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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.

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.

The study aims to investigate the consumers' behavioral intention toward green hotels. The tendency of individuals to afford green hotels is further escalating with progressing coronavirus disease-2019 (COVID-19) pandemic recurring waves. The increased worry of consumers toward health, hygiene and the climate is acquiring momentum and transforming how consumers traditionally perceive green hotels.

The study has recommended an integrated framework incorporating various research fields as attitude-behavior-context theory, theory of planned behavior (TPB) and moderating influences to study the associations among the antecedents of consumers' behavioral intention toward green hotels. The study comprised the participation of 536 respondents residing in the Delhi and National Capital Region (NCR) of India. The data analysis strategy involved the use of structural equation modeling (SEM) analysis to test the proposed research framework.

The results and findings of the study indicated a significant influence of fear and uncertainty of the COVID-19 pandemic and environmental concern on green trust. The results also revealed the considerable impact of green trust on willingness to pay premium, attitude and subjective norms, which significantly influenced behavioral intention. The analysis also revealed the moderating influence of environmental concern in the relationship of green trust and behavioral intention.

The study has recommended significant theoretical. The theorists may use this research framework to analyze better the transforming consumer behavior trends toward green hotels in the ongoing fearful and uncertain COVID-19 pandemic scenario.

The study has recommended significant managerial implications. The industry practitioners may also utilize the framework to sustain the hotel business and bring new strategic insights into practice to combat the impact of the pandemic and simultaneously win consumers' trust in green hotels.

Although the researchers have previously emphasized consumers' intention toward green practices embraced by hotels, the impact of the COVID-19 pandemic on the green hotel industry gained noticeable attention from researchers. Furthermore, there is a scarcity of literature providing insights on the behavioral dynamism of hotel customers' trust, attitude and willingness to pay for green hotels during the repetitive waves of the COVID-19 pandemic. The study will support the existing literature gap by enlightening the associations among the various antecedents of green hotels' behavioral intention, COVID-19 and environmental concern.

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.

The aim of this paper is to make a descriptive exploratory effort to discern the role of IT exports in India's macro-economic indicators, like national income, employment and balance of payment in the post-Liberalization, Privatization and Globalization strategy in the 1990s. The paper also explores the vital historical developments of various dimensions of IT, such as its export growth, major software and services exports destinations, compositions of IT exports and domestic growth in India.

This study is based on secondary data, which were collected from Balance of Payment Statistics Reserve Bank of India (RBI) and Handbook of Statistics on Indian Economy, National Association of Software and Service Companies (NASSCOM),rtd and Department of Electronics and Information Technology (DEITY). This study has used descriptive analysis and growth models for studying the objectives. Major IT sector dimensions, such as total output, exports revenue, domestic revenue, gross domestic product, employment and exports of the software and service industry, have been examined for the period 1991–2016.

The findings suggest that over the last 26 years, the information technology industry's economic footprint has extended by more than seven times. Over the same period, direct employment in the information technology sector increased at an average growth rate of around 17%. Software and services exports earn, on average, about three times greater than the other three major services of India's current account of the balance of payment.

This study focuses on originality in examining the role of IT exports in India's macro-economic indicators economic reforms of the 1990s and also explores the historical developments of various dimensions of IT exports and domestic growth in India. All the work has been done in original by the authors, and the work used has been acknowledged properly.

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 examine the effects of corporate social responsibility, social media marketing, sales promotion, store environment and perceived value on a purchase decision in the retail sector.

A quantitative research methodology was used and the data were collected from 278 customers of retail stores in Malaysia. The collected data were analysed using SPSS 19 and structural equation modelling on AMOS.

The findings showed that corporate social responsibility has significant positive effects on a purchase decision, whereas sales promotion has a negative effect on purchase decision. The outcomes of this study also indicated that store environment has a significant positive effect on consumers’ purchase decisions. Contrary to expectations, the findings revealed that the effect of social media marketing on purchase decision is insignificant. Finally, the results showed that perceived value has a significant positive effect on a purchase decision.

The findings of this study contribute to an understanding of the importance of the selected factors in affecting a consumer’s purchase decision in the retail industry.

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.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

How to obtain a list of the 100 largest scientific publishers sorted by journal count? Existing databases are unhelpful as each of them inhere biased omissions and data quality flaws. This paper tries to fill this gap with an alternative approach.

The content coverages of Scopus, Publons, DOAJ and SherpaRomeo were first used to extract a preliminary list of publishers that supposedly possess at least 15 journals. Second, the publishers' websites were scraped to fetch their portfolios and, thus, their “true” journal counts.

The outcome is a list of the 100 largest publishers comprising 28.060 scholarly journals, with the largest publishing 3.763 journals, and the smallest carrying 76 titles. The usual “oligopoly” of major publishing companies leads the list, but it also contains 17 university presses from the Global South, and, surprisingly, 30 predatory publishers that together publish 4.517 journals.

Additional data sources could be used to mitigate remaining biases; it is difficult to disambiguate publisher names and their imprints; and the dataset carries a non-uniform distribution, thus risking the omission of data points in the lower range.

The dataset can serve as a useful basis for comprehensive meta-scientific surveys on the publisher-level.

The catalogue can be deemed more inclusive and diverse than other ones because many of the publishers would have been overlooked if one had drawn from merely one or two sources. The list is freely accessible and invites regular updates. The approach used here (webscraping) has seldomly been used in meta-scientific surveys.