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Article
Publication date: 28 March 2024

Nikesh Nayak, Pushpesh Pant, Sarada Prasad Sarmah and Raj Tulshan

Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of…

Abstract

Purpose

Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.

Design/methodology/approach

This study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.

Findings

The findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.

Originality/value

Given the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 5 October 2022

Kesavan Manoharan, Pujitha Dissanayake, Chintha Pathirana, Dharsana Deegahawature and Renuka Silva

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries…

Abstract

Purpose

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries to face various challenges. This study aims to quantify the variations in the performance and productivity levels of labour in building construction projects through the applications of effective work-based training components.

Design/methodology/approach

A comprehensive literature review and a series of experts’ discussions with action-oriented communication approaches were conducted to develop a set of practices related to labour training, performance assessment and productivity measurements within a framework. The developed practices were applied to around 100 labourers working on nine building construction projects through a construction supervisory training programme.

Findings

The study presents the detailed patterns of the significant changes in labour performance and productivity levels. The majority of trained labourers have grown to perform the work process with some relevant theoretical and operational knowledge and skills. The overall results spotlight the significant behavioural changes that can be observed in workforce operations by improving labour performance, which resulted in implementing effective labour-rewarding practices within a framework.

Research limitations/implications

Although the study findings were limited to the Sri Lankan context, the proposed practices can be applied to the industry practices of the construction sector of other developing countries and the other developing industries in similar ways/scenarios.

Practical implications

The study outcomes contribute to uplifting the work qualities of labourers with life-long learning opportunities and unlocking the potential barriers for expanding the local labour supply while controlling the excessive inclination of the local firms towards foreign labour. This paper describes further implications and future scopes of the study elaborately.

Originality/value

The study provides generalised mechanisms and practices that transform the labour characteristics and add new attributes for strengthening the values of construction supervision practices to obtain well-improved work outputs. The study outcomes reinforce the chain relationships among the training elements, labour performance and productivity levels, leading to upgrading current planning and operational management practices, especially adding constructive mechanisms in resource levelling and productivity benchmarking practices.

Details

Construction Innovation , vol. 24 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 10 October 2023

Vivek Gopi and Saleeshya P.G.

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used…

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Abstract

Purpose

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

Design/methodology/approach

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

Findings

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

Research limitations/implications

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

Practical implications

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

Originality

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.

Details

Journal of Modelling in Management, vol. 19 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 24 November 2023

Vikas Ghute and Mahesh Deshpande

The paper aims to identify the effect of ignorance of correlatedness among process observations and to implement new sampling schemes; skip and mixed sampling, in order to reduce…

Abstract

Purpose

The paper aims to identify the effect of ignorance of correlatedness among process observations and to implement new sampling schemes; skip and mixed sampling, in order to reduce the effect of autocorrelation on process capability index (PCI) Cpm.

Design/methodology/approach

Autocorrelated observations are generated using autoregressive process of order two (AR (2)) using Monte Carlo simulations. The PCI is computed based on these observations assuming the independence. The skip and mixed sampling schemes are then used to form sub-groups among correlated observations. The PCI obtained using sub-groups from skip and mixed sampling schemes are assessed using sample mean and sample standard deviation.

Findings

The paper provides empirical insights into how the effect of autocorrelation decreases in the estimated value of PCI Cpm. The use of new sampling schemes, skip and mixed sampling, reduces the effect of autocorrelation on estimates of PCI Cpm.

Originality/value

This paper fulfills an identified need to study how to reduce the effect of autocorrelation on PCI Cpm.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 12 December 2023

M.A. Xianglin, Haochen Cai, Qiming Yang, Gang Wang and Kun Mao

This paper establishes a quality model for automation assembly of range hood impeller based on generalized grey relational degree, it improves the debugging efficiency of the…

Abstract

Purpose

This paper establishes a quality model for automation assembly of range hood impeller based on generalized grey relational degree, it improves the debugging efficiency of the newly developed assembly workstation.

Design/methodology/approach

First, spot check the trial production impellers and obtain three indexes that reflect the assembly quality of the impellers. Then, analyze the parameters that affect the assembly quality of the impeller using grey relational analysis (GRA), establish a model for the assembly quality of the range hood impeller based on the generalized grey relational degree and identify the main parameters. After that, analyze the transmission structure of automation assembly workstation, identify the reasons that affect parameters and propose improvement plans. Finally, a trial production is conducted on the automation assembly workstation after adopting the improved plan to verify the quality model of impeller automation assembly.

Findings

The research shows that compared to manual assembly, the automation assembly quality of the impeller using GRA model has been improved, shortening the debugging cycle of the newly developed assembly workstation.

Practical implications

The newly developed automation equipment will have some problems in the trial production stage, which often rely on the experience of engineers for debugging. In this paper, the automation assembly quality model of range hood impeller based on GRA is established, which can not only ensure the quality of finished impeller but also shorten the debugging cycle of the equipment. In addition, GRA can be widely used in the commissioning of other automation equipment.

Originality/value

This study has developed a set of impeller automation assembly workstation. The debugging method in the trial production stage is beneficial to shorten the trial production time and improve the economic benefits.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 25 January 2024

Ayesha Akter Sumi, Saif Ahmed and Syed Shah Alam

This study aims to examine the impact of Islamic teachings on environmental corporate social responsibility (CSR) practices in Bangladesh, a country where Islamic principles are…

Abstract

Purpose

This study aims to examine the impact of Islamic teachings on environmental corporate social responsibility (CSR) practices in Bangladesh, a country where Islamic principles are profoundly influential.

