Decision Support Systems最新文献_第9页

Social contagions in business resilience: Evidence from the U.S. restaurant industry in the COVID-19 pandemic 企业复原力中的社会传染病：美国餐饮业在 COVID-19 大流行中的证据

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-09 DOI: 10.1016/j.dss.2024.114288

Long Xia , Christopher Lee

{"title":"Social contagions in business resilience: Evidence from the U.S. restaurant industry in the COVID-19 pandemic","authors":"Long Xia , Christopher Lee","doi":"10.1016/j.dss.2024.114288","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114288","url":null,"abstract":"<div><p>The unprecedented COVID-19 has led to the collapse of numerous businesses, notably within the tourism and hospitality sectors. Despite the burgeoning research on resilience, few studies have embraced a theoretical lens, particularly from a social network perspective. In addition, most extant resilience studies have not explicitly considered the geographic accessibility prerequisite inherent to tourism and hospitality products. In this study, leveraging the social contagion theory, we present a holistic research framework to investigate the influence of geographic and social proximities, two pivotal social contagion mechanisms, on business resilience. We also delve into moderating factors to discern the conditions under which contagion effects are amplified or attenuated. To validate our theoretical model, we select the restaurant industry as our research context, given its severe impact from COVID-19. Utilizing an extensive dataset from Yelp, encompassing ten U.S. cities varying in sizes and geolocations, our findings indicate that both geographic and social influences exert significant direct effects on resilience. Additionally, these effects exhibit considerable variations contingent upon product attributes, customer characteristics, and geographic factors. Theoretically, we are the first to substantiate the role of social contagion theory in examining resilience, enriching our understanding of the social network mechanism of behavioral contagion among customers during the COVID-19 pandemic. We also offer valuable practical implications for various stakeholders in supporting their management strategies and decision-making in developing effective plans and preparations, minimizing adverse impacts, and ensuring sustainability in the face of future disruptions.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114288"},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141606539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The effect of different types of comparative reviews on product sales 不同类型的比较性评论对产品销售的影响

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-06 DOI: 10.1016/j.dss.2024.114287

Yuzhuo Li , Min Zhang , G. Alan Wang , Ning Zhang

{"title":"The effect of different types of comparative reviews on product sales","authors":"Yuzhuo Li , Min Zhang , G. Alan Wang , Ning Zhang","doi":"10.1016/j.dss.2024.114287","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114287","url":null,"abstract":"<div><p>Comparative online reviews have evolved into a vital instrument for consumers in decision-making, offering valuable comparisons and available options. Drawing on the insights from the linguistic category model (LCM) and elaboration likelihood model (ELM), we propose that different types (attribute-based and experience-based) of comparative reviews can affect consumers' perceived credibility of online reviews, thus impacting product sales. We analyzed 136,260 reviews on e-commerce platforms to assess these effects and introduced review valence as a boundary condition. Utilizing a combination of pattern discovery, supervised learning techniques, and manual coding, we identified attribute-based and experience-based comparative reviews and subsequently classified them based on positive, neutral, and negative valence. Subsequently, we took the product sales as the dependent variable and applied a two-way fixed effects model. The results indicate that attribute-based comparative reviews exert a more favorable influence on product sales compared to experience-based ones. Additionally, positive comparative reviews, irrespective of their attribute-based or experience-based nature, demonstrate a greater impact than regular positive reviews. However, negative and neutral comparative reviews, only when associated with attribute-based information, exhibit a significant effect. The results highlight the value of different types of comparative reviews and illuminate the moderating role of review valence. Our findings offer new insights and practical guidance for marketers and e-commerce platforms in capitalizing on the important influence of comparative reviews and enhancing the presentation of online reviews.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114287"},"PeriodicalIF":6.7,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141606537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Live streaming channel recommendation based on viewers' interaction behavior: A hypergraph approach 基于观众互动行为的直播流媒体频道推荐：超图方法

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-01 DOI: 10.1016/j.dss.2024.114272

