The innovation ecosystem construct has emerged as a promising approach in the literature on strategy, innovation and entrepreneurship. It draws upon former business ecosystem literature. However, the ...term innovation ecosystem has been employed in very polysemic and sometimes competing ways. Many adjectives used with reference to innovation ecosystems render the consolidation of the construct more difficult - which its characteristics, boundaries and relation with other, to some extent competing, constructs, such as supply chain and value chain are. To clarify concepts, to identify trends and research opportunities, we conducted a systematic literature review from 1993 to 2016, with a hybrid methodology including bibliometric and content analysis. Besides highlighting the most influential papers and exhaustively discussing the innovation ecosystem concept and its variations, we identify a turning point in the literature, the transition from business ecosystem to innovation ecosystem. Business ecosystem relates mainly to value capture, while innovation ecosystem relates mainly to value creation. We conclude by describing six research streams in innovation ecosystem: industry platform × innovation ecosystem; innovation ecosystem strategy, strategic management, value creation and business model; innovation management; managing partners; the innovation ecosystem lifecycle; innovation ecosystem and new venture creation. These streams lead us to propose opportunities for further research to solidify the innovation ecosystem concept.
Radically innovative products and services are frequently developed and commercialized by new ventures. In this context, entrepreneurs may face the challenge of coordinating a complex network of ...actors in the presence of individual and collective uncertainties. Previous literature on entrepreneurship has focused on how entrepreneurs manage individual uncertainties (those that affect a single firm) rather than collective uncertainties that also affect members of the innovation ecosystem, which in turn may fundamentally affect the survival and growth of new ventures. Drawing on five longitudinal, inductive, in-depth case studies of start-ups and their innovation ecosystems, we find that current approaches for coping with individual uncertainties do not consider the impacts of uncertainties and actions on the innovation ecosystem partners. In that sense, entrepreneurs themselves may contribute to the propagation of uncertainties in the innovation ecosystem. We also identify processes by which entrepreneurs manage collective uncertainties in the innovation ecosystem, i.e., perceiving collective uncertainties, bridging uncertainties, conducting collective learning experiments and building a common template. This study improves understanding of how entrepreneurs act in uncertain environments.
•How do entrepreneurs manage collective uncertainties in the innovation ecosystem?•Collective uncertainties affect a group of firms or other types of organizations.•We researched five innovation ecosystems created by start-ups.•We identified processes by which entrepreneurs manage collective uncertainties.•Entrepreneurs may contribute to the propagation of uncertainties.
Managers of exploratory projects might face uncertainties over long timeframes at different levels (e.g., project, portfolio, organization, and network). Although literature offers some guidance on ...how to deal with uncertainties (mainly at the project level), there is a need for more empirical ground and theoretical development of a systemic approach to the management of uncertainties. To fill this gap, this article employs a multiple case approach in two established firms, investigating six exploratory projects. As main contributions, we identified new categories of uncertainties (primitive, structural, and elementary) and aspects related to managing these uncertainties.
The innovation process has traditionally been understood as a predefined sequence of phases: idea generation, selection, development, and launch/diffusion/sales. Drawing upon contingency theory, we ...argue that innovation process may follow a number of different paths. Our research focuses on a clear theoretical and managerial question, i.e., how does a firm organize and plan resource allocation for those innovation processes that do not easily fit into traditional models. This question, in turn, leads to our research question: Which configuration of innovation processes and resource allocation should be employed in a given situation, and what is the rationale behind the choice? Based on a large-scale study analyzing 132 innovation projects in 72 companies, we propose a taxonomy of eight different innovation processes with specific rationales that depend on a project׳s contingencies.
•Not all innovation projects fit in the traditional linear process from-idea-to-launch.•Which configuration and rationale of the innovation process for which situation?•We researched 132 cases of innovation projects in 72 companies.•We propose eight types of innovation processes according to specific contingencies.•Uncertainties shape the structure and the content of the innovation process.
PurposeAlthough there is a growing research stream on Performance Measurement and Management Systems (PMMS) in Ecosystems literature, current research offers limited theoretical insights into how ...PMMS deal with two types of strategies in uncertain ecosystems: ecosystem-based strategy – EBS (at the focal firm level) and ecosystem strategy – ES (at the ecosystem level). This study aims at identifying how PMMS are employed to deal with different types of strategies in uncertain ecosystems.Design/methodology/approachThe authors employed an inductive, rich multiple case approach in five focal firms with platform ecosystems. Data collection involved multiple sources of information (primary and secondary data), combing retrospective and longitudinal perspectives. Data analysis combined replication and comparison logic with coding.FindingsThis study identifies four major distinctive dimensions of Ecosystem PMMS under uncertainty: (1) Integrative Performance (considering the different ecosystem actors’ performance), (2) Interdependence Performance (mutual, yet not necessarily convergent amongst ecosystem partners), (3) Regulative Performance (paradoxical in nature, having to cope with both flexibility and stability) and finally (4) Phased Learning Performance (non-linear).Research limitations/implicationsOur primary contribution is a new framework for PMMS literature: a performance measurement and management system for dealing with strategies in ecosystems. This framework enables managing performance regarding both types of strategies (EBS and ES) and their interplay in uncertain ecosystems.Practical implicationsThe ecosystem management requires focal firms to measure and manage the overall ecosystem’s performance, and it varies according to the type of strategy adopted in each case. Our framework provides dimensions that guide firms to build and implement PMMS for an ecosystem consistent with the ES. Therefore, it may improve performance, especially in uncertain business contexts.Originality/valueThe findings enrich PMMS literature in an ecosystem context related to the ES in uncertain environments.
