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This paper aims to assure the selection of the most suitable very light business aircraft which is preferred by the passengers based on effectiveness and aesthetic comfort. The proposed approach to determine the light business jet aircraft would provide long-range, less travel time, cozy seating arrangements, on-board lavatory facility, other aesthetic ambiance (audio systems, light systems and temperature-noise control) and appliances at reasonable flight cost.

The selection of a light business jet is obtained through multi-criteria decision-making based on the speed limit ranges from 0.57 to 0.70 Mach number and the distance traveled up to 3,000 km with the best aesthetic comfort level. To validate the approach, case studies of five aircrafts such as Honda Jet HA 420, Cessna Citation jet M2, Embraer Phenom 100, Eclipse 550 and Cessna Citation Mustang are performed. To obtain the best suitable business jet, criteria importance through intercriteria correlation (CRITIC) and technique for order performance by similarity to ideal solution (TOPSIS) is used to determine the rankings of listed aircraft.

The study concludes that the Cessna Citation jet M2 is chosen as the best Very Light Jet (VLJ) on the basis of speed, range, weight, cost, aesthetic and comfort. Based on the sensitivity, mean absolute percentage error (MAPE) and symmetric mean absolute percentage error analysis (sMAPE), the most and least sensitive criteria for a business jet came out to be cost and speed, respectively.

A real case study for several parameters of five different jets such as Honda Jet HA 420, Cessna Citation jet M2, Embraer Phenom 100, Eclipse 550 and Cessna Citation Mustang are shown in this paper. Based on the case study numerical values are assigned with speed, range, weight, cost, aesthetic and comfort which are applied with CRITIC and TOPSIS to obtain the most suitable business jet among the five mentioned jets which are rarely found in the literature.

This paper aims to study the effect of the addition of water treatment plant sludge (WTPS) and processed tea waste (PTW) on the properties of burnt clay bricks. The reuse of WTP sludge as a raw material for brick production is a long-term approach, to sludge disposal, for economic and environmental sustainability. Sludge have been added at 10, 20, 30 and 40% and processed tea waste at 5% (by weight) in replacement of clay for brick manufacturing. Each batch of hand-moulded bricks was fired in a heat controlled furnace at a temperature of 990°C. The compressive strength has been found to increase with the sludge content, however, a slight decrease in compressive strength was observed with tea waste addition. Further, PTW addition has improved the thermal insulation of bricks as compared to controlled bricks. The study shows that 40% WTPS, 5% PTW and 55% natural clayey soil can be considered as an optimum mix for bricks with good compressive strength as well as improved thermal insulation property.

Four different mixing ratios of sludge at 10, 20, 30 and 40% of the total weight of sludge-clay mixtures were used to make bricks. Similarly, PTW was investigated as a substitute of natural clayey soil in brick manufacturing. Each batch of hand-moulded bricks was fired in a heat controlled furnace at a temperature of 990°C. The physical, mechanical and engineering properties of the produced WTPS bricks and PTW bricks were determined and evaluated according to various Indian Standard Codes of Specification for burnt clay bricks and certain reference books.

The results exhibited that WTP sludge and PTW can be used to produce good quality brick for various engineering applications in construction and building. Increasing the sludge content increases the compressive strength. Moreover, thermal insulation of PTW bricks depicted an upward trend when compared to controlled bricks. Hence, an optimum mixture of 40% WTPS, 5% PTW and 55% natural clayey soil was found, at which bricks showed good compressive strength as well as improved thermal insulation property of the building material.

The present work provides a sustainable solution for disposal of WTP sludge and tea waste. Utilization of these waste materials in brick manufacturing is viable and economic solution.

Bricks with 40% WTP sludge and 5% processed tea waste proved to be economic, technically sound for construction purposes with added thermal insulation properties.

Bulk amount of waste such as WTP sludge is a threat to society owing to its environmental implications of disposal. Authors propose to use WTP sludge and tea waste for brick manufacturing and provide a solution to its disposal.

