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The purpose of this paper is to present a method to accurately forecast the tendency of the gross amount of energy sources consumption of the country and construct a new kind of algorithm for forecasting that synthesizes the advantages of the grey model, Markov chains, and least square method.

With the application of this new algorithm, this paper have forecasted the trend of the gross amount of energy sources consumption of the country and come to the conclusions that the new algorithm is more precise than the grey model. It is proved that the improved grey‐Markov chain algorithm is effective and can be used by authorities to make decision.

It was found that combining the grey model, Markov chains, and least square method, can be a new algorithm for forecasting the trendency of the gross amount of energy sources consumption.

The new algorithm is only suitable for the short‐term forecast.

The grey forecasting method reflects the overall tendency of primitive data sequence of the gross amount of energy source, and the Markov chain forecasting method reflects the effect of the random fluctuation. The least square method reflects the tendency of increase. The new algorithm is more precise than the grey model.

In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.

The kindergarten curriculum in mainland China has evolved through four periods and the current reform began in the end of 1980s. The reform aimed to transform kindergarten practice by shaping ideologies including respect for individual child, active learning, and play-based integrated curriculum. This review of research literatures shows that compared with the practice before the reform, many kindergarten teachers organize classrooms in learning centers, provide more play materials, pay time, and freedom for free play, and pay more attention to individuals. But indoor space organized in rice-seedling-bed model, teacher-led group instruction and teacher-controlled interactions are still often observed after three decades of reform efforts; there still exist great variations among kindergartens of different sponsoring bodies and in different regions. The problems resulted from the innate deficiencies of the top-down and value-priority reform, the conflicts between the advocated value and the traditional Chinese culture with emphasis on Ming-Fen, testing, and the value of children for the whole family and nation, and the unequal distribution of public resources decided by the educational institutions. Therefore, the curriculum reform is not a separate endeavor from other social changes, but a comprehensive and systematic change. To guarantee the success of the curriculum reform, the Chinese society needs cultural transformation and institutional reconstruction.

The purpose of this paper is to document an interview with Dr Xiao‐Ping Chen to share her professional and career experience as a management scholar. It shows the path of her scholarly journey fueled by her love and passion for the profession.

This paper is based on a recent interview with Dr Xiao‐Ping Chen.

Dr Xiao‐Ping Chen's experience demonstrated the importance of love and passion in one's career pursuit. It shows the importance of the interplays of internal passion and commitment and the external factors in paving and determining a scholar's career success, and how to balance personal life and a demanding role in research, teaching, and professional service.

Dr Chen's career provides an exemplar case for junior scholars to deal with the Chinese transitioning symptom associated with pursuing an academic research career. In particular, Dr Chen's optimistic and persistent way of dealing with difficulties in career and life may inspire junior scholars or those who wish to pursue a career in management research.

The interview profiles a picture of a passionate scholar in management research and offers an inspirational exemplar for the new generation of Chinese HRM researchers.

This article aims to present the second part of an interview with Dr Xiao-Ping Chen. The focus is on her experience in, and insight on, Chinese management research.

This paper is based on a recent interview with Dr Xiao-Ping Chen.

Dr Xiao-Ping Chen shared her research experience and insight in the following aspects: identifying topics in Chinese management research, collaborating with Chinese domestic scholars, and approaching a research question or idea to make research fruitful with evolving research agenda on Chinese guanxi. She also shared her insights on exploring new research topics vs following or extending others' ideas, and how the gap between research and practice might be bridged.

Dr Chen's research experience and insights provide an exemplary case for junior scholars to deal with the challenges in conducting and publishing Chinese management research, particularly in how to take an “insider's view” in identifying and engaging in interesting and valuable research.

The interview profiles a picture of a scholar in Chinese management research.

Artificial intelligence (AI) is revolutionizing product recommendations, but little is known about consumer acceptance of AI recommendations. This study examines how to improve consumers' acceptance of AI recommendations from the perspective of product type (material vs experiential).

Four studies, including a field experiment and three online experiments, tested how consumers' preference for AI-based (vs human) recommendations differs between material and experiential product purchases.

Results show that people perceive AI recommendations as more competent than human recommendations for material products, whereas they believe human recommendations are more competent than AI recommendations for experiential products. Therefore, people are more (less) likely to choose AI recommendations when buying material (vs experiential) products. However, this effect is eliminated when is used as an assistant to rather than a replacement for a human recommendation.

This study is the first to focus on how products' material and experiential attributes influence people's attitudes toward AI recommendations. The authors also identify under what circumstances resistance to algorithmic advice is attenuated. These findings contribute to the research on the psychology of artificial intelligence and on human–technology interaction by investigating how experiential and material attributes influence preference for or resistance to AI recommenders.

