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Entrepreneurship education has been largely treated as a pedagogical “black box.” Despite the emergence of popular entrepreneurship models such as business planning, the lean startup, or business model canvas, neither theoretical nor pedagogical foundations are typically evident. This limits the accumulation of useful evidence that could inform better teaching practices. In this chapter, we develop a set of conceptual models anchored in learning theory regarding how entrepreneurship education should be taught to students. These conceptual models are built on the techniques of entrepreneurship pedagogy such as experiential education. They are developed for three groups of students: students without any entrepreneurship experience, students with previous entrepreneurship experience, and students who are currently running their start-ups. A set of potential variables that could be used for course evaluation purposes is also included. The proposed models meet the needs of students with different levels of entrepreneurship experience. Theoretically, we demonstrate that entrepreneurship students should not be treated as a homogeneous group, as they have different levels of startup experience and different educational needs. Lecturers of entrepreneurship programs could choose the suitable model proposed in this chapter in teaching based on the characteristics of their students. The chapter provides novel insights with regard to how entrepreneurship programs should be designed for students with different levels of entrepreneurship experience.

Empirical evidence indicates that effective management of resources to implement strategy in a balanced scorecard (BSC) system is essential. We present a mathematical model for allocating limited resources in the BSC strategy implementation process.

The proposed facilitated negotiation model provides a systematic approach to prioritizing strategic initiatives in the design and implementation of a BSC.

Our joint decision model prioritizes strategic initiatives and concurrently calculates the optimal (or approximately optimal) set of BSC targets and weights, given multiyear resource restrictions.

The model assumes full, open, and truthful exchange of information between the parties; an assumption that may exclude many organizations.

We address an important gap in the BSC literature on how organizations can effectively link strategy to the potential constraint of resource budgets.

Quantitative models are being used in practice for allocating resources, but we are not aware of their use by organizations for allocating resources in a BSC application.

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.

Over the last decade, customer experience management has gradually emerged as the most important activity for organisations. Organisations have turned towards leveraging the ubiquitous and easy-to-use technology in enhancing and enabling experience for the time-crunched customers of today who are looking for greater convenience and choices. It is therefore not surprising that disruptive technologies such as smartphones, virtual and augmented reality, cloud computing, big data analytics, Internet of things, artificial intelligence and robotics have also found their way into the design of customer experience. This chapter aims to present an overview of the technologies that have transformed the customer experience landscape. This chapter contributes by showcasing two illustrative cases from very diverse domains, a private sector bank and a public sector transportation organisation, to elucidate how India, a rapidly developing economy, is embracing technology to enhance the customer experience.

Manufacturers have experienced many stages of evolution and paradigm shift. The paradigm shifts from crafts to mass production, then to lean production, and finally to agile manufacturing (AM). Agility will reduce the time to market for appropriate products and services. Twenty-first century companies must meet a demanding customer base that will increasingly seek high quality, low-cost products adapted to their specific and continually evolving needs. It is time for companies to compete, and “push the boundaries” in response to delivery, product quality, and overall excellence in customer service and satisfaction. For addressing these challenges, a new way to manage businesses was proposed called “Agility,” AM is defined as the ability to survive in a competitive environment characterized by the continual and unpredictable changes, by responding effectively to the changing markets with products and services designed by the customer. This chapter presents a review of research related to the agility concept through an analysis of the variously proposed studies. This analysis was conducted based on a meta-model of three words (Agility, Management, and Organization).

This study investigates the relationship between lean manufacturing practices, management accounting and performance measurement (MAC & PM) practices, organizational strategy, structure, and culture, and facility performance. We extended past research by examining the relationships between lean manufacturing, MAC & PM practices and performance in a broader organizational context. Our study was performed using survey data provided by managers and executives at 368 facilities that had contacted the Shingo Institute for information or that had entered a Shingo Prize competition. Consistent with past research we found a significant positive association between lean manufacturing practices and lean MAC & PM practices. We found that greater employee empowerment, use of process performance measures, and use of lean accounting practices were driven primarily by lean strategy and secondarily by the extent of lean manufacturing practices. We also found that changes in organization structure to support lean are driven primarily by lean strategy and secondarily by lean manufacturing practices. Change toward lean culture, on the other hand, is driven by the extent of lean manufacturing practices. Further, we found that emphasizing process performance measures does not reduce emphasis on results performance measures and emphasizing results performance measures leads to improved financial performance. Process and results measures are being used in tandem and value stream costing has not replaced traditional accounting. The results of our study provide important insights for managers of companies engaged in lean transformation and for academics who teach or research lean accounting.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

The emergence of the lean start-up movement has cast doubt and skepticism among entrepreneurship educators and practitioners regarding the usefulness of writing a formal business plan for training the next generation of entrepreneurs. In one camp, there is a group of entrepreneurship education professionals who continue to advocate for the usefulness and necessity for teaching students these basic business plan development skills. In an alternative camp, there is another faction of education professionals who believe that the business plan process is counterproductive and is an unnecessary distraction for today’s millennial entrepreneurs seeking to create their own new ventures. In this chapter, we argue why it is important to adopt a lean start-up framework and approach in both entrepreneurship courses and in curriculum design in early-stage venturing. We offer 10 reasons why entrepreneurship educators should place less emphasis on business planning and more emphasis on business modeling during the early stages of evaluating the feasibility of a venture. We believe that educators and curriculum designers need to rethink the traditional approach of building an entrepreneurship program based upon the business plan as the guiding framework. We then conclude our discussion with suggestions on where and how elements of the business plan can and should be introduced into the new venture development process and appropriately positioned in entrepreneurship curricula. We propose a renewed and reconciled view of the Lean Start-up versus Business Plan debate, as both are considered necessary but neither is sufficient to support the full lifecycle of the venturing process.

A crucial aspect of supply chain management (SCM) is the formulation of lean supply chain management (LSCM). In this sense, the key practices are extended towards the LSCM settings as alternative strategies and several frameworks were developed to help companies to make choices based on production disruption. Studies in this field have focussed mainly on SCM. Although manufacturing businesses recognise the necessity of effective SCM, but little study has been done on manufacturing LSCM. The behaviour and the potential for significant impacts on sustainable performance (SP) in manufacturing companies can vary with time and variations for approaches of the LSCM key practices. This chapter, therefore, focusses on main practices for LSCM on the basis of evaluations of experts in the Malaysian manufacturing sector in order to achieve SP in manufacturing companies. The aim of this chapter is to identify the key practices in LSCM on SP. Hence, this chapter reviewed 172 articles published from 2015 to 2019, used the methodology for SLR with three main steps: literature review planning, reviewing, and reporting. As a result, there are evidence that the key practices for LSCM used in previous studies are (1) customer relationship management, (2) supplier relationship management, (3) just in time manufacturing, (4) waste reduction, (5) cost reduction, and (6) minimise inventory level. In manufacturing industries, LSCM is more complex. Insights on the causing issues and SP are provided. Finally, this chapter contributes to SCM and literature on sustainability and has managerial implications for companies to improve SP more effectively.