Promoting continuity of care in nurse-patient assignment: A multiple objective heuristic algorithm

2023 | Decision Support Systems | Citations: 0

Authors: Jiang, Haoqiang; Gomes, Paulo; Meer, Debra Vander

Abstract: Continuity of care is a critical element for delivering quality of care in inpat ... Expand

Abstract: 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 study investigates the relationship between continuity of care and workload balance in NPA decisions in hospital inpatient units. We develop an NPA heuristic to guide continuity-care assignment while addressing the trade-off with workload balance. The heuristic prioritizes higher-acuity patients to the objective of continuity of care, while assignment of lower acuity patients seeks to minimize workload imbalance. A discrete event simulation model of an inpatient hospital unit is used to evaluate how the heuristic addresses the tradeoff between the two objectives under distinct work design sce­ narios. The heuristic enables significant increases in continuity of care for specific patient segments while limiting the impact on workload balance. We discuss implications for theory and managerial practice. Collapse

Topics: accounting legal context decision support system personality decision support

Methods: simulation computational algorithm sensitivity analysis mixed-integer programming experiment

Personal use of technology at work: a literature review and a theoretical model for understanding how it affects employee job performance

2023 | European Journal of Information Systems | Citations: 0

Authors: Jiang, Hemin; Siponen, Mikko; Tsohou, Aggeliki

Abstract: Employee personal use of technology at work (PUTW) – defined as employees’ activ ... Expand

Abstract: Employee personal use of technology at work (PUTW) – defined as employees’ activities using organisational or personal IT resources for non-work-related purposes while at work – is increasingly common. Our review of existing PUTW studies (n = 137) suggests that previous studies widely discussed PUTW outcomes, antecedents, and policies. The literature review also indicates that previous studies proposed opposing viewpoints regarding the effect of PUTW on employee job performance, but few studies offered empirical evidence. Consequently, the conditions under which PUTW can increase or decrease employee job performance have not been discussed. We develop a theoretical model for increasing the understanding of this issue. Our model suggests that executive attention is an important underlying mechanism through which PUTW affects employee job performance. We further suggest the effect of PUTW on executive attention (and job performance) depends on PUTW behavioural characteristics in terms of four dimensions: PUTW cognitive load, PUTW arousal level, PUTW timing, and PUTW frequency/duration. The model can advance researchers’ understanding of the possible conditions under which PUTW may increase or decrease employee job performance. The model also offers new insights into existing studies on PUTW antecedents and policies. As a result, our proposed model provides new theoretical guidance for future studies on PUTW. Collapse

Topics: task productivity switching cost electronic commerce

Methods: theory development structured literature research literature study field study experience sampling

Can Conversations on Reddit Forecast Future Economic Uncertainty? An Interpretable Machine Learning Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: Jiang, Jinhang; Feng, Mei; Srinivasan, Karthik

Abstract: In recent years, social media has become an indispensable source of information ... Expand

Abstract: In recent years, social media has become an indispensable source of information through which public attitudes, opinions, and concerns can be studied and quantified. This paper proposes an interpretable machine learning framework for predicting the Equity Market-related Economic Uncertainty Index using features generated from a popular discussion forum on Reddit. Our framework consists of a series of custom preprocessing and analytics methods, including BERTopic for latent topic identification and regularized linear models. Using our framework, we evaluate explanatory models with different configurations over a large corpus of Reddit posts belonging to the personal finance category. Our analysis generates valuable insights about discussion topics on Reddit and their efficacy in accurately predicting future economic uncertainty. The study demonstrates the potential of using social media data and interpretable machine learning to inform economic forecasting research. Collapse

Topics: Reddit social media explainable artificial intelligence Python permutation feature importance

Methods: descriptive statistic time series analysis longitudinal research topic model experiment

Workers' Perceived Algorithmic Exploitation on Online Labor Platforms

2023 | International Conference on Information Systems | Citations: 0

Authors: Jiang, Jennifer; Lippert, Isabell; Alizadeh, Armin

Abstract: Online labor platforms (OLPs) like Uber have become increasingly prevalent, att ... Expand

