Colorectal cancer (CRC) is the third most common cancer in terms of the number of cases and deaths in men and women in the USA. According to the Centers for Disease Control and Prevention, the CRC screening compliance rate remains low in the United States. It is even more concerning that the number of cases and deaths due to CRC is increasing in the younger population, for which there is no guideline

Digital platforms have emerged as an important technology underpinning the new economy. A key problem in such platforms concerns provisioning decisions for customer-service requests, in order to maximize the provider's revenue subject to resource availability. Provisioning is important to meet customer needs, and in turn, for customer retention. The service provisioning problem, in addition to being

The cyber security industry is rapidly adopting threat hunting as a proactive tool for early and faster detection of suspected malicious actors. In this paper, we propose a machine learning-based method, Unsupervised Hunting of Anomalous Commands (UHAC), to detect text-based anomalous commands in security information and event management (SIEM) logs that are good candidates for threat hunting. A unique

Continuity of care is a critical element for delivering quality of care in inpatient units, however it has rarely been considered in nurse-patient assignment (NPA) models. The nursing literature suggests that continuity of care helps reduce medical errors and readmissions and increases patient satisfaction. Balancing patient assignments to nursing staff is also critical to avoid overwork and burnout

This paper presents an assessment of the Chinese healthcare system in 31 provinces for a 10-year period in light of relevant physical and human resource variables. First, a novel TEA-IS (Trigonometric Envelopment Analysis for Ideal Solutions) model is developed to assess healthcare efficiency at the province level. Machine learning methods are also employed to predict high-low performance and the synergistic

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Financial statement fraud caused by listed companies directly jeopardizes the reliability the financial reporting process. Leveraging multimodal information for financial statement fraud detection (FSFD) has recently become of great interest to academic research and industrial applications. Unfortunately, the predictive ability of multimodal information in FSFD remains largely underexplored, particularly

Information systems (IS) projects are notoriously difficult to control, especially under conditions of uncertainty. This difficulty is particularly pronounced for senior IS managers, such as CIOs and IT Vice Presidents, who tend to have scarce time and limited project-related knowledge but are ultimately held accountable for IS project performance. Focusing on this under-researched controller category

What is the optimal size for online groups that use electronic communication and collaboration tools? Previous research typically suggested optimal group sizes of about 5 to 7 members, but this research predominantly examined in-person groups. Here we investigate online groups whose members communicate with each other using two electronic collaboration tools: text chat and shared editing. Unlike previous

Modern cyberattacks such as advanced persistent threats have become sophisticated. Hackers can stay undetected for an extended time and defenders do not have sufficient countermeasures to prevent advanced cyberattacks. Reflecting on this phenomenon, we propose a game-theoretic model to analyze strategic decisions made by a hacker and a defender in equilibrium. In our game model, the hacker launches

With society's wide-scale adoption of information technology, significant information about borrowers is distributed across various parties, information that can be jointly used to improve credit scoring. However, use of such information faces many challenges, such as the problems of preserving privacy and information redundancy. To address these challenges in leveraging multi-source information for

Ensuring the credibility of online consumer reviews (OCRs) is a growing societal concern. However, the problem of fake reviewers on online platforms significantly influences e-commerce authenticity and consumer trust. Existing studies for fake reviewer detection mainly focus on deriving novel behavioral and linguistic features. These features require extensive human labor and expertise, placing a heavy

The Proof-of-Stake (PoS) protocol is booming in blockchain networks because of excessive energy consumption and slow block generation associated with the Proof-of-Work (PoW) protocol. In terms of transaction settlement, does the PoS protocol perform better than PoW? We build a transaction settlement model based on the PoS blockchain, describing how the staking income and costs affect settlement performance

Effective and rapid triaging from primary care into secondary care plays a pivotal role in providing patients with timely treatment and managing increasing demands for healthcare resources. Existing triaging methods from primary care to secondary care are labor-intensive processes that involve manually reviewing referral data from multiple sources and can cause long referral to treatment time. There

Physician Review Websites (PRWs) help users select physicians by providing both structured and unstructured data on physicians and patients' experiences with physicians. In this paper, the adequacy of the available information on PRWs is investigated. An empirical study is conducted to understand the information that patients seek from PRWs through a survey instrument administered to 344 patients.

Design science research addresses important, complex real-world problems. Although well-accepted as part of research in information systems, initiating or progressing a design science research project still requires effort to describe how knowledge creation emerges and its underlying dynamics. Given the existing body of knowledge on design science research, it should be possible to learn from that

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The over-the-top (OTT) industry has witnessed remarkable growth in recent years with a sharp increase in the number of subscribers, leading to increased competition among OTT platforms to acquire movie rights. Consequently, the gap between the theatrical and OTT releases has been diminishing over the last few years. An early release of a movie on an OTT platform fetches a higher distribution fee for

Can you make profits by trading on corporate disclosures using machine learning? In this study, we aim to obtain a conservative estimate of profitability, while accounting for the combination of several important real-world aspects. Specifically, we consider the holistic research problem that combines model predictions based on the textual content of corporate disclosures and trading strategies while

