Prison Papermaking: Colonial Ideals of Industrial Experimentation in India.

This article questions the economic rationale of colonial experimentation and prison labor, arguing that for many administrators a prison-based experiment's success mattered less than its existence. It examines the position of convict labor and penal discipline within colonial industrial experiments in colonial India, where convicts performed experiments for what one administrator described as "the most penal" form of labor, papermaking. The belief that Indian fibers could open a new export market for global papermaking meant that prisons became prominent sites of experimentation with new pulps. Regional prisons gained state monopolies for handmade paper, often decimating local independent producers. Yet prison and industrial officers counterintuitively positioned the frequent failures of papermaking experiments as a continuing potential source for industrial improvement. They argued that the failures demonstrated the need to improve discipline and supervision. Prison experiments slotted convicts into repetitive, mechanized roles that served European investigations into the utility of Indian products.

European Technical Democracy? How Consumer Associations Did-or Did Not-Shape the 1980s Automotive Environmental Standards.

Did the 1980s automotive standards reflect the European Economic Community's move toward a "technical democracy" or a broader democratic deficit? In the early 1980s, Europe's automotive sector faced multiple challenges: the European Commission's desire to harmonize technical standards and achieve greater European integration, intense competition between manufacturers, and environmental issues like acid rain. Debates on reducing air pollution focused on unleaded petrol and catalytic converters. Two associations representing civil society in Brussels responded to the increase in environmental concerns with a 1982 joint campaign. Despite a rich historiography on pollutant emission standards, highlighting the strategies of governments and companies, no study has dealt with the role nongovernmental organizations played. Based on public and private archives, particularly those of the European Bureau of Consumers' Unions, this article argues the new regulations did not result from the EU's consultation with civil society organizations like consumer groups but rather with the automotive industry.

From crisis to responsibility: The role of industry type, leadership style, and regulatory environment in shaping post-COVID-19 CSR initiative.

Corporate social responsibility (CSR) is a major concern in modern industries. Chinese industries are growing rapidly and delivering products and services to the market. The Covid-19 pandemic has changed the working style of every type of industry. The objective of this research was to determine the influence of leadership style and industry type on the regulatory environment. This research also aims to determine the impact of the regulatory environment on CSR from the perspective of Chinese industries. Data based on a sample size of 599 was used for data analysis, and Smart PLS 3.0 was used for the results of measurement model assessment and structural model assessment. This study highlighted that industry type and leadership style have a significant positive impact on the regulatory environment and CSR. The framework of this research is based on the identified research gap, and the findings of this study are significant for Chinese policymakers. Furthermore, the research also asserted practical implications that are reliable to advance practices in the regulatory environment and achieve CSR by Chinese firms. This study has several limitations that are required to be significantly addressed for the sustainability of organizations.

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China.

In order to solve the problem of coordinated development among mining economy, social governance and environmental conservation in global resource-based cities, we choose Guangxi Zhuang Autonomous Region as the research area. The advantage of resource endowment and resource industry was measured by location quotient and input-output method. The panel data related to mining governance from 2010 to 2021 were selected to build the evaluation and coupling analysis model between mining economic, social governance and environmental conservation, and the spatial-temporal heterogeneity and coupling effect of them were analyzed by comprehensive empowerment evaluation, spatial autocorrelation analysis and barrier degree methods. The results show that: (1) Except for the overall upward trend of social governance, the development level of mining economy and environmental conservation are basically stable; (2) The resource-rich areas have obvious mining economic advantages, and the central cities have good social governance capabilities, and the environmental conservation effectiveness is uncertain; (3) The coupling effect between mining economy and social governance is stronger than that between mining economy and environment conservation, and the synergistic coupling effect of the three is relatively random. Finally, we put forward some policy response strategies to Guangxi, and theoretical and practical reference would be provided for resource-based cities around the world.

Constructing an evaluation model for the comprehensive level of sustainable development of provincial competitive sports in China based on DPSIR and MCDM.

