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Article
Publication date: 1 September 2004

Anuradha Chawla and E. Kevin Kelloway

Developed and tested a model of the change management strategies that predict openness and commitment to a large‐scale organizational change. Based on a sample of 164 employees, a…

12707

Abstract

Developed and tested a model of the change management strategies that predict openness and commitment to a large‐scale organizational change. Based on a sample of 164 employees, a partially‐ and a fully‐mediated model were compared with the former providing the best fit to the data. Communication and job security predicted openness and trust both directly and indirectly, via procedural justice. Participation predicted trust directly and indirectly but predicted openness to change only indirectly (via procedural justice). Turnover intentions were negatively predicted by openness and trust. Finally, turnover intentions predicted neglect. These results highlight the role of procedural justice perceptions in understanding organizational change.

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Leadership & Organization Development Journal, vol. 25 no. 6
Type: Research Article
ISSN: 0143-7739

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Article
Publication date: 1 September 2005

234

Abstract

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Leadership & Organization Development Journal, vol. 26 no. 6
Type: Research Article
ISSN: 0143-7739

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Article
Publication date: 1 February 2006

Marie McHugh

397

Abstract

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Leadership & Organization Development Journal, vol. 27 no. 2
Type: Research Article
ISSN: 0143-7739

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Article
Publication date: 12 June 2017

Ali Hasan Alsaffar

The purpose of this paper is to present an empirical study on the effect of two synthetic attributes to popular classification algorithms on data originating from student…

267

Abstract

Purpose

The purpose of this paper is to present an empirical study on the effect of two synthetic attributes to popular classification algorithms on data originating from student transcripts. The attributes represent past performance achievements in a course, which are defined as global performance (GP) and local performance (LP). GP of a course is an aggregated performance achieved by all students who have taken this course, and LP of a course is an aggregated performance achieved in the prerequisite courses by the student taking the course.

Design/methodology/approach

The paper uses Educational Data Mining techniques to predict student performance in courses, where it identifies the relevant attributes that are the most key influencers for predicting the final grade (performance) and reports the effect of the two suggested attributes on the classification algorithms. As a research paradigm, the paper follows Cross-Industry Standard Process for Data Mining using RapidMiner Studio software tool. Six classification algorithms are experimented: C4.5 and CART Decision Trees, Naive Bayes, k-neighboring, rule-based induction and support vector machines.

Findings

The outcomes of the paper show that the synthetic attributes have positively improved the performance of the classification algorithms, and also they have been highly ranked according to their influence to the target variable.

Originality/value

This paper proposes two synthetic attributes that are integrated into real data set. The key motivation is to improve the quality of the data and make classification algorithms perform better. The paper also presents empirical results showing the effect of these attributes on selected classification algorithms.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 2
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 17 January 2023

Shilpa Manocha, Pritpal Singh Bhullar and Timcy Sachdeva

The purpose of this study is to investigate the determinants that determine the investment behaviour of rural farmers. This study further examines the moderation effect of socio…

767

Abstract

Purpose

The purpose of this study is to investigate the determinants that determine the investment behaviour of rural farmers. This study further examines the moderation effect of socio traits in the association between investment behaviour and its determined factors.

Design/methodology/approach

This study used a cross-sectional research design to gather information. The information for this research survey was gathered using a structured questionnaire from 400 individual investors in the rural area of Punjab, who participated in the study. It has been decided to use the Cronbach’s alpha test to determine the validity and reliability of the questionnaire. To evaluate the hypothesis, structural equation modelling has been used in the research process.

Findings

The results of this study reveal that attitude, financial risk inclination, financial planning and investment intention determine the investment behaviour of the rural people of Punjab. The results for the interaction effect of socio traits with investment intention, financial risk propensity and investment attitude were found statistically significant amongst rural people. The results of the moderation effect stated that interaction between the attitude and investment intention and financial risk propensity and investment intention is significantly influenced by age of respondents. The results further reveal that marital status of rural people affect the interaction between attitude and investment intention and financial risk propensity and investment intention. Nothing about education seems to be a moderating influence on any of the relationships studied.

Originality/value

The authors contribute to the literature in two aspects. Firstly, to the best of the authors’ knowledge, this is the only study of its kind that focuses on the investment behaviour of farmers. Secondly, by looking at the farmer’s investing behaviour, the moderation effect of demographic variables is also studied which set this study apart from another existing scholarly research. This study contributes to the growing literature on investment behaviour of farmers in developing and developed markets.

Details

Journal of Indian Business Research, vol. 15 no. 3
Type: Research Article
ISSN: 1755-4195

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Article
Publication date: 6 May 2021

Rajesh Kumar Singh, Saurabh Agrawal, Abhishek Sahu and Yigit Kazancoglu

The proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of…

2113

Abstract

Purpose

The proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.

Design/methodology/approach

Fora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.

Findings

BD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.

Research limitations/implications

The proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.

Originality/value

There are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

Details

The TQM Journal, vol. 35 no. 1
Type: Research Article
ISSN: 1754-2731

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