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The impact of doctors' facial attractiveness on users' choices in online health communities: A stereotype content and social role perspective Decis. Support Syst. (IF 7.5) Pub Date : 2024-05-06 Xing Zhang, Yuanyuan Wang, Quan Xiao, Jingguo Wang
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Transparency in design science research Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-30 Alan R. Hevner, Jeffrey Parsons, Alfred Benedikt Brendel, Roman Lukyanenko, Verena Tiefenbeck, Monica Chiarini Tremblay, Jan vom Brocke
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When do consumers buy during online promotions? A theoretical and empirical investigation Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-28 Tao Zhu, Cheng Nie, Zhengrui Jiang, Xiangpei Hu
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Freedom of speech or freedom of reach? Strategies for mitigating malicious content in social networks Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-27 Saurav Chakraborty, Sandeep Goyal, Annamina Rieder, Agnieszka Onuchowska, Donald J. Berndt
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Explaining the model and feature dependencies by decomposition of the Shapley value Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-27 Joran Michiels, Johan Suykens, Maarten De Vos
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The information content of financial statement fraud risk: An ensemble learning approach Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-27 Wei Duan, Nan Hu, Fujing Xue
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Explainable Learning Analytics: Assessing the stability of student success prediction models by means of explainable AI Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-26 Elena Tiukhova, Pavani Vemuri, Nidia López Flores, Anna Sigridur Islind, María Óskarsdóttir, Stephan Poelmans, Bart Baesens, Monique Snoeck
Beyond managing student dropout, higher education stakeholders need decision support to consistently influence the student learning process to keep students motivated, engaged, and successful. At the course level, the combination of predictive analytics and self-regulation theory can help instructors determine the best study advice and allow learners to better self-regulate and determine how they want
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The design of human-artificial intelligence systems in decision sciences: A look Back and directions forward Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-24 Veda C. Storey, Alan R. Hevner, Victoria Y. Yoon
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Modeling the evolution of collective overreaction in dynamic online product diffusion networks Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-24 Xiaochao Wei, Yanfei Zhang, Xin (Robert) Luo
With the development of e-commerce, collective overreactions such as buying frenzy have become prominent. However, studies have rarely investigated the mechanism of irrational consumer behavior at the group level. To investigate the evolution of collective overreaction in dynamic online product diffusion networks, we employed a sequential multiple-methods approach. A conceptual model is constructed
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Strategic team design for sustainable effectiveness: A data-driven analytical perspective and its implications Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-21 Teng Huang, Qin Su, Chuling Yu, Zheng Zhang, Fei Liu
Teams are building blocks of organizations and essential inputs of organizational success. This article studies a data-driven analytical approach that exploits the rich data accumulated in organizations in the digital era to design teams, including prescribing team composition and formation decisions. We propose to evaluate a team regarding its performance and temporal stability, referred to as (SE)
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Enhancing healthcare decision support through explainable AI models for risk prediction Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-18 Shuai Niu, Qing Yin, Jing Ma, Yunya Song, Yida Xu, Liang Bai, Wei Pan, Xian Yang
Electronic health records (EHRs) are a valuable source of information that can aid in understanding a patient’s health condition and making informed healthcare decisions. However, modelling longitudinal EHRs with heterogeneous information is a challenging task. Although recurrent neural networks (RNNs) are frequently utilized in artificial intelligence (AI) models for capturing longitudinal data, their
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Hybrid black-box classification for customer churn prediction with segmented interpretability analysis Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-06 Arno De Caigny, Koen W. De Bock, Sam Verboven
Customer retention management relies on advanced analytics for decision making. Decision makers in this area require methods that are capable of accurately predicting which customers are likely to churn and that allow to discover drivers of customer churn. As a result, customer churn prediction models are frequently evaluated based on both their predictive performance and their capacity to extract
