Decision Support Systems最新文献

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

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

Augmenting micro-moment recommendations with group and serendipity perspectives 通过群体和意外发现的视角增强微时刻推荐

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-17 DOI: 10.1016/j.dss.2025.114454

Yi-Ling Lin , Yu-Xiang Zheng , Yi-Cheng Ku

{"title":"Augmenting micro-moment recommendations with group and serendipity perspectives","authors":"Yi-Ling Lin , Yu-Xiang Zheng , Yi-Cheng Ku","doi":"10.1016/j.dss.2025.114454","DOIUrl":"10.1016/j.dss.2025.114454","url":null,"abstract":"<div><div>With the pervasive integration of internet and mobile services, mobile devices have become integral to daily life. The concept of micro-moments, characterized by immediate intent within specific contexts, underscores the importance of timely and relevant information. Traditional RS, though effective in mitigating information overload, often fall short in addressing the dynamic and context-specific needs inherent in micromoments. This study investigates the enhancement of MMRS by incorporating group dynamics and serendipity, aiming to improve recommendation quality and user satisfaction. The research explores two primary objectives: the feasibility of a groupaugmented MMRS and the integration of serendipity into MMRS. Utilizing a design science approach, we conducted a two-phase iterative design involving preliminary studies and field experiments. The results indicate that integrating group recommendations based on social relationships and serendipity mechanisms significantly enhances user satisfaction and behavioral intentions. Close groups exhibited higher satisfaction and engagement compared to acquainted groups, emphasizing the importance of social relationships in recommendation strategies. Moreover, the serendipity mechanism, characterized by relevance, novelty, and unexpectedness, successfully mitigates overspecialization, enriching user experience by introducing unexpected yet relevant recommendations. Our findings contribute to the theoretical understanding of MMRS by demonstrating the viability of combining group dynamics and serendipity to cater to the evolving needs of mobile users in micro-moments. Practically, the study provides valuable insights for developing RS that are adaptive, context-aware, and capable of delivering engaging and satisfying user experiences. Future research should expand on diverse social relationships and longterm evaluations to refine the application of these mechanisms in various domains.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114454"},"PeriodicalIF":6.7,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854753","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

High efficiency or easy troubleshooting? Human use of autonomous Mobile healthcare robots 高效还是易于故障排除？人类使用自主移动医疗机器人

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-15 DOI: 10.1016/j.dss.2025.114453

Tzu-Ling Huang , Gen-Yih Liao , Alan R. Dennis , Ching-I Teng

{"title":"High efficiency or easy troubleshooting? Human use of autonomous Mobile healthcare robots","authors":"Tzu-Ling Huang , Gen-Yih Liao , Alan R. Dennis , Ching-I Teng","doi":"10.1016/j.dss.2025.114453","DOIUrl":"10.1016/j.dss.2025.114453","url":null,"abstract":"<div><div>Among modern information technologies, robots help reduce the effort employees expend on tasks that are repetitive and physically demanding. When helping employees, robots may be required to display enhanced efficiency, but such a design can also increase employees' effort required for operational troubleshooting. It is not yet known whether effort saving (i.e., increasing nurses' time and energy saved) or reduced troubleshooting effort (i.e., reducing nurses' time and energy costs) is more important for enhancing users' perception that the robot is performing optimally (user-perceived robot performance) and positive workplace outcomes. This hinders robot providers from making optimal decisions on robot design. In a healthcare context, nurses comprise the largest workforce and thus we examined autonomous mobile robots that help nurses carry heavy equipment and materials to and from operating rooms to meet the demand of surgical operations. Hence, this study examined the relative influence of increased effort saving versus reduced troubleshooting effort on perceived robot performance, patient care, and nurse health. We collected responses from 331 operating room nurses through two waves of surveys. Compared with reduced troubleshooting effort, effort saving effectively increased nurse-perceived robot performance, patient care and nurse health, from 39 % to 77 %. Nurses' greater professional experience reduced the negative influence of troubleshooting effort on perceived robot performance. These findings showed that designing information technologies for high efficiency is more important than designing for ease of troubleshooting. This research contributes to decision-making of robot makers and hospitals by indicating that the effects of benefits and costs may depend on the features of users.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114453"},"PeriodicalIF":6.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143842455","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

