DECISION SCIENCES最新文献_第3页

Dependence, power imbalance, and value gains in business process outsourcing 业务流程外包中的依赖性、权力不平衡和价值收益

IF 2.5 4区管理学

DECISION SCIENCES Pub Date : 2024-10-13 DOI: 10.1111/deci.12652

Sukruth Suresh, T. Ravichandran

引用次数: 0

Identifying influential individuals and predicting future demand of chronic kidney disease patients 识别有影响的个体并预测慢性肾脏疾病患者的未来需求

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-10-13 DOI: 10.1111/deci.12650

Zlatana D. Nenova, Valerie L. Bartelt

{"title":"Identifying influential individuals and predicting future demand of chronic kidney disease patients","authors":"Zlatana D. Nenova, Valerie L. Bartelt","doi":"10.1111/deci.12650","DOIUrl":"https://doi.org/10.1111/deci.12650","url":null,"abstract":"To ensure high service quality, managers need to personalize treatment options and meet their customer demands. Our research is motivated by the need to better anticipate and prepare for that. We develop a generalizable framework that is the first to address two healthcare risk management goals: (1) identifying high risk and stable-demand customers and (2) predicting the medium-term demand for services of stable-demand customers. We also design a model-agnostic method for variable evaluation. It can rank predictors based on their global impact, and highlight their effect on a model's local accuracy. In this research, we leverage a large electronic medical records' data set, which comprised of 48,344 chronic kidney disease patients treated across geographically diverse Veterans Affairs regions. Our framework indicates that although only 1.3% of the examined individuals are high-risk patients, it can correctly identify 35% of them and highlight an additional 8.9% as having important demand implications. Identifying high-risk individuals can be used in (1) monitoring prioritization, (2) patients' motivation, and (3) patients' stabilization. Furthermore, our model accurately predicts the monthly need for care of stable-demand individuals up to 3 years into the future and outperforms popular statistical and data mining models. This information is especially critical for hospital management in identifying future hiring needs.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 2","pages":"123-143"},"PeriodicalIF":2.8,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12650","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143849117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Variable-weight combined forecasting model with causal analysis and clustering for refined oil sales forecasting 成品油销售预测的因果分析聚类变权组合预测模型

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-10-08 DOI: 10.1111/deci.12648

Xiaofeng Xu, Wenzhi Liu, Lean Yu, Yinsheng Yu, Wanli Yi

{"title":"Variable-weight combined forecasting model with causal analysis and clustering for refined oil sales forecasting","authors":"Xiaofeng Xu, Wenzhi Liu, Lean Yu, Yinsheng Yu, Wanli Yi","doi":"10.1111/deci.12648","DOIUrl":"https://doi.org/10.1111/deci.12648","url":null,"abstract":"Forecasting refined oil sales is essential in energy supply chain management. However, accurate forecasting is limited by several factors, including multiple influences of external features, heterogeneity of different gasoline stations, and difficulty in balancing linear and nonlinear forecasting. To address these issues, we propose a novel variable-weight combined forecasting model. In the first stage, the model incorporates causal analysis and clustering methods to provide a quantitative description of multiple effects of external features and highly correlated aggregation of homogeneous data. Subsequently, based on the patterns of external feature influences learned from historical data, variable-weight combined forecasting is realized to balance linear and nonlinear forecasting dynamically. Experiments based on real sales data procured from several regions demonstrate that the proposed model outperforms other benchmark and widely used models in terms of forecasting accuracy and statistical significance. The ablation experimental results confirm the significance of causal analysis, clustering, and variable-weight combined forecasting in improving the balance between linear and nonlinear forecasting. Moreover, our results indicate that improving the quality of clustering can yield greater benefits than improving the amount of training data. Finally, we also explore whether the forecasting superiority translates into better inventory control, and our results show that the proposed optimization model can effectively balance inventory cost and service level, while also better suppress the bullwhip effect.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"577-604"},"PeriodicalIF":2.8,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860489","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}

引用次数: 0

Investigating the impact of postponement and stock-sharing strategies on prepositioned relief stocks 调查推迟和股票分享策略对预先安置的救济股票的影响

