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Network infrastructure is one of the most significant technological developments in recent decades, as well as a powerful boost for economic growth in both urban and rural area. However, whether improving network infrastructure reduces urban-rural income inequality (URII) remains uncertain in the previous literature. Considering that URII is an important research issue in the field of social change, it is worthwhile to investigate the causal relationship between network infrastructure and URII. Based on the exogenous shock from a quasi-natural experiment of "Broadband China" demonstration cities, this paper utilizes a time-varying Difference-in-Differences (Time-varying DID) model to identify the causal impact of the improvement of network infrastructure on URII in China. The results show that: (1) After controlling the impact of other commonly acknowledged factors, network infrastructure remains a significant factor in URII reduction. (2) The mechanism analysis confirms that the mediating effect of digital financial inclusion plays a vital role in the impact of network infrastructure on URII. (3) Further regional heterogeneity analysis reveals that the impact of network infrastructure on reducing URII also relies on region's characteristics, such as geographical location, traditional infrastructure level, and administrative level. This paper has figured out the causal relationship between network infrastructure and URII, thus inspiring policy-makers who aim to reduce inequality between urban and rural areas to commit to improving network infrastructure with an emphasis on digital financial inclusion mechanism and comprehensive consideration of regional heterogeneity. • Network infrastructure construction can significantly reduce urban-rural income inequality. • Time-varying Difference in difference method (Time-varying DID) was adopted to investigate the "Broadband China" Policy. • The mediating mechanisms and heterogeneity of network infrastructure development on urban income inequality are discussed. • The value of the "Broadband China" Policy for urban-rural development is shown. • Our findings offer advice for developing countries and local governments. [ABSTRACT FROM AUTHOR]

This paper seeks to answer the puzzling question whether Industry 4.0 inevitably triggers a sociogenesis that results in new attitudes toward the nature of the socio-economic innovation ecosystem. It asks whether Industry 4.0, as a shifter of techno-economic paradigm, may carry higher exaptation potential, and if so, which technology could catalyse this effect. Prevailing literature suggests that graphene technology can easily become a pathfinder in this respect. The paper does not only consider why and how a graphene-based unfolding of Industry 4.0 can fulfil this function (i.e., making exaptations easier in a broader scale), but it also takes into account the wider context for exaptations by asking whether the current configuration of the real economy, the financial universe and the public sector offers a supportive ground for innovation and exaptation seeker behaviours. • I call for the rejuvenation/extension of research on exaptation by encapsulating techno-economic paradigms via systems view. • I extend the literature on Industry 4.0 by examining its exaptationary power via the neglected graphene technology. • I call for systems view when dealing with graphene-aided Industry 4.0 due to asymmetry between finance and the real economy. • I decipher zombification as a side-effect of the asymmetry acting against the sustainable and exaptationary Industry 4.0. • I propose six policy-oriented insights to make a sociogenesis toward qualitative growth more possible. [ABSTRACT FROM AUTHOR]

Improving the level of innovation factor allocation is an important route to achieve high-quality economic development in China and has received much attention from scholars. As a policy system to change the old and new dynamics of innovation, the impact of innovation pilot cities on the allocation of innovation factors is of great importance. Using a sample of 254 prefecture-level cities in China from 2006 to 2019, this paper empirically analyses the impact of innovative pilot city policies on the allocation of innovation factors and their paths of action using a multi-temporal double-difference model. The study finds that the innovative pilot city policy significantly improved the level of innovation factor allocation, and this result held true after considering a series of robustness tests and endogeneity tests. Mechanistic tests show that the innovation pilot city policy has an impact on the allocation of innovation factors through the factor mobility effect and the innovation environment effect. Heterogeneity test shows that the influence of innovation pilot city policies on innovation factor allocation is greater in cities with higher administrative levels and better geographical locations. The economic consequences show that the innovation pilot city policy can significantly promote high-quality regional economic development. This study provides useful lessons for giving full play to the innovation-driven policy's innovation factor allocation effect, thereby enhancing China's high-quality economic development. • This paper studies the influence of innovative pilot cities on the allocation of innovation factors. • It provides a new method for measuring innovation factor allocation. • The basic results were confirmed by a series of robustness tests and endogeneity tests. [ABSTRACT FROM AUTHOR]

Improving the labor reallocation effect can promote the transformation of the driving force of economic growth and enable high-quality development. Therefore, this study constructs a growth source model from the perspective of human capital, considering labor price distortion and time-varying factor elasticity to measure the effect of labor reallocation under the crossover of provincial industries and analyze the impact of labor reallocation on employment share. The relevant findings are threefold. Aoki (2012)) The distortion of labor price is the largest in the primary industry, followed by the tertiary and secondary industries. Bai and Liu (2018)) Measuring the labor reallocation effect from the perspective of human capital allocation reveals a 3.7 % overall loss of the effect under allocation distortion compared with that under effective allocation. Bakas et al. (2017)) In terms of industrial structure adjustment, compared with the labor share under effective allocation, that of the primary industry still requires a 0.25 reduction, and that of the secondary and tertiary industries should be reduced by 0.07 and 0.18, respectively. The research results provide valuable insights for Chinese policymakers to further improve the market economy system and adjust the industrial structure to optimize resource allocation and advance economic growth. • This paper relaxes the constant factor output elasticity hypothesis in the multi-sector general equilibrium model proposed by Aoki, and introduces the time-varying elastic production function model to re-measure the labor reallocation effect of industries in China's provinces. • Unlike the existing studies, which mostly measure the factor mismatch of provinces or industries, this paper measures the labor reallocation effect under the industrial intersection of China's provinces. • From the perspective of factor measurement, considering the heterogeneity of labor quality, the effect of labor reallocation is measured from the perspective of human capital allocation. [ABSTRACT FROM AUTHOR]

Innovation systems present spatial heterogeneity across regions within states or provinces, posing a need for regional and state efficiency analysis. Yet existing efficiency models focus only on national and sub-national levels, inhibiting the analysis of resource misallocation across regions within each state. This paper aggregated region-level efficiency into state-level efficiency measures. We constructed a new measure of state-level overall efficiency and decomposed it into technical and allocative efficiency. We implemented these aggregation and decomposition strategies using a new slack-based dynamic network data envelopment analysis model. Using data from 316 regions across Australia from 2012 to 2018, our empirical application showed that the misallocation of resources across regions within states was one significant factor explaining low state-level overall efficiency. Using Spatial Durbin Models, we found evidence for spatial agglomeration effects and the crowding out effects on regional technical efficiency (RTE) in relation to population and business density. Net business entry is one important driver of RTE. Regions having a smaller proportion of the manufacturing sector and a bigger proportion of the service sector are found to have lower RTE, reflecting the shift towards service industries in the Australian economy during the period 2012–2018. • We construct state-level efficiency measures and decomposes them into technical and allocative efficiency components. • We use a slack-based dynamic network model in aggregation and decomposition strategies. • We provide the first empirical application to analyse regional innovation efficiency across Australian regions. [ABSTRACT FROM AUTHOR]

This study investigates the spatial and temporal evolution of ecosystem service value (ESV) in the Yangtze River Delta (YRD) region using an improved equivalent factor method based on land use data for five periods from 2000 to 2020. The research also examines the mechanism and spatial spill-over effects of economic development and urbanisation on ESV using a spatial econometric model. The findings indicate that YRD region's ESV rose from 442,422 million to 1,304,068 million between 2000 and 2020 and considerable spatial spill-over impact is evident. Although local economic development contributes positively to the improvement of ESV, development in nearby cities has a reducing effect on local ESV, leading to an overall negative impact. Urbanisation's effect on ESV presents an inverted U-shaped curve. When the population urbanisation rate is less than 56.96 %, expansion is advantageous to ESV growth; however, when the rate is higher than this threshold, blind expansion of population urbanisation is not advantageous to growth. The study's findings provide useful insights for policy formulation and forging a course for sustainable regional eco-economic development. • This paper reveals the spatial and temporal evolution of ESV in the YRD since 21st century. • This paper examines the spatial spill-over effects of economic development and urbanisation on ESV. • Local economic development contributes positively to the improvement of ESV. • Development in nearby cities has a reducing effect on local ESV, leading to an overall negative impact. • Urbanisation's effect on the ESV exhibits an inverted U-shaped curve. [ABSTRACT FROM AUTHOR]

