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This paper aims to investigate theoretically and empirically the interactions between smart economic development (SED) and competitiveness in Central and Eastern European (CEE) countries. The main argument to uphold here is that smartness approach has been traditionally more focused on smart urban planning and smart specialization.

An evaluation by index, correlation and significance analysis is used to present original empirical evidence from six CEE countries.

Smartness approach integration into economic development justifies the identification of SED determinants: basics (welfare, digitality, environmental, social responsibility) and enhancers (learning, networking, agility, innovations and knowledge-driven). The interaction between SED and countries’ competitiveness in CEE countries might be described by two approaches, namely, focus-based (several most important basics and enhancers) and balance-based (equal importance of basics and enhancers).

The limitations relate to the particular sample of CEE countries and gathering opportunities of statistical data.

The combination of SED-Index sub-indices and WEF GCI might aid a more accurate ex ante measurement. Despite common global challenges, each country should choose its own combinations for smartness determinants to achieve long-term competitiveness.

The findings are important for fostering smartness approach in economic development for long-term competitiveness.

This paper contributes to economic development literature by discovering basics and enhancers for SED. By linking well-known term of competitiveness and economic development with a concept of smartness, the new approaches, namely, focus-based and balance-based, to policy making in CEE countries emerged.

This paper aims to investigate the smart economic development (SED) patterns in Europe in relation to competitiveness. Motivational focus corresponds to global events: the fourth industrial revolution, transition to a low-carbon economy, economic shocks (such as the 2008 financial crisis, Brexit or the coronavirus pandemic), which requires rethinking development policies, targeting competitiveness increase and reducing imbalances in economic development.

The analysis includes self-organising neural networks cluster analysis and correlations, comparative analysis of SED indicators structure and cumulative index estimation with World Economic Forum (WEF) global competitiveness index. The panel data set of 19 years from 2000 to 2018 for 30 European countries.

Overall, cross-country examination suggests that European countries of higher competitiveness illustrate higher estimates in SED. The key determinants are juridical fairness, social responsibility, competence building, intelligence and welfare employment to develop smart patterns for reaching higher competitiveness.

The limitations relate to the particular sample of European countries and gathering statistical data and a methodology of the SED index calculation. In addition, the paper contains a macroeconomic environment focus on competitiveness estimation. Further research may be improved with micro and mezzo environment incorporation at a cross-country analysis level.

By linking well-known terms of competitiveness and economic development with a concept of smartness, new approaches to policymaking emerged. The methodology presented in this paper has implications for territorial cohesion policies, competitiveness and branching strategies. The combination of SED sub-indexes and WEF GCI might aid a more accurate ex ante measurement.

The findings are essential for fostering a smart approach in economic development for long-term competitiveness.

This paper provides original empirical evidence about the relationship between SED and competitiveness and adds new knowledge that smartness becomes a way for building countries’ competitiveness by identified two profiles of SED patterns by development stages, namely, integrated to economic development and institutional-based which is divided to focus and balanced.

The purpose of this study is to forecast the development performance of important economies in a smart city using mixed-frequency data.

This study introduces reverse unrestricted mixed-data sampling (RUMIDAS) to support vector regression (SVR) to develop a novel RUMIDAS-SVR model. The RUMIDAS-SVR model was estimated using a quadratic programming problem. The authors then use the novel RUMIDAS-SVR model to forecast the development performance of all high-tech listed companies, an important sector of the economy reflecting the potential and dynamism of urban economic development in Shanghai using the mixed-frequency consumer price index (CPI) producer price index (PPI), and consumer confidence index (CCI) as predictors.

The empirical results show that the established RUMIDAS-SVR is superior to the competing models with regard to mean absolute error (MAE) and root-mean-squared error (RMSE) and multi-source macroeconomic predictors contribute to the development performance forecast of important economies.

Smart city policy makers should create a favourable macroeconomic environment, such as controlling inflation or stabilising prices for companies within the city, and companies within the important city economic sectors should take initiative to shoulder their responsibility to support the construction of the smart city.

This study contributes to smart city monitoring by proposing and developing a new model, RUMIDAS-SVR, to help the construction of smart cities. It also empirically provides strategic insights for smart city stakeholders.

This chapter examines the transition from traditional cities to smart cities, with a focus on integrating digital technologies, data, and services into the urban environment. The concept of a smart city aims to create urban spaces that are more efficient, sustainable, and livable by fostering collaboration among stakeholders such as government, businesses, and citizens. This chapter highlights that this transformation encompasses not only technological advancements but also significant social, cultural, and economic implications. It emphasizes the need to rethink urban governance, citizen engagement, and public service delivery. By leveraging data for decision-making, smart city technologies enable cities to optimize urban services and streamline internal operations. Strategically, smart city development aims to attract businesses, investors, and visitors through improved services, sustainability, and accessibility. This chapter also explores how smart cities can enhance their competitiveness by promoting innovation, entrepreneurship, and a dynamic environment for residents and tourists. Moreover, it discusses how digital technologies enable smart cities to offer personalized and interactive experiences to visitors. Overall, this chapter provides a comprehensive perspective on the potential benefits and opportunities arising from smart city transformations, encompassing efficiency, sustainability, economic growth, and enhanced visitor experiences. It serves as a valuable resource for interpreting and understanding various aspects of the book.

