Linkage Effects Research Articles

Study on the Interactive Effect Between Public Library Construction and Human Capital Investment Efficiency

This paper measures the public library construction (PLC) level and the human capital investment (HCI) efficiency of 31 provinces in China from 2011 to 2021, tests the linkage effect and coupling coordination between PLC and HCI. The results show that: 1) the PLC level and the HCI efficiency of China shows a trend of rapid increase and fluctuating decrease respectively during this period, but the gap between regions is obvious. Both the PLC level and the HCI efficiency in the eastern region are obviously better than those in the central region and the western region. 2) There is not only a positive linkage effect between PLC and HCI efficiency, which promotes each other, but also the level of collaborative development between PLC and HCI efficiency shows a steady upward trend, with the coupling level reaching level 6, which is about to enter the primary coordination state, but there are obvious regional differences.

Investigating genotype by environment interaction for beef cattle fertility traits in commercial herds in northern Australia with multi-trait analysis

BackgroundGenotype by environment interactions (GxE) affect a range of production traits in beef cattle. Quantifying the effect of GxE in commercial and multi-breed herds is challenging due to unknown genetic linkage between animals across environment levels. The primary aim of this study was to use multi-trait models to investigate GxE for three heifer fertility traits, corpus luteum (CL) presence, first pregnancy and second pregnancy, in a large tropical beef multibreed dataset (n = 21,037). Environmental levels were defined by two different descriptors, burden of heat load (temperature humidity index, THI) and nutritional availability (based on mean average daily gain for the herd, ADWG). To separate the effects of genetic linkage and real GxE across the environments, 1000 replicates of a simulated phenotype were generated by simulating QTL effects with no GxE onto real marker genotypes from the population, to determine the genetic correlations that could be expected across environments due to the existing genetic linkage only. Correlations from the real phenotypes were then compared to the empirical distribution under the null hypothesis from the simulated data. By adopting this approach, this study attempted to establish if low genetic correlations between environmental levels were due to GxE or insufficient genetic linkage between animals in each environmental level.ResultsThe correlations (being less than <0.8) for the real phenotypes were indicative of GxE for CL presence between ADWG environmental levels and in pregnancy traits. However, none of the correlations for CL presence or first pregnancy between ADWG levels were below the 5th percentile value for the empirical distribution under the null hypothesis from the simulated data. Only one statistically significant (P < 0.05) indication of GxE for first pregnancy was found between THI environmental levels, where rg = 0.28 and 5th percentile value = 0.29, and this result was marginal.ConclusionsOnly one case of statistically significant GxE for fertility traits was detected for first pregnancy between THI environmental levels 2 and 3. Other initial indications of GxE that were observed from the real phenotypes did not prove significant when compared to an empirical null distribution from simulated phenotypes. The lack of compelling evidence of GxE indicates that direct selection for fertility traits can be made accurately, using a single evaluation, regardless of environment.

Spatial correlation effect of haze pollution in the Yangtze River Economic Belt, China.

With the rapid development of industry, haze pollution has become an urgent environmental problem. This study innovatively utilizes network-based methods to investigate the spatial correlation effects of haze pollution transmission between urban clusters in the Yangtze River Economic Belt. A spatial correlation network of haze pollution in the Yangtze River Economic Belt was constructed using 328 urban meteorological data collection points as research samples, and its structural characteristics were examined. Main findings are as follows: (1) The spatial correlation network of PM2.5 in the Yangtze River Economic Belt urban agglomeration exhibits typical network structural characteristics: obvious spatial correlation within the network. (2) Chengdu, Chongqing, Wuhan, Nanchang, Yichang, Changsha and Yueyang are located at the center of the spatial network. They have more receiving and sending relationships. (3) 36 cities can be divided into four types: bilateral overflow, net beneficiary, net overflow and broker. Each type has different functional characteristics and linkage effects in the network. (4) Haze pollution positively correlates with the city's synergistic development capacity and urbanization rate, the higher the city's development level and the higher the Urbanization rate, the stronger its haze pollution capacity. This study provides new insights into the study of the spatial correlation and impact of haze pollution.