Design/methodology/approach

Using a mixed-methods research approach (quantitative study with close-ended questionnaire and qualitative study with semistructure interview), this study aims to explore the role of individual characteristics and organizational contexts in environmental CSR practices. The study uses a robust analytical framework encompassing variance inflation factor, orthogonal loading, Cronbach’s alpha, composite reliability and average variance extracted to assess the reliability and validity of these metrics.

Findings

Thematic analysis reveals the motivations, attitudes and challenges experienced by organizational leaders in aligning Islamic ethics with environmental stewardship, whereas the quantitative results provide empirical support for the relationship between various organizational practices (denoted as M#1 to M#8) and environmental CSR.

Originality/value

The findings of this study illuminate the potential benefits of tailoring CSR policies to fit within specific religious and cultural frameworks, offering both theoretical contributions and practical insights.

Details

Journal of Islamic Marketing, vol. 15 no. 4
Type: Research Article
ISSN: 1759-0833

Keywords

Article
Publication date: 26 March 2024

Samira Joudi, Gholamreza Mansourfar, Saeid Homayoun and Zabihollah Rezaee

Considering the standards developed by the Sustainability Accounting Standards Board (SASB), this study aims to examine whether the link between material sustainability and…

Abstract

Purpose

Considering the standards developed by the Sustainability Accounting Standards Board (SASB), this study aims to examine whether the link between material sustainability and financial performance depends on the extent to which the company is oriented toward stakeholders.

Design/methodology/approach

To test the predictions, 13,942 firm-year observations from 43 different countries are used, covering the period from 2010 to 2019. Using a hand-mapping approach to match the indicators suggested by the SASB with those of the ASSET4, the authors realize that there are 170 material sustainability indicators among 466 indicators of the ASSET4. The authors use three different methods to verify if the materiality matters, including the alphas obtained from the Fama and French factor models, comparing the average abnormal returns of the portfolios and the bootstrapped Cramer technique.

Findings

The findings show that companies investing in material sustainability activities perform better than those investing in immaterial activities. Also, consistent with the theoretical foundations, the authors find that the effect of investing in material sustainability activities is more pronounced in stakeholder-oriented countries than that in shareholder-oriented countries. The results are robust to a battery of sensitivity tests.

Research limitations/implications

Owing to COVID-19 in late 2019, data from 2020 to 2022 have not been used to obtain reliable results.

Practical implications

The results obtained in the current research provide valuable guidance for investors to make investments considering the degree of materiality of sustainability activities in different industries. It also helps managers to increase the company’s financial performance, make efficient decisions related to investment in sustainability activities and find investment strategies on the material sustainability issues in their industries.

Social implications

This study provides a clearer understanding of investment in sustainability activities in different industries by separating material and immaterial sustainability activities in stakeholder and shareholder-oriented countries, and the results obtained can change the perspective of investors and company managers regarding investing in such activities in different countries. Investing in more materiality sustainability activities than the immateriality dimension can be new opportunities for companies to achieve predetermined goals, help retain and attract business partners or be a source of innovation for new product lines or services. Internal morale and employee engagement may increase while increasing productivity and firm performance. This discussion opens the way for future research.

Originality/value

This study provides insight into the effect of investing in material and immaterial sustainability activities in different industries on the company’s performance in shareholder and stakeholder-oriented countries.

Details

Corporate Governance: The International Journal of Business in Society, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1472-0701

Keywords

Article
Publication date: 21 March 2024

Graeme Newell and Muhammad Jufri Marzuki

Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery…

Abstract

Purpose

Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors.

Design/methodology/approach

Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio.

Findings

Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios.

Practical implications

Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward.

Originality/value

This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming.

Details

Journal of Property Investment & Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 26 May 2023

Neha Seth and Deepti Singh

This paper aims to provide a bibliometric review and visualisation analysis of the literature on Sustainable Stock Indices (SSI) between January 2001 and March 2022. The purpose…

Abstract

Purpose

This paper aims to provide a bibliometric review and visualisation analysis of the literature on Sustainable Stock Indices (SSI) between January 2001 and March 2022. The purpose of performing this bibliometric analysis is to empirically report the trend, intellectual structure, knowledge development directions and identify prospective research topics in the area of SSI.

Design/methodology/approach

A total of 222 publications were selected after evaluating, identifying and synthesising the extensive publications using the Preferred Reporting Items for the Systematic Reviews and Meta-Analyses (PRISMA) approach. The articles were extracted from the databases of SCOPUS, Web of Science and Google Scholar. The study uses VOSviewer and RStudio software to answer four research questions.

Findings

The results signify that there has been a considerable increase in the level of research considering SSI. Further, the study shows that SSI is among the top five trending keywords in the research related to finance and environment. Most papers considered as a sample for this study are based on Dow Jones Sustainable Indices. Noteworthy, very few economies are participating in this research domain, and the significant contribution is from the developed countries.

Practical implications

The present review paper may assist the researchers in identifying the trending research topics in this domain. It may serve as a roadmap for several further studies in the area.

Originality/value

This study is unique in terms of reviewing the literature based on SSI. Further, it provides a holistic view of the current trend, global position and research hotspots of SSI, which has important implications for future research.

Details

Qualitative Research in Financial Markets, vol. 16 no. 2
Type: Research Article
ISSN: 1755-4179

Keywords

Article
Publication date: 26 September 2023

Mohammed Ayoub Ledhem and Warda Moussaoui

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric…

Abstract

Purpose

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

Design/methodology/approach

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

Findings

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

Practical implications

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

Originality/value

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Details

Journal of Modelling in Management, vol. 19 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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