What middle-income countries can draw from the experience of the countries that have successfully crossed the middle-income trap has become a theoretical and practical issue where an in-depth study is demanded as these countries account for a large proportion of the world's economy. There are many research studies on crossing the middle-income trap and artificial intelligence, but few studies have combined the two. This paper investigates the impact of industrial robot applications on the middle-income trap crossing at both theoretical and empirical levels. In theory, the scale effect and pricing behavior of robots are introduced into the task model proposed by Acemoglu and Restrepo (2018a) in this paper, which proves that robots can affect economic growth directly, and the greater the robot application, the greater the total output. In terms of empirical analysis, this paper draws on the classification criteria of Felipe et al. (2014) and adopts the absolute value method to classify economies into five groups: trapped, crossed, high-income, middle-income, and low-income group. Based on the panel data of 24 trapped and 37 leapfrogged economies from 1993 to 2019, we have empirically examined the effect of industrial robot application on crossing the middle-income trap. The results indicate that industrial robot applications facilitate economies to cross the middle-income trap through technological innovation, industrial structure and FDI, of which industrial structure includes both output structure and employment structure. This paper provides empirical facts and policy implications for developing economies to cross the middle-income trap through industrial applications. • We explore the impact of industrial robot applications on the middle-income trap crossing. • We use crossed-country panel data from 1993 to 2019 to open up new empirical evidence of the effects on the middle-income trap crossing. • We investigate the influence mechanism of industrial robot applications on the middle-income trap crossing. • The technological innovation, industrial structure and FDI have been identified as mediator variables. • We adopt instrumental variables and find that the results remain robust. [ABSTRACT FROM AUTHOR]

The smart city emerges as an innovation-driven strategy to achieve green development. While a large body of existing literature has assessed the environmental performance of the smart city, rarely does literature investigate the effect of smart city on green technological innovation, an essential part of and path to green development. This paper analyzes the impact of the smart city on green technological innovation through the Multi-period DID approach, using a dataset of Chinese prefecture-level cities from 2003 to 2016. The baseline results show that smart city can promote green technological innovation. The heterogeneous tests show that the smart city's green technological innovation effects are heterogeneous by geographic location, urban population size, economic development level, and information facilities infrastructure. Moreover, the paper explores the role of green technological innovation as an essential mechanism of the other aspects of green development. The mediating effect analyses show that smart city can promote urban industry structure upgrading and green efficiency through green technological innovation. • Smart city can stimulate green technological innovation as a part of green development performance. • Smart city's green technological innovation effects are heterogeneous by cities' characteristics. • Smart city can achieve green efficiency improvement and industry structure upgrading via green technological innovation. [ABSTRACT FROM AUTHOR]

Information and Communication Technologies such as blockchain can significantly contribute to achieving the Sustainable Development Goals (SDGs) in the Global South (GS). Grounded in the innovation forecasting literature, this paper explores blockchain-based innovations and research in the context of economic and sustainable development to answer the following research questions: what is the status quo of blockchain innovations and research in the Global South?; and further, how can blockchain innovations contribute to economic and sustainable development? We follow a mixed-method approach based on web mining and topic modeling with unstructured empirical data on blockchain innovators from Crunchbase, their websites, and academic publications to address these research questions. Our results indicate that blockchain innovators already engage in various application areas beyond the financial sector, addressing critical development issues. However, the empirical data on blockchain research and innovations suggests a largely untapped potential in various promising application areas relevant for the SDGs, such as sustainable energy or integrity verification. The major contributions of this paper are an overview and status quo of entrepreneurial innovation activities and research on blockchain technology in the GS, an analysis of these areas in the context of the SDGs, and a lean methodological approach for innovation forecasting. • Blockchain innovators in the Global South focus on financial inclusion • Blockchain is not a panacea but rather an infrastructural resource. • Large untapped innovation potential for integrity verification in the Global South • Strong research focus on blockchain applications for sustainable energy • Lean methodology to advance innovation forecasting [ABSTRACT FROM AUTHOR]

Based on an analysis of companies developing artificial intelligence (AI) technologies, this study offers fresh evidence on the role of innovation as one of the drivers of employment growth. GMM-SYS estimates on a worldwide longitudinal dataset covering 4,184 firms that patented inventions involving AI technologies between 2000 and 2016 show a positive and significant impact of AI patent families on employment. The effect, presumably of product innovations, is small in magnitude and limited to service sectors and younger firms, which are at the forefront of the leaders of the AI revolution. We also detect some evidence of increasing returns, suggesting that innovative companies more focused on AI technologies are achieving larger impacts in terms of job creation. • This paper studies the possible job creation effect of AI innovation activity. • GMM-SYS estimates show that patenting in AI increases employment of AI innovators. • Job creation is limited to service sectors and younger firms. • Specialization in AI inventions increases employment returns of AI patents. • The findings show a labor-friendly nature of AI innovative activity. [ABSTRACT FROM AUTHOR]

The eighth United Nations Sustainable Development Goal (SDG) underscores the need to encourage inclusive and sustainable economic growth, while advancing full employment and ensuring decent work for all. This increased emphasis on decent work has garnered heightened attention from international organizations and businesses. Significantly, as laws pertaining to workers' rights and labor matters have evolved, the concept of decent work has continuously expanded. This study acknowledges that this dynamic nature of decent work poses challenges for businesses in devising appropriate policies. To gain better understanding of the shifting labor paradigm, this research employs a systematic review approach, specifically main path analysis (MPA), to trace the trajectory of decent work literature over the past two decades. Among the 737 articles retrieved on decent work, 23 critical papers are identified for in-depth analysis. The findings reveal that the research focus has evolved across three distinct stages: economic-oriented, identity-oriented, and culturally-oriented decent work. In response to this insight, this study proposes a comprehensive empowerment model to support organizations and decision-makers in promoting decent work and improving working conditions, ultimately contributing to inclusive growth. Furthermore, this study addresses the challenges associated with decent work, aiming to facilitate progress towards fair employment and sustainable workplaces. • This research employs a main path analysis to trace the trajectory of decent work literature over the past two decades. • The research focus has evolved across three stages: economic, identity, and culturally-oriented decent work. • This study proposes an empowerment model to promote decent work, ultimately contributing to inclusive growth. [ABSTRACT FROM AUTHOR]

It is widely accepted that the self-employed enjoy non-pecuniary benefits from their employment status. They have greater freedom and autonomy in running their businesses and can pursue their intrinsic ambitions relying on their experience and abilities. In this paper we focus on the group of solopreneurs – solo self-employed who have decided to remain as single employee businesses. What determines turnover growth and product/service innovation intentions among these firms? Within this interplay, previous experience from innovation and growth episodes, as well as entrepreneurial self-efficacy (ESE) plays crucial roles. We empirically analyse the relationship between, and the determinants of, innovation and growth intentions using data on a large sample of UK solopreneurs. Empirical results suggest that past innovation performance and growth shape future solopreneurial intentions through an adaptive learning process given the level of perceived ESE for each future objective. Nonetheless, empirical results suggest that for female and young solopreneurs, ESE does not contribute positively to shaping sales growth and innovation intentions. • We link the growth and innovation intentions of UK solopreneurs. • We find that previous innovation and growth experience affects intentions. • Entrepreneurial self-efficacy (ESE) affects growth and innovation intentions. • ESE does not affect innovation and growth intentions of female and young solopreneurs. [ABSTRACT FROM AUTHOR]

