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Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

This paper aims to address the conceptual and practical challenges in integrating triple bottom line (TBL) sustainability in the agriculture supply chain (ASC). It identifies the key enablers for each of the three dimensions of TBL sustainability, analyses their causal relationships as well as cross-dimensional interactions under each TBL dimension. Further, it develops a decision support framework (DSF) for the assessment of TBL sustainability practices and policies in ASC and validates it through a case study.

An interpretive structure modelling (ISM) methodology is deployed to establish the interrelationships among all TBL enablers and to identify the enablers with high driving power on sustainable ASC. Brainstorming by a group of experts was used to identify the relevant enables. Finally, a DSF was developed as a resultant of ISM.

The paper provides a set of enablers with high driving power that can significantly influence the sustainability practices and policies in ASC. The social enablers directly help to enhance the effect of economic enablers and collectively these enhance the effect of environmental enablers. If agriculture firms and supply chains design innovative policies and develop practices based on these enablers, they can achieve sustainable ASC. Consequently, the living standards of the people directly or indirectly associated with the agriculture firm or supply chain can be improved without compromising on economic performance.

The paper consolidates the fragmented knowledge of sustainable supply chain management in the agriculture sector and suggests a DSF to policymakers, managers and practitioners for assessing TBL sustainability practices and policies. The DSF has wide applicability in other sectors of production and operations management as these sectors also face the challenge of achieving TBL sustainability across their supply chain.

The DSF, developed in the paper, is a useful tool for practitioners to frame and analyse sustainability initiatives and policies for ASC. A firm or supply chain may achieve TBL sustainability if it succeeds in uplifting the social status of its stakeholders.

It is a first step towards addressing the practical challenge of integrating sustainability in the agriculture sector of emerging economies and provides a path to improve the livelihood of people in the agriculture sector. Stakeholder engagement with a focus on collaboration and awareness may lead to the desired social and environmental consequences. Potential adverse social effects also need to be considered.

This paper focusses on the so far rather neglected but essential aspect of integrating TBL sustainability in the agriculture sector of emerging economies. The hierarchal representation and classification of the TBL sustainability enablers of sustainability is a unique effort in the field of ASC. Development of DSF is one of the first attempts to create a mapping between various enablers of TBL sustainability. The novelty of the study lies in the sector-specific, holistic evaluation of TBL sustainability policy measures that may lead to improvements in practice.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders’ thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.

The authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.

This study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated “Lead time” as the most crucial, “Product Range” as the second and “Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.

The present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders’ decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.

The present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.

Industrialized construction (IC) is promoted to address some of the ills associated with the processes and products of the traditional construction approach. With several successful projects, IC is progressively becoming a preferred alternative construction approach and spurred the interest of contractors, developers and housing authorities in the technology. Increasingly, these stakeholders are keen to ascertain the compatibility and feasibility of using IC in their projects. This paper aims to develop a knowledge-based decision support framework for implementing industrialized construction projects (ICPs) that can facilitate better and informed decision-making when deciding to implement ICPs.

A comprehensive literature review was implemented to recruit 40 decision support factors (DSFs) and grouped into project requirements, location and site attribute, labour considerations and organizational factors. A 3-member expert panel validated the relevance of 35 DSFs, which became candidates for a structured questionnaire survey of experts in 18 countries. Statistical techniques are used to evaluate and prioritize the DSFs, leading to the development of a conceptual framework.

Statistical analysis revealed 33 significant DSFs. The top five most significant factors that could influence the decision to implement IC in a project include a stringent requirement for project quality control, suitability of the design for IC, organizational readiness and competencies in ICPs, client receptivity to IC and the need to minimize field construction time. A framework of project requirements, location and site attributes, labour considerations and organizational factors was proposed as decision support.

The proposed framework may help to inform decision-making regarding the implementation of IC in a project. It has wider applicability because it includes technical, managerial and operational aspects of and the required competencies for IC, which are shared between project types and territories. The prioritized DSFs could be used as a guide when implementing IC, especially in countries where bespoke decision support systems cannot be developed.

