Extending the theory of perceived risk, this study examines how risk perception, a vital factor in determining investment decisions, comprising both initiative risk statement generated by fundraisers and passive risk disclosure published by backers, influences crowdfunding financing performance. Utilizing a corpus of 126,593 innovative projects from Kickstarter, text analytics is employed to classify

Businesses and industries are placing a greater emphasis on information systems for cybersecurity decision-making due to the rising cybersecurity threat landscape and the critical need to protect their digital assets. Threat hunting provides a data-driven and proactive approach to cybersecurity, enabling organizations to efficiently detect, analyze, and respond to cyber threats in real-time. Despite

Enhancing a website's persuasiveness and improving users' satisfaction and intention are critical for companies and website designers. Based on the Fogg Behavior Model (FBM), this study explores the perspective of persuasive technology in the context of a website. We identify and design two types of persuasive features: a visual-preview feature and an information-sidedness feature. We propose that

Metaverse ecosystems are fast growing platforms which are witnessing wide adoption. Different digital platforms like social media are trying to evolve into metaverse ecosystems which are perceived to enhance the overall experiences of different users. However there is a lack of impactful empirical literature which have attempted to document diverse socio-technical perspectives surrounding these emerging

The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reliability of generated results and the credibility of contributing sources due to the limitations of traditional information retrieval algorithms and the LLM hallucination problem. We aim to transform LLM into a relevant, responsible

This editorial essay argues the design science decision support literature has unduly focused on developing technical systems when organizational problem solving and decision making often require socio-technical ones. Decision making in uncertain environments requires other aspects the technical view actively suppresses, such as effectiveness and innovation. We explore this in a three-step argument

Using empirical data from a third-party platform and a comprehensive public hospital (equipped with an official online healthcare platform) in China, this study employs a two-stage Heckman selection model and find that third-party online healthcare platforms (OHPs) should not be considered an obstacle to promoting official OHPs. Instead, doctors' activities on third-party OHPs increase the demand for

We consider a content market with an ad-supported content platform and a representative producer in the presence of altruistic consumers. The platform may launch different subsidy policies (i.e., a monetary subsidy based on the content demand that directly improves marginal profit or a traffic subsidy that directly improves content quality), and the producer creates content under two pricing strategies

Companies increasingly combine multiple media outlets when launching advertising campaigns. This study employs causal forest to examine the effects of complex multimedia campaigns. The model effectively corrects for selection bias, automatically identifies informative consumer features, and performs automated data-driven consumer segmentation based on the consumer features identified. We analyze a

Life event prediction is an important tool for customer relationship management (CRM), because life events shift customers’ preferences towards different products and services. Existing life event research mainly uses cross-sectional data, whereas in the CRM field, incorporating longitudinal data is increasingly common. Because longitudinal data can capture the dynamics of customer behavior, opportunities

Clustering for taxonomy-based archetype identification has become an established method in Information Systems (IS) research, aiding strategic decision-making across diverse research and business domains. However, the effectiveness of the approach depends critically on the compatibility of clustering methods and algorithms with the specific data characteristics. This study, based on a comprehensive

The metaverse is the next-generation Internet (Web3) that facilitates social connections and collaborations in a virtual world environment. Given the potential of the metaverse to provide more satisfying and effective means of remote collaborations, exploring the possibility of leveraging the metaverse for these endeavors is warranted. Therefore, an important question to address is whether greater

Artificial intelligence-powered chatbots capable of expressing emotions have gained significant popularity in the realm of customer service. Although previous studies have explored the impact of emotional expression in chatbots, there is a lack of understanding regarding the precise effects of different emotional cues. In this study, we drew upon social presence theory to investigate how different

Efficient team formation is critical to human resource management, particularly as large enterprise organizations continue to flatten and are increasingly driven by projects. Efficiently scheduling internal departments and reducing employee scheduling costs are essential objectives. This paper addresses the challenge of extracting employees from the existing network who possess the necessary skills

This paper presents a novel decision support system (DSS) to address the University Course Timetabling Problem (UCTP). The solution decomposes the NP-complete UCTP into two sub-problems, allowing a structured approach to addressing the complexities inherent in the UCTP process. A mixed integer linear programming (MILP) model is proposed to integrate academic year course schedule planning and instructor

Although previous studies have examined the relationship between Language Style Matching (LSM) and review helpfulness, little research has been devoted to exploring the underlying psychological mechanism of the effect. The current research was conducted to investigate the effect of LSM on review helpfulness, and to introduce perceived credibility as the psychological mechanism that explains the effect

This study investigates how NFT design features affect project performance. From the consumption perspective, NFT design features are divided into competency-related (image complexity, consistency) and investment-related (initial price, royalty). Using transaction data of 3297 NFT projects, we find that image complexity has an inverted U-shaped effect on long-term performance, while consistency boosts