Treating carbon emission rights as tradable commodities is a major institutional innovation in the carbon market's response to climate change. The level of carbon emissions from production activities is inextricably linked to climate policy adjustments. Thus, this article applies wavelet-based quantile-on-quantile regression to study the impact of climate policy uncertainty (CPU) on the carbon trading price (CTP) in the European Union Emissions Trading System (EU ETS). Short-term results show a mixed effect of CPU on CTP. In the medium to long term, there is a positive correlation between the two at the high quantiles of CPU. The results are supported by the theoretical mechanisms of CPU on CTP. The CTP represents the economic cost of carbon emissions, which can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. In addition, this paper can also inspire carbon market participants to help them make sound and scientific investment decisions. • Apply wavelet-based quantile-on-quantile regression to study the effect of CPU on the CTP. • The CPU is at different quantiles and time frequencies, the link between CPU and CTP is dynamic • The results are supported by the theoretical mechanisms of CPU on CTP. • The CTP can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. • Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. [ABSTRACT FROM AUTHOR]

Green technology innovation capability is an important support for the realisation of Sustainable Development Goals, and it is of great significance to discuss the impact of green product imports on green technology innovation policy formulation in importing countries. Based on the panel data of 30 provincial-level regions in China from 2012 to 2020, this paper empirically examines the effect and mechanism of green product imports on green technology innovation. The empirical results show that (1) the import of green products significantly constrain China's green technology innovation. After a series of robustness tests and endogeneity tests, the conclusion is still valid, and the inhibitory effect is mainly manifested as the import technology dependence effect. (2) From the impact of green product imports on different types of green technology innovation, the inhibition effect of incremental-type green technology innovation with lower innovation is stronger than that of radical-type technology innovation with higher innovation. (3) Further test of the moderating effect shows that green R&D investment weakens the inhibitory effect of green product import in the regions with higher and lower economic development levels, while the moderating effect of intellectual property protection only exists in the regions with less economic development. (4) The heterogeneity analysis shows that the import of different types of green products has a significant difference in the impact of green technology innovation. The finding of this study provides useful suggestions for formulating reasonable policies for promoting and protecting green technology innovation. • The effect of green product imports on green technology innovation • A panel regression model was developed. • Data of 30 provincial-level regions in China from 2012 to 2020 • The import of green products constrains China's green technology innovation [ABSTRACT FROM AUTHOR]

Foreign aid is an essential tool in economic diplomacy tool, yet its significance in global environment governance often goes underestimated. Taking 118 countries that received Chinese foreign aid from 2000 to 2018 as the research objects, this study investigated the impact of foreign aid on the carbon emissions of recipient countries and the mechanism. Firstly, the present study found that Chinese foreign aid increased the overall carbon emission levels of recipient countries during the sample period, with each 1 % increase in Chinese foreign aid being followed by a 0.0148 % increase in the carbon emissions of recipient countries. Secondly, the improvement of the economic growth and technological innovation of recipient countries served a mediating role in the process of Chinese aid affecting the carbon emissions of recipient countries. Thirdly, the threshold test results indicate that Chinese foreign aid helps to reduce the carbon emission levels of recipient countries when their economic growth rates and technology innovation levels are low, noting that this emission reduction effect may weaken as the recipient countries' economic growth rates and technological innovation increase. The findings of this paper expand the literature on the functional theory and non-economic consequences of foreign aid. Moreover, they told significant theoretical and policy implications for promoting cleaner aid practices and fostering low-carbon, green growth in recipient countries. • Chinese foreign aid (CFA) increased the overall CO 2 emission of recipient countries. • The improvement of the economic growth and technological innovation of recipient countries served a mediating role. • CFA helps to reduce the CO 2 emission of recipient countries with low economic growth rates and limited technical innovation. [ABSTRACT FROM AUTHOR]

Enhancing the green innovation capability of enterprises holds pivotal significance in achieving the "dual carbon" target. The integration of digital economy and real economy provides new ideas for promoting green innovation in enterprises. Based on the Chinese A-share listed companies panel data from 2011 to 2022, this paper empirically tests the impact of the integration of the digital economy and real economy on enterprise green innovation. The results show that integrating the digital economy and the real economy significantly positively affects green innovation. Improving the integration level of the digital and real economies is conducive to promoting green innovation. Intrinsic mechanisms show significant mediating effects on financing constraints, enterprise digital transformation, and corporate social responsibility. The integration of the digital and real economies can promote enterprise green innovation by alleviating enterprise financing constraints, driving enterprise digital transformation, and promoting corporate social responsibility. Heterogeneity analysis shows that the impact of integrating the digital and real economies on enterprise green innovation affects state-owned enterprises more than private enterprises. The effect on small enterprises is significantly positive at the 1 % confidence level; however, the impact on the green innovation of large enterprises is not significant. • Integrating the digital economy and the real economy significantly positively affects green innovation. • Can promote enterprise green innovation by alleviating enterprise financing constraints, driving enterprise digital transformation, and promoting corporate social responsibility. • Integrating the digital and real economies on enterprise green innovation affects state-owned enterprises more than private enterprises. • The effect on small enterprises is significantly positive, however, the impact on the green innovation of large enterprises is not significant. [ABSTRACT FROM AUTHOR]

As a major energy consumption province in China, Jiangsu Province is a key area for carbon emission reduction in China. Grasping the future trends of carbon emission in Jiangsu Province will help to find effective ways to reduce carbon emission. This paper proposes the STIRPAT-IGWO-SVR model, including screening the carbon emission influencing factors based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, optimizing the parameters of the support vector regression (SVR) model using the gray wolf optimization (GWO) algorithm improved by the differential evolution (DE) algorithm, and sets five scenarios to predict and compare the carbon emissions of Jiangsu Province under different scenarios. In addition, the Tapio decoupling model is used to analyze the decoupling relationship of carbon emission and economic growth in each scenario. The results show that the STIRPAT-IGWO-SVR model proposed in this paper shows good performance compared with other models. For Jiangsu Province, improving the energy structure has the strongest inhibitory effect on carbon emission, stronger than reducing energy intensity, and far stronger than optimizing the industrial structure. Compared with a single plan, even if the measures are slightly weakened, the implementation of combined planning measures can more effectively control carbon emission. • Predict and compare carbon emission and its decoupling status under 5 scenarios. • Propose the STIRPAT-IGWO-SVR model. • Use the GWO algorithm improved by the DE algorithm to optimize the SVR model. • The STIRPAT-IGWO-SVR model shows good performance compared with other models. • The combined planning measures can more effectively control carbon emission. [ABSTRACT FROM AUTHOR]

In China, people have a great demand for milk in their daily life. However, the process of dairy farming could produce greenhouse gases, resulting in global warming. Therefore, this paper analyzes the green total factor productivity of dairy cow (GDC) of China's 27 provinces in different scales and regions from 2006 to 2018, in order to improve the production efficiency of dairy cows and reduce pollution emissions. Based on Slack Based Measure (SBM) model and three-level Meta-frontier Malmquist Luenberger (MML) index, this paper analyzes the GDC from aspect of scale structure efficiency, technical efficiency and management efficiency. The following conclusions are drawn: (1) From 2006 to 2018, China's GDC has been in a state of fluctuation, which showing an upward trend on the whole, with an average annual growth rate of 2.45 %. In particular，TE increased by 0.40 %, ME increased by 2.48 %, and SE decreased by 0.44 %. (2) In terms of scale, the GDC of middle-scale is the highest, followed by large-scale, and then the GDC of small-scale is the lowest. It is obvious that the SE of small-scale and middle-scale is low, and the TE of large-scale is low. (3) In terms of regional distribution, the GDC in the western region is the highest, followed by eastern region, and then the central region. It should note that SE is low in the eastern and central regions, and TE is low in the western region. This paper provides theoretical guidance for the development of low-carbon dairy farming in China. [ABSTRACT FROM AUTHOR]

