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The industrial revolution 4.0 (IR4.0) signifies technological advancements and digitalization. The fragmented and labour-intensive nature of the construction industry inherently possesses difficulties for IR4.0 adoption compared to other industries. This paper aims to investigate the perspectives of quantity surveying students on the challenges of IR4.0 implementation in the construction industry.

A questionnaire survey were distributed to a population of 191 quantity surveying students, with 96 valid responses returned. Descriptive statistics and factor analysis were employed to analyse the collected data.

Factor analysis revealed eight components as the key challenges for IR4.0 implementation, which revolved around resistance to change, data security issues, etc.

The findings could provide a guideline to higher education institutions on certain IR4.0-related areas to be incorporated into the syllabus, in ensuring that the students are equipped with such skills and knowledge, in meeting market demands. The construction stakeholders' could look into the identified challenges for strategizing the organizations in moving towards IR4.0 adoption.

To the best of the authors’ knowledge, this is the first study to investigate quantity surveying students' perspectives on the challenges of IR4.0 implementation in the construction industry by employing factor analysis method. The findings contribute to the body of knowledge in relation to the opinions of a younger generation who has more exposure towards technology on the hindrance of IR4.0 adoption.

Digital transformation (DT) is among the vital factors contributing to innovation ambidexterity, especially for advanced manufacturing firms (AMFs). However, the empirical studies on the relationship between DT and innovation ambidexterity in AMFs from the perspective of knowledge management are inadequate. Therefore, this study aims to systematically analyze the impact of DT on innovation ambidexterity and its mechanism of action.

This study selects 254 listed firms within the ten key areas of “Made in China 2025,” as they occupy a key position in China’s advanced manufacturing system. Based on the knowledge-based view (KBV) and contingency theory, it constructs a model of the influence mechanism of DT on innovation ambidexterity.

The results show that the DT of AMFs positively influence innovation ambidexterity. External pressure from environmental turbulence enhances the positive relationship between DT and innovation ambidexterity, demonstrating the “resilience effect,” external knowledge search (EKS) and broadening the knowledge base mediating roles between them, highlighting the “accumulation effect.”

By identifying this mediation mechanism of DT and innovation ambidexterity, this study provides new ideas for path research on the KBV. Moreover, this study explores the triggering effect of market environmental turbulence on the DT of firms. It reveals the boundary conditions of DT acting on innovation ambidexterity, expands the research perspective on organizational resilience and enriches the theory of power change.

Together with developing information and communication technologies and the increasing use of the Internet, there have been changes in the behaviors of the consumers during the purchasing decision process. Today’s consumers realize most of the decision process phases (such as gathering the information, determining the alternatives, evaluating the alternatives and even purchasing) from the Internet. Tourists who would like to purchase a holiday are also using the Internet during their holiday decision process. Today, websites which became an increasingly popular information source for the consumers play a significant role in potential visitors/tourists’ choices related to the destinations. Websites are used as a distribution and marketing tool in promotion and marketing of the tourism destinations. In this context, the design and content of the destination websites should be on a level which would attract and satisfy the tourists. In this chapter, the author will primarily discourse the visual and auditory factors which affect the perception of tourists and the application areas of these factors in website design. Then, the subjects such as the key features of the websites, information that should be provided on websites, the design of the website and their functions will be covered. The parameters that should be taken under consideration in order to evaluate the performance of a website and the evaluation criteria for the sites will also be included within the context of this chapter. In this chapter, the author will also discourse the benefits that the websites provide for destinations and the success factors of the destination websites. In the conclusion section of this chapter, the author will provide propositions related to the factors that should be taken under consideration in destination website design.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

The purpose of this paper is to investigate the impact of mechanization services on farm productivity in Northern China from an empirical perspective, with the aim to identify the underlying market and institutional barriers.

The authors apply the regression method with the control of village fixed effects to examining the relationship between capital–labor ratio, mechanization service ratio and farm productivity, using the panel data collected in 2013 and 2015 by CCAP.