The paper delineated the most important DSFs that are shared between IC project types and territories and can be used to investigate the compatibility of using IC in a proposed project. This research constitutes the first exclusive attempt at delineating, quantifying and ranking the sets of decision-making factors, drawing on international data set and contributes to the empirical checklist of DSFs for ICPs.

The purpose of the present research is to develop a reliable and valid scale to distinguish and measure the three environmental factors of dynamic structural framework, control of workplace decisions, and fluidity in information sharing that are conceptually related to and affect an employee's perception of empowerment. By quantifying the environmental factors that facilitate empowerment through a valid and reliable scale human resource departments will be provided with information that will suggest environmental changes they can implement to improve perceptions of empowerment on the part of employees. Strengths and weaknesses of the scale developed, the organizational empowerment scale, are also discussed.

The purpose of this study intends to make a characterization of a shop floor management (SFM) system in the context of smart manufacturing, through smart technologies and digital shop floor (DSF) features.

To attain the paper objective, a mixed method methodology was used. In the first stage, a theoretical background was carried out, to provide a comprehensive understanding on SFM system in a smart manufacturing perspective. Next, a case study within a survey was developed. The case study was introduced to characterize a SFM system, while the survey was made to understand the level of influence of smart manufacturing technologies and of DSF features on SFM. In total, 17 experts responded to the survey.

Data analytics is the smart manufacturing technology that influences more the SFM system and its components and the cyber security technology does not influence it at all. The problem solving (PS) is the SFM component more influenced by the smart manufacturing technologies. Also, the use of real-time digital visualization tools is considered the most influential DSF feature for the SFM components and the data security protocols is the least influential one. The four SFM components more influenced by the DSF features are key performance indicator tracking, PS, work standardization and continuous improvement.

The study was applied in one multinational company from the automotive sector.

To the best of the authors’ knowledge, this work is one of the first to try to characterize the SFM system on smart manufacturing considering smart technologies and DSF features.

Headlines of increasing financial losses caused by natural hazards and the potential impact of climate change on these raise broad interest in risk management. This paper seeks to claim that the existing decision‐making support, for example through spatial planning, can easily integrate risk assessment schemes.

The paper is based on the results of two EU funded research projects and further applications of those – as well as on conclusions drawn from presentations and discussions at the International Disaster Reduction Conference.

Discussion around risk governance highlights the role of integration. This discussion is still very much in need of further development and successful ways to implement integrative, participatory governance.

The research results presented have been elaborated in close cooperation with stakeholders. One example is based on a commissioned EU task that analyzed the effectiveness of European Regional Fund projects in the case of environmental risks. The other one describes how a town council took a decision which was based on information drawn from a project focusing on climate change adaptation.

The paper describes two examples of successful implementation which make us ask if new approaches are actually required or whether current spatial planning and development practices might be sufficient, when properly applied and fine‐tuned, to respond towards natural hazards and climate change impacts.

The purpose of the paper is to demonstrate the short comings in decision-making in a complex system. An approach to coping with a complex decision-making task is to identify generic structures known as systems archetypes in a given decision situation. In the “shifting the burden” archetype, decision-makers fail to identify the fundamental solution early and are subjected to accumulated side effects as they resort to quick remedial solutions.

A system dynamics-based game has been built to highlight the pitfalls of “shifting the burden” systems archetype for a decision-making situation in the Indian two-wheeler industry. Participants of the game make strategic decisions for a company and receive feedback of their decisions and corresponding actions after every plan period.

The decision-makers who adopt short-term measures to alleviate the company’s problems, invariably fail in their endeavour. Success comes to those who realize the importance of having a long-term perspective in the form of pursuing fundamental solutions.

What could be a possible way of avoiding the pitfalls? The decision-makers should be aware of the pitfalls beforehand and identify the same – a decision support system possibly can aid them in this regard.

The complexity of the system increases as the business grows. The managers need to adopt systems thinking and embrace a long-term perspective. Decision support systems integrating models of systems archetypes provide an environment to simulate various decision situations and see the effects beforehand.