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Abstract In the field of technology management, methods have been developed to detect technologies that are important in industry by analyzing massive numbers of documents. Such methods have been applied to the field of the Internet of Things as well to investigate technological trends. The Internet of Things consists of several conventional concepts, such as radio frequency identification, near field communication, and sensor networks. However, no research compares these technologies by analyzing massive quantities of papers and patents. Thus, in this study, we explored the research areas of technologies related to the Internet of Things, for which there are opportunities for commercialization in the near future. We also discuss potential applications of these technologies in diverse systems. Highlights • Extracting commercialization opportunities of the Internet of Things • Measuring text similarity between papers and patents • Results were good agreement with public government document contains IoT policy. • Extracted important technological options even experts did not discuss. [ABSTRACT FROM AUTHOR]

Breakthrough research may signal shifts in science, technology, and innovation systems. Early identification of breakthrough research is important not only for scientists, but also for policy makers and R&D experts in developing R&D strategies and allocating R&D resources. Researchers mostly use scientific papers data to identify potential breakthrough research, but they rarely make use of Twitter data related to scientific research and machine learning methods. Analysis of Twitter data is of great significance for us to understand the public's perception of potential breakthrough research and to identify potential breakthrough research. Machine learning methods can assist us in predicting the trend of events by utilizing prior knowledge and experience. Therefore, this paper proposes a framework for identifying potential breakthrough research using machine learning methods with scientific papers and Twitter data. We select solar cells as a case study to verify the valid and flexible of this framework. In this case, we use machine learning method to discover potential breakthrough research from scientific papers, and we use Twitter data mining to analyze Twitter users' sense of and response to the discovered potential breakthrough research, which aims to achieve a more extensive and diverse assessment of the discovered potential breakthrough research. This paper contributes to identifying potential breakthrough research, as well as understanding the emergence and development of breakthrough research. It will be of interest to R&D experts in the field of solar cell technology. • We proposed a framework for identifying potential breakthrough research using machine learning method. • We found 8 potential breakthrough researches in the field of solar cell technology in 2015. • Twitter data mining could be used to assist in identifying potential breakthrough research. [ABSTRACT FROM AUTHOR]

Security token offerings (STOs), based on blockchain technology, are attracting increasing attention as an innovative alternative means of venture financing. Information about specific STOs is generally provided in white papers. This study analyses the content of white papers using a unique sample of 188 STOs from 2017 to 2021 to identify which topic is related to campaign success. We leverage latent Dirichlet allocation (LDA) topic modelling to identify the topics and themes in white papers. Nine topics are identified through LDA: company description, distributed ledger technology components, energy and green issues, financial and legal issues, artificial intelligence, and tech applications in different industries—specifically, healthcare, manufacturing and construction, education, and financial services. We find that energy and green issues represent one of the most prominent topics among all types of projects and that their disclosure is positively related to the probability of campaign success and the amount of funding raised. Another prominent topic that affects campaign outcomes is technology in the healthcare industry, reflecting wider investment trends in this sector. Our results may help entrepreneurs to improve their campaign disclosures and present new issues for policymakers regarding investments in digital tokens. • An integrated framework of STOs success is proposed by combining topic modelling with other campaigns' indicators. • Company's energy consumption and green impact is one of the most dealt topics among all types of projects. • The technological components in the healthcare field is a topic related to the campaign success • Energy consumption and green issues must be adequately disclosed to affect campaign success. [ABSTRACT FROM AUTHOR]

The number of citations is often used to estimate the impact of a study. Previous studies have investigated what factors of publications affect citations and how they affect citations. However, the findings of the studies were unable to reach a consensus because of the limited sample size, domain, and measurement. This study reviewed previous studies that addressed factors influencing citations and then identified 14 measurable factors. Approximately 33 million publications from the Scopus database were used to train and validate a CatBoost model. A SHAP framework was used to interpret the trained model by focusing on how salient factors affect the number of citations. The results showed that the year is a significant factor affecting the citation but not the priority factor. A publication source was presented as the most important factor contributing to the citation. Several implications and strategic approaches to maximizing the impact of a study were discussed. • This study examines 14 factors that can influence the citation of papers. • CatBoost model and SCOPUS dataset are used to examine the influences. • SHAP interprets the model and suggests how the factors contribute to the citation. • The results show that selecting the right journal/conference is the most important. [ABSTRACT FROM AUTHOR]

Abstract: Scientific breakthroughs are rare events, and usually recognized retrospectively. We developed methods for early detection of candidate breakthroughs, based on dynamics of publication citations and used a quantitative approach to identify typical citation patterns of known breakthrough papers and a larger group of highly cited papers. Based on these analyses, we proposed two forecasting models that were validated using statistical methods to derive confidence levels. These findings can be used to inform research portfolio management practices. [Copyright &y& Elsevier]

This paper considers preceding technical research on wood-biorefineries when assessing the potential socio-economic impacts caused by a practical implementation of the developed technologies and products. Four different scenarios were simulated by using a system dynamics-model called FOHOW covering the entire forest based sector in Austria. At first a base scenario (business as usual) was calculated and then three different biorefinery-scenarios were assessed. By boosting the gross production value the biorefinery-technologies are capable of securing the competitiveness of the European pulp and paper industry. Sawmills profit from biorefineries as they are able to increase their returns from selling sawmill residues, which is securing their entire competitiveness, at the same time sawnwood prices can be held stable or even a little lower. The use of wood for energy would not be negatively impacted by biorefineries in the scenarios, but the average cost of wood for energy can even decrease. Introducing biorefineries may have positive effects on employment, as there are new jobs established, current jobs in pulp, paper and sawmilling business are secured and new jobs in the downstream processing of the biorefinery products are created. [ABSTRACT FROM AUTHOR]

Scientific knowledge enhances the process of external technology search, which is key to generating technological innovations. We propose the interaction effects of scientific knowledge with two technology search dimensions: external technology search intensity (scale) and external technology search scope. We examine these interaction effects in the generation of technological outcomes by comparing between sectors with creative accumulation (hydrogen energy) and creative destruction (nanotech). Data on the U.S. patents and their citations were collected to measure external technology search activities and degree of scientific knowledge in generating technological outcomes. We find that scientific knowledge and high external technology search intensity jointly increase technological outcomes in the sector with creative accumulation and scientific knowledge and broad external technology search scope jointly increase technological outcomes in the sector with creative destruction. [ABSTRACT FROM AUTHOR]

Abstract: The global business environment of today requires industries to be increasingly agile in order to create added value. There is a particularly urgent need to innovate and redefine business models in the mature pulp and paper industry, which is continually announcing mill closures and reporting persistent profitability problems. This paper focuses on the emerging forest energy business, which appears to offer many novel opportunities for both the forest and the energy industry. We conducted a qualitative dissensus-based online Delphi study and carried out themed expert interviews in order to identify the main industry- and company-level factors that are most likely to influence the bioenergy sector, its value-creation potential and forest and energy companies'' future roles in it. The Delphi technique proved to be a valuable research tool with which we were able to obtain comprehensive information on a subject that lacks historical and financial data, and yet requires input from many quarters. The results suggest that the complementary resources held by forest and energy companies make collaboration in the bioenergy business favorable. Moreover, the procurement and logistics of forest raw material appear to be key success factors in terms of yielding the most synergetic gains. Uncertainty about policy interventions nevertheless causes concern given their relatively rapid effect on the prospects of the bioenergy business. [Copyright &y& Elsevier]

