Search results

China's stock market, which serves as an example of emerging markets, is steadily maturing in the context of globalization. In order to analyze the pricing mechanism of China's stock market, this paper builds a six-factor model to address the market features that are structurally efficient but not entirely efficient.

This study updates the Fama–French factor model's construction process to account for the unique features of China's stock market before creating a model that incorporates size, volume, value, profitability, and profit-income factors based on institutional investors' trading behavior and research preferences. The SWS three-tier sector stock index's monthly and quarterly data for the years 2016–2021 are used as samples for this study.

The results imply that China's stock market is structurally efficient and exhibits high levels of rationality in the region dominated by institutional investors. Specifically, big-size and high-volume portfolios that perform well in terms of liquidity can receive trading premiums. Growth-style sectors prevail at present, and investing in sectors with strong profitability and reliable financial reporting data can produce better returns.

The research on China's stock market can be extended to improve the understanding of the development process of similar emerging markets, thereby promoting their improvement. To enhance the development of emerging markets, the regulators should attach great importance to the role of local institutional investors in driving the market to maturity. It is crucial to adopt a structured approach to examine the market pricing mechanism throughout the middle stage of the transition from developing to mature markets.

This study offers a structured viewpoint on asset pricing in growing emerging markets by combining the multi-factor pricing model approach with behavioral finance theories.

This study aims to investigate the relationship between all three dimensions of perceived strategic value of m-commerce (operational support, managerial productivity and strategic decision aids), antecedents of m-commerce (organizational readiness, external context and m-commerce competence) and m-commerce adoption. The present study will further examine a mediation model in which all three dimensions of perceived strategic value of m-commerce affect m-commerce adoption through IT investment.

An online survey questionnaire was adopted to test the validity of this research and hypotheses. Data were collected from 178 Chinese family businesses via snowball sampling.

The results show that all three dimensions of perceived strategic value of m-commerce (operational support, managerial productivity and strategic decision aids) are positively connected to m-commerce adoption. Also, it was found that IT investment partially or fully mediates the relationship between all these dimensions of perceived strategic value of m-commerce and m-commerce adoption.

This study would enhance owners' and managers' understanding of the relationship between perceived strategic value of m-commerce, IT investment, antecedents of m-commerce and m-commerce adoption, thus contributing to their future adoption.

The purpose of this paper is to establish the regression model by a simulation method that was obtained by using the system response at unit cost as the response value. The unit availability was maximized, while the unit cost was minimized.

In this study, the Monte Carlo simulation method was used to simulate an operational system, and the regression model was obtained by using response surface methodology with the experimental matrix and different levels of experimental combinations.

The optimal value of mean time between failure (MTBF) and mean time to repair (MTTR) of each component was then obtained by using the system response at unit cost as the response value.

Due to the upgrading of industrial technology and the maturity of electronic technology, product development technology has become highly sophisticated with complex designs. Reliability engineering has become a key procedure of high-tech industry.

Based on the system availability of unit cost as the response value, it can maximize the availability to help decision makers to formulate the best selection strategy components and repair strategy.

Previous works regarding the parameter settings of reliability values never mention the simulation methodology. However, this study aims to achieve the above goals in finding the relationship of MTBF and MTTR simultaneously.

This paper aims to the perspective of stakeholders, from external variables of the Building Information Modeling (BIM) system, users, task flow, the nature of the development of the execution process, organizational structure and policy impacts, that established a relationship among the internal concepts and intentions for the BIM application, individual or organizational differences, controlling interference factors and environmental constraints, discussed the combination of the values and barriers of BIM implementation.

Through the co-occurrence statistics and genre analysis based on co-citation context analysis and constructs the common information that impacts the combination of values and barriers of BIM implementation. Then, the paper chose the expert database of the green construction and intelligent building branch of the China construction association, and obtained 104 sample data through modified snowball sampling, using exploratory factor analysis with factor load linear functions, combined factor variance contribution rate weights.actor variance contribution rate weights.

