The work identifies the main enabling dimensions and the strategic drivers to foster value co-creation and sustainable innovation in service ecosystems. The aim is to explore how resource and knowledge integration, through technology-mediated interactions, can lead to the emergence of novelties (new products, services, processes, social, and environmental practices). Based on a re-elaboration of literature, the study introduces a framework that describes the main drivers for managing the emergence of value co-creation and innovation (co-design, co-development, co-delivery, co-learning) across the contexts of exchange of service ecosystems (micro, meso, and macro). A “meta”-level is conceptualized to investigate how management can harmonize an actor’s objectives with an ecosystem’s goal to encourage the diffusion and renewal of a sustainable and innovation-oriented culture. The empirical research applies the framework proposed in the theoretical section to a case study analysis on “Palm”, an Italian company that designs and produces wood packaging. The technique employed is qualitative content analysis. The findings permit conceptualization of the key strategic levers for the management of co-creation and to increase managers’ and scholars’ understanding of (1) the enablers of value co-creation and innovation; (2) the mechanisms leading to knowledge renewal and the continuous production of sustainable innovation.

The growing complexity of environmental challenges has progressively led to the emergence of Sustainable Business Models (SBMs) able to embed economic, environmental, and social flows in a unified value network. All sectors are demanding innovative and sustainable solutions, including the oil and gas industry, which aims to address the issues about the decommissioning of offshore platforms. However, although the relevant literature highlighted the potentialities related to a multi-reuse of these structures, the effect of Sustainable Decommissioning (SD) on macro-environmental factors is still an open question. Based on these considerations, this study follows a Political, Economic, Social, Technological, Legal, and Environmental (PESTLE) analysis according to semi-structured interviews conducted with oil and gas key informants and stakeholders in the Italian context. The results of the analysis can provide a novel thinking for addressing the challenges related to a sustainable decommissioning of offshore platforms and shed light on the importance of synergistic efforts by local entrepreneurship and institutional arrangements to combine economic and environmental sustainability with social needs. This paper can contribute to the emerging field of sustainable business models related to the decommissioning of offshore platforms and suggests avenues for future research.

Purpose: The purpose of this paper is to provide a better understanding of the reasons why people use or do not use carpooling. A further aim is to collect and analyze empirical evidence concerning the advantages and disadvantages of carpooling. Design/methodology/approach: A large-scale text analytics study has been conducted: the collection of the peoples’ opinions have been realized on Twitter by means of a dedicated web crawler, named “Twitter4J.” After their mining, the collected data have been treated through a sentiment analysis realized by means of “SentiWordNet.” Findings: The big data analysis identified the 12 most frequently used concepts about carpooling by Twitter’s users: seven advantages (economic efficiency, environmental efficiency, comfort, traffic, socialization, reliability, curiosity) and five disadvantages (lack of effectiveness, lack of flexibility, lack of privacy, danger, lack of trust). Research limitations/implications: Although the sample is particularly large (10 percent of the data flow published on Twitter from all over the world in about one year), the automated collection of people’s comments has prevented a more in-depth analysis of users’ thoughts and opinions. Practical implications: The research findings may direct entrepreneurs, managers and policy makers to understand the variables to be leveraged and the actions to be taken to take advantage of the potential benefits that carpooling offers. Originality/value: The work has utilized skills from three different areas, i.e., business management, computing science and statistics, which have been synergistically integrated for customizing, implementing and using two IT tools capable of automatically identifying, selecting, collecting, categorizing and analyzing people’s tweets about carpooling.

The increasing fluidity of social and business configurations made possible by the opportunities provided by the World Wide Web and the new technologies is questioning the validity of consolidated business models and managerial approaches. New rules are emerging and multiple changes are required to both individuals and organizations engaged in dynamic and unpredictable paths.In such a scenario, the paper aims at describing the potential role of big data and artificial intelligence in the path toward a collective approach to knowledge management. Thanks to the interpretative lens provided by systems thinking, a framework able to explain human-machine interaction is depicted and its contribution to the definition of a collective approach to knowledge management in unpredictable environment is traced.Reflections herein are briefly discussed with reference to the Chinese governmental approach for managing COVID-19 spread to emphasise the support that a technology-based collective approach to knowledge management can provide to decision-making processes in unpredictable environments.

Due to the spread of COVID-19, new challenges and opportunities for business innovation have emerged, including the way work is organized and designed. In particular, pandemic created the conditions for the most extensive mass teleworking experiment in history. While there is a wide literature on the effects of teleworking as a business innovation, mainly from an environmental perspective, there are few studies investigating the public perceptions regarding teleworking and, in particular, studies that draw from social media analyses. Based on these considerations, a big data analysis has been carried out in order to frame the public perceptions about teleworking on Twitter. The six-months sentiment analysis of about 11,000 tweets shows that the ecological value of telework is not perceived by people; surprisingly, in a pandemic context of growing ecological concern, there is no significant evidence of environmental awareness in relation to teleworking. However, the positive and negative concepts which emerge in relation to teleworking and similar terms can be assimilated to the benefits and pitfalls highlighted in the literature, which are related to economic or social sustainability. This has important implications for practice in organizations employing teleworking, which are highlighted in the conclusion, together with the limitations and future research avenues.