Li Yu , Wei Gong , Dongsong Zhang

{"title":"Live streaming channel recommendation based on viewers' interaction behavior: A hypergraph approach","authors":"Li Yu , Wei Gong , Dongsong Zhang","doi":"10.1016/j.dss.2024.114272","DOIUrl":"10.1016/j.dss.2024.114272","url":null,"abstract":"<div><p>Live streaming has become increasingly popular in recent years. Viewers of live streaming channels can interact with live streamers through various behaviors, such as sending virtual gifts and Danmaku. It is very critical to accurately model such viewers' behaviors, which reflect their interest, for recommending live streaming channels. However, existing studies on live streaming channel recommendation usually model viewers' interaction behaviors through traditional graphs where an edge only connects two nodes, which cannot capture interaction relationships between multi-viewers and multi-channels. In this study, we propose a novel approach to live streaming recommendation based on <strong>V</strong>iewers' <strong>I</strong>nteraction <strong>B</strong>ehavior <strong>M</strong>odeled by <strong>Hyper</strong>graphs (VIBM-Hyper). Specifically, VIBM-Hyper first constructs two hypergraphs to model viewers' interaction behaviors, including a channel-oriented behavior hypergraph and a viewer-oriented behavior hypergraph. Then, it employs a hypergraph convolution technique to learn the representations of viewers and live streaming channels, respectively, which are finally used to predict a viewer's preference for a certain live streaming channel. We analyzed viewers' multiple types of behaviors in live streaming channels and conducted empirical evaluation to investigate the effectiveness of VIBM-Hyper with two real-world datasets. The evaluation results demonstrate its superior performance in live streaming channel recommendation in comparison to the state-of-the-art methods.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114272"},"PeriodicalIF":6.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141702214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MEMF: Multi-entity multimodal fusion framework for sales prediction in live streaming commerce MEMF：用于直播流商业销售预测的多实体多模态融合框架

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-29 DOI: 10.1016/j.dss.2024.114277

Guang Xu , Ming Ren , Zhenhua Wang , Guozhi Li

{"title":"MEMF: Multi-entity multimodal fusion framework for sales prediction in live streaming commerce","authors":"Guang Xu , Ming Ren , Zhenhua Wang , Guozhi Li","doi":"10.1016/j.dss.2024.114277","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114277","url":null,"abstract":"<div><p>Live streaming commerce thrives with a rich tapestry of multimodal information that intertwines with various entities, including the anchor, the commodities, and the live streaming environment. Despite the wealth of data at hand, the synthesis and analysis of this information to predict sales remains a significant challenge. This study introduces a framework for multi-entity multimodal fusion, which is characterized by the effective synthesis of multimodal data and its prioritization of entity-level fusion, thereby providing a comprehensive feature representation for improving predictive performance. In addressing the multimodal data associated with a diverse range of products, our framework improves the Transformer architecture to initially capture the intra-product modal features and subsequently integrate the inter-product features. Data experiments are conducted on a real-world dataset from Taobao Live. The framework outperforms both traditional machine learning methods and state-of-the-art multimodal fusion methods, which affirms its value as a robust decision-support tool for sales prediction, enabling more accurate pre-event predictions and strategic planning. We also examine the impact of different types of information in accurate sales prediction. It is found that harnessing a comprehensive suite of data leads to optimal performance across all evaluation metrics. Commodity-related data is primary factor in determining the prediction accuracy, followed by video data and streaming room-related data, providing insights regarding the resource allocation for collecting and analyzing multimodal data from live streaming platforms.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114277"},"PeriodicalIF":6.7,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141543679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable AI for enhanced decision-making 可解释的人工智能促进决策

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-28 DOI: 10.1016/j.dss.2024.114276

Kristof Coussement , Mohammad Zoynul Abedin , Mathias Kraus , Sebastián Maldonado , Kazim Topuz