The development and diffusion of digital technologies are transforming industries, including the agrifood sector, which is experiencing significant changes driven by the "Digital Agriculture" era. This paper explores the intersection of digital transformation and sustainability in agribusiness, examining how digital technologies impact organizational economics, social and environmental issues. The new competitive environment created by digital transformation necessitates strategic revitalization, collaborative engagements, and the cultivation of new skills and competencies. Despite the potential of digitalization to foster efficiency and sustainability, its relationship with sustainability initiatives requires further investigation. We discuss the cognitive processes influencing digital technology adoption and their implications for sustainability, proposing a 2 × 2 matrix framework to categorize different levels of technology integration and sustainability outcomes. Contributions to this discussion are positioned within this matrix, providing comprehensive insights into their practical and theoretical implications. The paper concludes with a research agenda for future studies, emphasizing the need for interdisciplinary approaches to deepen the understanding of the nexus between digital transformation and sustainability in agribusiness. [ABSTRACT FROM AUTHOR]

Pedestrians and cyclists are important stake-holders in a sustainable transport system whereas elderly and visually handicapped are related to the global ageing population issue. This paper examines the views espoused by respondents of different age on mobility precepts (notions of road usage) of four subject groups of vulnerable road users - pedestrian, cyclist, elderly (pedestrian), visually handicapped (pedestrian). An ethnographic study using a free association survey entailing an open-ended free listing technique was conducted on 259 ambulant respondents categorised (by age bands) into the Teenagers (15–25 years old), Middle-Aged (26–49 years old) and Pre-Elderly (50–64 years old). The respondents' views on mobility precepts of the four vulnerable road user groups are compared across the three age bands. "Crossing issue" as related to "pedestrian" is mentioned most frequently by all three respondent groups. "Dangerous" and "fast" are often associated with "cyclist'. The items associated with "elderly" and "visually handicapped" are rather similar, as centred on "slow reaction", "weak" and "requires help". These findings provide additional perspectives which have implications on appropriate types of interventions/strategies towards improving road usage experiences among vulnerable road users. • This paper examines the views espoused by respondents of different age on mobility precepts. • Four types of vulnerable road users - pedestrian, cyclist, elderly, visually handicapped are studied. • An ethnographic study using a free association survey entailing an open-ended free listing technique is conducted. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is emerging as a promising healthcare technology. Especially in critical, data-driven, and complex environments such as acute care, the use of AI can significantly improve treatment processes and support clinical staff. To date, AI applications in healthcare are scarce. Research remains fragmented across individual applications. To address this gap, we conduct a systematic literature review. In this review, we map the status quo of AI research in acute care and use service-dominant logic (SDL) from service science as a framework to integrate our analysis. Using a multilayered lens, we (1) identify intended beneficiaries of AI, (2) identify relevant activities supported by AI, and (3) determine those steps of the patient journey that have been in the spotlight for AI research. Our findings suggest that researchers have focused on hospital staff members as intended beneficiaries during the first three steps of the patient journey: admission, diagnosis, and treatment. The patient's perspective, however, remains underexplored. Moreover, 96 % of the research papers we reviewed focus on AI development and proof-of-concept studies, while only 4 % employ and test AI applications in the field. We identify three priorities for future AI research in acute care and provide suitable research methods. • First approach to combine systematic literature review with key determinants of SDL • SDL as an appropriate means to assess existent AI research in acute care • Four analysis determinants (micro level, meso level, activities, patient journey) • 96 % of the research papers focus on AI development and proof-of-concept. • 4 % of the research papers employ field study testing. [ABSTRACT FROM AUTHOR]

Material deprivation and the risk of poverty, exacerbated by recent unexpected events such as the ongoing Ukraine-Russia conflict, are significant social issues that profoundly affect the lives of numerous individuals. In contrast, social robots represent problem-solving innovations that have the potential to contribute to the achievement of the 17 sustainable development goals established by the United Nations. This paper investigates the association between the adoption of social robots and the risk of poverty, while also establishing the connection between the diffusion of social robots and the proportion of individuals experiencing material deprivation. The study involves a sample of 28 European countries and utilizes statistical analysis of data collected from 2018 to 2021.By taking into account variables such as average income and the unemployment rate, our findings indicate a negative association between the utilization of social robots and both the risk of poverty and the proportion of individuals living in material deprivation. Therefore, our research offers theoretical and managerial implications, serving as a basis for policymakers and managers to make informed decisions aimed at improving the standard of living for the most marginalized individuals. • Social robots represent problem-solving innovations enhancing life quality. • Social robots may help in facing material deprivation and the risk of poverty. • Social robots contribute to improving the living conditions of marginalized people. • We highlight socio-economic aspects of human-social robot interactions. • The paper highlights the positive impact of "machine substitution" on society. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to conceptualize and redefine trust within the blockchain ecosystem by exploring the trust construct across academic disciplines and its applicability in the blockchain context. We develop a conceptual model and testable propositions that extend the work of McKnight et al. (2001, 2002, 2011) to the blockchain ecosystem based on an integrative literature review. We conceptualize trust as a multidimensional, multi-object construct combining three major objects of trust: algorithmic trust in the blockchain protocol (platform), trust towards peers and services providers, and trust in decentralized applications (product). The model reflects the process of building a trust layer for users and institutions on top of the trustless technology. The paper demystifies the trust building process, from initial trust to knowledge-based trust, and its dimensions within the blockchain ecosystem, and, consequently, helps practitioners to build strategies that increase users' trust. The contribution to the academic literature resides in the unification of multiple perspectives on trust within an integrative conceptual framework to point out the mechanisms of trust building process, as well as to identify future research directions. • Trust in blockchain is a multidimensional and multi-object construct. • Trust in blockchain is a combination of algorithmic trust and trust towards peers. • Building trust in blockchain follows a process from initial to knowledge-based trust. • Trusting beliefs in blockchain comprise trust in the platform, dApp and peers. • Blockchain requires building a trust layer above trustless technology. [ABSTRACT FROM AUTHOR]

Our current historical moment is marked by a widespread sense of (ongoing and anticipated) crises, prompting calls to change existing economic, political, social, and environmental systems. This discourse has directed increased scholarly and policy-orientated attention to the concepts of "transformation" and "resilience." However, beyond attention, these concepts have increasingly adopted a place in rationales for policy action and measurements of its success, highlighting the need for conceptual clarity. In light of this, this paper reviews the use of transformation and resilience in the literature. These concepts appear across a broad spectrum of research fields, ranging from the natural to the social sciences. However, definitions and contexts vary broadly, further underlining the need for clarity. In this paper, we delve specifically into two disciplines: science, technology, and innovation (STI) policy research and economic history. Although unified in their explicit concern with societal change, the disciplines' different understandings of such change, particularly temporal aspects, offer fertile ground for exploring the divergent understandings, uses, and definitions of transformation and resilience in the literature. Through this work, the paper makes two main contributions. First, it produces a nuanced review of how the literature employs the concepts of transformation and resilience. Second, it offers an analysis of how transformation and resilience can be understood in relation to each other from a historical perspective. By historically anchoring these concepts while acknowledging that every time is different, the paper also offers some policy guidance on a key challenge of our era: how to successfully govern resilience and transformation in times of change. • Reviews the understanding, use, and definitions of transformation and resilience. • Specifically focuses on STI policy research and economic history. • Analyses how the two concepts can be understood from a historical perspective. • Contributes to both the literature and to policy thinking. • Offers policy guidance on governing resilience & transformation in times of change. [ABSTRACT FROM AUTHOR]

