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This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined with nonlinear programming algorithm, study how to schedule the number of labor in each process at the minimum cost to achieve an extremely short construction period goal.

The method of inverse optimization is mainly used in this study. In the first phase, establish a positive optimization model, according to the existing labor constraints, aiming at the shortest construction period. In the second phase, under the condition that the expected shortest construction period is known, on the basis of the positive optimization model, the inverse optimization method is used to establish the inverse optimization model aiming at the minimum change of the number of workers, and finally the optimal labor allocation scheme that meets the conditions is obtained. Finally, use algorithm to solve and prove with a case.

The case study shows that this method can effectively achieve the extremely short duration goal of the engineering project at the minimum cost, and provide the basis for the decision-making of the engineering project.

The contribution of this paper to the existing knowledge is to carry out a preliminary study on the relatively blank field of the current engineering project with a very short construction period, and provide a path for the vast number of engineering projects with strict requirements on the construction period to achieve a very short construction period, and apply the inverse optimization method to the engineering field. Furthermore, a double-nested genetic algorithm and nonlinear programming algorithm are designed. It can effectively solve various optimization problems.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

Drawing upon a political economy approach, this article aims to analyze the transformations in the labor market within the context of contemporary capitalism, focusing on the phenomenon of financialization.

Financialization is defined as a distinct wealth pattern marked by a growing proportion of financial assets in capitalist wealth. Within financial markets, corporate performance is continuously assessed, in a process that disciplines management to achieve expected financial results, with consequences throughout corporate management.

We find that this phenomenon has implications for labor management, resulting in the intensification of labor processes and the adoption of insecure forms of employment, leading to the fractalization of work. These two mechanisms, added to the indebtedness of workers, constitute three elements for disciplining labor in contemporary capitalism.

We argue that these forms of discipline constitute a subsumption of labor to finance, resulting in an increase in labor exploitation. This formulation of the relationship between financialization and changes in the realm of labor also contributes to understanding the unrealizing potential of social free time in contemporary capitalism.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This paper aims to apply a mixed-methods approach to redefine essential work skill sets, propose components of these skill sets that are necessary for workers in the contexts of emerging market economies (EMEs), examine potential selection tools that should be applied across firms and explain implications for the labour process theory (LPT) of work.

During the first phase of this study, qualitative data was collected from methods, including semi-structured interviews with human resources (HR) experts from the Personnel Management Association of Thailand, top and HR executives and managers of firms across industries in Thailand. Non-participant observations were made during the pre-interview, interview and post-interview stages. Analysis of archival documents and Web-based resources was then conducted. The authors used the qualitative data obtained from the first phase to develop survey instruments for conducting quantitative research during the second phase of this study.

The empirical findings demonstrate that essential work skill sets are “soft skills” that help workers survive and thrive in the business arena in EMEs. These essential work skill sets have implications for the LPT of work in that they play an important role in transferring the power of negotiation from employers to workers in the labour market. Essential work skill sets here can be divided into eight skill domains: (1) ideation and system thinking, (2) information and digital literacy, (3) social skills with appreciation for diversity and inclusion, (4) communication and language, (5) creativity and innovation, (6) emotional quotient (EQ) for self-management and development, (7) growth/outward mindset and (8) cognitive skills for the job role. Within each essential work skill set, there are several skills that workers in the current world of work need to possess (42 skills in total). Additionally, potential selection tools include behavioural observation, behavioural-based interviews, STAR (Situation, Task, Action and Results) interviews, role plays, case studies and simulations, high-pressure interview questions, project assignments, assessment centres, in-depth interview questions and special methods, such as face reading and fingerprint reading. Top and HR managers across industries strongly agree that the eight essential work skill sets and 42 skills are necessary for workers to survive in the business arena in EMEs. They also strongly agree that talent selection tools, especially behavioural-based interviews, are used by their firms to select high-skilled job candidates in the labour market.

Because the eight essential skill sets proposed in this paper are based primarily on the qualitative data obtained from top/HR managers in firms across some industries, generalization to respondents across other industries or across other EMEs may be limited. It is possible that the context of other EMEs may be different from that of Thailand. In this regard, some of the essential work skill sets that are suitable in the case of Thailand may not be suitable in the case of other EMEs. Future studies should thus explore how institutional contexts of other countries/economies shape the definition of essential skill sets and their components, as well as potential selection tools that shall be applied to select high-skilled labour in those contexts.

