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The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

In this study, the author intend to investigate the impacts of renewable energy use and environmental taxation on sustainable development measured by the adjusted net savings (ANS).

This study employs the quantile regression (QR) for a set of 24 Organization for Cooperation and Economic Development (OECD) countries over the period 1994–2018.

The main empirical findings of estimates show that access to renewable energy and environmental taxation generate positive and significant effects in increasing the ANS for most quantiles. Hence, they are practical tools for achieving sustainable development goals (SDGs).

This study has important implications for governments and policymakers of the OECD countries. Therefore, governments can use subsidies and incentives to promote the adoption of renewable energy sources, energy-efficient technologies and sustainable practices. Similarly, by imposing taxes on pollution and resource use, governments can encourage the adoption of cleaner technologies and practices toward more sustainable behavior.

This paper is based on a novel measure of sustainable development (ANS) and a novel econometric method (QR).

Traditional payment systems based on cash and bank cards are being replaced by new innovative formats. This research analyzes the success factors in the adoption by customers of Bizum, a peer-to-peer (P2P) mobile payment system widely used in Spain. This study proposes a theoretical framework based on the Stimulus–Organism–Response (S-O-R) model and includes the analysis of the moderating effect of perceived risk and the mediating effect of perceived trust.

To achieve the proposed objectives, an online questionnaire was administered to 701 Spanish smartphone users, potential users of the proposed P2P payment systems.

The results show that perceived usefulness is the most important predictor of intention to use. Additionally, a medium predictive relevance performance of the proposed model is found.

This research contributes to a more holistic understanding of the adoption of P2P payment systems and provides new business opportunities that companies can exploit through the use of this technology.

以現金和銀行卡為基礎的傳統支付系統、正被嶄新而又富創意的模式取代。本研究擬分析驅使消費者使用Bizum的成功因素 (Bizum 是一個在西班牙得到廣泛使用的P2P移動支付系統) 。本研究以刺激-有機體-反應模型為基礎, 建議了一個概念框架;研究亦擬分析感知風險的調節作用, 以及感知信任的中介效應。

為達研究目標, 研究人員處理了701名西班牙智慧型手機使用者回答的網上問卷, 這些使用者是本研究提出的P2P支付系統的潛在用戶。

研究結果顯示、感知有用性是消費者會否使用P2P支付系統最重要的預測因素。研究結果亦顯示、本研究建議的概念框架的預測能力水平屬中等。

本研究使我們對驅使消費者使用P2P支付系統的因素更全面地了解;研究也使企業可透過使用這技術, 為自己創造新的商機。

The forest products processing industry is a key component of the forestry economy, and the level of companies’ operating efficiency directly affects its profitability and market competitiveness.

In order to deeply study the operation status of forest product processing industry, this paper takes the panel data of 70 listed forest product processing companies from 2015 to 2022 as the basis, and adopts BBC, CCR and DEA-Malmquist models to measure the operating efficiency of these companies. Meanwhile, the Tobit model is applied to deeply explore the impact of innovation input on operating efficiency.

The results of the paper show that: (1) the overall operating efficiency of listed forest product processing companies performs well, and the improvement of technology level promotes the growth of total factor productivity; (2) innovation input plays a significant positive role in listed forest product processing companies, which positively affects the operating efficiency.

A scientific and reasonable evaluation of the operating efficiency of listed forest product companies is of great practical significance to the development of the forestry industry The study of forest product processing industry is of key significance to the social economy.

This paper explores the improvement of production and operation efficiency of forest products processing enterprises for the purpose of in-depth analysis of the current situation of China's forest products processing enterprises, which is conducive to improving the innovation and operation efficiency of China's forest products processing enterprises, and realizing the high-quality development of China's forest products processing industry.

Blood lipid and lipoprotein abnormalities are common among patients with diabetes. The study aimed to assess dietary fat intake and its association with blood lipids among patients with Type 2 diabetes mellitus (T2DM) considering sex differences.

A cross-sectional observational study was conducted with patients (207 males and 197 females) with T2DM. The daily food intake and its contents of fat and fat types were assessed through face-to-face interview. Anthropometric measurements, glycated hemoglobin (HbA1c), triglyceride, total cholesterol (TC), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol were initially recorded.

