...Anjali Dimri; Pankaj Kumar; Deepshi Garg Purpose As artificial intelligence (AI) and machine learning (ML) technologies continue to revolutionize various industries, understanding their impact on job embeddedness becomes crucial. This study examine the role of AI and ML technologies on job...

...Ross Taylor; Masoud Fakhimi; Athina Ioannou; Konstantina Spanaki Purpose This study proposes an integrated Machine Learning and simulated framework for a personalized learning system. This framework aims to improve the integrity of the provided tasks, adapt to each student individually...

... the efficacy and productivity of PMS. Practical implications The implementation of new technologies such as Artificial intelligence (AI), machine learning and robotics etc. in PMS have also been analysed to give a sneak peak of the bigger future picture of AI and strategic human resource integration...

... an updated review on neuro-marketing and face recognition marketing. Hakim et al. (2021) develop a framework based on electroencephalography recordings and a machine-learning algorithm to gain a more in-depth understanding of the buying behavior pattern of customers. Neuro-marketing assists...

...Ujjwal Kanti Paul Purpose This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches. Design/methodology/approach The study used a two-stage approach...

... Licensed re-use rights only Employee attrition Human resource management Machine learning Triangulation Retention policies Employee attrition is defined as voluntary or involuntary departure of employees from an organization. There are several measures to examine how it affects...

... to compare the research of supply chain risks before and during the COVID-19 pandemic based on machining learning and text clustering and using the relevant publications of the web of science database. Findings The results show that scholars' attention to supply chain crisis has increased in the wake...

...Rajan Kumar Gangadhari; Vivek Khanzode; Shankar Murthy; Denis Dennehy Purpose This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum...

...Syed Asif Raza; Srikrishna Madhumohan Govindaluri; Mohammed Khurrum Bhutta Purpose This paper conducts a Systematic Literature Review (SLR) of Machine Learning (ML) in Supply Chain Management through bibliometric and network analysis, the authors are able to grasp key features of the contemporary...

..., revealed that only 7% of MBA graduates are employable (Assocham, 2016). Employability Predictive modeling Predictive analytics Management education Machine learning There are several competitive examinations in India, which is the first step for those who aspire to pursue an MBA. The popular...

...Mohammadreza Akbari; Thu Nguyen Anh Do Purpose This paper presents a review of the existing state-of-the-art literature on machine learning (ML) in logistics and supply chain management (LSCM) by analyzing the current literature, contemporary concepts, data and gaps and suggesting potential topics...

... was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels. Originality/value The use of machine learning applications introduces advanced strategies...