Explainable artificial intelligence and agile decision-making in supply chain cyber resilience

Sadeghi R., Kiarash; Ojha, Divesh; Kaur, Puneet; Mahto, Raj V.; Dhir, Amandeep

doi:10.1016/j.dss.2024.114194

Cited by 12 publications

(2 citation statements)

References 58 publications

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“…Using the Natural Language Toolkit Python library, this paper utilized the Lemmatize method to reduce text complexity by converting all word cases to their root (e.g., caring to care and studies to study) [75]. Due to the inaccuracy of the stemming technique (e.g., caring to car), it was excluded in the data cleaning in this paper [76].…”

Section: Text Analysis: Studymentioning

confidence: 99%

A Multimethod Approach for Healthcare Information Sharing Systems: Text Analysis and Empirical Data

Malhan,

Pavur,

Pelton

et al. 2024

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This paper provides empirical evidence using two studies to explain the primary factors facilitating electronic health record (EHR) systems adoption through the lens of the resource advantage theory. We aim to address the following research questions: What are the main organizational antecedents of EHR implementation? What is the role of monitoring in EHR system implementation? What are the current themes and people’s attitudes toward EHR systems? This paper includes two empirical studies. Study 1 presents a research model based on data collected from four different archival datasets. Drawing upon the resource advantage theory, this paper uses archival data from 200 Texas hospitals, thus mitigating potential response bias and enhancing the validity of the findings. Study 2 includes a text analysis of 5154 textual data, sentiment analysis, and topic modeling. Study 1’s findings reveal that joint ventures and ownership are the two main enablers of adopting EHR systems in 200 Texas hospitals. Moreover, the results offer a moderating role of monitoring in strengthening the relationship between joint-venture capability and the implementation of EHR systems. Study 2’s results indicate a positive attitude toward EHR systems. The U.S. was unique in the sample due to its slower adoption of EHR systems than other developed countries. Physician burnout also emerged as a significant concern in the context of EHR adoption. Topic modeling identified three themes: training, healthcare interoperability, and organizational barriers. In a multimethod design, this paper contributes to prior work by offering two new EHR antecedents: hospital ownership and joint-venture capability. Moreover, this paper suggests that the monitoring mechanism moderates the adoption of EHR systems in Texas hospitals. Moreover, this paper contributes to prior EHR works by performing text analysis of textual data to carry out sentiment analysis and topic modeling.

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Section: Text Analysis: Studymentioning

confidence: 99%

A Multimethod Approach for Healthcare Information Sharing Systems: Text Analysis and Empirical Data

Malhan,

Pavur,

Pelton

et al. 2024

Information

View full text Add to dashboard Cite

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“…This makes it possible to identify serious diseases earlier and treat them more successfully. AI has transformed autonomous vehicles in the automotive sector, which can reduce traffic accidents and improve transit effectiveness (Alenizi et al, 2023;Mpatziakas et al, 2022;Sadeghi R. et al, 2024;Trzaska & Sus, 2023).…”

Section: Introductionmentioning

confidence: 99%

Development and Threats of Artificial Intelligence in Industry and Workforce

Alfiani

2024

IJSSR

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The abstract explores the transformative impact of Artificial Intelligence (AI) on global industries, highlighting its role in enhancing efficiency and innovation while also posing challenges such as job automation, skills gaps, data misuse, and ethical concerns. Drawing from the Global Risk Report 2024 and recent regulatory actions by the European Union and Indonesia, the abstract discusses the pressing need for AI governance. However, it lacks specificity in articulating the study's objectives and scope, and could benefit from providing concrete examples or statistics to support its claims. A clearer organizational structure and citation of relevant sources would enhance the coherence and credibility of the abstract. Furthermore, while emphasizing the importance of human control over AI, the abstract could offer a more nuanced conclusion that underscores the significance of the study's findings in achieving this goal.

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