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This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.

From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.

The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.

This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.

This paper aims to identify the main dimensions that determine the ability of cities to compete as locations for business and hubs for investment which can help policymakers to manage and prioritize urban development strategies.

A composite indicator is proposed as a weighted aggregate of sub-indicators for the identified component dimensions (basic, efficiency-related and innovation-related competitiveness). The indicator is used to draw up a ranking of 159 European Large Urban Zones (LUZs) located in 26 EU countries based on 31 indicators, broken down into the three core dimensions of urban competitiveness identified.

The dimensions underlying urban competitiveness in relation to the location of firms and attracting investment determine the level of economic development of the LUZs. The most competitive cities in the sample have a high level of economic development, and the innovation dimension is the most significant one for the three groups of cities considered, followed by the efficiency dimension and, to a lesser extent, the basic dimension.

The findings provide guidance to policymakers on the most relevant dimensions for urban competitiveness.

This paper contributes to the literature shedding light on the complex relationships between efficiency-related and innovation-related factors with regard to urban competitiveness.

Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.

After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.

The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.

On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.

The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.

The purpose of this paper is to analyze the patterns of location of key activities for break-out in corporate competitiveness. The key objective is to identify linkages that may exist among the location of corporate center activities, innovation capabilities and the break-out.

Patterns of location of corporate center across the world have been explored first, using sample data from Global 500. For the context of innovation and India, two polar locations were selected. The patterns in the growth of focal firms from the locations were evaluated using select competitiveness criteria such as revenues, profits and assets, based on data of a larger sample from Global 2000.

Findings support the view on “role of location with innovation clusters” such as Bangalore, particularly for competitiveness of born global firms. Surprisingly, Mumbai has increased its percentage share of contributions in terms of revenues and profits, indicating sustenance of cluster, entrepreneurial and other advantages.

Considering the enormous scope for enhancing contributions of emerging-country multinational enterprises to the world economy, decisions related to break-out in competitiveness are critical. Depending on strategic intent and the role of innovation and internationalization, firms can take better decisions related to the location of specific corporate activities to foster multinational enterprise (MNE) competitiveness.

The findings may inspire key stakeholders to take decisions that enhance sustainability of city clusters and communities.

Analyzing the role of location of key corporate activities, for the phenomenon “break-out to higher stages of competitiveness”, is a unique contribution. These concepts and findings can be of high value to firms and MNEs thinking long term about location or relocation of corporate center activities, particularly for innovation.

As the contradiction between economic development, resource and environment has become increasingly prominent, low-carbon competitiveness has received worldwide focus. This study aims to examine low-carbon competitiveness in 31 provinces (cities and regions) of China.

An evaluation index system for low-carbon competitiveness in China has been constructed, which is composed of 25 economic, social, environmental and policy indicators. To study the state of low-carbon competitiveness and resistance to China’ development of low-carbon competitiveness, this study uses a combination of the catastrophe progression model, the spatial autocorrelation model and the barrier method.

China’ low-carbon competitiveness gradually decreases from coastal to inland areas: the Tibet and Ningxia Hui autonomous regions are the least competitive regions, while the Shandong and Jiangsu provinces are the most competitive areas. The spatial correlation of the 31 provinces’ low-carbon competitiveness is very low and lacks regional cooperation. This study finds that the proportion of a region’ wetland area, the proportion of tertiary industries represented in its GDP and afforestation areas are the main factors in the development of low-carbon competitiveness. China should become the leader of carbon competitiveness by playing the leading role in the Eastern Region, optimizing the industrial structure, improving government supervision and strengthening environmental protection.

The paper provides a quantitative reference for evaluating China’ low-carbon competitiveness, which is beneficial for environmental policymaking. In addition, the evaluation and analysis methods offer relevant implications for developing countries.

Given the rapid growth of the Chinese cruise market, several Chinese cities are attempting to become a hub for cruise ships. The aim of this study is to evaluate the competitiveness of those cities with regard to hosting cruises. It employs a cloud model that transforms the qualitative description of competitive indicators into quantitative measurement and assesses the competitive advantage and specialization of the top homeports in China. Questionnaires are delivered to experts from eight cruise ports in China and the cloud model based on 14 evaluation factors is used to analyze the competitiveness of the ports under investigation. The result shows that the city’s scale, population, and development have been the main factors for assessing the competitiveness of port cities. The research provides insight about the Chinese cruise port cities’ competitiveness, which is particularly useful for future development decision and marketing strategies of ports and prospective destinations.

