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Industry 4.0 or the Fourth Industrial Revolution is characterized by robotic process automation and machine-to-machine communications. Since computers, machines, and robots share information and knowledge more swiftly and effectively than humans, the question is what human beings' role could be in the era of the Internet-of-Thing. The answer would be beneficial to institutions for higher education to anticipate. The literature reveals a gap between the intended learning outcomes in higher education institutions and the needs of employers in Industry 4.0. Evidence is shown that higher education mainly focused on knowledge (know-what) and theory-based (know-why) intended learning outcomes. However, competent professionals require knowledge (know-what), understanding of the theory (know-why), professional (know-how) and interpersonal skills (know-how and know-who), and need intrapersonal traits such as creativeness, persistence, a result-driven attitude et cetera. Therefore, intended learning outcomes in higher education should also develop interpersonal skills and intrapersonal characteristics. Yet, personality development is a personal effort vital for contemporary challenges. The history of the preceding industrial revolutions showed the drawbacks of personality and character education; politicians have abused it to control societies in the 19th and 20th centuries. In the discussion section, the institutions for higher education are alerted that the societal challenges of the twenty-first century could lead to a form of personality education that is not in the student's interest and would violate Isaiah Berlin's philosophical concept of ‘positive freedom’.

Gender competence as part of engineering education can better prepare men and women to work on sustainable solutions that benefit entire societies. This chapter describes the framework and lessons learned of a community of practice (CoP) for gender equality facilitated by the Mediterranean Engineering Schools Network. Faculty and students from Mediterranean European, North African and Middle Eastern countries came together in this CoP, which was supported by the TARGET project, to develop a practical plan using a reflexive approach. The transfer of knowledge between generations is achieved by using participatory learning processes, facilitating mindful awareness, widening experiences, deepening understandings and building a gender-sensitive mindset. Students embarked on the journey to become change agents. The process led to the consolidation of gender equality knowledge, competence building and the development of change agents for gender equality. This CoP can inspire other institutions to undertake a participatory path towards gender equality – at local, regional, or global level.

Purpose – This paper aims to detect or identify the presence of hydrocarbon infiltration on sampling point in the Rambe River area according to the obtained VOCs and the adsorbed SVOCs.

Design/Methodology/Approach – The Gore-sorber method has been used to capture volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) as indicators of subsurface hydrocarbon generation and entrapment. This method is usually used in environmental surveys for the oil investigations in certain areas for surface survey screening, designed to collect a broad range of VOCs and (SVOCs) at lower concentrations, quickly and inexpensively. The results also indicated a general correlation between the GORE-SORBER and reference method data. The research was conducted in Rambe River Village, Tebing Tinggi sub-district of Tanjung Jabung Barat district, Jambi Province Indonesia. The collection of the Gore-Sorber modules were analyzed using a gas chromatography-mass spectrometer thermal desorption (GC/MS).

Findings – The results showed that from all sampling points in Tebing Tinggi areas, the dominant components detected are carbonyl sulphide, dimethyl sulfide, ethane, propane, butane, 2-methyl butane, pentane, and carbon sulfide with carbon chain in the range C2-C5. These hydrocarbon gases (C1-C4) which may be from thermogenic or microbial processes. The highest concentrations of carbonyl sulfide were 392.67 ng and dimethyl disulfide 261.90 ng.

Originality/Value – In addition to estimate and predict the petroleum formation, this article provides information about the presence of oil fields in the area of the Sungai Rambe Village

This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

In recent years, both academics and institutions have acknowledged the crucial role multinational enterprises (MNEs) can play in addressing the sustainability challenges, as formalized by the sustainable development goals (SDGs). Nevertheless, because of their extensiveness and their design as country-level targets, SDGs have proven challenging to operationalize at a firm level. This problem opens new and relevant avenues for research in international business (IB). This chapter attempts to frame the topic of extended value chain sustainability in the IB literature. In particular, it addresses a specific topic, that is, how sustainability and resilience-building practices interact in global value chains (GVCs). To do so, the present study develops the case of STMicroelectronics (ST), one of the biggest semiconductor companies worldwide.

This chapter establishes the conceptual and analytic framework for the book. It relates not only to much of the existing work in evolutionary and institutional economics, but also to work in cultural science and cultural semiotics domains as well as in media convergence and transmedia studies. The central concept it first deploys is ‘innovation systems’ as applied in national, regional, international and sectoral contexts. It then builds on the general theory of economic evolution by Kurt Dopfer and Jason Potts and reviews the tools this theory provides to carry out a meso-level analysis of industries co-innovating and converging. It then proposes a new concept – ‘cross-innovation’ – to refer to the emergence of new structures and ‘rules’ at the boundaries of existing industries.