Decision Support Systems最新文献

Exploring the impact of free live-streamed medical consultation on patient engagement and patient satisfaction in the multistage online consultation process: A quasi-experimental design

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-12 DOI: 10.1016/j.dss.2025.114422

Haochen Song , Xitong Guo , Tianshi Wu

{"title":"Exploring the impact of free live-streamed medical consultation on patient engagement and patient satisfaction in the multistage online consultation process: A quasi-experimental design","authors":"Haochen Song , Xitong Guo , Tianshi Wu","doi":"10.1016/j.dss.2025.114422","DOIUrl":"10.1016/j.dss.2025.114422","url":null,"abstract":"<div><div>In recent years, many online healthcare communities (OHCs) in China introduced the feature of free live-streamed medical consultations (FLSMC), which allows patients to communicate with physicians and have an interactive consultation for free through live streaming. Despite the rapid growth of FLSMC, little is known about whether FLSMC can bring benefits to patients when they have online consultation needs in the future. Drawing on signaling theory, this study examines the impact of FLSMC on patient engagement and patient satisfaction in the multistage online consultation process. We further explore the moderating effects of physician's owned and earned signals in the pre-consultation stage by integrating social capital theory with signaling theory. We collect a panel data set of 16,151 physicians from a leading OHC in China. Based on the DID method, a quasi-experimental design, and the instrumental variable method, we demonstrate that FLSMC has a positive effect on patient choice, patient messaging, and patient satisfaction. In addition, we find that the physician's title and online rating can positively moderate the effects of FLSMC on patient choice. This study not only sheds light on the literature on online healthcare by identifying the role of signals in the context of FLSMC, but also provides decision support for patients, physicians, and OHC managers.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114422"},"PeriodicalIF":6.7,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429544","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

DECEN: A deep learning model enhanced by depressive emotions for depression detection from social media content

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-10 DOI: 10.1016/j.dss.2025.114421

Zhijun Yan , Fei Peng , Dongsong Zhang

{"title":"DECEN: A deep learning model enhanced by depressive emotions for depression detection from social media content","authors":"Zhijun Yan , Fei Peng , Dongsong Zhang","doi":"10.1016/j.dss.2025.114421","DOIUrl":"10.1016/j.dss.2025.114421","url":null,"abstract":"<div><div>Depression is a serious and recurrent mental illness that significantly affects an individual's life and the society as a whole. Automatic detection of depression is crucial for early intervention and minimizing negative consequences. Existing studies on building deep learning models for automated depression detection have mainly used post-level emotion polarity (i.e., positive and negative emotions) and word embeddings as predictive features. Few have considered depressive emotions (e.g., anhedonia) expressed in those posts, despite that depressive emotions are essential to clinical depression diagnosis. Moreover, existing approaches for depression detection often ignore the relationship between emotions and their context. This study proposes a Depressive Emotion-Context Enhanced Network (DECEN) that consists of a pre-trained depressive emotion recognition module and an emotion-context enhanced representation module to address those limitations. DECEN first integrates semantic and syntactic structure representations of textual content of social media posts to identify depressive emotions conveyed through terms either explicitly or implicitly, rather than general emotion words. Furthermore, we propose an emotion-context enhanced representation method to enhance the role of the context of depressive emotions in depression detection. The evaluation using real social media data demonstrates that DECEN outperforms the state-of-the-art models in depression detection. The results of an ablation experiment also reveal that the proposed depressive emotion recognition and emotion-context enhanced representation modules, the two novel design artifacts, improve model performance. This study contributes to depression diagnostic decisions by introducing a novel method and providing new technical and practical insights for detecting depression from social media content.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114421"},"PeriodicalIF":6.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395755","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

Is seeing the same as doing? An evaluation of vicarious experiences in the metaverse

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-06 DOI: 10.1016/j.dss.2025.114419

Caleb Krieger , Andy Luse , Ghazal Abdolhossein Khani , Rathindra Sarathy

引用次数: 0

A deep learning–based method to predict the length of stay for patients with traumatic fall injuries in support of physicians' clinical decisions and patient management

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-03 DOI: 10.1016/j.dss.2025.114411