The aim of the chapter is to identify the pattern of city–region relations in Polish spatial and economic development. Based on the regression analysis of GDP per capita growth in chosen cities and their regions, conclusions are drawn on: differences in urban development (measured by GDP per capita growth) between cities and their surrounding regions and the direction of the core-periphery mechanism (backwash vs. spread). Findings of the research enabled us to answer the questions of whether urban Poland follows the core-periphery model of development, and to identify the stage of this theoretical approach at which Polish cities might be. For the majority of studies, cities and regions follow the backwash mechanism in their relations with the surrounding regions; however, the trend of this impact differs. Warsaw is a city where the dependence on its region’s resources is decreasing; nevertheless, other findings presented in the chapter allow the statement that Polish cities reach for their region’s resources and the core-periphery mechanism is characterised by the backwash effect. The following chapter fills in the gap in urban competitiveness studies, as they usually concentrate on specific case studies and rarely use larger panels for analysis. Such approach enables us to draw conclusions for the overall urban development patterns in Poland. Also, the issue of growth spread and city–region relations is rarely found in the Polish urban research.

The theory of competitiveness of cities is based on Porter’s Diamond Theory. There is a relation between housing and urban competitiveness. The adequacy of land supply and allocation of land for new housing development is integral. This paper aims to estimate the required number of housing units to secure housing needs in Tehran for the next four years in 1400 H.Sh (2021 A.D.). The research methodology is carried out using qualitative and quantitative approaches based on the given data. First, the population of Tehran in 1400 H.Sh was predicted using nonlinear quadratic polynomial, Gompertz and logistic models. Then, a Logistic model is proposed to estimate the number of housing units in Tehran. The calculations of residential units related to the population obtained from the Gompertz model equivalent to 663141 is suggested as a criterion for local authority to future decision making and planning for urban development.

The present research is an applied research in terms of the purpose a descriptive research in terms of the nature and methodology and a descriptive-analytical research in terms of attitude and approach toward the research problem (Hafeznia, 2013, 58, 63 and 71). To provide the required information for the analytical stage, a documentary method, related to the use of internal and external books and papers, has been applied. First, the population of Tehran in 1400 H.Sh is estimated using three nonlinear models of quadratic polynomials, Gompertz and logistic. Then, among them, the options that were more consistent with the estimation of the new comprehensive plan of Tehran (1386 H.Sh), which is the most important plan of this city, were chosen. After that, by using the logistic model, which is an appropriate expression of saturable phenomena and a suitable method of estimating the number of residential units in a city and based on the past trend, the future of housing is predicted, and the number of required residential units is determined.

