Marco Pironti

This chapter provides an overview of the main literature on identifying and forecasting the abilities that are expected to gain value and importance as artificial intelligence continues to evolve. It explores various techniques used to anticipate the talent needs across industries and highlights the critical role of collaboration among businesses, academic institutions, and professionals in shaping and updating the workforce competencies. To illustrate this concepts in practice, the IBM SkillsBuild program is the case study presented, demonstrating how IBM proactively identifies emerging skill demand and cultivates future talent through a combination of internal training strategies and partnerships with educational institutions. So, this chapter outlines how organizations can utilize AI to predict and develop necessary future skills for the workforce within AI-powered workplaces.

The study delves into the concept of Circular economy target (CET) performance in the context of Green Open Innovation (GOI) to understand the role of Big Data Management (BDM) and Sustainable Supply Chain Practices (SSCP), including Knowledge Management (KM). The authors developed a self-administered survey for 294 participants from the cement, electronics, tyres, rubber, and energy sectors. These industries are relevant for their environmental impacts and sustainability challenges. The study's empirical findings emphasize the positive association between BDM with BDC and KM. Further, it positively associates with SSCP and CET, especially in the context of GOI. GOI was also observed as a moderating variable in the relationships between BDC-SSCP and KM-SSCP. The conceptual framework elucidates the interaction between BDC, Knowledge Capabilities, and SSCP. It underscores the collective synergy of these components in achieving CET. This is in the frame of GOI, which intertwines the value chain between territorial actors such as companies, universities, and research institutes that exploit and convert big data into knowledge to get new forms of sustainable innovations.

Purpose: The importance of knowledge-based assets and the capability to leverage them has been the subject of scholarly interest in entrepreneurial orientation literature. The authors attempt to understand the dominant themes in the prior literature and propose directions for future research. Design/methodology/approach: The authors performed a systematic review of 79 studies to answer the research questions: (1) What are the predominant themes in the literature on the role of intellectual capital and entrepreneurial orientation? (2) What are the potential fields of future research? Findings: The findings suggest that current research engages the topics of intellectual capital, the capability to leverage knowledge assets and entrepreneurial orientation. The thematic analysis reveals the role of knowledge management, organizational learning, intellectual capital and absorptive capacity in entrepreneurial firms. The authors propose a theoretical model to explain how intellectual capital and its management influence firm-level entrepreneurial behavior. Originality/value: Understanding the association between intellectual capital and the capability to leverage knowledge assets is crucial in a dynamic business environment. Effective deployment of knowledge is vital while searching for new entrepreneurial opportunities.

In this article, we provide a new insight into overcoming resistance to emerging green technologies through mobile app users' environmental engagement. The use of a mobile recycling application is evaluated with regard to its media richness with a sample of 12 539 users in Italy. The research is developed during the COVID-19 pandemic, at a time when users have become more environmentally conscious and aware of plastic pollution. This time period has also seen an increase in the use of mobile applications, which provide social engagement and other benefits. Although it has encouraged new research on recycling behavior and how environmental messages are spread, as far as we know, no research has included a specific technology, such as mobile applications. Through the lens of consumer social media engagement behavior, it has emerged that media richness has a positive correlation with user engagement and recycling behavior. Theoretically, the research offers a novel technological tool worthy of further exploration in the fields of management and engineering. New practical insights are offered in terms of best practices for strengthening the relationships between companies and their clients. As users become more accustomed to social technologies, those technologies may help to establish responsible consumption patterns.

Opportunities opened up by the Industry 4.0 paradigm are related to the acceleration of flexible and open business planning and governance mechanisms to foster the adaptability of the value chain to the rapid changes during ongoing operations by reducing gaps and controlling efforts. The constant search for a dual perspective (short- to medium/long term) and a twofold equilibrium (micro and macro vs. internal and external) is creating new challenges for sustainable business models. The Self-Tuning Open Reengineering Model (STORM) is well suited to explain the organizational behaviours of both industrial and craftsman firms in terms of the strategic and operational aspects of the smart factory paradigm.

Purpose: The purpose of this paper is to satisfy a clear gap in the main field of open innovation research whereabouts a very little scholarship try to analyze the mechanisms of innovativemilieudown smart cities environments by applying through innovative projects that seem to support efficiently the entry of private firms and citizens in public collaborations.Design/methodology/approach: The research performed an exploratory and qualitative evaluation based on the case study method built on the evaluation of organizational behavior and urban boosting innovation through smart city initiatives. In doing so, after a literature review in smart city as well in lean methodology fields, the case of Turin Smart City follows.Findings: As acknowledged by international literature, the paper shows how a lean approach enables local government to define and realize smart projects and initiatives in a faster and more effective way. Particularly, the government in one of the main cities in Italy, id est Turin, combines a lean methodology with the job-to-be done approach, according a new concept of smart initiatives involving a startup mentality for the lead users which enables interesting predictions relating the human aspects of open collaborations.Research limitations/implications: The specificity of this inquiry highlights valuable insights from double-gate smart cities’ innovation, social and urban as well. The research is largely interpretative and exploratory and while this provides a solid scientific foundation for further research, it does not, itself, subject any hypothesis to statistical testing and validation.Originality/value: Since the city approached the smart city subject in a lean way, it was able to realize some projects in a faster way. Through specific initiatives, the city acquires the ability to involve more and better all its stakeholders such as citizens, companies, and public employees, among others. In this regard, the paper invigorates managerial debates concerning the urban and social aspects of open innovation ecosystems which represent in our minds a superior level of open innovation, testbeds of positive knowledge, and stimulus of knowledge dissemination process around the city.

Purpose: The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics. Design/methodology/approach: This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1). Findings: The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment. Originality/value: This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.