Search results

1 – 3 of 3
Article
Publication date: 13 January 2021

Harleen Kaur and Rajpreet Kaur

Very little research has examined how adaptivity, adaptability resources, adapting responses and adaptation results are interlinked with each other. The current research…

Abstract

Purpose

Very little research has examined how adaptivity, adaptability resources, adapting responses and adaptation results are interlinked with each other. The current research aims to investigate whether career adaptability influences job outcomes via job content plateau. Taking career construction theory (Savickas, 2005) as a base, the research model of this study posited that employee's favorable job outcomes, i.e. job satisfaction and performance depend upon their psychosocial meta-capacities (career adaptability) and job content plateau. Further, the study is the first to examine the moderating role of proactivity among career adaptability, job content plateau and job outcomes relationship.

Design/methodology/approach

It is a two-wave longitudinal study, quantitative in nature and has collected data from 357 faculty members of Indian universities. The hypotheses have been empirically tested through the structural equation modeling technique.

Findings

The moderated mediation model was supported, and as predicted, (1) career adaptability was positively related to job outcomes and (2) the mediated relationship between career adaptability and job outcomes via content plateau was stronger for individuals with high levels of proactivity.

Practical implications

The study encourages career management practitioners and counselors to integrate proactive behaviors and career adaptability into counseling techniques to equip clients with necessary skills and deal with unfavorable job experiences, thereby engendering favorable job outcomes.

Originality/value

The current study is the first to test the intervening effect of proactivity in career adaptability and job outcomes relationships via job content plateau.

Details

Higher Education, Skills and Work-Based Learning, vol. 11 no. 4
Type: Research Article
ISSN: 2042-3896

Keywords

Article
Publication date: 5 July 2022

Harleen Kaur and Harsh V. Verma

The study aims to synthesize the state of research on pride in consumer behaviour and marketing. Specifically, this study aims to understand the emergent themes of…

Abstract

Purpose

The study aims to synthesize the state of research on pride in consumer behaviour and marketing. Specifically, this study aims to understand the emergent themes of literature, the key theories, analytical techniques and methodologies used, as well as key variables associated with pride in consumer behaviour and marketing.

Design/methodology/approach

Using a systematic literature review process, the study analyses 59 research articles and structures its findings by using the theory–context–characteristics–methodology framework.

Findings

The review proposes a taxonomical classification of the multiple conceptualizations of pride. It identifies that the phenomenon and regulation of pride is explained using theories from psychological self-related research. Pride has been experienced in sustainable, advertising, luxury and digital consumption contexts. Reviewed articles showed an over-reliance on the quantitative methodology and the experimental method. The review identifies that pride is associated with positive outcomes and has considerable influence on consumer behaviour. Building on this analysis, 12 research questions are developed to encourage future research.

Originality/value

To the best of the authors’ knowledge, this study is the first structured review on the emotion of pride in the domains of consumer behaviour and marketing.

Details

Management Research Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8269

Keywords

Open Access
Article
Publication date: 28 July 2020

Harleen Kaur and Vinita Kumari

Diabetes is a major metabolic disorder which can affect entire body system adversely. Undiagnosed diabetes can increase the risk of cardiac stroke, diabetic nephropathy…

4104

Abstract

Diabetes is a major metabolic disorder which can affect entire body system adversely. Undiagnosed diabetes can increase the risk of cardiac stroke, diabetic nephropathy and other disorders. All over the world millions of people are affected by this disease. Early detection of diabetes is very important to maintain a healthy life. This disease is a reason of global concern as the cases of diabetes are rising rapidly. Machine learning (ML) is a computational method for automatic learning from experience and improves the performance to make more accurate predictions. In the current research we have utilized machine learning technique in Pima Indian diabetes dataset to develop trends and detect patterns with risk factors using R data manipulation tool. To classify the patients into diabetic and non-diabetic we have developed and analyzed five different predictive models using R data manipulation tool. For this purpose we used supervised machine learning algorithms namely linear kernel support vector machine (SVM-linear), radial basis function (RBF) kernel support vector machine, k-nearest neighbour (k-NN), artificial neural network (ANN) and multifactor dimensionality reduction (MDR).

1 – 3 of 3