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Internet of Things (IoT), a strategic emerging industry, has brought a new driving force to the global economic growth, as well as an effective solution to break the barrier of economic development. However, standards system of IoT is not yet mature, existing obvious overlapping and even conflicting standards, and enterprises lack mature technology standardization model, which severely restricts the structural upgrading and development of IoT. The paper aims to discuss these issues.

In this regard, this study combs the research context of the IoT, technology standardization and competition behavior, and analyze technology standardization models of IoT by combining theory with practice. Using game theory and profit function, this paper analyzes the selection mechanism of standardization model of IoT enterprises, and explores practical application of these models using competitive behavior theory.

First, in the process of standardization, technology standardization model n enterprises is not single, nor is it immutable. Second, the trend of internationalization of technical standards is becoming more and more obvious. Third, if LoT enterprises want to achieve their own technology standardization, the corresponding competitive behavior is essential. Fourth, with the change of innovation capability and market forces, the competitive behavior of enterprises should be improved accordingly to better adapt to the changes of internal and external environment and ensure the realization of the standardization of enterprises. Fifth, if IoT attempts to achieve the same globalization as the internet, there must be a set of support systems.

Finally, some suggestions are given for the future development in the field of IoT. This study will provide some theoretical support for promoting the development of standards and enhancing the competitiveness of IoT enterprises.

Thermal protection of a flange is critical for preventing tower icing and collapse of wind turbines (WTs) in extremely cold weather. This study aims to develop a novel thermal protection system for the WTs flanges using an electrical heat-tracing element.

A three-dimensional model and the Poly-Hexacore mesh structure are used, and the fluid-solid coupling method was validated and then deployed to analyze the heat transfer and convection process. Intra-volumetric heat sources are applied to represent the heat generated by the heating element, and the dynamic boundary conditions are considered. The steady temperature and temperature uniformity of the flange are the assessment criteria for the thermal protection performance of the heating element.

Enlarging the heating area and increasing the heating power improved the flange's temperature and temperature uniformity. A heating power of 4.9 kW was suitable for engineering applications with the lowest temperature nonuniformity. Compared with continuous heating, the increased temperature nonuniformity was buffered, and the electrical power consumption was reduced by half using pulse heating. Pulse heating time intervals of 1, 3 and 4 h were determined for the spring, autumn and winter, respectively.

The originality of this study is to propose a novel electrical heat-tracing thermal protection system for the WTs flanges. The effect of different arrangements, heating powers and heating strategies was studied, by which the theoretical basis is provided for a stable and long-term utilization of the WT flange.

Unsteady simulation of forced convection of two heated horizontal cylinders confined in a 2D squared enclosure. The paper aims to discuss this issue.

The finite-volume method is used to solve the transient heat transfer problem by employing quadrilateral mesh type. To solve the governing equations (conservations of mass, momentum and energy) on unstructured control volumes, a second-order quadratic upwind interpolation of convective kinematics scheme for the convection terms and the semi-implicit method for pressure-linked equations pressure correction algorithm were used.

The results indicate that the variation of the area-averaged Nusselt number strongly depends on the Reynolds number. On the contrary, the effect of cylinders’ space on heat transfer was found to be nearly negligible for Re < 460. It is also observed that steady state flow and heat transfer shift to periodical oscillation, and ultimately chaotic oscillation in non-dimensional cylinders distance of 0.1; however the sequence of appearing this route is completely different for higher cylinder spaces.

Reynolds numbers between 380 and 550 and dimensionless horizontal distances of cylinders 0.1, 0.2 and 0.3.

Comprehensive knowledge of the effect of tube arrays flow regime on each other and in turn, heat transfer among them. Better understanding of convective heat transfer around an array of horizontal cylinders compared with from those around a single cylinder because of the mutual interaction of the buoyant plumes generated by the cylinders. Time-dependent phenomena of the problem including periodical oscillation or chaotic features.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

This paper aims to explore the key risk factors affecting the Personnel Localization Management of international construction projects under the major public emergencies represented by the novel coronavirus pneumonia pandemic (hereinafter COVID-19) and how the public emergency affected the Personnel Localization Management from three levels: staff turnover rate, the number of different personnel, the salary and performance of workers. The paper also helps to enhance the construction enterprises' response capacity of major public emergencies and provides a comprehensive framework of optimization strategies for the Personnel Localization Management of international construction projects (hereinafter projects).