Water treatment plant sludge along with tea waste have not been tried for brick manufacturing so far. Hence, the composition is new in itself and also have resulted into good performance.

The purpose of this paper is to provide a return on investment (ROI) based review of human resources (HR) analytics. The objectives of this paper are twofold: first, to offer an integrative analysis of the literature on the topic of HR analytics in order to provide scholars and practitioners a comprehensive yet practical ROI-based view on the topic; second, to provide practical implementation tools in order to assist decision makers concerning questions of whether and in which format to implement HR analytics by highlighting specific directions as to where the expected ROI may be found.

This paper is a review paper in which a four-step review and analysis methodology is implemented.

Study results indicate that empirical and conceptual studies in HR analytics generate higher ROI compared to technical- and case-based studies. Additionally, study results indicate that workforce planning and recruitment and selection are two HR tasks, which yield the highest ROI.

The results of this study provide practical information for HR professionals aiming to adopt HR analytics. The ROI-based approach to HR analytics presented in this study provides a robust tool to compare and contrast different dilemma and associated value that can be derived from conducting the various types of HR analytics projects.

A framework is presented that aggregates the findings and clarifies how various HR analytics tools influence ROI and how these relationships can be explained.

The purpose of this paper is to provide details of a survey conducted into 300 manufacturing SMEs from a range of different industrial sectors. The survey investigates, over a three‐year period, the attitudes towards and benefits obtained by SMEs through the adoption of Advanced Manufacturing Technologies (AMT). Its purpose is to analyse and disseminate these survey data to academics and industrialists.

The paper uses a research survey of 300 manufacturing SMEs. Analysis of the findings is provided and SME characterisation tables are developed.

The paper finds that characterisation, compatibility and innovativeness of SMEs towards AMT implementation were found to vary considerably with the SMEs surveyed. From the survey information, the paper develops a classification system based on the capabilities of these companies to implement Advanced Manufacturing Technologies. The paper will then characterise SME attitudes towards the development of AMT. The paper finally proposes a strategic model for the effective introduction and application of AMT in SMEs.

The survey is limited to SMEs and provides a strong body of evidence relating to AMT development with these companies.

The paper proposes a strategic model for the effective introduction and application of AMT in SMEs. The creation of a generic AMT implementation model provides a framework for a wider number of SMEs to introduce AMT into their respective organisations, since it provides for a systematic approach for SMEs to introduce AMT in an efficient and effective manner, thus reducing implementation costs, minimises risk of project failure and improves project management efficiency.

This paper is the first to explore in depth the AMT implementation issues within SMEs from large‐scale survey data. It not only analyses the survey data but also proposes a model for change, which aims to develop a more structured approach to AMT implementation in SMEs. Therefore, this work will make a contribution to this under‐researched area.

In software development (SD), practitioners have realized the importance of lean thinking. A new term “Leagile” is coined, which is an integrated approach of traditional lean and agile thinking to managing the operations. The study aims to investigate the application of the Leagile principles in a new sector and establish a relationship between the adoption of Leagile approach and operational performance (OP) in SD organizations.

Empirical research is conducted to investigate the linkage between the Leagile principles and operational measures. Data is collected through surveys from 256 SD industries located in 11 states of India and analysed using the structural equation modelling approach.

The practitioners envisage a positive impact of adoption of Leagile principles on OP of SD organizations, but one of the principles, i.e. perfection, is unable to influence the performance.

The study contributes by authorizing the contribution of Leagile principles towards OP of SD organizations. The outcomes will motivate the practitioners to enhance the adoption of Leagile principles in SD organizations.

This study intends to reveal the existing research stream and predict future research avenues for lean healthcare (LH). This paper analyzes the progress of LH research and identifies key trends, research gaps and future directions. By mapping the knowledge structure, the study offers insights into the effects of LH on healthcare efficiency, patient care and organizational performance.

The review used the bibliometric approach, involving 319 journal articles retrieved from the Web of Science database. Two science mapping approaches (i.e. bibliographic coupling and co-word analysis) were performed to investigate the current knowledge structure and future research direction in LH.

