Showing papers in "Decision Support Systems in 2022"

TL;DR: In this paper , a text-analytics framework is proposed to extract important service dimensions directly from consumer reviews, and the results indicate that the importance of service dimensions, on which consumers focus in reviews, varies with levels of interaction.

TL;DR: Wang et al. as mentioned in this paper investigated the various trust targets and their transfer mechanism in a blockchain-enabled healthcare mutual aid platform and found that three platform mechanisms, namely member credibility, blockchain certificate and structural assurance, significantly facilitate the three trust targets, which subsequently enhance individuals' behavioral intentions.

TL;DR: In this paper , a review-based matrix factorization method is proposed to improve the performance of collaborative filtering for recommendation systems by improving the sparsity of the rating matrix caused by insufficient rating data.

TL;DR: In this article , the complex interaction effects between IT-based atmospheric cues are explored using a mixed-methods approach to investigate the influencing mechanism of innovative decision-making contexts on customers' quick decisions.

TL;DR: Wang et al. as discussed by the authors investigated how information timeliness and richness affect public engagement using text data from China's largest social media platform during times of the COVID-19 pandemic.

TL;DR: Wang et al. as mentioned in this paper proposed a novel approach called ImDetector to detect fraudulent reviewers while handling data imbalance based on weighted latent Dirichlet allocation (LDA) and Kullback-Leibler (KL) divergence.

TL;DR: In this paper , the authors presented a novel feature engineering approach in which they extracted several review-centric and reviewer-centric features from a dataset, combined the cumulative effects of features distributions into a unified model that represents overall behavior of the fraudulent reviewers, and investigated the role of effective data pre-processing to improve detection accuracy.

TL;DR: The authors proposed an extended elaboration likelihood model for online review helpfulness, which integrates relevant quality indicators and sentiment features based on a circumplex model of affect, and empirically test the model using data sets from Amazon.com, Yelp.com , and Drugs.com .

TL;DR: In this article , the authors conceptualized and validated the concept of customer engagement with a social media post, proposing a research model which investigates the effects of popularity, discourse logic and argument frame on customer engagement on social media posts.

TL;DR: Li et al. as discussed by the authors presented a stock market forecasting model combining a multi-layer perceptron artificial neural network (MLP-ANN) with the traditional Altman Z-score model.

TL;DR: In this paper , a text-mining-based cyber-risk assessment and mitigation framework was proposed to identify expert hackers in online cyber-crime forums and their expertise in cyber-attacks.

TL;DR: In this paper , the authors investigate the behavior of coordinated accounts within a large set of retweet-based information cascades identifying key differences between coordinated and non-coordinated accounts in terms of position within the cascade, action delay and outreach.

TL;DR: In this paper , the authors investigated the differential roles of negative and positive reviews on the growth of independent and branded hotels and their underlying interplays, and they obtained several novel findings based on the resource-based view of firm growth and signaling theory.

TL;DR: In this article , a systematic review of the literature on fashion CMs with applications to decision-making in fashion retail supply chain is presented, mining topics for a research agenda, which could benefit distinct fashion stakeholders, not just customers.

TL;DR: In this article , the authors model how hierarchical privilege levels and non-hierarchical incentives serve as motivational goals to motivate knowledge contribution in online Q&A communities, and find that closeness to the next hierarchical privilege level has a curvilinear relationship with continued knowledge contribution.

TL;DR: In this article , the authors investigated how management control systems (MCS) aid in translating analytics capabilities (AC) generated insights into enhanced organizational competitiveness under conditions of environmental uncertainty, and provided interesting insights concerning the mechanisms through which AC can generate value and competitiveness.

TL;DR: In this paper , the authors combine evolutionary search algorithms, deep learning, and advanced model interpretation methods to develop a holistic exploratory-predictive-explanatory machine learning framework that can assist clinical decision-makers in reacting to the challenges of a pandemic in a timely manner.

TL;DR: In this paper , the authors use text mining tools to propose a method for rapid prioritization of online reviews, differentiating the reviews pertaining to innovation opportunities that are most useful for firms.

TL;DR: CATCHM as mentioned in this paper proposes a novel network-based credit card fraud detection method based on representation learning (RL), which can benefit fraud detection by avoiding manual feature engineering and explicitly considering the relational structure of transactions.

TL;DR: In this article , the authors presented an advanced network data envelopment analysis (NDEA) method to evaluate the sustainability and resilience of BSCs, including blood collection centers (BCCs), blood production centers (BPCs), and blood distribution centres (BDCs).

TL;DR: The concept of IT governance process capability is defined as the firm's ability to identify, design, implement and leverage the following IT governance processes: IT decision-making, IT planning, IT infrastructure modernization, IT services delivery, and IT monitoring as mentioned in this paper .

TL;DR: Wang et al. as mentioned in this paper built a three-level hierarchical promotion structure and evaluated the impact of different platform promotions on sales and conversion rate based on real-world transaction data from the largest online retailer in China, JD.com.

TL;DR: Wang et al. as mentioned in this paper used matrix decomposition based methods, random walk based methods and deep learning based methods to predict whether there is a new relationship between a pair of nodes or to discover hidden links in the network.

TL;DR: In this paper , the authors integrated the UGC and MGC literature and research of determinants of physical exercise to develop a comprehensive conceptual model to understand how consumers decide their engagement with free digital content delivered via social media channels.

TL;DR: In this paper , the authors proposed and evaluated a framework to extract features from event logs that capture the experience of the resources involved in a business process, such as experiential learning and social ties on the workplace.

TL;DR: In this article , the authors contextualize two important event impact factors (i.e., event criticality and event disruption) in the context of COVID-19 and examine their contingent roles in the effects of ITBA and BDAC on strategic decision-making.

TL;DR: In this article , a two-layer additive risk model is proposed, which is decomposable into subscales and each node in the first layer represents a meaningful subscale model, and all of the nonlinearities are transparent.

TL;DR: In this article , the credibility of online reviews in an intercultural context was investigated by building upon different theoretical frameworks and upon insights gained from an eye-tracking pre-study. But no other study has shed light on the effect of OR's presentation format by incorporating cross-national perspectives yet.

TL;DR: In this paper , a moderated moderation model was proposed to explore the interactive effect between sponsorship disclosure of positive reviews, emotional intensity, and tie strength on online review credibility and consumers' purchase intention.

TL;DR: In this article , the authors conduct a three-dimensional analysis of reviews from two popular mobile payment apps and uncover the sentiment and emotions captured in the review text, and the reactions in the emojis.