This study focuses on the objective assessment of sport development in socio-economic environments, considering the challenges faced by the industry. These challenges include disparities in regional investments, limited market participation, slow progress towards sports professionalization, and insufficient technological innovations. To tackle these challenges, we suggest implementing an integrated evaluation model that follows the DPSIR (Drivers, Pressures, States, Impacts, Responses) framework and incorporates comprehensive socioeconomic indicators. Subsequently, we utilized the Entropy power method and TOPSIS (Order Preference Technique for Similarity to an Ideal Solution, TOPSIS) analysis to comprehensively assess the progress of competitive sports development in 31 provinces and cities in China. Additionally, we recommended further developments in competitive sports and proposed precise strategies for promoting its growth. The framework and methodology developed in this paper provide an objective and scientifically based set of decision-making guidelines that can be adopted by government agencies and related industries in order to create successful plans that promote the sustainable growth of competitive sport. This is expected to bolster the nation's global influence, enhance social unity, and fuel economic expansion. The findings of this study offer policymakers valuable insights regarding competitive sports and can advance the development of the sports sector in China, thus making it a crucial driver of regional socio-economic progress.

Research on total factor energy efficiency in western China based on the three-stage DEA-Tobit model.

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation.

Research on the factors and path of sports industry development in China: A fsQCA study of 31 provinces.

The advancement of the sports industry's development constitutes a critical concern shared by regional authorities and the scholarly community, reflecting its significant role in economic and social development. This study employs a Fuzzy-set Qualitative Comparative Analysis (fsQCA) methodology to examine the 31 provincial-level administrative units in China. The objective is to elucidate the influence of technological, organizational, and environmental factors on the industry's development level, considering both a holistic national framework and dissected regional approaches (Eastern, Central, and Western China). This paper's contribution to the literature is structured around the following core findings: (1) The study establishes that a singular condition does not suffice as an essential prerequisite for achieving a heightened development state within the sports industry. (2) At the national level, there are three pathways to enhance the development level of the sports industry, specifically identified as "network-human resources dominant pathway," "technological innovation-human resources dominant pathway," and "comprehensive synergistic pathway."(3) From a regional perspective, the Eastern region has two pathways for sports industry enhancement: "network-economic pathway" and "comprehensive synergistic pathway." The Central region follows a "technology pathway," while the Western region has three pathways: "organization-environment pathway," "network-organization-environment pathway," and "organization pathway."(4) The synthesis of these findings underscores the multifactorial nature of sports industry development, suggesting a paradigm where diverse routes can lead to equivalent outcomes. This heterogeneity indicates that provinces or regions can tailor their development strategies to their unique situational contexts.

Assessing the technical efficiency performance of Chinese ports logistics: Evidence from the DEA and fsQCA.

Ports are critical centers of international trade and global logistics now that economic globalization has taken hold. The efficiency performance of port logistics is crucial to building an emerging pattern of development in which domestic and foreign dual cycles are complementary for China. This paper examines the efficiency performance of 19 ports within five major economic circles in China. It explores how their efficiency is distributed, and the configurations of efficiency improvement during the new normal of China's economy. First, the DEA-BCC model is employed to calculate the technical efficiency performance and distribution of each port from 2011 to 2020. Then, fuzzy-set qualitative comparative analysis (fsQCA) was applied to integrate and analyze the influencing factors. The results show as follows: (1) Each port group performed differently on efficiency rankings, as well as regional distributions. Among these, the port groups of the Bohai Rim region, the Yangtze River Delta region, and the Bohai Rim region continue to rank highly. (2) From the perspective of configuration analysis, the results suggest that government support is not necessary for port logistics with better economic endowments. However, it is critical for backward ones. (3) A rational industrial structure can enhance levels of infrastructure, openness, and information technology, improving port performance. The findings can provide theoretical and practical references for better promoting the development of Chinese port management.al references for better promoting the development of Chinese port management.

Technology empowerment: Digital transformation and enterprise ESG performance-Evidence from China's manufacturing sector.

In light of the long-term constraints posed by the "dual carbon" objective, can digital technology emerge as a transformative solution for enterprises to embark on a sustainable development trajectory? The existing body of research has yet to reach a consensus. In order to shed further light on the intricate relationship between digital transformation and ESG performance of enterprises, this study empirically examines the mechanisms and boundaries through which digital transformation influences ESG performance, based on observational data from A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange spanning from 2011 to 2021. The findings demonstrate that digital transformation exerts a significant positive impact on the ESG performance of manufacturing enterprises. Mechanism analysis reveals that the enabling effect of digital transformation primarily enhances company transparency, thereby fostering continuous improvements in ESG performance among manufacturing enterprises. The performance expectation gap will give rise to the phenomenon of "stop-loss in time" and impede the promotional impact of digital transformation. Further investigation into industrial characteristics and industry competition intensity indicates that state-owned enterprises and those operating within highly competitive environments experience more pronounced effects of digital transformation on their ESG performance. This study expands the mechanism and boundary of digital transformation on ESG performance of manufacturing enterprises, and provides a new perspective for manufacturing enterprises to realize the collaborative transformation of digital and green.