{"title":"Explainable AI for enhanced decision-making","authors":"Kristof Coussement , Mohammad Zoynul Abedin , Mathias Kraus , Sebastián Maldonado , Kazim Topuz","doi":"10.1016/j.dss.2024.114276","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114276","url":null,"abstract":"<div><p>This paper contextualizes explainable artificial intelligence (AI) for enhanced decision-making and serves as an editorial for the corresponding special issue. AI is defined as the development of computer systems that are able to perform tasks that normally require human intelligence by understanding, processing, and analyzing large amounts of data. AI has been a dominant domain for several decades in the information systems (IS) literature. To this end, we define explainable AI (XAI) as the process that allows one to understand how an AI system decides, predicts, and performs its operations. First, we contextualize its current role for improved business decision-making. Second, we discuss three underlying dimensions of XAI that serve as broader innovation grounds to make better and more informed decisions, i.e., data, method, and application. For each of the contributing papers in this special issue, we describe their major contributions to the field of XAI for decision making. In conclusion, this paper further presents a future research agenda for IS researchers in the XAI field.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114276"},"PeriodicalIF":6.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141543680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The faster or richer the response, the better performance? An empirical analysis of online healthcare platforms from a competitive perspective 响应越快或越丰富，性能就越好？从竞争角度对在线医疗保健平台进行实证分析

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-25 DOI: 10.1016/j.dss.2024.114274

Haoyu Ren , Liuan Wang , Junjie Wu

{"title":"The faster or richer the response, the better performance? An empirical analysis of online healthcare platforms from a competitive perspective","authors":"Haoyu Ren , Liuan Wang , Junjie Wu","doi":"10.1016/j.dss.2024.114274","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114274","url":null,"abstract":"<div><p>The emergence of online healthcare platforms has changed the competitive environment among physicians. However, little is known about how physicians can improve their performance in this new environment. Platforms also face challenges in comprehending the competitive mechanisms among physicians, which might hinder them from formulating strategic managerial decisions that foster sustained growth. In this light, we extract medical service-related information from physicians' response behavioral data on a prominent healthcare platform, and empirically investigate the factors affecting physicians' online performance from a competitive perspective as well as the gender differences in these effects. The results indicate that physicians' responses significantly impact their online performance, revealing a competitive relationship between physicians and their colleagues in the same department. Specifically, a fast response time and informative responses are positively correlated with the focal physician's performance, whereas colleagues' informative responses negatively impact the focal physician's performance, and this relationship is mediated by the focal physician's response informativeness. Nevertheless, there is no significant correlation between colleagues' response time and the focal physician's performance. The results also unveil that gender moderates the effect of response informativeness on the focal physician's performance. Specifically, colleagues' response informativeness has a more significant impact on male physicians' performance than on female physicians' performance, suggesting a greater propensity for competition among male physicians. Our findings could offer decision support for enhancing physician performance and healthcare platform management.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114274"},"PeriodicalIF":6.7,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141592931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How transparency affects algorithmic advice utilization: The mediating roles of trusting beliefs 透明度如何影响算法建议的使用：信任信念的中介作用

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-22 DOI: 10.1016/j.dss.2024.114273

Xianzhang Ning , Yaobin Lu , Weimo Li , Sumeet Gupta

{"title":"How transparency affects algorithmic advice utilization: The mediating roles of trusting beliefs","authors":"Xianzhang Ning , Yaobin Lu , Weimo Li , Sumeet Gupta","doi":"10.1016/j.dss.2024.114273","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114273","url":null,"abstract":"<div><p>Although algorithms are increasingly used to support professional tasks and routine decision-making, their opaque nature invites resistance and results in suboptimal use of their advice. Scholars argue for transparency to enhance the acceptability of algorithmic advice. However, current research is limited in understanding how improved transparency enhances the use of algorithmic advice, such as the differences among various aspects of transparency and the underlying mechanism. In this paper, we investigate whether and how different aspects of algorithmic transparency (performance, process, and purpose) enhance the use of algorithmic advice. Drawing on the knowledge-based trust perspective, we examine the mediating roles of trusting beliefs in the relationships between transparency and the use of algorithmic advice. Using the “judge-advisor system” paradigm, we conduct a 2 × 2 × 2 experiment to manipulate the three aspects of transparency and examine their effects on the use of algorithmic advice. We find that performance and process transparency promote the use of algorithmic advice. However, the effect of process transparency gets attenuated when purpose transparency is high. Purpose transparency is only useful when process transparency is low. We also find that while all three aspects of transparency facilitate different trusting beliefs, only competence belief significantly promotes the use of algorithmic advice. It also fully mediates the facilitating effects of performance and process transparency. This study contributes to the emerging research on algorithmic decision support by empirically investigating the effects of transparency on the use of algorithmic advice and identifying the underlying mechanism. The findings also provide practical guidance on how to promote the acceptance of algorithmic advice that is valuable to both individual users and practitioners.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114273"},"PeriodicalIF":6.7,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141482121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understand your shady neighborhood: An approach for detecting and investigating hacker communities 了解你的黑客社区检测和调查黑客社区的方法

