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This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.

Purpose of This Chapter: This research aims to study the need for more age of qualified talent. The evolving corporate needs, education, and curriculum require urgent reform. Current university methods do not align with corporate demands due to outdated content and ineffective pedagogy.

Design / Methodology / Approach: Drawing on established research, this study delves into 7 prominent training strategies across 14 sectors. A survey of 53 HR professionals and managers forms the basis for employing the non-linear best–worst method (BWM) and the Fuzzy BWM to discern the most effective training and development (T&D) modules. This comprehensive methodology ensures a nuanced analysis of T&D practices and insights for businesses seeking to align with Industry 5.0 demands.

Findings: On-the-job training emerges as the most impactful method, followed by case studies, interactive group learning, and more. These methods enhance employee skills in Industry 5.0.

Research Limitations: Limited by a small sample, future research should expand participant diversity for robustness.

Practical Implications: The study holds significance for bridging the skill gap between academic institutions and Industry 5.0. Aligning strategies with industry needs reduces skill disparities, fuels growth, and addresses employability. The study’s impact extends to society, lowering unemployment and shaping a resilient, adaptable workforce for Industry 5.0.

Originality: This innovative research examines decision-making for implementing T&D strategies in the emergence of Industry 5.0, aligning with a human-centric approach to business transformation.

Introduction: A company or organisation must resolve various problems in the business environment for better operation in any corporate environment. Such issues are traditionally handled in multiple ways. A small sector unit with many employees encounters this corporate issue, for example, the handicraft sector. The impact of handicraft issues and their intensity, speed, and regularity is growing in our system.

Purpose: This chapter studies how small businesses might succeed in the handcraft industry in a volatile, uncertain, complex, and ambiguous (VUCA) environment. There is a lack of proper knowledge of how the VUCA affects business proficiency in the Indian handicraft sector. A novel business strategy for the handicraft sector, like other business proficiency called best practices in handicraft business in a VUCA environment, will be presented along with a discussion about VUCA environments. This considers both the individual influences of each particular word and the overall impact of VUCA.

Methodology: The study included a thorough literature analysis for three learning areas: performance improvement, including VUCA, and the leadership incorporation of risk and quality. Awareness in the trade will be examined in further sections, as the mastery of VUCA is achieved with various traditional and digital management ideas.

Findings: The research defined a new unorganised firm concept to maintain and succeed in a high VUCA environment in the handicraft sector, identifying 18 important success characteristics through a comprehensive literature review. The authors proposed a conceptual framework for fusing quality management to attain proficiency in the handicraft sector VUCA environment.

The 26th United Nations Climate Change Conference of the Parties (COP26) has reinvigorated the policy focus on sustainable transport. Automated and Connected Transport (ACT) has been featured as a promising technology-based option to aid in meeting the Sustainable Development Goals (SDGs). Despite progress in certain areas of sustainability, there are still a lot of SDGs where limited progress has been observed since the 2015 Paris Agreement, particularly regarding the social pillar of sustainability which is reflected from the user perspective. This chapter will set the scene for this edited volume first by contrasting ACT potential with the SDGs and then by highlighting the requirement to focus more on addressing user needs through ACT. Remarkably, scholars have been increasingly sceptical about the transition to fully automated and connected vehicles, thus it is pertinent to highlight relevant opportunities and risks. Chapter recommendations foster the promotion of a Quadruple Helix approach to operationalise the inclusion of social concerns (e.g. gender balance and equity) in Sustainable Urban Mobility Plans (SUMP) across the world.

This chapter investigates the potential of integrating multiple criteria decision-making (MCDM) techniques with decision support systems of digital supply chain management (DSCM) to achieve optimal outcomes. Digital supply chain (DSC) employs digital technologies (DTs) such as artificial intelligence (AI), Internet of Things (IoT), and big data analytics to provide extensive datasets and valuable insights pertaining to supply chain operations. MCDM techniques employ these realizations to facilitate informed decision-making through the assessment of multiple competing criteria. Usually MCDM approaches are used in the academic research with comparatively lesser application in industry. We argue that MCDM methodologies can play an instrumental role in DSCM, specifically in the areas of supplier selection, demand forecasting, and inventory management. Nevertheless, the integration of MCDM like AHP, ANP, DEMATEL, etc., with decision support systems presents several challenges, including concerns regarding the quality of data and the intricate task of assigning weights to various factors.