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Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.

This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.

The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.

The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.

Effective cooperative communication and knowledge management capabilities are particularly important in the cross-team cooperation. Based on the social exchange theory, this paper aims to further explore the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in open innovation projects (OIPs).

This paper takes China’s high-tech enterprises as the research object by using a paired questionnaire survey based on 168 pairs of OIPs. Hayes’ PROCESS programme and the bootstrap technique are used to test the hypothesis model and the significance of the mediation effect.

This study finds that cooperative communication is an effective mechanism for the internal and external interaction of OIPs. Knowledge sharing plays an intermediary role in the relationship between cooperative communication and co-innovation performance; both explicit knowledge sharing and tacit knowledge sharing have a significant positive impact on co-innovation performance. And the impact of cooperative communication on co-innovation performance is based on effectively promoting the knowledge sharing of partners.

This research incorporates cooperative communication, knowledge sharing and co-innovation performance into a unified research framework to study the co-innovation at the project level, enriches the research scenario on the mechanism of cooperative behaviour, deepens the understanding of the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in OIPs, verifies the mediating role of knowledge sharing to co-innovation, and also helps extend the social exchange theory to a new research setting.

At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in concert. Therefore, current study intended to conduct more deep research into emerging phenomena and attempts to cover the gap by exploring how entrepreneurial orientations (EO) emphasize the use of two emerging capabilities under the moderating role of environmental dynamism which in turn augment co-innovation and hotel performance.

Data were collected from four-star and five-star hotels located in Kula Lumpur and Langkawi in Malaysia. A total of 260 responses were obtained from IT staff and senior managers with the assistance of a Manpower agency for data analysis. The hypotheses were examined by analyzing the data using PLS-SEM technique through Smart PLS 3 software.

The result revealed that EO has a positive and significant effect on co-innovation (CIN). Additionally, the BDAC and AIC have been tested and proven to be potential mediators between EO and CIN. Also, environmental dynamism as moderator has positive and significant effect on BDAC and co-innovation performance, however, not significant impact on AIC and co-innovation performance. Lastly, findings displayed positive and significant moderated mediation impact of environmental dynamics on BDAC and CIN with hotel performance, but not significant influence on AIC and co-innovation with hotel performance. For theoretical corroboration of the research findings, the current study integrated EO, resource-based view theory and contingent dynamic capabilities (CDC), because neither single stance can explicate an extant research framework.

This study anticipated the several implications for the entrepreneurs of hospitality industry. Managers are recommended to invest in the entrepreneurial traits of the employees/organizations and make strategic readjustment of their capabilities for sustained business performance.

The study goes beyond the normal inquiry by investigating moderated mediation impact of environmental dynamism between two emerging capabilities, co-innovation and hotel performance relationships. Another novelty of this study is to culminate the exploitation and adoption of emerging IT-based capabilities in cross domains of management, entrepreneurship, information systems management within the hotel industry.

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.