Unraveling Social Health Inequalities during COVID-19 in Belgium: The Vital Role of Data Linkages

Abstract Background During the COVID-19 crisis, data linkages were set up to efficiently monitor the outbreak and identify vulnerable population groups. Yet, considerable technical, administrative and data security issues have hindered the effectiveness of data linkages as a critical instrument during public health emergencies. This workshop aims to provide a practical demonstration of the challenges encountered in a Belgian data linkage during the COVID-19 crisis, along with the strategies implemented to overcome these challenges. This case study offers insights into the development of a highly sensitive linkage between COVID-19 hospital data and information related to social and health use in Belgium. Methods The HELICON data linkage is developed at the individual level to investigate the risk of COVID-19 hospitalization and the influence of various social and biomedical factors during and after the crisis. Data are drawn from data collections on hospitalization from the COVID-19 health surveillance (Sciensano), on the socioeconomic and sociodemographic context (Statistics Belgium), and on healthcare use and reimbursement (InterMutualistic Agency). Results A representative case-cohort study is established comprising 1,149,264 million randomly selected Belgians and 44,508 hospitalized patients. Annual follow-up is scheduled over a four-year span, allowing the investigation of pre- and post-pandemic health data from July 2020 to January 2026. Conclusions The HELICON data linkage took 3.5 years to complete. Among the many challenges, we were faced with complicated approval procedures, ambiguous data security guidelines, unclear cost estimates, and technical issues related to the analysis environment. Building on these experiences, we explore the strengths and weaknesses of data linkages as a research instrument during the COVID-19 pandemic and discuss which lessons should be drawn to for the post-pandemic era.

A co-evolutionary approach to MNE-assisted industry development: Uruguay’s forest-based pulp sector

Purpose This study aims to investigate how co-evolutionary interactions between multinational enterprises (MNEs) and local actors shaped resource-intensive industry development over several decades, examining the economic, industrial and social implications of these interactions. It details the long-term effects of MNEs’ activities on the host country’s economic and social development and unfolds the path-dependent sequence and mechanisms of occurrence. Design/methodology/approach In a historical case study of Uruguay’s forest-based pulp sector during the 1970s to 2023, the authors analyze data from interviews with local industry actors and from company archives, academic publications and public environmental organizations. Findings The findings untangle the path-dependent co-evolution between MNEs’ activities and local actors and the resulting gradual development of the local industry. The increasing commitment of MNEs to the host country and their engagement with business and social communities impact the development of the industry’s technology basis, activity networks, identity and market. Spillovers and linkages occur in these interactions, driving industry development processes forward. The authors also reveal how MNEs attempt to address the social and environmental tensions associated with their operations to support their long-term presence in the host country. Research limitations/implications The authors contribute to the MNE-assisted development literature by untangling the specific mechanisms of MNEs’ engagement in local industry development over a long-term period and elaborating on its industrial and social implications. The authors enhance knowledge about spillovers by capturing a wide range of spillover and linkage effects and assessing their long-term impacts on industry development. Practical implications The authors offer insights into how policymakers can tailor instruments for attracting MNEs by adopting a long-term perspective regarding the implications for local development and accounting for economic, industrial and social impacts. This approach can maximize beneficial outcomes from MNEs’ presence and limit tensions between MNEs and local actors. Social implications This historical case study illustrates the complexity of MNEs’ engagement with local actors over time, including various tensions and positive developments. It illustrates the importance of social acceptance in achieving quality linkages between local and foreign actors. Originality/value This historical analysis untangles the path dependency in the long-term impacts of MNE-assisted development, illustrating the value of a temporal perspective.

Effect of mesogenic linkages on two novel aromatic series-based liquid crystals: synthesis, theoretical and comparative studies

ABSTRACT Two novel groups of rod-like homologue molecules, one group (group A) having benzothiazole-aromatic mesogenic units and the other (group B) with only aromatic mesogenic units, were designed and synthesised. Both groups (compounds A and B) involve azomethine (−CH=N−), ester (−COO−), azo (−N=N−) and amide (−NH−CO−) linking groups at the different positions in their molecular structures. The structures of the synthesised compounds were elucidated using different analytical techniques (1H, 13C NMR, FT−IR, mass spectra and melting points). In order to verify the influence of the central linkages and their positions on physicothermal and mesomorphic properties, different types of linking groups including −CH=N−, −COO-, −N=N− and −NH−CO− were analytically and thermally investigated. Thermal analyses and mesomorphic properties of both series are discussed in terms of the linkages nature, comprising geometrical structure, interactions polarisability, subtle change in shape and their effective positions. The results revealed that the synthesised compounds (groups A and B) showed the only enantiotropic nematic mesophase in certain temperature regions except compounds A4 and A6. The change of the type linkages and their positions in some compounds (groups A and B) was theoretically investigated to verify if the theoretical calculations show an agreement with the experimental findings.

