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The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior.

Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead–lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock.

It turns out that the lead–lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time.

One limitation of this paper is that it studies China’s stock market only; however, different conclusions could be drawn for other financial markets or mature stock markets.

As for the implications, the new tool could improve the prediction accuracy of the model, thus have practical significance for stock selection and dynamic portfolio management.

This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.

This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this paper: designing an unsupervised method for extracting online Chinese features and opinion pairs, distinguishing different intensities of polarity in opinion words and examining the changes in polarity in the time series.

In this paper, a review analysis system is proposed to automatically capture feature opinions experienced by other tourists presented in the review documents. In the system, a feature-level SA is designed to determine the polarity of these features. Moreover, an unsupervised method using a part-of-speech pattern clarification query and multi-lexicons SA to summarize all Chinese reviews is adopted.

The authors expect this method to help travellers search for what they want and make decisions more efficiently. The experimental results show the F-measure of the proposed method to be 0.628. It thus outperforms the methods used in previous studies.

The study is useful for travellers who want to quickly retrieve and summarize helpful information from the pool of messy hotel reviews. Meanwhile, the system will assist hotel managers to comprehensively understand service qualities with which guests are satisfied or dissatisfied.

Climate change will have a significant impact on China’s potential agricultural production and change the distribution of the population in various regions of China, thus producing population migration. This paper aims to analyze China’s population migration in response to climate change and its socio-economic impact.

In this paper, the Potential Agriculture Production Index is introduced as an analytical tool with which to estimate the scale of the population migration induced by climate change. Also, this paper constructs a multi-regional computable general equilibrium (CGE) model and analyzes the effect of change in the population distribution pattern on regional economies, regional disparity and resident welfare.

The key finding of this paper is that, as a result of changes in potential agricultural production induced by climate change, the Circum-Bohai-Sea region, the industrialized region and the industrializing region, which are the main destination regions of the migrating population, will face a severe labor shortage. In response to population migration, the economic growth rate of the immigrating population regions has accelerated. Correspondingly, the economic growth rate of the emigrating population regions has decreased. In addition, the larger the scale of population migration is, the larger the economic impact is. Migration increases inner-regional disparity and decreases inter-regional disparity. However, overall regional disparity is only somewhat decreased.

This paper introduces a Potential Agriculture Production Index to estimate the scale of the population migration and introduce a multi-regional CGE model to analyze the correlated social-economic impacts.

This paper aims to capture tail dependence between sentiment index and Shanghai composite index (SCI) by proposing a sentiment index based on text mining.

Online text mining and the Copula model were used in this study.

First, the paper finds herding effect in the expression of investors’ sentiment from online text data, and the usage occurrence frequency of most vocabulary is less correlative with SCI. Second, given these two features, the paper uses weighted divide-and-conquer algorithm to construct a sentiment index. Finally, because of multivariate non-Gaussian joint distribution between them, the paper uses the Copula model to detect their tail dependences, and finds that both upper and lower tail dependences could have a significant influence between positive sentiment and SCI, with a higher probability on the upper one. Additionally, only the upper tail dependence exhibits the significant influence between negative sentiment and SCI.

This paper proposes a framework of constructing investment sentiment index with the weighted conquer-and-divide algorithm, and characterizes tail dependence between sentiment index and SCI. The implication can measure the environment of investment market of China and provide an empirical ground for bandwagon effect and bargain shopper effect.

The six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.

The performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.

The sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.

Hence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

The purpose of this paper shows the effect of hot and humid weather conditions (HHWCs) on workers that has resulted in considerable loss in the construction industry, especially during the hottest periods due to decline in worker productivity (WP). Until the last few decades, there is very limited research on construction WP in HHWCs. Nevertheless, these studies have sparked interests on seeking for the most appropriate methods to assess the impact of HHWCs on construction workers.