This paper examines the role of technological innovation in banking and its potential effects on economic cycles. Specifically, it utilizes a case study of a German bank (Bank A) in the business-to-business (B2B) banking, including green finance, to demonstrate how leveraging advancements in data analytics and machine learning can enhance efficiency, risk management, and profitability. However, scaling these innovations poses risks if not managed carefully. The paper concludes with policy recommendations for utilizing technology responsibly while promoting sustainable economic growth. The methodology involves collecting and analyzing the bank's CRM and transactional data. Machine learning algorithms including neural networks, random forests, and support vector machines are applied to predict cross-selling opportunities. The models are evaluated. Key findings show that business area, transaction volumes, and product diversity are significant factors influencing cross-selling success. Random forest was confirmed the most effective algorithm, achieving 96.6 % accuracy. The data quality assessment revealed strengths in accuracy, completeness, and consistency. Areas needing improvement included enhancing interpretability and understanding of business terminologies. This research contributes to updated literature on data analytics adoption in B2B banking for green finance. It provides a practical framework to assess readiness and demonstrates the feasibility of predictive analytics. For practitioners, it delivers actionable insights into optimizing cross-selling and provides a prototype for leveraging data analytics in B2B banking. Limitations of the study and areas for further research are discussed. • We leverage German B2B bank case study using data analytics and ML for green finance cross-selling optimization. • Random forest, neural networks outperform other models in predicting customer purchase propensities from CRM data. • Product diversity, transaction history, business areas emerge as key drivers of green finance cross-selling success. • Continuous monitoring of granular bank data offers real-time signals on innovation diffusion and economic cycles. • We recommend policy actions balancing tech innovation with privacy, stability, and equitable access in green finance. [ABSTRACT FROM AUTHOR]

This paper analyzes how the increase in the proportion of automated machines to general capital inputs affects the wage gap of the labor force complementary to the two types of capital, the general equilibrium model and constant elasticity of substitution production function are introduced and the impact mechanism is explored using a task-based model. Data for listed Chinese manufacturing companies from 2012 to 2020 is used and a double fixed effects model is invoked for empirical testing. The findings show that (1) a rise in the proportion of automated machines to general capital inputs increases the wage gap of labor complementary to automated machine capital and general capital, and a rise in the proportion of demand for both types of labor complementary to automated machines and general capital is an influential mechanism; (2) the productivity-enhancing effect suppresses the widening of the wage gap between the two types of labor; and (3) the results of heterogeneity analysis show that an increase in automated machine inputs among non-state-owned manufacturing firms and technology-intensive firms widens the labor wage gap. This paper makes a contribution to both theoretical and empirical analysis and provides references for the alleviation of the labor wage gap. • Labor is divided into those complementary to automated machines and general capital. • Increased automated machine input raises the wage gap between labor complementary to automated machines and general capital. • Labor structure and productivity effects are impact mechanisms. • Emphasize human advantages like creativity and social cognitive abilities. [ABSTRACT FROM AUTHOR]

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 study explores the role of Artificial Intelligence (AI) orientation in facilitating the internationalization speed of enterprises from emerging economies. Based upon a knowledge management perspective, the paper proposes that AI orientation positively affects internationalization speed via broadening the scope of new knowledge, promoting knowledge creation, application, and dissemination within organizations, and hastening the redundancy of existing knowledge to increase adaptability to global dynamics. Moreover, while online local knowledge search facilitates, offline local knowledge search constrains the acceleration effect of AI orientation on internationalization. Using a dataset from China, the paper finds that AI orientation has a significant positive effect on accelerating the internationalization processes of emerging market firms, and home country embeddedness negatively while regional digital development positively moderates this relationship. The findings contribute to the literature by elucidating how AI orientation expedites the process of an emerging market firm's internationalization from a knowledge management perspective, thereby providing insights for the future scholarly investigation and practical applications in this field. • AI orientation expedites internationalization speed. • Offline local knowledge search negatively affects the acceleration effect of AI orientation on internationalization. • Online local knowledge search positively affects the acceleration effect of AI orientation on internationalization. • A knowledge management perspective of AI orientation and internationalization speed is developed. [ABSTRACT FROM AUTHOR]

AI-tools such as ChatGPT can assist researchers to improve the performance of the research process. This paper examines whether researchers could apply ChatGPT to develop and empirically validate new research scales. The study describes a process how to prompt ChatGPT to assist the scale development of a new construct, using the example of the construct of perceived value of ChatGPT-supported consumer behavior. The paper reports four main empirical studies (US: N = 148; Australia: N = 317; UK: N = 108; Germany: N = 51) that have been employed to validate the newly developed scale. The first study purifies the scale. The following studies confirm the adjusted factorial validity of the reduced scale. Although the empirical data imply a simplification of the initial multi-dimensional scale, the final three-dimensional operationalization is highly reliable and valid. The paper outlines the shortcomings and several critical notes to stimulate more research and discussion in this area. • This paper examines whether researchers could apply ChatGPT to develop and empirically validate new research scales. • The study describes a process how to prompt ChatGPT to assist the scale development of a new construct. • Four empirical studies establish the prognostic validity and the construct validity of the newly developed scale. • The paper outlines the shortcomings and several critical notes to stimulate more research and discussion in this area. [ABSTRACT FROM AUTHOR]

This study aims to construct a monthly carbon emission index based on energy combustion in order to investigate its predictive power for the real GDP growth rate in the United States. Our objective is to evaluate and quantify the predictive performance and the potential impact of carbon-related factors on the GDP growth rate. We define the carbon emission index as the change rate index of monthly carbon dioxide emissions after accounting for seasonal effects, encompassing five sectors of energy consumption (residential, commercial, industrial, transportation, and electric power). Our findings demonstrate the robust and exceptional predictive capability of the newly developed carbon emission indices for GDP growth rates, particularly in relation to the transportation and industrial sectors. Moreover, in addition to popular macroeconomic variables, the carbon emission index contains incremental predictive information. The results obtained under diverse business cycle conditions and during the COVID-19 Pandemic further underscore the significance of our study. The findings of this paper provide more concise and efficient predictors for GDP growth rate forecasts. • This paper examines the relationship between carbon dioxide and economic growth. • This paper constructs a new set of carbon emission indexes (CEI) • These indexes have robust and excellent predictive power for GDP growth rate. • In particular, the carbon emission indices of the transportation sector and the industrial sectors show the strongest predictive power. [ABSTRACT FROM AUTHOR]

This paper aims to study the effects (benefits) of digitalization on management control systems and explore the factors affecting the relationship between digitalization and management control systems in small and medium enterprises (SMEs). The study is based on a survey administered to a sample of 132 Italian companies, mainly comprising small and medium enterprises. The findings provide evidence of the significant benefits of digitalization related to company performance improvements and internal and external communication. Furthermore, results reveal that top management, human resources, and financial resources are the main drivers leading to digitalization. Finally, medium-sized companies are found to be more active in digital transformation. The paper addresses the critical point that training people in digitalization, especially in SMEs, is key to getting a more mature Management Control System (MCS) and reaching a higher level of performance. Secondly, widespread digitalization in many company processes is a critical success factor. The originality of the current research lies in the focus on investigating the relationship between digitalization and management control systems in Italian SMEs. Finally, the research sheds light on the drivers and barriers that can lead to or impair improvement in the maturity level of management control systems. • This research examines the benefits of digitalization on management control systems and the factors that affect them in small and medium firms. • A survey of 132 Italian small and medium enterprises was used for the study. The data show that digitalization improves company performance and internal and external communication. • The research sheds light on the drivers and barriers that can lead to or impair improvement in the maturity level of management control systems. • The current research investigates the relationship between digitization and management control systems in Italian SMEs, which is novel. [ABSTRACT FROM AUTHOR]