A study on the backtesting and correlation of systemic risk in Chinese financial institutions: an empirical analysis based on MES and Delta CoVaR

Effectively measuring the risk level of financial institutions is the key to preventing and defusing systemic risks. This paper uses the unconditional coverage test method to backtest the systemic risk of 35 listed financial institutions in China, and uses the quantile coherence method to construct a quantile frequency domain correlation network to explore the frequency domain mechanism of systemic risk correlation of financial institutions. The study found that: (1) During the financial market crisis, the Delta CoVaR commonly used systemic risk measurement indicators such as MES, CoVaR, and failed to effectively measure the systemic risk of China's financial institutions. (2) Compared with the short-term correlation layer and the medium-term correlation layer, China's financial institutions have obvious extreme risk linkage effects in the long-term correlation layer.(3) In the short-term, medium-term and long-term correlation layers, small and medium-sized financial institutions such as Ningbo Bank, Industrial Securities and Dongfang Energy all have high correlation importance. Relevant departments should pay attention to preventing the risk of "too correlated to fail" of small and medium-sized financial institutions in my country.

The productivity spillover effect of foreign divestment: Evidence from Chinese industrial enterprises

Foreign divestment in China is garnering increasing social attention. This study investigates the productivity spillover effects of foreign divestment based on Chinese industrial enterprise data from 2000 to 2007. Our findings indicate that foreign divestment negatively impacts the total factor productivity (TFP) of incumbent enterprises, especially through backward linkages. We examine potential mechanisms based on the characteristics of divested and incumbent enterprises. The closure of foreign-invested enterprise disrupts industrial connections, whereas the sale of foreign equity to domestic shareholders strengthens local industrial linkages, thus presenting an opposite effect. Hong Kong, Macau, and Taiwan (HMT)-invested enterprises tend to local sourcing, leading to divestment effects through backward linkages. Conversely, non-HMT enterprises, with a higher capability to provide differentiated intermediate goods, primarily exhibit forward linkage effects. Further analysis reveals that incumbent enterprises with lower technological capabilities are more dependent on their foreign suppliers and customers. Domestic non-state-owned enterprises and those in regions with lower economic development or marketization levels also have less stable input-output relationships. As a result, these enterprises are more susceptible to the vertical spillover effects of foreign divestment.

Investigation of local stimulation effects of embedding PGLA at Zusanli (ST36) acupoint in rats based on TRPV2 and TRPV4 ion channels.

Acupoint Catgut Embedding (ACE) is an extended and developed form of traditional acupuncture that serves as a composite stimulation therapy for various diseases. However, its local stimulation effects on acupoints remain unclear. Acupuncture can activate mechanically sensitive calcium ion channels, TRPV2 and TRPV4, located on various cell membranes, promoting Ca2+ influx in acupoint tissues to exert effects. Whether ACE can form mechanical physical stimulation to regulate these channels and the related linkage effect requires validation. This study investigates the influence of TRPV2 and TRPV4 ion channels on the local stimulation effects of ACE by embedding PGLA suture at the Zusanli (ST36) acupoint in rats and using TRPV2 and TRPV4 inhibitors. Flow cytometry, immunofluorescence, Western blot, and Real-time quantitative PCR were employed to detect intracellular Ca2+ fluorescence intensity, the expression of macrophage (Mac) CD68 and mast cell (MC) tryptase, as well as the protein and mRNA expression of TRPV2 and TRPV4 in acupoint tissues after PGLA embedding. The results indicate that ACE using PGLA suture significantly increases the mRNA and protein expression of TRPV2 and TRPV4, Ca2+ fluorescence intensity, and the expression of Mac CD68 and MC tryptase in acupoint tissues, with these effects diminishing over time. The increasing trends are reduced after using inhibitors, particularly when both inhibitors are used simultaneously. Furthermore, correlation analysis shows that embedding PGLA suture at the ST36 acupoint regulates Mac and MC functions through Ca2+ signaling involving not only TRPV2 and TRPV4 but multiple pathways. These results suggest that embedding PGLA suture at the ST36 acupoint generates mechanical physical stimulation and regulates TRPV2 and TRPV4 ion channels, which couple with Ca2+ signaling to form a linkage effect that gradually weakens over time. This provides new reference data for further studies on the stimulation effects and clinical promotion of ACE.