This paper seeks to present a wavelet Galerkin boundary element method (WGBEM) for solving 2D Laplace's equation in which the coefficient matrices are exactly computed through fast Fourier transform (FFT).

When Daubechies periodized wavelets are used to approximate smooth functions the wavelet coefficients can be exactly computed through FFT, and numerical evaluation of wavelet integrations is discarded. The same methods for computing the expansion coefficients of 2D function and singular function are derived.

For Daubechies periodized wavelets based WGBEM, two remarkable advantages over the existing WGBEM are: the coefficient matrices can be exactly calculated through FFT; a linear system with potential and flux values at dyadic points as unknowns can be gained. Thus, the mixed boundary condition can be enforced with ease. Sparse matrices with only O(N log N) nonzero entries are obtained by performing the fast wavelet transform (FWT) and the truncation of matrix entries.

A wavelet‐integration‐free method for computing the wavelet coefficients is introduced into the WGBEM. The conventional numerical evaluation of wavelet integrations is avoided. Good performance and accuracy are obtained.

Taking attribution theory as an overarching framework, the study aims to examine how employees attribute and respond to a colleague's approach crafting.

Two complementary studies, including a scenario experiment (Study 1; N = 114) and an online survey (Study 2; N = 220), were conducted to test the hypothesized model.

Study 1 found support for the attribution of a prosocial motive to approach crafting, which in turn led to more social support and less social undermining among observers. This mediation was stronger when the job crafter was perceived as less other-oriented. Study 2 replicated the findings of Study 1 and further showed that when observers attributed both high impression management and prosocial motives to approach crafting, the positive relationship between their prosocial motive attribution and social support for the job crafter got weakened, while the negative relationship between their prosocial motive attribution and social undermining of the job crafter was strengthened.

The findings demonstrate that approach crafting gives rise to specific attributions and reactions toward the job crafter, which enrich the understanding of the social consequences of job crafting in the workplace.

The purpose of this paper is to propose a new method for knowledge worker productivity measurement which is based on valid principles and appropriate viewpoints.

Based on an extensive and thorough literature review the elements that need to be taken into consideration, while designing a method for knowledge worker productivity measurement, are determined and divided into principles and viewpoints. These elements must be incorporated into the design of knowledge worker productivity measurement methods so that the correctness and accuracy of these methods can be verified. The proposed model, which is based on appropriate principles and viewpoints, determines the outputs of knowledge work with respect to the tasks that a worker’s job includes. Considering nine measures, these outputs are evaluated using fuzzy numbers and, then, quantified. The inputs of knowledge work are knowledge, skills and abilities (KSAs) required to do the job. These inputs are identified and quantified using Job Element Method. Furthermore, fuzzy Data Envelopment Analysis is employed to model the productivity.

In this paper, the proposed method for knowledge worker productivity measurement follows both appropriate principles and viewpoints, simultaneously. In order to validate the obtained results and explore the applicability of the proposed method, a case study was carried out at an Iranian organization in electric power industry. Statistical analyses are employed to prove the validity of the results. Based on the obtained results, the productivity of a knowledge worker is said to be high when he/she delivers the expected amount of job outputs considering the values of his/her inputs (KSAs).

The originality of this paper is twofold. First, the extracted principles and viewpoints can serve as a guideline for the development of similar methods. Second, the proposed model offers an effective and efficient tool that can serve as the basis for the comparison among relative productivity of knowledge workers. Furthermore, the obtained results could form a basis to examine the productivity trend of each knowledge worker over different periods of time.

Established on the detailed exploration of Chinese ancient management philosophies (CAMPs), the purpose of this paper is to extract enlightenments from CAMPs to see whether there exist some similarities between CAMPs and contemporary human resources management thoughts (CHRMTs) and pinpoint CAMPs' implications on human resource management practices nowadays.

Inspired by Lao Tzu's “When we can lay hold of the Dao of old to direct the things of the present day, and are able to know it as it was of old in the beginning, this is called (unwinding) the clue of Dao”, the paper explores, categorizes and integrates wisdom stemmed from CAMPs to evaluate whether there exist some commonly accepted arguments between CAMPs and CHRMTs.

CAMPs which have been passed on by generations for the past 2,500 years in China provide firm ground for human resources management thoughts and practices development; CAMPs' emphasis on people's well cultured morality and highly developed virtues has kindled a light to illuminate human resources management practices, not only in the past but also in the future. CHRMTs' principles concerning “people‐centered strategies”, employee recruitment and selection strategies, employee training and education strategies, staffing as well as employee retention strategies, can all trace their sources from CAMPs.

The research on CAMPs is not only significant to complement and extend CHRMTs but also useful to direct current human resource management practices.