This paper utilizes the skill-biased technological change and routine-biased technological change hypotheses, along with the theory of firms' innovation behavior, to establish a comprehensive analytical framework. This framework aims to elucidate the mechanisms through which technological innovation, industrial evolution, and education affect the labor skill structure in China manufacturing. The empirical results that have been gathered can be succinctly described in the following manner: (1) Research and development innovation stimulates the demand for high-and low-skilled labor, and, the rising of total factor productivity reduces the demand for low-skilled labor, confirming the labor-friendly effect of product innovation and the labor-saving effect of process innovation. (2) The cyclical pattern of fluctuating demand for low-skilled labor can be attributed to the industrial concentration, driven by technological advancements. Nevertheless, the phenomenon of cyclicality has not been observed for high-skilled labor. (3) There exists a paradoxical relationship between higher education and industrial demand, wherein education and skill are mismatched. (4) There exists the SBTC in China manufacturing resulted from process innovation. However, the SBTC does not explain the cause or mechanism behind the relative productivity shift and the higher demand for educated workers. This paper examines several policy implications including R&D innovation, employment, and education. • SBTC/RBTC and firms' innovation behavior theories are incorprated in a unified framework. • R&D inputs promote the demands for high- and low-skilled labor, and rising TFP reduces the demand for low-skilled labor. • Industrial concentration leads to a cyclical pattern of the demand for low-skilled labor rather than for high-skilled labor. • There exists a paradoxical relationship between higher education and skill demand. [ABSTRACT FROM AUTHOR]

Announces the 18th International Symposium on Forecasting, which will be held on June 10 through 13, 1998 in Edinburgh, Scotland. Who the event will be sponsored by; Invitation for papers on any aspect of forecasting to be submitted by January 16, 1998; Contact information.

Announces the 42nd meeting of the International Society for the Systems Sciences, in Atlanta, Georgia, from July 19 to 24, 1998. Theme of the meeting; Features of the meeting; Deadline date for abstracts; Contact information.

This paper examines the impact of a firm's important social relationship, director network, on its open innovation. By matching the director network data of Chinese A-share listed companies from 2008 to 2018 with manually collected data on joint patent applications, we conduct an empirical study and explore the possible influence mechanisms. The results show that the director network has a significant positive impact on corporate open innovation. The conclusion still holds after endogeneity treatment, propensity score matching estimation, and other robustness tests. Heterogeneity analysis reveals that director networks promote more R&D cooperation among firms than firm-university and firm-research institution R&D cooperation; director networks have a more positive impact on the R&D cooperation activities of non-state-owned firms compared to state-owned firms; moreover, in terms of the type of director networks, independent director networks have a significantly higher positive impact on firms' open innovation than non-independent director networks. It is further found that director networks can facilitate firms' participation in R&D collaborative activities by alleviating firms' financing constraints and reducing transaction costs. This paper enriches the research related to social relations expanding firm boundaries. The findings provide some references for firms to further develop open innovation activities and the construction of innovation systems. • We investigate the aggregate causal effects of the director network on corporate open innovation. • We find that the director network has a significant positive impact on corporate open innovation. • The impact various from cooperative partners, firm ownership and the type of director networks. • Firms' financing constraints alleviation and transaction costs reduction are the two plausible mechanism. • Rich implications are provided to advance open innovation with potential social relationships like director network. [ABSTRACT FROM AUTHOR]

Green innovations sometimes have a debatable environmental impact, which could be related to how their adopters use them. This paper examines five factors encompassing a consumer trait of being innovative and various motivations that could help further understand the adoption of controversial green innovations. Mainly, this paper examines the use decision and users' behavioral intentions in two green innovations that have received mixed opinions – shared e-bikes and e-scooters, and how they are related to a consumer trait (eco-innovativeness) and consumer motivations (instrumental, environmental, hedonic, and symbolic). We surveyed shared e-bike and e-scooter users (n = 337) and non-users (n = 1001) in Sweden and applied structural equation modeling to test the relationship between the factors and adoption. Results show that eco-innovativeness and motivations affect use decisions and behavioral intentions differently. Specifically, environmental motivations negatively affect use decisions but are positively significant in future behavioral intentions. Hedonic motivations have the strongest effects, which could help explain the controversy surrounding shared e-bikes and e-scooters. Theoretically, we contribute to understanding how traits and motivations are significant in the diffusion of green innovations. The paper shows that despite being mainly promoted as good for the environment, other motivations could significantly drive the adoption of novel green products. Practically, this indicates that promotion and public policies surrounding green innovations should not be limited to communicating their functional and pro-environmental attributes. [ABSTRACT FROM AUTHOR]

Based on the panel data of 284 prefecture-level city in China from 2005 to 2019, this paper measures the urban capital allocation efficiency and takes smart city construction as a quasi-natural experiment. The multi-period difference-in-differences (DID) model has been built to verify the internal mechanism and practical effect of smart city construction driving the optimal allocation of capital. The results show that the construction of smart cities has significantly improved the efficiency of capital allocation, and the conclusion remains valid after a series of robustness tests; Mechanism analysis shows that strengthening environmental regulations and improving innovation capabilities, together with the construction of smart cities, have promoted the improvement of capital allocation efficiency; The heterogeneity analysis indicates that the effect of smart city construction on capital allocation efficiency is influenced by the administrative level and regional heterogeneity characteristics of the city. This paper provides empirical evidence for the policy effectiveness of smart city construction and provides policy enlightenment on how to optimize capital allocation. • The construction of smart cities significantly alleviates urban capital mismatch. • The transaction cost effects, environmental regulation effects, and innovation capability effects are important mechanisms. • The correction effect is influenced by the administrative level and regional characteristics. [ABSTRACT FROM AUTHOR]

Diversity is influential and integral in innovation and economic growth. Despite the extensive research on the relationship between diversity and innovation, little attention has been paid to dialect diversity. The paper fills the research gap by investigating the impact and mechanism of dialect diversity on urban innovation in China. Also, this paper confirms the potential role of language as a non-institutional factor in urban innovation. Based on data from 276 prefecture-level cities in China, we find that dialect diversity impedes urban innovation. Moreover, in mechanism, it is not the communication barriers, but rather the identity from dialectal diversity that reduces regional trust to constrain urban innovation. Finally, we find that the negative impact of dialect diversity on urban innovation is continuous and more pronounced in eastern and southern cities. The conclusions not only enrich the theoretical research on innovation but also provide insights on how to promote language diversity governance and urban innovation for China and other countries. • Dialect diversity profoundly affects innovation in non-immigrant countries. • Dialectal diversity has a significantly negative impact on the level of urban innovation in China. • The impact of dialectal diversity on urban innovation level is heterogeneous, with southern regions and eastern regions experiencing a greater degree of inhibition in China. • The regional culture and identity embodied in dialects form trust barriers, leading to lower regional trust, which in turn inhibits urban innovation. • The mechanism that dialectal diversity influences urban innovation level is the obstacle of trust, rather than oral communication barriers. [ABSTRACT FROM AUTHOR]

