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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.

Lean manufacturing, a philosophy that revolutionized the manufacturing industry, is often linked to the Toyota Production System (TPS). At the core of a lean company, one can observe proper implementation of lean manufacturing tools and practices such as just-in-time, work teams, cellular manufacturing, lean layout, etc. The goal of lean production is to minimize the waste producing activities while offering the same or enhanced quality to customers.

The aim of this research is to investigate the implementation degree of lean manufacturing and its tools and practices focusing on the case of an SME in Albania as a concrete example. Higher attention is given to some of the pillars of lean manufacturing such as just-in-time and cellular manufacturing.

In this case study, researchers observed a variety of features of lean production. Just-in-time was implemented to a certain extent and cellular manufacturing at a more surprising level, which was facilitated especially by the U-shaped facility layout designs observed during the site visits. The value stream mapping showed a proper group technology in place and the management displayed signs of engagement and future advancement desire regarding this philosophy.

Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.

This chapter explores the concept of identity-conscious advising and coaching to support the development of First-Generation Black Male College Students during their undergraduate experience. Advising and coaching represent foundational practices colleges and universities use to support student success. Much like other aspects of education, institutions implement advising and coaching practices without consideration for how the identity of the student or the professional delivering the service influences student outcomes. First-Generation Black Male College Students' interactions within the college context are often framed by their visible, racial, and gender identities as opposed to their first-generation experience. First-Generation Black Male College Students experience microaggressions, discrimination, deficit perspectives, or negative stereotypes. By exploring an identity-conscious approach to relevant advising theories and coaching approaches, the chapter highlights the importance of building trusting, affirming relationships that lean into the lived experiences of First-Generation Black Male College Students without subjecting them to false, harmful stereotypes. This approach requires self-awareness on the part of educators and an understanding of the racialized dynamics that are inherent in the experience. Without addressing anti-Blackness, the impact of advising and coaching on First-Generation Black Male College Students is likely to have diminished or limited effects for this vital student population.

The tourism industry is seeing unprecedented growth due to the convergence of the internet and growing travel trends. E-tourism digitises the tourism business, including processes, value chains, infrastructure, services and auxiliary industries, to maximise efficiency and effectiveness. It is in response to the globalisation of the tourism sector, which has spurred the introduction of information and communications technologies (ICTs) during the past four decades. ICT can boost travellers' satisfaction by providing pre-trip information about tourism attractions and allowing them to contact vendors directly, obtain accurate information and get the lowest price.

ICT has made the global tourism sector more competitive by providing pre-trip information about tourism attractions, allowing tourists to contact vendors directly, obtain accurate information and get the lowest price. Search engines, transport capacity and network speeds have increased the number of international travellers who use technology to organise and document their trips. E-tourism reduces seasonality, improves consumer communication and boosts reservations and sales. ICT also affects customer behaviour management and future marketing models and supports tourism industry globalisation by providing practical tools to tourism agents to develop and disseminate their offers globally. Strategic behaviours significantly impact tourism, as eliminating intermediaries shortens the distance between client and provider. ICT is a new way to boost tourism demand, which attracts more tourists and generates more revenue while improving the sector.

A literature review or review article is an integral part of a scientific body of research which synthesizes prior knowledge and provides a holistic overview of a subject domain. While several studies emphasize the significance of literature reviews and include the guidelines for conducting a review, limited studies demonstrated different types of literature review methodologies in a comprehensive way. Accordingly, this chapter presents various types of review methodologies which includes narrative, descriptive, systematic, meta-analysis, hybrid, umbrella, scoping, theoretical, and critical reviews. In addition, the authors' skills including logical reasoning, content analysis, literature mapping, critical writing, and ethical consideration are presented. Further, quality aspects of the literature review are discussed such as the rigor and relevance of the selected studies. Overall, this chapter provides implications for researchers in understanding types of literature review methodologies along with their objectives, strengths, and weaknesses which can assist them in selecting a suitable methodology while conducting a review.

One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.