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The purpose of this study is to explore the perception of the users concerning the role of artificial intelligence (AI) in enhancing personal learning profile (PLP), personal learning network (PLN) and personal learning environment (PLE) and their effect on the perceived ease of use, perceived effectiveness and perceived usefulness for enhancing the overall attitude and satisfaction of the e-learning.

The data were collected from students and professionals who have ever used the e-learning module, and smart partial least square-structural equational modeling (PLS-SEM) is used to see relations between the different variables.

It was seen that the PLE is affecting both perceived ease of use and perceived usefulness. The research has shown that perceived ease of use showed a mediating effect between PLE and attitude and satisfaction. Further satisfaction mediates between perceived ease of use and intention. PLP has come out to significantly impacting perceived effectiveness. The multigroup analysis also showed that the attitude and satisfaction level affecting intention to use the e-learning module differ across the two groups of learners, i.e. gender and type of learners.

The data are collected from students and professionals who have ever used the e-learning module and wholly based on their perceptions, leading to self-perception bias.

The current research is trying to integrate the user perception of PLP, PLN, PLE into the framework of the technology acceptance model and see how they impact the overall attitude and satisfaction of the learners. AI can be used to improve them and make e-learning more adherent to the users. AI can play an essential role in generating the right environment by matching the profile of the learner.

The purpose of this paper is to explore the role of social media in creating an attractive employer brand for any organization. It investigates one of the social media Glassdoor, which is an online employer branding platform, where employees put their reviews which are both positive and negative. Analysis of these reviews can generate a lot of insights into employer branding.

The data was collected as 1,243 reviews from Glassdoor, an online crowdsourced employer branding platform for 40 top-rated employers across four different sectors, namely, Pharma, IT, retail and FMCG. Text and sentimental analyses were done using SAS visual analytical for these reviews.

Ten themes were generated from the text analytics which is nothing but the employer value propositions (EVPs), and they were social, interest, development and economic value as given by Berthon et al. (2005) and also others, such as work–life, management and brand value emerged. Social value came as a significant EVP followed by interest value and work–life values.

This research is providing only ways to show that crowdsourced data can also be used to understand the mindset of employees regarding an employer’s image but is not providing any idea regarding how to generate the right employee value proposition.

The research has shown that employers can use crowdsourced employer branding insights to see where they stand in the employer's attractiveness spectrum. They can use innovative data analytics techniques, such as visualization for text and sentimental analysis to create employer branding intelligence strategies.

This study aims to look at the integration of gamification in an e-learning model based on the technology acceptance model. The data was collected from respondents residing in India and elements of gamification (achievement, immersion and social) and personal characteristics of learners (self-efficacy, computer anxiety and enjoyment) and their impact on perceived ease of use (PEOU) and perceived usefulness (PU) were tested.

The data were collected from students and professionals who have ever played games during learning while using an e-learning module. Structural equation modeling using smart partial least square was used to create a model.

The findings showed that enjoyment affected both PEOU and PU and attitude toward e-learning. Achievement and social elements impacted attitude and the immersion element moderated the relation between enjoyment and PEOU and PU. These finally impact attitude and satisfaction, leading to higher intention to use e-learning platforms.

Because this study is very specific to the Indian context, a broad generalization requires further exploration in other cultural contexts. The absence of this exploration is one of the limitations of this study.

This study tested the GAMEFULQUEST suggested by Högberg et al. (2019) based on self-determination theory and its impact on the overall e-learning experience. The moderation of immersion has come out to be significant and achievement and social elements impacted attitude.

This study aims to explore the emergence of the human resource (HR) analyst role. The job posts on LinkedIn display the industry demand and skills required by the organizations. This study identifies the different knowledge, skills and abilities (KSA) required for an HR analyst role in different stages of professional growth (i.e. entry-level, middle-senior level and top-level) across different industries/sectors as applicable to the crisis.

A total of 80 job posts were extracted from LinkedIn. Details such as industry, job levels, qualifications, job experience, job functions, job descriptions (JDs) and job skills (JS) were collected. Further, 30 videos were extracted from YouTube and converted into text. Text analysis was conducted using NVivo software to analyze JDs, JS and job functions. Using NVivo, word frequency, word cloud, word tree and treemap were created to visualize the data. Finally, ten in-depth interviews were conducted with senior HRA managers based in India to understand the essential competencies required for the HR analyst role and the strategies to develop them.

