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This study aims to understand the relative intensity of the challenges and problems faced by small-scale entrepreneurs in Uttarakhand.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

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).

The proposed method is a combination of Sumudu transform and a semi-analytc technique Daftardar-Gejji and Jafari method (DGJM).

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.

The present work is original. To the best of the author's knowledge, this work is not done by anyone in the literature.

The present study is aimed at examining the antecedents of online shopping user behavior and customer satisfaction. More specifically, (1) the effect of social influence, variety seeking behavior, advertising and convenience on user behavior, and (2) the effect of user behavior on customer satisfaction are examined.

A conceptual model is developed and tested after verifying the psychometric properties of the survey instrument. Data were collected from 556 respondents from three major cities (Hyderabad, Chennai and Bangalore) in the southern part of India using structured instrument. Hierarchical regression is performed. Measurement model was checked using structural equation modeling (Lisrel package).

The results reveal that (1) social influence, (2) variety seeking, (3) advertising, (4) convenience, (5) trust and (6) product factors were positively related to online user behavior. Results also show that user behavior is significantly and positively related to customer satisfaction. The hierarchical regression results also showed moderating effects of (1) trust in the relationship between social influence, variety seeking and user behavior, and (2) product factors in the relationship between advertising, convenience and user behavior. Finally, results suggest that user behavior is partially mediating the relationship between trust and customer satisfaction, i.e. trust has both direct and indirect effect on customer satisfaction.

As with any survey-based research, the present study suffers from the problems associated with self-report measures viz., common method bias and social desirability bias. However, the authors attempted to minimize these limitations by following appropriate statistical techniques.

This study contributes to both practicing managers and the literature on advertising. The study suggests that trust and product play a major role in strengthening the relationship between antecedents and user behavior.

This study provides new insights about the importance of gaining trust in influencing consumer behavior. The conceptual model the authors developed is novel in the sense not many studies are available in India to empirically examine the moderating relationships of trust and product in consumer behavior.

This paper aims to find the best tools to influence the improvement of sustainability in food supply chains (FSCs) by conducting a systematic review of articles. The reader will learn how the different industry 4.0 tools (I4.0T) benefit the FSC and the limitations of each tool.

A review of 436 articles published during the period 2019 to 2022 referenced in the Scopus and Web of Science databases was performed. The review was limited to articles published in English and directly related to Industry 4.0, circular economy and sustainability in the food supply chain.

The results show different contributions of I4.0, with some being more influential than others in improving sustainability in FSCs; for example, Internet of Things and Blockchain have been shown to contribute more toward transparency, traceability, process optimization and waste reduction.

The paper's contribution consisted of ranking according to their importance and the I4.0T that affect sustainability in FSCs by classifying the aspects of each tool and the sustainability factors through a categorization by the Analysis Hierarchy Process.

The purpose of this paper is to analyze the leadership decisions taken during the crisis and their influence on the goals recognized by managers as crucial for surviving.

During the survey, conducted in April 2020 (one month after the first economic lockdown in Poland), as part of a research project called Sur(VIR)val – Survival during the virus, data was collected from 178 leaders from randomly selected companies from Poland using the CAWI method. Ordered logistic regression modeling was used to examine the impact of the decisions taken by company leaders on the goals seen by leaders as most important for company survival.

The results obtained in the study show that during the first Covid-19 lockdown in 2020, leaders made decisions that can be seen as oriented toward survival and continuity. Changing to remote working, extending payment deadlines for customers, as well as selective employment reduction turned out to have the greatest influence on strategic support for maintaining current production levels and retaining competent employees in order to survive the crisis.

This study has certain limitations. First, the list of leadership decisions and company goals used as dependent variables is not exhaustive. Second, the selection of business goals oriented toward survival may not derive directly from the lockdown situation. Third, our study did not measure the actual accomplishment of the company goals, but the managerial perceptions as to which ones are crucial for company survival during crises, and which of them should be given strategic support respectively. Fourth, the research sample was randomly constructed and covered only business organizations in Poland. Fifth, the hypotheses were formulated in a way that treated leadership decisions as one construct. Finally, we used survey, with a scale measuring managerial perceptions.

Leaders should ensure that proper IT tools are developed within the organization, and that the skill level of employees is high enough for fast shifting employees on to remote working. At the same time, it is important to maintain IT infrastructure at a high level. In terms of general recommendations for leaders, they should make quick decisions, maintain the most valuable resources of the company (human resources and cash flow) and take actions aimed at taking advantage of opportunities (R&D) during and after the crisis.

Additionally, due to the key importance of human resources for the survival of the organization, leaders should respond quickly by making flexible decisions about sending employees on leave and downtime. As human resources are the most valuable assets of the company from the point of view of its survival, decisions concerning employment reduction should be taken carefully. Leaders who acted in panic after the first lockdown and made employees redundant, later on had problems recruiting skilled employees back and strived to return to full organizational capacity.

Although scholars have investigated leadership decisions and actions taken during economic crises, little is known about how leaders behave when taken by surprise, and what decisions they make when the duration of a crisis is difficult to predict. The results of this study show which leadership decisions during the first Covid-19 lockdown in 2020 influenced prioritizing critical company goals oriented toward survival.