The results revealed that TC, LDL and HDL cholesterol levels were significantly higher in females than in males. However, the TC: HDL ratio was significantly higher in males than in females. The results also showed that the daily intake of saturated fatty acid (SFA) slightly exceeded the daily recommended allowance. However, the monounsaturated fatty acid + polyunsaturated fatty acid/SFA (MUFA + PUFA/SFA) ratio was within the recommended ratio. In addition, this study found that the main sources of SFA and cholesterol intake were milk and milk products. A significant association between high fat intake and HbA1c levels was observed (r = 0.234, p < 0.001).

As it is a cross-sectional observational study, this study has the natural limitation where it can only demonstrate an association.

The types of dietary fat intake may contribute to blood lipid abnormalities and differences effects may exist among male and female. Studies on the effect of daily fat intake and its types on blood lipids in patients with diabetes, in particular Saudi patients with diabetes are limited. This study focused on the amount and type of the consumed fat among male and female Saudi patients with T2DM and studied the relationship between the type of consumed fat and blood lipid profiles.

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

Understanding China's carbon dioxide (CO2) emission status is crucial for getting Carbon Neutrality status. The purpose of the paper is to calculate two possible scenarios for CO2 emission distribution and calculated input-output flows of CO2 emissions for every 31 China provinces for 2012, 2015 and 2017 years.

In this study using the input and output (IO) table's data for the selected years, the authors found the volume of CO2 emissions per one Yuan of revenue for the industry in 2012 and the coefficient of emission reduction compared to 2012.

Results show that in the industries with a huge volume of CO2 emissions, such as “Mining and washing of coal”, the authors cannot observe the reduction processes for years. Industries where emissions are being reduced are “Processing of petroleum, coking, nuclear fuel”, “Production and distribution of electric power and heat power”, “Agriculture, Forestry, Animal Husbandry and Fishery”. For the “construction” industry the situation with emissions did not change.

“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of CO2 emissions, but they do not take products characterized by significant emissions from other provinces. Shandong produces a lot of emissions and consumes many of products characterized by large emissions from other provinces. However, Shandong showed a reduction in CO2 emissions from 2012 to 2017.

Many researchers partner with schools but may be unfamiliar with practices for initiating contact and sustaining relationships with school leaders. Partnering with schools requires significant effort from the researcher to nurture communication and trust. This can pose challenges for researchers who are new to the field, have relocated to a new university or need to rebuild relationships due to transitions in school staffing.

In this mixed-methods study, we interviewed and surveyed school and district leaders in Delaware to learn how researchers can best communicate and form relationships with schools and districts.

We found no singular best method exists to initiate contact with schools and districts. Rather, researchers should consider the unique needs of the local context. Leaders’ decision to participate in research was most influenced by their own interest in the research topic, alignment with schools’ needs and researchers’ willingness to build a relationship with the local education agency.

Despite broad acknowledgment about the importance of school–university partnerships, few studies directly engage educators in discussing their goals, preferences and needs when working with researchers. We sought to formalize an understanding of best practices researchers can consider when initiating contact and building relationships with schools, directly from the perspective of school and district leaders. Developing these understandings from practitioners ensures the information authentically represents the perspectives of those who researchers seek to connect with, rather than assumptions of the researcher.

Mouth segmentation is one of the challenging tasks of development in lip reading applications due to illumination, low chromatic contrast and complex mouth appearance. Recently, deep learning methods effectively solved mouth segmentation problems with state-of-the-art performances. This study presents a modified Mobile DeepLabV3 based technique with a comprehensive evaluation based on mouth datasets.

This paper presents a novel approach to mouth segmentation by Mobile DeepLabV3 technique with integrating decode and auxiliary heads. Extensive data augmentation, online hard example mining (OHEM) and transfer learning have been applied. CelebAMask-HQ and the mouth dataset from 15 healthy subjects in the department of rehabilitation medicine, Ramathibodi hospital, are used in validation for mouth segmentation performance.

Extensive data augmentation, OHEM and transfer learning had been performed in this study. This technique achieved better performance on CelebAMask-HQ than existing segmentation techniques with a mean Jaccard similarity coefficient (JSC), mean classification accuracy and mean Dice similarity coefficient (DSC) of 0.8640, 93.34% and 0.9267, respectively. This technique also achieved better performance on the mouth dataset with a mean JSC, mean classification accuracy and mean DSC of 0.8834, 94.87% and 0.9367, respectively. The proposed technique achieved inference time usage per image of 48.12 ms.

The modified Mobile DeepLabV3 technique was developed with extensive data augmentation, OHEM and transfer learning. This technique gained better mouth segmentation performance than existing techniques. This makes it suitable for implementation in further lip-reading applications.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.