Although skepticism is involved in technical change and scientific revolutions, surprisingly, the literature lacks a systematic analysis of the different forms, causes, and roles of skepticism in the diffusion of innovation. This paper defines, identifies and models different types and causes of skepticism and their role in technology adoption. The paper identifies and studies: skepticism involving the characteristics of the technology and the producer; skepticism that induces to disbelieve market signal; and comparative skepticism i.e., skepticism produced by an unbalance relationship between the perceived complexity of the problem and the solution. Among the theoretical findings of the paper and regarding skepticism on market signals, we found that the non-differentiability and oscillation of diffusion rates occur if individuals use the information on diffusion rates as proxy of the probability of technology working and modify this probability according to their skepticism. • Although scepticism is involved in technical change, general analysis of the different forms, causes and role of scepticism in innovation diffusion do not exist. • We developed a dynamic model of decision-making and innovation diffusion that incorporates technology diffusion and trust/scepticism. • Scepticism modifies market signals. • The model contributes to understanding mechanisms behind technology adoption and diffusion: adoption delay, adoption without social interaction, and oscillation of diffusion rates. [ABSTRACT FROM AUTHOR]

Measuring the level of green development is far from being a well-assessed problem, due to both the broad meaning of green development and the presence of randomness in environmental changes. In this paper, we develop the sustainable development evaluation index system from different perspectives, including resource utilization, green development management, green development quality, environmental protection, growth quality and green lifestyle. This evaluation index system is further viewed as a cybernetic system. Following a rough set approach, we properly address the issue of uncertainty and develop a robust estimation methodology. Neighborhood rough set and rough set methods based on genetic algorithms (GAs) have been used to identify the key indicators within the system. First, the results illustrate how a cybernetic approach deals with green policy and economic growth. Second, such a cybernetic approach provides new insights into identifying the main attributes for a sustainable development. Finally, stategies of improving green development in different parts of China are provided, concluding this paper. • Measuring green development is challenging due to its broad definition and environmental randomness, making standardized assessments difficult. • The paper introduces a sustainable development evaluation index system, viewing green development from multiple perspectives. • The conclusion presents strategies to enhance green development across China, providing a practical framework for implementing sustainable green policies. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of the use of industrial robots on labor income shares at both the theoretical and empirical levels. On the theoretical side, the role of induced technological progress, the creation of new tasks, and the penetration of industrial robots on labor income shares are systematically explored by incorporating industrial robots into task models and endogenizing the task induced technological progress. Empirically, industrial robot penetration at the regional level in China is constructed from the industrial robots data released by the International Federation of Robotics (IFR), which is matched with Chinese A-share listed companies in 2011–2019, and the causal strategy of Bartik-style instrumental variables is used to analyze the impact of the penetration of industrial robots and task induced technological progress on the share of labor income. The study shows that the penetration of industrial robots significantly increases the share of labor income, but the task induced technological progress reduces the share of labor income, and that the impact of the penetration of industrial robots varies significantly external financing dependence, ownership, and regions. From the perspective of the impact mechanism, robot penetration increase the levels of inputs complementarity and hence reduce the elasticity of substitution between robots and labor. Meanwhile, robots can effectively increase the wage level of the labor force, thus increasing the labor income share. The findings of this paper provide a decision-making reference for how industrial robots can better serve human beings in the new era so that workers can share the fruits of economic development. • It presents a theoretical model integrating robots into profit-maximizing tasks to assess their impact on labor income share. • Robot penetration affects labor income share across external financing dependence, ownership, and regions. • Increased robot penetration raises the labor share through effects on the elasticity of substitution and wages. [ABSTRACT FROM AUTHOR]

The current research focus in the field of digital rural development revolves around achieving high-quality digital rural construction and addressing the digital divide in different regions. This is particularly significant in China, where the issue has grown increasingly prominent. To delineate the pathway for rural digitalization and bridge the digital divide, we have constructed a Technology-Organization-Environment (TOE) framework, drawing upon configuration theory. Utilizing data from China's Top 100 Digital Rural Counties and applying the methods of Necessary Condition Analysis (NCA) and Qualitative Comparative Analysis (QCA), we identified the configurational paths necessary to achieve high-quality digital rural construction and discerned the nature of the digital divide across various regions. The findings show that: 1) none of the single antecedent conditions is a necessary condition for achieving a high level of digital rural construction. 2) There are four configurational paths for high-quality digital rural construction: technology-organization combination, technology-organization optimization, technology-organization symbiosis, and environmental integration. 3) Further analyses show that the configurational path for high-quality rural digitalization in the southeast coastal areas is organization-led, multi-coordinated, and technology-environment driven. In contrast, for inland provinces, it is technology-led, technology-innovation, and technology-external pressure. Moreover, a comparative analysis of regional differences shows that the high-quality digital rural construction in the southeast coastal provinces presents a well-rounded development type, whereas for the inland provinces it demonstrates a development mode of technology-driven under government leadership. The findings provide valuable insights for rural digitalization research and shed light on bridging the digital divide. • Rather than holistically evaluating the multiple drivers of rural digitalization, past research has primarily focused on a narrow perspective to evaluate the "nete effect" of driver factor affects the rural digitalization outcome. Instead, this paper advocate for an asymmetric configurational perspective that tests the causal complexity of high and not-high of rural digitalization outcomes. • This paper verified that none of a single antecedental factor constituted a necessary condition for achieve high-level of digital rural construction. Which means more attention should be paid to the confluence effect of multiple factors in rural digitalization. • This paper identified the paths to achieving high-quality of digital rural construction. There are four configurational paths for realize the high-quality of digital rural construction: technology-organization combination, technology-organization optimization, technology-organization symbiosis, and environmental integration. • This paper identified the nature of digital divide between regions in China. We classified the sample into two subsets, counties in the southeast coastal provinces and inland provinces. Comparative the two regions, this paper found that the high-quality of digital rural construction in the southeast coastal provinces presented a well-rounded development type. whereas, for the inland provinces it demonstrated a development mode of technology-driven under government leadership. [ABSTRACT FROM AUTHOR]

The number of patients with diabetes continues to grow, and the expense of treating diabetes is enormous. Therefore, predicting medical expenses for diabetes has become a priority in many countries. This paper proposes a new hybrid FSRF model to predict medical expenses. Firstly, in response to the problem of multiple features in medical data, we use a random forest (RF) feature extraction algorithm for feature extraction. Secondly, for complex medical concepts, we develop an improved multi-granularity embedding model for encoding medical concepts. Next, we establish the FA-SSA by optimizing the sparrow search algorithm (SSA) using the firefly algorithm (FA). Then, we employ the FA-SSA algorithm to optimize the parameters of the RF model with multi-granularity medical concept embedding. Finally, we build an improved FSRF model and conduct a case study on a medical dataset in Pingjiang County. This paper performs ablation experiments and four sets of comparative experiments, and the experimental results show the superiority of the FSRF model. • The RF algorithm is introduced to address the problem of massive redundancy in medical features. • A multi-granularity medical concept embedding model is developed for medical concept coding. • An FA-SSA parameter optimization algorithm is proposed. • An improved FSRF model is proposed for medical cost prediction studies. • Validate the model using medical data from Pingjiang County. [ABSTRACT FROM AUTHOR]

