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This study responds to the calls from the literature on identifying interactions among the sustainable supply chain management (SSCM) drivers, which influence focal firms’ SSCM decisions. It also determines how the effect of SSCM drivers differs across the upstream and downstream supply chains (SCs) entities of fast-moving consumer goods (FMCGs) companies.

We employ a multi-method design encompassing three studies: study 1 (multiple-case study), study 2 (quantitative survey), and study 3 (multiple-criteria decision-making or MCDM modeling).

The results show that the external drivers such as customer pressure, competition, and supplier pressure and internal drivers such as top management commitment interact to influence the adoption of SSCM practices, and this interaction is diverse across upstream and downstream SC entities of the FMCG sector. The study provides empirical evidence of relationships among the SSCM drivers, which influence SSCM decisions.

Understanding these interactions will help managers derive strategies to manage the overall SSCM ecosystem and recognize the multiplier effects of upstream to downstream and vice versa.

The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach.

A systematic literature review (SLR) was used to identify a total of 14 barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers.

The study reveals that training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach.

The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them.

The ranking of GLSS barriers gives top officials of HEIs a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers.

The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it is critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility and operational effectiveness.

GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation.

Lean is a continuous improvement methodology that has succeeded in eliminating waste in a variety of industries. Yet, there is a need for more research on Lean implementation in several under-studied contexts, including crisis situations such as those created by the recent COVID-19 pandemic. This research investigates how Lean programs were impacted by COVID-19, while previous research has primarily explored how Lean was used to solve problems created by the pandemic.

A mixed-method research approach was used to analyze employee feedback on how COVID-19 impacted the Lean programs using data from various levels of four energy-based utilities in the United States. First, an online questionnaire collected qualitative and quantitative data from a broad sample of participants. Then, a follow-up semi-structured interview allowed the elaboration of perceptions related to the research question using a smaller sample of participants.

Out of the 194 responses from the four companies, only 41% of the respondents at least somewhat agreed that COVID-19 impacted the Lean program at their company; of the remaining 59%, 35% indicated they were neutral, while 24% disagreed. The themes from the qualitative portion indicated that, while employees believed their companies had successfully found a new way to do Lean within the constraints of not always being in person, the collaboration and engagement were more challenging to sustain, and COVID-19 also otherwise made it more difficult to implement Lean. Meanwhile, some believed there was no impact on the Lean program.

The COVID-19 and Lean peer-reviewed literature published from 2020 to September 2023 focused primarily on using Lean to address problems created by the COVID-19 pandemic vs studying the pandemic's impact on Lean programs. This research partially fills this literature gap in understanding the impact COVID-19 had on Lean initiatives.

This paper aims to design a hybrid model of knowledge-based performance management system (KBPMS) for facilitating Lean Six-Sigma (L6s) application to increase contractor productivity without compromising human safety in Indonesian upstream oil field operations that manage ageing and life extension (ALE) facilities.

The research design applies a pragmatic paradigm by employing action research strategy with qualitative-quantitative methodology involving 385 of 1,533 workers. The KBPMS-L6s conceptual framework is developed and enriched with the Analytical Hierarchy Process (AHP) to prioritize fit-for-purpose Key Performance Indicators. The application of L6s with Human Performance Modes analysis is used to provide a statistical baseline approach for pre-assessment of the contractor’s organizational capabilities. A comprehensive literature review is given for the main pillars of the contextual framework.

The KBPMS-L6s concept has given an improved hierarchy for strategic and operational levels to achieve a performance benchmark to manage ALE facilities in Indonesian upstream oil field operations. To increase quality management practices in managing ALE facilities, the L6s application requires an assessment of the organizational capability of contractors and an analysis of Human Performance Modes (HPM) to identify levels of construction workers’ productivity based on human competency and safety awareness that have never been done in this field.

The action research will only focus on the contractors’ productivity and safety performances that are managed by infrastructure maintenance programs for managing integrity of ALE facilities in Indonesian upstream of oil field operations. Future research could go toward validating this approach in other sectors.

This paper discusses the implications of developing the hybrid KBPMS- L6s enriched with AHP methodology and the application of HPM analysis to achieve a 14% reduction in inefficient working time, a 28% reduction in supervision costs, a 15% reduction in schedule completion delays, and a 78% reduction in safety incident rates of Total Recordable Incident Rate (TRIR), Days Away Restricted or Job Transfer (DART) and Motor Vehicle Crash (MVC), as evidence of achieving fit-for-purpose KPIs with safer, better, faster, and at lower costs.

This paper does not discuss social implications

This paper successfully demonstrates a novel use of Knowledge-Based system with the integration AHP and HPM analysis to develop a hybrid KBPMS-L6s concept that successfully increases contractor productivity without compromising human safety performance while implementing ALE facility infrastructure maintenance program in upstream oil field operations.

The purpose of this study is to explore and model the strategies to overcome the barriers of Lean Six Sigma (LSS) implementation in Indian small manufacturing enterprises (SMEs).

In this research, 31 strategies of LSS implementation in SMEs have been identified through detailed literature review and out of them, 13 are finalized using statistical tools like CIMTC and Importance-Index analysis. Moreover, the consistency of finalized strategies was examined through reliability test using SPSS software version 22. The finalized strategies are modelled through interpretive structural modelling (ISM) and classified them using MICMAC based on their driving and dependency power.

The key findings of this techno-managerial study are identification and modelling of 13 strategies to overcome adoption challenges of LSS in context of Indian SMEs. The usage of ISM-MICMAC approach provides the guidance to industrialist consider the mutual interaction of strategies during planning and scheduling for LSS projects.

Due to human involvement and judgements, there may be chance of biasness and subjectivity during construction of self-interaction matrix. Also, the number of identified strategies to overcomes barriers of LSS adoption may vary by altering nature, scope and region of research.

Literature is full of studies regarding LSS barriers and its rankings. Also, few studies explored the solutions of LSS barriers and prioritized them. To the best of the authors’ knowledge, our study is very rare to witness which expose the strategies to overcome the barriers and frame the mutual interaction are per the driving and dependence power of strategies. The application of ISM-MICMAC approach suggests a roadmap for implementing LSS approach efficiently through considering developed ISM model of strategies in context of SMEs.