Decision Support Systems最新文献

A metaverse is a three-dimensional virtual space (3D VS) where businesses and individuals worldwide can engage, interact, communicate, transact, and exchange information in real-time through an immersive and collaborative platform. These interactions can create complex relationships influenced by the decision-making processes of businesses. Such complexity can lead to challenges in maintaining relationships, ensuring exclusiveness, preventing misuse, and addressing other ethical issues. Therefore, this study aims to identify ethical principles within the metaverse to guide decision-making and maintain complex relationships between users and businesses. Both qualitative and quantitative data were collected for analysis, and simple random sampling was employed for primary data collection. The empirical analysis was conducted using a mixed-method approach. The study identified four ethical principles that guide complex relationships within the metaverse: business benefit evaluation, fairness, explainability, and reliability principles. These principles positively influence decision-making, which, in turn, positively affects the maintenance of complex relationships within 3D VS.

Mobile fitness apps have gained popularity as a way of improving healthy behaviors. This study investigates the design and influence of fitness apps from a novel “group” perspective, focusing on the effects of group-level social interaction features in exercise participation. Through empirical studies on a unique dataset, we propose and verify a conceptual framework that shows that (1) group role model inspiration and group comparison features facilitate the intra-group assimilation and inter-group contrast processes and further significantly improve group participation, and that (2) offline activities moderate the effects of group comparison features on group participation. This study contributes to the literature on online communities and fitness apps/service design by demonstrating the motivating power of group-level interactions and online–offline engagement. It also provides practical guidelines for fitness app developers.

Conceptual models are used to help professionals understand complex information systems and solve problems during systems analysis and design. Because single model often do not represent all relevant information, typically multiple models are used in combination. To design effective combinations of models, we propose a systematic approach that uses color highlighting to foreground overlapping concepts between multiple models to help readers identify corresponding information between models. We conducted two empirical studies – an online experiment and an eye-tracking experiment – to evaluate the cognitive efficacy of this approach. Our findings suggest that color highlighting can somewhat improve participants’ domain understanding but not the efficiency of problem-solving. Findings from the eye-tracking study suggest that the use of color can have both beneficial and harmful effects, depending on the extent of overlap.

Corporate information systems (IS) functions have become ever closer and more intertwined with firms' marketing functions. Marketing technology and e-commerce implementations require synergy between these functions, which has been reflected in the emergence of researchers and practitioners who can work at the intersection of these disciplines. This article utilizes a systematic literature review to understand this environment and to provide a forward-looking analysis of research at the intersection of IS and marketing. First, a business-focused introduction describes the motivation for the review and puts it into context. This is followed by a bibliographic analysis to select articles at this intersection. A semi-automated content analysis of the selected articles groups them into homogeneous research clusters and further analysis is used to develop cluster themes. This process sheds light on the potential areas of collaboration, offering an in-depth comprehension of their symbiotic relationship. A set of pathways for future research is described based on “collaboration areas” between IS and marketing. These areas, including consumer trust and decision making, social media, online reviews, mobile platforms & apps, and marketing channels, among others, represent the specific areas where marketing and IS overlap and mutually influence each other. Insights are presented on bridging academia and industry and suggestions are proposed for enhancing research at the junction of IS and marketing.

While many companies have benefited from online sales as their sole sales channel with the rapid growth of online retailing, this approach has limitations, especially for products that contain non-digital information and require a complementary service to fully attract customers. Sellers of these types of products are actively considering or have already adopted a multichannel strategy, which includes maintaining the existing online channel and opening physical brick-and-mortar stores. To stimulate sales, the service operator may consider offering a product bundle with the product manufacturer by providing subsidies to them. Decisions on product bundling could potentially facilitate or pose barriers to channel expansion. This study employs a game-theoretic model to explore the optimal pricing, multichannel and bundling strategies for a product manufacturer and a service operator who offer the core products with ancillary services in either bundled or non-bundled format. Our equilibrium analysis yields several insights. First, the manufacturer’s offline expansion allows customers who visit in-store to try and inspect the product, which raises not only the offline price but also the manufacturer’s online price. Interestingly, this price increase is more significant for the bundled format compared to the non-bundled format. Second, the bundling strategy influences the manufacturer’s decision to expand into multichannel operations. Specifically, product bundling incentivises multichannel expansion if the newly added physical stores can attract a significant number of new customers, indicating that demand spillover is significant. Conversely, product bundling may deter multichannel expansion if the online hassle cost is moderate.

Recently, a growing number of credibility assessment technologies (CATs) have been developed to assist human decision-making processes in evidence-based investigations, such as criminal investigations, financial fraud detection, and insurance claim verification. Despite the widespread adoption of CATs, it remains unclear how CAT and human biases interact during the evidence-collection procedure and affect the fairness of investigation outcomes. To address this gap, we develop a Bayesian framework to model CAT adoption and the iterative collection and interpretation of evidence in investigations. Based on the Bayesian framework, we further conduct simulations to examine how CATs affect investigation fairness with various configurations of evidence effectiveness, CAT effectiveness, human biases, technological biases, and decision stakes. We find that when investigators are unconscious of their own biases, CAT adoption generally increases the fairness of investigation outcomes if the CAT is more effective than evidence and less biased than the investigators. However, the CATs' positive influence on fairness diminishes as humans become aware of their own biases. Our results show that CATs' impact on decision fairness highly depends on various technological, human, and contextual factors. We further discuss the implications for CAT development, evaluation, and adoption based on our findings.

Online social networks have greatly facilitated the spread of information of all sorts. Meanwhile, the abundance of information in today's world also means different pieces of information will increasingly compete for people's finite attention. When different pieces of information spread together in an online social network, why would some become trendy while others fail to emerge? Existing research either models the diffusion of each piece of information independently, or fails to consider users' inactivity in online social networks. Modeling each piece of information as a meme, this paper addresses this gap by proposing a unified model for the co-diffusion of competing memes simultaneously spreading across an online social network. We are the first to identify a ubiquitous threshold for competing meme. The threshold also functions as an effective predictor that contributes to better performance in determining the outcome of meme competitions. Outcomes from this study have important implications for online campaigns and mobilizations as well as the fight against misinformation.

In the age of digital advertising, consumers are bombarded with an overwhelming number of advertisements from various channels every day. While repeated exposures to advertising can capture consumers' attention and stimulate their purchases, it is crucial to recognize that excessive advertising campaigns can cause consumer fatigue, diminished responsiveness, or even irritation. In the present study, our objective is to formulate the optimal advertising policy considering the effect of consumer ad fatigue. By introducing an attenuation factor that accounts for the negative impact of excessive advertising expenditure, we modify the dynamics of goodwill in the classical Nerlove-Arrow model. This modification results in the advertising response function exhibiting an inverted U-shaped curve with respect to the advertising expenditure. Our analysis indicates that when consumers experience ad fatigue, it is advisable for the firm to proportionally reduce its advertising expenditure in all time periods. However, the firm should maintain its original direction of trajectory of optimal advertising expenditure despite the presence of consumer ad fatigue.