This paper contributes to debates on positive tipping points in climate mitigation, which are relevant for accelerating low-carbon transitions. The first contribution is to draw attention to dynamics after the tipping point and criticise the determinism of existing approaches, which excessively focus on irreversible self-reinforcing processes. We conceptually extend Geels and Ayoub's socio-technical perspective on tipping points by adding potential negative feedback processes on political and socio-cultural dimensions that can decelerate further diffusion after the tipping point. The second contribution is to replicate Geels and Ayoub's framework with two new case studies and thus enhance its empirical validity. The case studies are solar-PV diffusion in Germany and the UK, which both first accelerated because of positive feedbacks and then slowed down because of negative feedbacks. We explain why solar-PV diffusion almost entirely halted in the UK but regained momentum in Germany after 2016. Our findings demonstrate the importance of analysing both positive and negative feedbacks in low-carbon transitions. Our findings also show that the strength of various feedback processes is shaped by broader economic and political contexts. • Paper extends socio-technical transition perspective on positive tipping points • It shows that post-tipping negative feedbacks may decelerate change • Extensions are validated with comparative case study of solar-PV in Germany and UK • Balance of positive and negative feedbacks explains varying post-tipping patterns [ABSTRACT FROM AUTHOR]

This paper aims to present a comprehensive review and analysis to demonstrate the main papers, journals, authors, and trends significantly contributing to the scientific output in predicting the traffic incident duration using statistical and ML-based methods. We analyze new methods as well as data resources and characteristics such as incident time phases, data types, incident types, duration time distribution, available data resources, significant influencing factors, and unobserved heterogeneity and randomness. Also, this paper used the VOSviewer® software to conduct a visualization study of knowledge mapping on the literature of predicting traffic incident duration from 2010 to 2022 based on various databases. The contributions of this paper are three-fold. First, this paper undertakes a comprehensive comparison of previous studies in this field. Second, this paper identifies the key conceptual characteristics of analysis and prediction. Third, this paper explores the expected future trends in predicting the traffic incident duration. Furthermore, a key finding from this paper is that the usage of crowdsourcing, social media, and textual data is rare. Considering that future prediction methods of traffic incident duration will likely be utilized in all subfields related to traffic congestion, focusing on a review that summarizes such studies is a timely topic. • A comprehensive review of traffic incident duration prediction • Key papers, journals, authors, methods, and trends from 2010 to 2022 analyzed • Machine learning and HBDM are the most commonly used methods. • Rarely usage of crowdsourcing, social media, and textual data is revealed. • Potential challenges and future research on this topic indicated [ABSTRACT FROM AUTHOR]

The rapid emergence of digital technologies has considerably changed the environment for firms' survival and development, reshaping the way they operate and gain competitiveness in the market. The influence of digitalization on firms has emerged as a critical research topic. Nevertheless, studies on the relationship between digitalization and firms' performance remain scarce. Based on a European sample of 149,645 SMEs operating in the low-tech industries, this paper examines the impact of the country's digital performance (measured by the Digital Economy and Society Index - DESI) on the financial performance of low-tech SMEs and the existence of sector-specific differences over the period 2016–2020. Results reveal that the state of digitalization of the economy and society might significantly affect SMEs' financial performance. Indeed, the higher a country's overall digital performance, the better the financial performance of the SMEs that operate there. Additionally, the paper shows that digitalization positively impacts the performance of SMEs in the agriculture, construction, and wood and leather industry. By contrast, digitalization has a negative impact on the performance of SMEs operating in the publishing and printing industry, as well as in the textile and clothing industry. This study provides several implications for government investment policies and SMEs. • Firms' performance may be influenced by a digitally enabled external context. • Digitization at the national level can enhance the financial performance of SMEs in low tech-industry. • Agriculture, construction, wood, and leather industries benefit from the country's digital level. [ABSTRACT FROM AUTHOR]

While digital interventions in urban public spaces have been widely discussed in recent years in terms of their playability and their engaging design features, however, research on different types of playable digital interventions in urban public spaces from the perspective of urban design is relatively limited. This paper examines current precedents of playable digital intervention to develop a typological classification of open-ended Playable Digital Interventions in Public Space (PDIPS). With a focus on the applicability of playable digital elements to urban design, this paper collects relevant PDIPS representative precedents through association words online searching, then classifies the precedents by common feature extraction, and finally performs secondary analysis on the types to derive corresponding subtypes according to related theories. This paper identifies 5 main types and 11 sub-types of PDIPS typology, which are thematically organized by space composition, spatial perception, interactive mechanism, technology application, and implementation direction. The discussion on the applicability of playable digital elements to urban design in this paper provides insights into how such interventions can enhance public spaces and improve the urban experience for people. It also explores the potential and possibility of embedding such interventions in future urban design, offering guidance to urban designers. • Identified 5 types and 11 subtypes of PDIPS using secondary analysis • 5 PDIPS types identified by different spatial interaction characteristics • 11 subtypes identified by segmentation rules of 5 themes • Provides a two-way understanding between PDIPS scenarios and constituent elements [ABSTRACT FROM AUTHOR]

As a primary means of communication, the role of mobile telecommunications networks is important for a developing country's economic and social development. However, especially rural areas in low-income countries still lack mobile coverage. In the academic literature, only segmented solution strategies for this mobile coverage problem in rural areas are proposed. These are either technological, regulatory, or organizational solutions, whereas solving the mobile coverage gap requires an integrated approach to develop arrangements for mobile network rollout in rural areas. This paper presents a comprehensive overview of the causes of the lack of mobile coverage, the available solutions, and how they can be combined. Based on this overview, the paper proposes a decision support scheme for selecting a suitable arrangement for solving the mobile coverage gap. In this decision support scheme, the technical, organizational, and regulatory solutions are combined to develop a set of arrangements that match the local key causes of the lack of mobile coverage and that fit with the local context. In the last phase of the decision support scheme, the relevant stakeholders are involved in selecting the most suitable arrangement. We demonstrate the decision support scheme by applying it to the case of an unserved rural village in Indonesia, Unipa on the island of Papua, to show how it can guide a developing country to initiate the process of developing a solution for mobile coverage problems in rural areas. • Mobile telecommunication services play a crucial role in developing countries. • Only partial solutions to solve this gap are addressed in the literature. • We developed an integral decision support scheme for policy makers to go beyond the usual solutions. • Stakeholders need to be involved to prioritize solution arrangements. • We demonstrate the scheme with a case study in Indonesia to show its potential. [ABSTRACT FROM AUTHOR]

The prime objective of this study is to analyze the spatio-temporal evolution of the relationship between digital economy and green innovation in China. Based on the panel data of 26 cities in the Yangtze River Delta (YRD) urban agglomeration from 2012 to 2019, this paper measures the digital economy and green innovation in each city of the YRD urban agglomeration using the entropy weight model and the projection tracking model, analyzes the characteristics of the spatio-temporal evolution, and explores the impact of the digital economy on green innovation and the spatial spillover effect. The results show that in the spatial dimension, there is a significant spatial correlation between digital economy and green innovation in each city, and the regional heterogeneity of digital economy is higher than that of the west in the east, and the regional heterogeneity of green innovation is high and high agglomeration in the east of the city cluster, and high and low agglomeration in the west of the city cluster; there is a trend of incremental increase of the level of digital economy and green innovation in the temporal dimension, and the regional imbalance of the development of green innovation among cities is decreasing. The regional imbalance in the development of green innovation between cities is narrowing, and it tends to be more towards the synergistic development of a unified big market; the spatial measurement model shows that the digital economy not only has a significant impact on the level of green innovation in its own region, but also has a positive spatial spillover effect on the neighboring regions. The research in this paper helps to clarify the connection between digital economy and green innovation among regions, and provides decision-making reference for building a modernized innovation system and efficiently promoting the construction of beautiful China in the new period. • Spatial and Temporal Evolution of Digital Economy and Green Innovation. • 26 cities in the Yangtze River Delta city cluster from 2012 to 2020. • Entropy power model and projection tracing models are used. • The influence of the digital economy on green innovation in Chinese cities is very significant. • Sustainability based implications are discussed and suggested. [ABSTRACT FROM AUTHOR]

