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The purpose of this paper is to review the process of rural labor reallocation and unfolds its growth effect through sufficiently supplying human resources, preventing diminishing return to capital, and increasing labor productivity.

The author surveys literature and statistics related to the subject to comprehensively picture the 40-year course of the shift and reallocation of agricultural surplus labor.

In the past 40 years, reforms in relevant areas have eliminated institutional barriers deterring labor mobility and allowed agricultural laborers to exit from low-productivity farming employment, migrate beyond rural-urban boundary and across regions, sectors, and ownerships, and enter higher productivity employment in non-agricultural sectors. As a result, resources allocative efficiency has been substantially improved, contributing a significant part to labor productivity growth and thus economic growth of the Chinese economy as a whole.

To sustain this source of economic growth as far as China completes its transition from upper-middle income status to high-income status, deepening reforms is urgently needed. The author provides policy suggestions for further reform.

This paper enhances people’s understanding of the Chinese economic reform and its nature of efficiency and inclusion.

The purpose of this paper is to examine the relationship between training and education and associated workforce productivity and competitiveness also, to identify new effective strategies for China to maintain and enhance workforce productivity given the depleting abundant workforce supply.

Based on data from China's manufacturing firms that included all state‐owned and non‐state‐owned enterprises with annual revenue greater than ¥5 million in 2004, the authors calculate marginal labor productivity through production function and derived the relationship between workers' education and associated productivity.

At the time China arrives at a Lewisian Turing Point, workforce quality can substitute the quantity to maintain its competitive advantage. Higher workforce productivity generated from improved human capital can offset increases in labor cost, thus creating new impetus for sustained economic growth.

Formal education and workplace learning are complementary in maintaining and enhancing a productivity workforce. To build a new competitive edge for China's economic growth in the short run, enterprise‐based training should be a requirement in all industries.

The authors offer implications for HR managers and organizations on talent management strategies. Implications for governments to develop policies that promote and foster workplace learning and skill building activities are also presented.

This study is one of the first adopting large‐scale enterprise productivity data to show China's workforce competitiveness by examining the relationship between workforce productivity and training and education.

From a macro perspective, the paper aims to present human resources challenges after the new leadership transition in China and propose future directions for policy and research in relation to human resource management and development.

This essay is based on analyzing the most recent 2010 Chinese National Census data published in 2012 by the State Council of China incorporating the recent research on human resources in China.

With a fundamental change in the nation's demographics, the population dividend supporting the high rate of economic growth in the past three decades has come to an end. China started to suffer severe skill shortages, and it is likely to be extended to a significant period of time. Due to the skill shortage and lacking of innovation, the rate of economic growth will significantly slow down for the coming decade and beyond. Reform in existing household registration system is required to facilitate new skills formation for rural migrant workers combining reform in training and education system.

Addressing human resource issues at a macro level, the paper analyses the sources of human resource challenges facing the new national leadership and proposes directions for human resource policy reform and for future research.

The COVID-19 pandemic has resulted in significant changes in consumer behaviour, which has had a cascading effect on consumer-centric logistics. As a result, this study conducts a focused literature review of pandemic-related consumer behaviour research to address two research questions: 1) what are the pandemic's direct effects on consumer consumption behaviour, with an emphasis on changes in their basic and psychological needs? and 2) what are the consequences of behavioural changes on consumer-centric logistics?

The scientific procedure and rationales for systematic literature review (SPAR-4-SLR) protocol and the theory, context, characteristics and methodology (TCCM) framework were adopted as a guideline to map, refine, evaluate and synthesise the literature. A total of 53 research articles were identified for further analysis.

Using Maslow's hierarchy of human needs as a theoretical guide, this review synthesises the COVID-19 pandemic's effects on consumer behaviour into four categories: abnormal buying behaviour, changes in consumer preferences, digitalisation of shopping behaviour and technology-related behaviour. Furthermore, four consumer-centric logistics propositions are proposed based on the four aspects of consumer behavioural changes.

This study outlines the significant behavioural changes in consumers in the face of the COVID-19 pandemic and how these changes impact consumer-centric logistics, with implications for managing consumers' involvement in logistics and pointing out future research directions.