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A meta-path, attention-based deep learning method to support hepatitis carcinoma predictions for improved cirrhosis patient management Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-04 Zejian (Eric) Wu, Da Xu, Paul Jen-Hwa Hu, Liang Li, Ting-Shuo Huang
Hepatitis carcinoma (HCC) accounts for the majority of liver cancer–related deaths globally. Cirrhosis often precedes HCC clinically in a strong, temporal relationship. Therefore, identifying cirrhosis patients at higher risk of HCC is crucial to physicians' clinical decision-making and patient management. Effective estimates of at-risk patients can facilitate timely therapeutic interventions and thereby
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Crowdsourced firm ratings and total factor productivity: An empirical examination Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-04 Zongxi Liu, Donglai Bao, Xiao Xiao, Huimin Zhao
Employees' reviews, feedback, opinions, and experiences shared on crowdsourcing platforms are now widely used by human resource management researchers to analyze a firm's performance, management effectiveness, and culture. The analysis of firm ratings posted by employees on crowdsourcing platforms can not only provide timely feedback and insights into a firm's operations but also inspire managers to
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Towards explainable artificial intelligence through expert-augmented supervised feature selection Decis. Support Syst. (IF 7.5) Pub Date : 2024-04-01 Meysam Rabiee, Mohsen Mirhashemi, Michael S. Pangburn, Saeed Piri, Dursun Delen
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Prioritising national healthcare service issues from free text feedback – A computational text analysis & predictive modelling approach Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-31 Adegboyega Ojo, Nina Rizun, Grace Walsh, Mona Isazad Mashinchi, Maria Venosa, Manohar Narayana Rao
Patient experience surveys have become a key source of evidence for supporting decision-making and continuous quality improvement within healthcare services. To harness free-text feedback collected as part of these surveys for additional insights, text analytics methods are increasingly employed when the data collected is not amenable to traditional qualitative analysis due to volume. However, while
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Real-time decision support for human–machine interaction in digital railway control rooms Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-30 Léon Sobrie, Marijn Verschelde
This study proposes a real-time Decision Support System (DSS) using machine learning to enhance proactive management of Human–Machine Interaction (HMI) in safety–critical digital control rooms. The DSS provides explainable predictions and recommendations regarding near-future automation usage, customized for the railway control room management, who supervise the operations of traffic controllers (TCs)
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Uncovering the relationship between incidental emotion toward a disaster and stock market fluctuations: Evidence from the US market Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-29 Tao Yang, T. Robert Yu, Huimin Zhao
Despite having potentially important implications, there has been little research on the relationship between the public's incidental emotion and the stock market. To that end, we construct a valence-based measure of incidental emotion using BERTweet's sentiment analysis and empirically investigate the association between collective incidental emotion toward the COVID-19 pandemic and the U.S. stock
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D3S: Decision support system for sectorization Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-24 Elif Göksu Öztürk, Pedro Rocha, Ana Maria Rodrigues, José Soeiro Ferreira, Cristina Lopes, Cristina Oliveira, Ana Catarina Nunes
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Effects of enterprise social media use on employee improvisation ability through psychological conditions: The moderating role of enterprise social media policy Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-23 Mengyi Zhu, Yuan Sun, Justin Zuopeng Zhang, Jindi Fu, Bo Yang
The emergence of enterprise social media (ESM) allows enterprises to develop employee improvisation ability for effective decision-making in various emergencies. However, it remains unclear how the use of ESM by employees affects their ability to improvise. Based on the job demands-resources model and Kahn's psychological conditions framework, this study constructs a theoretical model capturing two
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How does escapism foster game experience and game use? Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-08 Tzu-Ling Huang, Jin-Rong Yeh, Gen-Yih Liao, T.C.E. Cheng, Yan-Cheng Chang, Ching-I Teng
Online games represent a rapidly growing and competitive global market for technology firms. Games are viewed as places where people can temporarily escape from reality. However, it is unclear how game escapism fosters game experience and game use, thus indicating a research gap. This gap keeps decision-makers (i.e., firms and policy-makers) in the dark regarding how game escapism affects gameplay
