Decision Support Systems最新文献_第4页

Time for a change! Uprooting users embedded in the status quo from habitual decision-making

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114371

Xue Sun , Bo Guo , Yufeng Yang , Yu Pan

{"title":"Time for a change! Uprooting users embedded in the status quo from habitual decision-making","authors":"Xue Sun , Bo Guo , Yufeng Yang , Yu Pan","doi":"10.1016/j.dss.2024.114371","DOIUrl":"10.1016/j.dss.2024.114371","url":null,"abstract":"<div><div>Introducing the feature of “Buy Again” or “Order Again” is a common practice for online platforms to facilitate consumer repurchases. Although the adoption of these features can cultivate consumers' dependence on focal products and promote habitual purchases, it potentially hinders the promotion of new products and reduces consumer choice diversity. This raises a broader issue of how to inhibit habitual decision-making, rendering exploring the underlying mechanisms for inhibiting habitual decision-making essential, a topic largely overlooked by previous literature. To address this gap, this research explores how decision-related new information, namely Bayesian updating information, influences consumers' repeated decision-making. Utilizing the paradigm of Monty Hall dilemma, the findings show that Bayesian updating information curtails habitual decisions by encouraging consumers to choose alternative options in both scenarios in which the initial choices are self-decided or given by default. Applying the HDDM (hierarchical drift-diffusion model), the results indicate that, in both scenarios, Bayesian updating information reduces consumers' status quo bias, i.e., mitigates their initial preferences for initial choices, and facilitates the accumulation of evidence for changing initial choices. Notably, when the initial choices are self-decided, consumers with Bayesian updating information tend to seek more evidence to make decisions than those without it, while this trend is not observed when the initial choices are given by default. These findings deepen our understanding of online repeated decision-making and provide valuable insights into the design of decision support systems to discourage consumers' habitual decisions and enhance their choice diversity in online shopping.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114371"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169633","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

Digitalization of the natural sciences: Design science research and computational science

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114368

Veda C. Storey, Richard L. Baskerville

引用次数: 0

Unveiling the metaverse: A comparison of multiple environments

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114384

Sumanta Singha , Kiran Pedada , Pradeep Racherla , Srinivas Pingali

{"title":"Unveiling the metaverse: A comparison of multiple environments","authors":"Sumanta Singha , Kiran Pedada , Pradeep Racherla , Srinivas Pingali","doi":"10.1016/j.dss.2024.114384","DOIUrl":"10.1016/j.dss.2024.114384","url":null,"abstract":"<div><div>The advent of the metaverse is fundamentally altering the relationship dynamics between brands and users. Brands that successfully navigate this new landscape create deeper engagement and foster lasting brand loyalty. Using a multi-method, multi-study approach, we examine the interplay between user characteristics and brand perception in a real metaverse environment called “Universe”, created by a large public sector bank in India. Study 1 involves a qualitative analysis (i.e., focus group discussion) to derive insights for the conceptual model. Study 2 involves quantitative analysis of survey data conducted in three different experimental settings: first-person perspective (1PP), third-person perspective (3PP), and third-person perspective with peer interaction (3PP social). The study reveals that users' social connectedness, technology readiness, and domain literacy positively impact brand perception via two distinct mechanisms: sense of presence and product engagement. Further, our analysis shows that these outcomes vary significantly across the three experimental settings. Whereas product engagement emerges as the dominant mechanism in the 1PP environment, sense of presence emerges as the dominant mechanism in the 3PP social setting. Our study provides several important theoretical and managerial implications for brands, users, and decision science scholars.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114384"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170845","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

Are you caught in the dilemma of metaverse avatars? The impact of individuals' congruity perceptions on paradoxical emotions and actual behaviors

