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Widespread technology adoption in tourism enables tourists to be active content creators, thus, influencing destination brands through co-creation. This study examines value co-creation, social commerce information sharing, and destination brand equity.

A quantitative approach was applied to analyse data collected from a global online survey. Hypotheses were tested using PLS-SEM analysis.

Results show that destination brand equity is positively influenced by value co-creation. Additionally, social commerce information sharing mediates the relationship between value co-creation and destination brand equity.

The article adds new insights to tourism marketing by investigating value co-creation, social commerce information sharing and destination brand equity. It also offers interesting implications for destination managers to improve Vietnam as a destination brand.

This paper is among the first to test the mediating role of social commerce on value co-creation and destination brand equity.

How to identify the critical success factors (CSFs) of public health emergencies (PHEs) is of great practical significance to carry out a scientific and effective risk assessment. The purpose of this paper is to address this issue.

In this paper, the authors propose a new approach to identify the CSFs by hesitant fuzzy linguistic set and a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. First, a larger group of experts are clustered into three groups according to similarity degree. Then, the weight of each cluster is determined by the maximum consensus method, and the overall direct influence matrix is obtained by clustering with hesitant fuzzy linguistic weighted geometric (HFLWG) operators. Finally, the overall direct influence matrix is transformed into the crisp direct impact matrix by the score function, and 11 CSFs of PHEs are identified by using the extended DEMATEL method.

In addition, an example of PHEs shows that the approach has good identification applicability. The approach can be used to solve the problems of fuzziness and subjectivity in linguistic assessments, and it can be applied to identify the customer service framework with the linguistic assessments process in emergency management.

This paper extends the above DEMATEL method to study in the hesitant fuzzy linguistic context. This proposed hybrid approach has a wider application in the high-risk area where disasters frequently occur.

Digital transformation continues to rapidly progress in higher education globally, spanning all aspects of higher education operations, values and culture. Despite expanding literature, guidance remains focussed on emergency application during pandemic lockdowns and/or on single organisational case studies. Digital transformation frameworks that move beyond these foci are heavily criticised for being commercially contextualised (outside of higher education) and are often too narrowly conceptualised. The purpose of this paper is to review the most common framework currently used in the UK, which takes a strategic and organisational perspective on digital transformation.

This is a technical review article that summarises key guidance for organisational digital capability and then reflects on its application in the UK (a developed economy and higher education system) and in Vietnam (one of the fastest-growing economies with a developing higher education committed to digital transformation) as an initial attempt to explore its applicability beyond the UK context. Vietnam has been chosen as a reference context, given its significant current digital transformation policy reform at the national level and as a collaboration partner with the UK in its digital transformation.

The guidance highlights six core areas to consider for digital capability: information and communication technology (ICT) infrastructure, content and information, research and innovation, communication, learning, teaching and assessment and organisational digital culture. Although the framework is normative, findings suggest it is sufficiently open-ended to enable its users to determine practical steps to drive digital transformation. However, complementary tools are suggested to deal with the rapidly developing digital transformation policy context of Vietnam.

This is the first time a review has been conducted from the perspective of different countries, with a view to supporting leaders, managers and policymakers in the UK, Vietnam and other Association of South Eastern Nations (ASEAN) networks in their own digital transformation transitions.

This paper aims to examine the impact of information and telecommunication technologies (ICT-proxied by mobile phone subscription and Internet usage) on carbon dioxide (CO2) emissions in the Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2018.

The Cross-section Autoregressive Distributed Lag (CS-ARDL) model is employed to address the potential cross-section dependence problem. Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used to test for robustness of results.

Results reveal contrasting effects of mobile phone subscription and Internet usage on CO2 emissions. While mobile phone penetration helps mitigate CO2 emissions, Internet usage tends to increase the emissions. Findings show that renewable energy is beneficial to the environment while economic growth is harmful to the environment. The effects of financial development and trade openness seem negligible.

This study offers practical implications for policymakers. As different proxies of ICT could have contradictory impact on CO2, governments should be cautious against utilizing ICT to mitigate CO2. Findings point to the benefits of renewable energy in alleviating CO2 emissions. Therefore, governments are strongly advised to implement policies facilitating renewable energy consumption.

Previous studies ignored the problem of cross-section dependence which could lead to biased results and cause misleading inferences. This study aims to fill this void in the literature.

As a new human resource management practice, developmental idiosyncratic deals (developmental I-deals) play an important role in attracting, retaining and motivating employees to promote creativity. Based on the social cognitive theory, the purpose of this study is to examine the impact of developmental I-deals on team creativity through team creative-efficacy and the moderating role of error management atmosphere in this process.

