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A bad safety accident at a manufacturing company usually results in casualties and economic losses. The company affected by such an accident must deal with pressure from multiple stakeholder groups. Employees, in particular, play a key role in pushing the affected company to develop strategies to improve occupational safety and health. The purpose of this paper is to seek answers to two questions: does a safety accident affect employee behavior in terms of giving up prospects to develop a career at the affected company? If yes, could innovation initiatives adopted by the company help moderate the negative consequences from a safety accident?

By investigating 120 safety accidents reported by publicly listed Chinese manufacturing companies between 2009 and 2016, the authors conduct an empirical study using regression-based statistical hypotheses testing to describe the companies’ responses and prospects for their employees.

The results show that the magnitude of the accident and the accident being caused by an employee error positively affect the turnover of employees. Furthermore, technical innovation initiatives, such as spending on R&D, by the accident-affected companies increase the positive effect of the accident magnitude on employee turnover. On the contrary, management innovation initiatives, such as corporate social responsibility activities, weaken the impact of the accident magnitude and employee error on employee turnover.

This study contributes to knowledge development by adding a crisis perspective in human resource management research. It helps to better understand the impact of safety accidents on employee behavior and the response taken by companies through innovation initiatives.

This paper aims to present error compensation based on surface reconstruction to improve the positioning accuracy of industrial robots.

In previous research, it has been proved that the positioning error of industrial robots is continuous on the two-dimensional manifold of six-joint space. The point cloud generated by positioning error data can be used to fit the continuous surfaces, which makes it possible to apply surface reconstruction on error compensation. The moving least-squares interpolation and the B-spline method are used for the error surface reconstruction.

The results of experiments and simulations validate the effectiveness of error compensation by the moving least-squares interpolation and the B-spline method.

The proposed methods can control the average of compensated positioning error within 0.2 mm, which meets the requirement of a tolerance (±0.5 mm) for fastener hole drilling in aircraft assembly.

The error surface reconstruction based on the B-spline method has great superiority because fewer sample points are needed to use this method than others while keeping the compensation accuracy at the same level. The control points of the B-spline error surface can be adjusted with measured data, which can be applied for the error prediction in any temperature field.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

This study aims to report the preparation, selective laser sintering (SLS) processing and properties of a new nylon elastomer powder. The effects of solvent, dissolution temperature and time and cooling method and speed on the particle size and morphologies of the prepared nylon elastomer powder are investigated.

The prepared nylon elastomer power possesses the particle size of around 50 mm and is spherical in shape, indicating that this study provides the feasible dissolution-precipitation process, a distillation cooling method and a suitable solvent to prepare nylon elastomer powders.

Compared to pure nylon 12, the nylon elastomer has a lower part bed temperature and a wider sintering window for the SLS process. The wider sintering window indicates the better SLS processibility. The lower part bed temperature is beneficial to the recycling of material and the decrease in the requirement of SLS equipment.

The nylon elastomer in this study has a lower part bed temperature and a wider sintering window for the SLS process. The wider sintering window indicates better SLS processibility. The lower part bed temperature is beneficial to the recycling of material and the decrease in the requirement of SLS equipment.

Semi-crystalline polymers such as polyamide-12 can be used for selective laser sintering (SLS) to make near-fully dense plastic parts. At present, however, the types of semi-crystalline polymers suitable for SLS are critically limited. Therefore, the purpose of this paper is to investigate the processibility of a new kind of semi-crystalline polypropylene (PP) with low isotacticity for SLS process.

The SLS processibility of the PP powder, including particle size and shape, sintering window, degree of crystallinity and degradation temperature, was evaluated. Effects of the applied laser energy density on the surface micromorphology, density, tensile strength and thermal properties of SLS-built PP specimens were studied.

The results show that the PP powder has a nearly spherical shape, smooth surfaces, an appropriate average particle size of 63.6 μm, a broad sintering window of 21 oC and low crystalline degree of 30.4 per cent comparable to that of polyamide-12, a high degradation temperature of 381.8°C and low part bed temperature of 105°C, indicating a very good SLS processibility. The density and the tensile strength first increase with increasing laser energy density until they reach the maximum values of 0.831 g/cm3 and 19.9 MPa, respectively, at the laser energy density of 0.0458 J/mm², and then decrease when the applied laser energy density continue to increase owing to the degradation of PP powders. The complex PP components have been manufactured by SLS using the optimum parameters, which are strong enough to be directly used as functional parts.

This paper provides a new knowledge for this field that low-isotacticity PPs exhibit good SLS processibility, therefore increasing material types and broadening the application of SLS technology.

The increasing threat of global warming and climate change has been a major worldwide concern for more than two decades. As the achievement of sustainable economic growth has gradually become a major global concern both policy makers and researchers have given considerable attention over the years on the link among energy consumption, emissions and economic growth. In this study, following a solovian growth structure, the authors assume that the aggregate output depends on the stock of physical as well as human capital and energy or power. Depending on the sources, the energy can be categorised into cleaner input generated from renewable sources and a dirty input extracted from non-renewable resources having by-products like pollution. This study finds that less-developed countries (LDCs) failing to afford sufficient access to clean energy which in turn has deleterious impact on the human capital which cascades into low level of production, low saving and low per capita output forming a vicious loop. On the other side, the developed nations are better poised with access to clean energy and this is what is reflected in having larger reserve of human capital yielding higher production, higher income, higher saving and higher per capita capital stock in a circular process. This hence posits a clinching picturing divergence in per capital output and income between developed and less-developed nation mediated through degree of access to clean energy and thereof, the capacity to control emission. The convergence situation between the developed and the less-developed nations shows that each ends up with the relative energy mix below the threshold and it is not desirous for the world as a whole. In case of per capita emission, the divergence situation with the global level of emission is bit ambiguous.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).