Enhancing return forecasting using LSTM with agent-based synthetic data 利用基于智能体的合成数据增强LSTM的收益预测

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-14 DOI: 10.1016/j.dss.2025.114452

Lijian Wei , Sihang Chen , Junqin Lin , Lei Shi

{"title":"Enhancing return forecasting using LSTM with agent-based synthetic data","authors":"Lijian Wei , Sihang Chen , Junqin Lin , Lei Shi","doi":"10.1016/j.dss.2025.114452","DOIUrl":"10.1016/j.dss.2025.114452","url":null,"abstract":"<div><div>Financial markets, as complex adaptive systems, are characterized by historical data limitations, inherent evolution and non-stationarity, which challenge the effectiveness of deep learning models such as Long Short-Term Memory (LSTM). We address these challenges by generating synthetic data using Agent-Based Modeling (ABM) to simulate complex market conditions through “what-if” scenarios. Our method comprises three steps: (i) pre-training the LSTM model on historical data, (ii) generating synthetic data with the ABM using “what-if” scenarios, and (iii) fine-tuning the pre-trained LSTM with ABM-generated synthetic data. The results show that ABM-generated data significantly improve model performance across various statistical and economic metrics and are robust to diverse market environments, model architectures, and data frequencies. Our primary contribution is modeling the properties of complex adaptive systems with ABM-generated data, highlighting the need for new complex scenarios to better simulate future market conditions that are distinct from historical trends. We explore the potential of ABM in generating unique synthetic data, offering a framework to address the challenges imposed by the complex adaptive system properties of financial markets, particularly, improving the discriminative ability of forecasting models such as the LSTM model.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114452"},"PeriodicalIF":6.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834655","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

Can comments and dialogues make sense? The effect of two-way interactions on sales and followers in live streaming commerce 评论和对话有意义吗？直播商业中双向互动对销售和粉丝的影响

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-05 DOI: 10.1016/j.dss.2025.114451

Xiaoping Lang , Sheng Lin , Xiangyang Ma , Tieshan Li

{"title":"Can comments and dialogues make sense? The effect of two-way interactions on sales and followers in live streaming commerce","authors":"Xiaoping Lang , Sheng Lin , Xiangyang Ma , Tieshan Li","doi":"10.1016/j.dss.2025.114451","DOIUrl":"10.1016/j.dss.2025.114451","url":null,"abstract":"<div><div>This research employs interaction ritual model to explore the two-way interaction between streamers and viewers on a live streaming commerce platform. To be specific, the study investigates the impact of viewers' real-time comments and streamer's dialogue on product sales and follower growth, using minute-level data for detailed analysis. The results show that real-time comments exhibit a nonlinear inverted U-shaped relationship with product sales and increment in followers. Such relationship indicates that the “overloaded comments” during live streams could cause a problem on live streaming commerce platforms. In addition, we find that streamer's dialogue has a positive effect on product sales and can mitigate the inverted U-shaped relationship between real-time comments and product sales. Furthermore, we identify that streamer's dialogue has a delayed effect on product sales, with sales typically occurring 2.5 to 5 min after the dialogue ends. The findings provide valuable guidance for optimizing the management of live streaming commerce platforms.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114451"},"PeriodicalIF":6.7,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800434","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

Remote work in the metaverse: The impact of gamification and online social connectedness on job satisfaction 虚拟世界中的远程工作：游戏化和在线社会联系对工作满意度的影响

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-04 DOI: 10.1016/j.dss.2025.114447