The results show that eight aspects can be defined as the values of BIM implementation (VI), and the barriers of BIM implementation (BI) mainly come from five aspects caused by insufficient cognition and two aspects of an uncertain value in China.

This research reflects a combined evaluation of the values of BIM implementation and barriers of BIM and highlights the significance of the sustainable development of BIM technology and the value of building future informatization applications.

The purpose of this paper is to examine the mediating role of job characteristics and social exchange in transformational leadership (TFL) and employability relationship.

The sample is composed of 760 participants employed in Yangtze Delta and Pearl River Delta in China. The participants have worked under their line manager for more than one year. In order to better prevent data from possible common method bias, two waves of surveys (in 2014) on a stratified sample, included a mix of industries, such as construction, manufacturing, finance, insurance and communications, were used to investigate the proposed relationship between TFL, job characteristics, social exchange and employability.

The research has empirically tested the relationship between TFL and employability. While previous research has analyzed the relationship between them, the authors have enriched existing literature by exploring the mediating factors and illustrating the importance of indirect effects. Besides the direct effect, the results of this study showed that TFL could also improve employees’ employability through job demands, skill discretion, decision authority, perceived organizational support and team–member exchange, but not leader–member exchange.

The study opens up a debate around the employability of employees as it stands apart from the performance measurement. The authors believe that this new mediating model can provide an insight into complex mechanisms of employability enhancement from the perspective of leader development.

This study aims to investigate the effect of combined use of granular graphite and petroleum coke on the properties of copper-based friction materials and the friction and wear mechanisms.

Copper-based friction materials with different proportions of petroleum coke and granular graphite were prepared by using powder metallurgy. The friction surfaces were analyzed.

Changing the ratio of petroleum coke/granular graphite affects the formation of oxides and sulfides on the surface of the materials. Increasing the petroleum coke promotes the production of metal sulfide and sulfate in the friction materials and reduces coefficient of friction (COF) and wear. Increasing petroleum coke also increases the amount of carbonic oxide (CO) released during the braking process and promotes the reduction process of iron oxide on the friction surface.

The synergistic effect of carbon materials on copper-based friction materials was studied in terms of the tribological chemical reaction. This research provides useful information for the selection of carbon materials in friction materials.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0075/

Open data and data sharing should improve transparency of research. The purpose of this paper is to investigate how different institutional and individual factors affect the data sharing behavior of authors of research articles in sociology and political science.

Desktop research analyzed attributes of sociology and political science journals (n=262) from their websites. A second data set of articles (n=1,011; published 2012-2014) was derived from ten of the main journals (five from each discipline) and stated data sharing was examined. A survey of the authors used the Theory of Planned Behavior to examine motivations, behavioral control, and perceived norms for sharing data. Statistical tests (Spearman’s ρ, χ²) examined correlations and associations.

Although many journals have a data policy for their authors (78 percent in sociology, 44 percent in political science), only around half of the empirical articles stated that the data were available, and for only 37 percent of the articles could the data be accessed. Journals with higher impact factors, those with a stated data policy, and younger journals were more likely to offer data availability. Of the authors surveyed, 446 responded (44 percent). Statistical analysis indicated that authors’ attitudes, reported past behavior, social norms, and perceived behavioral control affected their intentions to share data.

Less than 50 percent of the authors contacted provided responses to the survey. Results indicate that data sharing would improve if journals had explicit data sharing policies but authors also need support from other institutions (their universities, funding councils, and professional associations) to improve data management skills and infrastructures.

This paper builds on previous similar research in sociology and political science and explains some of the barriers to data sharing in social sciences by combining journal policies, published articles, and authors’ responses to a survey.

In this paper, the authors aim to propose an effective method to indirectly determine nonlinear elastic shear stress-strain constitutive relationships for nonlinear elasticity materials, and then study the nonlinear free torsional vibration of Al–1%Si shaft.

