Kamal Joshi, Manoj Kumar Mishra, Mohammad Jamal and Joney Janotra
This study aims to understand the relative intensity of the challenges and problems faced by small-scale entrepreneurs in Uttarakhand.
Abstract
Purpose
This study aims to understand the relative intensity of the challenges and problems faced by small-scale entrepreneurs in Uttarakhand.
Design/methodology/approach
A survey methodology was used for this study. The judgement sampling method was used to select the sample for this study. The data were collected from 240 small-scale entrepreneurs using a self-structured questionnaire. Descriptive statistics, principal component analysis and confirmatory factor analysis were used to analyse the data.
Findings
The survey found that marketing, finance, taxation, human resource and government support–related problems are the major problems of small-scale entrepreneurs in the state.
Research limitations/implications
This study was conducted in both rural and urban areas, but due to the unreachability of rural entrepreneurs, the representation of rural entrepreneurs is less, so the findings are more inclined towards urban entrepreneurs.
Practical implications
The research has highlighted the intensity of the major problems faced by small-scale entrepreneurs in Uttarakhand. Although many support schemes are operational in the state, small–scale entrepreneurs face many challenges, so this study provides solutions for those challenges.
Originality/value
This study is unique in that it measures the intensity of problems and challenges of small-scale entrepreneurs and provides insight into more serious issues prevalent in the state.
Details
Keywords
Gayatri Panda, Manoj Kumar Dash, Ashutosh Samadhiya, Anil Kumar and Eyob Mulat-weldemeskel
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore…
Abstract
Purpose
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.
Design/methodology/approach
The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.
Findings
The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.
Research limitations/implications
The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.
Originality/value
The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.
Details
Keywords
In this paper, the author presents a hybrid method along with its error analysis to solve (1+2)-dimensional non-linear time-space fractional partial differential equations (FPDEs).
Abstract
Purpose
In this paper, the author presents a hybrid method along with its error analysis to solve (1+2)-dimensional non-linear time-space fractional partial differential equations (FPDEs).
Design/methodology/approach
The proposed method is a combination of Sumudu transform and a semi-analytc technique Daftardar-Gejji and Jafari method (DGJM).
Findings
The author solves various non-trivial examples using the proposed method. Moreover, the author obtained the solutions either in exact form or in a series that converges to a closed-form solution. The proposed method is a very good tool to solve this type of equations.
Originality/value
The present work is original. To the best of the author's knowledge, this work is not done by anyone in the literature.
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Keywords
Angappa Gunasekaran, Nachiappan Subramanian and Manoj Kumar Tiwari
Abhishek Behl, Angappa Gunasekaran, Rajesh Kumar Singh and Sachin Kamble