This paper begins by reviewing the current measuring methods on WP in HHWCs, follows by presenting the potential impact of HHWCs on WP. The paper highlights the methodological deficiencies, which consequently provides a platform for scholars and practitioners to direct future research to resolve the significant productivity loss due to global warming. This paper highlights the need to identify the limitations and advantages of the current methods to formulate a framework of new approaches to measure the WP in HHWCs.

Results show that the methods used in providing real-time response on the effects of HHWCs on WP in construction at project, task and crew levels are limited. An integration of nonintrusive real-time monitoring system and local weather measurement with real-time data synchronisation and analysis is required to produce suitable information to determine worker health- and safety-related decisions in HHWCs.

The comprehensive literature review makes an original contribution to WP measurements filed in HHWCs in the construction industry. Results of this review provide researchers and practitioners with an insight into challenges associated with the measurements methods and solving practical site measurements issues. The findings will also enable the researchers and practitioners to bridge the identified research gaps in this research field and enhance the ability to provide accurate measures in HHWCs. The proposed research framework may promote potential improvements in the productivity measurements methods, which support researchers and practitioners in developing new innovative methods in HHWCs with the integration of the most recent monitoring technologies.

This paper aims to propose a conceptual model for understanding the influence of change readiness on knowledge management processes and knowledge management effectiveness. It is suggested that change readiness should be assessed as a multidimensional construct consisting of psychological and structural facets. Furthermore, as the process of managing organizational knowledge requires interaction among members of the organization, a holistic view of readiness at individual and organizational levels is presented.

A comprehensive literature review results in the development of the conceptual model that depicts potential relationships between change readiness and knowledge management processes. It also postulates the effects of different knowledge management processes on effective knowledge management implementation.

Potential implications of change readiness from both psychological and structural dimensions for knowledge acquisition, creation and sharing processes are put forward. Further, it offers possible fruitful areas for continuous research of knowledge management effectiveness from a change perspective.

This article puts forward a number of potential relationships among the construct that are empirically testable to further understanding of multidimensional change readiness influences on the various types of knowledge management processes and its effective implementation.

Through a conceptualisation of the relationships between change readiness, knowledge management processes and knowledge management effectiveness, this paper offers a number of practical guidelines for the development of knowledge management policy and a road map from a change management perspective.

Previous literature on knowledge management focuses on understanding organizational readiness to promote successful knowledge management implementation in terms of the structural dimension. This paper proposes understanding of change readiness from a more comprehensive perspective comprising both psychological and structural readiness and its influences on knowledge management processes, which could affect overall effectiveness of knowledge management implementation.

Balanced leadership is attracting increasing attention from academia and practitioners. In this rapidly changing world, maintaining balance while moving ahead is becoming a challenge for organizational leaders concerned with effective leadership. The traditional concept of balancing, theoretically, has been frequently re‐visited by researchers, while new concepts of balancing are being developed by researchers and practitioners, in order to effectively guide the practice in the real institutional settings. The purpose of this paper is to examine the classic Chinese perspectives from Wu Xing, I Ching and Tao Te Ching. Some western perspectives (e.g. Waters and Leithwood) on balanced leadership are also examined, to reach a hybrid model in an effort to decipher the meanings of balancing, and to address their applicability in modern organizational lives.

This paper provides analyses of the perspectives in the Chinese classics Wu Xing, I Ching and Tao Te Ching, and presents insights on the principles for organizational leaders to apply in dealing with changes.

There is a philosophical base for balanced leadership. It is becoming imperative for leaders to practice balanced leadership in the following aspects of organizational lives: Leaders' steady dispositions; Harmonious human relations; Categorization of the magnitudes of change for improvement; and a hybrid model integrating both eastern and western concepts of balanced leadership.

This paper focuses on one domain of leadership – balancing in the interactions between the leaders and their people. It is relevant for those who have interest in, and are concerned for, the vertical, lateral relations, organizational development and improvement.

This paper reflects the researchers' deep insight into the Chinese classics, their expertise, and their empirical practices in organizational leadership. The paper will help those with similar interests in this area to better understand the implications of the Chinese perspectives.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.