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Measuring Intellectual Capital (IC) is essential for contemporary firms. To succeed in a radically changed economic environment, organizations must develop reliable measures of IC. Yet existing studies focused on this topic missed evaluating the uncertainty sources. To our knowledge, we performed the first systematic literature review with thematic analysis to understand which IC measurement model works better in the following uncertainty areas: digital transformation, environmental impact, financial crisis, social impact and turbulent environments. We searched three databases and included quantitative peer-reviewed articles relevant to IC measurement methods in business uncertainty. This yielded 2,709 studies, of which 27 were eligible and included in the final sample. Our study found no agreement on the best IC measurement tool for uncertain times due to varying firm characteristics, including location, industry, size, and performance dimensions. Additionally, included studies emphasized the importance of human capital in enhancing company competitiveness and profitability. However, investing in IC alone cannot ensure agility and resilience in the digital era. Firms must effectively manage intangible assets like innovation, R&D, and employee knowledge and skills to drive growth. For future research, we recommend focusing IC measurement research on under-investigated industries, such as automotive, transportation, and hospitality, which require tailored IC measurement solutions. Furthermore, to highlight the broader societal benefits of effective IC management, research should also focus on measuring IC’s impact on social development goals, such as ecological sustainability, fair employment and gender parity.

Summary: This chapter makes the case for informal spaces in the workplace by emphasising the qualitative benefits they can provide, most specifically in the realm of innovation. This goes against the current bias in evidence-based policy that the most valued evidence is that which can be measured (Belfiore & Bennett, 2008, p.5) and aligns with qualitative forms of representing experience, knowledge, and outcomes. The link is made here between transformation and innovation. Innovation is seen as the fertile offshoot of creating a space for growth, debate and experimentation; one parallel to and overlapping with the more formal channels of established communication and interaction in the workplace. Transformation is difficult to substantiate and requires qualitative forms of expression and analysis to come into view. This chapter aims for a more balanced view of all forms of analysis and argues that qualitative forms are the most effective at capturing innovation. Background: The current bias for quantification is the result, as Eleonora Belfiore and Oliver Bennett outline in their intellectual history of cultural policy, of a growing reliance on evidence to make the case for policy. This took form in the 1990’s as a pragmatic response to what was then viewed as ideologically driven decision-making. Decisions would be based on effectiveness rather than political bias. Elements would be measured against one another in order to ascertain the best way forward. In an effort to make the case for evidence-based decision-making, “hard data, such as facts, trends and survey information, were widely seen as the ‘gold standard’” (Belfiore & Bennett, 2008, p.5). Quantitative forms of analysis took over as they provided a way of measuring and comparing which sated the need to base decisions on clearly-arguable numerical frameworks. If experiences and spaces can be reduced to numerical units, comparisons can be more readily made, and more importantly, argued. This approach was all

Purpose: This paper provides the first results of a scoping study exploring in detail how Cultural and Creative Industries(CCI) can represent a source and resource of critical and creative thinking as well as a set of processes to be deployed in order to foster and support innovation. Scope: Focusing on a sample of Italian companies, the aims, the forms and the specific practices of collaborations between CCI and knowledge-based and traditional businesses are identified and discussed. Method: In order to derive and test theories, trace causal pathways, explore hypotheses, researchers have designed and implemented qualitative research methods and conducted investigation mainly based on web-available data, archives and interview-based information. Results: The case examples of relevant Italian companies effectively provide evidences of the impact and modalities of adopting initiatives to develop innovation capacity. Recommendations and conclusions: The investigation of a sample of Italian companies suggests that most of the attention is focused on collaborations aimed to reinforce company image and reputation, to develop corporate social responsibility and to improve brand recognition.

The purpose of this chapter is to examine the state-of-the-art of Knowledge Assets Management (KAM) in the energy industry, reviewing both the literature and the practice of KAM initiatives. Particular attention is provided to renewable energy sector and to the Small and Medium Enterprises (SMEs). It emerges that most of the literature is focused on big companies and little attention is paid to renewable energy sector. It emerges that some organizations, especially in the oil industry, are seen as leaders in KM practice. On the other hand, SMEs operating in the renewable energy industry are not still aware of the relevance of KAM and then do not still address explicitly KAM initiatives or projects. The research revealed that small firms do indeed manage knowledge assets informally as part of their normal activities, without using of the terminology and concepts of knowledge management discipline.

The aim of this chapter is to address the lack of clear, coherent and shared frameworks for identifying, managing, assessing and reporting knowledge-based factors at regional level. According to a knowledge-based interpretation about territorial strategic resources, the Knoware Tree as framework to identify and classify territorial knowledge-based factors and the Knoware Dashboard as framework driving the design of potential indicators and metrics to assess territorial knowledge-based factors are presented. Finally, a set of key indicators for identifying and assessing the knowledge-based factors potentially supporting regional development paths is elaborated.