Khadija Ali Vakeel , Saurav Chakraborty , Lamont Black

{"title":"Remote work in the metaverse: The impact of gamification and online social connectedness on job satisfaction","authors":"Khadija Ali Vakeel , Saurav Chakraborty , Lamont Black","doi":"10.1016/j.dss.2025.114447","DOIUrl":"10.1016/j.dss.2025.114447","url":null,"abstract":"<div><div>This study explores the potential of the metaverse in enhancing job satisfaction for remote employees. With the increasing shift towards remote work, firms are investing more in the metaverse to create dynamic and immersive digital environments. Drawing upon media richness theory, we investigate the roles of gamification and online social connectedness within the metaverse, which are crucial factors shaping employee job satisfaction. Survey results show that remote employees perceive higher gamification in the metaverse but have similar online social connectedness to video conferencing platforms. Contrary to linear assumptions, polynomial regression analysis reveals an intriguing S-shaped relationship between gamification and job satisfaction in the metaverse, highlighting an optimal threshold beyond which excessive gamification in the metaverse may diminish job satisfaction. Additionally, online social connectedness in the metaverse significantly strengthens job satisfaction. This study contributes to theoretical and practical knowledge by expanding the application of the metaverse to remote work. Our findings provide valuable guidance for firms navigating the evolving landscape of remote work and technology adoption, paving the way for more engaging and satisfying remote work experiences.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114447"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143790851","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

Unravelling the effects of two inconsistencies on online review helpfulness: Evidence from TripAdvisor 揭示两种不一致对在线评论有用性的影响：来自TripAdvisor的证据

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-04-04 DOI: 10.1016/j.dss.2025.114450

Dujuan Wang , Qianyang Xia , Yi Feng , T.C.E. Cheng

{"title":"Unravelling the effects of two inconsistencies on online review helpfulness: Evidence from TripAdvisor","authors":"Dujuan Wang , Qianyang Xia , Yi Feng , T.C.E. Cheng","doi":"10.1016/j.dss.2025.114450","DOIUrl":"10.1016/j.dss.2025.114450","url":null,"abstract":"<div><div>Facing the challenge of information overload, some travel websites have introduced systems for travelers to vote on helpful reviews, prompting researchers to focus on the determinants of review helpfulness. While evaluations from multiple reviews may provide travelers with more perspectives, inconsistent information within the reviews may cause confusion. Studies exploring the effects of multiple inconsistencies on review helpfulness are relatively rare. Grounded in the heuristic-systematic model, we explore the relationships between systematic cues, i.e., review and rating inconsistencies, and review helpfulness. We also investigate how reviewer expertise and hotel rank moderate these inconsistency-helpfulness links, serving as heuristic cues. Applied to a real-world hotel dataset collected from TripAdvisor, our findings show that review inconsistency negatively influences review helpfulness, while rating inconsistency positively affects it. Furthermore, we find that reviewer expertise negatively moderates the review and rating inconsistency-helpfulness links, while hotels that rank low positively moderate both links. These findings offer both theoretical insights for research and practical implications for consumers, reviewers, and platform managers.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114450"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821319","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

Dynamic model selection in enterprise forecasting systems using sequence modeling 序列建模在企业预测系统中的动态模型选择

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-03-29 DOI: 10.1016/j.dss.2025.114439

Jinhang Jiang , Kiran Kumar Bandeli , Karthik Srinivasan

{"title":"Dynamic model selection in enterprise forecasting systems using sequence modeling","authors":"Jinhang Jiang , Kiran Kumar Bandeli , Karthik Srinivasan","doi":"10.1016/j.dss.2025.114439","DOIUrl":"10.1016/j.dss.2025.114439","url":null,"abstract":"<div><div>Enterprise forecasting systems often involve modeling a large scale of heterogeneous time series using a pool of candidate algorithms, such as in the case of simultaneous sales forecasts of thousands of stock-keeping units. In such cases, it can be advantageous to automatically monitor and replace algorithms for each time series. We introduce TimeSpeaks, a framework that adapts sequence modeling in natural language processing to the problem of dynamic model selection in enterprise forecasting. We instantiate our framework using sequential (BiLSTM) and transformer-based (TimeXer) deep learning models to learn the temporal dependencies between candidate algorithms. We compare the performance of our framework with state-of-the-art forecasting models using two public benchmarking datasets. We further demonstrate its practical application on two retail case studies, while comparing them to alternative model selection scenarios. TimeSpeaks has superior predictive performance and scalability across different scenarios and datasets. Its ability to adapt to evolving data patterns and its minimal reliance on exogenous information make TimeSpeaks a suitable framework for large-scale enterprise forecasting applications.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"193 ","pages":"Article 114439"},"PeriodicalIF":6.7,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748335","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