• The paper examines how the agri-food system is currently responding to the grand challenges of sustainability. • It reviews the literature related to sustainability-oriented innovation to identify ways in which the agri-food system could better respond to grand challenges in the future. • It highlights the key contributions of the seven articles in the special issue. • It draws three potential avenues for future research. The agri-food system features prominently in discussions about sustainable development because of its broad economic, social, and environmental impacts. To examine how the agri-food system is responding – and can respond – to the grand challenges of sustainability, we position this Special Issue (SI) within the stream of sustainability-oriented innovation (SOI) literature, and in relation to the much-cited framework provided by Adams et al. (2016). This introductory article contains an overview of the selected papers, described by using the above-mentioned framework and by highlighting the contributions that these articles bring to fill current knowledge gaps in the field. Such knowledge gaps have been identified by investigating SOI links to sustainability and circular economy concepts and by studying how SOI relates to development in the agri-food system. The contributions to this SI explore different facets of the research agenda we have laid out and covers the range of SOI proposed by Adams et al. To help the field move forward, we finally identify a few areas as the most relevant for future research. [ABSTRACT FROM AUTHOR]

Adoption of information and communication technology (ICT) to create a digital ecosystem gives rise to substantial economic and social benefits. Therefore, many countries develop National digital strategies (NDSs) to establish objectives, policy priorities and outline necessary actions for implementation of digital transformation. However, given the digital divide between different economies, it is difficult to compare consistently the priorities of NDS across various countries. This paper is an effort to explicate various priorities on different country groups. Using a macro-analysis lens, this research project explored specific policies and regulations that are perceived useful in identifying strategies for strengthening ICT adoption for economic and digital growth. We surveyed members of Asia Productivity Organization (APO) from mid-2020 to 2021 and interviewed three member countries (Indonesia, Malaysia, and the Republic of Korea). Findings offer a guideline for countries to develop their NDS and discuss implications for policy makers in the Asia Pacific region. • This study discusses the transmission channels between ICT's impact on productivity and its subsequent impact on economic growth. • This study provides guidelines and examples for executives in technology to develop digital strategic plans. • This study collected data from APO countries, comprising a sample of 436 respondents and a total of 22 interviews • It help technology stakeholders to review their current strategic and convince others to put essential efforts to include ICT in strategic plannings. [ABSTRACT FROM AUTHOR]

The empirical literature validates a linear relationship between historical technology and current economic development. While the emphasis is not usually on the underlying mechanisms, in this paper we question this relationship in a less optimistic way and we contribute to the literature by testing instead the hypothesis of a U-shaped relationship between these two variables. We use cross-sectional data on a global sample of 107 countries from developed and developing countries. Historical technology is measured using the technology adoption index in 1500 CE. Economic development is proxied by real GDP per capita. Based on a variety of econometric methods, we find strong and robust evidence that the effects of technology in 1500 CE on current economic development persist in a non-linear U-shaped fashion. Specifically, below a given threshold, historical technology reduces current economic development, while above that threshold, it stimulates development. This persistence of historical technology effects is primarily driven by the level of technology in the communication sector and is mediated by various technologies in 2000 CE, formalization of the economy, and life expectancy. Our results suggest the importance of investing in technology and improving absorptive capacity of the economy to ensure long-term economic development. • The effects of historical technology in 1500 CE on current economic development persist in a non-linear U-shaped fashion • Below a threshold, historical technology reduces current economic development, while above that threshold, it stimulates it • The effects of historical technology are mediated by various technologies in the 2000s CE, formalizing the economy, life expectancy • The persistence of historical technology effects is primarily driven by the level of technology in the communication sector [ABSTRACT FROM AUTHOR]

The paper deals with an immensely important and topical issue related to the implementation of sustainable development policies at the regional level. It focuses on assessing the level of sustainability in building stable infrastructure, promoting sustainable industrialization, and fostering innovation between 2015 and 2021 at the regional level in Poland. The areas included in the assessment relate to Goal 9 of the UN Agenda 2030 adopted by member states. The basis for the assessment was a developed research methodology based on a selected set of 19 indicators characterizing the development of innovation, industrialization and infrastructure at the regional level. The research covered 16 regions (provinces) in Poland from 2015 to 2021. In addition to determining the dynamics of change of individual indicators, characterizing the rate of change of the sustainable economy in these 16 regions, their ranking was created, reflecting the status of implementation of Goal 9 of the Agenda. The ranking was made using the developed new approach to analyzing a multi-criteria problem based on the MCDM methodology. The CODAS and CoCoSo methods and the Laplace criterion were used to determine the final value of the index for assessing the level of sustainable development of regions. Meanwhile, the values of the indicator weights were determined based on the Shannon Entropy and CRITIC methods and the aforementioned criterion. The determined index values formed the basis for making a ranking of the studied regions and assessing their level of development. The result of this process was their division into four classes differing in the level of achievement of Goal 9 of the Agenda. With the use of non-parametric tests (Kendall's Rank and Spearman Rank), an evaluation was carried out of the relationship between the values of the determined index and selected economic and social parameters characterizing the studied regions between 2015 and 2021. The results show that Poland is highly differentiated both temporally and spatially at the regional level. Throughout the entire analyzed period, the high level of development in the assessed scope was reported for the Masovia, Lower Silesia and Pomerania provinces, and the low level – for the Holy Cross Province. The results also confirm the relationship between a high degree of innovation, industrialization and stable infrastructure and economic development and living standards. The results show regions that need a decision on their nature and the role they are to play in the national and European economy. • Regional Implementation of Sustainable Development Goal 9 in Poland was assessed; • A new integrated approach was used for the assessment; • In Poland occur the great diversity of the regions in terms of SDG9; • SDG9 index has a strong relationship with economic and social parameters. [ABSTRACT FROM AUTHOR]

As individual investors who act independently can generate only limited influence on corporate decisions, this paper considers clustered institutional investors connected through investor networks as salient external stakeholders and investigates whether shared preferences for environmental, social, and governance (ESG) among clustered institutional investors induce more low-carbon innovation of family firms. Using a dataset with 9249 observations over the period of 2007–2019 of Chinese family firms, we develop a novel measurement for the shared preferences for ESG activities among clustered institutional investors and find that such shared preferences are positively related to corporate low-carbon innovation. From a stakeholder perspective, we explore the moderating effects of green finance and family control. Our findings suggest that green finance strengthens the above relationship, but this positive moderating effect is significant only in the low-uncertainty economic context. We also find that as family control increases, the positive impact of the shared preferences for ESG among clustered institutional investors on low-carbon innovation becomes less pronounced, and such a negative moderating effect disappears if a family successor is present in the top management team. • Shared ESG preference of institutional investors (S_ESG) spur low-carbon innovation • Green finance positively moderates the effect of S_ESG on low-carbon innovation • Such moderating effect of green finance is pronounced in stable economic situation • Family control negatively moderates the effect of S_ESG on low-carbon innovation • Such moderating effect of family control weakens if young family member present in TMT [ABSTRACT FROM AUTHOR]

• This paper investigates the impact of ICT and education on environmental quality. • Second generation unit root and cointegration methods are employed to check the stationary properties and cointegration for the study variables. • Continuously Updated Fully Modified Ordinary Least Square (CUP-FM) is employed for selected Asian countries. • ICT and financial development increase environmental quality. • Education decreases environmental quality. Rising environmental concerns due to extensive energy consumption and carbon emission in the process of developing information communication and technology (ICT) cannot be overshadowed by its significant contribution in economic growth. This study is an attempt to explore long run influences of ICT and education on environmental quality. By incorporating the role of financial development, energy consumption and income into the function of carbon emissions, the results obtained by the continuously updated and fully modified (Cup-FM) test indicate that economic growth, education and energy consumption stimulates carbon emissions intensity in Asian countries (1990-2018). The second-generation unit root tests and Lagrange Multiplier (LM) bootstrap cointegration method investigate stationary properties and cointegration. Our findings suggest that investment in technology and financial markets require policymakers' attention as we have empirically established long-run inverse impacts of financial development and ICT on carbon emissions. Furthermore, the study suggests a focus on clean energy policy as the rising pollution levels due to fossil fuel hampers long-run productivity. This paper contributes to the existing literature by proposing that ICT-led economic policies may help solve environmental quality and economic growth issues. [Display omitted] [ABSTRACT FROM AUTHOR]