This study adopts Porter's hypothesis as its theoretical framework and focuses on Chinese A-share listed companies. Using a multidimensional fixed effect model and mechanism analysis, it investigates the impact of carbon emission reduction on enterprises' green technological innovation. The findings reveal a notable inverted U-shaped relationship between carbon emission reduction and corporate green technology innovation, highlighting the presence of the green innovation paradox. Additionally, the study demonstrates that carbon emission reduction positively influences green technology innovation by promoting the fulfillment of corporate environmental, social, and governance (ESG) responsibilities. Furthermore, through panel threshold model analysis, it identifies a threshold value of 21.1448 for corporate ESG responsibility, beyond which the inhibitory effect on corporate green technological innovation shifts to facilitation. By establishing a novel theoretical analysis framework, this paper contributes to the understanding of corporate carbon emission reduction, ESG responsibility fulfillment, and green technology innovation. Moreover, it provides practical insights on implementing carbon emission reduction targets, advancing ESG system construction, and enhancing green technology innovation capacity for enterprises. • The findings reveal a notable inverted U-shaped relationship between carbon emission reduction and corporate green technology innovation, highlighting the presence of the green innovation paradox. • The study demonstrates that carbon emission reduction positively influences green technology innovation by promoting the fulfillment of corporate environmental, social, and governance (ESG) responsibilities. • The article identifies a threshold value of 21.1448 for corporate ESG responsibility, beyond which the inhibitory effect on corporate green technological innovation shifts to facilitation. • By establishing a novel theoretical analysis framework, this paper contributes to the understanding of corporate carbon emission reduction, ESG responsibility fulfillment, and green technology innovation. [ABSTRACT FROM AUTHOR]

The rapid development of China's high-speed railway (HSR) has deeply affected the reorganization and reallocation of production elements, which has exerted a profound impact on the regional economic pattern. Existing research lacks attention to how HSR can impulse the regional pollution pattern. The operation of HSR serves a high-speed channel for knowledge spillover, which is an important mechanism to reshape the regional pollution pattern. Based on the data of 250 peripheral cities in China from 2004 to 2018, this paper utilizes a difference-in-differences model (DID) to investigate the impact of HSR opening on regional pollution gap, and provides a mechanism explanation from the perspective of knowledge spillover. It is found that the opening of HSR significantly helps to reduce the industrial pollution gap between HSR cities and central cities. The result remains unchanged after using instrumental variable method (IV) and a series of robustness tests. Heterogeneity tests show that the effect of HSR opening on narrowing the regional pollution gap is greater in the eastern region, areas with low pollution intensity and areas within the half-hour economic circle, and HSR service widens the pollution gap in the western region, areas with high pollution intensity and areas outside the one-hour economic circle. Further mechanism examinations reveal that HSR opening contributes to narrowing the regional pollution gap through knowledge spillover effects, and the knowledge spillover effects driving knowledge improvement to shrink the regional pollution gap is verified. This paper provides a new idea for the balanced regional development of cities in the aspect of environmental protection as well as empirical evidence for promoting environmental equity in China. • The HSR opening significantly helps to reduce the industrial pollution gap between HSR cities and central cities. • The effect of HSR opening on narrowing the regional pollution gap is greatly related to city factor endowments. • Both the direct and indirect mechanisms of knowledge spillover contribute to narrowing the regional pollution intensity gap. • Knowledge spillover effects of HSR opening driving knowledge improvement to shrink the regional pollution gap is verified. [ABSTRACT FROM AUTHOR]

With the proposal of sustainable development goals, the world has placed increasing emphasis on energy transition and green, low-carbon initiatives, leading to the emergence of green technology. This article explores the spillover effects among green technology innovation (GTI), oil prices (OP), clean energy (CE), sustainable development (SD), and economic cycles (EC) with the time-varying parameter vector autoregression (TVP-VAR) connectedness method. The empirical results demonstrate that, in static analysis, the short-term connectedness is significantly stronger than that in the long term. SD serves as the main transmitter, while EC acts as the primary receiver. Furthermore, dynamic analysis suggests that spillover effects fluctuate with time and frequency. Finally, the net direction and net pairwise connectedness reveal that GTI is favorable for mitigating OP shocks and accelerating EC in the long term, while it is driven by CE and SD in the short term. The contribution of this paper lies in its incorporation of GTI, energy markets, economic cycles, and SD into a unified framework, and its detailed analysis of the channels of influence. Also, based on a time-frequency domain perspective, the paper dynamically examines the different performances of specific markets in the short or long term. Finally, the paper proposes some policy recommendations, including the strengthening of green technology innovation and the acceleration of energy transition. • The connectedness among GTI, OP, CE, SD and GLI are presented. • Spillover effects are more significant in the short term. • GTI accepts the spillover effects of ESG and CEI in the short term. • OP and CLI exert dynamic influence on GTI in the long term. [ABSTRACT FROM AUTHOR]

This paper examines the further question of whether water-related environmental innovations affect water stress in three main sectors such as agriculture, industry and services. The sample consists of 30 OECD countries for the period 2000–2019. This paper employs the method of moments quantile regression (MMQR) with fixed effects to analyze the effects of water-related innovative activities across different quantiles of water stress for all three sectors separately. The empirical results indicate that water-related innovations positively affect water stress in the agricultural sector in the lower and middle quantiles, while it has a negative effect in the middle and higher quantiles for the services sector and the higher quantiles for the industrial sector. These findings reveal nuanced effects of water-related innovations on water stress across sectors. Furthermore, the study suggests that while innovations in the industrial and services sectors can mitigate water stress beyond a certain threshold level, the agricultural sector appears to benefit comparatively less from such innovations. These findings underscore the importance of complementing water-related innovations with appropriate regulatory measures, to address informal practices such as losses and leakages in agricultural irrigation. Ultimately, this study provides valuable insights for policy makers to formulate targeted environmental policies and strategies, especially in the context of climate change adaptation, thereby enabling a more effective allocation of resources to mitigate water stress within each sector. • The relationship water-related environmental innovations affect water stress in three main sectors. • Water-related environmental innovations are closely related to water stress. • Environmental innovations has an important nonlinear role for water stress. • Environmental innovation has different impacts depending the level of water stress. [ABSTRACT FROM AUTHOR]

Most banking institutions are inadequately prepared for the ongoing integration of technology, including the digitalization of financial services, the advent of the Metaverse, and the emergence of Web 3.0. While other sectors are making strides in navigating virtual environments, financial institutions appear to be trailing. Concurrently, the nascent ecosystem of the Metaverse presents promising opportunities for businesses and industries, potentially revolutionizing economic models, governance frameworks, and ethical paradigms. This study aims to contribute to the emerging discourse on the provision of financial services within the Metaverse. The paper envisages virtual reality's future financial services landscape using a scenario-based technological foresight approach. This research is the first attempt to map the comprehensive landscape of financial services in the Metaverse, both in the present context and the foreseeable future. The paper delineates the economy of the Metaverse, its key sectors, and its enablers. It overviews the initial experiences with virtual financial services and proposes potential prospects for financial institutions operating within the Metaverse. This study, therefore, serves as a foundational reference for understanding the evolving dynamics of financial services in the virtual realm. • The study analyzes of the Metaverse economic and financial landscapes. • The study defines key features of meta-economy. • The study explores financial institutions' pioneering efforts in virtual reality. • The study offers technological foresight for financial services perspectives in the Metaverse. [ABSTRACT FROM AUTHOR]

