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The more recent emergence of advanced digital technologies and the acceleration of process digitization, combined with rising stakeholder expectations, have created an urgent imperative for organizations to embrace open innovation.

The analysis in this paper is based on a survey 2,379 executives representing 24 industries and 26 countries conducted by the IBM Institute for Business Value. IBV researchers used descriptive statistics to understand innovation trends. To understand the role of open innovation for business performance IBV researchers segmented the sample based on two criteria: extent to which the organization sees open innovation as important for their growth strategy and the extent to which they are effective in advancing open innovation.

Ecosystems are key to success with open innovation, creating value opportunities within and across the value chains. 10;

Open and interoperable technologies like hybrid cloud, APIs, blockchain and AI allow for many more ways to create value by unlocking hidden potential in existing relationships.

Open innovation drives growth; new research found that 84 percent of executives think open innovation is important for their future growth strategy.

Four management capabilities for successfully operationalizing open innovation are: strategy and culture, ecosystem capability, internal capability and technology enablement. Surveying more than 1,000 executives on current open innovation practices and capabilities, IBM IBV was able to identify how the different operating model capabilities interact and complement each other to drive better innovation and business performance.

To help organizations build and improve their open innovation capabilities, the IBM Institute for Business Value (IBV) partnered with APQC to develop the Ecosystem-Enabled Innovation Maturity Model (EEIMM) - an open standards model encompassing four domain competencies required for successful open innovation. To assess the maturity and benchmark the performance of organizations’ open innovation capabilities, the IBV, in collaboration with Oxford Economics, used the EEIMM to survey over 1000 leaders responsible for open innovation at their organizations.

Four management capabilities for successfully operationalizing open innovation are: strategy and culture, ecosystem capability, internal capability and technology enablement. IBV analysis found that organizations that are more advanced in developing the four building blocks see significantly better performance across key financial and innovation metrics.

For every dollar of investment, the proportion of direct revenue attributed to open innovation is four times higher than for traditional innovation.

Leading organizations are embracing open innovation as a critical component of innovation strategy and investment. They recognize that adopting open innovation yields far greater returns than traditional innovation can. Recent research by the IBM Institute for Business Value (IBM IBV) reveals, for example, that as many as 84 percent of executives now view open innovation as important for their organization’s future growth.

This paper posits that by selectively applying open innovation, companies can enrich their stock of valuable ideas, effectively manage product development and upgrade their emerging businesses without wholesale changes to their innovation initiative.

This is a case study of the open innovation process at Whirlpool Corporation written by two Strategos consultants who have worked with the firm.

Whirlpool has developed a set of questions and discussion guides that help to inform the decision to go “open” or not at each step of the innovation process.

Whirlpool believes that open innovation is really about building and maintaining relationships and alliances. These relationships are managed by “relationship managers” as part of the new business development activities.

By changing the context to competences within any organization, not just Whirlpool, the company is now considering and pursuing a number of opportunities that would have previously been rejected, and Whirlpool is successfully expanding its business to adjacent spaces through the help of open innovation partners.

This study aims to investigate the direct effect of intellectual capital on the organizational performance of Indonesian state-owned enterprises (SOEs) and their subsidiaries. Furthermore, it also examines whether the relationship is mediated by open innovation and moderated by organizational inertia.

This study is designed as quantitative research. A survey method is employed to collect data by distributing questionnaires to the upper-level managers of the SOEs and their subsidiaries. A total of 293 questionnaires were distributed to the respondents, and 97 responses were obtained for further analysis. The partial least square structural equation modeling (PLS-SEM) is used to test the hypotheses. A mediation-moderation research framework is employed.

The results show that intellectual capital has a positive effect on organizational performance. Further results also demonstrate that open innovation mediates the intellectual capital–organizational performance relationship and organizational inertia moderates the intellectual capital–organizational performance relationship. Theoretically, the findings contribute to the resource-based view (RBV) and knowledge-based view (KBV) by providing empirical evidence of the importance of distinctive internal resources in achieving superior organizational performance. Practically, the findings provide strategic information for managers that they should properly manage intellectual capital, open innovation and organizational inertia because of their effects on organizational performance.

First, this study addresses the previous research gaps by confirming that intellectual capital has a positive effect on organizational performance in the research setting of an emerging market. Second, by using a mediation research framework, this study shows that open innovation mediates the relationship between intellectual capital and organizational performance. Third, by using a moderating research framework, this study also reveals that organizational inertia weakens the relationship between intellectual capital and organizational performance. Those associations are rarely researched.

This paper aims to review the extant literature on open innovation and new product development (NPD) using bibliometric analysis to gauge the evolving journey of this concept in the domain of Business and Management.

The researcher used the Scopus database to search the relevant documents for bibliometric analysis. The data range was from 2006 till June 2023. Citation analysis, co-citation analysis and co-occurrence of authors' keywords were used for bibliometric analysis.