The proliferation of variable renewable energy increases the significance of reserve markets, which provide energy flexibility to compensate for supply–demand mismatches on short notice. Accordingly, market regulators in different locations have been continuously adopting different mechanisms to attract flexible sources, such as batteries to participate in reserve markets. While these mechanisms are

A key group decision making task is to aggregate individual preferences. Conventional group decision methods adopt pre-defined and fixed strategies to aggregate individuals' preferences, which can be ineffective due to the varying importance and influence of individual group members. Recent studies have proposed to assign different weights to individual members automatically based on the level of consistency

Although recent developments in Artificial Intelligence (AI) and machine learning (ML) aim to enhance the fairness and transparency of decision-making systems, research has found that neural networks (or other similar AI techniques) are still effected by human cognitive biases due to the training datasets. In this study, we focus on order effects, i.e., when the input of information impacts human perception

Due to the rapid growth of social media and mobile devices, social apps have become deeply integrated into people's lives. Extensive adoption of social apps entails the collection of massive amounts of users' private information, causing serious privacy issues. To protect their privacy, in practice, social app users are quite likely to disclose false information (i.e., to engage in misrepresentation

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Business processes are a key driver of organizational success, which is why business process improvement (BPI) is a central activity of business process management. Despite an abundance of approaches, BPI as a creative task is time-consuming and labour-intensive. Most importantly, its level of computational support is low. The few computational BPI approaches hardly leverage the opportunities brought

Online mail order and online retail purchases have increased rapidly in recent years worldwide, with Covid-19 forcing almost all non-grocery shopping to move online. These practices have facilitated the availability of new data sources, such as web behavioural variables providing scope for innovation in credit risk analysis and decision practices. This paper examines new web browsing variables and

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With the rapid development of mobile devices, spatial crowdsourcing has become an important way to collect data. Task assignment is an important aspect of spatial crowdsourcing. How to improve the quality of the results and decrease the travel distance has been extensively studied in recent years. Existing studies often assume that moving speed is constant or real-time road network information is known

Pay-for-performance (P4P) schemes are implemented to incentivize or penalize hospitals for their safe caregiving. Given that health information technology (HIT) results in better healthcare outcomes, P4P schemes are expected to promote hospital HIT adoption. However, P4P schemes could also discourage hospitals from adopting HIT because they may take away resources initially allocated for HIT adoption

Although previous studies indicate the critical role of collaborative commerce (c-commerce) adoption and dynamic capability in the supply chain process, they have not addressed the relationship between c-commerce behavior and dynamic capability. By adopting the commitment-trust theory and the dynamic capability view, this study empirically examines the effects of relationship quality, c-commerce behavior

Priming is challenging when consumers start shortlisting products before the final purchase. This is because this shortlisting process is performed in multiple user sessions online across time, the shortlist does not stay as a static list, and product comparison in this stage uses the heuristics internal to individual consumers. The goal of this study is two folds: (1) to approximate user heuristics

Advanced fraud detection systems leverage the digital traces from (credit-card) transactions to detect fraudulent activity in future transactions. Recent research in fraud detection has focused primarily on data analytics combined with manual feature engineering, which is tedious, expensive and requires considerable domain expertise. Furthermore, transactions are often examined in isolation, disregarding

Extracting useful knowledge from multimodal data is the core of many multimedia applications, such as recommendation systems, and cross-modal retrieval. In this paper, we propose a label-based multimodal topic (LB-MMT) model to jointly model text and image data tagged with multiple labels. Specifically, we use the labels as supervised information to generate the text and image data. In the LB-MMT model

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In Cognitive Fit Theory (CFT) based research, there is a consensus about cognitive effort as the underlying mechanism impacting performance. Although critical to the theory, cognitive effort and its direct empirical assessment remain a challenge. In this repeated measures experimental study, we introduce a research model and develop hypotheses based on the fundamental relationships underlying CFT while

This study examines the dynamic stages of exploration and exploitation efforts by organizations in their cybersecurity responses using multistate modeling. Using textual data from the annual 10-K reports of S&P 100 organizations, this study uses a combination of text analytics and Markov chain approach to quantify exploration and exploitation in organizational cybersecurity responses. The study models

Information overload often makes it difficult for consumers to identify valuable online reviews through the traditional “helpful votes” button in the big data era, so it is essential to locate helpful reviews. Unlike the existing efforts that often measure online reviews’ helpfulness one-sidedly, this study takes the intrinsic helpfulness (IH) and extrinsic helpfulness (EH) into account, and the intrinsic-extrinsic

Over the past few decades, the strategies to perform energy systems analysis have evolved into multiple criteria-based frameworks. However, there still remains a lack of guidance on how to select the most suitable Multiple Criteria Decision Analysis (MCDA) method. These methods provide different decision recommendations for the Decision Makers, including ranking, sorting, choice, and clustering of