Abstract: Online labor platforms (OLPs) like Uber have become increasingly prevalent, attracting numerous workers with the appeal of flexible work arrangements. OLPs present themselves as an innovative alternative to traditional employment structures, but there remains a sense of exploitation among their workers. This perception is impelled by the platforms' heavy reliance on algorithmic management (AM), which often exerts a tighter form of management than traditional human-led oversight. This study examines how AM induces workers' exploitation perceptions (i.e., perceived algorithmic exploitation) by conducting a grounded theory methodology on 22 interviews with Uber drivers. We identified several forms of perceived algorithmic exploitation (i.e., manipulation, falsification, disempowerment, and dependency), which include AM practices that workers perceive as disadvantaging them to the potential benefit of the OLP. Overall, this study contributes to the "dark side" of AM and offers platform providers and policymakers crucial insights to create more sustainable working environments for platform workers. Collapse

Topics: Uber platform worker ride sharing platform electronic mail decision making

Methods: qualitative interview computational algorithm qualitative coding grounded theory theoretical contribution

Theories: lemon market theory

COVERT RESISTANCE AGAINST ALGORITHMIC CONTROL ON ONLINE LABOR PLATFORMS – A SYSTEMATIC LITERATURE REVIEW

2023 | European Conference On Information Systems | Citations: 0

Authors: Jiang, Jennifer

Abstract: Online labor platforms (OLPs) such as Uber or Upwork heavily rely on algorithms ... Expand

Abstract: Online labor platforms (OLPs) such as Uber or Upwork heavily rely on algorithms instead of human managers to control workers' behavior. While algorithmic control (AC) allows platform providers to control their workers efficiently, it is often perceived by workers as a tighter control (compared to human-based control) which increases their motivation to resist. Especially covert resistance (i.e., workers' hard-to-observe oppositional actions) provides essential insights into how workers deal with AC that affect platforms' longevity. In this study, we conducted a systematic literature review to develop a theoretical framework showing how and why workers perform covert resistance against AC. Further, our analysis reveals the enabling role of sensemaking for diverse forms of covert resistance. Overall, our study expands the literature on AC by shedding light on the formation of workers' covert resistance. Therefore, we offer platform providers and policymakers crucial insights to create fairer working environments for workers under AC. Collapse

Topics: resistance to change sensemaking organizational control organizational change privacy

Methods: literature sample theory development computational algorithm structured literature research literature study

Review Moderation Transparency and Online Reviews: Evidence from a Natural Experiment

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Jiang, Lianlian (Dorothy); Ravichandran, T.; Kuruzovich, Jason

Abstract: This paper empirically investigates how review moderation transparency affects ... Expand

Abstract: This paper empirically investigates how review moderation transparency affects the volume, length, and negativity of reviews. A change to the Yelp platform in 2010, introducing review moderation and displaying filtered reviews, created a natural experiment. We used a panel dataset of online reviews from the same set of restaurants on both the Yelp and TripAdvisor platforms in a difference-in-differences (DID) model to test how review moderation transparency affected our outcome variables. We found that increasing review moderation transparency negatively affects review volume but positively affects review negativity. The results also indicate that providing review moderation transparency reduces review length, especially for reviews with positive sentiment. Our findings suggest that providing review moderation transparency induces users to invest less effort in review contributions, especially when they are submitting positive reviews. We discuss the theoretical and practical implications of these results as they relate to the design and use of online review platforms. Collapse

Topics: online review user behavior user-generated content digital platform application programming interface

Methods: longitudinal research difference in differences experimental group natural experiment descriptive statistic

Model-Based Cybersecurity Analysis

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Jiang, Yuning; Jeusfeld, Manfred A.; Ding, Jianguo; Sandahl, Elin

