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The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

This study aims to investigate the factors affecting urban economic development in emerging economic market countries and to provide a new research perspective on urban skyscraper construction.

An empirical analysis based on a difference-in-differences (DID) model is conducted using data of urban data in China that expand into developed markets from 2003 to 2018.

The results of the spatial heterogeneity test indicate that the construction of skyscrapers has a significant promotional effect on the eastern city's economy. In contrast, it has a significant inhibitory effect in the central and western regions. Further findings demonstrate that the construction of skyscrapers can influence urban economic development by promoting industrial agglomeration, especially when the transmission effect of the diversified accumulation of tertiary industry is more prominent. The expansion analysis shows that skyscrapers have increased the level of trade in the city, and the impact on trade has an optimal height.

This paper focuses on the economic and trade effects of skyscrapers, and the optimal height of skyscrapers needs to be discussed in more depth, which is also the next problem the researchers need to study.

The government should attach importance to and promote the construction of urban skyscrapers, and do a good job in overall planning and design. The city should formulate preferential policies in land, taxation, finance, system and other aspects to increase support for urban skyscraper construction and promote local economic development.

This study focuses on the impact of urban skyscraper construction on the economic and trade development of cities in developing countries, which not only complements the relevant research on the economic effects of urban skyscraper construction, but also helps to provide reference for the sustainable development of urbanization in many developing countries.

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

The authors seek to advance the understanding of small- and medium-sized enterprise (SME) internationalization at the regional level and examine the role of home market institutions in this process.

The authors analyze hypotheses with data from SMEs in five country markets and from the Global Entrepreneurship Monitor. A cluster analysis establishes the regional diversification patterns (based on regional diversification scope, speed and rhythm) and a multinomial regression tests the effect of home market institutions on their adoption.

The results offer a refined picture of SME regional diversification by revealing three patterns: intra-regionally focused firms, late inter-region diversifiers and early inter-region diversifiers. They also suggest that the adoption of these patterns is determined by SMEs' home market institutions.

The authors develop a nuanced understanding of SME internationalization by building upon and expanding the regionalization rationale in the internationalization patterns literature. Additionally, the authors address the acknowledged, yet rarely investigated, country-level determinants of internationalization patterns.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

The study explores how the intention to export affects financing and non-financing variables for small and medium-sized enterprises (SMEs) in a low-income country (LIC). The objectives of this study are (1) to discern between regional and global exporting and (2) to evaluate its policymaking implications.

Primary survey data were collected from 330 Rwandan SMEs and were analysed using ordered logistic models as an application of the expectation-maximisation iterating algorithm, which was tested for robustness using a sampling model variation.

The results show that alternative sources of finance are the predominant choice to finance the intention to export within and outside Africa. As the scope of export intentions broadened from regional to global, there was a shift in preferences from less formal to more formal lending technologies, moving from methods like factoring to lines of credit. Moreover, reliance on bank officers became more significant, with increasing marginal effects. Finally, the study determined that government financing schemes were not relevant for SMEs pursuing either regional or global exporting.

Whilst alternative sources of finance predominate the export intentions of Rwandan SMEs, establishing a robust banking relationship becomes crucial for global exporting. Despite this implication, the intention to export should prompt more transparent communication regarding government financial support programmes. There is an opportunity for increased usage of relationship lending to customise support for SMEs involved in exporting, benefiting both the private and public sectors.

This study accentuates how export distance alters SME financing priorities. The results also contribute to understanding how the value of relationship lending changes when less familiar markets (i.e. global exporting) are the objective. Moreover, the study offers a new perspective on how institutional voids affect entrepreneurial financing decisions in LICs.

This paper aims to explore how sub-national or regional cultural differences influence backers’ willingness to crowdfund projects. The paper also explores how migrant transnationalism influences the impact of backer’s sub-national culture and crowdfunding relationships.

This paper is based on the experimental design technique using analysis of covariance methods. The authors tested the study hypotheses on a sample of 790 respondents.

The study results suggest that individuals differ in their intent to crowdfund product campaigns depending on value congruence between their cultural values derived from the region to which they belong and the nature of the product category, such as environmentally friendly or happiness-enhancing products.

This paper explores the role of regional cultural differences in determining the intention to crowdfund different campaigns based on the nature of the product. Value congruence, as driven by regional cultural differences with crowdfunding campaigns, has not been explored before.

The effects of country-of-origin (COO) cues on product evaluations are well documented. However, research on the relative effects of COO compared to other geographical indicators, such as region-of-origin (ROO), on food purchases is still limited. This study investigates how geographical origin labels influence consumers' perceptions of product value and authenticity of foreign food, as well as subsequent purchase intention (PI) and willingness to pay premium prices (WTPPP). The moderating role of health consciousness on these relationships is also examined due to the coronavirus disease 2019 (COVID-19) pandemic.

This study uses a between-subjects experimental design conducted with 300 middle- and high-income Chinese consumers aged between 25 and 50 years. Hypotheses were tested using structural equation modelling.

Whilst under both COO and ROO cues, all five product values positively influenced consumers' WTPPP, only functional, economic and novelty values influenced PI. The ROO cue performed significantly better than the COO cue in eliciting functional, economic and novelty value perceptions, which triggered stronger PI and willingness to pay a premium price. These relationships were mediated by product authenticity (PA) and moderated by consumers' health consciousness (HC).

Because food labels provide salient product information that facilitates consumers' evaluation of products, marketers should assess which product value perceptions they wish to enhance and then choose the appropriate geographical indicators for their labelling strategies.

This study identifies the effects of COO and ROO cues on product values, authenticity, PI and WTPPP. It also provides valuable insights into the role of HC on consumers' purchase decisions, which also aids in understanding the impact of global crises on food purchases.