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The definition of the ‘information industry’ is given. The state of the art of China's information industry is described. The problems and the opportunities for its development are analysed. And finally, considerations on its development are put out.

The Library System of China and the Information System of China are the two systems of information organisations in China. This paper discusses the types of information agencies in each, focusing on structural characteristics, and governing regulations and especially on programmes and activities. Included in the discussion are such topics as publications, cooperative undertakings, new services and evaluation procedures.

In this paper I shall try to define the ‘world information industry’, and to outline its present situation.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

The purpose of this study is to propose an automatic leveling method for a printing platform based on a three-point coordinate feedback. The proposed method is used in fused deposition modeling additive manufacturing systems. The coordinate error of the leveled plane is constrained to within  ± 0.2 mm, which is less than the printed layer thickness.

First, the model of the forward and inverse solutions of the parallel arm is obtained based on the principles of vector algebra. Second, the automatic leveling mechanism for collecting the z-coordinate is designed. The best position of the virtual origin plane is obtained by comparing the z-coordinates of the test points. Finally, after making multiple adjustments through a closed-loop z-coordinate feedback, the parallelism of the printing plane and the virtual origin plane is limited to an effective range.

The experimental results show that after three leveling attempts, the z-coordinate of the test points can be constrained to within  ± 0.2 mm, which shows that this method can effectively achieve automatic leveling in a delta three-dimensional (3D) printer.

This study presents a novel and distinctive delta 3D printer leveling system by designing a leveling mechanism and a leveling algorithm. The method uses a closed-loop feedback mode to make the leveling process simple, convenient and efficient without requiring major changes to the printer. The error after leveling is less than the printed layer thickness, which fully guarantees the accuracy of the leveling process.

Today's logistics industry is facing severe challenges since global transportation demand increases substantially. Carriers are urged to reduce empty loads and CO2 emissions through collaboration. Therefore, the concept of Physical Internet (PI) came into being. However, PI is still in its infancy. It is difficult to understand its sophisticated coordination mechanism, which makes learning of the concept more complicated.

Gamification is an effective approach to help students improve their learning curve. At the same time, the psychological and behavioral changes in learning will also pose an impact on learning efficiency. This paper introduces a PI transportation game and designs a set of gamification teaching experiments. In the experiment, a control group and three experimental groups are set up, and the experiment was designed to respond to a plethora of research questions using the methods of T-test, correlation analysis and regression analysis. Experimental results were analyzed through the method of multivariate statistics.

This paper looks for superior pedagogical methods and procedures for students to learn PI while providing suggestions for PI's learning among undergraduates. The authors found (1) gamification teaching will make participants feel more satisfied and master more knowledge points; (2) the scores of logistics testing have been significantly improved after gamification teaching and (3) flow experience has a significant impact on game revenue.

This is the first study about the impact of gamification on teaching and learning PI. The authors apply the methods of T-test, correlation analysis and regression analysis to analyze the collected data. The paper proves that gamification can help students learn PI and that flow experience can improve the efficiency of students learning PI.

Since the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.

An exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.

The study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.

The authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.

The objective of this study is to examine how formal and informal institutional environment influences managers’ fair value opinion shopping behaviour in the largest International Financial Reporting Standards adopter, China.

To test the hypotheses, I conduct a 2 × 2 between-subject randomised experiment since the inferences about cause and effect are important in this study. The between-subject experimental situations are manipulated on the basis of the financial condition of companies and boards’ oversight.

I find that managers are likely to seek favourable fair value opinions from external valuation professionals when they are under the weak boards’ oversight and high stress to meet the regulation target of the China Securities Regulatory Commission. These results are more pronounced for managers with higher both rent-seeking and favour-seeking guanxi orientations are more likely to engage in fair value opinion shopping.

Consistent with theoretical analysis of Balfoort et al. (2017), this study provides empirical evidence that guanxi influences the neutrality and faithful representation in fair value measurement in China. In addition, the findings extend Salzsieder’s study (2015) and reflect the context-embeddedness nature of accounting.

This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

This research aims to model the relationship between the credit risk signals in the credit default swap (CDS) market and agency credit ratings, and determines the factors that help explain the variation in such signals.

A comprehensive analysis of the differences in the relative credit risk assessments of CDS-based risk signals and agency ratings is provided. It is shown that the divergence between credit risk signals in the CDS market and agency ratings is explained by factors which the rating agencies may consider differently than credit market participants.

The results suggest that agency credit ratings of relative riskiness of a reference entity do not always correspond with assessments by CDS spreads, as the price of risk is a function of additional macro and micro factors that can be explained using statistical analysis.

This research is unique in modeling the relationship between the credit risk assessments of the CDS market and the agency ratings, which to the best of the authors' knowledge has not been analyzed before in terms of their agreement and the level of discrepancy between them. This model can be used by investors in debt instruments that are not explicitly CDSs or which have illiquid CDS contracts, to replicate market-based, point-in-time credit risk signals. Based on both market-based and firm-specific factors in this model, the results can be used to augment through-the-cycle credit risk assessments, analyze issues surrounding the pricing of CDSs and examine the policies of credit rating agencies.