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This study investigates the implications and significance of immersive technologies (viz. metaverse, virtual reality, and extended reality) in organizational learning and development.

Employing a strategy map (using Biblioshiny) and network analysis (using VOSViewer), the study analyzed a total of 189 Scopus-indexed documents, spanning the period 1997 to 2023.

The findings revealed four thematic clusters, knowledge management, training, e-learning, and technology. Each cluster provided insights into the various facets of development and learning in respect to these technologies. The strategy map identified key themes, revealing core ideas, emerging trends, and foundational concepts within the domain.

Organizations can utilize this study to incorporate metaverse, virtual reality, and extended reality in organizational development, optimizing training and boosting employee experience and productivity.

While most literature delves into the technical side of immersive technologies, our study uncovers their impact on development and learning in organizations, addressing a critical research gap and offering a guiding framework.

This research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This study aims to explore the impact of oil prices on housing prices using Pakistani annual data from 1973 to 2021.

The Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests were used for unit-root testing, whereas the johansen-juselius test was used for cointegration. For the short-run, the error correction model is used and the robustness of the model is checked using the dynamic ordinary least squares (DOLS) and fully modified OLS (FMOLS). The cumulative sum (CUSUM) and CUSUM of Squares tests were used to check the stability of the model, while parameter instability was confirmed by the Chow breakpoint test. Finally, the impulse response function was used for causality.

According to the findings, rising oil prices, among other things, have an impact on housing prices. Inflation is the single most important factor affecting not only the housing sector but also the entire economy. Lending and exchange rates have a significant impact on housing prices as well. The FMOLS and DOLS results suggest that the OLS results are robust. According to the variance decomposition model, housing prices and oil prices are bidirectionally related. The Government of Pakistan must develop a housing policy on a regular basis to develop the country’s urban housing supply and demand.

It is suggested that in Pakistan, the rising oil prices is a problem for the housing prices as well as many other sectors. The government needs to explore alternative ways of energy generation rather than the heavy reliance on imported oil.

Pakistan has been experiencing rising oil prices and housing prices with the rapid urbanisation and rural–urban migration. The contribution to the literature is that neither attempt (as to the best of the authors’ knowledge) has been made to check the impact of rising oil prices on housing sector development in Pakistan.

This study aims to examine the association between globally responsible leadership (GRL) and pro-environmental behavior (PEB), specifically probing the mediating role of green management initiatives (GMI) in this relationship.

This study used a quantitative research design, using survey data from 390 participants working in manufacturing sector organizations in one of the emerging economies in the Asian region, namely, Pakistan. AMOS was used to test the hypothesized relationships.

The results reveal that GRL has a significant positive link with GMI and PEB. In addition, this study found that GMI mediates the association between GRL and PEB, suggesting that GRL indirectly promotes PEB through the implementation of GMI.

This study has several limitations, including its reliance on self-reported data, its cross-sectional design and its focus on participants from only one nation. Future research may benefit from using mixed-study designs and diverse samples from multiple industries and nations.

The results suggest that businesses can promote PEB among their staff by adopting GRL and implementing GMI. In doing so, businesses can demonstrate their commitment to sustainability, enhancing their credibility and competitive advantage.

This research contributes several new insights to the existing literature on sustainable leadership. First, it provides empirical evidence to support the hypothesis that GRL, GMI and PEB are interrelated. Second, it highlights the mediating role of GMI in this relationship.

This study aims to quantitatively consolidate the research conducted over the past four decades on how internal branding activities drive employee commitment. It summarizes several operationalizations of internal branding and tests the moderating effect of employee’s personal characteristics and job characteristics on the relationship between internal branding and employee commitment.

This paper uses meta-analysis as the research methodology. The analysis includes a sample of 65 studies (from 62 published works), yielding 226 effect sizes (coded into 82 composite effect sizes) over an aggregated sample of 21,706 respondents.

