• IUJ Journal of Management

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  • SJIF Impact Factor (2022): 7.458

    The IUJ Journal of Management

    The IUJ Journal of Management (IUJ-JOM) is the flagship journal of ICFAI University Jharkhand, Ranchi. The aim of the journal is to provide insight into the business and management research. It also creates a platform for the researchers, academicians, professors, practicing management professionals and proponents in disseminating original,

    theoretical and applied research in the field of management and allied disciplines. The Journal is a Bi-Annual, . . . . .Read more.

    ISSN NO : 2347 - 5080 Journal EOI : 10.11224/IUJ

  • SJIF Impact Factor (2022): 7.458

    Convolutions in Ophthalmic - Based Entrepreneurial Decisions: Research Agend

    Exploration on complex decision making has extended from complex decision behaviourist approach to cognitive approach that focuses on complex decision processes that ensue prior to response. In neural computational simulations, each complex decision during complex decision task is represented by node of neural activity. Read more.

    ISSN NO : 2347 - 5080 Journal EOI: eoi.citefactor.org/12.11224/IUJ.12.02.03

  • SJIF Impact Factor (2022): 7.458

    Farmers Producer Organization Scheme by NABARD: Need for an Ecosystem of support for Rural Entrepreneurship in Jharkhand

    Jharkhand (“Bushland” or “land of forest”) is an under developed state in India, which includes twenty four districts and shared its border with five states. Read more.

    ISSN NO : 2347 - 5080 Journal EOI: eoi.citefactor.org/12.11224/IUJ.12.02.01

  • SJIF Impact Factor (2022): 7.458

    Data Privacy Concerns in AI and HRM

    The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) practices offers significant potential for efficiency and improved decision-making. Read more.

    ISSN NO : 2347 - 5080 Journal EOI: eoi.citefactor.org/12.11224/IUJ.12.02.05

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Farmers Producer Organization Scheme by NABARD: Need for an Ecosystem of support for Rural Entrepreneurship in Jharkhand

Dr. Dilip Kumar, Prof. P.V. Rajeev

Keywords : : Jharkhand,agriculture, allied sector,tribal population

EOI : eoi.citefactor.org/12.11224/IUJ.12.02.01

[Abstract]
Jharkhand (“Bushland” or “land of forest”) is an under developed state in India, which includes twenty four districts and shared its border with five states. It was the 28th of state of India which formed on 15 November, 2000 after a long standing tribal movement for statehood. It was earlier part of Bihar; specifically it was the south Bihar, a highly mineral rich area with a generous tribal population. As per census 2011, Jharkhand has population of 33 million, literacy rate 66.41% in which male rate was 76.84% and female literacy rate 55.42%. The unemployment rate of Jharkhand is 3.1% as against national rate of 2.7% which is alarming signal for the government to think over it. Jamtara is the most backward district in Jharkhand, which was created by separating from Dumka district. It is also nick named as phishing capital of India. It has an area of 1811sq.km with population 7, 91,042 and mainly Hindi and Santali speaking people are living. It is one the important district for the agriculture and allied sector in Jharkhand.
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Citation Text :
Dr. Dilip Kumar, Assistant Professor, Faculty of Management Studies, GNSU, Sasaram, Rohtas, Bihar Email- dilip.kumar@gnsu.ac.in

Prof. P.V. Rajeev, Professor, Institute of Management Studies, BHU, Varanasi, U.P. Email- rajeev285@gmail.com

Adapted Neuromanagement And Integral Methodology

Col. Prof. Dr. J Satpathy, Prof. Dr. S. Sandhya, Prof. Dr. P. S. Aithal

Keywords : Adapted Neuromanagement, Neuro-Integral Methodology, 3600 Evaluation, Neurofeedback and Intervention

EOI : eoi.citefactor.org/12.11224/IUJ.12.02.02

[Abstract]
With the advent of Management and Technology, the World is witnessing a plethora of problems; mental issues occupying the prime spot. This provides an opportunity for the discipline of adaptive neuromanagement and integrated methodologies to offer a ‘way out’; for those afflicted with mental issues. Based on the protocol evaluations obtained through Adapted Neuromanagement, this paper applies a variety of personalized intervention techniques oriented from the neurointegral methodology. These techniques include; intervention with neurofeedback and biofeedback, personalized training programs to improve neuronal and physiological self-regulation. mindfulness and relaxation techniques, implementation of specific protocols to reduce stress and improve attention, adapted to individual needs virtual reality exposure therapy, development and application of personalized scenarios to treat phobias, anxiety and ptsd, cognitive performance training based on computational interface, implementation of adaptive programs to improve specific executive and cognitive functions, based on the individual neurocognitive profile, qualitative neuropsychological training, implementation of rehabilitation and neuropsychological correction programs aimed at improving the psychological and brain functioning of people, emotional freedom techniques, application of emotional reprocessing protocols to improve self-regulation, adapted to specific emotional needs, guided neuroplasticity interventions, application of cognitive stimulation techniques designed to promote neuroplasticity in specific brain areas, character strengths program, implementation of psychological well-being management programs based on scientific evidence and personalized neuromanagement education.

