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The purpose of this paper is to predict bibliometric indicators based on ARIMA models and to study the short-term trends of bibliometric indicators.

This paper establishes a non-stationary time series ARIMA (p, d, q) model for forecasting based on the bibliometric index data of 13 journals in the library intelligence category selected from the Chinese Social Sciences Citation Index (CSSCI) as the data source database for the period 1998–2018, and uses ACF and PACF methods for parameter estimation to predict the development trend of the bibliometric index in the next 5 years. The predicted model was also subjected to error analysis.

ARIMA models are feasible for predicting bibliometric indicators. The model predicted the trend of the four bibliometric indicators in the next 5 years, in which the number of publications showed a decreasing trend and the H-value, average citations and citations showed an increasing trend. Error analysis of the model data showed that the average absolute percentage error of the four bibliometric indicators was within 5%, indicating that the model predicted well.

This study has some limitations. 13 Chinese journals were selected in the field of Library and Information Science as the research objects. However, the scope of research based on bibliometric indicators of Chinese journals is relatively small and cannot represent the evolution trend of the entire discipline. Therefore, in the future, the authors will select different fields and different sources for further research.

This study predicts the trend changes of bibliometric indicators in the next 5 years to understand the trend of bibliometric indicators, which is beneficial for further in-depth research. At the same time, it provides a new and effective method for predicting bibliometric indicators.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.

Given the inevitable transition to renewable resource utilization and the urgent need to reduce carbon emissions, this study conducted quasi natural experiments to assess the impact of renewable resource utilization on carbon emissions based on the national “urban mining” demonstration bases (NUMDB).

This study uses panel data from 275 prefecture-level cities in China from 2006 to 2019. The paper selects NUMDB as the proxy variable and conducts a quasi-natural experiment using a multi-period differences-in-differences model. We examine the impact of NUMDB on reducing carbon emissions, and then deeply explore its mechanism and spatial spillover effect.

This study found that: (1) the construction of NUMDB can significantly decrease the carbon emission in the host cities; (2) NUMDB’s construction has more significantly reduced the carbon emission in regions with higher levels of circular economy development, green technology innovation, regional environmental pollution, digital economy development and financial development; (3) by means of green technology innovation, optimized energy structure, and high-quality talent aggregation, NUMDB reduces urban carbon emissions; (4) NUMDB construction positively affects the carbon reduction efficiency of neighboring regions.

We propose corresponding policy suggestions to further promote the carbon emission reduction effect of NUMDB and develop the renewable resources industry in China based on the research findings.

The contributions of this paper are as follows. Our study contributes to expanding the research scope on the environmental impact of the renewable resource industry, as there are few quantitative studies in this area.

We further consider the spatial heterogeneity of policies and analyze the carbon reduction effect of the NUMDB from the city level, which is beneficial to exploring more targeted and operable carbon reduction paths.

This study on identifying the causal relationship between renewable resource utilization and carbon emission reduction helps to explore the sustainable development path of renewable resource more comprehensively. Meanwhile, this paper provides a reference for other countries to improve the utilization of renewable resource and effectively reduce carbon emissions.

This study aims to enhance the bioavailability and antioxidant function of vitamin E (VE) by combining it with inositol and choline, exploring their synergistic effects and underlying mechanisms.

An oxidative stress model in mouse hepatocytes was established using hydrogen peroxide to assess the antioxidant effects of combined VE, inositol and choline treatments. Cell viability, the levels of reactive oxygen species (ROS) and malondialdehyde (MDA) and antioxidant enzymes, including superoxide dismutase (SOD) and catalase (CAT), were measured to evaluate protective effects. α-Tocopherol (α-T) and α-tocopherol transfer protein (α-TTP) levels were assessed to determine VE bioavailability. Transcriptome sequencing was conducted to identify gene expression changes and pathways impacted by the treatment.

An optimal oxidative stress model was established with 641 µM hydrogen peroxide for 6 h. The combination of 20 µM VE, 1.5 mM inositol and 0.3 mM choline significantly improved cell viability, reduced ROS and MDA levels and increased SOD and CAT activities, indicating enhanced antioxidant protection. In addition, α-T and α-TTP levels were higher with this combination, suggesting improved VE bioavailability. Transcriptome analysis revealed that the treatment modulated key pathways linked to inflammation, cancer and lipid metabolism, particularly impacting interleukin-17 and nuclear factor kappa-light-chain-enhancer of activated B cells signaling, cytokine interactions and the alcoholic liver disease pathway.

This study demonstrates a novel approach for improving VE’s bioavailability and effectiveness through its combination with inositol and choline, providing insights that could inform antioxidant therapies and liver health interventions.

This study aims to investigate the most effective approach for governments and enterprises to combat desertification by considering the governance cycle. The focus is on understanding how the government can incentivize enterprises to actively engage in desertification combat efforts.

