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As responsibilities of high school principals continue to expand, their workweeks become longer, and their attention is stretched in multiple directions. How principals from various school types use their time is influenced by their organizational structures and external policies. To gain deeper insights into the workload, priorities and constraints faced by high school principals, this study examines principal time use (PTU) patterns across different school types, including traditional public schools (TPSs), charter schools, Catholic schools and non-Catholic private schools.

Drawing on the national representative data from the High School Longitudinal Study of 2009 in the USA, this study examines and compares PTU in various leadership tasks across different school types, controlling for school and principal characteristics.

Among various high school types, principals in TPS had the longest workweeks. However, the extended workweek did not necessarily result in significantly more hours or a larger proportion of their time dedicated to instructional leadership. Instead, TPS principals allocated more time to administrative tasks and student affairs than principals in other school types.

By examining PTU of different school types, this study adds new evidence on the influence of contextual factors on leadership behavior. It also offers policy implications to enhance principals’ capacities, alleviate their workload and to prioritize time use in different leadership domains.

This study aims to investigate the research productivity in terms of publications count of the top four premiers Indian Institute of Management (IIM) institutions and to explore the current research trends.

Bibliometric techniques were employed to assess the performance in terms of research productivity of authors affiliated with IIMs. The Elsevier Scopus database was selected as a tool to extract the prospective publications data limiting the time frame for 2010–2021. The IIM-Ahmedabad, IIM-Bangalore, IIM-Calcutta and IIM-Lucknow have been selected for the study. The harvested data were analyzed by using the standard bibliometric indicators and scientometric parameters to measure the research landscape such as average growth rate, compound average growth rate, relative growth rate, doubling time, degree of collaboration, collaborative index, collaborative coefficient and modified collaborative coefficient. VOSviewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The research productivity of selected four IIMs has shown an upward trend during the study period from 2010–2021 and accrued 4,397 publications with an average of 366 publications per year. The authorship patterns demonstrate the collaborative trends as most of the publications were produced by the multiple-authors (81.03%). IIM-Ahmedabad has produced the maximum number of publications (32.20%). The research productivity of IIMs has come out in collaboration with the 125 nations across the world and the USA, the UK, Canada, Germany and China are the front runners with IIMs in the collaborative network. The high magnitude and density of collaboration are evident from the calculated mean values of the degree of collaboration (0.82). The mean values of the collaborative index (2.64), collaborative coefficient (0.51) and modified collaborative coefficient (0.51) demonstrated a positive trend, but indicate the fluctuation in the collaborative pattern as time proceeds.

The study is limited to the publications data indexed in the Scopus database, therefore the outcome may not be generalized across other databases available in the public domain like Web of Science (WoS), PubMed, Dimensions and Google Scholars.

The findings of the study may aid academics and library professionals in identifying research trends, collaboration networks and evaluating other academic and research institutions by using the current advancement in data analysis.

The present study is the first effort to evaluate the research productivity of IIMs. The expanding literature will make an important contribution to identifying patterns and evaluating current research trends on a worldwide scale.

Assessing the research performance of researchers offers inducement toward excellence in research. This study aims to analyze the research productivity of the most prolific authors of Pakistan considering their trends toward publications, citations and collaboration.

Top 100 authors from the top 10 Pakistani universities from Web of Science over the 10 years with the rigorous data cleaning process were selected. Scientometric analysis techniques were carried out to evaluate the research profile of these authors.

The findings revealed that majority of the productive authors were male working in the position of Professor in the physical sciences area. The publications and citations gradually increase with time. They preferred to collaborate for their publications, while first authorship publications were found less in number. Moreover, the propensity to collaborate at the international level increases double-fold from the first five years to the next five years period. In addition, the position of the authors was explored among different performance metrics. The finding exhibits variation in the ranking of authors among them. The impact of numbers of authors, funding status, publication of articles, presence of collaboration and international collaboration on the dependent variable and citation count was insignificant. However, the publication of review papers has a significant impact on the citation counts.

Findings have significant implications for policymakers to make maximum opportunities for researchers to strengthen linkages for collaboration and increase the funding prospects.

Studies on this topic are scarce, and therefore, this study provides useful recommendations to researchers and institutes to improve research productivity.

Building on the social cognitive theory, a mediation model was examined to understand the role of teacher self-efficacy as the underlying mechanism for the relationship between instructional leadership and teacher job satisfaction.

The study tests a mediation model between instructional leadership, teacher self-efficacy and job satisfaction. The data were collected via online survey from primary school teachers (N = 320) working for the Municipal Corporation of Delhi (MDC) in India. The mediation model was tested using the AMOS 22.0 after establishing the reliability and validity of measures.