The paper charts the intellectual structure of literature related to open innovation and NPD. The five major themes emerge as prominent themes in the literature, i.e. Open Innovation: Conceptualization, Dynamic Capabilities and Competitive Advantages; Open Innovation: Contingencies and Possibilities; Co-creation and New Product Development (NPD); Open Innovation for Businesses: A Shifting Paradigm; and Implementing of Open Innovation in Industries: Cases. Besides this, the study also reveals the most influential authors, journals and countries in their contribution to open innovation and new product development. Future research directions are also presented.

The present study contributes on academic and managerial fronts. The study provides important insights contributing to the open innovation and NPD literature. From the organizational point of view, the study provides a detailed understanding of the concept of open innovation and NPD that can aid managers in acquiring a comprehensive knowledge of the concept before using it as a strategic intervention.

The present study identifies the gradual progression of this research area over time. It delineates key themes emerging from past literature, providing avenues for future research.

Quite often than not, a new industry can be created, thanks to the countless entrepreneurs and innovative activities across the globe. Smart city (SC) is one such industry and a living lab using the key roles of the digital platform that enable a seamless flow of information and knowledge for innovation within the SC. The purpose of this paper is to illustrate how SC can be a new regional industry engine through an “open collective innovation system” as its new concept. In particular, SC provides efficient transaction costs and knowledge flows. Eventually, SC can be an innovation hub for entrepreneurship through openness.

To frame the research goals, the authors used qualitative research methodologies based on grounded theory. In particular, the author used inductive reasoning to generate arguments and conclusions about the future of an SC as a new growth engine in the era of the fourth industrial revolution. Numerous documents and prior literature were used for the preliminary conceptualization of an SC. Interview data were then coded for reasoning in an open collective innovation system based on “openness”.

SC maximizes efficiency in practicing innovation. In the perspective of innovation costs, SC can minimize transaction costs, specifically the information processing costs, through data openness. In this context, transaction costs can be considered an economic equivalent of friction in a physical system. So, as the friction is low, some movements of an object on the surface are likely to be easy. SC is optimized for innovation activities through an “open collective innovation system”. In terms of innovation networks, an SC results in an innovation efficiency derived from both the network and the spatial agglomerations in physical and cyberspace. The efficiency-based SC itself overlaps knowledge creation, dissemination and absorption, providing an open innovation (OI) ecosystem.

This paper remarkably extends that SC can be an “open collective innovation system model” and a new conceptualization. Eventually, SC will play a crucial role in developing regional industries as a new growth engine. To operate as a new growth engine fully-fledged, the SC is needed to accumulate innovative assets such as the critical mass of residents, numerous firms, etc. However, this study has some limitations. First, difficulties in any analytic approach to SC resulted from their many interdependent facets, such as social, economic, infrastructural and spatial complex systems, which exist in similar but changing forms over a huge range of scales. Also, this research is at a quite an early stage. Thus, its theoretical stability is weak. So, this paper used the qualitative methodology with a grounded theory. Another limitation is in the research methodology. The limitation of using grounded theory adapted by this work is that the results of this study may not be generalizable beyond the context of this study. This non-generalizability occurs because ours is an inductive approach to research, meaning that the findings are based on data collected and analyzed. As such, the results of this study may not be applicable to other contexts or situations. In addition, the analysis of data in the grounded theory is based on researcher’s subjective interpretations. This means that the researcher’s own biases, preferences and assumptions may influence the results of the study. The quality of the data collected is another potential limitation. If the data is incomplete or of poor quality, it can cause researcher’s own subjective interpretations.

Findings of this study have some practical implications for enterprises, practitioners and governors. First, firms should use value networks instead of value chains. Notably, the firms that pursue new products or services or startups that try to find a new venture business should take full advantage of SC. This taking advantage is possible because SC not only adapts state-of-the-art information technology (e.g. sensor devices, open data analytics, IoT and fiber optic networks) but also facilitates knowledge flow (e.g. between universities, research centers, knowledge-based partner firms and public agencies). More importantly, with globalized market competition in recent years, sustainability for firms is a challenging issue. In this respect, managers can take the benefits of SC into consideration for strategic decisions for sustainability. Specifically, industrial practitioners who engage in innovation activities have capabilities of network-related technologies (e.g. data analysis, AI, IoT and sensor networks). By using these technologies in an SC, enterprises can keep existing customers as well as attract potential customers. Lastly, the findings of this study contribute to policy implementation in many aspects. At first, for SC to become a growth engine at regional or natural levels, strong policy implementation is crucial because SC is widely regarded as a means of entrepreneurship and an innovation plaza (Kraus et al., 2015). To facilitate entrepreneurship, maker spaces used for making the prototypes to support entrepreneurial process were setup within universities. The reason for establishing maker spaces in universities is to expand networking between entrepreneurs and experts and lead to innovation through a value network. One of the policy instruments that can be adapted is the “Data Basic Income Scheme” suggested by this research to boost the usage of data, providing content and information for doing business. Also, a governor in SC as an intermediator for the process of the knowledge flow should initiate soft configuration for SC.