Coupling development of sports industry and tourism industry based on internet of things.

This study investigates the positive coupling between the sports industry and tourism, exploring the ways to promote their interconnection. Under state guidance, the integration of sports industry services is facilitated to attract sports culture and tourism fairs, leveraging regional economic development advantages to enhance the industrial market appeal. The emerging leisure consumption mode of sports tourism injects vitality into the economy, fostering the core sports service industry. The coupling of the education and tourism sectors is strategically aligned with long-term national policies. Using IoT technology, this paper employs a grey relational analysis to assess the coupling between the sports industry and tourism, revealing a significant correlation. Experimental results demonstrate a positive coupling trend, likened to conjoined twins with a natural material basis and technical support. This coupling not only aligns with industry trends but also resonates with the "environmental protection era," "green era," and "ecological era," marking a pivotal aspect of industrial development. The study contributes valuable insights into the symbiotic relationship between the sports and tourism industries, emphasizing their interconnectedness and the positive implications for economic and environmental sustainability.

Does the opening of producer services promote the wage growth of the downstream manufacturing industry?-Empirical evidence from Chinese manufacturing listed companies.

Based on the vertical connection between upstream and downstream industries, a unique theoretical model is constructed to analyse the impact mechanism of the opening of producer services on downstream manufacturing wage growth. The empirical tests are carried out using the data of China's manufacturing listed companies from 1999 to 2020. Our findings indicate that the opening of producer services has an inverted-U-shaped impact on downstream manufacturing wage growth, and the average level of the opening of producer services in the sample period is lower than the corresponding threshold. Overall, it is in the stage of promoting the wage growth of the downstream manufacturing industry. The opening of producer services mainly affects the wage growth of the downstream manufacturing industry through two channels: labour productivity and labour income share. The results of heterogeneity analysis show that the wages of capital and technology-intensive and low-competitive manufacturing industries are relatively strongly promoted by the opening of producer services. Therefore, promoting the orderly opening of producer services and strengthening the technological links between industries will help promote the wage growth of downstream manufacturing industries.

Understanding and including 'pink-collar' workers in employment-based travel demand models.

The segmentation of commuters into either blue or white-collar workers remains is still common in urban transport models. Internationally, models have started to use more elaborate segmentations, more reflective of changes in labour markets, such as increased female participation. Finding appropriate labour market segmentations for commute trip modelling remains a challenge. This paper harnesses a data-driven approach using unsupervised clustering-applied to 2017-20 South East Queensland Travel Survey (SEQTS) data. Commuter types are grouped by occupational, industry, and socio-demographic variables (i.e., gender, age, household size, household vehicle ownership and worker skill score). The results show that at a large number of clusters (i.e., k = 8) a highly distinct set of commuter types can be observed. But model run times tend to require a much smaller number of market segments. When only three clusters are formed (k = 3) a market segmentation emerges with one female-dominated type ('pink collar'), one male-dominated type ('blue collar') and one with both genders almost equally involved ('white collar'). There are nuances as to which workers are included in each segment, and differences in travel behaviours across the three types. 'Pink collar' workers are mostly comprised of female clerical and administrative workers, community and personal service workers and sales workers. They have the shortest median commutes for both private motorised and active transport modes. The approach and methods should assist transport planners to derive more accurate and robust market segmentations for use in large urban transport models, and, better predict the value of alternative transport projects and policies for all types of commuters.

Effects of environmental regulation on adjustment of agricultural industrial structure--An empirical study based on panel data of 31 provinces in China.

Using the panel data of 31 provinces in China between 2000 and 2018, this study theoretically and empirically analyses the impact of environmental regulations on the adjustment of the agriculture industrial structure from the perspectives of rationalisation and optimisation. Overall, variability in the impact of environmental regulation on the adjustment of the agricultural industrial structure is identified: a negative influence on the rationalisation of agricultural industrial structure and a positive influence on the optimisation of agricultural industrial structure. The impact of environmental regulations on the adjustment of agricultural industrial structure also reflects "large country characteristics": environmental regulations are more significant at the medium and low industrial structure levels. Environmental regulation significantly impacts the rationalisation of agricultural industrial structure in central and western regions and its optimisation in eastern and central regions. Through the panel threshold model test, this paper further finds that the effect of environmental regulations on the adjustment of agricultural industrial structure is not invariant. However, there is a non-linear relationship with significant threshold characteristics. Based on the above results, some countermeasures are suggested.

