Search results

The development of prefabricated buildings has become one of the primary solutions to transform the traditional construction industry around the world. Incentive policy is one of the important driving factors for the development of prefabricated building. The policy system in the field of prefabricated buildings needs to be improved urgently. However, there is still a dearth of research on how incentive policies exert impact on the development of prefabricated buildings. This paper aims to reveal the impact mechanisms of different types of policies on the development system of prefabricated buildings.

This study categorizes prefabricated building policies, constructs a system dynamics model of prefabricated building policies and conducts scenario simulations to examine the impact and sensitivity of different types of policies on the development system of prefabricated buildings.

The results show that compulsory policies play a greater role in the early stage of prefabricated building development and need to be withdrawn at the right time. Preferential and encouraging policies play an incentive role in the middle and later stages of prefabricated building development. Encouraging policies predominate in the later stage of prefabricated building development. Based on the research results, policy recommendations for prefabricated building development are put forward respectively from the government, developers and consumers.

The research results are expected to make up for the lack of clear policies paths in existing research and provide theoretical references for the formulation and optimization of future policies.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.

This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.

The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.

This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

Despite a growing body of research focusing on the dark side of sharing economy development, arguments are fragmented and incomplete. This study aims to address the gap by integrating existing viewpoints based on a provider’s perspective.

This study conducted a bibliometric analysis using text mining and clustering algorithm techniques to measure the scope of scientific output on this topic and identify the main research themes.

Through the bibliometric analysis, this study developed an integrative framework based on the platform providers’ internal management issues and external conflicts with consumers, society, government regulations and traditional business. It also identified significant gaps within each research theme and proposed a future research agenda.

Sharing economy development has not yet been fully understood and regulated, leading to unprecedented challenges to existing business systems. The study addresses knowledge gaps and advances the understanding of the dark side of the sharing economy based on the provider’s internal management and interplay with external forces. It offers a roadmap for future research to advance understanding of the “hidden” dark side of the sharing economy.

The digital economy has become a key force supporting the high-quality development of tourism. This paper discusses the coupling coordination relationship and spatiotemporal evolution path of digital economy and tourism in China's provinces.

This paper uses the entropy method to measure the development level of digital economy and tourism, and establishes coupling coordination model and spatial autocorrelation model to study the interaction between the two industries.

Results show that the development levels of the two industries are rising, which spatially show a progressively decreasing pattern of east-middle-northeast-west. The coupling coordination degrees of the two industries have increased steadily, but the overall level is still near maladjusted. Spatially, the positive correlation is increasing, but the incongruity of spatial agglomeration is still significant. The coupling coordination evolution path in the provinces shows differentiated characteristics. The migration path is mainly concentrated in Zones I and II. The eastern region has an obvious trend of extending to Zone III, where the tourism industry was the most affected by the pandemic.

The study helps clarify the industrial coupling and coordination relationship in various regions and formulate regional tourism digital transformation strategies to promote the high-quality development of China's tourism industry.

This paper enriches the research on the relationship between digital economy and tourism from the perspective of industrial integration. The development commonality of China's tourism digital transformation summarized provides theoretical reference and demonstration for the coordinated development of China's tourism.

This study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.

The authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.

The authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.

The limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.

This study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.

This paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.

This study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

Although the significance of technological progress in economic development is well-established in theory and policy, it has remained challenging to agree upon shared priorities for strategies and policies. This paper aims to develop a model of how policymakers can develop effective and easy to communicate strategies for science, technology and economic development.

By integrating insights from economic complexity, competitiveness and foresight literature, a replicable research framework for analysing the opportunities and challenges of technological revolutions for small catching-up countries is developed. The authors highlight key lessons from piloting this framework for informing the strategy and policies for bioeconomy in Estonia towards 2030–2050.

The integration of economic complexity research with traditional foresight methods establishes a solid analytical basis for a data-driven analysis of the opportunities for industrial upgrading. The increase in the importance of regional alliances in the global economy calls for further advancement of the analytical toolbox. Integration of complexity, global value chains and export potential assessment approaches offers valuable direction for further research, as it enables discussion of the opportunities of moving towards more knowledge-intensive economic activities along with the opportunities for winning international market share.