Horizontal and vertical foreign direct investment linkages, absorptive capacity and domestic investment: evidence from Indonesian plant-level data

PurposeThis study examines the effect of horizontal and vertical foreign direct investment (FDI) linkages on the investment decisions of domestic plants. It explores this link for plants in a developing country, where the dynamics of FDI spillovers on domestic investment choices are distinct from those in developed countries. It also adds to the literature by examining the role the absorptive capacity of plants plays in this nexus, enriching our understanding of the interaction between FDI and the investment choices of domestic plants and providing insights for policymakers and managers seeking to maximize the positive effects of FDI spillovers.Design/methodology/approachThis study specifies the dynamic investment equation using the Euler and Q models. This equation is estimated using the first-difference and system generalized method of moments GMM estimators, which allow us to address persistency, endogeneity and unobserved plant-specific effects. FDI exposure proxy, calculated by weighing the FDI engagement variable by firm size, captures the strength of foreign equity participation in an industry and time. Input–output (IO) tables are used to calculate the proxies for horizontal and vertical (backward and forward) FDI. Total factor productivity is calculated using a method advocated by Olley and Pakes (1996) that allows us to control for selection and simultaneity.FindingsWe find that FDI inflows into both the domestic plants’ own industry and the input-supplying industry significantly boost the capital accumulation of the average domestic plants. Differentiating plants based on their absorptive capacities reveals that the presence of foreign firms significantly increases capital deepening for domestic plants with high absorptive capacity within their own industry (horizontal linkage) and in industries that supply inputs to the FDI-exposed industry (backward linkage). However, it leads to a decrease in capital deepening for high absorptive capacity domestic plants in industries using inputs produced by the industry exposed to FDI (forward linkage).Research limitations/implicationsThese findings have implications for policymakers and managers who aim to design incentives to maximize the positive spillover effect of horizontal and vertical FDI linkages on the capital deepening of domestic plants. Exploring additional mechanisms that could play a role in this nexus, separately for plants in different industries (such as the industries in which the country has a comparative advantage), may be fruitful.Originality/valueTo our knowledge, the relationship between the investment behavior of the domestic plants and FDI linkages has not been examined for a developing country. It is useful to explore this link in developing countries, as the investment choices of plants in these nations may be impacted differently by FDI spillovers than those in advanced nations. This study further contributes to the literature by investigating whether the plants’ absorptive capacity affects the nexus between FDI linkages and investment decisions of the domestic plants. The findings are valuable for policymakers and managers who aim to increase plants’ capital accumulation in developing countries.

Linkability measures to assess the data characteristics for record linkage.

Accurate record linkage (RL) enables consolidation and de-duplication of data from disparate datasets, resulting in more comprehensive and complete patient data. However, conducting RL with low quality or unfit data can waste institutional resources on poor linkage results. We aim to evaluate data linkability to enhance the effectiveness of record linkage. We describe a systematic approach using data fitness ("linkability") measures, defined as metrics that characterize the availability, discriminatory power, and distribution of potential variables for RL. We used the isolation forest algorithm to detect abnormal linkability values from 188 sites in Indiana and Colorado, and manually reviewed the data to understand the cause of anomalies. We calculated 10 linkability metrics for 11 potential linkage variables (LVs) across 188 sites for a total of 20680 linkability metrics. Potential LVs such as first name, last name, date of birth, and sex have low missing data rates, while Social Security Number vary widely in completeness among all sites. We investigated anomalous linkability values to identify the cause of many records having identical values in certain LVs, issues with placeholder values disguising data missingness, and orphan records. The fitness of a variable for RL is determined by its availability and its discriminatory power to uniquely identify individuals. These results highlight the need for awareness of placeholder values, which inform the selection of variables and methods to optimize RL performance. Evaluating linkability measures using the isolation forest algorithm to highlight anomalous findings can help identify fitness-for-use issues that must be addressed before initiating the RL process to ensure high-quality linkage outcomes.