The multi-strategy hybrid forecasting base on SSA-VMD-WST for complex system.

In view of the strong randomness and non-stationarity of complex system, this study suggests a hybrid multi-strategy prediction technique based on optimized hybrid denoising and deep learning. Firstly, the Sparrow search algorithm (SSA) is used to optimize Variational mode decomposition (VMD) which can decompose the original signal into several Intrinsic mode functions (IMF). Secondly, calculating the Pearson correlation coefficient (PCC) between each IMF component and the original signal, the subsequences with low correlation are eliminated, and the remaining subsequence are denoised by Wavelet soft threshold (WST) method to obtain effective signals. Thirdly, on the basis of the above data noise reduction and reconstruction, our proposal combines Convolutional neural network (CNN) and Bidirectional short-term memory (BiLSTM) model, which is used to analyze the evolution trend of real time sequence data. Finally, we applied the CNN-BiLSTM-SSA-VMD-WST to predict the real time sequence data together with the other methods in order to prove it's effectiveness. The results show that SNR and CC of the SSA-VMD-WST are the largest (the values are 20.2383 and 0.9342). The performance of the CNN-BiLSTM-SSA-VMD-WST are the best, MAE and RMSE are the smallest (which are 0.150 and 0.188), the goodness of fit R2 is the highest(its value is 0.9364). In contrast with other methods, CNN-BiLSTM-SSA-VMD-WST method is more suitable for denoising and prediction of real time series data than the traditional and singular deep learning methods. The proposed method may provide a reliable way for related prediction in various industries.

Comparative stability analysis of Indonesian banks: Markov Switching-Dynamic Regression for Islamic and conventional sectors.

The banking industry necessitates implementing an early warning system to effectively identify the factors that impact bank managers and enable them to make informed decisions, thereby mitigating systemic risk. Identifying factors that influence banks in times of stability and crisis is crucial, as it ultimately contributes to developing an improved early warning system. This study undertakes a comparative analysis of the stability of Indonesian Islamic and conventional banking across distinct economic regimes-crisis and stability. We analyze monthly banking data from December 2007 to November 2022 using the Markov Switching Dynamic Regression technique. The study focuses on conducting a comparative analysis between Islamic banks, represented by Islamic Commercial Bank (ICB) and Islamic Rural Bank (IRB), and conventional banks, represented by the Conventional Commercial Bank (CCB) and Conventional Rural Bank (CRB). The findings reveal that both Islamic and conventional banks exhibit a higher probability of being in a stable regime than a crisis regime. Notably, Islamic banks demonstrate a greater propensity to remain in a stable regime than their conventional counterparts. However, in a crisis regime, the likelihood of recovery for Sharia-compliant institutions is lower than for conventional banks. Furthermore, our analysis indicates that larger banks exhibit higher stability than their smaller counterparts regarding assets and size. This study pioneers a comprehensive comparison of the Z-score, employed as a proxy for stability, between two distinct classifications of Indonesian banks: Sharia (ICB and IRB) and conventional (CCB and CRB). The result is expected to improve our awareness of the elements that affect the stability of Islamic and conventional banking in Indonesia, leading to a deeper comprehension of their dynamics.

The impact of COVID-19 pandemic on the world's major economies: based on a multi-country and multi-sector CGE model.