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114387

Xusen Cheng , Shuang Zhang , Jian Mou

{"title":"Are you caught in the dilemma of metaverse avatars? The impact of individuals' congruity perceptions on paradoxical emotions and actual behaviors","authors":"Xusen Cheng , Shuang Zhang , Jian Mou","doi":"10.1016/j.dss.2024.114387","DOIUrl":"10.1016/j.dss.2024.114387","url":null,"abstract":"<div><div>As the foundation of the metaverse, three-dimensional avatars are increasingly shaping our personal and professional lives. However, a nuanced reading of avatar literature proposes that avatars can exhibit both positive and negative dimensions, leading to a paradoxical phenomenon. This study aims to conceptualize a holistic framework elucidating the intricate interplay between perceptions, emotions, and actual behaviors to substantiate the salience of paradoxical emotions. Employing a mixed-methods approach comprising think-aloud experiments and interviews (Phase 1), surveys (Phase 2), and follow-up interviews (Phase 3), the study endeavors to develop and validate a model grounded in a three-congruity perspective encompassing self, privacy, and function. Research findings underline that perceived control, social presence, and avatar perception heighten individuals' emotional attachment toward avatars, while social presence mitigates emotional paradoxes. Avatar privacy concern increases emotional paradox without affecting emotional attachment. Additionally, emotional attachment negatively correlates with actual metaverse resistance, whereas emotional paradox positively influences such resistance; conversely, emotional attachment positively correlates with actual metaverse avatar usage. This study extends the existing dual-congruity theory and provides practical implications for metaverse platforms to improve interactive experiences with avatars.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114387"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170847","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 earnings conference calls tell more lies? A contrastive multimodal dialogue network for advanced financial statement fraud detection

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-02-01 DOI: 10.1016/j.dss.2024.114381

Qi Lu , Wei Du , Shaochen Yang , Wei Xu , J. Leon Zhao

{"title":"Can earnings conference calls tell more lies? A contrastive multimodal dialogue network for advanced financial statement fraud detection","authors":"Qi Lu , Wei Du , Shaochen Yang , Wei Xu , J. Leon Zhao","doi":"10.1016/j.dss.2024.114381","DOIUrl":"10.1016/j.dss.2024.114381","url":null,"abstract":"<div><div>Financial statement frauds by listed firms pose significant challenges to public investors and jeopardize the stability of financial markets. Previous studies have identified deceptive verbal and vocal cues from earnings conference calls as indicators of financial statement fraud. However, these studies only extracted managers' verbal and vocal cues separately over the entire call, neglecting the utterance-level fusion between verbal and vocal cues as well as the multi-turn interaction between analysts and managers. To fill this gap, we develop a novel end-to-end <em><strong>c</strong>ontrastive <strong>m</strong>ulti<strong>m</strong>odal <strong>d</strong>ialogue network</em> (CMMD) that considers both verbal-vocal fusion and multi-role interactions to uncover hidden deceptive cues in earnings conference calls. The proposed model comprises two core modules, namely, the <em>Multimodal Fusion Learning module and the Dialogue Interaction Learning module</em>. Building on Vrij's verbal-nonverbal complementary mechanisms in deception detection, the designed <em>Multimodal Fusion Learning</em> employs contrastive learning to align verbal and vocal cues and a co-attention mechanism to learn cross-modal interaction. Inspired by the Interpersonal Deception Theory that emphasizes the dynamic interaction process between deceivers and targets, the <em>Dialogue Interaction Learning</em> utilizes a dialogue-aware co-attention mechanism to model multi-turn analyst-manager interaction and uses contrastive learning to improve dialogue representations. Our extensive empirical results show that CMMD achieves 8.64 % improvement in detecting fraudulent cases compared to the best baseline model. As such, our study advances the research frontier in fraud detection and contributes an innovative IT artifact in practice.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"189 ","pages":"Article 114381"},"PeriodicalIF":6.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170849","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

Should a better-informed manufacturer hold pricing power for the direct channel: The role of consumer reviews

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-01-31 DOI: 10.1016/j.dss.2025.114408

