Firms are grappling with multiple challenges because of COVID-19, such as supply discontinuity, disruptions, irregular demand patterns, and service delivery issues, among others. The disruption brought by the pandemic has highlighted the relevance of responsiveness and agility in service chains in particular. The unprecedented nature of the pandemic, however, has made design of agile and responsive supply chains difficult, especially for services that draw on intangible, unique resources. In this paper, we develop relevant—and thus far largely absent—theory for the design of service supply chains through a model of service supply chain fit that will guide service firms to prepare better for COVID and future threats. Our model guides the identification of the right supply chain (responsive, efficient, or agile) for services based on their operant resources, which are the intangible resources that act on other resources. Using a qualitative study, we first draw on service-dominant logic and supply chain fit framework to develop the concept of service supply chain fit; that is, the strategic consistency between a service firm’s operant resources and its supply chain. We then validate our model using survey data. The results indicate that service supply chain acts as both moderator and mediator for the relationship between operant resources and firm performance. Our findings indicate that, unless managers view service supply chain fit strategically and invest in developing operant resources for the right supply chain, future COVID-like disruptions may continue to severely impact firm performance.
{"title":"Service Supply Chain Fit: Consistency Between Operant Resources and Service Supply Chains","authors":"Raveen R. Menon, T. Niranjan, Dayna Simpson","doi":"10.1287/serv.2022.0299","DOIUrl":"https://doi.org/10.1287/serv.2022.0299","url":null,"abstract":"Firms are grappling with multiple challenges because of COVID-19, such as supply discontinuity, disruptions, irregular demand patterns, and service delivery issues, among others. The disruption brought by the pandemic has highlighted the relevance of responsiveness and agility in service chains in particular. The unprecedented nature of the pandemic, however, has made design of agile and responsive supply chains difficult, especially for services that draw on intangible, unique resources. In this paper, we develop relevant—and thus far largely absent—theory for the design of service supply chains through a model of service supply chain fit that will guide service firms to prepare better for COVID and future threats. Our model guides the identification of the right supply chain (responsive, efficient, or agile) for services based on their operant resources, which are the intangible resources that act on other resources. Using a qualitative study, we first draw on service-dominant logic and supply chain fit framework to develop the concept of service supply chain fit; that is, the strategic consistency between a service firm’s operant resources and its supply chain. We then validate our model using survey data. The results indicate that service supply chain acts as both moderator and mediator for the relationship between operant resources and firm performance. Our findings indicate that, unless managers view service supply chain fit strategically and invest in developing operant resources for the right supply chain, future COVID-like disruptions may continue to severely impact firm performance.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89016577","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}
F. Sloothaak, A. Akçay, G. van Houtum, M. van der Heijden
We consider a physical asset consisting of complex systems, where the systems may require upgrades during the lifetime of the asset. In practice, the asset owner and system supplier can make the upgrade decisions together, requiring a decision-support model that can be jointly used to optimize the total benefit for both parties. Motivated by a real-life use case including an asset owner and a system supplier, we build a continuous-time model to optimize the upgrade decisions of a system during the fixed lifetime of the asset. In our model, we capture the key critical factors that drive the upgrade decisions: increasing functionality requirements due to evolving technology, age-dependent maintenance costs, a predetermined overhaul plan of the asset, and the lifetime of the asset. A system upgrade is less costly if it is executed jointly with an asset overhaul. We first analyze the case with no additional cost of upgrading outside an overhaul. We analytically characterize the structure of the optimal upgrade policy under various realistic assumptions that lead to different types of cost functions. We then use these results as a building block to characterize the optimal policy for a generalized cost function. When there is a penalty for upgrading outside an overhaul moment, we propose a dynamic programming approach that efficiently determines the optimal upgrade policy by using our analytical results. We also prove that as this penalty increases, the optimal policy can only change to one where the number of upgrades not jointly executed with overhauls is reduced. However, the optimal number of upgrades is a nonincreasing function of this penalty. Also, surprisingly, more overhauls may lead to a smaller number of upgrades under the optimal policy. Funding: This publication is part of the project “Maritime Remote Control Tower for Service Logistics Innovation (MARCONI)” (project 439.18.309) of the research program “Integrator-Logistics as Enabler for Enhancing Society,” which is (partly) financed by the Dutch Research Council (NWO).