As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising solution to this challenge, leveraging technology and data to improve urban systems and services while reducing environmental impact. This chapter provides an overview of the concept of sustainable smart cities and its implications for urban development. It explores the key features of sustainable smart cities, including their focus on technology, data and citizen engagement and the challenges they are facing in terms of infrastructure, data management, social equity, environmental sustainability, governance and regulations. The chapter also highlights the implications of sustainable smart cities for urban planners, policymakers and other stakeholders, emphasising the need for collaborative approaches that engage citizens and stakeholders in the design and implementation of smart city initiatives.

This study aims to investigate the influence of the built environment of smart cities on citizens’ quality of life in a developing country like India, focusing on the role of citizens’ participation as a moderator.

This study used partial least square-based structural equation modelling to test the hypotheses using data from 542 sample respondents residing in five smart cities of India.

The findings of this study confirmed that the smart city-built environment dimensions of smart governance, smart economy, smart mobility, smart environment and smart living positively relate to citizen quality of life, except for the smart people dimension. This study also confirmed that citizen participation moderates the relationship between all six dimensions of the smart city-built environment and citizens’ quality of life.

This study investigates the relationship between the built environment of smart cities and residents’ quality of life and the moderating effect of citizen participation on this relationship.

The purpose of this paper is to understand the perceptions of visitors in terms of multiple aspects of smart cities to allow wise decisions to be made about smart tourist destinations by municipal governments and tourism authorities.

This study takes a sample of inbound visitors (n=205) from Hong Kong as an empirical questionnaire-based survey on visitors’ perceptions of these smart city attributes, which are collected from literature, and framed in Cohen’s Smart City Wheel.

This paper identifies the distinctive factors for branding Hong Kong as a smart city. The results from the factor analysis identify four factors for determining what a smart city is from the perspective of visitors, namely, the quality of a smart society: energy consumption in an urban environment, smart city governance and smart city livelihood. The first two factors further become the determinants of a successful smart city brand considered by visitors, which contribute to their locational decisions and thus the strategies and policies of smart destination branding.

The results obtained can serve as insights for tourism policy makers and destination marketers when considering significant information and communication technology, or other smart and sustainable attributes for city branding (e.g. Buhalis and Amaranggana, 2014; Marine-Roig and Anton Clavé, 2015), as well as common investment and resource allocation for shared benefits in similar metropolises.

The smartness factors represent important dimensions of urban smartness as prioritized areas for further development, innovation and marketing of tourism industries and enterprises in Hong Kong, as a mature urban destination incorporating the branding of a proposed smart district as a strategy of urban development.

Smart urban development and tourism development have increasingly become inseparable, especially when visitors utilize cities as tourist destinations but share other urban resources and spaces with local citizens. Unlike the development of smart tourist attractions, smart tourist destinations should have a wider scope of smartness. A smart tourist destination may carry similar and overlapping characteristics of smart cities, which may be interpreted by visitors and may eventually affect their perceived image of a city.

The major goal when transforming a city to smart city is to achieve sustainability. Sustainable development (SD) has been talked over the years with several industries considering the principles attached. Also, for a functional smart city planning, considerations must be anchored on sustainability that can be achieved through digitalisation and advancement of technological tools. The contradictory discourse of sustainability in SD, contemporary challenges of the concept of SD, drivers of SD, innovation and SD, thinking about innovation and technology, how companies manage innovation, barriers to smart cities development and others highlight what to be discussed in this chapter.

The purpose of this paper is to examine the role of creativity and innovation as important attributes of smartness in cities/destination branding.

A conceptual support to the notion of smart destination branding is provided by discussing the relationship between creativity, innovation and technology as determinants for the smartness concept applied to destination branding and marketing. This paper adopts a qualitative and logical-deductive approach. The cases of Milan (Italy) and Tomsk (Russia) are presented and compared as smart cities approach to branding within and outside Europe. The authors emphasise the importance of smart destination branding strategies based on people participation, creativity and innovation as drivers of smart urban development.

The endogenous ability of cities/destinations to embrace creativity across stakeholders is essential to smart branding strategies relying on advanced information and communication technologies. The entwined connection between smart cities/destinations creative initiatives and innovation underpins innovative branding strategies.

The paper is conceptual and the findings cannot be generalised to other destinations, even if a couple of examples are briefly discussed. The authors intend to provide a basis for future research concerning smart destination branding.

The technological, human and institutional dimensions of smart cities and smart tourism destinations have been increasingly addressed by scholars and practitioners. Despite the reference and attention to human factors is not new, there is still a lack of extensive focus on creativity as crucial driver of innovation in smart destination branding. This paper aims to fill such gap by focussing on the implications of urban smartness driven by creativity and innovation in destination branding and marketing.

This study aims to comprehend the smart city–built environment’s (SCBE) effect on citizens’ quality of life in the smart cities of a developing country such as India. This study also sought to investigate the moderating effect of technological anxiety on the association, as mentioned earlier.

This study’s hypotheses were tested using data from 494 sample respondents who lived in the top five smart cities of India using partial least square-based structural equation modeling.

This study validated five dimensions of an SCBE, including smart governance, smart economy, smart people, smart transportation, smart environment and smart living, and demonstrated a favorable connection between a SCBE quality of life. This study confirmed that technology anxiety strongly moderates the relationship between the built environment of smart cities and citizens’ quality of life.

This study is a pioneering effort that explores the relationship between SCBE and the quality of life of its residents and the moderating effect of technology anxiety on this relationship.