The findings indicate that not only technical skills are needed, but business and communication skills are particularly important for all job levels during a crisis. The JD word cloud showed words, such as data, business, support and management, and the word tree depicted HR data and change agents as important words with many related sentences as branches. General JS included analytical, communication, problem-solving and management. Technical JS were the most widely used and included structure query language, system applications & products in data processing, human capital management, TABLEAU, management information system and PYTHON. Strategies to develop these competencies included case studies, live projects, internships on HR analytics (HRAs) assignments and mentoring by senior HRA professionals.

The sample used was small, as the study included 80 job posts available on LinkedIn restricted to India. The study was restricted to qualitative approach and text analytics was used. Survey methods and a quantitative approach can be used to collect data from HR recruiters, job holders and senior leaders to understand the role of HRAs in the job market and then these variables can be tested empirically.

Based on the McCartney et al.’s (2020) competency model for the HR Analyst role, this study has explored the KSA framework using data visualization techniques and used text analytics to analyze LinkedIn job posts for different levels, videos from YouTube and in-depth interviews. It also mapped the KSA for the HR analyst role to the various stages of crisis system management given by Mitroff (2005). The use of social media analytics, such as analyzing LinkedIn data and YouTube videos, are highlighted.

The coronavirus disease 2019 (COVID-19) situation has led to the emergence of virtual teams in all organizations, and the role of leadership has become more pertinent. The current research focuses on understanding the factors for better team performance in virtual teams. Based on the contingency perspective, the behavioral complexity in leadership (BCL) theory is the most appropriate as BCL requires the leader to demonstrate multiple contrasting leadership behaviors according to the situation. Both internal as well external roles were explored, which could facilitate better communication quality and role clarity to increase interpersonal trust and leadership effectiveness in the current crisis.

Data were collected from employees who have worked in virtual teams during the crisis and who have experience of working in a virtual team environment. A total of 200 questionnaires were distributed, and 175 were received. A path model was built applying partial least squares structural equation modeling (PLS-SEM).

Communication quality has come as a partial mediator for the relationship between internal and external leadership roles and trust. Role clarity fully mediated the relationship between external leadership roles and conflict. Internal and external leadership roles showed a significant effect on leadership effectiveness, which were further related to team performance in virtual teams. Additionally, synchronous technology was used more by virtual teams.

The study did not examine cultural differences or cultural adaptation in virtual teams. Instead of the BCL theory, future research may apply attribute-based or relational-based theory to examine leadership roles in virtual team performance.

Using the BCL theory, the current study contributes to an understanding of virtual team performance and the internal as well as external role of leaders. This is relevant in an environment of extreme ambiguity such as COVID-19.

The recent COVID-19 pandemic has (triggered) lots of interest in work from home (WFH) practices. Many organizations in India are changing their work practices and adopting new models of getting the work done. The purpose of the study to look at the boundary-fit perspective (Ammons (2013) and two factors, namely, individual preferences (boundary control, family identity, work identity and technology stress) and environmental factors (job control, supervisor support and organizational policies). These dimensions are used and considered to create various clusters for employees working from home.

K-mean clustering was used to do the cluster analysis. Statistical package for social sciences 23 was used to explore different clusters based on a pattern of characteristics unique to that cluster, but each cluster differed from other clusters. Further analysis of variance test was conducted to see how these clusters differ across three chosen outcomes, namely, work-family conflict, boundary management tactics used and positive family-to-work spillover effect. The post hoc test also provided insights on how each cluster differs from others on these outcomes.

The results indicated four distinct clusters named boundary-fit family guardians, work warriors, boundary-fit fusion lovers and dividers consistent (with previous) research. These clusters also differ across at least two major outcomes like boundary management tactics and positive spillover. The high control cluster profiles like Cluster 3 (boundary-fit fusion lovers) and Cluster 4 (dividers) showed low technostress and higher use of boundary management tactics. Cluster 3 (boundary-fit fusion lovers) and Cluster 1 (boundary-fit family guardians) having high environmental influencers also showed higher positive family-to-work spillover.

Because this study is very specific to the Indian context, a broad generalization requires further exploration in other cultural contexts. The absence of this exploration is one of the limitations of this study. On the culture continuum, countries may vary from being individualistic on one extreme to being collectivistic on the other extreme. Interaction of these two cultural extremities with the individual and the environmental dimension, as espoused in this research, can be examined further in a different cultural setting.

This study has extended the work of Ammons (2013) and added external influencers as a dimension to the individual preferences given by (Kossek 2016), and created the cluster for employees in the Indian context. This study has demonstrated the importance of reduced technostress, and the use of boundary management tactics (temporal and behavioral) leads to positive family-to-work spillover. It has also emphasized the relevance of organization policies and supervisor support for better outcomes in WFH.