Assessing carbon capture and storage technology in industrial joint venture

Carbon Capture and Storage (CCS) technology can effectively reduce carbon dioxide emissions from industrial and energy production processes. Yet the commercialization of CCS technology is hampered by financial requirements. Existing research compares the costs and benefits of business models for individual CCS projects, no studies assess the industry and national levels. Here we use a dynamic computable general equilibrium model, constructure the vertical integration and joint venture business models for CCS. This study assesses the emission and economic impacts of joint ventures between China's high-emission industries and their upstream and downstream sectors. We find that adopting the joint venture model in the coal power sector, compared to the vertical integration model, initially exerts a negative economic impact but can mitigate 0.04 % of GDP by 2060. The chemical industry consistently benefits from the joint venture model both economically and in emission reductions. Downstream sectors of the steel and cement industries are unsuitable for participation in joint ventures. In addition, the joint venture model has significant industry linkage effects, affecting energy consumption, the scale and cost of CCS deployment. This work provides important information for the large-scale commercialization of CCS technology.

Moderating Effect of Strategic Linkages on Corporate Leadership and Organizational Performance in Kenya Agricultural and Livestock Research Organization (KALRO)

The urgency of securing safe, affordable, reliable, and nutritious food amid a growing global population and shrinking land productivity underscores the pivotal role of corporate leadership in fostering strategic partnerships and organizational performance. This is crucial for organizations like Kenya Agricultural and Livestock Research Organization (KALRO) to enhance performance and drive agricultural innovation that ensure achievement of national targets and mandate. Understanding the dynamics between leadership effectiveness, strategic alliances, and organizational performance is essential for addressing food security challenges and optimizing the impact of agricultural research institutions worldwide. The projected 27% increase in global population by 2050 emphasizes the need for strong corporate leadership and strategic partnerships to ensure balanced diets for over half a billion smallholder farmers. Despite Kenya&amp;apos;s higher productivity than East Africa and Africa averages, challenges remain in enhancing food security through effective leadership and strategic alliances, particularly within institutions like KALRO. The study explored the moderating influence of strategic linkages on the relationship between corporate leadership and the performance of KALRO. Rooted in organizational excellence, upper echelons, legitimacy, and stakeholder theories, the research employed a pragmatic philosophy, and mixed methods design to mitigate bias. The target population included 75 management organs, with 60 directors and 188 top leadership units as units of observation. Quantitative analysis, using a composite regression model and ANOVA, revealed a significant impact of strategic linkages on corporate leadership and KALRO&amp;apos;s performance. The study verified consistent variances and normality across variables, supporting parametric analyses. Autocorrelation analysis indicated no significant autocorrelation. Multicollinearity tests showed acceptable values, ensuring the reliability of the regression model. No outliers were detected. Cronbach&amp;apos;s alpha scores demonstrated strong internal reliability. Significant correlations confirmed associations between variables, aligning with previous research findings. Strategic linkages emerged as enhanced moderator, explaining 69.4% of the variance. In this case, the moderator variable amplified or strengthened the relationship between corporate leadership and organizational performance of KALRO. Rejecting the null hypothesis highlighted the positive impact of strategic linkages on performance. Conditional effects analysis revealed strong corporate leadership influence at low strategic linkages but diminishing at higher levels. Recommendations encompassed gender diversity, inclusive leadership development, regular performance appraisals, enhanced monitoring and evaluation system, and improved linkages. The findings provide valuable guidance for KALRO&amp;apos;s leadership amid competing priorities and budgetary constraints.

Singular effect of linkage on long-term genetic gain in Fisher's infinitesimal model.

During the founding of the field of quantitative genetics, Fisher formulated in 1918 his "infinitesimal model" that provided a novel mathematical framework to describe the Mendelian transmission of quantitative traits. If the infinitely many genes in that model are assumed to segregate independently during reproduction, corresponding to having no linkage, directional selection asymptotically leads to a constant genetic gain at each generation. In reality, genes are subject to strong linkage because they lie on chromosomes and thus segregate in a correlated way. Various approximations have been used in the past to study that more realistic case of the infinitesimal model with the expectation that the asymptotic gain per generation is modestly decreased. To treat this system even in the strong linkage limit, we take the genes to lie on continuous chromosomes. Surprisingly, the consequences of genetic linkage are in fact rather singular, changing the nature of the long-term gain per generation: the asymptotic gain vanishes rather than being simply decreased. Nevertheless, the per-generation gain tends to zero sufficiently slowly for the total gain, accumulated over generations, to be unbounded.