This work makes two theoretical contributions to OI aspects: (1) it explores dynamic model archetypes; and (2) it articulates and highlights how SC with digital technology (i.e. in the AI, IoT and big data context) can be used to create collective knowledge flow efficiently. First, the findings of this study shed light on the OI dynamic model. It reveals important archetypes of new sub-clustering creation, namely, a system that underpins the holistic process of innovation by categorization in amongst the participating value network (Aguilar-Gallegos et al., 2015). In innovation studies, scholars have particularly paid attention to a cluster’s evolution model. In the process of innovation, the “open innovation dynamic model” suggested by this study illustrates sub-clustering that happens in value networks by taking the benefits of SC. Eventually, the evolution or development of sub-clusters can bring in a new system, namely, an OI system. Second, the findings of this study contribute to the understanding of the role of digital technologies in promoting knowledge flow. The usage and deployment of digital technologies in SC may enormously and positively influence innovative activities for participants. Furthermore, the rising of digital economy, in the so-called platform business, may occur depending on advanced technologies and OI. In doing so, the findings can further tow innovation research through juxtaposition between SC and innovation research (Mehra et al., 2021).

This paper shows that the function of an SC not only improves the quality of life but also acts as an engine of new industry through an open collective innovation setting using dynamic and ecological models.

In the knowledge economy, greater togetherness is the prerequisite for innovating and having more: selflessness extends scope while selfishness increases limitations. But human beings are not automatically attracted to innovation: between the two lies culture and cultural values vary widely, with the egoistic accent or the altruistic intonation setting the scene. In the representations of open innovation we submit to the reader’s attention, selfishness and selflessness are active in the cultural space.

Popularized in the early 2000s, open innovation is a systematic process by which ideas pass among organizations and travel along different exploitation vectors. With the arrival of multiple digital transformative technologies and the rapid evolution of the discipline of innovation, there was a need for a new approach to change, incorporating technological, societal and policy dimensions. Open Innovation 2.0 (OI2) – the result of advances in digital technologies and the cognitive sciences – marks a shift from incremental gains to disruptions that effect a great step forward in economic and social development. OI2 seeks the unexpected and provides support for the rapid scale-up of successes.

‘Nothing is more powerful than an idea whose time has come’ – this thought, attributed to Victor Hugo, tells us how a great deal is at stake with open innovation. Amidon and other scholars have argued that the twenty-first century is not about ‘having more’ but about ‘being more’. The promise of digital technologies and artificial intelligence is that they enable us to extend and amplify human intellect and experience. In the so-called experience economy, users buy ‘experiences’ rather than ‘services’. OI2 is a paradigm about ‘being more’ and seeking innovations that bring us all collectively on a trajectory towards sustainable intelligent living.

Entrepreneurship as a socially engaged and responsible movement is increasingly conceptualised as creating multiple sources of value: social, environmental, technological, cultural as well as financial, all contributing to wider economic performance. There is a rapid growth in the availability and expectation of ‘Open’ tools and resources, including innovation; data; research access; source code; educational and learning materials; and government. There is an increasing interest in their potential for value creation, requiring research attention and clarity of what ‘Open’ means in this context.

This chapter explores the following three dimensions of the ‘Open Space’ of freely available resources for entrepreneurship:

• (1)

  What is ‘Open’ in the context of entrepreneurship?

• (2)

  Why is Open Entrepreneurship (OE) important for conceptualisation, education and practice?

• (3)

  Can OE provide significant new opportunities for innovation, value creation and learning, and if so, how can these be realised?

What is ‘Open’ in the context of entrepreneurship?

Why is Open Entrepreneurship (OE) important for conceptualisation, education and practice?

Can OE provide significant new opportunities for innovation, value creation and learning, and if so, how can these be realised?

The chapter defines ‘OE’ as a unifying approach for value creation through a conceptual model combining ‘Open’ tools and resources. Open resources for digital and data-led entrepreneurship offer conditions for new, pervasive and distributed forms of value-creating entrepreneurial activity. These can create learning environments with rich access to data and resources, innovative connections and opportunities for co-creating value in multiple forms. This learning-centred approach builds on the concept of entrepreneurship as an educational philosophy of value creation for others. Without this, there are risks that entrepreneurial education, and the capabilities of micro-business owners and managers, may lag the development of an Open digital economy, rather than creating new forms of OE.

Innovation challenges are increasingly complex, cutting across distributed actors from different disciplines, organizations, and fields. Solving such challenges requires creating the capacities of opening up for innovation to access and develop a greater amount and variety of knowledge and resources. Perspectives on open source, open innovation, and interorganizational collaboration have explored such capacities, but from different origins and scopes of analysis. Our practice-based integrative framework of “opening innovation” helps highlight these differences and connect their relative strengths. Through a critical literature review paired with an analysis of different empirical cases from Hacking Health, a non-profit organization helping drive digital health innovation, the authors reveal the user-centric, firm-centric, and field-centric approaches to opening innovation that progressively connect a greater variety of actors and resources. The authors show how specific new relational practices they produce address the new relational dynamics these connections bring to accumulate more resources for innovation to keep progressing.