[HTML][HTML] Machine learning, knowledge risk, and principal-agent problems in automated trading

C Borch - Technology in society, 2022 - Elsevier
Present-day securities trading is dominated by fully automated algorithms. These algorithmic
systems are characterized by particular forms of knowledge risk (adverse effects relating to …

An evaluation framework of IT‐enabled service‐oriented manufacturing

Y Sun, Y He, H Yu, H Wang - Systems Research and …, 2022 - Wiley Online Library
Abstract Service‐oriented manufacturing (SOM) strategy is a new manufacturing mode by
integrating servitization with the traditional manufacturing industry. As a vital paradigm of …

[HTML][HTML] Assessment of Personal Values for Data-Driven Human Resource Management

T Kimura - Data Science Journal, 2023 - datascience.codata.org
Business organizations have introduced data analytics to human resource management
(HRM) to predict employee behavior in recent years. This practice is called HR analytics …

[HTML][HTML] Effective machine learning, Meta-heuristic algorithms and multi-criteria decision making to minimizing human resource turnover

N Pourkhodabakhsh, MM Mamoudan… - Applied Intelligence, 2023 - Springer
Employee turnover is one of the most important issues in human resource management,
which is a combination of soft and hard skills. This makes it difficult for managers to make …

Identification of potential biomarkers in stomach adenocarcinoma using machine learning approaches

E Nazari, G Pourali, M Khazaei, A Asadnia… - Current …, 2023 - ingentaconnect.com
Background: Stomach adenocarcinoma (STAD) is a common cancer with poor clinical
outcomes globally. Due to a lack of early diagnostic markers of disease, the majority of …

Towards a paradigm shift: how can machine learning extend the boundaries of quantitative management scholarship?

D Valizade, F Schulz, C Nicoara - British Journal of …, 2024 - Wiley Online Library
Management scholarship is beginning to grapple with the growing popularity of machine
learning (ML) as an analytical tool. While quantitative research in our discipline remains …

[HTML][HTML] An ensemble learning model for predicting the intention to quit among employees using classification algorithms

AK Biswas, R Seethalakshmi, P Mariappan… - Decision Analytics …, 2023 - Elsevier
Employees are often more likely to use social media for job searching, which sometimes
causes withdrawal behaviour. This study proposes an ensemble learning model for …

Drilling down artificial intelligence in entrepreneurial management: A bibliometric perspective

X Li, Y Long, M Fan, Y Chen - Systems Research and …, 2022 - Wiley Online Library
Artificial intelligence (AI) has been adopted in entrepreneurial practices and generates huge
economic benefits. It creates a number of digital start‐ups and changes the way in which …

Comparative Analysis of Entropy Weight Method and C5 Classifier for Predicting Employee Churn

M Chaudhary, L Gaur… - 2022 3rd International …, 2022 - ieeexplore.ieee.org
As per Aon, three out of four employees leave voluntarily, hence making employee churn
(EC) a key issue that has an adverse impact on the productivity and growth of the …

Analysis and classification of employee attrition and absenteeism in industry: A sequential pattern mining-based methodology

MS Nawaz, MZ Nawaz, P Fournier-Viger, JM Luna - Computers in Industry, 2024 - Elsevier
Employee attrition and absenteeism are major problems that affect many industries and
organizations, resulting in diminished productivity, elevated costs, and losses. These …