Exploration on complex decision making has extended from complex decision behaviourist approach to cognitive approach that focuses on complex decision processes that ensue prior to response. In neural computational simulations, each complex decision during complex decision task is represented by node of neural activity. Complex decision related neural activity has components of intensification of activity and complex decision inception for neural activity to overcome for complex decision to be completed. One way to investigate computational complex decision making is to scan positioning of complex decision behaviour leading to judgment point. Eye movements are central measure of complex decision. Eye movements are indissolubly linked to optical consideration as both are prime tools for choosing stimulating shares of chromatic prospects for enriched perceptual and rational processing. Investigating eye movements is expedient in providing evidence of orientation of complex decision behaviour replicating computational complex decision during complex decision formation. Role of eye movements, intentional or reflex, help in gaining, possessing and tracing visual inducements, during complex decision formation is not entirely clear. Current proof suggests that orientation of eye movement itself may not be an essential constituent. Rather, it can be as a result of intensification in contact to incitement as an e influential factor in complex decision formation. Purpose of present scholarship is to survey foregoing conclusions that eye movements have contributory stimulus on complex decision formation in a rational fashion. We review experiential studies that employ eye movement monitoring as process tracing and tracking method with gazing in complex decision - making research. Using Kowler model, we present an investigation that explains experimental methods and analysis with contemporary eye tracking savoir-faire. This proposal countenances a specific hypothesis about role of eye movements in complex decision; understanding how eye movements are premeditated, carried out notwithstanding recurrent vicissitudes in optical assortment that eye movement harvest. One major effort is understanding how should complex decision makers’ decide, deal with risks and uncertainties, create options better than originally available, potential responses to problems and evaluate strengths and weaknesses of each prospective action using apparatus of eye tracking / tracing and gazing.

Universities and colleges must recognize that, in pursuit of their primary goals of teaching and research, they must also take into account their obligations to society and the environment. However, a detailed investigation of how faculties perceive their college/university social responsibility is still lacking. This research investigates the perceptions of faculty members in business schools regarding corporate social responsibility (CSR) endeavors. Gender, age, income, marital status, years of experience, and education are the demographic variables considered in the study. The study was conducted among 298 faculty members from all over Nepal. The findings reveal that faculties, in general, have favorable attitudes towards their university social responsibility initiatives. At the same time, female faculty, in general, have more positive attitudes toward university social responsibility initiatives in Nepal compared to their male counterparts. Furthermore, the results demonstrate that there is no significant difference in CSR perception among faculty members based on their length of service, income, age, education, and marital status. The insights gained in this chapter shed light on how CSR is perceived within universities and colleges by their staff, offering a valuable starting point for defining or reevaluating strategies related to CSR in business school settings.
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Citation Text :
Col. Prof. Dr. J Satpathy, Post - Doc Fellow, Poornaprajna Institute of Scientific Research, Bengaluru, India Email: jyotisatpathy@gmail.com

Prof. Dr. S. Sandhya, Post - Doc Fellow, Poornaprajna Institute of Scientific Research, Bengaluru, India

Prof. Dr. P. S. Aithal, Director, Poornaprajna Institute of Management, Udipi, India

Convolutions in Ophthalmic - Based Entrepreneurial Decisions: Research Agenda

Prof. Dr. S. Sandhya,Col. Prof. Dr. J Satpathy,Prof. Dr. P. S. Aithal

Keywords : Complex Decision, Eye Movements, Kowler Model, Optical Assortment, Eye Tracking / Tracing and Eye Gazing

