Open Innovation Platform Design: The Case of Social Product Development

Open Innovation as a new product development strategy has been used by businesses for decades. However, Social Product Development (SPD) has been recently introduced and popularized as an open innovation business model. The SPD model formalizes and monetizes the collaboration between an organization and creative communities through introducing new products and services. Either managed by intermediaries or directly by innovation sponsors, SPD platforms enable and support online innovative communities to ideate, collaborate, and network. Despite their abilities, many of these platforms do not provide fulfilling user experiences. To bridge this gap, the present study focuses on how SPD platform developers can offer more robust user interfaces (UI) and engaging user experiences (UX) alongside the six key SPD processes—social engagement, ideation, experiential communication, social validation, co-development, and co-commercialization. Building on experience and affordances theories, we offer a design framework that can more broadly inform the design and evaluation of open innovation platforms

“Experience First”: Investigating Co-creation Experience in Social Product Development Networks

Social product development (SPD) is a network-based innovation model in which firms or platforms use social mechanisms and social technologies to mobilize organizationally independent individuals––co-creators––to co-create new products. SPD networks require the maintenance of external participation across the innovation cycle to survive competition and thrive in the innovation sector. While prior research suggests that the viability, survivability, and productivity of social networks generally depend on user experience, we have limited evidence on the particular role of user experience in the context of SPD networks. Responding to this need, we introduce a conceptual model to theorize and operationalize co-creation experience in SPD networks. Through validating the proposed model, we demonstrate why co-creation experience is critical for predicting co-creators’ behavioral intentions and maintaining their actual contribution. Finally, we explore the theoretical and practical implications of the results. Future studies can leverage the findings to better capture co-creation experience and contribute to designing successful SPD networks

Classifying Motivations in Social Product Development Networks: a Discriminant Analysis of Actor Profiles

This study develops a classification model to predict social actors’ co-innovation behavior in social product development (SPD) networks based on motivational differences. The study first identifies motivations for actors to continuously participate in co-innovation activities. Then, three discriminant functions are developed and cross-validated to classify actor groups, based on their level of willingness to participate in three types of behaviors: ideation, collaboration, and socialization. The results indicate that financial gains, entrepreneurship, and learning are significant predictors of ideation behaviors. Enjoyment and learning are strong indicators of collaboration, whereas networking, enjoyment, and altruism are most strongly related to socialization behaviors. These findings highlight three classes of SPD actors (Ideators, Collaborators, and Networkers) based on motivational differences. These classes provide a theoretically parsimonious model to predict the co-innovation behaviors in SPD and highlight the importance of platform design to appeal to different classes of potential contributors

The Limits of Open Innovation: A Case Study of a Social Product Development Platform

Proponents of open innovation have long argued that essential resources for sustained innovation lie beyond an organization’s boundaries with its customers and value chain partners and that organizations must work collaboratively with internal and external stakeholders to build creative solutions. Unlike the traditional internal Research and Development model, open innovation practices are implemented differently (e.g., crowdsourcing, innovation marketplace, user innovation, and open-source community). Previous studies have articulated the general logic of these models, described the workings of some well-known examples, and examined the logic of engaging external actors in new product development. While open innovation can potentially facilitate and enhance the innovation process and outcomes, the downside and the limits of this openness remain understudied. Further research on the limitations of open innovation is more needed than ever since in the last few years many companies closed down their customer innovation communities, open innovation marketplaces were abandoned, and innovation intermediaries filed for bankruptcies. Open innovation can fade due to many reasons. Open innovation models such as crowdsourcing and innovation marketplace usually hold tight control over the innovation process and activities that require external actors. These platforms still set structurally defined requirements and standard procedures for the actors to ideate based upon. Meanwhile, they often predefine the innovation scope with narrowly defined tasks for the innovative actors to complete. With the sponsors’ tight control, external actors often cannot freely ideate and become motivated to deliver a creative solution. Even with incentives, the traditional open innovation models sometimes cannot reach the most effective innovation results. For example, the cost of implementing and running open innovation model sometimes does not justify its benefits. Research also showed that open innovation does not necessarily reduce the risk or failure rate of new products. Unpredictability in the innovation results and uncertainty in the environment, including sociotechnical factors, can also become a part of why open innovation fails. Hence, it is crucial to understand the open innovation process and its interplay with success or failure in new product or service development. In this study, we used the case of Social Product Development (SPD) as an open innovation model to investigate and document the limitations of open innovation in consumer product development. The SPD model encompasses many key and common features of open innovation models while being more dynamic and less restrictive. The SPD model also has a high failure rate. Examining the SPD process model thus helped us identify the limitations in the open innovation with some generalizability to other open innovation models. We first identified key activities in the SPD model, including social engagement, ideation, experiential communication, social validation, co-development, and co-commercialization, at three different levels: innovation activities, innovation projects, and innovation community. Then we examined when and how the identified activities at each level may fail to deliver the expected outcomes. We categorized the results (open innovation failure factors) into three phases associated with invention initiation, development, and commercialization. For each group, we identified contributing groups namely Innovation sponsor, innovation partners, and problem-solver. Lastly, we proposed a 3 by 3 activity-phase matrix that includes open innovation success/failure factors such as technology affordances, reward systems, mass-screening, community culture, collaboration support, social validation, social selling, osmotic communication, manufacturing agility, and intellectual property right. For each group, we also identified the responsible actors namely innovation sponsors, innovation partners, and problem-solver. Our findings provide a richer picture of SPD failure factors that holds relevance for the design of open innovation platforms. Our results also provide practical recommendations on open innovation platform governance including rules and policies concerning reward systems, partnerships, and manufacturing