{"title":"After-Sales Services During an Asset’s Lifetime: Collaborative Planning of System Upgrades","authors":"F. Sloothaak, A. Akçay, G. van Houtum, M. van der Heijden","doi":"10.1287/serv.2023.0318","DOIUrl":"https://doi.org/10.1287/serv.2023.0318","url":null,"abstract":"We consider a physical asset consisting of complex systems, where the systems may require upgrades during the lifetime of the asset. In practice, the asset owner and system supplier can make the upgrade decisions together, requiring a decision-support model that can be jointly used to optimize the total benefit for both parties. Motivated by a real-life use case including an asset owner and a system supplier, we build a continuous-time model to optimize the upgrade decisions of a system during the fixed lifetime of the asset. In our model, we capture the key critical factors that drive the upgrade decisions: increasing functionality requirements due to evolving technology, age-dependent maintenance costs, a predetermined overhaul plan of the asset, and the lifetime of the asset. A system upgrade is less costly if it is executed jointly with an asset overhaul. We first analyze the case with no additional cost of upgrading outside an overhaul. We analytically characterize the structure of the optimal upgrade policy under various realistic assumptions that lead to different types of cost functions. We then use these results as a building block to characterize the optimal policy for a generalized cost function. When there is a penalty for upgrading outside an overhaul moment, we propose a dynamic programming approach that efficiently determines the optimal upgrade policy by using our analytical results. We also prove that as this penalty increases, the optimal policy can only change to one where the number of upgrades not jointly executed with overhauls is reduced. However, the optimal number of upgrades is a nonincreasing function of this penalty. Also, surprisingly, more overhauls may lead to a smaller number of upgrades under the optimal policy. Funding: This publication is part of the project “Maritime Remote Control Tower for Service Logistics Innovation (MARCONI)” (project 439.18.309) of the research program “Integrator-Logistics as Enabler for Enhancing Society,” which is (partly) financed by the Dutch Research Council (NWO).","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87085746","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}
Surgical procedures require a large number of consumable supplies that need to be kept in hospital inventory and transported to the operating rooms (OR) before the surgery. A surgical preference card (SPC) provides a list of items to be prepared for each surgery. For each item, a SPC also specifies how many should be taken to the OR (fill quantity). As the usage of most consumables in the OR is subject to uncertainty, the cards also specify how many of the filled items should be opened at the beginning of the surgery (open quantity). The fill and open quantities control the flow of consumables between the hospital inventory and the ORs and directly affect the wastage in ORs. In this work, we formulate the problem of determining the fill and open quantities on the preference cards as a stochastic optimization problem, where the objective is to minimize a weighted sum of the expected wastage and operational costs. We show that, as in the newsvendor problem, the optimal solution for the fill and open quantities takes the form of critical quantiles of the item usage distribution in the OR. The solution form together with historical usage data provide a data-driven approach to design of SPCs, as well as insights on the value of including an open decision. We demonstrate our approach using extensive numerical experiments and real usage data from a Canadian hospital. The results suggest a potential for significant reduction of wastage and operational costs in the ORs.
{"title":"A Newsvendor Approach to Design of Surgical Preference Cards","authors":"Berk Görgülü, Vahid Sarhangian","doi":"10.1287/serv.2021.0298","DOIUrl":"https://doi.org/10.1287/serv.2021.0298","url":null,"abstract":"Surgical procedures require a large number of consumable supplies that need to be kept in hospital inventory and transported to the operating rooms (OR) before the surgery. A surgical preference card (SPC) provides a list of items to be prepared for each surgery. For each item, a SPC also specifies how many should be taken to the OR (fill quantity). As the usage of most consumables in the OR is subject to uncertainty, the cards also specify how many of the filled items should be opened at the beginning of the surgery (open quantity). The fill and open quantities control the flow of consumables between the hospital inventory and the ORs and directly affect the wastage in ORs. In this work, we formulate the problem of determining the fill and open quantities on the preference cards as a stochastic optimization problem, where the objective is to minimize a weighted sum of the expected wastage and operational costs. We show that, as in the newsvendor problem, the optimal solution for the fill and open quantities takes the form of critical quantiles of the item usage distribution in the OR. The solution form together with historical usage data provide a data-driven approach to design of SPCs, as well as insights on the value of including an open decision. We demonstrate our approach using extensive numerical experiments and real usage data from a Canadian hospital. The results suggest a potential for significant reduction of wastage and operational costs in the ORs.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85402855","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}
This study investigates different types of operant resources and their effects on cocreation by considering the moderation effects of cocreation potential and the provider’s positive attitude. The contextual nature of operant resources is discussed based on how consumers activate resources in different service situations. The first study explores whether context-specific resources contribute to cocreation more than general resources. This hypothesis is found to be valid only for certain service contexts. In-depth interviews are conducted in the second study to understand the phenomenon more deeply. The qualitative study reveals three distinct types of resources: general, context-specific, and interpersonal resources. In the third study, a scenario-based experimental study is conducted to test the hypotheses, which are confirmed. We conclude that context-specific resources more directly shape cocreation, moderated by perceived level of cocreation potential. The relationship between potential and resources is then moderated by the provider’s positive attitude.