Musen Xue , Jiahui Guo , Lin Feng

{"title":"Should a better-informed manufacturer hold pricing power for the direct channel: The role of consumer reviews","authors":"Musen Xue , Jiahui Guo , Lin Feng","doi":"10.1016/j.dss.2025.114408","DOIUrl":"10.1016/j.dss.2025.114408","url":null,"abstract":"<div><div>Manufacturers can effectively obtain precise demand information through the utilization of data analysis technologies. These better-informed manufacturers commonly distribute their products not only through traditional offline retailers but also via direct sales channels. In this context, distinct pricing strategies for online channels, namely holding pricing power and giving up pricing power, can be observed in practice. Furthermore, these online channels also enable consumers to post consumer reviews, which significantly impacts consumers’ purchasing decisions. By applying a signaling game, our study examines the interaction between pricing strategy of a direct sales channel and consumer reviews. Our findings indicate that consumer reviews significantly influence the determination of the optimal pricing strategy of direct channel for a better-informed manufacturer. Holding pricing power is always the optimal strategy when the direct channel functions as an authentic distribution channel. However, giving up pricing power can be optimal when the direct channel personates a competitive threat, conditional on the travel cost of traditional channel and the information disclosed through consumer reviews. Contrary to expectations, manufacturer’s retention of pricing power for the direct channel can benefit the retailer when the travel cost to the traditional channel is moderate and the information disclosed in consumer reviews does not exhibit extreme negativity or positivity. Additionally, our findings indicate that the chain members can acquire an agreement on the direct channel’s pricing strategy, which results in a win-win outcome, thereby improving supply chain efficiency.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114408"},"PeriodicalIF":6.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169045","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

Tell me a story! Narrative-driven XAI with Large Language Models

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-01-31 DOI: 10.1016/j.dss.2025.114402

David Martens , James Hinns , Camille Dams , Mark Vergouwen , Theodoros Evgeniou

{"title":"Tell me a story! Narrative-driven XAI with Large Language Models","authors":"David Martens , James Hinns , Camille Dams , Mark Vergouwen , Theodoros Evgeniou","doi":"10.1016/j.dss.2025.114402","DOIUrl":"10.1016/j.dss.2025.114402","url":null,"abstract":"<div><div>Existing Explainable AI (XAI) approaches, such as the widely used SHAP values or counterfactual (CF) explanations, are arguably often too technical for users to understand and act upon. To enhance comprehension of explanations of AI decisions and the overall user experience, we introduce XAIstories, which leverage Large Language Models (LLMs) to provide narratives about how AI predictions are made: SHAPstories based on SHAP and CFstories on CF explanations. We study the impact of our approach on users’ experience and understanding of AI predictions. Our results are striking: over 90% of the surveyed general audience finds the narratives generated by SHAPstories convincing, and over 78% for CFstories, in a tabular data experiment. More than 75% of the respondents in an image experiment find CFstories more or equally convincing as their own crafted stories. We also find that the generated stories help users to more accurately summarize and understand AI decisions than they do when only SHAP values are provided. The results indicate that combining LLM generated stories with current XAI methods is a promising and impactful research direction.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114402"},"PeriodicalIF":6.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143193315","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

Multimodal review helpfulness prediction with a multi-level cognitive reasoning mechanism: A theory-driven graph learning model

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-01-29 DOI: 10.1016/j.dss.2025.114406

Hai Wei , Ying Yang , Yu-Wang Chen

{"title":"Multimodal review helpfulness prediction with a multi-level cognitive reasoning mechanism: A theory-driven graph learning model","authors":"Hai Wei , Ying Yang , Yu-Wang Chen","doi":"10.1016/j.dss.2025.114406","DOIUrl":"10.1016/j.dss.2025.114406","url":null,"abstract":"<div><div>Customers' perception of review helpfulness entails a cognitive reasoning process influenced by the contextual information of reviews including product descriptions and review neighbors. Current studies on helpfulness prediction primarily focus on static features of individual reviews, neglecting the dynamic interaction among products, reviews and their contextual neighbors. To address this gap, we propose a theory-driven deep learning model for multimodal review helpfulness prediction (DeepMRHP-MCR). The model can collectively simulate human cognitive processes when voting on whether a review is helpful. Specifically, this study presents a multi-level cognitive reasoning mechanism that reconciles the inconsistencies among product descriptions, reviews and their neighbors from the modality, individual and contextual level, respectively. A case study is conducted on the real-world datasets collected from <span><span>Amazon.com</span><svg><path></path></svg></span>. Empirical results show that the proposed model can improve the quality and interpretability of review prediction process, and present a deep comprehension of consumer's cognitive decision-making process when evaluating reviews.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114406"},"PeriodicalIF":6.7,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143193316","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

