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Aerospace field is demanding a material with superior strength and high resistance against wear, tear and corrosion. The current study aimed to develop a new material with high performance to be applicable in aerospace field

A metal matrix composite AA8090-WC-ZrC was fabricated using stir casting method and its tribological behavior was investigated. Totally, five composites viz. AA/Z, AA/W, AA/WZ (1:3), AA/WZ (1:1) & AA/WZ (3:1) were prepared. Micro hardness, tensile and wear study were performed on the fabricated composites and the results were compared with AA8090 alloy

Vickers hardness test resulted that the AA/W composite showed the higher hardness value of 160 HB compared to other materials due to the reinforcing effect of WC particles with high hardness. Tensile test reported that the AA/W composite displayed the maximum tensile strength of 502 MPa owing to the creation of more dislocation density. Further, wear study showed that the AA/W composite exhibited the least wear rate of 0.0011 mm3/m because of the more resisting force offered by the WC particles. Furthermore, the AA/W composite showed the slightest mass loss of 0.0028 g and lower COF value of 0.31 due to the hinder effect of WC particle to the movement of atoms in AA8090 alloy

This work is original in the field of aerospace engineering and materials science which deals with the fabrication of AA8090 alloy with the reinforcement particles such as tungsten carbide and zirconium carbide. The impact of the combination of hybrid particles and their volume fractions on the tribological properties has been investigated in this work. This work would provide new scientific information to society.

This study aims to explore the “psychological contract of safety” (PCS), a key factor in the safety climate (SC), which relies on the behavioral safety actions of workers at construction sites. While numerous factors have been identified in various sectors across different countries, there is a consensus among researchers that there is a dearth of common assessment factors specifically for the Indian construction industry (ICI). Therefore, this study undertakes a systematic review of existing literature to identify the factors that determine PCS in construction and to ascertain the relative importance index (RII) of these variables and their interrelationships using structural equation modelling (SEM).

A structured survey was conducted among 420 professionals in the ICI to collect data. This data was then analyzed using descriptive and inferential statistical methods to derive results.

The findings of the study indicate that PCS factors have a significant impact on the construction industry (CI). The inferential analysis ranks “Safety System” as the top factor with the highest RII value. The chi-square results highlight two key SC factors that enhance and regulate an organization’s safety performance. The SEM results reveal that SC factors contribute to the improvement of PCS and influence worker safety behavior.

The outcomes of this study will be beneficial for stakeholders aiming to improve safety at construction sites and enhance safety performance by fulfilling the mutual safety obligations of employers and employees and by improving safety norms, procedures and policy-making. This paper also provides a theoretical framework for scholars to reassess the results in various contexts.

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.

This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.

The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.

The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

More attention should be paid to human resource management practices, as they play a vital role in the retention of the skilled workforce for improved competitive advantage and reduced skill shortage. This study aims to examine the impact of engineers' satisfaction regarding fairness in key human resource management practices such as performance management, compensation and pay, and employee relations on their intention to stay in Indian construction firms.

This research was undertaken using a questionnaire survey conducted among 230 engineers working in Indian construction firms. Data collection was done by using self-administered questionnaires. The quantitative analysis of the collected data was carried out. The constructs involved in the study were validated using factor analysis. The correlation and regression analyses were used to examine the relationship between engineers' satisfaction with fairness in human resource practices and their intention to stay.

Results showed that satisfaction with fairness in human resource practices, such as performance management and employee relations are positively related to engineers' intention to stay, whereas satisfaction with fairness in employee relation practices highly predicts engineers' intention to stay.

This study adds to the body of knowledge by examining the impact of engineers' satisfaction with fairness in human resource practices on their intention to stay in the Indian construction sector, which is an under-researched area. Satisfaction with fairness in employee relation practices is identified as the strongest predictor of engineers' intention to stay. The finding of the research could help construction companies develop human resource practices and policies to promote the retention of construction professionals, particularly engineers, who work for them.

The nature of construction works has a negative impact on physical, mental and emotional well-being and makes it difficult for the construction industry to attack and retain its workforce. The current study seeks to integrate the current knowledge focused on work–life balance (WLB) in the industry into an understandable whole.

An interpretivist philosophical approach was adopted using a bibliometric review and a narrative review of existing studies from both Scopus and Google databases. The Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps from the bibliographic data garnered.

The study reveals that the prominent factors influencing the WLB of the construction workforce are organizational culture, salary earned, heavy workload, long working hours and inflexible working time. The recent WLB discourse is on organisational commitment, job satisfaction and workplace dynamics. While WLB areas for further exploration are job stress, safety performance, employee attrition and an ageing workforce. Meanwhile, Africa and South America are still lagging in WLB research.

The findings reported here will assist stakeholders in identifying appropriate WLB initiatives that can be used to improve the well-being of the construction workforce. Also, the gaps in knowledge for further research were highlighted.

The findings reveal current trends and a road map for future studies on WLB in construction. It also reveals prominent factors influencing the WLB of workers in the construction industry.

This paper aims to deal with the selection of the sustainability-oriented Green Lean Six Sigma (GLS) project for the manufacturing industry in the complex decision-making environment. Moreover, the study also proposes a GLS implementation framework for improved organizational performance.