The current research trend in LH focuses on developing frameworks and strategic implementation by considering critical determinants and decision-making strategies. In the future, the research on LH will emphasize the holistic frameworks and efficient strategies for healthcare excellence, along with strategies to overcome barriers to its implementation.

This study will benefit researchers and practitioners by advancing their understanding and applying LH principles.

This study provides valuable practical implications for healthcare managers to navigate the complexities of lean implementation, optimize processes and drive sustainable improvements in the healthcare context.

Substantial pressure from civil society and investors has forced governments around the world to take climate neutrality initiatives. Several countries have pledged their nationally determined contributions towards net-zero. However, there exist various obstacles to achieving the same and the agriculture sector is one of them. Thus, this study identifies and models the critical barriers to achieving climate neutrality in the agriculture food supply chain (AFSC).

Sixteen barriers are identified through a literature survey and are validated by the questionnaire survey. Furthermore, the interactions amongst the barriers are estimated through the application of the “weighted influence non-linear gauge system (WINGS)” method which considers the both intensity of influence and the strength of the barrier. To mitigate these barriers, a framework based on green, resilient and inclusive development (GRID) is proposed.

The obtained results reveal that lack of collaboration amongst AFSC stakeholders, lack of information and education awareness, and lack of technical expertise obtained a higher rank (amongst the top five) in three indicators of the WINGS method and thus are the most significant barriers.

This paper is the first attempt in modelling the climate neutrality barriers for the Indian AFSC. Additionally, the mitigating strategies are prepared using the GRID framework.

Global competition has intensified pressure on small- and medium-sized enterprises (SMEs) to implement lean. Recently, the debate has converged to the role of lean implementation barriers (LIBs). The purpose of this paper is to contribute to this debate by exploring the LIBs in SMEs through three case studies.

A case study approach was employed followed by interpretive structural modelling (ISM) to model the interrelationship among the LIBs.

This study reveals that lack of management commitment, leadership and resources are the key barriers to lean implementation in SMEs in India. Furthermore, poor communication between different levels of the organisation and inadequate dissemination of the knowledge of lean benefits also creates hindrance in lean implementation. Managerial implications of the identified barriers for lean implementation in SMEs have been discussed.

The research regarding lean implementation in SMEs is scarce. This study is the first attempt of its kind to identify the lean barriers in a small industry setup through mathematical analysis.

The study seeks to explore why despite growing concern for the environment, consumers’ intention to purchase organic foods remains relatively low. In addition, the study also seeks to investigate the role of perceived marketplace influence (PMI) and moral norms in organic food consumption.

Data collected from 330 young consumers chosen with non-probability sampling were analysed using structural equation modelling in Amos 22.0.

The results of the parallel mediation analysis confirmed that environmental concern influences purchase intention indirectly through attitude, subjective norms, perceived behavioural control and perceived marketplace influence. In addition, moral norms were found to moderate the effect of perceived behavioural control on purchase intention. Moreover, the results also indicated that the impact of environmental concern on consumers’ attitude toward organic foods was also moderated by moral norms. Further, the results of moderated mediation showed that the indirect effect of environmental concern on purchase intention (through attitude and perceived behavioural control) was moderated by moral norms.

The study contributes to the existing literature by investigating the inconsistency between environmental concern and purchase intention. In addition, the study also investigate role of perceived marketplace influence and moral norms in stimulating organic food consumption intentions.

The emergence of perceived marketplace influence as an important determinant of organic food consumption shows that every individual needs to realise the importance of their environment friendly actions to promote organic food consumption. In addition, the study also highlights the pivotal role of moral norms in the promotion of organic food consumption. Thus, markets, policy-makers, family, friends, society all should promote and inculcate the spirit of contributing in the cause of safeguarding the environment to the young children specially by promoting consumption of organic foods.

The study examines the role of perceived marketplace influence as predictor of purchase intention towards organic foods which is rarely explored specially in the domain of organic food consumption. In addition, the results also produced some novel insights into the moderating role of moral norms.

This article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.

20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.

The study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.

This study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.

This study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.