Exploring the motivations behind behavior: A theory-driven deep-learning framework for cyberviolence behavior detection

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-01-28 DOI: 10.1016/j.dss.2025.114409

Xuelong Chen , Yiping Chen , Guojie Yin

{"title":"Exploring the motivations behind behavior: A theory-driven deep-learning framework for cyberviolence behavior detection","authors":"Xuelong Chen , Yiping Chen , Guojie Yin","doi":"10.1016/j.dss.2025.114409","DOIUrl":"10.1016/j.dss.2025.114409","url":null,"abstract":"<div><div>The anonymity and convenience of social media platforms enable the public to express and even vent themselves, which drives a surge of cyberviolence behaviors (CVB). Recent advances in machine learning, especially in deep learning, have drastically benefited CVB detection. However, despite the wide use of state-of-the-art deep-learning models, previous studies only analyzed each post/comment for the presence of (obfuscated) abusive text, which is not comprehensive and exact because the content posted online may not necessarily include negative words. In complex and conflicting situations, people may overlook implicit violence, leading to failures in situational judgment. Herein, we designed a well-grounded and explainable deep-learning framework based on the theory of planned behavior (TPB) to explore the motivations behind CVB to better detect it. Specifically, we constructed a systematic and comprehensive suite of computable features grounded in TPB and then proposed a novel model named <strong>M</strong>ultilevel and <strong>M</strong>ultiattribute <strong>E</strong>mbedding CVB detection model considering <strong>D</strong>ual-view <strong>C</strong>ontextual <strong>I</strong>nformation. Our framework detected implicit and explicit CVB with macro F1 scores of >88.67 %, outperforming state-of-the-art methods. We further provided differentiated strategies according to the scale and distribution of different classes of CVB and proposed related management implications. Our study sheds light on platform operations in managing online content and mitigating the risk of governance cost wastage and deterioration of the cyber ecosystem.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"190 ","pages":"Article 114409"},"PeriodicalIF":6.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160447","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

Does the most popular answer lead to the best answer: The moderating roles of tenure, social closeness, and cultural tightness

IF 6.7 1区计算机科学

Decision Support Systems Pub Date : 2025-01-27 DOI: 10.1016/j.dss.2025.114405

Yuxin Cai , Xiayu Chen , Shaobo Wei

{"title":"Does the most popular answer lead to the best answer: The moderating roles of tenure, social closeness, and cultural tightness","authors":"Yuxin Cai , Xiayu Chen , Shaobo Wei","doi":"10.1016/j.dss.2025.114405","DOIUrl":"10.1016/j.dss.2025.114405","url":null,"abstract":"<div><div>Online question and answer (Q&A) communities rely on the general audience or the question asker to determine the best answer. However, limited attention has been directed toward understanding the influence of the general audience-favored answer (i.e., most popular answer) on the question asker-selected best answer (i.e., best answer). This study examines whether and how the general audience-favored answer influences the question asker-selected best answer. Drawing upon uncertainty reduction theory (URT), this paper investigates how three uncertainty reduction strategies (i.e. question askers' tenure, social closeness between the question asker and question answerer, and cultural tightness of the question asker's region) moderate the relationship between the general audience-favored answer and the question asker-selected best answer. To test the theoretical model, we used a dataset from an online Q&A community comprising 161,695 observations. Our results reveal that the general audience-favored answer more likely leads to the question asker-selected best answer. Furthermore, we find that the question asker's tenure and the social closeness between the question asker and question answerer negatively moderate the above relationship, while the cultural tightness of question asker's region positively moderates the above relationship. This research offers a new perspective on the mechanisms through which the general audience-favored answer leads to question asker-selected best answer. By identifying the critical roles of uncertainty reduction strategies during the best answer selection process, our research provides valuable insights for online Q&A community managers to optimize user engagement and satisfaction.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"191 ","pages":"Article 114405"},"PeriodicalIF":6.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143193314","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