The main research method of this paper is the case study, and ten representative international construction projects are selected for case study in China construction enterprises (hereinafter CCE). And this study used the failure mode and effects analysis (FMEA) and comparative analysis to find out all potential risk factors under the COVID-19 and analyze how the epidemic affects the Personnel Localization Management of projects which based on the primary data from 10 projects obtained through in-depth interviews and the secondary data from China First Metallurgical Group and Central South Construction Group's Overseas Enterprise.

The findings show that the outbreak of the major public emergencies not only greatly increased eight risk factors but also directly led to an increase in staff turnover rate. Meanwhile, the numbers of Chinese and local managers and workers are all affected, and an increase in the number and the salary performance of local workers can be reduced, to a certain extent, to the cost-to-output ratio of the projects. The findings would help construction enterprises better cope with Personnel Localization Management and enhance the response capacity of major public emergencies.

This study will broaden researchers' horizons regarding “Personnel Localization Management under major public emergencies” and “risk factors of Personnel Localization Management in an international context.” Furthermore, construction enterprises looking for a better mechanism of Personnel Localization Management can benefit from research findings and lessons learned from the authors' case study during or before an outbreak of major public emergency. Lastly, the framework of optimization strategies for Personnel Localization Management can be used both for research purposes and practice issues in international construction projects.

The findings from the authors' case study offer the direction for international construction enterprises in China and other countries to formulate effective measures, strengthen overseas business and establish a crisis management mechanism for Personnel Localization Management under major public emergencies, and the findings provide emergency plans for projects to improve the public crisis handling capacity and respond to major public emergencies such as the COVID-19.

This study analyzes the impact of the COVID-19 on the Personnel Localization Management of international construction projects from the perspective of personnel. This study provides a theoretical reference for the international construction industry to actively respond to major public emergencies. Besides, the research is conducive to improving the emergency response mechanism in the construction industry, and further promoting the high-quality and globalized development of international construction.

This study provides other researchers with a comprehensive understanding of the risk factors affecting the Personnel Localization Management of projects under the COVID-19 and insight for further research on localization management, risk management, and project management.

The performance of the first batch of listed companies since the restart of new initial public offerings (IPOs) in January 2014 and their accounting information face repeated and volatile questioning from different sides. This paper aims to take Guirenniao (China) Co. Ltd. (GRN for short), one of the first batch of listed companies in 2014 that suffered performance decline, as an example to analyze how it managed earnings before IPO.

This paper examines earnings management signs that exist in GRN through analysis of its financial statements compared to those of its industry peers. This paper then uses the modified Jones model to detect its accrual earnings management and build three models, which are abnormal levels of cash flows from operations, abnormal production costs and abnormal discretionary expenses, to detect real earnings management.

This paper finds that GRN managed earnings through accrual and real activities in 2012 and 2013. Finally, this paper provides evidence on the specific methods of earnings management, which are easing credit policy to recognize revenue in advance, abnormal expansion, decreasing costs and connected transactions.

This paper examines earnings management signs exist in GRN through analysis of its financial statements comparing to those of its industry peers. This paper then uses the modified Jones Model to detect its accrual earnings management and build three models which are abnormal levels of cash flows from operations, abnormal production costs and abnormal discretionary expenses to detect real earnings management.

Driven by sustainable production, mobile robots are introduced as a new clean-energy material handling tool for mixed-model assembly lines (MMALs), which reduces energy consumption and lineside inventory of workstations (LSI). Nevertheless, the previous part feeding scheduling method was designed for conventional material handling tools without considering the flexible spatial layout of the robotic mobile fulfillment system (RMFS). To fill this gap, this paper focuses on a greening mobile robot part feeding scheduling problem with Just-In-Time (JIT) considerations, where the layout and number of pods can be adjusted.

A novel hybrid-load pod (HL-pod) and mobile robot are proposed to carry out part feeding tasks between material supermarkets and assembly lines. A bi-objective mixed-integer programming model is formulated to minimize both total energy consumption and LSI, aligning with environmental and sustainable JIT goals. Due to the NP-hard nature of the proposed problem, a chaotic differential evolution algorithm for multi-objective optimization based on iterated local search (CDEMIL) algorithm is presented. The effectiveness of the proposed algorithm is verified by dealing with the HL-pod-based greening part feeding scheduling problem in different problem scales and compared to two benchmark algorithms. Managerial insights analyses are conducted to implement the HL-pod strategy.