EOI : eoi.citefactor.org/12.11224/IUJ.12.02.03

[Abstract]
Exploration on complex decision making has extended from complex decision behaviourist approach to cognitive approach that focuses on complex decision processes that ensue prior to response. In neural computational simulations, each complex decision during complex decision task is represented by node of neural activity. Complex decision related neural activity has components of intensification of activity and complex decision inception for neural activity to overcome for complex decision to be completed. One way to investigate computational complex decision making is to scan positioning of complex decision behaviour leading to judgment point. Eye movements are central measure of complex decision. Eye movements are indissolubly linked to optical consideration as both are prime tools for choosing stimulating shares of chromatic prospects for enriched perceptual and rational processing. Investigating eye movements is expedient in providing evidence of orientation of complex decision behaviour replicating computational complex decision during complex decision formation. Role of eye movements, intentional or reflex, help in gaining, possessing and tracing visual inducements, during complex decision formation is not entirely clear. Current proof suggests that orientation of eye movement itself may not be an essential constituent. Rather, it can be as a result of intensification in contact to incitement as an e influential factor in complex decision formation. Purpose of present scholarship is to survey foregoing conclusions that eye movements have contributory stimulus on complex decision formation in a rational fashion. We review experiential studies that employ eye movement monitoring as process tracing and tracking method with gazing in complex decision - making research. Using Kowler model, we present an investigation that explains experimental methods and analysis with contemporary eye tracking savoir-faire. This proposal countenances a specific hypothesis about role of eye movements in complex decision; understanding how eye movements are premeditated, carried out notwithstanding recurrent vicissitudes in optical assortment that eye movement harvest. One major effort is understanding how should complex decision makers’ decide, deal with risks and uncertainties, create options better than originally available, potential responses to problems and evaluate strengths and weaknesses of each prospective action using apparatus of eye tracking / tracing and gazing.
[PDF Paper] [HTML Paper] [Cite]
Citation Text :
Prof. Dr. S. Sandhya, Post - Doc Fellow, Poornaprajna Institute of Scientific Research, Bengaluru, India

Col. Prof. Dr. J Satpathy, Post - Doc Fellow, Poornaprajna Institute of Scientific Research, Bengaluru, India Email jyotisatpathy@gmail.com

Prof. Dr. P. S. Aithal, Director, Poornaprajna Institute of Management, Udipi, India

Data Privacy Concerns in AI and HRM

Dr. Pallavi Kumari,Mr. Anjan Niyogi

Keywords : Data Privacy, Algorithmic Bias, Data Security, GDPR, Machine Learning, Transparency, Ethical Implications

EOI : eoi.citefactor.org/12.11224/IUJ.12.02.05

[Abstract]
The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) practices offers significant potential for efficiency and improved decision-making. However, this technological advancement brings forth considerable data privacy concerns that require careful consideration and robust mitigation strategies. This chapter explores the multifaceted challenges posed by the use of AI in HRM, focusing on the ethical and legal implications of collecting, processing and sensitive employee data.

One key area of concern lies in the data collection phase.AI-powered HRM systems often require extensive datasets encompassing various aspects of employee lives, including personal information, performance metrics, health data, and even social media activity. The sheer volume and sensitivity of this data raise questions regarding informed consent, transparency, and the potential for unauthorized access or misuse. The nuances of obtaining meaningful consent, particularly in contexts where employee participation might be implicitly or explicitly mandated.

Furthermore, the processing and analysis of employee data through AI algorithms introduce further privacy risks. The chapter examines the potential for bias amplification in AI-driven processes like recruitment, performance evaluation, and promotion decisions, and explores techniques for mitigating algorithmic bias and ensuring fairness.

The storage and security of employee data are critical considerations. AI systems often involve the storage and transfer of vast quantities of sensitive information, creating vulnerabilities to data breaches and cyber-attacks. The chapter discusses the importance of implementing robust security measures, such as encryption, access controls, and regular security audits, to safeguard employee data from unauthorized access and potential misuse. Further, the chapter addresses the legal frameworks, such as GDPR and CCPA, which govern the handling of personal data and their relevance to AI in HRM.

Finally, the chapter explores the ethical implications of using AI in HRM. The potential for surveillance, the erosion of employee autonomy, and the lack of human oversight in decision-making processes all raise ethical concerns. Ultimately, striking a balance between leveraging the benefits of AI in HRM and safeguarding employee data privacy.
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Citation Text :
Dr. Pallavi Kumari, Associate Professor
ICFAI University, Ranchi, Jharkhand, India ORCHID ID-0000-0002-6344-3795 Email ID:-pallavikumari@iujharkhand.edu.in

Mr. Anjan Niyogi, Research Scholar ICFAI University, Ranchi, Jharkhand, India ORCID ID-0009-0000-3579-4232 Email ID: -annjani.y20@iujharkhand.edu.in