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Phishing attacks pose substantial threats to the security of individuals and organizations. Although current anti-phishing tools achieve high accuracy rates and present a potential solution to this problem, users are often reluctant to rely on the predictions of these competent tools. However, we continue to lack a means of resolving this reluctance—or even an explanation for it. To address this need

We offer theory and evidence regarding the impact of content ideology (i.e., emotionally charged beliefs expressed in sentiments) on opinion polarization (i.e., conflicting attitudes about an event) on social media. Specifically, we consider the moderating role of functional affordances and symbolic expressions to draw inferences about opinion polarization. From a sentiment analysis of 3600 posts and

In the recent past, several studies have empirically compared the effectiveness of two or more online marketing channels in influencing consumer behavior. While some of these studies have found that the effectiveness tends to vary across channels, at a conceptual level, there is no clear understanding of why such consumer differences exist. There is, therefore, an urgent need to develop a conceptual

As a mainstream advertising channel, Search Engine Advertising (SEA) has a huge business impact and attracts a plethora of attention from both academia and industry. One important goal of SEA is to increase sales. Nevertheless, while previous research has studied multiple factors that are potentially related to the outcome of SEA campaigns, effects of these factors on actual sales generated by SEA

Online crowdfunding platforms offer a valuable channel to raise funding for various philanthropic causes, and fundraisers need to understand how to present campaign appeals to motivate charity giving decisions. This study examines the relationship between multi-modal emotion expression in campaign messages and charity crowdfunding success. Specifically, we explore the interaction of two modalities

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Although projects are regularly exposed to disruptive events, the literature lacks an effective measurement system for project resilience. This gap presents challenges for decision makers because of the consequent lack of quantitative information about the level of resilience and its impact on project performance throughout a project's life. We argue that managers can be supported by a priori information

Analyzing adverse drug events (ADEs) is an integral part of drug safety monitoring, which plays a significant role in medication decision-making. The increasing prevalence of health-related social media may provide an avenue for drug safety profiling using patients' online posts. Recent advances in machine learning, especially in deep learning, have dramatically benefited ADE detection and extraction

The COVID-19 pandemic and the lockdown bore a devastating impact on organizations across the globe. In this crisis, organizations belonged to the victim cluster, with a low crisis responsibility. Nevertheless, organizations needed to strategize their crisis responses and communicate with stakeholders to reduce the threat to reputational capital and manage stakeholder reactions in the pandemic. In this

While browsing through an online video platform, potential viewers decide which videos to click and watch based on the information and impression they obtain from thumbnails. Therefore, a thumbnail needs to be able to tell potential viewers what the video is about (i.e., be informative), and at the same time, a thumbnail needs to grab potential viewers' attention (i.e., be visually appealing). Drawing

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We explore the effects of coordinated users (i.e., users characterized by an unexpected, suspicious, or exceptional similarity) in information spreading on Twitter by quantifying the efficacy of their tactics in deceiving feed algorithms to maximize information outreach. In particular, we investigate the behavior of coordinated accounts within a large set of retweet-based information cascades identifying

Phishing attacks rate as one of the most prevalent security threats to contemporary organizations. Hence, managers strive heavily to apply security measures that keep their employees safe from these risks, thereby relying on insights from security researchers who have predominantly focused on recipient characteristics, message attributes, and interventions to explicate the phishing susceptibility of

To target crowding at locations, decision support systems (DSS) increasingly feature crowding information (CI) to indicate how much of a location's available capacity is occupied. Yet, little is known about how and why the timeliness of such CI (e.g., “updated just now”) influences users' selections of differently crowded locations and the effectiveness of location recommendations. Addressing this

Customers in cloud spot market choose from a set of computing resources (spot instances) some of which are same along one or more of the dimensions of hardware configuration, hardware capacity, software, and location (or zones within the same region). While prior research in IS has shown that cloud market consumers do not substitute identical spot instances across distant locations or regions due to

The COVID-19 pandemic led to a great deal of financial uncertainty in the stock market. An initial drop in March 2020 was followed by unexpected rapid growth over 2021. Therefore, financial risk forecasting continues to be a central issue in financial planning, dealing with new types of uncertainty. This paper presents a stock market forecasting model combining a multi-layer perceptron artificial neural

Using a large-scale panel of U.S. hospitals across health referral regions (HRRs), we empirically examine how a hospital's and its neighboring hospitals' adoption of the Clinical Decision Support System (CDSS) (and their meaningful use of CDSS) affects the hospital's quality of care. We find that CDSS adoption significantly reduces a hospital's readmission rate of heart failure, acute myocardial infarction

Depression is a leading mental health problem affecting 300 million people globally. Recent studies show that social networks provide a tremendous potential for mental health professionals as a source of supplemental information about their patients. This study presents a methodological framework for clinical decision support systems (CDSSs) through analysis of social network data to distinguish the

Debt collection is a very important business application of predictive analytics. This task consists of foreseeing repayment chances of late payers. In this sense, contact centers have a central role in debt collection since it improves profitability by turning monetary losses into a direct benefit to banks and other financial institutions. In this paper, we study the influence of contact center variables