IF 2.5 4区管理学

DECISION SCIENCES Pub Date : 2024-10-03 DOI: 10.1111/deci.12647

Lamia Gülnur Kasap-Şimşek, Burcu Balcik, Florent Chané

{"title":"Investigating the impact of postponement and stock-sharing strategies on prepositioned relief stocks","authors":"Lamia Gülnur Kasap-Şimşek, Burcu Balcik, Florent Chané","doi":"10.1111/deci.12647","DOIUrl":"https://doi.org/10.1111/deci.12647","url":null,"abstract":"Prepositioning is a critical disaster preparedness mechanism for humanitarian organizations (HOs) but requires significant investment. Improving the efficiency of prepositioned stocks is a primary concern within the humanitarian community. This study, conducted in collaboration with the Emergency Supply Prepositioning Strategy (ESUPS) Working Group, examines the impact of implementing postponement and stock-sharing strategies in a regional humanitarian warehouse. We focus on a setting where multiple HOs preposition supplies within the same warehouse to serve disaster-affected countries. Traditionally, these prepositioned supplies are branded with the respective HOs' logos, hindering the sharing of surplus stock during disaster response. Our system defers the branding process for a portion of the stockpile until after a disaster, facilitating the sharing of unbranded stock among HOs. To evaluate the benefits of postponement in this humanitarian context, we develop a two-phase inventory allocation framework for distributing branded and unbranded stocks to disaster-affected countries and for sharing unbranded stocks among HOs. We then incorporate our inventory allocation models into a Monte Carlo simulation algorithm that accounts for uncertainties regarding the occurrence and impact of disasters. Using a case study based on data from ESUPS members in the Caribbean region, we demonstrate that the proposed strategy can significantly enhance the efficiency and effectiveness of prepositioning. Remarkably, we observe a U-shaped relationship in response time as the postponement rate increases, while the fill rate and inventory utilization consistently improve. Our numerical study provides valuable insights for decision making in humanitarian logistics.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 6","pages":"533-552"},"PeriodicalIF":2.5,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12647","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145824409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

When do people switch queues? An empirical study of discretionary queue switching at a physical examination center 人们什么时候换队？某体检中心自主队列切换的实证研究

IF 2.5 4区管理学

DECISION SCIENCES Pub Date : 2024-10-01 DOI: 10.1111/deci.12646

Yi-Na Li, Zhijian Cui, Junkai Ji, Jiuchang Wei

{"title":"When do people switch queues? An empirical study of discretionary queue switching at a physical examination center","authors":"Yi-Na Li, Zhijian Cui, Junkai Ji, Jiuchang Wei","doi":"10.1111/deci.12646","DOIUrl":"https://doi.org/10.1111/deci.12646","url":null,"abstract":"Automatic queueing systems have been applied in many practical settings to guide customers through a sequence of service stages and achieve efficient queueing. However, our field observations of queueing from a large-scale physical examination center, which adopts an automatic assignment system with the option of discretionary switching, reveal a relatively high likelihood of queue-switching requests. That is, many queuers request overriding the algorithm's sequence and ask for a different one, leading to increased total waiting times. Motivated by these observations, this study investigates the behavioral mechanisms behind driving queuers’ switching decisions. Specifically, we examine the roles of two competing mechanisms as the waiting progresses: the motivation to explore a better opportunity (to reduce waiting time) and the consumption of cognitive resources for self-control to adhere to the assigned queue. Our empirical results reveal a U-shaped relationship between the examinees’ tendency to switch and the service progress. This U-shaped relationship steepens when more (vs. less) queuers are ahead of the focal examinee and when the time is (vs. is not) “on an hour” (e.g., 9:00 and 10:00). This study contributes to the behavioral theory of queueing systems through a novel perspective highlighting the competing mechanisms driving individuals’ algorithm aversion behavior (i.e., queue switching) during the progress of multiple services, providing insights into how to design efficient queueing systems.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 4","pages":"361-382"},"PeriodicalIF":2.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935263","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}

引用次数: 0

Tax privacy concerns hamper digitization of the nanostore channel 税收隐私问题阻碍纳米存储通道数字化

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-09-17 DOI: 10.1111/deci.12643

Rafael Escamilla, Prisca Brosi, Jan C. Fransoo, Camilo Mora-Quiñones, Christopher Mejía-Argueta

{"title":"Tax privacy concerns hamper digitization of the nanostore channel","authors":"Rafael Escamilla, Prisca Brosi, Jan C. Fransoo, Camilo Mora-Quiñones, Christopher Mejía-Argueta","doi":"10.1111/deci.12643","DOIUrl":"10.1111/deci.12643","url":null,"abstract":"Various entities, such as startups, suppliers, and governments, face substantial difficulties in convincing nanostore shopkeepers to adopt digital technologies. Given the informal status of nanostores, we posit that shopkeepers experience Tax Privacy Concerns from their operational records potentially becoming transparent to the tax authorities, which hampers their inclination to digitize. Through the application of a survey and vignette experiments in the field with hundreds of shopkeepers across three cities in Latin America, we find consistent evidence for the negative role of Tax Privacy Concerns, above and beyond shopkeepers' Willingness to Share Data with various entities, Trust in the government and other entities, and general Privacy Concerns. Further, we show that having entities that shopkeepers trust and are willing to share data with offer technological solutions does not mitigate shopkeepers' Tax Privacy Concerns and boosts digitization. In contrast, positive word of mouth that data are unlikely to be shared with the tax authorities does mitigate Tax Privacy Concerns. Overall, our findings provide novel evidence for the existence and influence of privacy concerns for operational data among microentrepreneurs, which answers calls in the extant literature to explore privacy concerns beyond the consumer context.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 3","pages":"235-253"},"PeriodicalIF":2.8,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12643","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An interpretable machine learning methodology to generate interaction effect hypotheses from complex datasets 从复杂数据集生成交互效应假设的可解释机器学习方法

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-08-13 DOI: 10.1111/deci.12642

