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This paper aims to investigate the intersection between crowdfunding (CF), open innovation (OI) and responsible innovation (RI) and identify the emerging trends and gaps in research and new paths for CF research in the future. In addition, this paper proposes a conceptual framework and propositions.

This paper is structured in line with the systematic literature review protocol. After reading all the titles, keywords and abstracts, 172 papers focused on OI and RI were selected for this research. Finally, 27 papers that are based on dimensions related to responsible OI were selected for the study.

Due to CF's multidisciplinary nature, the scientific literature on the role of CF in endorsing responsible OI for shared value co-creation appears fragmented and redundant. Several emerging trends and gaps of research and new paths for CF research in the future arise regarding research methodology and theoretical perspective.

To the best of the authors' knowledge, this is the first study investigating the intersection between CF OI and RI.

This study examines the existing literature on generative artificial intelligence (Gen AI) and its impact across many sectors. This analysis explores the potential, applications, and challenges of Gen AI in driving innovation and creativity and generating ideas.

The study adopts a comprehensive literature review approach, carefully assessing current scientific articles on Gen AI published from 2022 to 2024. The analysis examines trends and insights derived from research.

The review indicates that Gen AI has significant potential to augment human creativity and innovation processes as a collaborative partner. However, it is imperative to prioritize responsible development and ethical frameworks in order to effectively tackle biases, privacy concerns, and other challenges. Gen AI is significantly transforming business models, processes, and value propositions in several industries, but with varying degrees of effect. Findings indicate also that despite the theory-driven approach to investigating Gen AI's creative and innovative potential, cutting-edge applications research prioritizes examining the possibilities of Gen AI models.

Although this review offers a picture of great possibilities, it concurrently underlines the necessity for a deep knowledge of Gen AI nuances to fully harness its capabilities. The findings indicate that continuous research and exploration efforts are required to address the challenges of Gen AI and assure its responsible and ethical implementation. Therefore, more study is needed on enhancing human-AI collaboration and defining ethical norms for varied circumstances.

This study presents a relevant analysis of Gen AI's transformational potential as an innovation catalyst. It emphasizes major potential, applications across industries, and ethical issues for responsible integration.

As part of the growing necessity for inter-organisational and multi-disciplinary interaction to facilitate complex innovation in digital security, there needs to be greater engagement with regulation in the innovation process. This is particularly true in the case of security technologies that are embedded within wider systems and that are largely invisible to most of the users of that system. This paper aims to describe stakeholders’ perspectives on regulation in the digital security innovation process and evaluates the implications of these perspectives on anticipatory regulation in digital security.

Using a qualitative methodology based on semi-structured expert interviews and ethnographic participant observation, the study draws on the authors’ involvement in a formally organised programme of academia–industry–government collaboration called Digital Security by Design (DSbD).

The study highlights a relational dimension to establishing regulatory responsibilities that is enabled through interdisciplinary dialogue. The study contributes to understanding the multifaceted roles of regulation in digital security innovation across organisations and areas of expertise. It does so by identifying four themes in how regulation is perceived in the DSbD programme: ethical imperative, adding value, adoption lever and passive compliance.

Incorporating regulatory responsibilities through dialogue early in the innovation process, rather than only once a security technology’s deleterious effects are noticeable, which could make digital innovation and transformation safer and better regulated. It can also make regulation successfully adopted, rather than an exercise in damage control or an adversarial process between regulators and organisations.

This paper presents original empirical research on how regulation is considered by stakeholders in a novel multi-disciplinary digital security innovation process. It then uses these findings as a basis to evaluate the implications for establishing regulatory responsibilities for a class of security technologies that are embedded within wider systems and that are largely invisible to most of the users of those wider systems.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

This chapter focuses on Responsible Research and Innovation (RRI) as a new approach for academic institutions, such as universities and Universities of Applied Sciences (UASs) as organizations based on empirical evidence. A University of Applied Sciences in Switzerland was selected as a case. An analysis of the organization's most representative documents, extensive interviews with employees having expertise in the different RRI keys (public engagement, gender equality/diversity, science education, open access, ethics) and Anticipation, Inclusiveness, Reflexivity, Responsiveness (AIRR) dimensions, as well as a focus group produced interesting insights regarding the discourse and institutionalization of the RRI approach in the organization. Furthermore, the drivers, barriers, best practices, and monitoring of each of the RRI keys and AIRR dimensions were further described. The findings suggest that RRI could be a helpful policy framework at a time that universities are going through a systemic change.

In the face of pressing global challenges, the role of educational institutions in fostering responsible management practices has never been more crucial. Drawing on the preceding chapters, this concluding contribution explores the nexus of innovation and social impact within the realm of responsible management education (RME), offering a synthesis of perspectives and strategies for driving positive change at micro-, meso-, and macro level. The authors argue that the frequent inertia of higher education institutions must be overcome with urgent action in reshaping curricula, teaching methodologies, and institutional policies to foster sustainable development and effect positive social impact. The chapter emphasizes the role of innovation in education and the development and diffusion of responsible business practices as a means to catalyze systemic change.

To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.

A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.

Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.

The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.

The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.

The purpose of this paper is to explore the extent to which the concept of learning organization can support the embedding of responsible innovation (RI) in organizations.

Based on literature in the fields of corporate social responsibility, learning organizations and quadruple helix collaborations, the authors constructed the responsible learning organization (RLO) framework for RI. With the framework, the authors want to show that the RLO can enable RI within organizations.

Based on this framework, the distinction is made between, on the one hand, the learning processes inside the organization, which resemble reflexivity, and, on the other hand, the learning processes that take place with stakeholders outside the organization, which resemble the other three core processes of RI: anticipation, inclusion and responsiveness. Based on these insights, the authors argue that if an organization wants to do good on innovation, which is seen as the core of RI, organization’s core values should guide that.

Organizational core values should be developed by means of learning inside the organization. Therefore, the process of reflexivity should be stressed more, and employees should be empowered to take part in developing these values, which in return can guide the organization as a compass through all the uncertainty it will encounter during the learning outside the organization when interacting with stakeholders.

The RLO framework for RI shows what learning processes organizations should facilitate first and what content should be at stake during these learning processes to embed RI. Furthermore, the framework puts emphasis on reflexivity as a condition for responsiveness, inclusion and anticipation.

This study aims to examine the influence of organizational flexibility (OF) and shared vision (SV) on sustainable competitive advantage (SCA) with the mediation role of responsible innovation (RI) in the manufacturing industry of a developing country. Furthermore, big data analytics capability (BDAC) serves as a moderator between RI and SCA.

The study's hypotheses are investigated using the structural equation modeling (SEM) method. Through simple random sampling, information was gathered from 247 owners/managers of manufacturing SMEs.

The results elucidate that OF and SV significantly determine RI and SCA. Moreover, RI significantly mediates between SV, OF and SCA. Besides, RI significantly determines SCA. BDAC significantly leads to SCA. Finally, BDAC significantly moderates between RI and SCA.

RI is crucial for manufacturing small and medium-sized enterprises (SMEs) to gain SCA and BDAC is important to address the changing demands of consumers for environment-friendly products. This study gives the public an overview of the different degrees to which SMEs are embracing RI and BDAC; with more environment-friendly initiatives, the natural environment will become more sustainable. Environmental sustainability will benefit each individual living in society.

This study adds value to the existing literature by focusing on predictors that affect SCA. Using dynamic capability theory, this initial study examines the influence of SV and OF on SCA and RI as mediators. Furthermore, BDAC is used as a moderating variable between RI and SCA. Managers, students and researchers can benefit from this study.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.