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Knowing the factors influencing the success of collaborative innovation is particularly relevant for both academics and practitioners. Nonetheless, many studies have regarded the megatrends influencing innovation imperatives, the development of co-innovation strategies, the selection of partners and the involvement of user communities, but not so much the understanding of how the co-innovation process is concretely designed and managed. Adding to extant research, the purpose of this paper is to explore how companies collaborate in co-innovation processes.

A longitudinal, single case study has been conducted on the co-innovation process between Loccioni, an Italian medium-sized, high tech family firm, and Pfizer, one of the largest companies operating in the pharmaceutical sector.

From the case study analysis, three main results have emerged. First, the role of medium-sized companies in leading the co-innovation process as both the initiator and orchestrator. Second, the interplay between the local and the global dimension of co-innovation and the importance of (un)formal roles in innovation. Third, the “double funnel” of co-innovation, linking both the technological and the relational dimensions. Specifically, the case highlights the relevance of the relational – beyond the technological – aspects of co-innovation, providing a relational model that links the geographical dimensions (local/distant) and the role of specific individuals.

The paper presents an example of how a medium-sized firm has implemented its co-innovation process, shedding new light on possible barriers and success factors that other smaller or similar companies may follow when dealing with large multinationals.

Co-innovation networks face the important challenge of cultivating collective innovation outcomes while also preserving the interests of individual contributors. Addressing this challenge requires first understanding and then managing individuals’ perception of co-innovation risks. The purpose of this paper is to provide a meaningful approach to addressing co-innovation risks using a valid and reliable model to assess actors’ perception of risk and examine its effect on actor co-innovation behavior.

The construct of co-innovation risk from the actor’s perspective was conceptualized based on a case study of a co-innovation network. The measurement items underwent a pilot study and a field study to establish the necessary reliability and validity. This paper also empirically assesses a nomological network that illustrates the effect of risk on co-innovation behavior with a moderating effect of prior experience.

Co-innovation actors perceived four different individual risks: time, social, intellectual property right, and financial. The empirical results from the field study demonstrate a high degree of confidence in both translation validity and criterion-related validity. Negative effects of perceived co-innovation risk on actors’ continuous intention to ideate, collaborate, and communicate in co-innovation were evident, but prior experience moderated these relationships.

Drawing from co-innovation and individual risk literature, this study develops and validates a general instrument to measure co-innovation risk from the actors’ perspective. The result is a reliable and parsimonious instrument with 15 items, which contributes significantly to future empirical investigations of co-innovation behavior on virtual platforms.

While co-innovation with third parties (e.g. customer or supplier) has been widely documented, the literature seems to pay scant attention on co-innovation with business partners. Building on the resource dependence theory (RDT) and the input-process-output model, the purpose of this paper is to examine how four criteria of business partner selection affect service delivery co-innovation, which, in turn, influences firms’ competitive advantage.

A mail survey was sent to 600 IT service firms in Taiwan, the target respondents being senior marketing managers in charge of collaborative new service development. A total of 120 usable questionnaires were collected, for a response rate of 20 percent.

The findings support the argument that all four criteria of business partner selection have positive relationships with service delivery co-innovation. Meanwhile, adopting these criteria, firms’ service delivery co-innovation is able to create superior competitive advantage.

The findings enrich the existing literature by proposing and empirically confirming that the use of appropriate criteria to select business partners enhances the effectiveness of firms’ service delivery co-innovation and competitive advantage.

Managers must be aware of the criteria to select their business partners, in terms of developing service delivery co-innovation.

This study adds to the service innovation literature by providing support for the RDT that partner reliability, partner complementarity, partner expertise, and partner compatibility are important business partner selection criteria to create service delivery co-innovation and achieve firms’ competitive advantage.