• The scale of shadow economy in China varies greatly from province to province. • The entropy weight method is applied for comprehensive urbanization measurement. • Symmetric and asymmetric estimation for both short-term and long-term analysis. • Urbanization level has an inversed U-shaped impact on the scale of shadow economy. Urbanization and shadow economy are both common social problems in developing countries, yet rare studies have explored their potential relationships. Based on the provincial panel data in China, this paper estimates both the short-run and long-run non-linear relationship between urbanization and shadow economy combining with GMM (Generalized method of moments) and threshold analysis specifications, for symmetric analysis and asymmetric analysis, respectively. This paper also estimates if shadow economy is consistent with the EKC (Environment Kuznets Curve) assumption, and including other explanatory variables such as energy consumption, FDI (Foreign Direct Investment), tertiary industry and environmental regulation. Results show that urbanization does have an inversed U-shaped effect on shadow economy, so does economic growth, for both symmetric and asymmetric analyses. Tertiary industry can redouble the scale of shadow economy, which is consistent with all four analysis aspects. Other explanatory variables show slight differences in either symmetric/ asymmetric or short-run/ long-run results. [ABSTRACT FROM AUTHOR]

• Circular Economy requires a holistic approach to Business Analytics. • Business Analytics enables a more efficient and effective digital-enabled CE. • Circular Economy sets greater demand for data collection, integration, and analysis. Digital technologies are growing in importance for accelerating firms' circular economy transition. However, so far, the focus has primarily been on the technical aspects of implementing these technologies with limited research on the organizational resources and capabilities required for successfully leveraging digital technologies for circular economy. To address this gap, this paper explores the business analytics resources firms should develop and how these should be orchestrated towards a firm-wide capability. The paper proposes a conceptual model highlighting eight business analytics resources that, in combination, build a business analytics capability for the circular economy and how this relates to firms' circular economy implementation, resource orchestration capability, and competitive performance. The model is based on the results of a thematic analysis of 15 semi-structured expert interviews with key positions in industry. Our approach is informed by and further develops, the theory of the resource-based view and the resource orchestration view. Based on the results, we develop a deeper understanding of the importance of taking a holistic approach to business analytics when leveraging data and analytics towards a more efficient and effective digital-enabled circular economy, the smart circular economy. [ABSTRACT FROM AUTHOR]

• We combined IoT technology and 5 G technology to build an intelligent planning model under the background of the current economic level. • Our work designs a systematic planning method based on the demands of innovative green city planning. • The research results show that the model constructed in this paper has certain effects. The increasing economic level impacts the urban structure. Therefore, based on the continuous improvement of the level of science and technology, it is necessary to conduct green city innovation and development planning in combination with economic development. This article combines IoT technology and 5 G technology to build an intelligent planning model under the current economic level background. Moreover, based on network dual connectivity research, our work discusses and analyzes the application of dual connectivity technology and specific architecture selection in the early stage of 5 G deployment and 4 G LTE network collaborative networking. Simultaneously, this paper studies and analyzes related protocols and proposals that were proposed and frozen, researches and improves the hybrid networking technology in 5 G heterogeneous networks, and constructs the functional structure model. In addition, this paper designs a systematic planning method based on the demands of innovative green city planning. Finally, this paper analyzes the performance of this method through simulation experiments. The research results show that the model constructed in this paper has certain effects. [ABSTRACT FROM AUTHOR]

Increasing population and economic growth in Europe and the world are leading to growing demand for food, livestock feed, and energy, and consequently to growing negative impacts on the environment and climate change. Tensions and price fluctuations in international material supply chains have recently become an even greater challenge. As for biomass, its availability is limited due to land, water, human, and financial resources as well as the environmental boundaries. Therefore, efficiency of biomass use is becoming increasingly important; it is crucial to develop and apply integrated assessment frameworks for tracking progress in resource use efficiency that would allow comparing the efficiency of biomass and non-biomass use. This paper embarks on the analysis of biomass and non-biomass resource use in selected European countries over 2010–2019. The index decomposition analysis model is set up to decompose the changes in biomass consumption with respect to intensive and extensive drivers. Resource use efficiency is then assessed via the non-parametric frontier, taking into account the other inputs (labour and capital). The results suggest that biomass efficiency is higher than that of non-biomass materials. The efficiency scores suggest that further decoupling of domestic material consumption and economic growth is needed. • The biomass and non-biomass material consumption is assessed in the European economies. • The index decomposition analysis is used to factorize the changes in the biomass use. • The Data Envelopment Analysis is applied to identify performance gaps. • The intermediate consumption efficiency is much higher than that for the material use. • The improved use of biomass and non-biomass resources is crucial for the European economies. [ABSTRACT FROM AUTHOR]

Promoting rural entrepreneurship provides solutions for depopulation and economic development. This paper studies the phenomenon of rural entrepreneurial activity in Spain, where the depopulation of territories has become a serious problem. Using regional panel data for the period 2007–2018, the study examines whether factors such as the unemployment rate, GDP per capita, economic growth, bank credit, road infrastructure, R&D investment and the level of human capital are related to the propensity to undertake entrepreneurship in the rural environment. On the one hand, rural entrepreneurship is based on market opportunities, not conditioned by the level of regional unemployment. On the other hand, rural entrepreneurs find greater opportunities for entrepreneurship when they are in an environment characterised by investment in R&D and available credit. However, professionals with a higher level of education find the rural environment less attractive for entrepreneurship than do professionals with secondary education. This work enriches our knowledge of the factors that encourage rural entrepreneurship in Spain and invites public authorities to reflect on the economic policies of employment, education, innovation and the promotion of financing that revitalise the rural environment. • Exists a negative relationship between unemployment and rural entrepreneurship. • Bank financing is essential for the development of rural entrepreneurship. • Entrepreneurs take more opportunities to start its projects in the regions where the invests are high enough in innovation and development. [ABSTRACT FROM AUTHOR]

• Reveals the affects of human health on economic growth under the constraint of environment pollution. • There is a threshold for the effectiveness of the human health investment share on economic growth. • Reinterprets the driving force and source of China's economic. On the basis of considering the impact of environment pollution on human health, this paper expands and constructs a four-sector endogenous economic growth model including production, research and development, human capital cultivation and resource development, and reveals the affects of human health on economic growth under the constraint of environment pollution. Through static analysis it is found that the irrational allocation of physical capital and human capital will affect the scale of resource utilization and trigger an unsustainable economic growth model. Under the circumstance that the proportion of human capital invested in the production sector remains unchanged, a decline in physical capital investment will increase resource consumption. Under the condition of a certain proportion of physical capital investment, the decline in the share of human capital invested in the production sector will also cause the economy to consume a large amount of non-renewable resources and form an unsustainable development model. The parameter simulation results show that there is a threshold for the effectiveness of the human health investment share on economic growth; according to the development stage, the economy can adjust the investment share of education and health in a timely manner to maximize economic growth. Inspired by theoretical analysis, this paper reinterprets the driving force and source of China's economic from the perspective of human health utilizing common panel model and spatial panel model. In addition to the static analysis, this paper also makes a dynamic analysis of China's economic growth with the help of Cobb-Douglas production function. It is found that China's economic growth relies on physical capital investment and energy consumption, and insufficient reliance on human capital (including education and human health). [ABSTRACT FROM AUTHOR]

