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The study queries the drivers of innovation management in contemporary data-driven organizations/companies. It is argued that data-driven organizations that integrate a strategic orientation grounded in data, human abilities and proactive management are more effective in triggering innovation.

Research reported in this paper employs constructivist grounded theory, Gioia methodology, and the abductive approach. The data collected through semi-structured interviews administered to 20 Italian start-up founders are then examined.

The paper identifies the key enablers of innovation development in data-driven companies and reveals that data-driven companies may generate different innovation patterns depending on the kind of capabilities activated.

The study provides evidence of how the combination of data-driven culture, skills' enhancement and the promotion of human resources may boost the emergence of innovation.

Industry 4.0 defines the application of digital technologies on business infrastructure and processes. With the increasing need to take into account the social and environmental impact of technologies, the concept of Society 5.0 has been proposed to restore the centrality of humans in the proper utilization of technology for the exploitation of innovation opportunities. Despite the identification of humans, resilience and sustainability as the key dimensions of Society 5.0, the definition of the key factors that can enable Innovation in the light of 5.0 principles has not been yet assessed.

An SLR, followed by a content analysis of results and a clustering of the main topics, is performed to (1) identify the key domains and dimensions of the Industry 5.0 paradigm; (2) understand their impact on Innovation 5.0; (3) discuss and reflect on the resulting implications for research, managerial practices and the policy-making process.

The findings allow the elaboration of a multileveled framework to redefine Innovation through the 5.0 paradigm by advancing the need to integrate ICT and technology (Industry 5.0) with the human-centric, social and knowledge-based dimensions (Society 5.0).

The study detects guidelines for managers, entrepreneurs and policy-makers in the adoption of effective strategies to promote human resources and knowledge management for the attainment of multiple innovation outcomes (from technological to data-driven and societal innovation).

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

Given the growing attention on service ecosystem and the role played by technology and institutions in shaping of actors’ relations and interactions, the purpose of this paper is to examine a tourism environment with the lens of service ecosystem in order to derive a deeper understanding on the underlying mechanisms.

A mixed methodology was used. First, literature review based on service ecosystems framework was conducted to critically analyze the roles of technology and institutions to shape a tourism service ecosystem. Then a case study was conducted.

Two main findings are described: the role and the characteristics of physical and virtual engagement touchpoints in the emergence of a tourism service ecosystems; and the relationship between technology and institutions in the resource integration. In particular, the authors conclude that institutions can shape the usage of technology which, in turn, can enable and imply the emergence of new institutions, continually adjusting the system of the tourism service ecosystem.

The analysis contributes to deepening the knowledge about value co-creation processes and engagement expedients in tourism destination, explaining the role of institutions and technology in helping actors to integrate resources and exchange services. The study can also be useful for practitioners in search for powerful tool to increase the competitiveness of a tourism destination.

The study is one of the first attempts to conceptualize and operationalize a tourism destination in a service ecosystem framework. In this way it contribute to enhance scientific knowledge in a tourism management literature.

The purpose of this paper is to reconceptualize Total Quality Management (TQM) in the light of service ecosystem view through the identification of dimensions underlying both the approaches and a clarification of the relationship between the two theories.

An overview on service ecosystems and on TQM is conducted, with particular focus on the main dimensions of the two frameworks derived from extant research. Consequently, an assessment of the key features of both theories is performed.

The work identifies four recurring dimensions in TQM, suggesting their rereading in the light of the assessed five recurring dimensions of service ecosystem. Moreover, a reconceptualization of TQM in the light of service ecosystem view is proposed.

This paper compares and proposes an integration between TQM and service ecosystem view. Such a reinterpretation of “traditional” view of quality management in the light of current trend of Service-Dominant (S-D) logic can represent a starting point for further research aimed at analysing the mechanisms underlying joint production of value in service delivery.

The purpose of this paper is to explore the emergence of innovation in smart service systems to conceptualize how actor’s relationships through technology-enabled interactions can give birth to novel technologies, processes, strategies and value. The objectives of the study are: to detect the different enablers that activate innovation in smart service systems; and to explore how these can lead dynamically to the emergence of different innovation patterns.

The empirical research adopts an approach based on constructivist grounded theory, performed through observation and semi-structured interviews to investigate the development of innovation in the Italian CTNA (Italian acronym of National Cluster for Aerospace Technology).

The identification and re-elaboration of the novelties that emerged from the analysis of the Cluster allow the elaboration of a diagram that classifies five different shades of innovation, introduced through some related theoretical propositions: technological; process; business model and data-driven; social and eco-sustainable; and practice-based.

The paper embraces a synthesis view that detects the enabling structural and systems dimensions for innovation (the “what”) and the way in which these can be combined to create new technologies, resources, values and social rules (the “how” dimension). The classification of five different kinds of innovation can contribute to enrich extant research on value co-creation and innovation and can shed light on how given technologies and relational strategies can produce varied innovation outcomes according to the diverse stakeholders engaged.

In line with the precepts of service-dominant logic (SDL), the purpose of this paper is to devise a measurement framework of customer value co-creation practices during the service process.

Answering the call of McColl-Kennedy et al. (2012), the present study develops a general conceptual model for the measurement of customer value co-creation behavior, in line with the procedure elaborated by Churchill (1979). In particular, the paper focuses on the first stage of the protocol, corresponding to the specification of the domain of the construct.

The study shows that the scale for measuring behavioral processes in customer value co-creation has an implicit hierarchical structure based on eight activities to ensure adequate semantic coverage of the concept: cerebral activities, cooperation, information research and collation, the combination of complementary activities, changes in habits, co-production, co-learning, and connection. Moreover, the work highlights that the analysis of customer value co-creation behavior leads to three diverse steps of value co-creation and various levels of interaction.

By systematizing the construct of customer value co-creation behavior within a comprehensive framework, the conceptual model attempts to fill a gap evidenced by previous research in order to show that actions performed by users during the value co-creation process strictly conform to SDL assumptions. Moreover, the framework underpinning the practical application of SDL principles could benefit future practitioners and suggest interesting implications for future research.

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.

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.”

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).

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.

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.

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 growing turbulence of the external environment has progressively led to the necessity by organizations of exploiting new opportunities provided by data-driven approaches for supporting the even more complex decision-making processes. The new digital environment has led to the development and adoption of innovative approaches; also in the urban context which has always been characterized by different, interconnected, and dynamic dimensions. Urban governance models have been enhanced by smart technologies, which act as enablers of advanced services and foster connections between citizens, public and private organizations, and decision-makers. In this context, the objective of this chapter is to examine the role of data-driven approaches in the urban context during the chaotic and high variable circumstances related to the diffusion of the Coronavirus disease 2019 (Covid-19). Thanks to the adoption of the co-evolutionary perspective, a cycle in urban governance decision-making approach based on digital technologies is depicted and its contribution for managing the ongoing Covid-19 is traced. The results of the analysis highlight how the data-driven approach supports urban decision-making process and shed light on the co-evolutionary perspective as heuristic device to map the interactions settled in the networks between local governments, data-driven technologies, and citizens. In this sense, this chapter offers interesting insights, potentially capable of generating useful implications for both researchers and professionals in the public sector.