Decision Support Systems最新文献_第5页

Incentive hierarchies intensify competition for attention: A study of online reviews 激励等级加剧了注意力竞争：在线评论研究

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-30 DOI: 10.1016/j.dss.2024.114293

Baojun Zhang , Zili Zhang , Kee-Hung Lai , Ziqiong Zhang

{"title":"Incentive hierarchies intensify competition for attention: A study of online reviews","authors":"Baojun Zhang , Zili Zhang , Kee-Hung Lai , Ziqiong Zhang","doi":"10.1016/j.dss.2024.114293","DOIUrl":"10.1016/j.dss.2024.114293","url":null,"abstract":"<div><p>While many online platforms use incentive hierarchies to stimulate consumers to generate more online reviews, the extent to which these hierarchies influence reviewer behavior is not fully understood. This study, drawing on image motivation theory and consumer attention theory, takes a novel approach to investigate whether reviewers strategically adjust their review behavior after reaching higher ranks in a hierarchy. We use data from rank change timestamps on platforms to accurately identify reviewers' ranks when posting reviews and then employ a quasi-natural experimental design for causal inference. Additionally, we use Fisher's permutation test to explore the different effects at various ranks. The empirical results reveal that reviewers tend to increase their review length and insert more pictures into their reviews after they reach higher ranks. Reviewers at lower ranks tend to submit more extreme ratings upon rank advancement, whereas their higher-ranking counterparts do not demonstrate significant change. Unlike ratings, reviewers tend to consistently increase the sentiment intensity of their expressions in text after reaching higher ranks. Furthermore, our findings indicate that the magnitude of changes in reviewing behavior only shows an increasing trend in the early stages of rank progression. These insights contribute to a better understanding of the efficacy of incentive hierarchies and offer practical implications for decision-making by platform managers.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"185 ","pages":"Article 114293"},"PeriodicalIF":6.7,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947987","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

Guiding attention in flow-based conceptual models through consistent flow and pattern visibility 通过一致的流程和模式可见性，在基于流程的概念模型中引导注意力

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-28 DOI: 10.1016/j.dss.2024.114292

Kathrin Figl , Pnina Soffer , Barbara Weber

{"title":"Guiding attention in flow-based conceptual models through consistent flow and pattern visibility","authors":"Kathrin Figl , Pnina Soffer , Barbara Weber","doi":"10.1016/j.dss.2024.114292","DOIUrl":"10.1016/j.dss.2024.114292","url":null,"abstract":"<div><p>A critical part of flow-based conceptual modeling, such as process modeling, is visualizing the logical and temporal sequence in which activities in a process should be completed. While there are established standards and recommendations, there is limited empirical research examining the influence of process model layout on model comprehension. To address this research gap, we conducted a controlled eye-tracking experiment with 70 participants comparing different layouts. The experimental results confirm that the visibility of control flow patterns is critical for assisting users with visual processing, particularly attentional allocation, when comprehending process models for both local comprehension tasks and tasks requiring cognitive integration of model components. In models with more directional changes, users’ visual attention is more drawn to irrelevant regions, but comprehension is less affected as long as patterns remain visible. Our findings not only elucidate how cognitive fit between a visual representation and a task can manifest itself and the perceptual benefits it brings, but they can also guide the automated layout of models in tools and complement practical process modeling guidelines.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"185 ","pages":"Article 114292"},"PeriodicalIF":6.7,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167923624001258/pdfft?md5=2baf9307632a49e6559b80fd25878063&pid=1-s2.0-S0167923624001258-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141842842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bridging realities into organizations through innovation and productivity: Exploring the intersection of artificial intelligence, internet of things, and big data analytics in the metaverse environment using a multi-method approach 通过创新和生产力将现实与组织连接起来：使用多种方法探索元环境中人工智能、物联网和大数据分析的交叉点

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-26 DOI: 10.1016/j.dss.2024.114290