Originating in Germany, Industry 4.0 quickly became the new standard with industries adopting it worldwide. However, in the hurry to become digitalized for increasing production and efficiency, industries have failed at embracing the sustainability aspect of production. With the rise in concern for environmental safety and the re-introduction of circular economy, the authors have identified the integration of I4.0 and CE as a strong research point for overcoming the obstacles in achieving sustainable operations management (SOM). The research explains the criticality of the integration of I4.0 and CE and how it is the next step in becoming sustainable and resilient in today's turbulent environment. The study incorporates a four-step hybrid methodology with the identification and validation of enablers as the first phase using the PRISMA statement and PF-Delphi technique respectively. The second phase employs the PF-AHP technique for calculating the criteria weights which are subsequently used in the third phase by applying PF-CoCoSo to rank the enablers in priority order. Lastly, sensitivity analysis is performed to check the robustness of the results. The paper identified service and policy framework as the most critical criteria and product lifecycle management as the highest priority enabler for achieving SOM. The authors have also put forward seven recommendations for industries looking to implement I4.0 and CE for SOM by taking instances from previous case studies. • Exploring criteria and enablers for industry 4.0 (I4.0) and circular economy (CE) • List down the enablers using systematic review of literature and Delphi method • Evaluating relationship between enablers using Pythagorean Fuzzy AHP and Pythagorean Fuzzy Combined Compromise Solution • Identified service and policy framework and industrial ecosystem as critical enablers • Propose recommendations to be adopted and verified by different sectors to achieve resilient and sustainable operations. [ABSTRACT FROM AUTHOR]

This paper offers a new perspective on the energy efficiency literature by bringing evidence of political contextual factors as the predictors of energy efficiency. Specifically, we posit that the Democrat administration is more energy-efficient considering the reduction of environmental impact, in contrast, the Republican administration is more efficient considering only financial expenditures leading to the production of economic growth. In addition, we predict that political administration tenure is negatively correlated with green energy efficiency and that political distancing moderates the relationship between political party administration and energy efficiency. This study sheds light on these matters by performing an efficiency analysis of fifty North American states through a bootstrap DEA non-parametric model, followed by Tobit regressions to evaluate our hypotheses concerning the effect of the contextual factors on the calculated efficiency scores. • We investigate the impact of political factors on energy efficiency in the United States. • We perform a two-stage DEA-Tobit bootstrapped regression analysis. • The Democrats consistently demonstrated higher energy efficiency scores. • The political tenure as a feature had mild or mixed impact on energy efficiency. • We confirmed the positive time-passage effect on energy efficiency. [ABSTRACT FROM AUTHOR]

Religious interaction, supported by effective theories and practical approaches, can be influenced by the social environment, resulting in differing religious paths and characteristics with changes in society. The acceleration of population aging directly affects personal consumption and indirectly affects economic development. By analyzing big data, this paper examines and predicts the interaction between contemporary social change and religionization. Through statistical analyses of cultivated land and urbanization rate data, a strong negative correlation is revealed between GDP development level and cultivated land area. The correlation coefficient between these variables can reach −0.9258, indicating that they are closely related. There is also a high positive correlation between urbanization rate and the natural logarithm of fixed asset investment, with a correlation coefficient of 0.9417. Urbanization rate has the greatest impact on fixed asset investment. Religious interaction not only maintains and cultivates political culture and improves individuals' political quality and ability but also facilitates the development of political identity, which can effectively promote social change in China. • It is concluded that there is a strong negative correlation between GDP development level and cultivated land area, and the correlation coefficient between them can reach -0.9258 through the calculation of correlation degree, which indicates that they are closely related. • There is a high positive correlation between urbanization rate and natural logarithm of fixed assets investment, and the correlation coefficient between them is 0.9417 through data analysis. The change of political culture is the primary factor in social change. One of the non-negligible purposes of religious interaction is to spread the dominant political culture to members of society, so that members of society can accept and recognize the dominant political culture, thus forming a broad political identity. • In the process of religious interaction, the broad masses of people can feel the benefits brought by the society personally, so that they can strongly support and support the party's line, principles and policies, and make concerted efforts to contribute to social reform. [ABSTRACT FROM AUTHOR]

In the setting of Digital China, the smart city pilot strategy has become a fundamental part of the intelligent upgrading of the urban development model. Exploring the influence of smart city pilot policies on urban innovation performance is critical for achieving high-quality economic development and creating an innovation-driven country. This study views the experimental smart city policy in China as a quasi-natural experiment and assesses the improved influence of smart city development on urban innovation performance by constructing a multiple period difference-in-differences (DID) model, then confirms it using a variety of robustness test methodologies. The results show that urban innovation performance benefits from the construction of smart cities, and the promotion effect is sustainable. The level of economic development and information infrastructure, as well as the financial innovation expenditure, have a beneficial effect in encouraging smart city construction innovation performance, while the degree of opening-up hinders the improvement of smart city urban innovation performance. In addition, it is also found that there is heterogeneity in the promotion effect of smart city building on urban innovation performance. The research of this paper provides useful enlightenment for better exerting the promotion effect of smart city building on urban innovation performance. • Smart city construction positively promotes urban innovation performance. • There indeed exists economic region and city size heterogeneity of the positive effect. • The influencing factors of smart city innovation performance are discussed. • The multiple period difference-in-differences (DID) model was adopted. [ABSTRACT FROM AUTHOR]

High-quality energy development (HED) is conducive to achieving a win-win situation for economic development and carbon emission reduction in the context of the current "carbon neutrality" constraints in China, and the digital economy will likely accelerate the achievement of its goals. To verify the above hypothesis, based on China's provincial panel dataset from 2007 to 2017, this paper uses a dynamic panel model to estimate the nexus between the digital economy and HED and further explores their heterogeneous influence. The main results indicate that: (1) the digital economy positively affects HED in China; in other words, a 1 % increase in the digital economy index will boost HED by an average of 0.191 %; (2) the results of heterogeneity show that the influence of the digital economy on HED is stronger in regions with higher digital economy indexes and higher HED indexes; and (3) the digital economy positively affects HED through the innovation and application sub-indicator and the economic growth and jobs sub-indicator. We also provide policy implications for governments and scholars in related fields for reference. • The impact of the digital economy on high-quality energy development (HED) is explored. • We measure the digital economy indexes and HED indexes in China. • The digital economy has a positive effect on HED in China. • The digital economy positively affects HED through two dimensions: "innovation and application" and "economic growth and jobs." • The effect of the digital economy on HED is heterogeneous. [ABSTRACT FROM AUTHOR]

This paper presents empirical evidence on the link between social equality and technology waves in the U.S. 1860–2019. We measure the impact of various technology adoption by the U.S. households on their social condition (social equality). Using unbalanced panel data for the U.S., we measure the individual technology impact (wave) on social equality over the last 160 years. The findings indicate that technology substantially impacts social equality (proxied by the life inequality index). Technology's impact on social equality varies across technology waves so that we can conclude not all technology is equally suitable for people. Digital technology adoption is significantly improving social equality in the U.S. The results also confirm that technology waves alone in the U.S. can explain about 30 % of changes in social equality. Policymakers should look at technology as a strong driver of social equality and adjust social policy accordingly. Economic growth models in a digital revolution time must pay attention not only to the Solow (1957) residual but also on social equality as a source of growth. • Income inequality occupies a large part of the economics body of literature • Using univariate singular spectrum analysis (SSA) (Ghil et al., 2002) we build a new time-series database. • We use this database for U.S 1860-2019 to investigate the link between technology adoption and social equality in the U.S • Our results show that technology's impact on social equality varies across technology waves • Our research raises an important question about the role of technology in promoting social equality [ABSTRACT FROM AUTHOR]

China inaugurated its nationwide emissions trading scheme (ETS) in 2021 as a key policy instrument to fulfill its carbon-peak and carbon-neutrality commitments. The allocation scheme of Chinese ETS is based on grandfathering and benchmarking and has been argued as economically inefficient. This paper proposes an alternative emission quota allocation scheme, a prospective zero-sum gain data envelopment analysis (pZSG-DEA) approach, to efficiently allocate CO 2 emission quotas among market participants. We examined the potential economic gains and losses of implementing this scheme in China. Results showed that the proposed quota allocation can potentially lower the country's carbon intensity in 2020 by an additional 6.96 % compared to the 2005 level. The gains and losses vary substantially across 30 provinces. Beijing, Chongqing, and Zhejiang, were identified as potential quota receivers because increasing their emission quotas could lead to large economic gains; while Liaoning, Hebei, and Guizhou could be major quota givers as their emission reduction is associated with low economic losses. This study could be informative for the design of a high-efficiency emission quota allocation scheme for China's nationally unified emission trading market. • Emission quota allocation via prospective zero-sum gain data envelopment analysis • Welfare distribution effect studied using non-radial directional distance function • Long short-term memory is used to make predictions based on time-series data. • Correlation between carbon emission allocation and economic development [ABSTRACT FROM AUTHOR]

