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This chapter examines the competitiveness of the tourism cluster in the United Arab Emirates (UAE) by applying Porter's competitiveness of nation diamond model, with its four dimensions: factor conditions, demand conditions, the related and supporting industries, and, lastly, the firm's strategy and rivalry. Specifically, we provide a thorough analysis of the UAE's strategic plans, initiatives, and tactics to cultivate competitiveness in tourism across the nation. This includes the draft of a vision for the nation, decisions to build and reinforce their infrastructure, determination to develop and nurture skilled workforce, ability to respond innovatively to their customers' evolving demands, selection of the appropriate base for competition, and, finally, continuous melioration of related industries. Examining secondary data and by reviewing governmental reports, we find that UAE did not cultivate a national advantage by owning random natural resources, but rather by having a strategic intent to converge all their efforts and to deliberately build a coherent cluster in the tourism sector. The chapter also provides some limitations and recommendations for future research.

This study aims to provide current and organised insights into past published studies on tourism destination competitiveness (TDC) in the past decade through systematic literature analysis.

A comprehensive review was performed by systematically gathering the literature published from 1983 to 2021 and coded according to categories such as author, year, article title, name of journal and TDC determinants.

The key findings of this review reveal that no universal set of items, attributes or indicators to measure the competitiveness of tourism destinations exists; the complexity and variability of many definitions and measuring elements from various perspectives portray the multi-faceted concept of competitiveness; and synergistic connection between the source of comparative and competitive advantages of TDC focusing on destination image, tourism experience and loyalty.

Research works considered in the study are only from indexed and peer-reviewed journal publications.

The study findings reveal a lack of studies that address the relationship between destination image, tourism experience and loyalty within the TDC realm. Future studies should consider complementing the tourism supply and demand side to avoid a “strategic drift” of TDC concepts, perceptions and practices.

Since competitiveness is crucial in international trade, this paper contributes to the literature by interrogating the information and communication technology (ICT)-trade nexus on competitiveness in Eastern and Western European countries. Does ICT usage promote or hinder the impact of trade openness on competitiveness? This study attempts to answer two questions: (1) is the interaction of trade and ICT significant in promoting competitiveness? (2) Is the effect significantly different by European classification?

With data on 17 European countries from 2007 to 2020 and using mobile phones and fixed telephone usage as ICT indicators, the study engages the bootstrapped ordinary least squares (BOLS) and method of moments quantile regression (MM-QR) techniques to probe the discourse.

The empirical findings reveal that (1) the interaction of trade and ICT boost competitiveness; (2) the effect of mobile phone is consistent across the full, East, and West European samples; (3) the interaction effect is also significant across the conditional distribution of competitiveness and (4) mobile phones and fixed broadband usage reveal “leapfrog” effect across the quantiles. Overall, the study submits that ICT usage will enhance the impact of trade, and thus, ICT is a critical enabler of competitiveness in Europe; policy recommendations were discussed.

To the best of the authors' knowledge, this is the first study examining the interaction effect of trade openness and ICT usage on competitiveness in Europe. In other words, the authors attempt to analyze how ICT usage influences trade-competitiveness dynamics. To fill the gap in the literature, the authors' use a sample of 17 European countries from 2007 to 2020. The variables of interest are the competitiveness index, trade openness, and four ICT indicators (mobile phone, fixed telephone subscriptions, fixed telephone subscriptions, and Internet users).

This study aims to identify the main factors affecting export competitiveness and its barriers, focusing on the minerals industry so that a scale is achieved for measuring export competitiveness in this industry.

The research was conducted with a mixed method approach in the minerals industry. Among the active companies involved in this industry, 34 export companies and export management companies were selected and evaluated. In the qualitative phase, 18 experts and managers of the industry were interviewed to identify the factors affecting the export competitiveness of these companies and the barriers ahead of them. In the quantitative phase, a questionnaire was distributed among 412 managers and experts in this industry to categorize the identified factors and to measure the relationships among them. For data analysis in the qualitative phase, theme analysis was used. For the quantitative phase, factor analysis and structural equation modeling were adopted.

In addition to identifying the main components affecting the competitiveness of companies in exporting minerals as well as the main barriers ahead of them, the findings of the current research categorized these components using factor analysis. These components were categorized into factors, such as manufacturing factors, demand conditions, related and supporting industries, structural factors, competitive strategy and governmental supports. Afterward, their impacts on export competitiveness were measured and supported.

