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The purpose of this study is to address the impact of three issues: degree of skills, favorable working environment and R&D on manufacturing productivity of labor‐intensive industries.

Convenience sampling method has been used to conduct this study. Three categories of labor‐intensive manufacturing industries (A, B and C) have been chosen to perform this research. Industrial category A represents the manufacturing operations which are based on skill of labor. Category B is a group of industries which provides a favorable working environment to utilize the potential of skill in manufacturing process. Category C is a specialized group of industries and its manufacturing process is dependent on R&D. Input–output data for manufacturing operations of the sample industries have been analyzed by using standard statistical techniques to establish the relationship between dependent and independent variables.

The degree of skill and productivity is positively correlated, but not strongly (r<0.5). The study found that productivity is positively (r>0.5) associated with favorable working environment. However, a significantly positive correlation (r>0.7) is found between R&D expenditure and productivity. The study concludes that a higher degree of skills, favorable working environment and R&D are important inputs to a labor‐intensive manufacturing process, which is positively associated with productivity.

Manufacturing productivity is an important parameter of industrial growth, and this paper addresses this issue. The current work addresses the garments sector, i.e. a part of the labor‐intensive industries. Though this work is focused on only one part of this sector; the findings of this study have significant policy implications. The results would be useful for manufacturing business executives and policy makers.

This study addresses the important issue of productivity of labor‐intensive manufacturing industries, and generates quantitative evidence of the impact of degree of skills, favorable working environment and R&D on productivity. The generated information enriches the present knowledge stock of manufacturing systems. The findings could be the basis for further academic research on manufacturing systems.

This study is designed to examine the impact of favorable working environment (FWE) and R&D on manufacturing productivity of labor intensive industries. More specifically, the purpose of this study is to generate quantitative evidence of the effect of FWE and R&D‐based manufacturing process on outputs and productivity.

Convenience sampling method has been used to conduct this study. This method provides the opportunity for selecting those manufacturing industries that are convenient to get access for collecting relevant information. Three categories of labor intensive manufacturing industries such as category A, B and C have been chosen to perform this research. Industrial category A represents the manufacturing operations which are based on skill of labor. Category B is a group of industries which provides the FWE the ability to utilize the potential of skill in the manufacturing process. However, category C is a specialized group of industries and its manufacturing process is dependent on R&D. The operating data of inputs cost and the revenue of corresponding outputs have been gathered from audited documents of the relevant sample industries and the data have been analyzed by using standard statistical techniques in order to establish the relationship between dependent and independent variables.

It is found that the industrial category B has spent about 1 percent of revenue on FWE and gained 9.5 percent higher productivity compare to industrial category A. However, the result has shown that the expenditure on FWE is positively associated with productivity (r<0.5). Whereas, the study has revealed that industrial category C has spent about 1.5 percent of revenue on R&D activities for improving manufacturing process and gained 20 higher productivity compare to industrial category A. Nevertheless, the expenditure on R&D is strongly correlated with productivity (r>0.7). The study concludes that FWE as proxy of job satisfaction of workforce and R&D on manufacturing process are value‐added inputs for labor intensive industries and it is positively associated with manufacturing productivity.

This paper presents three original case studies on labor intensive manufacturing industries. This study has addressed an important issue of labor intensive manufacturing industries and generated quantitative evidence of the impact of FWE and R&D activities on productivity. These issues have been well researched in developed and many developing countries in capital‐intensive industries, but no dedicated study is available that has addressed this issue from the perspective of the highly labor intensive industries such as the garment industry. The findings of this research would enrich the present knowledge stock of manufacturing systems. Eventually, the findings would be the basis for further research on manufacturing process for enhancing performance. Based on this concept, this study would be valuable to policy makers, academics and government agencies.

Several studies have shown that the mechanism of labour-intensive construction (LIC) projects can mitigate high unemployment and create skilled development, especially in developing nations. The guidelines and practices for implementation may have faced some encumbrances in some countries. Whether the current guidelines and practices for municipal infrastructure support agent (MISA) to execute LIC projects face hindrances in South Africa has yet to receive in-depth studies. Thus, this study attempts to proffer policy solutions to improve the proposed revised guidelines and practices for MISA in LIC project execution in South Africa.