The CDEMIL algorithm's ability to produce Pareto fronts for different problem scales confirms its effectiveness and feasibility. Computational results show that the proposed algorithm outperforms the other two compared algorithms regarding solution quality and convergence speed. Additionally, the results indicate that the HL-pod performs better than adopting a single type of pod.

This study proposes an innovative solution to the scheduling problem for efficient JIT part feeding using RMFS and HL-pods in automobile MMALs. It considers both the layout and number of pods, ensuring a sustainable and environmental-friendly approach to production.

This study aims to investigate whether auditors compromise their independence for economically important clients in family business settings.

The authors empirically examine the research question based on China for the years 2011 to 2020. The dependent variable is the auditors’ propensity to issue modified audit opinions, which is a proxy for auditor independence. The authors use relative client audit fees as a proxy for client importance. To address endogeneity issues in the selection of family firms, the authors use the two-stage least squares regression model and, subsequently, the propensity score matching and Hausman firm fixed effect modeling.

This study reveals that the propensity to issue modified audit opinions is positively correlated with client importance. Big-N auditors are more likely to issue modified audit opinions for their economically important family firm clients, whereas such evidence is not found for non-Big-N auditors. Results are consistent and robust to endogeneity test and sensitivity analysis.

This study enriches the literature on auditor independence and the effect of family firms’ ownership structure factors on audit reporting behavior for their economically important clients. Findings may prove useful for managers and practitioners interested in family business.

From an agency perspective, the authors investigate whether family ownership and control configurations are systematically associated with a firm's choice of auditor and audit fees. Agency theory is an economic theory that purposes the existence of a contract between two parties, principals and agents. Auditor choice and audit fees by family firms provide interesting insights given the unique nature of the agency problems faced by such firms.

The authors employ Big-4 auditors (PWC, KPMG, E&Y and Deloitte) as a proxy for high quality auditor (Big N) for the auditor choice model. For the audit fee model, the dependent variable is the natural logarithm of audit fees (LnAF). The authors use two measures for family firm as explanatory variables: (1) a dummy variable (FAM_Control), which equals one if the firm is classified as a family firm and (2) FAM_Ownership, which is an indicator variable with a value of one if a firm has family members who hold CEO position, occupy board seats, or hold at least 10% of the firm's equity. Data of Chinese listed firms from 2011 to 2021 are used. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

The findings suggest that compared with non-family firms, Chinese family firms have a less tendency to employ Big-4 auditors due to less severe agency problems between owners and managers. Additionally, Chinese family firms sustain higher audit fees than non-family firms. Similar to the prior literature, however, Chinese family firms audited by Big-4 auditors incur lower audit fees than family firms audited by non-Big-4 auditors in this study. In contrast to young-family firms, old-family firms are less likely to pick top-tier auditors and sustain lower audit fees. Consistent and robust results are found from endogeneity tests and sensitivity analyses.

The empirical evidence provides a unique insight, for accounting practitioners, policymakers, family owners and other capital market participants concerning the diverse effects of various family ownership and control features on selecting high-quality auditors and audit fees. This study advances the understanding, showing that a lower demand for audit quality occurs in Chinese family firms as they encounter less severe Type I agency problems. However, the more severe Type II agency problems in Chinese family firms sustain higher audit fees due to higher audit risk and greater audit effort.

With the advancement of social economy, science and technology, nowadays, people face increasingly complex decision-making problems and ever-growing decision-associated information contents. Owing to the unique advantages of the evidence theory, evidence decision flow fits in well with the cognitive process of human beings, which provides us with an effective decision method. However, traditional evidence theories are built upon the one-dimensional evidence recognition framework, which merely reflects the reliability of information determined by evidence source and as such may fail to present the characteristic information of evidence source itself or the information required for the process of determining reliability. This greatly influences processes in decision-making, such as evidence processing and combination. This essay aims to propose a two-dimensional evidence-reasoning theory to address specific decision problems.

This article uses a two-dimensional evidence framework to reflect the process and characteristic information of evidence source based on the traditional evidence framework. As a result, evidence is processed and combined by two-dimensional modified information.

This research is of theoretical and practical significance by extending theoretical connotation, fully utilizing precise evidence information and therefore meeting the requirements of efficient and accurate decision-making performances.

The theory adds a two-dimension to modify and capture evidence on the basis of the traditional evidence framework. This proposal has significant theoretical and practical value to expand evidence theory and provides more accurate use of evidence information, higher efficiency and quality requirements and more precise decision-making.