Objective: To quantitatively assess the impact of COVID-19 pandemic on public health, as well as its economic and social consequences in major economies, which is an international public health concern. The objective is to provide a scientific basis for policy interventions. Subject and methods: This study utilizes a multi-country, multi-sector CGE-COVID-19 model to analyze the repercussions of the pandemic in 2022. The re-search focuses on quantifying the effects of COVID-19 on the macroeconomy and various industry sectors within six economies: the United States, China, the EU, the United Kingdom, Japan, and South Korea. Results: The COVID-19 pandemic shock had the most significant impact on China and the EU, followed by notable effects observed in the United States and the United Kingdom. In contrast, South Korea and Japan experienced relatively minimal effects. The reduction in output caused by the pandemic has affected major economies in multiple sectors, including real industries such as forestry and fisheries, and the services such as hotels and restaurants. Conclusion: The overall negative macroeconomic impact of the epidemic on major economies has been significant. Strategic interventions encompassing initiatives like augmenting capital supply, diminishing corporate taxes and fees, offering individual subsidies, and nurturing international cooperation held the potential to mitigate the detrimental economic consequences and enhance the global-economic amid the pan-demic. Consequently, this study contributes to the advancement of global anti-epidemic policies targeting economic recovery. Moreover, using the CGE-COVID-19 model has enriched the exploration of general equilibrium models in PHEIC events.

Does the "Belt and Road Initiative" benefit the environment? Insight from analysis of intra-industry trade in environment goods.

The expansion of the Belt and Road Initiative (BRI) has raised a wide range of concerns about its environmental impact. Therefore, from the perspective of environmental impacts, this study used the two-way fixed effect staggered differences in differences (TWFE Staggered DID) method to examine the impact of the BRI on the Environment Goods (EGs) intra-industry trade (IIT) between China and other Belt and Road (B&R) countries, including a sample of 191 countries, covering the period from 2010 to 2019 for eliminating the impact of COVID-19 and the financial crisis in 2008 and 2009. Because only 135 countries signed a Memorandum of Understanding between 2010 and 2019, this study treated these B&R countries as the study group, and the other 73 countries (non-B&R countries) as the control group. This study described EGs using the 54 6-digit code Environment Goods in Harmonized Commodity Description and Coding System listed in the "APEC LIST OF ENVIRONMENT GOODS" published by the Asia-Pacific Economic Cooperation in 2012, and used the intra-industry trade index proposed by Grubel and Lloyd in 1971 to measuring dependent variable. The research results indicated that the BRI has significantly promoted bilateral EGs IIT. The mechanism test implied that, in addition to direct impacts, the BRI also has indirect impacts by boosting the energy restructuring of B&R countries. These results prove that the BRI has positive impacts on the environment. The heterogeneity test showed that there is a heterogeneous impact depending on the type of IIT, product categorization, B&R countries' income levels, and geographic environment. This study not only gives theoretical and empirical evidence of the positive environmental impacts of the BRI, but also provides practical guidance for the development of EGS IIT between China and B&R countries, thereby contributing to global carbon emissions reduction and environmental governance to some degree.

AI technology specialization and national competitiveness.

This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effect panel logit model to examine the relationship between AI specialization and its determinants. The results indicate that the development of AI technology is strongly contingent on a nation's pre-existing technological capabilities, which significantly affect AI specialization in emerging domains. Additionally, this study reveals that scientific knowledge has a positive impact on technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors. Although complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields, such as AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies to outpace competitors. This insight points nations toward enhancing AI competitiveness in new areas, emphasizing the vital importance of both scientific and technological capabilities, and the integration of novel AI knowledge with established sectors. This research offers critical guidance for policymakers in less technologically and economically developed countries, as these nations may not have the technological infrastructure required to foster AI specialization through increased technical complexity.

Changes in the labor share of enterprises under the green and low-carbon transition: Empirical evidence from China's carbon emission trading pilot.

Green and low carbon reflect the high-quality development, while income distribution is an indicator of the balance of development. Is there a lack of fairness in the process of green and low carbon transition of enterprises? Using data from A-share listed companies from 2009 to 2016, this paper constructs a DID identification framework for controlling the endogeneity problem using the 2013 carbon trading policy pilot as a quasi-natural experiment to empirically test the impact of corporate low-carbon transformation on corporate labor income share in the context of carbon trading policy. The findings indicate that carbon trading policy decreases the labor income share of firms. In addition, we demonstrate that the low-carbon transition promotes labor productivity, suggesting that the Porter's hypothesis is confirmed in China, but the increase in labor wages is not in tandem with productivity growth, resulting in reduced labor income share. Heterogeneity analysis shows that the impact of carbon trading policy on labor income share is mainly pronounced in larger firms, high technology firms and persistent incumbent firms. Collectively, these results are expected to accurately improve our understanding on the impact of low-carbon transformation of enterprises on income distribution and provide reference for the government to formulate industrial policies and distribution mechanisms under low-carbon economy.