Jiaxuan Peng , Da Xu , Paul Jen-Hwa Hu , Jessica Qiuhua Sheng , Ting-Shuo Huang

{"title":"A deep learning–based method to predict the length of stay for patients with traumatic fall injuries in support of physicians' clinical decisions and patient management","authors":"Jiaxuan Peng , Da Xu , Paul Jen-Hwa Hu , Jessica Qiuhua Sheng , Ting-Shuo Huang","doi":"10.1016/j.dss.2025.114411","DOIUrl":"10.1016/j.dss.2025.114411","url":null,"abstract":"<div><div>Accurate estimates of the length of stay (LOS) for patients who suffer traumatic fall injuries are crucial to inform physicians' clinical decisions and patient management. They also have important implications for resource utilization efficiency and cost containment efforts by healthcare organizations. Effective predictions should consider essential relationships across different variables pertaining to patient demographics, clinical history, injury severity, and physiology. A proposed deep learning–based method incorporates these relationships and can predict LOS more accurately, as demonstrated by a comparative evaluation involving 3722 patients who suffered traumatic fall injuries between 2011 and 2017. The results show the superior performance of the proposed method, relative to eleven prevalent methods that represent different analytics approaches. Our method demonstrates superior predictive performance, as manifested by the highest F-measure values and area under the curve. It is particularly efficacious for patients likely in need of longer LOS, which is relatively more important to physicians and healthcare organizations. This study underscores the value of incorporating important relationships and interactions among distinct patient variables to estimate LOS, with a particular emphasis on the inter-disease relationships, physiology-severity interactions, and patient information in clinical notes. The proposed method can be implemented as a decision support system to enhance physicians' clinical decisions and patient management, and improve healthcare organizations' resource planning and utilization efficiency, with nontrivial cost containment implications.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114411"},"PeriodicalIF":6.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350672","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

Contending with coronaries: May HIT be with you

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-02 DOI: 10.1016/j.dss.2025.114410

Nirup Menon, Amitava Dutta, Sidhartha Das

{"title":"Contending with coronaries: May HIT be with you","authors":"Nirup Menon, Amitava Dutta, Sidhartha Das","doi":"10.1016/j.dss.2025.114410","DOIUrl":"10.1016/j.dss.2025.114410","url":null,"abstract":"<div><div>Health Information Technology (HIT) is revolutionizing healthcare by serving as the backbone for various decision support activities across the healthcare continuum, particularly within hospital settings. While existing literature highlights its positive impact on patient satisfaction, costs, and quality, its role in complementing other crucial hospital inputs to influence clinical healthcare outcomes has been relatively understudied. In this study, we explore the complementary effects of a specific type of HIT, Clinical Decision Support Systems (CDSS) on cardiac mortality rates (CMR) in hospitals. Though hospital personnel and cardiac medical services (CMS) are pivotal in reducing CMR, CDSS plays a complementary role by providing information and decision support throughout the cardiac care delivery process. Leveraging panel data spanning from 2016 to 2020, our analysis reveals that CDSS complements CMS and hospital personnel in mitigating CMR. These findings provide theoretical insights into the benefits facilitated by CDSS in cardiac care and hold managerial implications for the effective deployment of this technology within hospital settings. Through our analysis, we aim to elucidate the synergistic effects of CDSS, cardiac medical services, and healthcare personnel in improving clinical healthcare outcomes, particularly in the management of cardiac disease.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114410"},"PeriodicalIF":6.7,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372582","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

Impact of multidimensional presence on user well-being in metaverse communities

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114382

Arslan Rafi , Sanjit K. Roy , Mohsin Abdur Rehman , Muhammad Junaid Shahid Hasni

{"title":"Impact of multidimensional presence on user well-being in metaverse communities","authors":"Arslan Rafi , Sanjit K. Roy , Mohsin Abdur Rehman , Muhammad Junaid Shahid Hasni","doi":"10.1016/j.dss.2024.114382","DOIUrl":"10.1016/j.dss.2024.114382","url":null,"abstract":"<div><div>In metaverse communities, users engage in various activities, such as socializing, gaming, and exploration. Presence in such communities refers to the feeling of being there and being fully immersed. This study examines the role of various dimensions of presence (e.g., social, spatial, and self) in driving user well-being in metaverse communities. Moreover, the study tests the mediating roles of social connectedness and social support. The data set comprised responses from 357 metaverse users. Data were analyzed using multigroup analysis (MGA), necessary condition analysis, partial least squares path modeling, and artificial neural network analysis. Results show that social presence, spatial presence, and self-presence affect users' well-being in metaverse communities. Further, they indicate that spatial presence has a particularly strong impact on user well-being among extroverts and introverts. This study is one of the first to investigate how aspects of presence and user well-being interact inside metaverse communities. The practical implications of the results are discussed.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114382"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169637","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

IS/IT Backsourcing decision making - A design science research approach

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114379

Jacky Akoka , Isabelle Comyn-Wattiau

{"title":"IS/IT Backsourcing decision making - A design science research approach","authors":"Jacky Akoka , Isabelle Comyn-Wattiau","doi":"10.1016/j.dss.2024.114379","DOIUrl":"10.1016/j.dss.2024.114379","url":null,"abstract":"<div><div>Many organizations implement outsourcing solutions for information systems and/or information technology (IS/IT). Some of them face problems resulting from dissatisfaction with these outsourcing decisions. Reasons for dissatisfaction include an outsourcing agreement that did not meet expectations, organizational changes, and a loss of control over the business. As a result, companies are rethinking their existing contracts by adopting a backsourcing solution. IS/IT backsourcing refers to the full or partial repatriation of previously outsourced activities. Given the strategic stakes of backsourcing, it is imperative to develop a decision-making process based on a solid framework. Based on an extensive literature review, we propose a design science research (DSR) approach consisting of four artifacts: a set of requirements, a conceptual framework, a decision model, and a prototype to support decision makers considering IS/IT backsourcing issues. A validation is presented, consisting of an illustrative scenario, a logical argument, and an expert evaluation. In addition, the approach was compared with recommendations found in the literature. Finally, the comments of a panel of IS/IT experts were collected. Our decision support system can be used by decision makers to investigate the backsourcing of IS/IT activities, choosing between three scenarios: backsource, renegotiate the contract, or change vendor.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114379"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170850","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 implications of account suspensions on online discussion platforms

