This research aimed to explore the concerning characteristics of information literacy in the physical education faculty of higher education institutions in Yunnan Province. This study provides a systematic meta-analysis of 33 peer-reviewed papers from 2019 to 2023. It discusses that information literacy includes basic research skills, critical thinking, and problem-solving, which include their application in the learning process. The paper describes some approaches that can be used to implement information literacy into teaching and learning, including courses with learning objectives, learner-centered approaches, and institutional support. The study also explored technology and its relation to adopting competencies for the growing technologies’ evolution within the region’s education sector. In addition, the following factors could have enhanced the process: time constraints, differences in discipline, and variations in the usage of information technology. The results indicate the need for context-specific professional learning and policy intervention to facilitate the practice of physical education faculty in Yunnan. The information collected here serves as the framework for effective regional policies regarding education, curriculum, and teacher training, among other related aspects.

This study aimed to examine the impact of working conditions and sociopsychological factors on job satisfaction among office workers. Using data from the 2017–2018 Working Conditions Survey, exploring how workplace conditions and sociopsychological elements could impact job satisfaction. This study examined data from 9801 workers to explore the effects of working conditions and psychosocial environments on job enthusiasm, which subsequently impacts job satisfaction. Analyzing 1416 office workers, it found that fewer working hours, better work-life balance, improved work conditions, and lower depression levels enhance job enthusiasm, significantly affecting job satisfaction. The work environment had the most substantial impact, encompassing relationships with colleagues, task completion time, and confidence. Work-life imbalance and depression were also significant, with work-life balance being crucial for modern society, especially the younger generation. Poor working conditions and unstable psychosocial environments negatively affect job enthusiasm and satisfaction, with findings supporting previous research on job stress and turnover intentions in various industries. This study highlights the need for organizational policies that support these aspects to improve overall employee well-being and productivity.

Business model innovation (BMI) has garnered substantial academic and corporate attention in recent decades. Researchers have not yet agreed on the most complicated BMI practices in the high-tech startups (HTS). Despite being the second-biggest economy in the world today, China has done little research on the practice of business model innovation in China’s high-tech startups. This study addresses the factors that impact the business model innovation of high-tech startups in China. Our study aims to fill the research gap by visualising and analysing, using systematic literature review (SLR) analyses and reviewing 36 in-depth articles, from 688 academic literature sources. Relevant publications from Scopus, Springer, ScienceDirect, Web of Science, IEEE Xplore, and the JDM e-library expose the current research status from 2013 to December 2023 without bias. We conducted a literature-based investigation to identify essential insights on the BMI factors in the literature and derived a high-tech startup’s BMI critical factor. Our study shows that three main factors affect the innovation of business models in high-tech startups in China. The findings raise managers’, entrepreneurs’, and executives’ knowledge of corporate resource bricolage and cognitive style constraints in business model innovation and their pros and cons. The findings will help Chinese academics understand enterprises’ institutional environment and resource bricolage as final suggestions and proposals for corporates, regulators, and policymakers are presented.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.