{"title":"Types of Consumer Operant Resources and Co-creation in Dialogical Service Relationships","authors":"Berna Tarı Kasnakoğlu,Yunus Kalender,Hatice Gökkaya","doi":"10.1287/serv.2021.0296","DOIUrl":"https://doi.org/10.1287/serv.2021.0296","url":null,"abstract":"This study investigates different types of operant resources and their effects on cocreation by considering the moderation effects of cocreation potential and the provider’s positive attitude. The contextual nature of operant resources is discussed based on how consumers activate resources in different service situations. The first study explores whether context-specific resources contribute to cocreation more than general resources. This hypothesis is found to be valid only for certain service contexts. In-depth interviews are conducted in the second study to understand the phenomenon more deeply. The qualitative study reveals three distinct types of resources: general, context-specific, and interpersonal resources. In the third study, a scenario-based experimental study is conducted to test the hypotheses, which are confirmed. We conclude that context-specific resources more directly shape cocreation, moderated by perceived level of cocreation potential. The relationship between potential and resources is then moderated by the provider’s positive attitude.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138542606","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}
Kate Karniouchina, Kumar R. Sarangee, Carol Theokary, Raoul V. Kübler
Pandemics cause business disruptions that have serious implications for the design and delivery of services, leading to adverse performance consequences for services industries. Focusing on the restaurant industry, the authors present a conceptual framework of restaurants’ resilience during a pandemic that is grounded in existing services and strategy research, secondary and qualitative sources, and insights obtained from social media data. This framework is tested via an empirical analysis of the Yelp COVID-19 data set. Several interesting trends in consumer preferences are identified including a rapid shift toward third-party app delivery models. Surprisingly, the analysis shows that partnering with third-party app delivery services before COVID improved firms’ resilience, whereas during the pandemic, these partnerships have a negative impact on restaurant survival. Furthermore, the study documents some important differences between the drivers of restaurant survival before versus during the pandemic, highlighting critical changes in consumer preferences that may shape the industry in the future.
{"title":"The Impact of the COVID-19 Pandemic on Restaurant Resilience: Lessons, Generalizations, and Ideas for Future Research","authors":"Kate Karniouchina, Kumar R. Sarangee, Carol Theokary, Raoul V. Kübler","doi":"10.1287/serv.2021.0293","DOIUrl":"https://doi.org/10.1287/serv.2021.0293","url":null,"abstract":"Pandemics cause business disruptions that have serious implications for the design and delivery of services, leading to adverse performance consequences for services industries. Focusing on the restaurant industry, the authors present a conceptual framework of restaurants’ resilience during a pandemic that is grounded in existing services and strategy research, secondary and qualitative sources, and insights obtained from social media data. This framework is tested via an empirical analysis of the Yelp COVID-19 data set. Several interesting trends in consumer preferences are identified including a rapid shift toward third-party app delivery models. Surprisingly, the analysis shows that partnering with third-party app delivery services before COVID improved firms’ resilience, whereas during the pandemic, these partnerships have a negative impact on restaurant survival. Furthermore, the study documents some important differences between the drivers of restaurant survival before versus during the pandemic, highlighting critical changes in consumer preferences that may shape the industry in the future.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84931557","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}
In populous metropolitan areas, the free-floating bicycle-sharing system (FFBSS) acts as an innovative urban mobility as a service, which provides an ease-of-use feature and extra flexibility in contrast to the traditional shared bicycles with docks. In consideration of customer behaviors, such as abandonment and retrial, which occur in FFBSS, a redistribution strategy for shared bicycles among different user-density locations is presented with an aim to diminish the total operational cost while enhancing the overall service level. To formulate the user and multitype shared bicycle–arrival patterns as nonhomogeneous queues, our results provide a tractable analytical paradigm for a time-varying balancing strategy for FFBSS. The bicycle variation at each virtual zone after each redistribution is determined via a nonstationary queueing model, in which the service time, patience time, and research delay are all subject to general distribution. Then, the bicycle-deployment strategy is evaluated with respect to average queueing length and abandonment rate during a normal workday based on a tailored nonhomogeneous probabilistic matching queue. To verify the efficacy and cost-effectiveness of the proposed bicycle-redistribution strategy, multiple simulation runs are conducted with respect to various times of the day. It shows that the resulting optimal rebalancing strategy is batch-based in synchrony with the time heterogeneity in the traffic demand. Furthermore, several managerial insights are provided to shed light on the rule of thumb in practical FFBSS redistribution coordination.