Ashutosh Samadhiya , Rohit Agrawal , Anil Kumar , Sunil Luthra

{"title":"Bridging realities into organizations through innovation and productivity: Exploring the intersection of artificial intelligence, internet of things, and big data analytics in the metaverse environment using a multi-method approach","authors":"Ashutosh Samadhiya , Rohit Agrawal , Anil Kumar , Sunil Luthra","doi":"10.1016/j.dss.2024.114290","DOIUrl":"10.1016/j.dss.2024.114290","url":null,"abstract":"<div><p>This study investigates how organizations may increase innovation and productivity through the Metaverse environment efficacy (MVEE), Artificial intelligence usage (AIU), Internet of Things usage (IoTU), and Big Data Analytics usage (BDAU). The study gathers responses from the gaming, information technology, and entertainment industries, using a multi-method involving Partial Least Squares Structural Equation Modeling, Fuzzy-set Qualitative Comparative Analysis, and Artificial Neural Networks to investigate how these technologies might be used to improve the linking of disparate realities in a business context. The use of AI in personalized and decision-support applications, IoT for real-time data collecting, and BDAU for an insights-driven strategy all combine to create a dynamic MVEE ecosystem. The research also delves into theoretical implications concerning the viability of using the MVEE to boost innovation and productivity. This research identifies the applications of using AI, IoT, and BDA to drive organizational performance in terms of innovation and productivity. Also, the research lays out the role of AI, IoT, and BDA in creating a dynamic metaverse ecosystem.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"185 ","pages":"Article 114290"},"PeriodicalIF":6.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167923624001234/pdfft?md5=358c5d38e7c9ef28ff47eabad293513e&pid=1-s2.0-S0167923624001234-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141840216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The value of data, machine learning, and deep learning in restaurant demand forecasting: Insights and lessons learned from a large restaurant chain 数据、机器学习和深度学习在餐饮需求预测中的价值：一家大型连锁餐厅的启示和经验教训

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-23 DOI: 10.1016/j.dss.2024.114291

Bongsug (Kevin) Chae , Chwen Sheu , Eunhye Olivia Park

{"title":"The value of data, machine learning, and deep learning in restaurant demand forecasting: Insights and lessons learned from a large restaurant chain","authors":"Bongsug (Kevin) Chae , Chwen Sheu , Eunhye Olivia Park","doi":"10.1016/j.dss.2024.114291","DOIUrl":"10.1016/j.dss.2024.114291","url":null,"abstract":"<div><p>The restaurant industry has been slow to adopt analytics for the supply chain, operations, and demand forecasting, with limited research on this sector. The COVID-19 pandemic's significant impact on the restaurant industry, one of the hardest-hit sectors, has underscored the need for digital technologies and advanced analytics for managing supply chains and making operational decisions. This paper presents a collaborative study with one of the largest restaurant chains in the United States, highlighting the value of advanced data analytics in forecasting restaurant demand. The study offers insights into the benefit of integrating external data, including macroeconomic and pandemic-related factors, into demand forecasting. It explores traditional machine learning algorithms and state-of-the-art deep learning architectures, evaluating their effectiveness in the context of the restaurant industry. The paper further discusses the implications of utilizing advanced forecasting models, providing valuable insights for the restaurant industry in the face of supply chain disruptions and pandemics.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114291"},"PeriodicalIF":6.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141844336","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

From whales to minnows: The impact of crypto-reward fairness on user engagement in social media 从鲸鱼到小鱼：加密奖励公平性对社交媒体用户参与度的影响

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-18 DOI: 10.1016/j.dss.2024.114289

Woojin Yang , Yeongin Kim , Tae Hun Kim , Chul Ho Lee , Yasin Ceran

引用次数: 0

The strength of weak ties and fake news believability 弱联系的强度与假新闻的可信度

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2024-07-10 DOI: 10.1016/j.dss.2024.114275

Babajide Osatuyi , Alan R. Dennis

{"title":"The strength of weak ties and fake news believability","authors":"Babajide Osatuyi , Alan R. Dennis","doi":"10.1016/j.dss.2024.114275","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114275","url":null,"abstract":"<div><p>Are we more likely to believe a social media news story shared by someone with whom we have a strong or weak tie? We tend to trust close ties more than weak ties, but weak ties are sources of new information more often than strong ones. We conducted an online experiment to examine the effect of tie strength (strong ties vs. weak ties) on the decision to believe or not believe fake news stories. Participants perceived false stories from weak ties to be more believable than false stories from strong ties (after controlling for the trustworthiness of the sharer). We found that a sharer's perceived ability to share reliable information plays a significant role in individuals' decision to believe news stories on social media, regardless of whether the source is a strong or weak tie. Interestingly, a sharer's perceived integrity was found to be important only when the information came from weak ties, while a sharer's perceived benevolence was not important for either weak or strong ties. These findings show that the perceived integrity of the sharer is a key factor in the decision to believe stories from weak ties, more so than from strong ties. Furthermore, a sharer's perceived ability to share reliable information is less critical when weak ties share true stories. The impact of weak ties does not stem from the novelty of their information, as we used identical headlines across both study groups. Thus, while the strength of weak ties effect is present in this context, the underlying theoretical mechanism differs from the novelty of information traditionally observed in other settings.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"184 ","pages":"Article 114275"},"PeriodicalIF":6.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141606538","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

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