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical co ... Expand

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid. Collapse

Topics: IT security virtualization technology database system knowledge representation data center

Methods: reference modelling case study qualitative interview design artifact simulation

ICU Outcome Predictions Using Real-Time Signals with Wavelet-Transform-based Convolutional Neural Network

2023 | HICSS | Citations: 0

Authors: Jiang, Yiqun; Wang, Shaodong; Li, Qing; Zhang, Wenli

Abstract: Intensive care units (ICUs) serve patients with life-threatening conditions. The ... Expand

Abstract: Intensive care units (ICUs) serve patients with life-threatening conditions. The limited ICU resources cause severe economic and healthcare burdens worldwide. It is critical to conduct ICU outcome predictions at an early stage and promote efficient use of ICU resources. However, all the current prediction methods have limitations such as unsatisfactory accuracy and depending on resource-demanding laboratory tests or expert domain knowledge. In this research, we design a wavelet-transformed-based convolutional neural network, WTCNN, which only requires patients’ vital sign series and information at ICU admission for real-time ICU outcome predictions. The model is evaluated using a large real-world ICU database and outperforms state-of-art baselines on both ICU mortality and length-of-stay prediction tasks. We conduct LIME for model interpretation and prescriptive analysis. Our work provides an efficient tool for ICU outcome predictions, allowing healthcare providers to take action promptly on patients at risk and reduce the negative impacts on patient outcomes. Collapse

Topics: local interpretable model agnostic explanation database system missing data societal evaluation criteria healthcare data

Methods: machine learning longitudinal research time series analysis deep learning electrocardiography

A Collective Opinion Mechanism for Crowdfunding Recommendation

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Jin, Bih-Huang; Li, Yung-Ming; Kamolporn, Sanamlao

Abstract: ... Expand

Abstract: Collapse

Topics: crowdsourcing crowdfunding Twitter social network Python

Methods: sentiment analysis experiment topic model logistic regression parametric test

To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders

2023 | Information Systems Research | Citations: 0

Authors: Jin, Chen; Yang, Luyi; Hosanagar, Kartik

Abstract: Brushing—online merchants placing fake orders of their own products—has been a w ... Expand

Abstract: Brushing—online merchants placing fake orders of their own products—has been a widespread phenomenon on major e-commerce platforms. One key reason why merchants brush is that it boosts their rankings in search results. Products with higher sales volume are more likely to rank higher. Additionally, rankings matter because consumers face search frictions and narrow their attention to only the few products that show up at the top. Thus, fake orders can affect consumer choice. We focus on this search-ranking aspect of brushing and build a stylized model to understand merchants’ strategic brushing behavior as well as how it affects consumers. We consider a high-type merchant (who sells a more popular product) and a low-type merchant (who sells a less popular product) competing on an e-commerce platform where product rankings evolve over time. We find that if brushing gets more costly for merchants (e.g., due to stricter platform policies), it may sometimes surprisingly harm consumers as it may only blunt brushing by the high-type merchant but intensify brushing by the low-type merchant. If search is less costly for consumers (e.g., due to improved search technologies), it may not always benefit consumers, either. Moreover, the design of the ranking algorithm is critical: placing more weight on sales-volume-related factors may trigger a nonmonotone change in consumer welfare; tracking recent sales only as opposed to cumulative sales does not always dial down brushing and, in fact, may sometimes cause the low-type merchant to brush more.History: Ravi Bapna, Senior Editor; De Liu, Associate Editor.Funding: C. Jin gratefully acknowledges the Singapore Ministry of Education Academic Research Fund [Tier 1, Grant R-253-000-144-133], The Wharton School Dean’s Postdoctoral Research Fund, and Mack Institute Research Fund. All authors gratefully acknowledge the 2019 Networks, Electronic Commerce and Telecommunications Institute (NET) Summer Research Grant.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1128. Collapse

Topics: IS economics consumer surplus electronic commerce fake review electronic market

Methods: computational algorithm literature sample

Theories: economic search theory