The study's objectives were accomplished via a combination of 16 virtual interviews of built environment professionals and government officials involved in LIC project execution in South Africa and supported by the analysed documents. A thematic approach was used to analyse the data and presented two main themes.

Findings show lax enforcement of discretionary funds, lax institutional capacity and inadequate individual skills, among others, as the gaps in existing South Africa's LIC guidelines and practices. Also, policy solutions to address the gaps were proffered.

The suggested feasible policies will improve the proposed revised guidelines and practices for MISA in LIC project execution in South Africa. This guide will promote the development of individual skills, institutional capacities and increase employment across South Africa.

This study promotes the use of LIC to create employment and contribute to proffering measures that will improve the proposed revised third edition of the guidelines and practices for MISA to execute LIC.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The purpose of this paper is to study the cutting performance of high-speed regime end milling of AISI 4340 by investigating the tool life and wear mechanism of steel using the minimum quantity lubrication (MQL) technique to deliver the cutting fluid.

The experiments were designed using Taguchi L9 orthogonal array with the parameters chosen: cutting speed (between 300 and 400 m/min), feed rate (between 0.15 and 0.3 mm/tooth), axial depth of cut (between 0.5 and 0.7 mm) and radial depth of cut (between 0.3 and 0.7 mm). Toolmaker microscope, optical microscope and Hitachi SU3500 Variable Pressure Scanning Electron Microscope used to measure tool wear progression and wear mechanism.

Cutting speed 65.36%, radial depth of cut 24.06% and feed rate 6.28% are the cutting parameters that contribute the most to the rate of tool life. The study of the tool wear mechanism revealed that the oxide layer was observed during lower and high cutting speeds. The former provides a cushion of the protective layer while later reduce the surface hardness of the coated tool

A high-speed regime is usually carried out in dry conditions which can shorten the tool life and accelerate the tool wear. Thus, this research is important as it investigates how the use of MQL and cutting parameters can prolong the usage of tool life and at the same time to achieve a sustainable manufacturing process.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

This study aims to identify the intention to purchase Halal food products amongst non-Muslim consumers in Malaysia, moderated by the acculturation effect.

A structured close-ended questionnaire was used to gather data through the random distribution of 397 non-Muslim consumers from the Alumni network of several private higher education institutions in Malaysia.

The collected data was analyzed through the structural equation modelling technique using partial least squares with SmartPLS 3.0. The result indicated that attitude, subjective norms and perceived behavioral control were positively influenced by the purchase decision of Halal food products amongst non-Muslim consumers in Malaysia. Apart from that, the acculturation effect moderates the relationship between attitude and intention to purchase.

This finding will contribute to academics, Halal food makers and government in understanding the Halal food purchase intention amongst non-Muslim consumers in Malaysia.

The outcome of this study can be used as an input for Halal entrepreneurship in terms of marketing and operation strategy. On the government aspect, this study also provides an implication on national public policy and strategic economic planning in developing overall national Halal policy.

The social harmonization amongst the multiple races in Malaysia is partially contributed through the acculturation effect. The acculturation effect has been reflected through the food choice decision amongst Malaysian, despite of different religious belief and home culture background.

Research in studying Halal food purchase intention amongst non-Muslim consumers are scarce. This research is able to reinforce the theory of planned behavior model in dealing with Halal food choice decisions, taking into consideration of acculturation effect.

The purpose of this paper is threefold: first, to analyse the current state of the literature on the relationship between quality management (QM) and productivity as a performance indicator; second, to identify the key constructs of QM practices related to productivity; and, finally, to reveal whether QM can actually be regarded as a determinant of productivity.

This research was carried out through a systematic literature review, considering 150 papers that studied this relationship between 1997 and 2017 and another 37 papers on the internal determinants of productivity.

The findings revealed that human resource management, top management and process management were the more relevant constructs of QM practices related to productivity. In addition, 89 per cent of the internal determinants of productivity were related to the proposed constructs of QM practices, which suggest that QM is a determinant factor of productivity.

This review analysed the literature on the relationship between QM and productivity, as few studies have done before, generating original, interesting and useful findings that can guide future research and that also represent a useful tool for researchers, practitioners, managers and policy makers.