Regression analyses using the bootstrapping method indicated that teacher self-efficacy mediates the relationship between instructional leadership and teacher job satisfaction.

This is a cross-sectional study. The scope for causal inferences is, thus, limited.

In the Indian setting, the study examines the association between instructional leadership and job satisfaction. The results show that the instructional leadership of the school principal is strongly related to teachers' self-efficacy, which, in turn is positively associated with teacher’s job satisfaction. Further, the findings confirm that instructional leadership, emphasizing instructional improvement, improves teachers' self-efficacy and job satisfaction.

The study explains the underlying process through which a school principal’s instructional leadership is related to teacher job satisfaction. This study is perhaps the first to focus on an Indian or a non-Western context.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

Although the majority of Ethiopians continue the on-farm and off-farm work, the country still struggles to secure food for its citizens and farmer welfare is very low. To increase farmers' welfare, improving farmers' entrepreneurial competency is believed to be the solution. However, entrepreneurial competencies are diversified, and investigating the most important dimensions specific to the agricultural sector is important. As a result, the objective of this research is to look into important entrepreneurial competencies that could help farmers.

To achieve the objective, survey data, collected from 178 households in North Shoa, Amhara National Regional State, Ethiopia is analyzed through structural equation modeling (SEM).

The study revealed that of the six entrepreneurs' competencies considered, only two of them (Strategic competency and relationship competency) have a significant association with the welfare of farmers. Moreover, the study revealed that the moderating effect of agricultural extension (taking model and non-model farmers as a group) on the relationship between entrepreneurial competency and farmers' welfare is not significant.

This study focuses only on six entrepreneurial competencies from which two of them are found significant factors in farmers' welfare. Thus, future research could broaden the scope in terms of looking into additional variables.

The study investigated the moderating effect of the farmers' category as a model and non-model on the relationship between entrepreneurial competency and farmers' welfare, which is the first to discuss the moderation effect.

The purpose of this study was to investigate the relationship between job crafting and work engagement and the potential mediating effect of organizational happiness on this relationship.

A sample of 256 full-time employees from various industries such as automobiles, retail, real estate, petrochemicals, investment, industrial and education, working at top 50 Forbes Middle East companies in UAE, were surveyed to gather data on job crafting, organizational happiness and work engagement. The study used an empirical research design, with data collected through surveys.

The results of this study, obtained through a two-step structural equation modelling approach, indicate that job crafting has a positive and direct influence on both organizational happiness and work engagement. The findings also suggest that the relationship between job crafting and work engagement is partially mediated by organizational happiness.

The findings emphasize the need for human resources (HR) professionals to develop programmes and training workshops focused on cultivating these concepts, particularly as remote and blended working arrangements become more prevalent. In addition, the study highlights the global impact of employee disengagement on financial losses and stresses the importance of revising HR policies in the UAE to mitigate potential risks. Lastly, the study suggests that enhancing happiness and reducing disengagement can be achieved through training managers and employees in task structuring techniques, emphasizing the teachability of job crafting skills through interventions that align tasks with employees’ interests.

To the best of the author's knowledge, this is the first study to theoretically explore and empirically test a proposed model on the relationships between job crafting, organizational happiness and work engagement in the context of the UAE.

The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously.

The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board.

The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods.

This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship.

The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon.

The purpose of this study is to investigate the impact of Inclusive Leadership (IL) and Organizational Justice (OJ) on employees’ Happiness at Work (HAW). Utilizing a mediation mechanism, the study additionally uncovers the mediating impact of Workplace Inclusion (WI).

The research involved a cross-sectional study with a quantitative methodology, collecting data from 311 employees working in IT sector firms in India by administering standardized questionnaires. Statistical analyses, including Partial Least Square Structural Equation Modelling using SmartPLS4.0, were conducted to examine the relationship between constructs.

The hypothesized mediation model was supported. WI mediated the relationship partially between OJ and HAW, whereas there is a full mediating effect of WI on the IL–HAW relationship. Overall, the study shows that by providing fair treatment, inclusive leaders promote inclusivity among employees, further enhancing HAW.

The study’s implications suggest that leaders, with their inclusive behaviour and fair practices, can have a significant positive impact on employees’ workplace happiness when accompanied by a sense of inclusivity among employees.

Organizations and leaders can utilize this study’s findings to promote inclusiveness and HAW, which can be a key to organizational growth and development in a post-pandemic era.

This study contributes to the research literature by addressing the unexplored relationship between IL, OJ and HAW. The exclusive as well as inclusive focus on the mediating role of WI adds new insights and enriches the understanding of the intricate conceptualization of the variables under study.