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":"74 1","pages":""},"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":"25 1","pages":""},"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":"9 1","pages":""},"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":"4 1","pages":""},"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":"6 1","pages":""},"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":"184 1","pages":""},"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}
Building on contingency theory and the input–process–output model, this paper investigates the relationships between customer relationship management (CRM) technology adoption, customization capability, CRM effectiveness, and strategic alignment. By surveying senior managers of customized service projects from 288 information technology service firms in Taiwan, we find that CRM technology adoption has a positive relationship with customization capacity, which is, in turn, positively correlated with CRM effectiveness with the correlation being moderated by strategic alignment. This study suggests that CRM marketing and operational technologies can enhance CRM effectiveness via customization capability. This study also uncovers approaches to achieving enhancement.
{"title":"Linking Customization Capability with CRM Technology Adoption and Strategic Alignment","authors":"Hung-Tai Tsou","doi":"10.1287/serv.2021.0286","DOIUrl":"https://doi.org/10.1287/serv.2021.0286","url":null,"abstract":"Building on contingency theory and the input–process–output model, this paper investigates the relationships between customer relationship management (CRM) technology adoption, customization capability, CRM effectiveness, and strategic alignment. By surveying senior managers of customized service projects from 288 information technology service firms in Taiwan, we find that CRM technology adoption has a positive relationship with customization capacity, which is, in turn, positively correlated with CRM effectiveness with the correlation being moderated by strategic alignment. This study suggests that CRM marketing and operational technologies can enhance CRM effectiveness via customization capability. This study also uncovers approaches to achieving enhancement.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":"105 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72440672","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}
Ruichen Sun, L. Maillart, Silviya Valeva, Andrew J. Schaefer, Shaina Starks
Human breast milk provides nutritional and medicinal benefits that are important to infants, particularly those who are premature or ill. Donor human milk, collected, processed, and dispensed via milk banks, is the standard of care for infants in need whose mothers cannot provide an adequate supply of milk. In this paper, we focus on streamlining donor human milk processing at nonprofit milk banks. On days that milk is processed, milk banks thaw frozen deposits, pool together milk from multiple donors to meet nutritional specifications of predefined milk types, bottle and divide the pools into batches, and pasteurize the batches using equipment with various degrees of labor requirements. Limitations in staffing and equipment and the need to follow strict healthcare protocols require productive, expedient, and frugal pooling strategies. We formulate integer programs that optimize the batching-pasteurizing decisions and the integrated pooling-batching-pasteurizing decisions by minimizing labor and meeting target production goals. We further strengthen these formulations by establishing valid inequalities for the integrated model. Numerical results demonstrate a reduction in the optimality gap through the strengthened formulation versus the basic integer programming formulation. A case study at Mothers’ Milk Bank of North Texas demonstrates significant improvement in meeting milk type production targets and a modest reduction in labor compared with former practice. The model is in use at Mothers’ Milk Bank of North Texas and has effectively improved their production balance across different milk types.
{"title":"Optimal Pooling, Batching, and Pasteurizing of Donor Human Milk","authors":"Ruichen Sun, L. Maillart, Silviya Valeva, Andrew J. Schaefer, Shaina Starks","doi":"10.1287/serv.2021.0285","DOIUrl":"https://doi.org/10.1287/serv.2021.0285","url":null,"abstract":"Human breast milk provides nutritional and medicinal benefits that are important to infants, particularly those who are premature or ill. Donor human milk, collected, processed, and dispensed via milk banks, is the standard of care for infants in need whose mothers cannot provide an adequate supply of milk. In this paper, we focus on streamlining donor human milk processing at nonprofit milk banks. On days that milk is processed, milk banks thaw frozen deposits, pool together milk from multiple donors to meet nutritional specifications of predefined milk types, bottle and divide the pools into batches, and pasteurize the batches using equipment with various degrees of labor requirements. Limitations in staffing and equipment and the need to follow strict healthcare protocols require productive, expedient, and frugal pooling strategies. We formulate integer programs that optimize the batching-pasteurizing decisions and the integrated pooling-batching-pasteurizing decisions by minimizing labor and meeting target production goals. We further strengthen these formulations by establishing valid inequalities for the integrated model. Numerical results demonstrate a reduction in the optimality gap through the strengthened formulation versus the basic integer programming formulation. A case study at Mothers’ Milk Bank of North Texas demonstrates significant improvement in meeting milk type production targets and a modest reduction in labor compared with former practice. The model is in use at Mothers’ Milk Bank of North Texas and has effectively improved their production balance across different milk types.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":"9 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78278412","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 paper examines older adult care services during the outbreak of the COVID-19 global pandemic. Specifically, it investigates emerging developments initiated or augmented by the pandemic and discusses their permanency in a postpandemic world. Primary survey data are collected from both older adult care-providing organizations (supply) and individuals receiving or considering care (demand) in the United States. Qualitative support from various sources supplements the surveys. The results indicate a movement toward deinstitutional care options, which began prepandemic but intensified during the outbreak. Care organizations confirm this development, reporting more occupancy-related concerns. Findings also suggest that telehealth and digital communication tools have substantially expanded. Benefits, issues, and future projections of these trends are discussed, and some suggestions for industry reform are proposed. These results illuminate many actionable ideas for various stakeholders, including older adults, industry practitioners, and policymakers.
{"title":"Caring for an Aging Population in a Post-Pandemic World: Emerging Trends in the U.S. Older Adult Care Industry","authors":"Lu Kong,Kejia Hu,Matthew Walsman","doi":"10.1287/serv.2021.0280","DOIUrl":"https://doi.org/10.1287/serv.2021.0280","url":null,"abstract":"This paper examines older adult care services during the outbreak of the COVID-19 global pandemic. Specifically, it investigates emerging developments initiated or augmented by the pandemic and discusses their permanency in a postpandemic world. Primary survey data are collected from both older adult care-providing organizations (supply) and individuals receiving or considering care (demand) in the United States. Qualitative support from various sources supplements the surveys. The results indicate a movement toward deinstitutional care options, which began prepandemic but intensified during the outbreak. Care organizations confirm this development, reporting more occupancy-related concerns. Findings also suggest that telehealth and digital communication tools have substantially expanded. Benefits, issues, and future projections of these trends are discussed, and some suggestions for industry reform are proposed. These results illuminate many actionable ideas for various stakeholders, including older adults, industry practitioners, and policymakers.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":"6 1","pages":"258-274"},"PeriodicalIF":2.3,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138517783","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}
Saif Benjaafar, Editor-in-Chief of Service Science, thanks the referees who have generously provided expert counsel and guidance on a voluntary basis to the journal. Without them, the journal would not be able to function. The following list acknowledges those who acted as referees for papers considered during this past calendar year.
{"title":"Appreciation to Referees, 2021","authors":"","doi":"10.1287/serv.2021.0288","DOIUrl":"https://doi.org/10.1287/serv.2021.0288","url":null,"abstract":"Saif Benjaafar, Editor-in-Chief of Service Science, thanks the referees who have generously provided expert counsel and guidance on a voluntary basis to the journal. Without them, the journal would not be able to function. The following list acknowledges those who acted as referees for papers considered during this past calendar year.","PeriodicalId":46249,"journal":{"name":"Service Science","volume":"16 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74772912","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：