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Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.

A total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.

The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.

This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

The purpose of this paper is to investigate the impact of political instability at the local level on foreign firms in China. Building on the literature on political embeddedness and business power, the authors propose a theoretical framework to explain how political turnover can affect foreign firms’ performance and how they respond to such challenges by leveraging their power bases.

To test the hypotheses, the authors apply fixed effects regression to an unbalanced panel data set comprising 13,360 foreign firms from 1998 to 2013 and the political replacement that involved changes in provincial governors.

The findings confirm that political turnover incidents have a negative impact on the performance of foreign firms in China. However, the authors also found that this negative relationship is weaker for firms that can choose various types of power sources. Specifically, the study reveals that foreign firms with large firm size, government ownership and a strong foreign direct investment community are better qualified to mitigate the negative effects of political instability.

This study contributes to the literature by developing the understanding of how political uncertainties and risks affect the performance of foreign firms in China and the importance of firms’ power in counterbalancing these effects. The research provides valuable insights into how multinational corporations can exploit their power to manage the effects of local political turnover, which has practical implications for the strategy and management of foreign firms operating in China.

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

This paper aims to expand the application area of Inconel 718 alloy in marine environment, the sensitivity of pitting corrosion should be analyzed and discussed, especially the effect of block carbides.

Effect of carbides on the sensitivity of pitting corrosion for Inconel 718 alloy was carried out at 30°C in 3.5% NaCl solution using dynamic electrochemical impedance spectroscopy and anodic polarization techniques. In addition, the initiation of pitting corrosion was investigated by immersion test in 0.05 M HCl + 6% FeCl₃ solution.

As a result, the precipitation of carbides, as the initiation of pitting corrosion, increased pitting corrosion susceptibility, especially the block carbides could lead to deep-spalling. Within that process, temperature and potential acted as the main controlling factors, and the effect of the latter was more distinct.

The initiation of pitting corrosion was revealed by the immersion test. The mechanism of pitting corrosion was analyzed and discussed.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

The purpose of this study is to examine the impact of service quality, perceived usefulness and users’ cognitive satisfaction to determine the third-generation (3G) mobile phone users’ behavioural retention in using 3G telecommunications services.

A total of 243 valid questionnaires were collected from 3G users in the Klang Valley, Malaysia. The combination of partial least squares (PLS) path modelling approach and structural equation modelling (SEM; PLS-SEM) technique was used to analyze the measurement and structural model.

Our empirical assessment supports the proposed research hypotheses and further suggests that service quality is a second-order reflective construct comprising navigation and visual design, management and customer service and system reliability and connection quality.

Prior studies have examined the impact of service quality, perceived usefulness, overall users’ satisfaction and behavioural intention on an information system in general. This study is among the few studies that have attempted to gain insights into 3G users’ post-adoption experience with telecommunications services.

The purpose of this paper is to discuss characteristics of organic food value chain governance and policy tools that can increase the supply of good quality of agri-products.

This paper discusses a national organic food supply system in China, identifying the link between an organization form with a social confidence crisis and information asymmetry as the main challenges. It develops an analytical model of the market structure of organic certification based on the contract theory, which considers the certification incentive driven by both farmers and processors. Two cases of raw milk producers and processors provide empirical data.

The argument which is brought forward is that product information asymmetry together with strict requirement for ensuring organic food integrity brings the organic milk value chain into a highly integrated organization pattern. A tight value chain is effective in the governance of organic food supply chain under third party certification (TPC), while a loose value chain discourages producing organic products because of transaction costs. TPC is found to be a positively correlation with a tight value chain, but it brings high organizational cost and it raises cost for consumers.

This is the first paper discussing the governance of organic food value chain in Chinese milk industry.

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.