The importance of co-innovation platforms has been well established, but a valid and reliable instrument to measure the affordances of these platforms for co-innovation behavior has not yet been reported in the literature. A robust, validated instrument to measure co-innovation platform affordances (PAs) will facilitate the conduct of studies across different platforms and contribute to enhanced understanding of co-innovation behaviors, outcomes, and platform design. The purpose of this paper is to conceptualize co-innovation PAs, develop a reliable measurement instrument capturing critical facets of co-innovation, namely ideation, collaboration, and communication, and validate the instrument.

The construct of PAs was conceptualized based on the findings from two case studies of co-innovation networks and the key characteristics of social mediating technology affordances. The measurement items newly developed via a case study underwent a two-round exploratory analysis to ensure face validity and content validity. The resulting instrument was subjected to a pilot study and a field study to establish the necessary reliability and validity.

The findings of the study reveal that co-innovation PAs have three distinctive components, namely ideation, collaboration, and communication. Furthermore, the results of the study suggest that PAs are most appropriately operationalized as a second-order construct comprising all three components. The empirical results from the field study show a high degree of confidence in both translation validity and criterion-related validity.

Drawing from co-innovation and affordances literature, this study develops and validates a general instrument to measure co-innovation PAs. The result is a reliable and parsimonious instrument with 12 items. The authors believe that the instrument can contribute significantly to future empirical investigations of co-innovation behavior on virtual platforms.

Building on recent advances in innovation research on developing country agriculture, this paper explores the concept of co-innovation, i.e. innovations that combine technological, organisational and institutional changes and that encompass different actors in and around the value chain. The purpose of this paper is to contribute to a further conceptualisation of co-innovation and show its usefulness for analysing innovation initiatives in agrifood chains.

The paper combines two streams of literature (innovation systems and value chains) and is based on a review of the experiences with innovation in three different value chains in three African countries: potato in Ethiopia, pineapple in Benin and citrus in South Africa.

Co-innovation is the combination of collaborative, complementary and coordinated innovation. “Collaborative” refers to the multi-actor character of the innovation process, where each actor brings in specific knowledge and resources. “Complementary” indicates the smart combination of technological, organisational and institutional innovation. “Coordinated” draws attention to the importance of chain-wide adjustments and changes to make innovation in one stage of the chain a success.

The identified dimensions of co-innovation (the triple “co-”) provide a practical guide for the design of effective interventions aimed at promoting innovation in African agrifood chains.

The paper is the first to provide a comprehensive conceptualisation of co-innovation. On the basis of both theoretical arguments and evidence from three illustrative case studies it is argued that successful innovation in agrifood chains requires the innovation process to be collaborative, coordinated and complementary.

The purpose of this paper is to investigate the relationship between “social identities” and “innovation as a collective act”, specifically how multiple social identity processes construct, reconstruct and revise organisational identity, and create positive commitment and motivation for collaborative innovation (co‐innovation).

The paper adopted an inductive theory building from cases (particularly, theory building from a singular case) methodology. As the purpose of the research is to develop theory and not to test it, theoretical sampling was used. The particular case was specifically chosen because the business – a successful co‐operative for over 30 years – enables the investigation of organisational identity construction and development on different levels including intra‐ and inter‐organisational interactions.

While still leaving scope for the readers to make interpretations and conclusions from the case themselves, the study suggests some general conclusions drawn from the interrelationship of key concepts in the case, and from the subsequent model of evolving multiple social identity processes for co‐innovation that emerged. These conclusions may not only broaden “the social identity approach to organisations” and “organisational innovation”, but also link their underlying theories.

The case explains the phenomena in a particular social system, namely a co‐operative business with a common purpose. The co‐operative model can be associated with organisations with poor democratic governance and accountability. The ultimate success of the case depended on the ability of the organisation and its members to construct and maintain a common organisational identity of innovation and to innovate collectively.

This paper extends “the social identity approach to organisations” and “organisational innovation” by developing a model, inductively sourced from a “real‐life” case, for explaining the construction, reconstruction or revision of social identities that result from the reciprocal relationship between co‐innovating organisations. The proposed model suggests an evolutionary (rather than a revolutionary) framework for the presentation of co‐innovation as a product of social identity construction.