Both the government and the enterprise are treated as rational entities, making strategic choices for joint participation in combating desertification. Recognizing the dynamic nature of the desertification combat area, differential game models are employed to identify the optimal mode for combating desertification.

The findings underscore the significant influence of the governance cycle duration on the selection of desertification combat modes for government and enterprise. A cooperative mode is best suited to a short governance cycle, while an ecological subsidy mode is optimal for a longer cycle. Enhancing governance technology and shortening the governance cycle are conducive to combating desertification. Reducing taxes alone may not be an effective control strategy; rather, the government can better motivate enterprises by adopting tax rate policies aligned with the chosen governance mode.

This research contributes by elucidating the impact mechanism of the government cycle’s length on the desertification combat process. The results may offer valuable insights for governments in formulating strategies to encourage corporate participation in combating desertification and provide theoretical support for selecting optimal desertification combat modes.

Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai.

Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions.

Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD.

In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.

Some papers have investigated the complex factors impacting building information modeling (BIM) application in prefabricated buildings (PBs), but few paid attention to their interaction relationships. Ignoring the fact that different factors are not isolated may lead to some key factors being overlooked without appropriate improvement strategies being proposed. This paper aims to analyze those factors and their inter-relationships, with the view to identify the critical factors and their interaction relationships so as to derive constructive strategies that would effectively facilitate BIM adoption in Chinese prefabrication.

First, factors influencing BIM application in prefabrication are extracted and collated by literature review, expert interview and analysis of PBs characteristics. Thereafter, an evaluation laboratory (decision-making trial and evaluation laboratory) and interpretive structural modeling are used to explore the relationships and hierarchy among the factors. Based on the degree of cause and centrality, critical factors are extracted and the interaction relationship are investigated.

The results show that BIM policies and standards for PBs are the main causal factors. The maturity of BIM software and BIM data interface for PBs, willingness to share data, the strategic goals of the enterprise, BIM law and BIM input and benefit are the main transitional factors while BIM staff and workflow, enterprise attitude, distribution of BIM liability and cooperation of participants are the main direct factors.

Based on the above findings, corresponding improvement strategies are proposed so as to promote BIM application in prefabrication and the rapid development of China’s PBs efficiently.

The purpose of this paper is to examine the direct and indirect effects of demographic factors on employee compensation, job satisfaction and organizational commitment in private higher educational institutes in Bangladesh. Specifically, how do compensation structure and job satisfaction mediate in the link between demographic factors and organizational commitment? To answer this question, a theoretical framework using the theory of employee retention provided by Martin and Kaufman, as its basis was established.

Data (n = 515) were collected from faculty members of the private universities in Bangladesh. Structural equation modeling was used to analyze the data.

Findings indicate that though demographic factors have no direct impact on organizational commitment, they have indirect impacts on organizational commitment through the mediation of compensation structure and faculty job satisfaction. Besides, compensation structure also has a significant mediating role in the link between demographic structure and faculty job satisfaction.

One possible drawback is the number of private universities from which the data were collected. In the sample used here, only 20 private universities were selected to conduct the survey. Besides, the study could not include public universities that are also a significant part and parcel of higher education in the country. So, if more private and public universities were taken into consideration to collect the data, the results might be improved. Thus, the usual cautions about overgeneralizing findings from this sample, to populations for which it is not strictly representative, apply.

From a practical perspective, as a cumulative body of work on organizational commitment, we will be better able to advise policymakers and educators on the elements they need to address to increase the longer engagement of the faculty members in their institutes. In this study, the one area of findings that may help policymakers and educators the most concerns compensation package that affects job satisfaction and organizational commitment. We found that demographic factors and compensation packages are the most important factors for the faculty members to impact on organizational commitment in this study.

The social implication is that policymakers of the private universities can focus on fair justice in terms of demographic factors and compensation package for job satisfaction, motivation and organizational commitment of the faculty members in their universities.

The findings of the study are important for the policymakers of the higher education institutes.

The transition from high school to university poses many challenges for university students including dietary behaviors’ change and subsequent obesity risk. More tailored interventions and promotions to establish a healthier eating habit are needed to reduce obesity risks. The purpose of this paper is to investigate food intake differences on obesity risk among university students in China through exploring the differences of food intakes with gender, the year in college and body mass index (BMI).

Cross-sectional study was carried in five universities which were randomly selected in all the universities located in different geographical areas of Beijing, China. The sample consisted of 631 university students whom aged from 18 to 25 years. t-tests and one-way ANOVA tests were used to find differences of food intakes with gender, the year in college and BMI.

Having more consumption of food with high protein, high fat and high sugar, but less consumption of fruits and vegetables, may give university students a greater chance to be obese, and food intakes were significantly varied in different genders among Chinese university students.

There is a lack of evidence for investigating the differences of food intakes with gender on obesity among young adults in China. Findings of this study indicated that the food intakes of male students might make them more prone to obesity than female students, and suggested more tailored interventions, food marketing strategies and promotions on controlling students’ food intakes for a healthier life are needed.