Service Science最新文献

{"title":"Service Science Editorial Board, 2024","authors":"","doi":"10.1287/serv.2024.eb.v16.n3","DOIUrl":"https://doi.org/10.1287/serv.2024.eb.v16.n3","url":null,"abstract":"Service Science, Volume 16, Issue 3, Page C3-C3, September 2024. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211531","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":"Earnings Pressure and Corporate Social Responsibility Impression Management","authors":"Chang Liu, Xiaoping Zhao","doi":"10.1287/serv.2023.0052","DOIUrl":"https://doi.org/10.1287/serv.2023.0052","url":null,"abstract":"Service Science, Ahead of Print. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211532","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":"Understanding the Determinants of Secondhand Goods Buying Decisions: A Young Adult Consumers’ Perspective","authors":"Abdul Bashiru Jibril, John Amoah, Sulemana Bankuoru Egala, Michael Amponsah Odei","doi":"10.1287/serv.2023.0001","DOIUrl":"https://doi.org/10.1287/serv.2023.0001","url":null,"abstract":"Service Science, Ahead of Print. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141518779","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":"Service Science/Stochastic Systems Joint Special Issue","authors":"Saif Benjaafar, Shane G. Henderson","doi":"10.1287/serv.2024.intro.v16.n2","DOIUrl":"https://doi.org/10.1287/serv.2024.intro.v16.n2","url":null,"abstract":"Service Science, Volume 16, Issue 2, Page 69-69, June 2024. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500756","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":"Service Science Editorial Board, 2024","authors":"","doi":"10.1287/serv.2024.eb.v16.n2","DOIUrl":"https://doi.org/10.1287/serv.2024.eb.v16.n2","url":null,"abstract":"Service Science, Volume 16, Issue 2, Page C3-C3, June 2024. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500706","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":"Dynamic Exception Points for Fair Liver Allocation","authors":"M. Celdir, Mustafa Akan, Sridhar Tayur","doi":"10.1287/serv.2023.0092","DOIUrl":"https://doi.org/10.1287/serv.2023.0092","url":null,"abstract":"There are disparities in access to livers based on transplant patients’ height, which disproportionately affects Hispanics, Asians, and women (across all ethnicities), because short patients can receive transplants from a smaller pool of available deceased donors for medical reasons. Reduced likelihood of transplantation leads to higher mortality rates and longer waiting times. We analyze fairness within the current U.S. liver allocation system where patients receive priority dynamically, based on their model for end-stage liver disease (MELD) scores, which reflect the severity of liver disease. We propose a simple adjustment, providing additional (exception) points based on height and MELD score, that can be easily implemented in practice, which materially reduces the disparity without sacrificing overall efficiency. We model the liver allocation system as a multiclass fluid model of overloaded queues with heterogeneous servers. We impose explicit equity constraints for all static patient classes, that is, height. We characterize the optimal solution under the objective of minimizing pretransplant mortality. The discretized version of the optimal policy is numerically solved using estimates from clinical data and a detailed simulation study demonstrates its effectiveness. The optimal policy, called the equity adjusted mortality risk policy, advocates ranking patients based on their short-term mortality risk adjusted for equity among height classes. Interpretation of the shadow prices of equity constraints in the optimal control problem as MELD exception points is novel in the transplant context since they can be seamlessly mapped into the existing system. Our simulations show that for women, the disparity can be almost completely eliminated. Hispanics and Asians greatly benefit from receiving these MELD exception points also. Our work provides a remedy to reduce the disparities in access to liver transplantation within the MELD-based allocation. Our approach can help the on-going analysis of the continuous distribution model for livers because it also considers aspects of candidate biology, notably height and body surface area. Funding: M. Akan was supported by the National Science Foundation [Grant CMMI-1334194] and the Carnegie Mellon University (CMU) [Onetto Fellowship in Operations Management]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0092 .","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141360531","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":"Can Lawyers’ Facial Attractiveness Increase the Popularity or Customer Satisfaction? An Example of Expert Q&A Services","authors":"Ya-Ling Chiu, Jying‐Nan Wang, Yuan-Teng Hsu","doi":"10.1287/serv.2022.0040","DOIUrl":"https://doi.org/10.1287/serv.2022.0040","url":null,"abstract":"The purpose of this study was to examine the impact of facial attractiveness on popularity and customer satisfaction. We conducted an empirical analysis using 7,525 professional experts’ photographs provided by a well-known expert question-and-answer (Q&A) platform in China. The findings showed that, although experts’ facial attractiveness positively affected their popularity, it negatively impacted their customer satisfaction. However, these relationships were moderated by gender. Facial attractiveness had a stronger positive effect on popularity for female experts than for male experts. By contrast, facial attractiveness negatively impacted satisfaction for female experts but had no significant effect for male experts. This study discusses the managerial implications of the findings and avenues for future research. Funding: Y.