Murtaza Nasir, Nichalin S. Summerfield, Serhat Simsek, Asil Oztekin

{"title":"An interpretable machine learning methodology to generate interaction effect hypotheses from complex datasets","authors":"Murtaza Nasir, Nichalin S. Summerfield, Serhat Simsek, Asil Oztekin","doi":"10.1111/deci.12642","DOIUrl":"10.1111/deci.12642","url":null,"abstract":"Machine learning (ML) models are increasingly being used in decision-making, but they can be difficult to understand because most ML models are black boxes, meaning that their inner workings are not transparent. This can make interpreting the results of ML models and understanding the underlying data-generation process (DGP) challenging. In this article, we propose a novel methodology called Simple Interaction Finding Technique (SIFT) that can help make ML models more interpretable. SIFT is a data- and model-agnostic approach that can be used to identify interaction effects between variables in a dataset. This can help improve our understanding of the DGP and make ML models more transparent and explainable to a wider audience. We test the proposed methodology against various factors (such as ML model complexity, dataset noise, spurious variables, and variable distributions) to assess its effectiveness and weaknesses. We show that the methodology is robust against many potential problems in the underlying dataset as well as ML algorithms.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"549-576"},"PeriodicalIF":2.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12642","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beneficiary appointment and delivery planning in a conflict setting 冲突环境下的受益人任命和交付规划

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-08-13 DOI: 10.1111/deci.12645

Burcu Balcik, Maria Battarra, Melih Celik, Bashar Khoury, Anand Subramanian

{"title":"Beneficiary appointment and delivery planning in a conflict setting","authors":"Burcu Balcik, Maria Battarra, Melih Celik, Bashar Khoury, Anand Subramanian","doi":"10.1111/deci.12645","DOIUrl":"10.1111/deci.12645","url":null,"abstract":"In this study, we explore the challenges faced by humanitarian organizations engaged in relief efforts for internally displaced individuals during armed conflicts. Based on our semistructured interviews with three local nongovernmental organizations (LNGOs) in Syria, we introduce a new appointment scheduling problem to improve decision-making for aid delivery planning in conflict settings. Operating in a highly resource-constrained environment, these LNGOs face complexities that necessitate effective decision support tools to streamline supply delivery at relief facilities, where a large number of registered beneficiaries are served. Our proposed appointment scheduling problem aims to optimize the allocation of delivery times for various supplies, taking into account the urgency of needs and operational limitations. We present a heuristic that addresses the complexities of the proposed scheduling problem in a flexible way. The heuristic can accommodate simple rules derived from LNGOs' operational policies on the ground, such as imposing a single visit per beneficiary, delivering a single supply type per day, and preallocating time slots to conflict groups. We present a case study based on the Latakia district of Syria to assess the performance of our heuristic and the effectiveness of simplified delivery strategies. Our results not only showcase the efficiency of the heuristic, but also provide valuable managerial insights. We find that cross-training of staff is more beneficial when supplies are relatively abundant. Furthermore, the simplified delivery policies are effective in certain conditions contingent upon various factors, including supply scarcity, difficulty of travel, and the level of conflict in the population.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 3","pages":"297-315"},"PeriodicalIF":2.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven inventory forecasting in periodic-review inventory systems adjusted with a fill rate requirement 在定期审查库存系统中进行数据驱动的库存预测，并根据填充率要求进行调整

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-08-10 DOI: 10.1111/deci.12644

Joanna Bruzda, Babak Abbasi, Tomasz Urbańczyk

引用次数: 0

Sharing is caring: Designing incentive rebate strategies for information-sharing alliances 分享就是关爱：为信息共享联盟设计激励回扣战略

IF 2.8 4区管理学

DECISION SCIENCES Pub Date : 2024-07-14 DOI: 10.1111/deci.12640

Yueran Zhuo, Senay Solak, Yi Zou, Bingyan Hu

{"title":"Sharing is caring: Designing incentive rebate strategies for information-sharing alliances","authors":"Yueran Zhuo, Senay Solak, Yi Zou, Bingyan Hu","doi":"10.1111/deci.12640","DOIUrl":"10.1111/deci.12640","url":null,"abstract":"Information security plays a crucial role in organizational governance and management, and information-sharing alliances (ISAs) have emerged as effective platforms for the secure and controlled sharing of information security knowledge. Despite their potential, many ISAs face financial and operational challenges, including inadequate pricing policies and insufficient incentives for information sharing. This study addresses these challenges by proposing a modeling framework for the fee rebate strategies that ISAs can deploy to motivate effective information sharing. Taking into account the economic implications of both information sharing and information security technology investment, we propose two ISA-based pricing rebate strategies for information sharing: the split-return rebate strategy and the swap-return rebate strategy. Analytical and numerical analyses are conducted to demonstrate the dynamics in different ISA settings under these pricing rebate strategies. The results suggest that in addition to firm size, the price for participating in sharing should be adjusted based on each participating firm's technology investment level, its information-sharing level, and the marginal cost of information sharing. Also, by focusing on various information-sharing environments, the study identifies specific conditions under which unfair sharing practices are likely to occur.","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 3","pages":"254-281"},"PeriodicalIF":2.8,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141650418","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}

引用次数: 0