Decision Support Systems最新文献_第5页

More than meets the eye: Feature concerns and suggestions in mobile XR app reviews 手机XR应用评论中的功能关注点和建议

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-19 DOI: 10.1016/j.dss.2025.114475

Nohel Zaman , David M. Goldberg , Zhilei Qiao , Alan S. Abrahams

{"title":"More than meets the eye: Feature concerns and suggestions in mobile XR app reviews","authors":"Nohel Zaman , David M. Goldberg , Zhilei Qiao , Alan S. Abrahams","doi":"10.1016/j.dss.2025.114475","DOIUrl":"10.1016/j.dss.2025.114475","url":null,"abstract":"<div><div>This study aims to address quality concerns in mobile Extended Reality (XR) apps by developing tools to classify user reviews from the Google Play Store. Our first major contribution is a holistic approach to coding thousands of reviews, offering a unified framework to assess feature concerns and feature suggestions, thereby enhancing the understanding of user expectations. We also introduce a novel toolset for extracting key terms related to these concerns and suggestions, facilitating rapid analysis and improvement of app functionalities. To validate our approach, we compare the performance of this automated coding method with sentiment analysis, deep learning-based BERT, and several large language models (LLMs). Additionally, our study extends the understanding of user satisfaction by analyzing quantitative indicators such as app ratings and review helpfulness, offering new perspectives on user perceptions of XR app quality. This research has discovered vital areas for feature improvement without implementing complex infrastructure and using advanced technical expertise, enabling app firms to better target their efforts in improving XR app experiences.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"195 ","pages":"Article 114475"},"PeriodicalIF":6.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098457","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

Integrating temporal association rules into intelligent prediction system for metabolic dysfunction-associated fatty liver disease 将时间关联规则集成到代谢功能障碍相关脂肪肝疾病智能预测系统中

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-13 DOI: 10.1016/j.dss.2025.114467

Zhuoqing Wu , Chonghui Guo , Jingfeng Chen , Suying Ding , Yunchao Zheng

{"title":"Integrating temporal association rules into intelligent prediction system for metabolic dysfunction-associated fatty liver disease","authors":"Zhuoqing Wu , Chonghui Guo , Jingfeng Chen , Suying Ding , Yunchao Zheng","doi":"10.1016/j.dss.2025.114467","DOIUrl":"10.1016/j.dss.2025.114467","url":null,"abstract":"<div><div>Healthcare big data provides trajectory data on chronic disease onset, progression, and outcomes, essential for understanding metabolic dysfunction-associated fatty liver disease (MAFLD) patient health dynamics. However, constructing explainable predictive models for MAFLD using longitudinal healthcare big data remains challenging due to its complexity. While several high-performance machine learning models have shown promise, their “black box” nature limits interpretability and trust among clinical healthcare professionals. Most studies also rely on cross-sectional data, which lacks the depth of longitudinal data, hindering accurate health status tracking. This paper proposes an intelligent MAFLD prediction system integrating temporal association rules (TARs) through a “human-in-the-loop” approach. By analyzing TARs that capture disease dynamics, the system incorporates high-quality domain knowledge into its predictive model. To enhance explainability, we use the SHapley Additive exPlanations framework alongside clinically significant TARs. The system’s effectiveness was validated on real-world data, showing improved MAFLD outcome prediction. Sensitivity analysis identified optimal TARs and robust model configurations. Finally, the online-deployed explainable prototype system demonstrates potential to boost trust and adoption among clinical healthcare professionals. Additionally, the system’s effectiveness and their willingness to use it were further evaluated through the “human-on-the-loop” method. These findings suggest the system could serve as a valuable tool for clinical applications and advance information systems design.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"195 ","pages":"Article 114467"},"PeriodicalIF":6.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084474","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

40 years of Decision Support Systems: A bibliometric analysis

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-08 DOI: 10.1016/j.dss.2025.114469

Li Guan, José M. Merigó, Ghassan Beydoun

{"title":"40 years of Decision Support Systems: A bibliometric analysis","authors":"Li Guan, José M. Merigó, Ghassan Beydoun","doi":"10.1016/j.dss.2025.114469","DOIUrl":"10.1016/j.dss.2025.114469","url":null,"abstract":"<div><div><em>Decision Support Systems</em> (DSS) is a leading international journal dedicated to decision support system research and practice, with the aim of exploring theoretical and technical advancements to facilitate enhanced decision making in industry, commerce, government, and other business settings. The journal published its first issue in 1985, and in 2025, celebrates its 40th anniversary. Motivated by this special event, this paper develops a comprehensive bibliometric analysis to present a lifetime overview of the development characteristics and leading trends of DSS journal between 1985 and 2023. By using the bibliographic data collected from the Scopus and Web of Science Core Collection databases, this study analyzes the publication and citation structure of the journal and investigates a wide range of issues including the most cited papers, the most cited documents by the journal's publications, the citing articles, the most productive and influential authors, institutions and countries/territories, and the most popular keywords and topics. Moreover, this work also graphically maps the bibliographic material by using the visualization of similarities (VOS) viewer software. In the graphical analysis, several bibliometric techniques in terms of co-citation, bibliographic coupling, and co-occurrence of author keywords are adopted. The results accentuate the significant growth and impact of DSS journal throughout its lifetime. It is expected that the journal will continue to grow its international reputation and disseminate knowledge in decision support, information systems, and business area, providing an efficient mechanism for researchers around the world to keep abreast with advances in the scientific community.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114469"},"PeriodicalIF":6.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943493","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