-T. Hsu was supported by the China Postdoctoral Science Foundation [Grant 2023M732269].","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140978183","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":"Dine in or Takeout? Trends on Restaurant Service Demand amid the COVID-19 Pandemic","authors":"Linxuan Shi, Zhengtian Xu","doi":"10.1287/serv.2023.0103","DOIUrl":"https://doi.org/10.1287/serv.2023.0103","url":null,"abstract":"<p>The COVID-19 pandemic has caused unprecedented damage to restaurant businesses, especially indoor dining services, because of the widespread fear of coronavirus exposure. In contrast, the online food ordering and delivery services, led by DoorDash, Grubhub, and Uber Eats, filled in the vacancy and achieved explosive growth. As a result, the restaurant industry is experiencing dramatic transformations under the crossfire of these two driving forces. However, these changes are not fully exposed because of the lack of firsthand data, let alone their potential consequences and implications. This study, thus, leverages foot traffic data to reveal and understand the trends of restaurant service demand through the pandemic. We devise a mixture model to decompose the aggregate foot traffic by dwelling time patterns into dine-in and takeout volumes. The transitions of demand structures are then identified for various restaurant sectors by service types, price levels, and locations. We observe that limited-service and budget restaurants saw a significantly faster recovery than full-service counterparts given their comparative advantages in adapting toward takeout channels. But, in the long run, our results suggest more robust demands for dine-in services at full-service restaurants, particularly those that provide more premium dining experiences. Comparatively, the off-line channels at limited-service restaurants appeared vulnerable to the cannibalization from online ordering and delivery channels, which strengthened even after society moved out of lockdown. Regionally, exurban restaurants seem to trend toward the takeout mode, whereas urban areas did not see a notable modal migration between dine-in and takeout from restaurants.</p>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887021","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 Special Issue on the Impact of AI on Service Design and Delivery","authors":"Maxime Cohen, Tinglong Dai, Beibei Li","doi":"10.1287/serv.2024.cfp.v16.n2","DOIUrl":"https://doi.org/10.1287/serv.2024.cfp.v16.n2","url":null,"abstract":"Service Science, Ahead of Print. <br/>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570715","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":"Data Sharing Between Firms and Social Planners: An Economic Analysis of Regulation, Privacy, and Competition","authors":"Ayesha Arora, Tarun Jain","doi":"10.1287/serv.2022.0052","DOIUrl":"https://doi.org/10.1287/serv.2022.0052","url":null,"abstract":"<p>Digital platforms share their customers’ data with social planners, who may utilize it to improve socioeconomic infrastructure. This may benefit customers because of the experience of improved infrastructure. On the contrary, it may lead to privacy concerns among them (as these data sets may include sensitive information). In this paper, we analyze the game-theoretic model to characterize the granularity of data sharing between firms and the social planner and the investments by the social planner to improve public infrastructure. In order to analyze the impact of regulation on data sharing strategy, we consider the cases when data sharing is regulated (decided by the social planner) and unregulated (strategically decided by firms). Our analysis reveals that the firms as well as the social planner decrease the granularity of data with an increase in privacy concerns among customers. To analyze the impact of regulation, we compare the granularity of data shared under unregulated and regulated scenarios. We find that when the firm is monopolist, it shares data with a higher level of granularity in the unregulated scenario. Interestingly, we find that under market competition, the data granularity may be higher or lower compared with the regulated scenario. Specifically, we find that if firms jointly determine the granularity of data to be shared, they share data with higher granularity under the unregulated scenario; however, if they do not collaborate and individually decide on data sharing, we find that regulation leads to higher granularity of data to be shared. Finally, we find that firms’ payoffs and customer surplus are higher under the unregulated data-sharing setup if they jointly determine the granularity of data; however, if they do not collaborate on data sharing, their payoffs, as well as customer surplus, are higher under regulation.</p><p><b>Supplemental Material:</b> The online appendix is available at https://doi.org/10.1287/serv.2022.0052.</p>","PeriodicalId":46249,"journal":{"name":"Service Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140301201","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}