The research merges insights from the economic complexity, competitiveness and foresight literature in a novel way and illustrates the applicability and priority-setting in a real-life setting.

This study is intended to analyze the impact of information and communication technology (ICT) infrastructure, technological innovation, renewable energy consumption and financial development on carbon dioxide emissions in emerging economies.

The present study adopts the autoregressive distributed lag (ARDL) cointegration technique for the annual data collection of Vietnam from 1990 to 2020.

The results of the study unveil that renewable energy consumption, the interaction between renewable energy consumption and ICT infrastructure and financial development have significant predictive power for carbon dioxide emissions. In the long term, renewable energy consumption, export and population growth reduce CO2 emissions, whereas the interaction between renewable energy consumption and ICT infrastructure and financial development increases CO2 emissions, while ICT infrastructure does not affect emissions. In the short run, changes in ICT infrastructure contribute to carbon dioxide emissions in Vietnam. In addition, changes in renewable energy consumption, financial development, the interaction between ICT infrastructure and renewable energy consumption and population growth have a significant effect on CO2 emissions. Notably, technological innovation has no impact on CO2 emissions in both the short and long run.

The current study provides new insights into the environmental effects of ICT infrastructure, technological innovation, renewable energy consumption and financial development. The interaction between renewable energy consumption and ICT infrastructure has a significant effect on carbon dioxide emissions. The paper suggests important implications for setting long-run policies to boost the effects of financial development, renewable energy consumption and ICT infrastructure on environmental quality in emerging countries like Vietnam in the coming time.

In this paper we explore potential barriers for commodification of academic research in emerging countries.

We carried out an exploratory study employing a mixed-method sequential exploratory design. Initially, qualitative interviews were performed to identify cognitive, structural, and ideological barriers associated with commodification. Subsequently, we administered a survey at three universities in Kazakhstan to gather quantitative data. The quantitative insights served to complement our qualitative findings and facilitate the interpretation of the observed patterns within the broader population.

We found that a too rapid shift toward commercialization exacerbated concerns among faculty members and created obstacles to commodification. The obstacles identified through inductive clustering of themes from exploratory qualitative interviews were grouped into three intentionally broad categories: cognitive, structural, and ideological barriers. We argue that in emerging economies, the path to commodifying academic research should start with developing local infrastructure to address identified structural, cognitive, and ideological barriers. This, in turn, will lead to more successful commercialization and redefine the role of academics in society.

Our study has several limitations related to its empirical scope. We concentrated solely on one country, Kazakhstan. For future research, it is crucial to broaden the investigation to include more studies from the Central Asia region and other emerging economies. We believe that while there may be some minor institutional differences, the findings are generalizable to all post-socialist countries. However, incorporating a diverse range of institutions, particularly those with foreign ownership or private capital, would enhance the comprehensiveness of the findings. Furthermore, collecting a more extensive and balanced sample of responses from industry partners, academics, and students would have provided more valuable insights. By including a broader representation of stakeholders, we could have gained a more nuanced understanding of the complexities surrounding commodification in higher education. Given the exploratory nature of this study, it is essential to regard the findings as a source of inspiration rather than empirical confirmation.

Our research has practical implications for managing universities in emerging markets, as well as important policy implications, both for international actors and local governmental bodies.

Our findings carry implications for policymakers. The focus that international institutions place on the matter of commodification and commercialization of knowledge is a positive step. Challenges emerge when this matter is approached with a narrow perspective. Drawing on the empirical context of the Republic of Kazakhstan, a country often overlooked in the literature on emerging markets, we find evidence that knowledge has indeed transformed into a commodity. The rapid shift toward commercialization, driven by substantial institutional pressures, may have occurred too precipitously in this particular context. In light of these findings, we advocate for a more balanced and contextually nuanced discourse concerning both the commodification and commercialization of knowledge.

This study represents one of the few endeavors into exploring commodification within the context of emerging economies. In recent decades, universities have faced substantial pressures to commodify academic research. While there has been a significant volume of research discussing and documenting the success of commodification in developed country universities, those in emerging economies have faced similar pressures without achieving comparable success. This paper delves into the reasons why.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.