Agility has a special place in the start-up Industry 4.0 era. More research is required to properly comprehend the agile implications of start-up Industry 4.0 regarding the impact of digitization on the economy, the environment, and society. Investigating the effects of start-up 4.0 agility is still in its early stages. The current study simulates the variables impacting agility in start-up activities in Industry 4.0 to tackle this problem. In addition to the pre-arranged interview, a closed-ended questionnaire was used to gather information. In the context of start-up operations 4.0, the MICMAC technique is used to evaluate and categorize the components that contribute to agility in order to comprehend their interconnections. The research identified eleven characteristics of facilitating agility in start-up operations 4.0. Industry 4.0 concepts have significantly influenced large organizations but deploying agility in start-up 4.0 has been less visible. Hence, this study presents an innovative approach to incorporating agility in modern start-up operations. The significance of artificial intelligence, cloud computing, network and connectivity, technology, and digital twin in this context is evident. The research provides important light on the elements that contribute to the successful use of agility in start-up 4.0, offering useful insights for stakeholders and academics.

Ergoecology in sustainable healthcare refers to incorporating the aspects of ergonomics, which emphasises tailoring the healthy workplace to the abilities and constraints of healthcare employees, and ecological considerations, which consider the overall environmental impact of healthcare activities. The purpose of this study is to identify ergoecology factors influencing healthy and sustainable workplaces in the context of healthcare organisations and to develop a conceptual model. Literature review and opinions of healthcare experts have opted to identify the factors influencing ergoecology in healthcare organisations. The identified factors were face-validated by the healthcare experts. Scheduled interviews and closed-ended questionnaires were employed to collect data for this research. This research employed total interpretive structural modelling (TISM) and matrix multiplication applied to classification (MICMAC) analysis. TISM methodology is utilised to better comprehend how the components interact with one another, and why. MICMAC analysis is employed to prioritise factors and categorise these factors into four categories: driving factors, autonomous factors, dependent factors, and linkage factors. It is observed that analysis of surroundings and the adoption of ecological and ergonomic measures have strong driving power, but weak dependence. These factors are key factors and are termed as independent factors of ergoecology in healthcare for a healthy and sustainable workplace. The structural model and methodological approach are employed in a healthcare organisation; this approach can be extended to different industries in the future. This study helps to understand the concept of ergoecology and the influencing factors for ergoecology in the context of healthcare organisations. Ergoecology concept not only benefits the environment and the health of healthcare employees but also boosts productivity within the healthcare industry. In this study, the total interpretive structural modelling and matrix multiplication applied to classification analysis for healthcare is proposed as an innovative approach to address the ergo-ecology concept in the context of healthcare for a healthy and sustainable workplace to improve productivity within the healthcare industry.

This research examines the drivers of lean implementation in sustainable energy enterprises (SEEs) to balance efficiency, sustainability, and competitiveness. This research investigates the interdependence among lean drivers and classifies them by driving power and dependence. This study followed a novel mixed-method approach combining a systematic literature review for driver identification, interviews with entrepreneurs for expert consensus, and analysis using total interpretive structural modelling (TISM), cross-impact matrix multiplication applied to classification (MICMAC), and a graph-theoretic approach (GTA). The result indicated that leadership commitment, teamwork and collaboration, and time management are high drivers; cost reduction, resource optimization, and continuous improvement are linkage drivers; and customer focus and flexibility are found as dependent drivers, revealing the sustainable outcome. This provides a structured pathway for the SEEs for the lean implementation drivers, where prioritization is required. The exploration adds to the Resource-Based View, dynamic capability theory, system theory, etc. The study calls for policymakers’ interventions in designing capacity-building programmes, leadership training, and collaborations. This research incorporated the antecedents–decisions–outcomes (ADO) framework for highlighting the antecedents, leading to decisions, and the outcomes of the choices, with future research questions connecting with multiple sustainable development goals (SDGs), such as SDG7, SDG9, SDG12, and SDG13.