In this study the authors use BoxLucas1 model to fit the determined-experimentally nonlinear elastic normal stress–strain constitutive relationship curve of Al–1%Si, a typical case of isotropic nonlinear elasticity materials, and then derive its nonlinear shear stress-strain constitutive relationships based on the fitting constitutive relationships and general equations of plane-stress and plane-strain transformation. Hamilton’s principle is utilized to gain nonlinear governing equation and boundary conditions for free torsional vibration of Al–1%Si shaft. Differential quadrature method and an iterative algorithm are employed to numerically solve the gained equations of motion.

The effect of four variables, namely dimensionless fundamental vibration amplitude ϑmax, radius α and length β, and nonlinear-elasticity intensity factor δ, on frequencies and mode shapes of the shafts is obtained. Numerical results are in good agreement with reference solutions, and show that compared with linearly elastic shear stress-strain constitutive relationships of the shafts made of the nonlinear elasticity materials, its actual nonlinearly elastic shear stress-strain constitutive relationships have smaller torsion frequencies. In addition, but β having opposite hardening effect, the rest of the four variables have softening effect on nonlinearly elastic torsion frequencies. Eventually, taking into account nonlinearly elastic shear stress-strain constitutive relationships, changes of the four factors, i.e. ϑmax, α, β and δ, cause inflation and deflation behaviors of mode shapes in nonlinear free torsional vibration.

The study could provide a reference for indirectly determining nonlinear elastic shear stress-strain constitutive relationships for nonlinear elasticity materials and for structure design of torsional shaft made of nonlinear elasticity materials.

The purpose of this paper is to develop a better understanding of how Sino-Japanese joint ventures implemented the three Japanese improvement methods, i.e. Kaizen, Kaikaku and Kaizen Blitz. The specific objectives of this study are to identify the key enablers for the three improvement methods; and to identify the most selected improvement method.

This study employs a fuzzy analytic hierarchy process to pairwise-compare the three improvement methods. Data are collected from 28 industry experts from Sino-Japanese joint ventures. The study then adopts extent analysis approach for pairwise comparisons and extent analysis to obtain synthetic extent values for priority weights.

The results of the study indicate that personnel (humanware) factor enablers are the most important factor for Kaizen, whilst software factor enablers (essential rules, policies and institutional arrangements) weight second and hardware factor enablers (physical, measurable hard facts or resources) weight last. The study also reviews that Kaizen is the most selected improvement method among the three.

The sample of this study is limited to Sino-Japanese ventures in Guangzhou, China. This study only identifies the key improvement enablers based on interviews with shop floor managers and improvement experts.

Practical implications are threefold: the improvement implementations should be based on factors such as regular training, incentives for motivations and shop floor management; improvement methods are transferable and standard operations may only have small effects on collecting improvement ideas; and Kaizen is the appropriate method to support long-term and process-oriented improvements.

This study is the first to specifically pairwise-compare the three Japanese improvement methods and to identify priorities of their key enablers in Sino-Japanese joint ventures.

Digital healthcare has become one of the most important Internet applications in the recent years, and digital platforms have been acting as interfaces between the patients and physicians. Although these technologies enhance patient convenience, they create new challenges in platform management. For instance, on physician rating websites, information overload negatively influences patients' decision-making in relation to selecting a physician. This scenario calls for an automated mechanism to provide real-time rankings of physicians. Motivated by an online healthcare platform, this study develops a method to deliver physician ranking on platforms by considering patients' browse behaviors and the capacities of service resources.

The authors use a probabilistic model for explicitly capturing the browse behaviors of patients. Since the large volume of information in digital systems makes it intractable to solve the dynamic ranking problem, we design a ranking with value approximation algorithm that combines a greedy ranking policy and the value function approximation methods.

The authors found that the approximation methods are quite effective in dealing with the ranking optimization on the digital healthcare system, and it is mainly because the authors incorporate the patient behaviors and patient availability in the model.

To the best of the authors’ knowledge, this is one of the first studies to present solutions to the dynamic physician ranking problem. The ranking algorithms can also help platforms improve system and operational performance.