The conceptualization of smart emerged by technological advancements penetrated the tourism industry with the pace of globalization transformed the destinations providing digitalized products. Even though smart tourism destinations are initiated by advanced technologies, the notion evolved in embracing Sustainable Development Goals (SDGs) project economic, social, and environmental proliferation. A tourism destination is counted as “smart” which provides advanced technologies to improve the quality of tourists' experiences and enhance the residents' quality of life. The structure of a smart tourism destination is established on four basic pillars that cover technology, innovation, accessibility, and sustainability issues. Designating the notion of smart into tourism destinations is extremely vital since the shifting paradigm of tourists’ demands concern sustainability. The development of smart in a tourism destination is a crucial concern for destination management organizations (DMOs) integrating key destination components with the dimensions of a smart city to enhance the tourists' satisfaction and competitiveness of the destination. Therefore, one aim of this chapter is to elucidate the association between key destination components with the dimensions of a smart city to reveal the related smart tourism destination applications. Moreover, cultural heritage in smart tourism destinations forms an important part of tourism both with its tangible and intangible resources which have been involved in the emergent era of digitalization inevitably with all parties and processes. Hence, another aim of this chapter is to examine the dimensional shift in cultural heritage tourism within the framework of digitalization. Sharing cases of digitization of cultural heritage from different parts of the world, this chapter also reflects that it is inevitable to benefit from digitization and ICTs in order to reach the SDGs on the scale of smart tourism destinations. Analysis of academic publications and the national and international reports of the related authorities sums the methodology used to conclude the study with suggestions of future research paths to develop the field.

This study aims to evaluate the use of polyoxyethylene lauryl ether (PLE) as a dispersant in the preparation of novel pigment dispersion with enhanced dispersion ability, which can find application in the printing industry.

To obtain a good dispersion, PLE was used as a dispersant in pigments dispersion. The colloidal and rheological properties of the PLE-based dispersion, such as particle distribution, zeta potentials and apparent viscosity were evaluated.

The particle sizes of the pigment dispersions were within the range of 150 to 200 nm. The measurement of zeta potentials varied between −24 to −32 mV, revealing a strong surface charge interaction between pigments and PLE. Subsequently, its stability to high-speed centrifuge and freeze-thaw treatment was carefully investigated. To demonstrate the coverage of pigment particles by PLE, thermogravimetric analysis was carried out. Moreover, X-ray diffraction was used to disclose the combined impacts of PLE and ultrasonic power on the crystal structures of the pigments. Finally, the coloring performance and leveling properties of pigment dispersions on cotton substrates were evaluated by measuring their K/S values (color strength), rub and color fastness properties, which possessed good results.

The dispersant used is incompatible with strong oxidizing agents and strong bases. More so, modification to improve its dispersion properties can be studied.

The use of PLE as a dispersant could be readily used in pigment dispersion processes and other suitable applications. PLE could also be used as a co-surfactant in synergy with other surfactants or dispersants in the dispersion process.

The use of PLE in pigment dispersion as well as investigating its coloring properties on cotton fabric is novel and can find various applications in the dying, printing and coating industry.

This chapter studies the asymptotic properties of within-groups k-class estimators in a panel data model with weak instruments. Weak instruments are characterized by the coefficients of the instruments in the reduced form equation shrinking to zero at a rate proportional to nTδ, where n is the dimension of the cross-section and T is the dimension of the time series. Joint limits as (n,T)→∞ show that this within-group k-class estimator is consistent if 0≤δ<12 and inconsistent if 12≤δ<∞.

Emerging-market (EM) assets have historically been regarded as inherently risky and particularly vulnerable to international shocks that result in a general increase in investor risk perceptions. In this chapter, we assess the ongoing relevance of this view by examining the linkages between EM and non-EM stock and bond markets in the past two decades, with a focus on how these relationships played out during the global financial crisis of 2007–2009. We evaluate how these linkages have evolved over the period 1992–2009, through statistical tests of whether the volatility of EM financial markets changed – either in their response to international shocks originating in advanced-economy markets or in their independent fluctuations.

We find that over a longer period EM, bond and stock prices have on average moved in the same direction as the prices of non-EM risky assets, and this co-movement has persisted. However, these relationships have evolved somewhat over time. Both EM sensitivity to international shocks and EM-specific volatility in EM sovereign-bond spreads appear to have decreased over time, consistent with the greater fundamental stability of EM economies and perhaps a reduced inclination by investors to sell off EM assets in response to a rise in risk perceptions. Somewhat in contrast, while an upward trend in co-variation between EM and non-EM stock prices suggests an increasing degree of global market integration, idiosyncratic volatility has declined, consistent with a diminished level of locally driven risk in these markets.

In addition, the response of EM asset prices to the latest financial crisis appears to be moderate in comparison to historical experience. This evidence may reflect reduced EM vulnerability to external shocks in general, which is consistent with some encouraging improvements in the underlying fundamentals of EM economies over the decade preceding the onset of the crisis.

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.