Exploring the Linkage Effects between Coking Coal Futures and Carbon Emission Rights Prices under the Dual-Carbon Framework

Coking coal is a vital energy resource for economic development, with fluctuations in coking coal futures prices significantly guiding spot prices. Additionally, variations in carbon emission rights prices directly affect China&amp;#39;s energy conservation and emission reduction efforts. This paper examines the daily trading prices of carbon emission rights and coking coal futures. It utilizes various tests, including the ADF test and cointegration test, and constructs a two-dimensional vector autoregression (VAR) model with a two-period lag. The paper also performs an impulse response function analysis and variance decomposition. Empirical results reveal: First, the daily trading prices of coking coal futures have exhibited a fluctuating upward trend over the past six years; Second, there is a long-term cointegration relationship between coking coal futures prices and carbon emission rights prices; Third, there is no Granger causality between the two; Fourth, fluctuations in carbon emission rights prices have a stronger guiding effect on coking coal futures prices than vice versa. Recommendations include: (1) Strengthening oversight of the coking coal futures market and leveraging policy guidance to prevent extreme prices; (2) Systematically including more participants in the carbon market, optimizing the trading structure, and promoting healthy market development; (3) When developing policies for carbon emission rights, the government should mitigate the impact of price fluctuations on other sectors.

The Impact of E-sports Event on Urban Economic Development: A Case Study of the Hangzhou Asian Game

With the continuous development of society, the importance of urban economy has become particularly important. At the same time, sports events have also become an important way to enhance the competitiveness of cities and realize the government's improvement of urban economy. this article takes Hangzhou as a representative to conduct corresponding research and analysis. It is found that the Hangzhou urban government has issued relevant policies for sports events to drive the city's economy in order to better organize events, in order to promote the linkage between event preparation and urban development. This article is based on the perspectives of public management, economics, sports and other disciplines, and comprehensively uses research methods such as literature review and case analysis to study the empowerment of urban economic development by the Hangzhou Asian Games e-sports project. This paper mainly explores three aspects: first, how international events promote urban economy, second, how events promote urban infrastructure construction, and finally, how electronic competitions promote urban economic development. Through the research results, it has been found that as the influence and scale of the e-sports industry gradually increase, the proportion and linkage effect of the industry continue to increase. The development of the e-sports industry-enabled city is also full of uncertainties. On the other hand, from the perspective of driving urban economic development through the e-sports industry, it is proposed to strengthen the development foundation of the e-sports industry, improve the development system of the e-sports industry, and expand the implementation path of the e-sports industry development direction.

A novel green learning artificial intelligence model for regional electrical load prediction

Load prediction is crucial to unit commitment and scheduling in electricity systems; however, load prediction models consume considerable electricity. Most conventional prediction methods are based on deep learning (DL) models, such as long short-term memory and gated recurrent units. The nonlinear activation functions and backpropagation mechanisms used in these methods result in high computational complexity and correspondingly high energy consumption. This paper proposes a prediction model based on a green learning (GL) framework aimed at reducing energy consumption. The proposed GL model replaces the activation functions conventionally used for feature extraction with a hybrid scheme combining categorical and numerical features, such as seasonal climate features and multi-autoregression terms. The proposed GL model also eliminates the backpropagation methods used to optimize hyperparameters by employing seasonal centroids and the quantile auto-regression forest algorithm for classification/regression. In a case study, the proposed GL model significantly outperformed conventional DL models in terms of energy consumption without compromising accuracy. The energy savings of the proposed GL model are equivalent to the annual electricity consumption of 211 ∼ 565 households, increasing with model penetration. This paper demonstrates the importance of energy-saving models in mitigating the linkage effect of industrial carbon emissions. It also explores policy implications for the implementation of GL models.