GLS project selection has been done based on the six sustainability-oriented criteria formed from 17 sub-criteria (found from the literature and developed by authors). The weights of the criteria have been determined through the entropy method. The projects have been ranked based on the criteria through the advanced decision-making approach: grey relation analysis (GRA). The results of the study were validated using best worst method and sensitivity analysis.

It has been found that the productivity-related criterion is the most significant among other criteria with entropy weight of 0.2721. GRA has been used in this research work to rank the potential GLS projects in a manufacturing industry based on six sustainability criteria, to select a project that exhibits the maximum potential for sustainable improvement. The machine shop has been found as the most significant GLS project with grey relation grade of 0.4742.

The present study facilitates practitioners and industrial managers to implement an inclusive GLS approach for improved sustainability dynamics through effective GLS project selection and implementation framework.

With increased globalized competition in recent times, new projects are being considered as the foundation stone for organizational success. The decision-making becomes quite complex to select an effective project due to the intriguing nature of various criteria, sub-criteria and different aspects of sustainability. To the best of the authors’ knowledge, the present study is the first of its kind that provides ways for the selection of sustainability-oriented GLS projects.

Using coconut shell aggregates (CSA) in concrete benefits agricultural waste management and reduces the demand for mineral resources. Several studies have found that concrete containing CSA can achieve strengths that are comparable to regular concrete. The purpose of the present work is to evaluate the concrete’s durability-related properties to supplement these earlier findings.

Cylindrical specimens were prepared with a constant water–cement ratio of 0.50 and CSA content ranging from 0% to 50% (at 10% increment) by volume of the total coarse aggregates. The specimens were cured for 28 days and then tested for density, surface hardness, electrical resistivity and water sorptivity. The surface hardness was measured to describe the concrete resistance to surface wearing, while the resistivity and sorptivity were evaluated to describe the material’s resistance to fluid penetration.

The results showed that the surface hardness of concrete remained on average at 325 Leeb and did not change significantly with CSA addition. The distribution of surface hardness was also similar across all CSA groups, with the interquartile range averaging 59 Leeb. These results suggest that the cement paste and gravel stiffness had a more pronounced influence on the surface hardness than CSA. On the other hand, concrete became lighter by about 9%, had lower resistivity by 80% and had significantly higher initial sorptivity by up to 110%, when 50% of its natural gravel was replaced with CSA. Future work may be done to improve the durability of CSA when used as coarse aggregate.

The present study is the first to show the lack of correlation between CSA content and surface hardness. It would mean that the surface hardness test may not completely capture the porous nature of CSA-added concrete. The paper concludes that without additional treatment prior to mixing, CSA may be limited only to applications where concrete is not in constant contact with water or deleterious substances.

This paper presents a case study conducted in a sugar mill. The multi‐level lot‐sizing model suggested by Gunasekaran where the whole manufacturing system modelled as a function of total system cost (TSC) is used for this application. This study deals with minimising the TSC of a multi‐stage, multi‐facility and multi‐product manufacturing system in which the buffer in between the stages is not allowed. The model is applied to find out the TSC and hence the fluctuating purchase prices of raw material. The consequence of implementing different costs that may occur due to change in government policies is analysed. This work has been carried out in an IBM/PC compatible system.

Green or sustainable supply chain management (GSCM/SSCM) has in recent years attracted much attention from academia and practitioners in all part of the world. In recent years, all humanity has experienced severe climate change which is widely attributed to human activity. Harmful emissions have made a major contribution to recent climate change which presents major challenges and threats to the entire human race in form of global warming, earthquakes, hurricanes, tsunami and floods. The purpose of this paper is to propose a conceptual GSCM/SSCM framework contributing to knowledge-based view theory and systems theory (ST) and provide an exhaustive list of further research directions.

In this paper the authors have used a systematic literature review to identify building blocks of the conceptual framework, which is the principal contribution of the present paper.

In this paper the authors have proposed a conceptual framework for sustainable supply chain network and at the end the authors have outlined further research directions.

The current paper is an attempt to develop a conceptual framework which is grounded in knowledge-based theory. The study helps to extent the prior works which lacks theory focused approach.

The present work has immense theoretical value and can be useful to the policy makers or practitioners engaged in GSCM practices.

A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain partners. The purpose of this paper is to help design a system that strikes a balance between the strategic objectives of the focal firm and its supply partners vis-à-vis the requirements of supply chain performance (cost, quality, speed and customer taste).

A theoretical framework on the strategic supply chain performance measurement system is developed based on existing literature and subsequently tested using a survey on 136 successful manufacturing organizations in India. The organizations were clustered into three strategy types and compared using analysis of variance on ranks to look for differences in preference for performance parameters.

The study examined the five dimensions of the supply chain practices, namely, strategic supply/distribution network, customer relationship, internal operations, information sharing and social and environmental responsiveness. The empirical results demonstrate the inclusion of business strategy orientation in designing today’s supply chain and hence its performance measurement system. Not supported hypotheses were addressed in the light of contextual factors.

The study is confined to finding preferences of non-financial aspects of supply chain performance and tier-1 suppliers. The research helps better design and benchmark supply chain performance metrics, based on the strategic choice of the firm.

This paper highlights the shortcomings in the existing performance measurement and gaps in the existing literature in the supply chain context. Further, it gives a holistic view of strategic supply chain performance measurement design.