This paper provides new evidence on how outward and inward foreign direct investment (FDI) and economic freedom influence opportunity and necessity entrepreneurship in emerging markets. Studying 38 emerging economies, the empirical results show that both types of FDI exert opposite spillover effects on opportunity and necessity entrepreneurship and that greater economic freedom increases inward FDI and reduces outward FDI, thereby enhancing entrepreneurial activities. Additional analysis shows that the influence of FDI on entrepreneurship development depends on the dimensions of economic freedom. In particular, better economic freedom allows FDI to increase opportunity-driven entrepreneurship and decreases necessity-driven entrepreneurship. Policy and practical implications are also discussed. • The moderating effect of economic freedom on the FDI-entrepreneurship nexus is examined. • The impact of FDI on entrepreneurial activity is likely to be different across types of both. • The effect of economic freedom on entrepreneurial activity is contingent on the types of this later. • Economic freedom supports FDI for increasing opportunity entrepreneurship and reduces necessity entrepreneurship. [ABSTRACT FROM AUTHOR]

• We investigate the relation between digital technology and green economic growth. • A novel by-production model is applied to evaluate green productivity gains. • The results show a substantial green growth is observed in Chinese agriculture. • We find internet technology indeed promote sustainable development in agriculture. As the primary industry in an economy, sustainable agricultural growth has attracted much attention from researchers and policy-makers worldwide. Digitalization reform and information technology greatly impact agriculture, rural areas, and farmers, improving high-quality development and green growth in the agricultural sector. Based on a measure of digitalization and a green productivity indicator, this paper investigates the impact of internet development on the economic and environmental performance of Chinese agriculture. The empirical results suggest that substantial green growth is observed in Chinese provincial agriculture, which is largely motived by technological progress. Internet popularization and digital technology indeed promote sustainable development in agriculture. Furthermore, the corresponding policy implications are provided to create a new path for steady growth in Chinese agriculture. [ABSTRACT FROM AUTHOR]

• Economy-related regional innovation ability shows a "pro−rich" inequality. • Mitigation effect of economic synergy promotion on regional innovation inequality. • Cumulative effect exacerbates the inequality of regional innovation ability. To bridge the research gap regarding the inequality of innovation ability, this paper proposes a more reasonable proxy indicator of research and development capital, applying the concentration index to quantify the inequality of regional innovation ability based on the regional economic levels in China and to dynamically decompose changes of regional innovation ability inequality. The study reveals that China's innovation ability has gradually improved, accompanied by significant regional agglomeration effects and widening regional gaps. The findings indicate that inequality of regional innovation ability in China remains high, and the correlation between the regional innovation ability and economic development level has increased. Improvement in the degree of synergy between regional economic development is conducive to alleviating the inequality of regional innovation ability, and cumulative innovation ability effects, particularly the scale factor, exacerbate the inequality of regional innovation ability. This research has important practical significance for policymakers and researchers seeking approaches to investigate and promote effective the coordinated development of regional innovation and improve the overall quality and efficiency of innovation ability. [ABSTRACT FROM AUTHOR]

• The comprehensive TFP in China is calculated by integrating economic, environmental and societal performance. • A novel nonparametric approach incorporating the three dimensions is utilized. • Medical care provided the largest contribution for the increase of TFP. • China's TFP growth rates differ significantly across different regions. Total factor productivity (TFP) indicators or indices are usual measurements for evaluating economic performance in terms of output and input evolution. This approach has been extended in the environmental dimension in the literature. However, the social dimension is equally important for a comprehensive TFP, which is ignored in existing studies. Using provincial-level data from 2000 to 2017 in China, this paper applies a novel nonparametric approach incorporating three dimensions (economy, environment and society) to estimate the Luenberger productivity indicator in order to understand how to realize sustainable and high-quality development. Then, the overall productivity gain is decomposed into three different parts to evaluate economic, environmental, and social performance. The results show that the growth rate of TFP in China within the sample interval was 6.822%. Regarding its decomposition, medical care provided the largest contribution to the increase in TFP (3.840%), followed by emission reduction (1.981%), economic growth (0.975%), education (0.016%) and employment (0.010%). However, there is regional variety showing that eastern China had high-quality TFP growth (4.696%), while the TFP change was negative (-1.165%) in western China due to an inferior economy, environment, and educational development. [ABSTRACT FROM AUTHOR]

This paper analyzes the Covid-19 pandemic impact of the global process of automation on employment in a developing economy. This is particularly interesting because developing economies characteristics, such as having larger informal sectors and weaker social safety nets, shapes the impact of automation on labor markets. We show that occupations with a higher risk of automation exhibit the most significant employment contraction. More specifically, we find that one standard deviation higher in sectoral share of employment in occupations at risk of automation (OaRA) implied around 7% less employment on average between the last quarter of 2019 and the first quarter of 2021. The effect on informal employees is three times more in comparison to formal employees, and the estimation for self-employed workers is not statistically significant. We also find that employees in sector with relatively low compared to high wages, both vis-à-vis the US, exhibit a 20% smaller reaction on employment due to the pandemic restrictions. We do not find robust evidence showing that the employment contraction has been larger among female workers or in jobs with higher at-work physical proximity, but we do find a positive relationship related to the capacity of working remotely. [ABSTRACT FROM AUTHOR]

• With the reform of the marketization of factors, the distortion of capital prices has been alleviated, and the degree of distortion of capital prices has generally shown a downward trend. As the quality of labor improves, the degree of labor price distortion is generally on the rise. • Starting from the time-varying characteristics of China's factor shares, combining with the typical characteristics of China's economic unsteady growth, introducing a time-varying elasticity production function to obtain factor output elasticity and factor output. • Based on the time-varying elasticity production function, the Cobb-Douglas production function underestimates the 5.9% underestimation of the average capital factor price distortion measure, and exceeds the translog production function is underestimated by 1.5%; on the average labor price distortion measure, the Cobb-Douglas production function is overestimated by 5.5%, and the translog production function is underestimated by 5.4%. • The trend of capital and labor price distortions is a response to China's policy and structural changes, and the study of factor price distortion measurement has important practical significance for China's factor market allocation reform. • The output elasticity of the time-varying elasticity production function of capital and labor is not a fixed constant, and it can objectively and truly reflect the changes in the income share of capital and labor in different periods. Factor price distortions affect factor allocation efficiency, which in turn affects the total factor productivity. This paper proposes a new method, the time-varying elasticity production function model, to measure the price distortions of capital and labor factors. The actual price of factors is measured by the factor share method according to national accounting. The empirical research in China from 1978 to 2017 finds: First, from 1978 to 1991, the degree of capital price distortion was greater than 1, and after 1992, it was less than 1, showing a positive distortion. With the reform of the marketization of factors, the distortion of capital prices has been alleviated, and it has generally shown a downward trend. Second, the degree of labor price distortion from 1978 to 2003 was less than 1, and it was greater than 1 since 2004. As the quality of labor improves, the degree of labor price distortion is generally on the rise. Third, the time-varying elasticity production function model can truly describe the actual changes in the income shares of capital and labor in different periods. Based on the time-varying elasticity production function, the Cobb-Douglas production function underestimates the 5.9% of the average capital factor price distortion measure, translog production function underestimates 1.5%. As for labor price distortion, the Cobb-Douglas production function overestimates 5.5%, and translog production function underestimates 5.4%. This study provides a new production function for correctly measuring factor price distortions and helps understand China's factor market reforms and structural changes. [ABSTRACT FROM AUTHOR]

