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Building industrial clusters is getting much more political attention and strategic orientation in all developing countries. This study started by revising the conceptual and theoretical frameworks for industrial clusters, followed by some insights and contributions about empirical bases for clusters' dynamics and processes. The study focused on the case of Agadir Agreement between four Arab countries (Egypt, Jordon, Morocco, and Tunisia), which was initiated after the Euro-Mediterranean partnerships, and the rationale of the agreement was based on the concept of cumulative value-added origin. The study based its methodology on analyzing the international and bilateral trade flows of six industrial goods from the automotive sector among the four countries and with the EU countries to detect the degree of industrial collaboration and the achieved success of each country in this sector. The study indicated that the four countries used the concept of industrial clusters for economic development, but the results of the analysis showed that till now Agadir Agreement only achieved a shallow integration, while failed to deeply integrate as one big collaborative industrial cluster.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

The purpose of this study is to explore teen-adult dialogic interactions during the co-design of data literacy activities in order to determine the nature of teen thinking, their emotions, level of engagement, and the power of relationships between teens and adults in the context of data literacy. This study conceives of co-design as a learning space for data literacy. It investigates the teen–adult dialogic interactions and what these interactions say about the nature of teen thinking, their emotions, level of engagement and the power relationships between teens and adults.

The study conceives of co-design as a learning space for teens. Linguistic Inquiry and Word Count (LIWC-22), a natural language processing (NLP) software tool, was used to examine the linguistic measures of Analytic Thinking, Clout, Authenticity, and Emotional Tone using transcriptions of recorded Data Labs with teens and adults. Linguistic Inquiry and Word Count (LIWC-22), a natural language processing (NLP) software tool, was used to examine the linguistic measures of Analytic Thinking, Clout, Authenticity and Emotional Tone using transcriptions of recorded Data Labs with teens and adults.

LIWC-22 scores on the linguistic measures Analytic Thinking, Clout, Authenticity and Emotional Tone indicate that teens had a high level of friendly engagement, a relatively low sense of power compared with the adult co-designers, medium levels of spontaneity and honesty and the prevalence of positive emotions during the co-design sessions.

This study provides a concrete example of how to apply NLP in the context of data literacy in the public library, mapping the LIWC-22 findings to STEM-focused informal learning. It adds to the understanding of assessment/measurement tools and methods for designing data literacy education, stimulating further research and discussion on the ways to empower youth to engage more actively in informal learning about data.

This study applies a novel approach for exploring teen engagement within a co-design project tasked with the creation of youth-oriented data literacy activities.

Employee burnout is increasingly coming under attention due to its negative impact on employee well-being and organisational effectiveness. This study, a systematic review, aims to evaluate the role of servant leadership and its mediators in preventing and mitigating against burnout experiences in organisations.

A preferred reporting items for systematic review and meta-analyses (PRISMA) was conducted using three databases, Academic search Complete, Embase and Scopus, in addition to bibliography searches. Articles were included if they reported on primary data, in English from inception to 2023. The mixed methods critical appraisal tool was used to assess the quality of articles, and a narrative synthesis was used to report results.

The search strategy yielded 4,045 articles, of which (N = 17), with total sample size of (N = 10,444) are included. Findings suggest that servant leadership is predictive of burnout, and that several mediators impact this relationship. Most studies were conducted in health care (n = 8) and banking (n = 3), and while the quality of the studies was mostly high (64%), the methods used were mainly descriptive and cross-sectional, which limits the extent to which causality can be inferred. A theory of change is provided based on the findings from this review and integrated with the extant literature on servant leadership theory, and can be used by organisations to support the policy, training and practice of servant leadership to reduce burnout.

Servant leadership is predictive of burnout; however, further research needs to be undertaken in this important emerging area.

This study aims to examine the cryptocurrency adoption (CA) level among Indian retail investors who use cryptocurrency as an investment and mode of transaction.

Through self-administered survey questionnaires, data is collected from 397 retail investors of Haryana (India). This study adopted a quantitative method using partial least squares structural equation modeling (PLS-SEM).

