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Recent years have seen a meteoric rise in the study of narcissism in entrepreneurship, although little consolidation has occurred in this area. The purpose of this paper is the development of an integrative framework to harmonise the academic discussion and serve as a structured foundation for future research.

The authors conducted an artificial intelligence-aided, structured literature review focused on content analysis of concepts and contexts to map out current findings and research gaps in startup narcissism research.

According to the findings of this study, narcissistic tendencies have the potential to positively influence startup success early on in an entrepreneur's journey, but after a certain point in the process, the influence of narcissism on success becomes predominantly negative.

The research field is currently not very harmonised regarding research measures, research subjects and key research terms. Further research must use a standardised approach to add value to the research body.

Narcissism is a two-sided sword for founders. In the early stages of a company, many of the founder’s tasks can benefit from narcissistic tendencies. In the later stages of a company, that might shift to overwhelmingly negative effects of narcissism.

Methodically, this study is the first one to establish an artificial intelligence component to add value to the results of a review paper to the best of the authors’ knowledge. The results of this study provide a clear framework of entrepreneurial intention, entrepreneurial activity and entrepreneurial performance to give researchers the opportunity of a more differentiated way of organising work.

Entrepreneurial ventures aspiring to disrupt existing market incumbents often use business-model innovation to increase the attractiveness of their offerings. A value proposition is the central element of a business model, and is critical for this purpose. However, how entrepreneurial ventures modify their value propositions to increase the attractiveness of their comparatively inferior offerings is not well understood. The purpose of this paper is to analyze the value proposition innovation (VPI) of aspiring disruptors.

The authors used a flexible pattern matching approach to ground the inductive findings in extant theory. The authors conducted 21 semi-structured interviews with managers from startups in the global electric vehicle industry.

The authors developed a framework, showing two factors, determinants and tactics, that play a key role in VPI connected by a continuous feedback loop. Directed by the determinants of cognitive antecedents, development drivers and realization capabilities, aspiring disruptors determine the scope, focus and priorities of various configuration and support tactics to enable and secure the success of their value proposition.

The authors contribute to theory by showing how cognitive antecedents, development drivers and capabilities determine VPI tactics to disrupt existing market incumbents, furthering the understanding of configuration tactics. The results have important implications for disruptive innovation theory, and entrepreneurship research and practice, as they offer an explanatory framework to analyze strategies of aspiring disruptors who increase the attractiveness of sustainable technologies, thereby accelerating their diffusion.

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 paper explores the convergence of Education 4.0 and Industry 4.0 and presents a Twin Peaks model for their seamless integration.

A high-level literature review is conducted to identify and discuss the important challenges and opportunities offered by both Education 4.0 and Industry 4.0. A novel Twin Peaks model is devised for the convergence of these domains and to cope with the challenges effectively.

The proposed Twin Peak model for the convergence of Education 4.0 and Industry 4.0 suggests that the development of these two domains is interdependent. It emphasizes ethical considerations, inclusivity and understanding the concerns of stakeholders from both education and industry. We have also explained how continuous incremental adaptation within the proposed Twin Peaks model might assist in addressing concerns of one sector with the opportunities of the other.

First, Education 4.0 and Industry 4.0 are reviewed in terms of opportunities and challenges they present. Second, a novel Twin Peaks model for the convergence of Education 4.0 and Industry 4.0 is presented. The proposed discovers that the convergence is adaptive, iterative and must be ethically sound while considering the broader societal implications of the digital transformation. Third, this study also acts as a torch-bearer for the necessity for more research of this kind to guarantee that our educational ecosystem is adaptable and capable of producing the skills required for success in the era of IR4.0.

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.

This study aims to investigate religiosity and entrepreneurial motivation roles in the goal-specific, involving Muslim students’ entrepreneurial intention and self-efficacy. Besides, it examines the robustness model based on group context.

Partial least square structural equation modelling is employed to examine 502 data collected from Muslim students in Indonesia through an online survey. Meanwhile, partial least square multigroup analysis tests the robustness model.

Religiosity plays a powerful role in increasing goal-specificity. Meanwhile, entrepreneurial motivation and self-efficacy perform as full mediations in the pathway mechanism of religiosity's effect on entrepreneurial intention.

The current study is conducted based on the previous recommendations and contradictions. Therefore, it clarifies and develops a study on the role of religiosity and entrepreneurial motivation in the goal-specific motivation of Muslim students.

To increase the goal-specificity of entrepreneurship activities, policymakers in the ministry of education and universities must implement and revitalize Muslim students' understanding of the relationship between religiosity and entrepreneurship.

This study defines the role of religiosity in goal-specific, especially Muslim students’ entrepreneurial intentions, by gender, faculty/department and age. Furthermore, it completes the opportunity for research agendas on the relationship between religiosity, entrepreneurial motivation, self-efficacy and entrepreneurial intention.