Unlocking big data success in the AI-driven era: Toward a unified theory for intelligent decision support

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-08 DOI: 10.1016/j.dss.2025.114468

Xi Zhao , Hua Dai , Tao “Eric” Hu , Hsing K. Cheng , Ping Zhang

引用次数: 0

Product return prediction in live streaming e-commerce with cross-modal contrastive transformer 基于跨模态对比变压器的电商直播产品退货预测

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-05 DOI: 10.1016/j.dss.2025.114470

Wen Zhang , Rui Xie , Pei Quan , Zhenzhong Ma

{"title":"Product return prediction in live streaming e-commerce with cross-modal contrastive transformer","authors":"Wen Zhang , Rui Xie , Pei Quan , Zhenzhong Ma","doi":"10.1016/j.dss.2025.114470","DOIUrl":"10.1016/j.dss.2025.114470","url":null,"abstract":"<div><div>The live-streaming e-commerce industry is suffering heavy economic losses due to the high product return rate, which leads to rising logistics costs, greater inventory pressure, and unsatisfactory consumer experiences. Accurate product return prediction is highly desirable for the vendors to optimize their business operations in advance to reduce return-related costs. This paper proposes a novel approach, called Contraformer (Contrastive transformer), to predict product returns in live streaming e-commerce by leveraging fine-grained streamer behavior features extracted from three modalities (i.e., visual, acoustic, and language). The primary contribution lies in that we adopt Transformer with the encoder-decoder architecture with a novel class-supervised contrastive learning (CSCL) to fuse streamer behavior for multimodal representation alignment and inter-modal interaction characterization. By using a real-world dataset with 2584 product streamers and 864 items collected from Tiktok China live streaming platform, we demonstrate that the proposed Contrasformer approach outperforms the baseline methods in predicting product return rate with a 25 % reduction in terms of mean absolute error. This study offers great managerial implications for vendors to manage their practice in live streaming commerce.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114470"},"PeriodicalIF":6.7,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922198","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

Sponsored search and organic listings in online food delivery platforms: The role of keyword categories 在线外卖平台的赞助搜索和自然列表：关键词类别的作用

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-05-05 DOI: 10.1016/j.dss.2025.114472

Guo Chen, Siyu Zhang, Luning Liu, Yuqiang Feng

{"title":"Sponsored search and organic listings in online food delivery platforms: The role of keyword categories","authors":"Guo Chen, Siyu Zhang, Luning Liu, Yuqiang Feng","doi":"10.1016/j.dss.2025.114472","DOIUrl":"10.1016/j.dss.2025.114472","url":null,"abstract":"<div><div>Online sellers appear in search results through sponsored listings (paid advertising links) or organic listings (unpaid links) based on their associations with keywords in consumer search queries. This approach allows sellers to deduce consumers' purchasing preferences, thereby ultimately increasing their economic payoffs. Therefore, selecting appropriate keywords is critical for online sellers. Although previous research has explored the effectiveness of keyword categories in traditional e-commerce settings (e.g., online retail), there are limited studies within the quick e-commerce context (e.g., online food delivery). Moreover, the extent to which keyword categories influence the spillover effects between sponsored and organic listings remains unclear. This study leverages a large panel dataset from an online food delivery platform to analyze the impact of keyword categories on the performance of both sponsored and organic listings. We also examine how keyword categories moderate the spillover effects of sponsored listings on competitors' performance in organic listings. The results reveal that dish keywords achieve the highest click-through rate (CTR), whereas cuisine keywords lead to the lowest conversion rate (CVR). Furthermore, sponsored listings reduce competitors' CTR in organic listings, although this adverse effect is not significant for seller keywords. However, sponsored listings increase the CVR of competitors in organic listings, and this positive spillover effect is exclusively limited to seller keywords. These findings have direct implications for sellers in online food delivery markets in terms of effective keyword selection and for online food delivery platforms in terms of informing more profitable keyword sets.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114472"},"PeriodicalIF":6.7,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929607","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

Using large multimodal models to predict outfit compatibility 使用大型多模态模型预测服装兼容性

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-26 DOI: 10.1016/j.dss.2025.114457

