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This paper provides a comprehensive assessment of the influencing factors on knowledge transfer through meta-analysis with an emphasis on the influence of cultural contexts.

The approach involved the evaluation and analysis of 69 published empirical studies and the categorization of these studies into two groups based on different cultural contexts as described by Hofstede. A meta-analytic approach was then employed to provide a comparative analysis of the categorized studies.

The results of the meta-analysis of the influencing factors of knowledge transfer are consistent with the results obtained in most previous studies, indicating a maturation of research in this area. Influencing factors such as knowledge ambiguity, tie strength, trust, and common cognition are shown to impact knowledge transfer in different cultural contexts, particularly with regard to the individualism-low power distance and collectivism-high power distance dimensions defined by Hofstede.

This analysis was limited to the correlation between the influencing factors and the general performance in knowledge transfer and did not specifically address more detailed dimensions such as efficiency and effectiveness. In addition, this analysis was restricted to the cultural contexts of only two cultural dimensions. However, the review of this broad range of studies provided sufficient data to allow an in-depth analysis of related influencing factors and helped to illustrate and exemplify the influencing mechanisms of culture on knowledge transfer.

The results presented in this paper can help managers working in cross-cultural environments to understand the key influencing factors that affect knowledge transfer in the workplace. By understanding these factors, managers can more effectively implement methods and procedures that improve cross-cultural knowledge transfer in the work environment.

This paper provides a detailed insight into the influencing factors found between two distinctive cultural contexts and offers a fresh analysis of influencing factors with regard to knowledge transfer in a cross-cultural environment.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.

The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

Notes with concern the current negative rate of personal saving in the USA, reviews previous research on factors affecting savings and explores the interrelationships between personal savings and the returns on stock and family homes. Develops a mathematical model and applies it to 1980‐2000 data using causality tests, cointegration and error‐correction models. Finds a significant, negative causal relationship from stock returns to savings and a possible positive causal relationship from returns on homes, although the latter was not supported by tri‐variate analysis. Concludes that changes in a household’s stock returns are adjusted through changes in savings.

With the accelerated technological advancement, innovation has become a critical factor, which affects the core competitiveness of a company. However, studies about the relationship between internal stock option mechanisms and innovation productivity remain limited. Therefore, this paper aims to examine the impact of stock options and their elements design on innovation output from an internal mechanism perspective.

Using a sample of 302 stock option incentive plans announced and implemented between 2006 and 2016, this study uses the propensity score matching and difference-in-difference model to find out whether the implementation of stock options improves the innovation outputs of enterprises.

Based on the statistical analysis, it is concluded that: stock options can stimulate corporate innovation; a stock option may drive innovation outputs through two ways, performance-based incentives and risk-taking incentives, with the latter one playing a more dominant role and the risk-taking incentives of stock options, could be optimised when the non-executives granting proportion is larger, the granting range is limited, the incentive period is longer, the exercisable proportion is increasing, the price-to-strike ratio is lower and relatively loose performance assessment criteria are applied.

The conclusion reached in the study may provide valuable information to listed firms in designing and implementing the stock option plans.

The purpose of this paper is to identify the interactions of factors impacting the widespread adoption of prefabricated building technologies and the intervention strategies to facilitate the development of prefabrication based on fuzzy cognitive maps (FCMs).

Through in-depth interviews with six stakeholder groups, namely, the government, developers, designers, contractors, manufacturers and researchers, 13 critical factors were identified and used to construct stakeholder-grouped FCMs, which were further aggregated into a collective FCM. The complexity and density of the collective FCM and the centrality of factors in the FCM were examined. Subsequently, a series of “what-if” simulations of the collective FCM were conducted to analyze the effectiveness of different interventions in promoting prefabrication.

The results show that three factors including market demand, cost, and policies and regulations have been mentioned by all stakeholder groups. However, these factors were ranked differently by stakeholder groups, implying that different stakeholder groups perceive the barriers to prefabricated building technologies differently. FCM simulations show that strengthening policies and regulations yield the strongest overall effect stimulating prefabrication, alleviating the organizational and environmental barriers more than the technological barriers, while improving the knowledge and expertise alleviate the technological barriers more. These measures need to be accompanied by other approaches, such as reducing cost and improving quality.

It is a tough task to promote prefabrication as it is affected by numerous barriers with complex interactions, which have been overlooked by previous studies. This study clearly shows which strategy could tackle which barriers to prefabrication through the FCM simulations. This provides valuable references for the enterprises’ decision making and the governments’ policy making to facilitate the diffusion of prefabricated building technologies.

Few studies aim to analyze the interactions among the barriers to prefabrication, while this study specifically investigates this issue by illustrating the complex interactions using FCMs. Few studies also aim to identify the intervention strategies promoting prefabrication based on a quantitative approach, while this study employs FCM simulations to directly simulate the effectiveness of different strategies to facilitate prefabrication in a quantitative manner.

Drawing on signaling theory, the purpose of this study is to explore how high-performance work systems (HPWS) interact with leader–member exchange (LMX) to predict employees' proactive behavior and job engagement. Moreover, the present study also proposes the mediating role of job engagement in the interactive effects of HPWS and LMX quality on proactive behavior.

The data of this study include 228 customer-contact employees and 44 store managers from chain store enterprises in the service sector in Taiwan. The proposed models were tested with hierarchical linear modeling and Monte Carlo simulation.

The results show a significant interactive effect of HPWS and LMX on job engagement and proactive behavior. In addition, job engagement serves as a vital mechanism linking the interactive effect of HPWS and LMX quality on proactive behavior.

This study uses signaling theory to unpack the question when and how HPWS can be more influential on employees' proactive behavior. In particular, the positive effect of HPWS on proactive behavior is more prominent only when employees enjoy high LMX quality with their respective line managers. In addition, the interactive effects of HPWS and LMX quality on proactive behavior are mediated by job engagement. The findings provide valuable theoretical and managerial contribution by integrating HRM and leadership research.

This chapter studies the dynamic responses of the conditional quantiles and their applications in macroeconomics and finance. The authors build a multi-equation autoregressive conditional quantile model and propose a new construction of quantile impulse response functions (QIRFs). The tool set of QIRFs provides detailed distributional evolution of an outcome variable to economic shocks. The authors show the left tail of economic activity is the most responsive to monetary policy and financial shocks. The impacts of the shocks on Growth-at-Risk (the 5% quantile of economic activity) during the Global Financial Crisis are assessed. The authors also examine how the economy responds to a hypothetical financial distress scenario.