To reduce the effects of common method biases and causal lag effect, this study was divided into three stages for data collection, with a time interval of a month. A total of 365 employee samples (72 team samples) from seven internet enterprises in Shanghai and Wuhan were selected, and Bootstrap method and Johnson-Neyman method were used to test the hypothesis.

The results of this study show that developmental I-deals positively affect team creativity, and team creative-efficacy mediates the relationship between developmental I-deals and team creativity. Error management atmosphere strengthens the impact of developmental I-deals on team creative-efficacy and further strengthens the indirect effect of developmental I-deals on team creativity through team creative-efficacy.

Based on the social cognitive theory, this study examines the impact of developmental I-deals on team creativity through team creative-efficacy and the moderating role of error management atmosphere in this process. First, the study of I-deals category was further refined. The existing research defines the concept of I-deals in a general way and does not classify it in detail. Second, the internal mechanism of I-deals is revealed. Third, it expands the multi-level research of I-deals.

This paper aims to adopt the dynamic capabilities view to investigate the relationship between managerial ties (i.e. business and political ties), dynamic capabilities and innovation climate on ambidextrous innovation (i.e. balanced and combined ambidextrous innovation), in the renewable and sustainable energy context. It also examines the mediating effects of dynamic capabilities between managerial ties and ambidextrous innovation (i.e. balanced and combined ambidextrous innovation), and moderating effects between dynamic capabilities and ambidextrous innovation relationships.

Multilevel analyses conducted using AMOS 26 on 288 employees working in 47 UAE energy firms.

Results found that business ties influences balanced and combined ambidextrous innovation indirectly, whereas political ties only impact combined ambidextrous innovation indirectly through dynamic capabilities. Dynamic capabilities insignificantly mediated managerial ties–ambidextrous innovation and political ties–balanced ambidextrous innovation relationships, with stronger indirect effect on combined than on the balanced dimension. Findings also indicate that innovation climate is the crucial moderator between dynamic compatibilities and ambidextrous innovation, as well as balanced and combined ambidextrous innovation, with stronger effect on balanced dimension than the combined.

This study addresses recent calls by highlighting the role of dynamic capabilities, an important yet underexplored organizational capabilities in the innovation and ambidexterity literature. Also, this study advances insight into how balanced and combined exploration–exploitation innovation and dynamic capabilities are connected and enhances the understanding into how organizational factors stimulate dynamic capabilities leading to superior innovation.

Since the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.

An exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.

The study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.

The authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.

This paper examines asymmetric multifractality (A-MF) in the leading Middle East and North Africa (MENA) stock markets under different turbulent periods (global financial crisis [GFC] and European sovereign debt crisis [ESDC], oil price crash and COVID-19 pandemic).

This study applies the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method of Cao et al. (2013) to identify A-MF and MENA stock market efficiency during the COVID-19 pandemic.

The results show strong evidence of different patterns of MF during upward and downward trends. Inefficiency is higher during upward trends than during downward trends in most of the stock markets in the whole sample period, and the opposite is true during financial crises. The Turkish stock market is the least inefficient during upward and downward trends. A-MF intensifies with an increase in scales. The evolution of excessive A-MF for MENA stock returns is heterogeneous. Most of the stock markets are more inefficient during a pandemic crisis than during an oil crash and other financial crises. However, the inefficiency of the Saudi Arabia and Qatar stock markets is highly sensitive to oil price crashes. Overall, the level of inefficiency varies across market trends, scales and stock markets and over time. The findings of this study provide investors and policymakers with valuable insights into efficient investment strategies, risk management and financial stability.

This paper first explores A-MF in the MENA emerging stock markets. The A-MF analysis provides useful information to investors regarding asset allocation, portfolio risk management and investment strategies during bullish and bearish market states. In addition, this paper examines A-MF under different turbulent periods, such as the GFC, the ESDC, the 2014–2016 oil crash and the COVID-19 pandemic.

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

In recent years, there has been a growing trend of individuals willingly opting for employment positions that do not fully use their education, skills and abilities, a phenomenon known as voluntary overqualification. This study aims to investigate the factors that influence and the formation mechanism of this emerging phenomenon. Drawing upon social cognition theory, this study explores the relationship between work values and voluntary overqualification while also examining the mediating role of the future work self and the moderating role of perceived marketability.

This study used a longitudinal approach, collecting data through questionnaires administered at multiple time points. The sample consisted of 607 employees from various departments of five Chinese companies. Regression analysis using the PROCESS macro in SPSS was used to test the research hypotheses.

The results indicate a positive relationship between employees’ work values and voluntary overqualification. Furthermore, this relationship is mediated by the future work self. Additionally, perceived marketability plays a moderating intermediary role in the whole model.

This study contributes to the overqualification literature by introducing a novel type of overqualification and unveiling the mechanism by which work values influence voluntary overqualification. The findings provide insights for understanding and managing employees who are voluntarily overqualified.