Recommender systems play an important role in identifying and filtering relevant products based on the behaviours of users. Nevertheless, recommender systems suffer from the ‘cold-start’ problem, which occurs when no prior information about a new session or a user is available. Many approaches to solving the cold-start problem have been presented in the literature. However, there is still room for

The emergence of Industry 4.0, characterized by rapid technological change and fierce competition, challenges technology firms to make strategic innovation decisions. Central to this is the metaverse, a hybrid virtual space combining virtual reality, augmented reality, and the internet. Recognizing that the implications of metaverse applications extend beyond individual organizations, this research

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

We build upon the theoretical underpinnings of federated networks and adopt a socio-technical imaginaries perspective to envision the future of the Metaverse, informed by an understanding of the past and an assessment of the present. In doing so, we employ a two-step methodological approach that includes interviews with experts on Metaverse development, complemented by a historical analysis of archival

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

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

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

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

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

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

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

In customer service, emotional expressions by chatbots are considered a promising direction to improve customer experience. However, there is a lack of comprehensive understanding of how and when chatbots' emotional expressions improve customer attitudes. Although chatbots' emotional expressions of care and concern may feel inauthentic to customers in the inferential path, which can negatively affects

Multimorbidity, the presence of two or more chronic conditions within an individual, represents one of the most intricate challenges for global health systems. Traditional single-disease management often fails to address the multifaceted nature of multimorbidity. Network model emerges as a growing field for elucidating the interconnections among multimorbidity. However, the field lacks a standardized

We consider how to make dynamic pricing decision for Chinese Online (COL) at time-points, an online publisher that allow authors to sell their ongoing book projects. Instead of paying for a book, readers pay for each chapter (pay-per-chapter mode) of the ongoing book project. This mode allows readers to pay for as many chapters as they want without taking the risk that the releasing of new chapters

As a part of natural language processing (NLP), the intent of topic modeling is to identify topics in textual corpora with limited human input. Current topic modeling techniques, like Latent Dirichlet Allocation (LDA), are limited in the pre-processing steps and currently require human judgement, increasing analysis time and opportunities for error. The purpose of this research is to allay some of

The use of machine learning (ML) models in decision-making contexts, particularly those used in high-stakes decision-making, are fraught with issue and peril since a person – not a machine – must ultimately be held accountable for the consequences of decisions made using such systems. Machine learning explainability (MLX) promises to provide decision-makers with prediction-specific rationale, assuring

The conventional aggregated performance measure (i.e., mean squared error) with respect to the whole dataset would not provide desired safety and quality assurance for each individual prediction made by a machine learning model in risk-sensitive regression problems. In this paper, we propose an informative indicator to quantify model reliability for individual prediction (MRIP) for the purpose of safeguarding

We propose a novel curvature-based indicator constructed on log-price time series that captures an interplay between trend, acceleration, and volatility found relevant to quantify risks and improve trading strategies. We apply it to diagnose explosive bubble-like behaviors in cryptocurrency price time series and provide early warning signals of impending market shifts or increased volatility. This

The Common Vulnerability Scoring System (CVSS) is widely used in the cybersecurity industry to assess the severity of vulnerabilities. However, manual assessments and human error can lead to delays and inconsistencies. This study employs situational awareness theory to develop an automated decision support system, integrating perception, comprehension, and projection components to enhance effectiveness

In today's digital economy, virtually everything from products and services to political debates and cultural phenomena can spark WOM on social media. Analyzing online WOM poses at least three challenges. First, online WOM typically consists of unstructured data that can transform into myriad variables, necessitating effective dimension reduction. Second, online WOM is often continuous and dynamic

Successful attended home delivery (AHD) is the most important aspect of e-commerce order fulfillment. Prior literature focuses on incentive scheme development for customers' choices of delivery windows and predictive analytics for delivery results, but it is not clear whether the effect of AHD on the appointment date set by customers increases the success rate of AHD. Therefore, we developed an uplift

While many online platforms use incentive hierarchies to stimulate consumers to generate more online reviews, the extent to which these hierarchies influence reviewer behavior is not fully understood. This study, drawing on image motivation theory and consumer attention theory, takes a novel approach to investigate whether reviewers strategically adjust their review behavior after reaching higher ranks

A critical part of flow-based conceptual modeling, such as process modeling, is visualizing the logical and temporal sequence in which activities in a process should be completed. While there are established standards and recommendations, there is limited empirical research examining the influence of process model layout on model comprehension. To address this research gap, we conducted a controlled

This study investigates how organizations may increase innovation and productivity through the Metaverse environment efficacy (MVEE), Artificial intelligence usage (AIU), Internet of Things usage (IoTU), and Big Data Analytics usage (BDAU). The study gathers responses from the gaming, information technology, and entertainment industries, using a multi-method involving Partial Least Squares Structural