Mechanization services improve farm productivity through substituting labor, but it may generate a less positive impact on farms who do not have self-owned capital equipment.

It is the first study to investigate how mechanization services affect farm productivity for grain producers in Northern China.

This study investigates the effect of renting in land on farm productivity, and the impacts of rented-in land size and transaction partner type on farm productivity.

Data from the 2015 China Household Finance Survey are analyzed using an extended regression model and the two-stage least squares method.

Farm households that rent in land are likely to achieve higher farm productivity, and ignoring endogeneity underestimates the positive effect of land renting-in. Further evidence indicates that rented-in land size has an insignificant impact on farm productivity, and that there is no difference in farm productivity between lessees renting-in land from acquaintances and those renting-in land from non-acquaintances. These results may be caused by the higher degree of marketization of land rentals between acquaintances in China. With increasing competition in agricultural factor markets, in theory, rented-in land size should not affect farm productivity.

Overall, the analysis suggests that renting in land improves farm productivity, which supports the land transfer policies that have been rolled out in recent decades in China. However, our finding that rented land size does not affect farm productivity, consistent with the results in the literature, implies that the Chinese government should no longer subsidize or prefer large farms with low productivity. More attention should be paid to small lessees and market-oriented land rentals between acquaintances. Promoting the marketization of land transfers inside acquaintance networks could realize the potential of the land market, especially if land transfers decrease.

This study identifies the effects of renting in land, rented-in land size and type of rental transaction partner on farm productivity using nationally representative data. The findings imply that the government should pay more attention to the marketization of land rentals between acquaintances. Although existing studies regard land rental between acquaintances as informal and of low efficiency, the recent evidence shows that China's land markets are changing, and policy makers should adjust their policies accordingly.

Blockchain has the potential to facilitate a paradigm shift in the construction industry toward effectiveness, transparency and collaboration. However, there is currently a paucity of empirical evidence from real-world construction projects. This study aims to systematically review blockchain adoption barriers, investigate critical ones and propose corresponding solutions.

An integrated method was adopted in this research based on the technology–organization–environment (TOE) theory and fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach. Blockchain adoption barriers were first presented using the TOE framework. Then, key barriers were identified based on the importance and causality analysis in the fuzzy DEMATEL. Several suggestions were proposed to facilitate blockchain diffusion from the standpoints of the government, the industry and construction organizations.

The results highlighted seven key barriers. Specifically, the construction industry is more concerned with environmental barriers, such as policy uncertainties (E2) and technology maturity (E3), while most technical barriers are causal factors, such as “interoperability (T4)” and “smart contracts' security (T2)”.

This study contributes to a better understanding of the problem associated with blockchain implementation and provides policymakers with recommendations.

Identified TOE barriers lay the groundwork for theoretical observations to comprehend the blockchain adoption problem. This research also applied the fuzzy method to blockchain adoption barrier analysis, which can reduce the uncertainty and subjectivity in expert evaluations with a small sample.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The purpose of this paper is to study the identification methods for multivariable nonlinear Box‐Jenkins systems with autoregressive moving average (ARMA) noises, based on the auxiliary model and the multi‐innovation identification theory.

A multi‐innovation generalized extended least squares (MI‐GELS) and a multi‐innovation generalized ex‐tended stochastic gradient (MI‐GESG) algorithms are developed for multivariable nonlinear Box‐Jenkins systems based on the auxiliary model. The basic idea is to construct an auxiliary model from the measured data and to replace the unknown terms in the information vector with their estimates (i.e. the outputs of the auxiliary model).

It is found that the proposed algorithms can give high accurate parameter estimation compared with existing stochastic gradient algorithm and recursive extended least squares algorithm.

In this paper, the AM‐MI‐GESG and AM‐MI‐GELS algorithms for MIMO Box‐Jenkins systems with nonlinear input are presented using the multi‐innovation identification theory and the proposed algorithms can improve the parameter estimation accuracy. The paper provides a simulation example.