This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation.

The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory.

The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners’ understanding of using unstructured data.

This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives.

This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights.

Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.

This study sets out to examine the relationship between firms' learning orientation and network collaboration. The aim is to investigate how learning orientation enhances network collaboration and to discuss the role of the co‐innovation focus in the learning orientation‐network collaboration relationship.

Based on a partial least squares (PLS) structural equation modeling analysis of 90 small and medium‐sized industrial firms (SMEs), the study tests hypotheses regarding how two diverse learning orientations – i.e. exploration and exploitation – precede firms' network collaboration.

The analysis shows that learning drives firms' co‐innovation focus in terms of product and process co‐innovation. In particular, the explorative learning orientation is found to foster firms' network collaboration through product co‐innovation. Exploitative learning orientation promotes process innovations but discourages networking.

A key implication for business practitioners is the understanding that SMEs' explorative learning approaches drive their network collaboration. The development of novel product innovation calls for learning with partners in inter‐organizational networks, whereas process improvements rely on the firm's intra‐organizational learning.

The paper provides evidence of the connection between firms' learning orientation, co‐innovation focus, and networking. Thus, it contributes to the literature on organizational learning, innovation management, and business networks by explicating how learning drives a firm's networking through its co‐innovation focus.

This paper aims to propose an extended model to examine these motivations. As technology-led changes have revolutionized the marketplace, researchers and practitioners have grown keen to understand customers’ motivations for engaging in co-innovation in online communities.

The research model is based on a review of previous literature and relevant business practices.

The proposed conceptual model can be used to test empirically and explicate customers’ attitude towards engagement in co-innovation communities in the hospitality industry. Three major motivations drive customer engagement in online co-innovation communities (OCCs): brand equity, sense of community and monetary incentive. Customers’ prior experience with co-innovation projects also moderates the effects of the three motivations on customers’ attitude towards engagement in OCCs.

The proposed model highlights the importance of engaging customers through OCCs to create service innovations. These OCCs advance customers’ active participation in the firm’s co-creation and co-innovation process. Leading service firms already rely on online brand communities to stay on the cutting edge. Co-creation represents a unique, strategic partnership between the firm and the customer that can enhance both the customer experience and the firm’s innovativeness.

This study provides an initial exploration of the key components of the co-innovation of service through online communities in the hospitality industry.

Previous work has asserted that the co-innovation process in the music business is composed of four stages, i.e. co-discovery, co-creation, co-delivery and co-capture. This study aims to re-examine and validate this proposed conceptualisation by gathering and interviewing additional respondents, specifically academics and professional event organisers, who were not formerly involved. By gaining more insight from different stakeholders, this study expects to gain more reliable results regarding the proposed concept derived from the previous study.

This study uses the case study method by carrying out qualitative interview data collection from 11 respondents. Narrative analysis is used in examining the findings. Pattern matching is used as the basis of the analysis using the proposed conceptualisation from co-discovery to co-capture of co-innovation as the rival analysis to the empirical findings discovered in this study. This paper also discusses how the validity and reliability of the qualitative analysis carried out are ensured.

This study supports the notion that the co-innovation process in the music industry follows the four stages of co-discovery, co-creation, co-delivery and co-capture. The respondents, from different professional backgrounds, interviewed in this study indicated and validated that the proposed framework aligns with their actual practices, expectations and realities, along with their specific roles in the music industry’s ecosystems.

The results of this study can be used as a reference in developing guidelines or policies for co-innovation practices in the music business, which previous studies have not explored, e.g. focusing only on preconditions for positive collaboration, open license and music for co-creation or discussions that are merely conceptual.

This study validates the co-innovation process in the music business proposed by the previous works, which integrates the value chain thinking concept within the analysis.