This study finds that brand communication, brand-centered human resource management (HRM), training and development, organizational support and culture, brand-centered leadership and an excellent reward system are the key operationalizations of internal branding. Furthermore, employee’s personal (education, age and gender) and job (tenure, work status and level of customer orientation) characteristics significantly moderate the internal branding–employee commitment relationship.

Limited empirical literature on some of the internal branding operationalizations such as brand-centered HRM and rewards has curbed the scope of moderator analysis.

This paper proposes some effective ways of implementing internal branding strategies and provides support for boundary conditions that brand managers should consider to strengthen the impact of internal branding activities on employee commitment.

As per the authors’ knowledge, this paper is among the few quantitative consolidations of four decades of research on the internal branding–employee commitment relationship.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

This study aims to examine the effect of governance on the consumption of modern renewable energy in the East African Community (EAC), controlling for economic growth, trade openness and foreign direct investment (FDI).

The study relied on secondary data sourced from the World Development Indicators, World Governance Indicators and the International Energy Agency (IEA) for the EAC from 1996 to 2019. A panel Cross-Sectional Augmented Distributed Lag (CS-ARDL) model and second-generation panel data models were employed in the analysis.

The findings indicate that poor governance and inadequate FDI are significantly responsible for the low level of modern renewable energy consumption (MREC) in the EAC. On the other hand, trade openness significantly enhances MREC, while GDP per capita has no significant effect on MREC.

The consumption of modern renewable energy sources (excluding the traditional use of biomass) and its determinants, as most studies focus on renewable energy consumption as a whole. The study also employed the panel CS-ARDL model and second-generation panel data models.

Economic ties and formation of trade blocks escalates the movement of goods among the participants and bring different economic and structural changes. Therefore, the current research emphasises on the distribution of market structure and industrial value added among the participant countries of China–Pakistan economic corridor project while focussing on pre and post FTA status.

This study utilises the footloose capital model for analysing whether China or Pakistan is more suitable for attracting factors of production to increase their share of industrial value added. For econometric analyses the current research utilises data from 1995 to 2018 and maximum likelihood effect method to assess factors that affect regional value-added distribution.

Results show that both countries owe different level of economic developments. Effect of capital is, comparatively, similar for both countries while Pakistan supports trade openness which points towards the fact of positive utilisation of abundant labour resources in Pakistan by establishing industrial structure either through domestic capital formation or foreign investment. Whereas, share of labour and trade openness of China positively affect value added production of China.

This is one of the unique studies that studies the regional economic treaties usefulness for any developing country across Asia. Where this study uses the footloose capital model and maximum likelihood method for its analysis which is not previously done, while for detailed analyses the study further divides the timeframe into two parts as pre-FTA ranges from 1995 to 2006, post-FTA from 2007 to 2018 while overall results consist of whole-time frame.

This study examines the evidence of the impact of climate change on the financial performance of basic materials companies in Vietnam.

The research sample includes eighty-two basic materials companies listed on the Vietnamese stock market from 2003 to 2022. This study used one-way and two-way fixed-effects feasible generalized least squares (FGLS) estimation methods.

Climate change, measured through variables including changes in temperature, average rainfall, greenhouse gas emissions and rising sea levels, has a negative impact on the financial performance of companies in this industry. The study also found that, with rising temperatures, the financial performance of steel manufacturing companies decreased less than that of coal mining and forestry companies, but increasing greenhouse gases and rising sea levels reduced the financial performance of steel companies. We did not find evidence of any difference in the impact of climate change on the financial performance of basic materials companies before and after the UN Climate Change Conference (COP 21). This is a new finding, which is consistent with empirical studies in Vietnam and different from previous studies in that it provides new evidence on the impact of climate change on the financial performance of basic materials companies in the Vietnamese market and cross-checks the impact of climate change by sector and over time.

To the best of our knowledge, this is one of the first articles on climate change and the financial performance of basic materials companies.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.