This paper offered a robust model with a high explanatory value for CA in which four of the five proposed factors of diffusion of innovation theory (trialability, compatibility, complexity and observability) and one of the two proposed factors of consumer behavioral theory (perceived value) significantly influences CA. More specifically, the absence of regulatory support is a barrier to the broad adoption of cryptocurrencies, as its regulations are necessary to mitigate or minimize uncertain outcomes.

This research primarily focuses on CA in India. Thus, it can be extended to cover diverse other countries for more precise results.

The results provide insights to the government to design the policies, better regulate and make investment strategies that can ultimately enhance CA. In addition, the study’s results also inform financial educators, policymakers, employers and academicians about the significance of several variables affecting CA in India.

From a social standpoint, this study is an advance that directs central banks and governments to develop, regulate and manage digital currencies and implement a digital currency ecosystem. Moreover, the results assist in understanding investors’ perceptions and decision-making perspectives toward cryptocurrencies through the country’s digitalization.

This paper fills the study gap to assist policymakers and cryptocurrency experts in broadening their knowledge base and recognizing prioritized intentions. Additionally, this study provides a theoretical model with the latent variable for a present and pertinent matter.

The purpose of this paper is to provide an organizing lens for viewing the distinct contributions to knowledge production from those research communities addressing the impact of competitive strategy on company performance in general, and the influence of cost leadership and differentiation strategy on organizational performance in detail.

The research methodology was based on the PRISMA review, and thematic analysis based on an iterative process of open coding was analyzed and then the sample was analyzed by illustrating the research title, objectives, method, data analysis, sample size, variables and country.

The main factor that influenced the competitive strategy is strategic growth; strategic growth has a significant influence on competitive strategy. Furthermore, competitive strategy will boost firm network, performance measurement and organization behavior. In the same way, the internal goal factor will enhance organizational effectiveness. Also, a differentiation strategy will support management practice factors, strategic positions, product price, product characteristics and company performance.

This study contributes to the literature by identifying a framework of competitive strategy factors, company performance factors, cost leadership strategy factors, differentiation strategy factors and competitive strategy with global market factors. This study provides a complete picture and description of the resulting body knowledge in competitive strategy and organizational performance.

This paper aims to investigate the relationship between entrepreneurial motivation and pharmapreneurial intention among pharmacists in Jordan.The authors also assessed the moderating effect of gender and the COVID-19 pandemic on the relationship between these two variables.

This study is a quantitative study targeting pharmacists and using a nonprobability sample. A structured questionnaire was distributed through official channels to the entire population of registered pharmacists in Jordan. SmartPLS 3 was used for carrying an advanced structural equation model analysis, and SPSS 26 for the descriptive statistics.

The three entrepreneurial motivation variables (behavioral control [BC], risk tolerance and desirability of self-employment) affected pharmapreneurial intention, with BC contributing more to pharmapreneurial intention among pharmacists in Jordan than the other variables examined. On the other hand, gender and COVID-19 did not moderate this relationship.

The authors find that entrepreneurial motivation affects pharmapreneurial intention. Consequently, the authors provide insights to policymakers and educators regarding dovetailing the recent financial literacy programs implemented in Jordanian schools with medical education in Jordan to better motivate the formation of pharmapreneurial intention.

Policymakers and educators should be dovetailing the recent financial literacy programs implemented in Jordanian schools with medical education in Jordan to better motivate the formation of pharmapreneurial intention.

To the best of the authors’ knowledge, this is the first study to examine pharmapreneurship in Jordan.

In the light of high reliance on digital technology to mitigate the consequences of the coronavirus disease 2019 (COVID-19) pandemic and its containment measures, this study investigates the factors influencing firms' decision to adopt digital technologies during COVID-19 in four Middle East and Northern African (MENA) countries, namely, Egypt, Jordan, Morocco and Tunisia.

The study used the International Labour Organization (ILO)/Economic Research Forum (ERF) COVID-19 - MENA Monitor Enterprise Survey (CMMENT), comprising 5,480 firms, surveyed during 2020–2021. The empirical model is estimated using the linear probability model (LPM) to address the problem of unobserved heterogeneity between firms, countries, and time.