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Towards fair decision: A novel representation method for debiasing pre-trained models Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-06 Junheng He, Nankai Lin, Qifeng Bai, Haoyu Liang, Dong Zhou, Aimin Yang
Pretrained language models (PLMs) are frequently employed in Decision Support Systems (DSSs) due to their strong performance. However, recent studies have revealed that these PLMs can exhibit social biases, leading to unfair decisions that harm vulnerable groups. Sensitive information contained in sentences from training data is the primary source of bias. Previously proposed debiasing methods based
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To be honest or positive? The effect of Airbnb host description on consumer behavior Decis. Support Syst. (IF 7.5) Pub Date : 2024-03-02 Xinyu Sun, Li Gui, Bin Cai
On accommodation-sharing platform, host self-description influence consumer behavior as an important information. Based on the Perceived Value Theory and the Expectation Confirmation Theory, we developed an analytical framework to investigate the relationship between host description strategies and consumer behavior of room booking and satisfaction. We measured host description strategies ( and ) using
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How self-selection Bias in online reviews affects buyer satisfaction: A product type perspective Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-29 Yancong Xie, William Yeoh, Jingguo Wang
Online reviews play a crucial role in shaping buyers' purchase decisions. However, previous research has highlighted the existence of self-selection biases among buyers who contribute to reviews, which in turn leads to biased distributions of review ratings. This research aims to explore the further influences of self-selection bias on buyer satisfaction through agent-based modeling, considering two
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Developing a goal-driven data integration framework for effective data analytics Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-23 Dapeng Liu, Victoria Y. Yoon
Data integration plays a crucial role in business intelligence, aiding decision-makers by consolidating data from heterogeneous sources to provide deep insights into business operations and performance. In the big data era, automated data integration solutions need to process high volumes of disparate data robustly and seamlessly for various analytical needs or operational actions. Existing data integration
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Navigating autonomy and control in human-AI delegation: User responses to technology- versus user-invoked task allocation Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-21 Martin Adam, Christopher Diebel, Marc Goutier, Alexander Benlian
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Responsible machine learning for United States Air Force pilot candidate selection Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-21 Devin Wasilefsky, William N. Caballero, Chancellor Johnstone, Nathan Gaw, Phillip R. Jenkins
The United States Air Force (USAF) continues to be plagued by a chronic pilot shortage, one that could be exacerbated by an accompanying shortfall in the commercial airlines. As a result, efforts have increased to alleviate this shortage by finding methods to reduce pilot training attrition. We contribute to these efforts by setting forth a decision support system (DSS) for pilot candidate selection
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Outlier detection using flexible categorization and interrogative agendas Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-19 Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia Panettiere, Apostolos Tzimoulis, Nachoem Wijnberg
Categorization is one of the basic tasks in machine learning and data analysis. Building on formal concept analysis (FCA), the starting point of the present work is that different ways to categorize a given set of objects exist, which depend on the choice of the sets of features used to classify them, and different such sets of features may yield better or worse categorizations, relative to the task
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Explainable artificial intelligence and agile decision-making in supply chain cyber resilience Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-17 Kiarash Sadeghi R., Divesh Ojha, Puneet Kaur, Raj V. Mahto, Amandeep Dhir
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Assessing financial distress of SMEs through event propagation: An adaptive interpretable graph contrastive learning model Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-17 Jianfei Wang, Cuiqing Jiang, Lina Zhou, Zhao Wang
Accurate assessment of financial distress of SMEs is critical as it has strong implications for various stakeholders to understand the firm's financial health. Recent studies start to leverage network data and suggest the effect of event propagation for predicting financial distress. Yet such methods face methodological challenges in determining and explaining event propagation due to heterogeneous
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Simplicity in joy and detail in anger: Intertwining effect of cognitive and affective review disposition on review helpfulness Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-15 Yicheng Zhang, Xinqi Zhao, Ya Zhou