Although some studies have been conducted to examine the competitiveness in different industries, no research has been found that has examined and identified the main factors affecting export competitiveness and their impacts in the minerals industry with a mixed quantitative and qualitative approach. The findings of this research may help managers and policymakers, at the industrial and national levels, to reach a scale for assessing the export companies involved in this industry by identifying the most essential factors of export competitiveness of minerals. Furthermore, the findings of this research can act as a model for future researchers to develop a scale for export competitiveness in other industries.

Blood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.

This study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.

The results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.

This study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.

This study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

The purpose of this paper is to determine whether the way competitiveness is measured matters, as well as to analyze the relationship between tax burden and economic competitiveness using a variety of model specifications.

This paper uses statistical models aimed at finding the relationship between taxes and different measures of economic competitiveness, such as gross domestic product per capita, employment and a third-party competitiveness index. Other variables are also considered, and statistical procedures such as lag specifications and “white period” errors are used to address problems of endogeneity and serial correlation.

The models find no robust relationship between taxes and competitiveness. Certain models find correlations between the tax burden of specific income groups with economic competitiveness, but these vary in direction and are difficult to interpret. This follows past research, which shows different results depending on the period analyzed, measure of competitiveness and other variables used.

This paper looks at many of the different measures of competitiveness, control variables and periods that are used in the previous literature and shows how any changes to these model specifications cause inconsistent results. This paper highlights that, because results can vary greatly depending on the model, researchers and policymakers must be careful when drawing any conclusions from relationships between taxes and economic competitiveness.

The objective of this study is threefold–first, to develop a Regional Competitiveness Index (RCI) for measuring competitiveness of sub-national regions for India; second, to test this index for its ability to explain regional growth, which validates usage and applicability of this index; and third, to further investigate if the competitiveness of states is in turn caused by economic growth, i.e. it is tested if there is a bidirectional causality between competitiveness and regional growth.

The data of indicators used in the index are from sources available freely in public domain. The competitiveness index is constructed using equal weightage supported by principal component analysis (PCA) technique. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMMs) is used for this dynamic regression estimation.

Based on RCI score, states have been ranked and through rank analysis, the authors observe the performance status of these sub-national regions and are able to categorize them as improving, no change or deteriorating in regional competitiveness. Using the GMM estimation, the association between RCI and economic growth is found to be significant at 10% level. This shows that regional competitiveness as captured through the RCI score is able to explain regional economic growth and economic disparity among the sub-national units. Further, that RCI score is found to Granger-cause growth, while growth does not lead to better RCI scores. This establishes the usefulness of RCI as an important policy variable to compare states and provide direction for sectoral reforms.

The limitations of the study include (1) broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment, and (2) data constraints as it is a longitudinal study. The study implies that the composite index could capture differences in regional competitiveness explaining regional economic disparity and that competitiveness causes higher economic growth and not vice versa.

The RCI score can prove to be a useful indicator of economic performance of different states and can be used by national and state policymakers to compare and assess regional disparity among different states. The pillar-wise scores will be useful for in-depth study of weakness and strength of the sub-national territories.

Construction of an RCI for sub-national territories and analysis of panel data for longitudinal study of ten years is unique in the regional competitiveness literature.

This paper aims to identify factors that affect the sports tourism destination's competitiveness on a small island. Hence, this study looks at and evaluates these factors. The study then comes up with a model that clarifies the interrelationships between these factors.

The authors broke down the data analysis process into three steps. The first step was to conduct a literature review and use industry and academia experts' help to determine the essential aspects (fuzzy Delphi method). Then, a hierarchical model was developed, and the factors were categorised using the interpretive structural modelling (ISM) approach. Factors' driving and dependency power were also determined using MICMAC analysis.

This work has identified 13 key factors related to the sports tourism destination's competitiveness on a small island. For a small island like Kish Island, the two independent variables (government support and destination political stability) that define the institutional framework for the destination are most important. Building corresponding competitive and support strategies to address these two independent variables is thus beneficial.

The research's results provide decision-makers, practitioners, and researchers with new insights into the hierarchical model of determinants. The study will fill the existing gap between theory and practice.

Sports tourism destination managers on small islands may benefit from the proposed model since the model will enable them to organise the managers' priorities better to enhance the managers' destinations' competitiveness and provide tourists with a more accurate depiction of the destination.

According to the authors' knowledge, the research design presented in this article has provided the first attempt to hierarchical analyse these factors and develop a model for sports tourism destination competitiveness on small islands and destinations with less-developed economies. This study fills the gap in the destination competitiveness and sports tourism literature by not only identifying the key influencing factors but also examining the interactions between these factors and providing empirical evidence supporting their relationships.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.