An ambidextrous approach to practice-based innovation for social product development: lessons from a Dutch company

In the face of increasing competition, an organization’s capacity to acquire knowledge from the outside has become fundamental for new product development. Pertinent extant literature has stressed how an organization should practice social product development, allowing for the inclusion of all types of stakeholders in idea generation, selection, validation, and commercialization. This study investigates how organizations can acquire, maintain, and use different sources of knowledge via ambidextrous habits of exploitation and exploration to sustain social product development. A case study based on 27 semi-structured interviews and field observations at a leading, large-size, Dutch food-service company has been carried out. The findings illustrate the organizational processes and mechanisms that the company has adopted to address and combine practice- and research-based knowledge, as well as the main barriers limiting the accumulation and usage of this knowledge inside organizational boundaries

Taking Open Innovation to the Next Level: A Conceptual Model of Social Product Development (SPD)

The initial success of open business models is encouraging many organizations to implement their own co-innovation networks. Social product development, or SPD, represents a new business model enabled by social technology platforms. It extends collaboration beyond customer-involvement models to socially-engaged individual actors in the ideation and development of new products. The increasing adoption necessitates developing a framework to help researchers clearly understand and practitioners effectively design the SPD platforms. This paper develops a conceptual model for SPD and illustrates the validity of the model via a case study on a particular SPD platform, focusing on its business model, network governance, and key processes and design features. The proposed model is sufficiently general yet grounded in the phenomenon to guide future research on socially-enabled innovation and SPD networks in particular

Investigating Factors Influential on the Success of Social Product Development initiatives

Social Product Development (SPD) is represented by tenants including crowdsourcing, open innovation, cloud-based design and manufacture (CBDM) and mass collaboration that either individually or in concert contribute to the democratization of design, manufacture and innovation. Although widely and very successfully used in thousands of documented case studies [1], these tenants have not yet fully arrived within the domain of professional and commercial industrial product development. Amongst the reasons for this are a lack of clear definitions as to what these tenants are and clear guidelines or procedures that outline how they can be used to aid the various phases of the product development process. In this paper, the authors investigate how success for each of the tenants or any combination thereof can be influenced. The tenants of Social Product Development can be mapped according to three factors; proximity to other participants (Pa), proximity to leading organization (Po) and the number of participants (N). In this paper, the authors hypothesize that these three variables are related to the success of SPD tenants. An analysis study is then conducted with expert researchers to test this hypothesis and determine whether these variables are influential on SPD success. The expert researchers determined that only one relationship, between open innovation success and organizational proximity existed, therefore rendering all other relationships non-existent and disproving the hypothesis. Results and limitations of the study are discussed before aims for further research are highlighted. These include clarifying definitions of success for Social Product Development, providing success factors for the tenants and supporting practitioners in applying SPD tenants

Stimulating innovation on social product development: an analysis of social behaviors in online innovation communities

With firms' increasing adoption of social product development strategies, such as mass collaboration and crowdsourcing, online users are actively participating in the development of new products and services via social media platforms. Online innovation communities (OICs), one representative of such social media platforms, have been used by large firms to collect ideas from their users and facilitate the product development process. While it is extensively studied that product ideas with high popularity on OICs are of great importance to the product development, research on what social behaviors of online users lead to the high popularity is largely unclear. This paper conducts an empirical study by collecting a large-scale, quantitative dataset from an OIC between 2014 and 2018. With the analysis of users' online idea posting and commenting behaviors, our results reveal that the idea contribution experience, together with comment diversity positively in uence the overall popularity of an individual's ideas, while the motivation of providing comments is negatively related. Moreover, user's innovation capability poses a positive effect on both overall and average popularity of ideas. These findings can help firms better incentivise their users on OICs to improve the effectiveness and efficiency of social product development

Open innovation using satellite imagery for initial site assessment of solar photovoltaic projects

One of the responses to the fight against climate change by the developing world has been the large-scale adoption of solar energy. The adoption of solar energy in countries like India is propagating mainly through the development of energy producing photovoltaic farms. The realization of solar energy producing sites involves complex decisions and processes in the selection of sites whose knowhow may not rest with all the stakeholders supporting (e.g., banks financing the project) the industry value chain. In this article, we use the region of Bangalore in India as the case study to present how open innovation using satellite imagery can provide the necessary granularity to specifically aid in an independent initial assessment of the solar photovoltaic sites. We utilize the established analytical hierarchy process over the information extracted from open satellite data to calculate an overall site suitability index. The index takes into account the topographical, climatic, and environmental factors. Our results explain how the intervention of satellite imagery-based big data analytics can help in buying the confidence of investors in the solar industry value chain. Our study also demonstrates that open innovation using satellites can act as a platform for social product development