Trade policy uncertainty and capacity utilisation rate: Firm‐level evidence from China's WTO accession

AbstractThis paper was one of the first to explore the impact of trade policy uncertainty (TPU) reduction on Chinese firm capacity utilisation rate from the perspective of trade policy variation. Based on a quasi‐natural experiment of the implementation of Permanent Normal Trade Relation (PNTR) after China's WTO accession, this paper adopts the difference‐in‐difference (DID) method to conduct empirical analysis, and finds that reduction in TPU significantly raises firm capacity utilisation rate. The mechanism tests show that export expansion is an important channel through which reduction in TPU raises firm capacity utilisation rate, especially for firms exporting to the United States; reduction in TPU also raises firm capacity utilisation rate through the improvement of production efficiency; in addition, reduction in TPU raises firm capacity utilisation rate along the downstream linkages, whereas the effect of the upstream linkages is insignificant. Finally, this paper takes a step further to conduct empirical analysis at industry level, the results show that reduction in TPU also significantly raises manufacturing aggregate capacity utilisation rate, and the improvement of resource reallocation efficiency (especially the exit of the firms with backward production capacity) plays an important role. Our study was helpful to understand the driving forces of the changes in Chinese manufacturing capacity utilisation rate in recent years, and it also provides new ideas for solving over‐capacity.

Coupling Study of Green Finance and High-Quality Economic Development

Based on panel data from 16 prefecture-level cities in Shandong Province from 2012 to 2021, a comprehensive evaluation system for the development of green finance and high-quality economic development in Shandong Province was constructed. The entropy weight method was used to calculate the comprehensive index of both. The research shows that, temporally, from 2012 to 2021, the coupling degree between green finance development and high-quality economic development in the prefecture-level cities of Shandong Province was mostly at a high or relatively high level, with the coordination degree increasing year by year. However, the overall level remained low, with most cities in a state of mild or near imbalance. Spatially, only coastal cities such as Qingdao, Dongying, Weihai, and Rizhao achieved basic coordination, with the coordination degree of coastal cities being higher than that of inland cities. Among them, coastal cities mainly exhibited high-high or high-low types, while inland areas mostly showed low-low types, failing to form a good linkage effect.

Investigating the effectiveness of web-based HIV self-test distribution and linkage to HIV treatment and PrEP among groups at elevated risk of HIV in Viet Nam provinces: a mixed-methods analysis of implementation from pilot to scale-up.

In Viet Nam, key populations (KPs) face barriers accessing HIV services. Virtual platforms can be leveraged to increase access for KPs, including for HIV self-testing (HIVST). This study compares reach and effectiveness of a web-based HIVST intervention from pilot to scale-up in Viet Nam. A mixed-methods explanatory sequential design used cross-sectional and thematic analysis. The pilot launched in Can Tho in November 2020, followed by Hanoi and Nghe An in April 2021. Scale-up included Can Tho and Nghe An, with 21 novel provinces from April to December 2022. After risk assessment, participants registered on the website, receiving HIVST (OraQuick®) by courier, peer educator or self-pick-up. Test result reporting and completing satisfaction surveys were encouraged. Intervention reach was measured through numbers accessing the testing, disaggregated by demographics, and proportion of individuals reporting self-testing post-registration. Effectiveness was measured through numbers reporting self-test results, testing positive and linking to care, and testing negative and using HIVST to manage pre-exposure prophylaxis (PrEP) use. Thematic content analysis of free-text responses from the satisfaction survey synthesized quantitative outcomes. In total, 17,589 participants registered on the HIVST website; 11,332 individuals ordered 13,334 tests. Participants were generally young, aged <25 years (4309/11,332, 38.0%), male (9418/11,332, 83.1%) and men who have sex with men (6437/11,332, 56.8%). Nearly half were first-time testers (5069/11,332, 44.9%). Scale-up participants were two times more likely to be assigned female at birth (scale-up; 1595/8436, 18.9% compared to pilot; 392/3727, 10.5%, p < 0.001). Fewer test results were reported in scale-up compared with pilot (pilot: 3129/4140, 75.6%, scale-up: 5811/9194, 63.2%, p < 0.001). 6.3% of all tests were reactive (pilot: 176/3129, 5.6% reactive compared to scale-up: 385/5811, 6.6% reactive, p = 0.063); of which most linked to care (509/522, 97.5%). One-fifth of participants with a negative test initiated or continued PrEP (pilot; 19.8%, scale-up; 18.5%, p = 0.124). Thematic analysis suggested that community delivery models increased programmatic reach. Live chat may also be a suitable proxy for staff support to increase result reporting. Web-based self-testing in Viet Nam reached people at elevated risk of HIV, facilitating uptake of anti-retroviral treatment and direct linkage to PrEP initiations. Further innovations such as the use of social-network testing services and incorporating features powered by artificial intelligence could increase the effectiveness and efficiency of the approach.