Review length and readability, are cognitive dispositions of reviews supposed to reflect diagnostic content and lead to favorable evaluation of review helpfulness. However, underlying these two cognitive dispositions of reviews, are discrepancies that make it difficult for a helpful review to simultaneously satisfy both of them. To resolve the discrepancies, this present study, drawn on cognitive tuning
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Improving answer quality using image-text coherence on social Q&A sites Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-09 Yining Song, Xiaoying Xu, Kaushik Dutta, Zhihong Li
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Distilling wisdom of crowds in online communities: A novel prediction market constructed with comment posters Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-09 Li Dong, Haichao Zheng, Liting Li, Chunyu Zhou
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“To share or not to share?” – A hybrid SEM-ANN-NCA study of the enablers and enhancers for mobile sharing economy Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-05 Lai-Ying Leong, Teck-Soon Hew, Keng-Boon Ooi, Patrick Y.K. Chau
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How technical features of virtual live shopping platforms affect purchase intention: Based on the theory of interactive media effects Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-05 Yuan Sun, Yating Zhong, Zuopeng Zhang, Yonggui Wang, Mengyi Zhu
Virtual live shopping platforms (VLSPs) are an innovative form of intelligent shopping DSS that offer brands novel opportunities to interact with customers. However, the impact of VLSPs on purchase intention and underlying mechanisms remains unexplored. Therefore, focusing on VLSPs' technical features is crucial for designing and developing their functionalities. This study addresses the research gaps
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How customized managerial responses influence subsequent consumer ratings: The language style matching perspective Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-04 Xiaojing Ren, Le Wang, Xin (Robert) Luo
In previous studies, customized managerial responses have been viewed as an effective tool for sellers to intervene in online consumer opinions. However, formulating a customized response warrants strategic use of language. To explore this further, this study draws on communication accommodation theory to examine the effect of language style matching between managerial responses and online customer
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Blockchain enabled dynamic trust management method for the internet of medical things Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-02 Xinyin Xiang, Jin Cao, Weiguo Fan, Shousheng Xiang, Gang Wang
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A decision support framework for integrated lane identification and long-term backhaul collaboration using spatial analytics and optimization Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-01 Mohsen Emadikhiav, Sudip Bhattacharjee, Robert Day, David Bergman
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Multi-criteria evaluation of health news stories Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-01 Ermira Zifla, Burcu Eke Rubini
The proliferation of digital and social media technologies has enabled quick and wide dissemination of news stories and press releases about new medical treatments. Evaluating these stories is difficult for two reasons. First, these stories are often not completely true or false. A nuanced approach that considers different aspects of these stories (e.g., the presence of inflated claims, suppression
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FedDQA: A novel regularization-based deep learning method for data quality assessment in federated learning Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-01 Zongxiang Zhang, Gang Chen, Yunjie Xu, Lihua Huang, Chenghong Zhang, Shuaiyong Xiao
Researchers strive to design artificial intelligence (AI) models that can fully utilize the potentials of data while protecting privacy. Federated learning is a promising solution because it utilizes data but shields them from those who do not own them. However, assessing data quality becomes a challenge in federated learning. We propose a data quality assessment method, Federated Data Quality Assessment
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Minimizing block incentive volatility through Verkle tree-based dynamic transaction storage Decis. Support Syst. (IF 7.5) Pub Date : 2024-02-01 Xiongfei Zhao, Gerui Zhang, Hou-Wan Long, Yain-Whar Si
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Is decentralization sustainable in the bitcoin system? Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-29 Varghese S. Jacob, Sailendra Prasanna Mishra, Suresh Radhakrishnan
The Bitcoin system is a decentralized monetary system in that any participant can potentially verify and record transactions onto a public ledger. Using a simple model, we show that the number of miners could be negatively (positively) related to the expected rewards if miners with low-operating costs also have less (more) severe financing constraints. We characterize the possibility of miners with
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Towards an integrated framework for developing blockchain systems Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-26 Mahdi Fahmideh, Babak Abedin, Jun Shen