This paper provides practical implications for top managers and/or HR managers of firms across various industries in EMEs. In particular, managers should internally train and develop their employees/workers to possess the eight essential skill sets: (1) ideation and system thinking, (2) information and digital literacy, (3) social skills with appreciation for diversity and inclusion, (4) communication and language, (5) creativity and innovation, (6) EQ for self-management and development, (7) growth/outward mindset and (8) cognitive skills for the specific job role so that their employees/workers can survive and thrive in the era of the brittleness, anxiety, non-linearity and incomprehensibility of the business world under pandemic conditions. Additionally, top managers and/or HR managers of these firms should apply the potential selection tools proposed in this paper to probe into job candidates’ past experience and behaviours to better predict such candidates’ success at work. In this regard, job candidates/workers should prepare themselves to possess these essential work skill sets so that they can be successful in the business arena and should understand potential selection tools that firms may apply to recruit and select them.

This paper provides social/policy implications for the government and/or relevant public agencies of Thailand and of other EMEs. These governments should encourage firms across industries to invest resources in training and developing their employees/workers to possess those essential work skill sets so that these employees/workers are industry-ready, leading to the alleviation of the problems of skill and mismatch in the labour market.

This paper contributes to the prior literature on human resource management (HRM), the comparative institutional perspective on employment systems based on the varieties of capitalism (VoC) framework and the LPT of work in the following ways: first, this paper fills in the research gap in the field of HRM that calls for studies that explore how the COVID-19 pandemic shapes essential skill sets and skills development among workers within firms (Cooke et al., 2021). Second, this paper provides implications for the LPT of work regarding how essential work skill sets are likely to return the power of negotiation from employers to workers in EMEs during the current situation. Third, the VoC framework tends to focus on only two types of economies, liberal market economies and coordinated market economies. However, this paper examines essential work skill sets and potential screening tools in the context of the underresearched country of Thailand, an EME. In fact, the Thai labour market is quite different from that of other EMEs labour markets, as it is impacted by an aging workforce. This paper contributes to the literature on comparative institutional perspectives on employment systems as it redefines essential work skill sets, proposes various components of these skill sets among workers and examines potential selection tools that are applied across firms located in EMEs.

The purpose of this paper is to study the spillover effects of foreign direct investment (FDI) on skilled–unskilled wage inequality in the Indian manufacturing industries.

The authors show theoretically with a model of spillover that if foreign firms (receiving FDI) have a negative spillover effect on domestic firms (not receiving FDI), then the level of capital and skilled workers in the domestic firms falls down. Consequently, the authors conduct an empirical analysis by using system GMM estimation technique on the firm-level data of the Indian organised manufacturing sector.

The authors show that wage inequality worsens when there is negative spillover effects like competition spillover or skill spillover effect of FDI in India.

To the best of the authors’ knowledge, this is the first attempt to measure the various spillover effects of FDI on the wage inequality in the Indian manufacturing industries by using firm-level data.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

The farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.

A meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.

The results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.

Although the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.

The contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

The purpose of this paper is to analyze the impact of the coronavirus (COVID-19) pandemic on participation and time allocated to work from home (WFH) by ethnic/racial group.

The authors employ USA time-use data [American Time Use Survey (ATUS)] for the 2017–2020 period and a parametric approach in their analysis.

Estimates show that the time allocated to WFH increased during COVID-19, especially for women. This increase is likely driven by more workers shifting to WFH (higher participation) rather than by longer hours worked by those who already teleworked. The authors also find relevant differences in the impact of COVID-19 on WFH by ethnic/racial group. Among ethnic/racial groups, only Asians increased WFH compared to White Americans. Within this ethnic group, the authors find significant differences across genders. Asian men increased participation in WFH, whereas Asian women increased both participation and hours worked, compared to White American women. Differences in this racial/ethnic group could be explained by previous research, which demonstrates a higher ability of Asians to perform job tasks remotely. However, this finding could also be attributed to an increase in discrimination during the COVID-19 pandemic.

This paper contributes to the recent and limited literature exploring the heterogeneous impact of COVID-19 on participation and time allocated to WFH by ethnic/racial group. Understanding the mechanisms driving vulnerable populations' abilities to work during socioeconomic downturns is of high policy importance.