This paper systematically reviews the literature on sociotechnical multi-system innovation frameworks that broaden the usual focus on one sociotechnical system to encompass influences from multiple systems. The review includes 75 peer-reviewed papers that span a broad range of energy-demanding systems and mainly build upon the core frameworks of the Multi-level Perspective (MLP) and Technological Innovation Systems (TIS). The analysis identifies three key aspects to consider in multi-system frameworks. The first aspect is the importance of considering the overarching directionality of multiple sociotechnical systems and how they influence each other. The second is to explicitly analyse the phase of each transitioning system. The third aspect is a need for explicit system configuration analysis. This includes analysing the value chain and the number and types of sectors linked to it, typifying the distinct characteristics of sectors internally and how they interact, and analysing complementary or competitive technologies. The paper concludes by providing recommendations for future research, with a particular focus on the further development of new multi-system frameworks that include one or more of the prior-mentioned three key takeaways. Firstly, focusing on dynamics within multi-system niches. Secondly, performing actor-level analysis, including demand-side analysis. Finally, applying quantitative methods, such as computer simulation modelling. • The systematic review of 75 multi-system transition studies presents three key takeaways. • Considering system interactions in macro-level transition pathways is necessary. • It is important to consider the overarching directionality of multiple sociotechnical systems. • The phase in which each system in transition is should be considered. • System configuration analysis, including value chains and their interactions, is key. [ABSTRACT FROM AUTHOR]

The marketization of factors in China lags behind that of products, and this lag is directly manifested as insufficient effective supply of labor, rising labor costs of enterprises, and serious distortion of labor resource allocation, which to a great extent restricts the economic transformation from "quantity" to the "quality" growth. The labor allocation effect of smart cities plays an important role in promoting the transformation to high-quality development in China, but there is still a lack of empirical research testing this effect. Based on panel data of 151 cities at the prefecture level and above for the period 2006–2018, this paper uses a DID model to evaluate the impact of smart city pilot projects on labor misallocation. The results show that, first, smart cities can significantly reduce labor misallocation, and this finding holds under a series of robustness tests. Second, smart cities can reduce labor misallocation through the formation of industrial agglomeration and the upgrading of the industrial structure. Third, the effect of smart cities was more significant in central and eastern cities and large-scale cities than in western cities and small and medium-scale cities. Fourth, smart cities have a significant spatial spillover effect on the reduction of labor misallocation. • This paper enriches the smart cities and labor misallocation research. • This paper regards the construction of smart cities as a quasinatural experiment. • The smart city project is divided into direct, indirect and spatial spillover effect. [ABSTRACT FROM AUTHOR]

Global climate change poses an unprecedented and urgent challenge, driving the international community towards a consensus on low-carbon sustainable development. Enterprise digital transformation is a strategic response to the evolving demands of the Information Age, which reshapes business processes and reduces energy consumption. This paper empirically investigates the impact of enterprise digital transformation on low-carbon urban development, based on matched "firm-city" data covering the period 2006–2020. The SBM-DDF model is employed to assess low-carbon urban development, and the text mining approach is utilized to calculate the digital transformation index of enterprises. The results indicate that enterprise digital transformation significantly facilitates low-carbon urban development and the primary mechanisms involve fostering green technology innovation, increasing the scale of green investment, and driving the transformation of industrial structure. This promotional effect is positively reinforced by government environmental concerns, government environmental subsidies, and fintech development. Additionally, the positive impact of digital transformation on low-carbon development occurs more predominantly in regions with lower levels of industrialization and marketization, and this effect becomes more evident after the digital transformation wave. By establishing a micro-level empirical foundation, this paper aims to contribute to digital transformation strategic decision-making within enterprises, while also offering a tangible and feasible pathway for advancing low-carbon urban transformation initiatives. • Enterprise digital transformation significantly facilitates low-carbon urban development. • he primary mechanisms through which enterprise digital transformation promotes low-carbon urban development involve fostering green technology innovation, increasing the scale of green investment, and driving the transformation of industrial structure. • The impact of enterprise digital transformation on low-carbon urban development is positively reinforced by government environmental concerns, government environmental subsidies, and fintech development. [ABSTRACT FROM AUTHOR]

This study explores the impact and potential of generative AI, specifically Open AI's ChatGPT, on the transformation of higher education, particularly in the domain of business education. Adopting a qualitative mixed-methods research strategy, this study employs a three-phased methodology consisting of a systematic literature review, semi-structured interviews with academics, and text analysis of opinion posts on professional platforms. This comprehensive approach lends a holistic perspective, integrating insights from both national and global contexts, thereby enhancing the study's methodological rigor and ensuring a nuanced understanding of AI's implications in the educational landscape. ChatGPT, with its personalized and interactive features, enhances pedagogical innovation, academic integrity, and experiential engagements in the teaching-learning-assessment (TLA) process, as revealed by these methodologies' central themes. However, potential obstacles such as plagiarism and diminished development of interpersonal skills were also identified. The findings have significant ramifications for academia and the evolution of AI in education, casting light on the practical benefits and obstacles associated with AI implementation. The study identifies unexplored research avenues to encourage further investigation in this field. This paper contributes to the emerging discourse on AI-enhanced education in business institutions by providing a comprehensive and multifaceted examination of the impact of generative AI on higher education. • Examined the potential of generative AI, specifically Open AI's ChatGPT, in business education. • three-phased methodology is applied to triangulate the findings. • findings have significant ramifications for academia and the evolution of AI in education. • paper contributes to the emerging discourse on AI-enhanced education in business management. [ABSTRACT FROM AUTHOR]

This conceptual paper challenges the notion that the enhanced data security of blockchain results in superior privacy. Blockchain's fundamental characteristics - immutability, decentralization, and transparency - promote an excessive reliance on historical data. This reliance, in turn, leads to inaccurate predictions and misguides consumer privacy preferences. The paper contends that this stern protection conflicts with the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). We argue that the lack of choice in managing data denies freedom, causing psychological reactance. Additionally, the dependence on past data contributes to an intensified privacy paradox as consumers need to assert accurate privacy preferences. These combined effects result in increased consumer digital vulnerability, which arises from an imbalanced power dynamic in data management. We propose a novel approach, which we call "modified blockchain". The approach is based on three pillars: i) selective immutability, ii) federal decentralization, and iii) supervised transparency. These pillars aim to effectively integrate regulations, organizations, and end-users within advocating for a socio-technical decision-making approach. This work also broadens the scope of the psychological reactance theory and the privacy paradox literature by affirming that a lack of autonomy in data management leads to digital vulnerability. • Blockchain technology creates intricate privacy issues despite the prevailing standards on data security. • Blockchain necessitates to adopt a customer-centric "outside-in" approach. • We propose modified blockchain as a paradigm shift from the current blockchain technology. • The modified blockchain framework builds on psychological reactance and privacy paradox theories. [ABSTRACT FROM AUTHOR]