Chia-Ling Chang , Yen-Liang Chen , Dao-Xuan Jiang

{"title":"Using large multimodal models to predict outfit compatibility","authors":"Chia-Ling Chang , Yen-Liang Chen , Dao-Xuan Jiang","doi":"10.1016/j.dss.2025.114457","DOIUrl":"10.1016/j.dss.2025.114457","url":null,"abstract":"<div><div>Outfit coordination is a direct way for people to express themselves. However, judging the compatibility between tops and bottoms requires considering multiple factors such as color and style. This process is time-consuming and prone to errors. In recent years, the development of large language models and large multi-modal models has transformed many application fields. This study aims to explore how to leverage these models to achieve breakthroughs in fashion outfit recommendations.</div><div>This research combines the keyword response text from the large language model Gemini in the Vision Question Answering (VQA) task with the deep feature fusion technology of the large multi-modal model Beit3. By providing only image data of the clothing, users can evaluate the compatibility of tops and bottoms, making the process more convenient. Our proposed model, the Large Multi-modality Language Model for Outfit Recommendation (LMLMO), outperforms previously proposed models on the FashionVC and Evaluation3 datasets. Moreover, experimental results show that different types of keyword responses have varying impacts on the model, offering new directions and insights for future research.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114457"},"PeriodicalIF":6.7,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898565","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

Governmental enforcement against piracy on media platforms 政府对媒体平台盗版行为的执法

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-23 DOI: 10.1016/j.dss.2025.114458

Meiqian Li , Guowei Liu , Guofang Nan , Yinliang (Ricky) Tan

{"title":"Governmental enforcement against piracy on media platforms","authors":"Meiqian Li , Guowei Liu , Guofang Nan , Yinliang (Ricky) Tan","doi":"10.1016/j.dss.2025.114458","DOIUrl":"10.1016/j.dss.2025.114458","url":null,"abstract":"<div><div>The rapid growth of illegal websites hosting pirated content has significantly reduced demand for legitimate media platforms, causing substantial economic losses to the media industry. Governmental departments must take measures to combat these illegal websites and restrict access to pirated content. This paper examines governmental enforcement against piracy on media platforms that offer consumer services under three revenue models: subscription, ad-based, and mixed. Our analysis yields the following key findings with critical managerial insights. First, under the subscription and mixed models, the optimal governmental enforcement levels lie within the piracy threat region where piracy exists in the market, but there is no demand for it, whereas under the ad-based model, the optimal governmental enforcement can allow the piracy to have a demand and even if no enforcement occurs. Second, optimal governmental enforcement exhibits a non-monotonic effect with respect to the quality of pirated content under each revenue model, which implies that the government does not necessarily strengthen its enforcement facing a higher quality of pirated content. Finally, the optimal governmental enforcement decreases as the consumer nuisance cost for advertisement increases under the ad-based model, whereas it presents a non-monotonic change under the mixed model. We further extend our main model to a duopoly platform setting and a situation of decreasing marginal efficiency of enforcement. The results demonstrate that the insights derived from our main model remain hold. These findings suggest that social planners should consider media platforms' revenue models and market conditions when formulating enforcement policies against piracy.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114458"},"PeriodicalIF":6.7,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922199","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

Metaverse opportunities and challenges: A research agenda and editorial on the special issue on the evolution of Metaverse platforms (part 2) 元世界的机遇和挑战：关于元世界平台发展的专题研究议程和社论（第2部分）

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-21 DOI: 10.1016/j.dss.2025.114456

Arpan Kumar Kar , Patrick Mikalef , Rohit Nishant , Xin (Robert) Luo , Manish Gupta

{"title":"Metaverse opportunities and challenges: A research agenda and editorial on the special issue on the evolution of Metaverse platforms (part 2)","authors":"Arpan Kumar Kar , Patrick Mikalef , Rohit Nishant , Xin (Robert) Luo , Manish Gupta","doi":"10.1016/j.dss.2025.114456","DOIUrl":"10.1016/j.dss.2025.114456","url":null,"abstract":"<div><div>The growing adoption of Metaverse offers an exciting opportunity to connect stakeholders on these technology platforms across industries. These platforms offer capabilities to interact, engage, transact and create different user experiences and functional values for users onboarded. The research on Metaverse is still at a nascent stage and our editorial provides research directions in Metaverse as a unique IT artefact. The current editorial is the second part of the special issue on Metaverse and introduces 8 new articles. We further synthesize all the empirical evidences in Metaverse in this special issue. Subsequently we propose a conceptual layered framework for future researchers to extend when they work on Metaverse platforms. Here the bottom layer starts with the technology artifacts and gradually showcase techno-functional features, before guiding the users towards the adoption and appropriation of Metaverse platforms which further shapes impacts on individuals, organizations and societies.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"194 ","pages":"Article 114456"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895697","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

Leveraging meta-path and co-attention to model consumer preference stability in fashion recommendations 利用元路径和共同关注来模拟时尚推荐中的消费者偏好稳定性

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-20 DOI: 10.1016/j.dss.2025.114455

Ya-Han Hu , Ting-Hsuan Liu , Kuanchin Chen , Fan-Chi Yeh

引用次数: 0