Any city for competitiveness must seek the search and development of a set of unique strategies and practices that will shape its status from other cities. No single action for all cities is feasible. In fact, the most important challenge is to propose a unique value proposition and to formulate a strategy that distinguishes that city from the rest. Among the measures taken around the world is attention to infrastructure. From the point of view of competitiveness, different types of investment in infrastructure are important for different types of cities and in different stages of development of a city. Large cities need targeted investments in housing issues to overcome the segments associated with the poorer neighborhoods. Without investment in desirable housing, there will be holes in competitive advantage. In this paper, the number of residential units in Tehran was projected for 2021. The city’s population was originally estimated for 2021. In addition to the models used to predict and estimate necessary, it is necessary to consider the area, land use map, future development lines and […] city. To this end, the city can continue to meet the needs of residents’ diversification and the city’s needs. We cannot accept any predictions about the population and, consequently, the number of residential units. Providing predictions can provide the most predictive, or more prudent, and different scenarios that can emerge, which will lead to flexibility in the presentation of plans and programs. Among the models that were used to predict the population, the result obtained from second-order polynomial and Gompartz models was found to be appropriate for the estimation of the new comprehensive design of Tehran (2007). But the prediction of the population of the logistic model was beyond the prediction of the new comprehensive plan of Tehran (2007) and thus was not considered appropriate. The number of residential units required according to the predicted population of the second order polynomial models, Gompartz and the population considered in the new comprehensive plan of Tehran (2007). After the finalization of the proposed population, using the logistic model, the number of residential units needed in Tehran was projected for 2021. Since these three estimates are somewhat close to each other, it is suggested that Gompertz model calculations, equivalent to 663,141 residential units, are proposed, and according to that, local authorities are planning to supply land to achieve economic competitiveness (urban). As it is shown in the conceptual model of the paper in Figure 1, after determining the need for housing, it is necessary to ask whether the adequacy of the supply and allocation of land, as well as the importance of maintaining it for the development of housing by local authorities, is clear. Also, is there any suitable planning for that? Despite the severe shortage of ready-made land for the city of Tehran, a large volume of land is a large area owned by natural and legal persons, and, in particular, state-owned enterprises of semipublic and public institutions, which have been abandoned in cities for years without use and in the form of barren. According to municipal management laws, municipalities can receive land, taxes and fees that are included in the annual budget of the Tehran Municipality. According to the figure obtained from this study, which states that 663,141 residential units are needed for Tehran in 2021, large landowners in Tehran need to supply their land to the market. According to the Population and Housing Census in Tehran in 2011, there are 245,769 inhabited vacancies in Tehran; hence there are two scenarios for the provision of residential units in the city of Tehran in 2021, assuming that these units in the housing market require 417,372 units Another residence will be for Tehran, otherwise 663141 residential units will be needed for Tehran in 2021. Other possibl

Tehran is the largest city and the capital of Iran, and it is also the capital of the province Tehran. In the southern foothills of the Alborz Mountains within a longitude of 51 degrees and 2 minutes East to 51 degrees and 36 minutes East, with an approximate length of 50 kilometers and latitude 35 degrees and 34 minutes North to 35 degrees and 50 minutes North with an approximate width of 30 kilometers. The area of this city is 730 km². This is one of the largest cities in West Asia, the 25th the most populous city, and the 27th greatest city to the world. The administrative structure of Iran has been concentrated in this city. The city has been divided into 22 zones, 134 areas (including Rey and Tajrish), and 370 districts (Wikipedia). The problem of housing in the city of Tehran has always been one of the important issues that less has been planned for it. The result is housing shortage, high housing prices and so on, due to the excessive expansion of the city, its population increase and so on.

The purpose of this paper is to analyze the dynamic competitive profile of Istanbul and to compare it to ten other European cities by using a multidimensional approach.

Starting from a review of existing competitiveness models, the paper develops a methodology that takes into account the complex shifting nature of the network of “mobilities” interacting within and around the destination.

The proposed approach proves to be effective in designing a dynamic competitive profile of every city and in identifying the factors that drive competitiveness within and between different competitive clusters of cities.

The new approach presents several original elements, since it embeds the evolution of the system of diverse intersecting tourism and non tourism “mobilities” that characterize an urban destination, and integrates different dimensions and disciplinary points of view.

The paper aims to relook at the notion of competitiveness in the challenging times of pandemic. The failure of global value chains caused many nations despite their state of economic development to struggle for necessary items. The goal of achieving profitability abated by having self-sufficiency, specifically in the manufacturing sector where unlike services, the production processes jolted. Under this backdrop, the paper attempts to project local industry clusters as a panacea for achieving resilient competitiveness.

To explore the credibility of clusters as an important tool to prepare nations towards a resilient future, a correlation between the state of cluster development in a country and its national competitiveness has been tested. Besides, any difference in the notion of state of cluster development between least developing countries, developing countries and developed countries has also been tested. The paper uses the data from World Economic Forum’s Global Competitiveness Report.

Strong support for the research hypothesis has been found. High positive correlation exists between the state of cluster development and national competitiveness. The state of cluster development is found to be significantly different among three categories of countries.

Clusters have been promoted in academic literature, policy circles and the business community for many advantages. This paper is a novice attempt to showcase these can serve as an instrument to prepare economies for self-sufficiency and a resilient future by performing an objective evaluation.