (March–June 2020), our results have important implications on curbing future fast-spreading variants of the coronavirus or other related potential epidemics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0321 .","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76131899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers’ productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules. Introducing teams on OSPs creates a hierarchical single-leader multi-follower game. The leader (platform) establishes rewards and intrateam revenue-sharing rules for distributing workers’ payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of interteam competition and intrateam coordination causes dual effects, which are captured by an equilibrium analysis of the followers’ game. To align the platform’s interest with workers’ heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner’s reward and time-varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the nonconvex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intrateam coordination helps teams strategically mitigate the negative externalities caused by overcompetition among workers. For the platform, the optimal scheme can direct teams’ schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services. Funding: This work was supported by the National Science Foundation [Grant FW-HTF-P 2222806]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/serv.2023.0320 .
{"title":"The Dual Effects of Team Contest Design on On-Demand Service Work Schedules","authors":"Tingting Dong, Xiaotong Sun, Qi Luo, Jian Wang, Yafeng Yin","doi":"10.1287/serv.2023.0320","DOIUrl":"https://doi.org/10.1287/serv.2023.0320","url":null,"abstract":"Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers’ productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules. Introducing teams on OSPs creates a hierarchical single-leader multi-follower game. The leader (platform) establishes rewards and intrateam revenue-sharing rules for distributing workers’ payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of interteam competition and intrateam coordination causes dual effects, which are captured by an equilibrium analysis of the followers’ game. To align the platform’s interest with workers’ heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner’s reward and time-varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the nonconvex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intrateam coordination helps teams strategically mitigate the negative externalities caused by overcompetition among workers. For the platform, the optimal scheme can direct teams’ schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services. Funding: This work was supported by the National Science Foundation [Grant FW-HTF-P 2222806]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/serv.2023.0320 .","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80835294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jonas Schwamberger, Moritz Fleischmann, Arne Strauss
The outbreak of the COVID-19 pandemic led demand for online grocery orders for both click & collect (C&C) and attended home delivery (AHD) to outstrip delivery capacity by a wide margin. In the United Kingdom, the booking systems of some e-retailers could not handle the flood of incoming requests, forcing the retailers to proactively reach out to certain priority customer segments with the aim of serving as many high-priority customers as possible. To determine when to contact each customer segment in this extraordinary demand environment, we investigate the new demand management concept of proactively contacting customers. We first develop a decision policy for the C&C fulfillment method to address the problem of when to contact customers. We then extend this approach to the AHD setting. To cope with increased problem complexity, we propose a three-step procedure to solve this problem. First, we subdivide the delivery area into smaller subareas; second, we select the most promising subareas; and third, we determine which customers to contact within the chosen subareas. To gain managerial insights and to show the practical benefits of our approaches, we apply both approaches to realistic data from the London area. Our results show that proactive customer contacting allows for a tailored allocation of scarce capacity in e-groceries. We conclude with a discussion on how these contacting techniques can be valuable in postcrisis times. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services.
{"title":"Feeding the Nation—Dynamic Customer Contacting for E-Fulfillment in Times of Crisis","authors":"Jonas Schwamberger, Moritz Fleischmann, Arne Strauss","doi":"10.1287/serv.2022.0304","DOIUrl":"https://doi.org/10.1287/serv.2022.0304","url":null,"abstract":"The outbreak of the COVID-19 pandemic led demand for online grocery orders for both click & collect (C&C) and attended home delivery (AHD) to outstrip delivery capacity by a wide margin. In the United Kingdom, the booking systems of some e-retailers could not handle the flood of incoming requests, forcing the retailers to proactively reach out to certain priority customer segments with the aim of serving as many high-priority customers as possible. To determine when to contact each customer segment in this extraordinary demand environment, we investigate the new demand management concept of proactively contacting customers. We first develop a decision policy for the C&C fulfillment method to address the problem of when to contact customers. We then extend this approach to the AHD setting. To cope with increased problem complexity, we propose a three-step procedure to solve this problem. First, we subdivide the delivery area into smaller subareas; second, we select the most promising subareas; and third, we determine which customers to contact within the chosen subareas. To gain managerial insights and to show the practical benefits of our approaches, we apply both approaches to realistic data from the London area. Our results show that proactive customer contacting allows for a tailored allocation of scarce capacity in e-groceries. We conclude with a discussion on how these contacting techniques can be valuable in postcrisis times. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135907509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Niels A. H. Agatz, Soo-Haeng Cho, Hai Wang, S. Benjaafar
{"title":"Introduction to the Special Issue on Innovation in Transportation-Enabled Urban Services, Part 1","authors":"Niels A. H. Agatz, Soo-Haeng Cho, Hai Wang, S. Benjaafar","doi":"10.1287/serv.2023.0317","DOIUrl":"https://doi.org/10.1287/serv.2023.0317","url":null,"abstract":"","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80477641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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：