The restaurant industry has been slow to adopt analytics for the supply chain, operations, and demand forecasting, with limited research on this sector. The COVID-19 pandemic's significant impact on the restaurant industry, one of the hardest-hit sectors, has underscored the need for digital technologies and advanced analytics for managing supply chains and making operational decisions. This paper

In an era where user-generated content drives social media growth, effectively incentivizing contributions remains a challenge. This study explores the empirical impact of a crypto-integrated platform, Steemit, focusing on a system transition designed to enhance fairness in reward distribution. We assess how this shift affects user engagement, specifically through the volume of posts. Our findings

Are we more likely to believe a social media news story shared by someone with whom we have a strong or weak tie? We tend to trust close ties more than weak ties, but weak ties are sources of new information more often than strong ones. We conducted an online experiment to examine the effect of tie strength (strong ties vs. weak ties) on the decision to believe or not believe fake news stories. Participants

The unprecedented COVID-19 has led to the collapse of numerous businesses, notably within the tourism and hospitality sectors. Despite the burgeoning research on resilience, few studies have embraced a theoretical lens, particularly from a social network perspective. In addition, most extant resilience studies have not explicitly considered the geographic accessibility prerequisite inherent to tourism

Comparative online reviews have evolved into a vital instrument for consumers in decision-making, offering valuable comparisons and available options. Drawing on the insights from the linguistic category model (LCM) and elaboration likelihood model (ELM), we propose that different types (attribute-based and experience-based) of comparative reviews can affect consumers' perceived credibility of online

Live streaming has become increasingly popular in recent years. Viewers of live streaming channels can interact with live streamers through various behaviors, such as sending virtual gifts and Danmaku. It is very critical to accurately model such viewers' behaviors, which reflect their interest, for recommending live streaming channels. However, existing studies on live streaming channel recommendation

Live streaming commerce thrives with a rich tapestry of multimodal information that intertwines with various entities, including the anchor, the commodities, and the live streaming environment. Despite the wealth of data at hand, the synthesis and analysis of this information to predict sales remains a significant challenge. This study introduces a framework for multi-entity multimodal fusion, which

The emergence of online healthcare platforms has changed the competitive environment among physicians. However, little is known about how physicians can improve their performance in this new environment. Platforms also face challenges in comprehending the competitive mechanisms among physicians, which might hinder them from formulating strategic managerial decisions that foster sustained growth. In

Although algorithms are increasingly used to support professional tasks and routine decision-making, their opaque nature invites resistance and results in suboptimal use of their advice. Scholars argue for transparency to enhance the acceptability of algorithmic advice. However, current research is limited in understanding how improved transparency enhances the use of algorithmic advice, such as the

Cyber threat intelligence (CTI) researchers strive to uncover collaborations and emerging techniques within hacker networks. This study proposes an empirical approach to detect communities within hacker forums for CTI purposes. Eighteen algorithms are systematically evaluated, including state-of-the-art and benchmark methods for identifying overlapping and disjoint groups. Using discussions from five

Developing new products by multiple stakeholders is inclined to project delays and even failures due to complex risk propagation, calling for accurate predictions of varying risk states and stakeholders' potential response actions. This study proposes an adaptive simulation-based decision support approach, starting with an adaptive simulation model capable of generating future intervention actions

This paper examines video games, a form of digital innovation, and seeks to predict a successful game based on the composition of game development team members. Team composition is measured with observable features generated from a graph network based on development team information derived from individual team member work on previous games. Features include network features, such as team member closeness

Information on firms' sustainability often partly resides in unstructured data published, for instance, in annual reports, news, and transcripts of earnings calls. In recent years, researchers and practitioners have started to extract information from these data sources using a broad range of natural language processing (NLP) methods. While there is much to be gained from these endeavors, studies that

Competitive intelligence is vital for enterprises to survive in the market. Recently, online reviews have gained popularity among enterprises and researchers as a means to acquire timely and precise competitive insights. However, extant studies overlook the evolution of competitive information because they do not account for the variation of online reviews and products. In this research, we propose

Biometric authentication has become ubiquitous and profoundly impacts decision-making for both individuals and firms. Despite its extensive implementation, there is a discernible knowledge gap in understanding the nuanced influence of biometric characteristics on user security behaviors. To advance this line of research, we embrace the controversial information technology framework to delve into the

The popularity of online mobile trading has led to an increase in the development of mobile stock trading applications. Despite this increase in popularity, there is a dearth of empirical studies that examine the factors influencing the continued usage intention of these applications (hereafter, apps). Drawing on stimulus-organism-response (S-O-R) theory, this paper investigates the features of stock

Product seeding, defined as the act by which firms send products to selected customers and encourage them to spread word of mouth, is a critical decision support strategy for the success of new products. Using multiple agent-based simulation techniques, we investigated the relative importance of three widely adopted seeding strategies (seeding influentials, early adopters, and random targets) in a