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You jump, I jump? Herding behavior in blockchain application platforms Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-23 Jingxuan Cai, Xin (Robert) Luo, Fujun Lai, Peilin Ai, Xi Zhao
Blockchain technology has brought opportunities and challenges to many fields, including operations and supply chain management. Due to the innovative characteristics of decentralization, transparency, immutability, and anonymity, blockchain applications break new ground for users' decision-making in an operations environment. There is a lack of evidence regarding herding in blockchain technology in
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Designing trust-enabling blockchain systems for the inter-organizational exchange of capacity Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-23 Nick Große, Frederik Möller, Thorsten Schoormann, Michael Henke
In times of rapid and unpredictable developments, companies experience significant volatility in capacity utilization. Virtual capacity exchange platforms help to mitigate this challenge by exchanging capacities with anonymous participants in market-like peer-to-peer networks. However, its efficiency is hindered by behavioral uncertainties, including a lack of inter-organizational trust in other participants
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Meme-affordance tourism: The power of imitation and self-presentation Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-20 Yerin Yhee, Jahyun Goo, Chulmo Koo, Namho Chung
To respond to information systems (IS) researchers' on-going call for understanding what happens in new, social media-enabled processes in diverse contexts, this research investigated how Internet memes facilitate the emergence of new online travel activities and influence visit intentions in new forms of meme tourism. Meme tourism involves new forms of visit intention, where individuals are motivated
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Predicting financial distress using current reports: A novel deep learning method based on user-response-guided attention Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-16 Chenyang Wu, Cuiqing Jiang, Zhao Wang, Yong Ding
Effective financial distress prediction (FDP) can discover a company's potential financial risks and support relevant decisions in a timely manner. Previous studies on FDP have mostly focused on using financial indicators and periodic reports. Compared with periodic reports, current reports disclose major events in a timelier manner. But leveraging the information in current reports involves the critical
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A method for the competitiveness estimation of the incremental new product through user-generated content Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-12 Yu-Mei Ma, Xiao-Hu Zhu, Ping-Ping Cao, Ming-Yang Li
The current dynamic market environment challenges successful incremental new product (INP) launches, compelling enterprise managers to promptly recognize and respond to competitive situations. Estimating INP competitiveness before sale helps enterprise managers adjust their strategies effectively and in a timely manner to ensure successful INP launches. However, a lack of historical evaluation information
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Knowledge transfer to aid social coding: The case of Stack Overflow Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-11 Orcun Temizkan, Ram L. Kumar
Focused online question and answer (Q&A) communities aid social coding. Despite the growing importance of social coding, knowledge transfer in this context remains under-researched. Our primary objective is to understand the knowledge transfer process in this context. We conceptualize knowledge transfer as a process that is impacted by the prior knowledge transfer interactions (network) among participants
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Investigating the beneficial impact of segmentation-based modelling for credit scoring Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-08 Khaoula Idbenjra, Kristof Coussement, Arno De Caigny
Due to its vital role in financial risk management, credit scoring has been investigated extensively in extant information systems studies. However, most credit scoring studies rely on one-size-fits-all classifiers with logistic regression (LR) as a popular benchmark. Moreover, extant literature largely focuses on predictive performance as an evaluation criterion. To find a better balance between predictive
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The secret of voice: How acoustic characteristics affect video creators' performance on Bilibili Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-05 Shixuan Fu, Yan Wu, Qianzhou Du, Chenwei Li, Weiguo Fan
The importance of voice has been well acknowledged in sensory decision-making. Yet, past literature on video creators' performance did not shed much light on the impact of video creators' acoustic characteristics. Building on signaling theory of portfolios, we examine how the acoustic characteristics of a video creator and the signals of video quantity affect the number of likes a video creator receives
