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Amidst the COVID-19 pandemic, education has shifted to online teaching and learning. Interactivity is a crucial tool used to make online education effective. This study empirically examines the role of interactivity in higher education and its influence on students' behavioral outcomes, specifically focusing on soft skills and personality upgradation.

A quasi-experimental research design was carried out for post-graduate students undergoing a business communication course from four major institutions. For analysis, t-test, confirmatory factor analysis (CFA) and partial least squares structural equation modeling (PLS-SEM) have been employed. Experimental research has established the causal relationship between interactivity, personality and soft skill upgradation (SSU).

It was found that the theoretical structural model has a rational model-fit validity. Resultantly, practitioners may use prior knowledge of virtual community (VC) members to enhance web interactivity, thereby increasing social identity and social bonds in a group for more meaningful and effective delivery of online courses.

The major limitations lie in its context-dependent nature, predominantly influenced by the pandemic-induced mandatory online learning. The study's cross-sectional design also inhibits its ability to assess goal-directed behaviors over time, necessitating further longitudinal research.

The study is one of the pioneering pieces of research that examines the role of pre-defined grouping and enhanced web interactivity in VCs in the context of online learning, especially during the COVID-19 pandemic. Integrating theories of web interactivity, social bond theory (SBT) and social identity theory (SIT) provides a novel understanding of cognitive and social influences that drive meaningful online discussions and their impacts on knowledge enhancement and personality development. Its findings have implications for the design of effective online learning environments and e-learning pedagogy, contributing to the growing domain of information and communication technology (ICT)-enabled education.

This study aims to explore the innovation deployment of construction contracting firms through exploratory–exploitative learning and organisational ambidexterity.

Firstly, a literature-based conceptual framework was developed to explain innovation implementation through exploratory–exploitative learning and organisational ambidexterity. A prominent Hong Kong construction contracting firm was then selected as the case study to explore its innovation deployment at different organisational levels (i.e. firm and project levels). Qualitative data were attained by conducting 12 semi-structured interviews with industry experts and document analysis. The thematic analysis using NVivo 12 software was adopted to analyse data.

Findings reveal that the case study firm successfully fosters innovation when ambidexterity is achieved through the balance between exploratory (i.e. radical innovation) and exploitative learnings (i.e. incremental innovation).

Establishing uniform ambidexterity (i.e. 50:50) at the firm or project level is not mandatory to deploy innovation successfully. The ratio can vary based on the characteristics and requirements of construction firms.

This paper shall motivate construction practitioners to adopt radical–incremental innovation ambidexterity in firms and ultimately enhance the productivity and efficiency of the construction industry.

Previous construction innovation research has frequently explored firm or project-level innovation separately. This study identified a multi-level focus on innovation. Through the lens of exploratory–exploitative theory, different forms of innovation ambidexterity for different levels are suggested rather than one specific ambidexterity.

This study intends to examine the relationships between external knowledge sourcing (EKS), organizational ambidexterity (OA), and manufacturing performance (MP) in the context of large manufacturing firms within a dynamic environment setting. The research framework and derived hypotheses are grounded in the knowledge-based view (KBV) and dynamic capability (DC) theories.

A self-administered online survey was used in this study to gather data. Respondents were the operation leaders representing large manufacturing firms. The collected data were screened for invalid responses, and hypotheses were tested using structural equation modeling.

The study reveals that OA and EKS play key roles in achieving a better MP. Likewise, OA also mediates the relationship between EKS and MP.

Cross-sectional data were collected from large manufacturing firms within five focus sectors in Malaysia. A similar study can be conducted with more sectors of different contexts to confirm the findings.

Knowledge is critical for the firm to react to environmental dynamism, and the ability to manage it ambidextrously will enable the firm to enhance its performance.

This study offers empirical insights from the perspective of the large manufacturing firms in Malaysia, which are undergoing an Industrial Revolution 4.0 (IR4.0) transformation. This study bridges the knowledge gap by revealing the value that EKS can facilitate MP, exploring OA as the prevalent factor and demonstrating how KBV and DC can be applied in this study.

This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.

A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.

Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.

Implications are limited to the e-commerce B2C domain.

The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.

The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.

This paper aims to explore how female academics use cronyism to cope with the lack of emancipative support resulting from their intense teaching and research duties, poor representation at senior administrative levels and their exhausting familial commitments.

Qualitative semi-structured interviews were conducted with 32 female academics working full-time at four public universities in Egypt.

The findings showed that the low action resources (considering their unreasonable teaching loads, research requirements and supervision engagements), emancipative values (the unfair representation of female academics at senior administrative levels) and civic entitlement (universities not serious about promoting gender equality) are perceived by female academics as a lack of empowerment that necessitates their adoption of cronyism as their main coping strategy. Moreover, in male-dominated societies, female academics who do not have the power to shape their work-related status tend to use undesirable behaviours such as cronyism to mitigate the negative consequences of the shocks they encounter.

This paper contributes by filling a gap in human resources management in which empirical studies on the relationship between cronyism, emancipation and career shocks have been limited so far.

Business growth is one of the most studied areas over the years. However, with the current uncertainty and entrepreneurial dynamism it becomes relevant to consider new variables such as entrepreneurial skills and competencies that influence its development. Accordingly, this research refers to the impact that the individual's skills have on the entrepreneurial environment. For this purpose, a survey has been developed of employees of different organizations considering the variables of high degree of proactivity in the employees' attitude, entrepreneurial training, innovation, previous experience or risk aversion.

The research has been conducted through fuzzy set qualitative comparative analysis (fsQCA) and the result shows the differences between the combination of variables for business growth through the consideration of sales growth and profit.

The results of this research provide new insights that allow the development and boosting of business growth.

The main contribution of this work is to pay attention to the human team of startups and show the role that this has in their growth.

Cyberbullying has become one of the reasons behind the increase in psychological and medical problems. A need to prevent recurrences of cyberbullying incidents and discourage bullies from further bullying the victims has risen. This problem has attracted the attention of all stakeholders across the globe. Various researchers have developed theories and interventions to detect and stop bullying behavior. Previously, researchers focused on helping victims, but as the times have changed, so has the focus of researchers. This study aims to analyze scientific research articles and review papers to understand the development of the knowledge base on the topic.

This study analyzes the performance of literature on cyberbullying perpetration (CBP) using the widely accepted bibliometric analysis techniques: performance analysis and science mapping. The study is based on a dataset extracted from the Web of Science database. Initially, 2,792 articles between 2007 and 2022 were retrieved, which were filtered down to 441. The filter was based on various criteria, but primarily on CBP. VOSViewer and MS Excel were used to analyze the data. In addition, VOSViewer was used to create “bibliometric citations, co-citations, and co-word maps.”

The findings include publication and citation quantum and trends, the top 20 active countries, the most significant research articles and leading journals in this domain. Major themes or clusters identified were “Cyberbullying and victim behavior,” bullying behavior, adolescents and intervention, “cyberbullying associations,” and “cyberbullying personality associations.”

The study is unique because it analyses research articles based on cyberbullies, whereas past studies explored only the victims' side. Further, the present study used the Web of Science database, whereas most studies use the Scopus database.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.