The results revealed that firm characteristics, such as firm size and foreign ownership, encourage digital transformation in the business sector. Moreover, firms that face challenges during the pandemic, comply with the containment measures, and receive government assistance are more likely to adopt digital solutions. Furthermore, the results indicated that firms operating in services sector have a higher likelihood to adopt digital technology. Disaggregating the total sample into several sub-samples, the results are robust across countries and technology types, supporting the initial hypothesis that COVID-19 encourages digital transformation in the MENA region.

The study has numerous contributions. First, to the best of the authors' knowledge, this is the sole study that uses micro data collected during the COVID-19 to examine the factors influencing firms' decision to adopt and invest in digital solutions in the MENA countries. Second, the paper employs the LPM estimator to address the issue of unobserved heterogeneity between firms, countries and time. Finally, the paper offers some practical recommendations for accelerating digital transformation in MENA region.

The Russian export flow is highly concentrated on few trading partners that results in its high vulnerability to external shock. Furthermore, the Russian–Ukraine conflict and corresponding western sanctions has enhanced the need of export markets diversification for Russia. Therefore, this study is a baseline attempt to explore determinants of export flow along with identifying potential export markets. This objective is realized by employing an augmented version of gravity model on export flow of Russian Federation to 108 trading partners from 2000 to 2020.

The augmented gravity model of export flow is estimated by using employing contemporary panel econometrics such as panel generalized ordinary least square estimation technique with cross-sectional weight along with heteroskedasticity consistent white coefficients is employed to explore impact of selected macroeconomic and policy variables. Furthermore, the sensitivity analysis is performed by using panel random effect along with the Driscoll–Kraay standard errors with pooled ordinary least squares (OLS) regression and random effect generalized least square (GLS) estimator techniques. The estimated result of panel GLS technique is subjected to in-sampled forecasting technique to explore potential export markets.

The findings show that an increase in the income of trading partners and enhancement of domestic production capacity has significant positive impact on Russian export flow, whereas geographic distance has a significant negative impact. Income of trading partners emerged as major determinant of export flow with high explanatory power. Among augmented variables, the real exchange rate reveals a significant positive impact of lower intensity, whereas binary variables for the common border, common history and preferential/free trade agreement show a significant positive impact. The finding of export potential reveals a high concentration of export with existence of large potential for exports across the globe. For instance, many developing countries in Asia, Africa and America reveal high potential for Russian exports.

The findings urge Russian Federation to diversify its export markets by targeting potential export markets. Many emerging developing countries are witnessing a high potential for Russian exports, therefore attempts should be taken to diversify toward them. The expansion of existing transportation facilities along with development of cargo trade can be important policy instrument to realize objective of export diversification.

This study is the first comprehensive analysis that employs augmented gravity model to explore potential export markets for Russian Federation by using panel data of 108 global trading partners from 2000 to 2020. This finding of this study provides a framework of export diversification toward potential markets across the globe.

The oil and gas construction projects in Saudi Arabia are commonly impacted by the frequent occurrence of change orders. Therefore, this study aims at determining the factors influencing change orders in the oil and gas construction projects in Saudi Arabia.

Firstly, the factors are extracted by examining the literature and further refined through experts' feedback. Twenty-one factors were identified in this manner. Thirdly, the factors are prioritized using a questionnaire survey. Responses from 162 professionals have been collected through surveys and ranked using the significance index. The correlation between factor rankings between classes is assessed using Spearman's correlation coefficient. Lastly, using principal component analysis, a change order-related factors conceptual model is developed.

The five most significant factors were identified and ranked in a general manner or per the category involved. Four main types were involved: project management team (PMT), consultants, contractors and clients. Moreover, a change order-related factors model is proposed. The factors are grouped under four main groups: project definition and planning factors, project stakeholder-related factors, project execution-related factors and project performance and control factors.

Despite the vast factor-related literature in Saudi Arabia. Nevertheless, there has never been a study that investigates the factors influencing change orders in oil and gas projects in Saudi Arabia before. This study not only identifies the change order-related factors but also proposes a model that captures the importance of these factors. This model can aid project professionals in mitigating the impact of the most critical factors encountered during the various phases of the project.