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Sustainable decision making based on systems integration and decision support system promoting endorheic basin sustainability Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-05 Yingchun Ge, Feng Han, Feng Wu, Yanbo Zhao, Hongyi Li, Yong Tian, Yi Zheng, Wenfei Luan, Ling Zhang, Ximing Cai, Chunfeng Ma, Xin Li
Sustainability has become a target in official policy rhetoric. However, the gap between scientific investigation and practical decision-making poses a significant challenge in achieving sustainability, particularly in endorheic regions. Addressing this challenge requires the translation of scientific outcomes into available decision-making information. In this study, we propose a sustainable decision-making
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Relative effects of the different bundles of web-design features on intentions to purchase experience products online Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-05 Sung Hee (Jodie) Yoo, Muammer Ozer, Jingjun (David) Xu
Selling experience products online is usually more challenging than selling search products. Addressing the calls for future research in the literature, we study how the different combinations of different web-design features can explain people's intentions to purchase experience products online by mitigating three different product uncertainties associated with such products. The results of a detailed
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To alert or alleviate? A natural experiment on the effect of anti-phishing laws on corporate IT and security investments Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-04 Xiaoxiao Wang, Wilson Weixun Li, Alvin Chung Man Leung, Wei Thoo Yue
In the United States, between 2005 and 2017, 23 states enacted anti-phishing laws to prosecute those suspected of phishing. As the primary targets of phishing attacks, firms' interpretations and reactions toward these laws are worth investigating. Utilizing a unique dataset in a natural experimental setting, this study employed the difference-in-differences method to contrast firms' investment decisions
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Entity recognition from colloquial text Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-04 Tamara Babaian, Jennifer Xu
Extraction of concepts and entities of interest from non-formal texts such as social media posts and informal communication is an important capability for decision support systems in many domains, including healthcare, customer relationship management, and others. Despite the recent advances in training large language models for a variety of natural language processing tasks, the developed models and
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Decoding algorithm appreciation: Unveiling the impact of familiarity with algorithms, tasks, and algorithm performance Decis. Support Syst. (IF 7.5) Pub Date : 2024-01-02 Hasan Mahmud, A.K.M. Najmul Islam, Xin (Robert) Luo, Patrick Mikalef
Algorithm appreciation, defined as an individual's reliance or tendency to rely on algorithms in decision-making, has emerged as a subject of growing scholarly interest. Inquiries into this subject are crucial to understanding human decision-making processes as in the era of artificial intelligence, algorithms are increasingly being integrated into decision-making. To contribute to this evolving field
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A new perspective on classification: Optimally allocating limited resources to uncertain tasks Decis. Support Syst. (IF 7.5) Pub Date : 2023-12-30 Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke
A central problem in business concerns the optimal allocation of limited resources to a set of available tasks, where the payoff of these tasks is inherently uncertain. Typically, such problems are solved using a classification framework, where task outcomes are predicted given a set of characteristics. Then, resources are allocated to the tasks predicted to be the most likely to succeed. We argue
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Unlocking B2B buyer intentions to purchase: Conceptualizing and validating inside sales purchases Decis. Support Syst. (IF 7.5) Pub Date : 2023-12-29 Migao Wu, Pavel Andreev, Morad Benyoucef, David Hood
This study focuses on understanding the purchase decision-making process of B2B buyers in the context of inside sales. While many studies have explored this topic in a B2C context, there has been little attention given to the unique features of B2B inside sales. To address this gap, we developed and empirically validated a buyer's intention to purchase (BIP) model that integrates the B2B purchase decision-making
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Delegation of purchasing tasks to AI: The role of perceived choice and decision autonomy Decis. Support Syst. (IF 7.5) Pub Date : 2023-12-27 Mariyani Ahmad Husairi, Patricia Rossi
Although artificial intelligence (AI) outperforms humans in many tasks, research suggests some consumers are still averse to having AI perform tasks on their behalf. Informed by the literature of customer decision-making process, we propose and show that consumer autonomy is a significant predictor of customers' decision to adopt AI in the purchasing context. Across three experiments, we found that
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