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The concept of circular economy (CE) has been receiving a lot of attention over the past years from academics, practitioners and policymakers. This is particularly the case for small- and medium-sized enterprises (SMEs) who find in CE a way to overcome their resource scarcity. However, little is known about how embracing the CE perspective can contribute to meet the sustainable development goals (SDGs). The present chapter aims at answering this question. Through a single case study, we explore the drivers, managerial practices and collaborations implemented by SMEs to generate economic, social and environmental values.

This research aims to demonstrate how the circular economy is employed to drive the sustainability of the tourism industry in Krabi, Thailand, through the concept of mindful consumption and service-dominant logic (hereafter S-D logic).

A seven-year longitudinal study (2013–2020) was conducted through four studies from different perspectives, including macro, meso and micro levels of development in Krabi province.

Krabi tourism stakeholders have collaborated to co-create green culture and behavior whereby the value network among stakeholders plays an important role in driving the circular economy in practice.

This study provides an understanding of how the circular economy society has been co-created. However, further research should be conducted in other tourism cities by focusing on the key success factors that drive the circular economy.

The longitudinal study with multi-perspective micro, macro and meso levels of development in this study has shed the light on how the circular economy (CE) policy can be turned into practice.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

Technological platforms encourage the exchange of knowledge and creation of new ideas that create new value for participating members who pool and combine their knowledge, facilities, tools and skills, thus contributing to the development of innovative solutions. This paper focuses on hackathon platforms, working as open innovation intermediaries, investigating their role and functions and exploring how they encourage the collaboration and the innovativeness among participants in order to boost their innovative new ideas.

The research method is a qualitative design that includes in-depth interviews of ten stakeholders that play different roles in “Hack for Travel,” the case under analysis. It is a hackathon organized entirely online, as a response to the crisis generated by coronavirus disease 2019 (COVID-19).

Findings revealed six processes developed by the hackathon platform used to effectively organize the event and facilitate participants to cooperate and share knowledge in order to boost the spread of innovative ideas. Results identify how hackathons should be organized and through which processes they work as innovation platforms.

This is one of the first attempts to study the increasing phenomenon of hackathons, providing theoretical contribution and practical implications about their role in developing innovation.

This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

This paper aims to identify, synthesise and critically examine the extant academic research on the relation between big data analytics (BDA), corporate accountability and non-financial disclosure (NFD) across several disciplines.

This paper uses a structured literature review methodology and applies “insight-critique-transformative redefinition” framework to interpret the findings, develop critique and formulate future research directions.

This paper identifies and critically examines 12 research themes across four macro categories. The insights presented in this paper indicate that the nature of the relationship between BDA and accountability depends on whether an organisation considers BDA as a value creation instrument or as a revenue generation source. This paper discusses how NFD can effectively increase corporate accountability for ethical, social and environmental consequences of BDA.

This paper presents the results of a structured literature review exploring the state-of-the-art of academic research on the relation between BDA, NFD and corporate accountability. This paper uses a systematic approach, to provide an exhaustive analysis of the phenomenon with rigorous and reproducible research criteria. This paper also presents a series of actionable insights of how corporate accountability for the use of big data and algorithmic decision-making can be enhanced.

This paper discusses how NFD can reduce negative social and environmental impact stemming from the corporate use of BDA.

To the best of the authors’ knowledge, this paper is the first one to provide a comprehensive synthesis of academic literature, identify research gaps and outline a prospective research agenda on the implications of big data technologies for NFD and corporate accountability along social, environmental and ethical dimensions.

Despite the multiple calls for research on the dark side of open innovation, very few studies have approached the topic so far. This study aims to analyse successful and unsuccessful open innovation projects.

This study uses thematic analysis to describe the factors determining their (un)success. The researchers interviewed 27 managers and owners in the manufacturing sector. Then, the respondents were asked to discuss one successful and one unsuccessful open innovation project to explore the differences in triggers and setbacks, focusing on the causes that determined the failures.

Findings show that many interviewees are reluctant to identify failure cases, which somewhat explains the paucity of studies on the topic, and others do so when the failure is recognised by a third party (such as a public institution not granting funds to the project). This study discussed how this phenomenon is linked with the paradoxical relation between innovation success and failure. It is also found that triggers and setbacks determining the project's (un)success are markedly differently based on the technological intensity of the firm. Implications for scholars and practitioners are also drawn.

This study provides a balanced view between open innovation successes and failures to offer informative recommendations to practitioners. Furthermore, it contributes to filling the scarcity of studies related to risks and failures of open innovation projects. This gap has been addressed by studying the factors that determine the success and unsuccess of an open innovation project.

The unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.

This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.

Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.

This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.

This paper studies the Digital Service Innovation (DSI) concept by systematically reviewing earlier studies from various scholarly communities. This study aims to recognize how recent advances in DSI literature from different research streams complement and can be incorporated into the growing digital servitization literature to define better and understand DSI.

After systematically identifying 123 relevant articles, this study employed complementary methods, such as author bibliographic coupling, linguistic text mining/textual analysis and qualitative content analyses.

This paper first maps the intellectual structure and boundaries of the DSI-related communities and qualitatively assesses their characteristics. These communities are (1) Innovation for digital servitization, (2) Service innovation in the digital age and (3) Adoption of novel e-services enabled by information system development. Next, the composition of the DSI concept is examined and depicted to comprehend the notion's critical dimensions. The findings discuss the range of theories and methods in the existing research, including antecedents, processes and outcomes of DSI.

This study reviews, extends the understanding of origins and critically evaluates DSI-related research. Moreover, the paper redefines and clarifies the structure and boundaries of the DSI-concept. In doing so, it elaborates on the substance of DSI and identifies the essential themes for its understanding and conceptualization. Thus, the study helps the future development of the concept and allows knowledge accumulation by bridging adjacent research communities. It helps researchers and managers navigate the foggy emerging research landscape.

This paper aims to enhance the small and medium enterprises’ (SMEs) ability to develop resilience in the face of any turbulences, addressing the question on how these organizations can maintain business continuity when faced with a critical event.

A mediated regression analysis is conducted to investigate the relationships among big data analytics (BDA) capabilities, coinnovation (CI) and organizational resilience (OR) with reference to 192 big data SMEs in Europe.

Research reveals that the BDA capability and CI are positively associated with OR. Moreover, this study discovers the mediating impact of CI on the relationship between BDA capability and OR.

This paper provides important implications for considering CI as a viable strategy especially in a time of crisis and shows how SMEs are more able to recognize business opportunities. The microfoundations of the resilience building capacity of SMEs are also identified. These microfoundations become recommendations for practitioners to enhance SMEs’ responsiveness in light of coronavirus-related crises.