{"title":"Dynamic Rebalancing Strategy in Free-Float Bicycle Sharing Systems: Orbit Queues and Two-Sided Matching","authors":"Zhi Pei, Xu Dai, Tianzong Yu, Lu Zhao, Qiaochu He","doi":"10.1287/serv.2021.0287","DOIUrl":"https://doi.org/10.1287/serv.2021.0287","url":null,"abstract":"In populous metropolitan areas, the free-floating bicycle-sharing system (FFBSS) acts as an innovative urban mobility as a service, which provides an ease-of-use feature and extra flexibility in contrast to the traditional shared bicycles with docks. In consideration of customer behaviors, such as abandonment and retrial, which occur in FFBSS, a redistribution strategy for shared bicycles among different user-density locations is presented with an aim to diminish the total operational cost while enhancing the overall service level. To formulate the user and multitype shared bicycle–arrival patterns as nonhomogeneous queues, our results provide a tractable analytical paradigm for a time-varying balancing strategy for FFBSS. The bicycle variation at each virtual zone after each redistribution is determined via a nonstationary queueing model, in which the service time, patience time, and research delay are all subject to general distribution. Then, the bicycle-deployment strategy is evaluated with respect to average queueing length and abandonment rate during a normal workday based on a tailored nonhomogeneous probabilistic matching queue. To verify the efficacy and cost-effectiveness of the proposed bicycle-redistribution strategy, multiple simulation runs are conducted with respect to various times of the day. It shows that the resulting optimal rebalancing strategy is batch-based in synchrony with the time heterogeneity in the traffic demand. Furthermore, several managerial insights are provided to shed light on the rule of thumb in practical FFBSS redistribution coordination.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72812057","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}
Huiwen Jia, Siqian Shen, Jorge Alberto Ramírez García, Cong Shi
Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.
{"title":"Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic","authors":"Huiwen Jia, Siqian Shen, Jorge Alberto Ramírez García, Cong Shi","doi":"10.1287/serv.2021.0294","DOIUrl":"https://doi.org/10.1287/serv.2021.0294","url":null,"abstract":"Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84386607","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}
The COVID-19 pandemic has highlighted the instrumental role of supply chains in delivering economic, human, and societal value. At the same time, the pandemic has intensified interest among businesses, governments, and academics to examine environmental, social, and governance (ESG) issues. In today’s hyper-globalized economy, ESG measures are futile unless they explicitly incorporate a firm’s end-to-end operations throughout its entire supply chain. On the other hand, well-calibrated ESG measures should play a central role in guiding a firms’ day-to-day supply chain management practices. To illustrate the value of unifying ESG and end-to-end supply chain thinking, we present three supply chain cases that arose amid the COVID-19 pandemic, involving online platforms; public health supply chains; and vaccine development, manufacturing, and distribution, respectively. Drawn from these three cases, we spotlight some new research opportunities in both ESG and supply chain management.
{"title":"Frontiers in Service Science: Integrating ESG Measures and Supply Chain Management: Research Opportunities in the Postpandemic Era","authors":"Tinglong Dai, Christopher S. Tang","doi":"10.1287/serv.2021.0295","DOIUrl":"https://doi.org/10.1287/serv.2021.0295","url":null,"abstract":"The COVID-19 pandemic has highlighted the instrumental role of supply chains in delivering economic, human, and societal value. At the same time, the pandemic has intensified interest among businesses, governments, and academics to examine environmental, social, and governance (ESG) issues. In today’s hyper-globalized economy, ESG measures are futile unless they explicitly incorporate a firm’s end-to-end operations throughout its entire supply chain. On the other hand, well-calibrated ESG measures should play a central role in guiding a firms’ day-to-day supply chain management practices. To illustrate the value of unifying ESG and end-to-end supply chain thinking, we present three supply chain cases that arose amid the COVID-19 pandemic, involving online platforms; public health supply chains; and vaccine development, manufacturing, and distribution, respectively. Drawn from these three cases, we spotlight some new research opportunities in both ESG and supply chain management.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85374117","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}
Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.
{"title":"Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan","authors":"Miao Yu, Zhongsheng Hua","doi":"10.1287/serv.2021.0291","DOIUrl":"https://doi.org/10.1287/serv.2021.0291","url":null,"abstract":"Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86475800","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}
{"title":"Call for Papers: Service Science/Stochastic Systems Joint Special Issue","authors":"S. Benjaafar, S. Henderson","doi":"10.1287/serv.2021.0297","DOIUrl":"https://doi.org/10.1287/serv.2021.0297","url":null,"abstract":"","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81585902","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}
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