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114389

Pattharin Tangwaragorn , Warut Khern-am-nuai , Wreetabrata Kar

{"title":"The implications of account suspensions on online discussion platforms","authors":"Pattharin Tangwaragorn , Warut Khern-am-nuai , Wreetabrata Kar","doi":"10.1016/j.dss.2024.114389","DOIUrl":"10.1016/j.dss.2024.114389","url":null,"abstract":"<div><div>This study explores the impact of temporary account suspensions on users' engagement in online platforms. Using observational data obtained through a collaboration with a prominent online discussion forum in Asia, we conduct empirical analyses that are guided by regulatory focus theory and reactance theory, and we use both propensity score matching and a difference-in-differences regression analysis to uncover insights. We find that suspended users post less frequently after they experience temporary account suspension, but that these users create longer content compared to those users who did not face account suspension. We also find that user characteristics (e.g., platform tenure, prior suspension history) moderate the impact of suspensions on content length and volume. Further, mechanism analyses reveal that content posted by users who experienced temporary account suspension receives more negative reactions from the community after the suspension, even when the content does not violate platform's content contribution guidelines. As a result, suspended users are more likely to leave a platform after the suspension. Our findings contribute to the literature that explores the effects of temporary suspensions on user-generated content management, as well as offer practical insights for platform managers who develop and enforce content moderation policies.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114389"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169650","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

Metaverse adoption for competitive edge: The role of implementation capability & willingness to change

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114385

Georgios S. Bekos , Simos Chari , Davit Marikyan , Savvas Papagiannidis

{"title":"Metaverse adoption for competitive edge: The role of implementation capability & willingness to change","authors":"Georgios S. Bekos , Simos Chari , Davit Marikyan , Savvas Papagiannidis","doi":"10.1016/j.dss.2024.114385","DOIUrl":"10.1016/j.dss.2024.114385","url":null,"abstract":"<div><div>The metaverse has recently attracted significant attention from the business community as it offers various opportunities for enhanced business value creation. Nevertheless, there is a limited understanding as to why some firms are better able than others to realise the performance benefits afforded by the metaverses. To address this shortcoming, we draw on the ‘organisational excellence’ framework and investigate the role of ‘implementation capacity’ and ‘willingness/readiness to change’ to understand how metaverse adoption intentions can translate into organisational performance benefits (i.e., competitive edge over rivals). Based on data collected from 431 organisations, we test our hypotheses with a regression analysis and complement our findings with a fuzzy-set qualitative comparative analysis (fsQCA) to identify the organisational excellence factors—pertaining to organisational culture, structure, human capital, and capabilities—that enable the effective implementation of the metaverse. The study findings shed light on the effective integration of the metaverse into organisations and offer unique implications for technology adoption and implementation theory and practice.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114385"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170846","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

A decision support framework for misstatement identification in financial reporting: A hybrid tree-augmented Bayesian belief approach

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114369

Serhat Simsek , Ali Dag , Kristof Coussement , Eyyub Y. Kibis , Abdullah Asilkalkan , Srinivasan Ragothaman

{"title":"A decision support framework for misstatement identification in financial reporting: A hybrid tree-augmented Bayesian belief approach","authors":"Serhat Simsek , Ali Dag , Kristof Coussement , Eyyub Y. Kibis , Abdullah Asilkalkan , Srinivasan Ragothaman","doi":"10.1016/j.dss.2024.114369","DOIUrl":"10.1016/j.dss.2024.114369","url":null,"abstract":"<div><div>Over a six-year period, employees and managers at Wells Fargo created 3.5 million false deposit and credit card accounts resulting in $4.8 billion in fines. Following this incident, there has been a newfound focus on effective internal controls. The purpose of the current study is to improve misstatement identification by formulating a novel hybrid decision support framework to a) accurately predict financial misstatements and frauds, b) build a parsimonious model by employing a comprehensive variable selection procedure without hurting (in contrast, potentially improving) the model's prediction power, c) uncover the conditional inter-dependencies between the predictors via a Bayesian-belief based probabilistic network, and d) provide stakeholders with a firm-specific MWIC risk score. In an extensive real-life experimental setup, we validate our decision support system and find that the Tree-Augmented Bayesian Belief Network (TAN) model provides high misstatement identification accuracy results when the variables are selected through the <em>Genetic Algorithm (GA)</em> that employs <em>Random Forests</em> (RF) as the classification algorithm (AUC of 0.856 by employing only 5 out of 23 potential variables). Financial experts and stakeholders can use the probabilistic scores provided, while their intuition/incentive should collaborate with prediction models to make final decision on the cases where the model is not confident enough (i.e., when the probabilistic scores are close to 50/50). These insights enable stakeholders to improve the early warning systems for MWIC and financial misstatements and therefore potential frauds.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114369"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169634","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