• R&D subsidies increase total R&D inputs despite reducing private R&D investments. • Total effects promote technological progress, capital deepening and economic growth. • Increasing investments in residential buildings suggest misallocation of public funds. This paper investigates the impact of research and development (R&D) subsidies on R&D inputs and their wider economic effects. The empirical analysis employs a structural vector autoregressive (VAR) model using a panel of Chinese provinces during the 2000–2010 time period. In support of a partial crowding-out view, public R&D subsidies allocated to large and medium-sized enterprises (LMEs) are found to increase total R&D inputs proxied by total R&D personnel, despite reducing privately-financed R&D inputs. Specifically, we find that an increase of R&D subsidies by one standard deviation decreases private R&D expenditures in LMEs by 6.5%, but increases total R&D personnel in LMEs by 2.6%. We also find evidence that the effects of R&D subsidies extend beyond their main effect on corporate R&D, promoting technological upgrading, capital deepening, and economic growth. We further find evidence suggesting some misallocation of research-oriented public funds. The findings help shed important insights into the ongoing debate regarding the role of the state in promoting innovation in a transitioning economy context. [ABSTRACT FROM AUTHOR]

• Insights into the guns and butter phenomena of Pakistan is provided. • Quantile Autoregressive Distributive Lag model is applied to capture all asymmetries at the same time. • Military expenditure shows negative impact on human development and economic growth. • Urbanization and food deficit shows positive effect on economic growth. • Policy implications for policymakers are provided. The so-called 'guns and butter' phenomenon reflects that Pakistan is experiencing a difficult choice to improve defense and welfare sector to achieve sustainable economic growth. However, results remain controversial. Therefore, this paper attempts to explore the long and short-term associations among military expenditure, human development, and economic growth as informed by both urbanization and food deficit from 1965 to 2016. This study applies a newly-developed econometric model of Quantile Autoregressive Distributive Lag that not only takes asymmetries into account but also captures all conditions simultaneously. Our findings indicate that military expenditure has a negative impact on human development and economic growth, while urbanization and food deficit have a positive effect on it. We also confirm this long and short-run equilibrium by applying the Wald test. Possible economic policy implications - such as improving the quality and quantity of education, a true implementation of the National Rural Support Program, and improving gender equity in the Pakistani economy - are also discussed. [ABSTRACT FROM AUTHOR]

The development of disaster-prone areas is always lack of sustainability. The change of these areas needs to develop its resilience to grow internal and continue development power. However, the interaction mechanism of resilience and sustainable development in these areas is still unclear, and there is a lack of effective resilience cultivation strategies. This paper develops a theoretical framework of resilience and builds the regional economic-social development path of post-disaster reconstruction using a case in Heishui, a deep poverty county in the western China. Specifically, we investigate its regional resilience from three stages including the recovery stage, poverty alleviation stage and revitalization stage. Then, we analyze a balance relation and endogenous dynamics between the long-striding social system and the backward development mode of the sustainable economic-social development. The results show that the effective internal development structure can improve the resilience of poor and disaster-prone areas. In addition, these areas should focus on the physical level and the cultural level to improve the social resilience and institutional resilience, which contribute to the reconstruction and sustainable development of the disaster-prone areas. [ABSTRACT FROM AUTHOR]

• Founders' team composition variety is not a neutral element in academic spin-offs. • A moderate degree of variety does not allow to grasp spontaneous coordination mechanisms of homogenous team. • High variety increases growth performance and contributes to mitigate coordination and integration problems challenging academic spin-offs. • The integration of venture capitalist fund is preferable to sustain the heterogenization process of the founding team. University spin-offs are a peculiar type of venture that encapsulate a core technology or key scientific knowledge stemming from academic research activities and that are founded by university personnel, professors, or researchers. The high level of scientific knowledge of the team is a critical factor for the new academic venture, but previous research shows that the low cognitive variety of the team members, and in particular, the absence of market-based knowledge, may hinder subsequent performance rates. The aim of the paper is to understand how the degree of composition variety of the founding team affects the growth performance of the university spin-offs, given the founders' roles in shaping the future development path of the new ventures and their origin within the scientific and academic domain. Based on a new hand-picked database of Italian university spin-offs, we evaluate the nonlinear relationship between founding teams with low, moderate, and high levels of composition variety and subsequent growth performance by studying also the role of external backers as moderating variables. Results show a higher performance with high or low levels of founding team variety and a lower performance with moderate levels of variety. In addition, venture capitalist funds play a positive moderating role. [ABSTRACT FROM AUTHOR]

• Our findings indicate that smart city construction has increased the propensity for pollution reduction in China. • We identify two main mechanisms by which smart city construction affects ecological environment. • This paper makes marginal contributions to existing studies related to the impacts of improved technology on environment. This study aims to examine the impact of smart city construction on the ecological environment quality (EEQ) of China. Due to the problems arising from urbanisation, local governments construct smart cities as inherent innovative advantages that can improve their level of science and technology, and efficiency in resource allocation, thereby reducing environmental pollution. Through this innovation-driven channel, shocks to the degree of city smartness can have a significant impact on the regional environment. In order to compute the sensitivity of urban pollution to the degree of city smartness in China both conceptually and empirically, we modify a theoretical model of classic land allocation decisions to demonstrate how local officials' responsibilities to protect the ecological environment and promote economic growth can lead to the long-run spatial expansion of smart cities, resulting in the improvement of EEQ. Using a difference-in-differences (DID) analysis, we find that from 2005 to 2017 period, smart city initiatives in China reduced industrial exhaust gas and industrial wastewater by approximately 20.7% and 12.2%, respectively, such that most of the reduction may be attributed to the technology effect and allocation effect of urban innovation. [ABSTRACT FROM AUTHOR]

• Various actors must explore knowledge about environmental innovation in agriculture. • Institutions and coordination in innovation ecosystem impact exploration strategies. • Exploration strategies can change actors' positions within innovation ecosystems. By studying a case of environmental innovation, variety mixture in the cereal supply chains, this paper shows that the adoption of this type of innovation is not limited to the integration of a new product or process. Environmental innovations can require a profound change in the knowledge base of economic actors. Furthermore, these innovations are based on an ecosystem involving a diversity of actors operating along the supply chain who need to explore new knowledge to understand, test and evaluate their potential. Such exploration needs are studied in detail on the basis of interdisciplinary research. The case studied here reflects innovation "in the making". Several development scenarios are possible, leading to a more or less pronounced redistribution of the roles of the actors in innovation. Beyond the actors' exploration needs, we show that current market regulations and standards can constitute obstacles to exploration. Thus, the development of such systemic innovations requires both an exploration of new knowledge by the actors of the sector and an evolution of market standards. [ABSTRACT FROM AUTHOR]

• An ETS linkage of brazil with a developed region (Europe) and two developing regions (Latin america and China) would increase opportunities for mitigation at lower cost. • Brazil exhibits a permit-importer profile in all linkage scenarios. • The magnitude of the ETS linkage effects varies according to the partner energy profile, macroeconomic development and mitigation commitments. • Matching with a trading partner suitable in the selected priorities (economic performance, environment outcomes and political acceptance) is recommended. • Brazil should consider including land use and forestry-related emissions in ETS policy and linkage agreement. The Paris Agreement has recently underlined the relevance of international cooperation via carbon pricing to tackle climate change. With Emissions Trading Schemes (ETS) emerging in developed and developing regions worldwide, linking ETS systems is likely to be necessary in the future. This raises the question as to the appropriateness of linking ETS systems from the perspective of each trading partner. This paper analyses the impact of a hypothetical ETS, covering the electricity and energy-intensive sectors of Brazil, using a global economy-wide model - the EPPA6. We simulate links for Brazil with a developed region (Europe) and two developing regions (Latin America and China). Linking Brazil with a heterogeneous partner such as Europe results in more substantial emissions reductions, a movement towards low carbon energy and losses in GDP and welfare, as both regions assume ambitious targets. Linking with China is less costly due to less stringent targets. A link with Latin America, a region of similar energy and economic profile to Brazil, produces moderate reductions. Accordingly, there are advantages and disadvantages associated with each proposed trading situation. An ETS with a less stringent cap, or one that encompasses additional sectors, might allow for mitigation opportunities at lower costs for Brazil. [ABSTRACT FROM AUTHOR]