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-21 DOI: 10.1016/j.dss.2024.114271

Dalyapraz Manatova , Charles DeVries , Sagar Samtani

{"title":"Understand your shady neighborhood: An approach for detecting and investigating hacker communities","authors":"Dalyapraz Manatova , Charles DeVries , Sagar Samtani","doi":"10.1016/j.dss.2024.114271","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114271","url":null,"abstract":"<div><p>Cyber threat intelligence (CTI) researchers strive to uncover collaborations and emerging techniques within hacker networks. This study proposes an empirical approach to detect communities within hacker forums for CTI purposes. Eighteen algorithms are systematically evaluated, including state-of-the-art and benchmark methods for identifying overlapping and disjoint groups. Using discussions from five prominent English hacker forums, a comparative analysis examines the influence of the algorithms’ theoretical foundations on community detection. Since ground truths are unattainable for such networks, the study utilizes a multi-metric strategy, incorporating modularity, coverage, performance, and a newly introduced quality measure, Triplet Hub Potential, which quantifies the presence of influential hubs. The findings reveal that while modularity optimization algorithms such as Leiden and Louvain deliver consistent results, neighbor-based expanding techniques tend to provide superior performance. In particular, the Expansion algorithm stood out by uncovering granular hierarchical community structures. The ability to investigate these intimacies is helpful for CTI researchers. Ultimately, we suggest an approach to investigate hacker forums using community detection methods and encourage the future development of algorithms tailored to expose nuances within hacker networks.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114271"},"PeriodicalIF":6.7,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141543681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An adaptive simulation based decision support approach to respond risk propagation in new product development projects 在新产品开发项目中应对风险传播的自适应模拟决策支持方法

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-06-16 DOI: 10.1016/j.dss.2024.114270

Shanshan Liu, Ronggui Ding, Lei Wang

引用次数: 0

Predicting digital product performance with team composition features derived from a graph network 利用图网络得出的团队组成特征预测数字产品性能

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-12 DOI: 10.1016/j.dss.2024.114266

Houping Xiao, Yusen Xia, Aaron Baird

{"title":"Predicting digital product performance with team composition features derived from a graph network","authors":"Houping Xiao, Yusen Xia, Aaron Baird","doi":"10.1016/j.dss.2024.114266","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114266","url":null,"abstract":"<div><p>This paper examines video games, a form of digital innovation, and seeks to predict a successful game based on the composition of game development team members. Team composition is measured with observable features generated from a graph network based on development team information derived from individual team member work on previous games. Features include network features, such as team member closeness, success percentile, and failure percentile, and non-network features, such as the number of games published prior by the studio. We propose a novel framework using these features to predict the chance of success for new games with an accuracy higher than 92%. Further, we investigate important features for prediction and provide model interpretability for practical implementations. We then build a decision support tool that allows video game producers, and associated stakeholders such as investors, to understand how the predictive model decides, predicts, and performs its recommendations. The findings have implications for those seeking to proactively impact digital product performance through graph network-generated features of team composition, where features are directly observable, as opposed to features that are more challenging to observe, such as personalities.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114266"},"PeriodicalIF":7.5,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0