Setting the right approach for new product development (NPD) in the presence of uncertainty remains an ongoing debate in innovation management. Stage‐gate systems (SGS) and agile methodology (AM) are ...the dominant approaches. Recently, hybrid approaches (combining SGS and AM) have been proposed. Although these hybrid approaches represent a significant development in NPD, combining them without considering their design principles might lead to contradictory and competing conceptual formulations, thus increasing the difficulty of comparison among studies. Moreover, scholars and practitioners may struggle to understand when, why and how a certain configuration of the NPD process provides the right response to different manifestations of uncertainty. The current literature faces problems regarding the clarity of design principles (e.g. flexibility and adaptability), and this has led to research gaps concerning the uncertainty contingency and outcomes of hybrid approaches. This study combines bibliometric and content analyses to identify four design parameters and principles of NPD hybrid approaches: flexibility, adaptability, velocity and integration. Our findings might help advance the development and comparison of different hybrid approaches.
The bullwhip effect, or how uncertainty associated with the end customers' demand propagates through the entire supply chain, has been widely discussed in supply-chain management literature. Although ...there is a well-established research stream on the causes and mitigating factors for the bullwhip effect in forward supply chains, few studies have investigated how this phenomenon manifests itself in closed-loop supply chains. We argue that this phenomenon can affect the supply chain's environmental performance by increasing emissions, waste and consumption of natural resources. Aiming at filling this theoretical gap, this article compares the causes and mitigating factors of the bullwhip effect in forward supply chains and closed-loop supply chains. To this end, we employ a systematic literature review that combines bibliometric and content analyses. The studies examined in our review indicate that the causes of the bullwhip effect in closed-loop supply chains are similar to those in forward supply chains. However, most of the studies have not considered that the quality of returned products are different from the quality of their new counterparts' products, adding another variable into the complexity of a given supply chain which, in turn, could lead to higher variability, thereby causing the bullwhip effect. Regarding mitigation, we found that the primary mitigating factor is related to increasing the product return rate. Moreover, we suggest that closing a supply chain can reduce the bullwhip effect, which could lead to positive impacts in the environmental performance of supply chains.
•This paper addresses a great (and not well investigated) challenge in open innovation projects: the uncertainty propagation.•This paper presents a framework of uncertainty propagation assessment for ...interorganizational open innovation projects.•We identify three distinct approaches to mitigate the detrimental impact of uncertainty assessment.•Understanding the consequences of uncertainty propagation in interorganizational open innovation projects leads to positive project performance.•We increase the portfolio of project management approaches to counter uncertainty in open innovation projects.
Consider an interorganizational open innovation project, in which different organizations cooperate to generate value for clients or to solve a technological problem. In this setting, both the focal firm and the partners face uncertainties over time (e.g., technological uncertainties, market uncertainties) and, therefore, the performance of the focal firm and the overall interorganizational project depend on that firm's ability to assess potential uncertainties. The process of diffusion of a particular uncertainty throughout an inter-organizational project can be defined as uncertainty propagation. Assessment of uncertainty propagation can be employed to mitigate its detrimental impact. This paper connects previous studies of open innovation, uncertainty management and project management by providing a comprehensive, but structured, framework to assess uncertainty propagation. First, we propose the underlying causes of uncertainty propagation. Then, we present the three different approaches to its assessment, based on causes, effects and protection.
Managing uncertainty propagation in innovation ecosystems Gomes, Leonardo Augusto de Vasconcelos; Facin, Ana Lucia Figueiredo; Salerno, Mario Sergio
Technological forecasting & social change,
10/2021, Letnik:
171
Journal Article
Recenzirano
•The propagation of uncertainty occurs when information, perceived as revealing uncertainty, spreads through the innovation ecosystem.•This study explores how entrepreneurs cope with uncertainty ...propagation in innovation ecosystems.•We conducted four in-depth inductive case studies of innovation ecosystems.•We identified four mechanisms for dealing with uncertainty propagation: i) identification of a protected niche; ii) use of cognitive alignment; iii) adoption of sequential learning; iv) use of a communication platform.•These mechanisms serve as the basis of a holistic framework that can be used to mitigate the effects and occurrence of uncertainty propagation.
The propagation of uncertainty occurs when information, perceived as revealing uncertainty, spreads through the innovation ecosystem. This paper explores how entrepreneurs cope with uncertainty propagation. Drawing on four in-depth inductive case studies of innovation ecosystems, we characterise the phenomenon of uncertainty propagation and the mechanisms by which entrepreneurs might manage the same. The mechanisms are: i) identification of a protected niche; ii) use of cognitive alignment; iii) adoption of sequential learning; and iv) use of a communication platform. These mechanisms serve as the basis of a holistic framework that can be used to mitigate the effects and occurrence of uncertainty propagation. Overall, this paper contributes to the reinvigoration of the study of uncertainty and the management of uncertainty in new firms and in the innovation ecosystems.
Pivot decisions in startups: a systematic literature review Flechas Chaparro, Ximena Alejandra; de Vasconcelos Gomes, Leonardo Augusto
International journal of entrepreneurial behaviour & research,
05/2021, Letnik:
27, Številka:
4
Journal Article
Recenzirano
PurposeEntrepreneurs' pivot decisions are poorly understood. The purpose of this paper is to review the existing literature on pivot decisions to identify the different conceptualizations, research ...streams and main theoretical building blocks and to offer a baseline framework for future studies on this phenomenon.Design/methodology/approachA systematic literature review of 86 peer-reviewed papers published between January 2008 and October 2020, focusing on the pivot decision in startups, was performed through bibliometric, descriptive and content analyses.FindingsThe literature review identifies four research streams concerning the pivot concept – pivot design, cognitive, negotiation and environmental perspectives. Building on previous studies, this paper provides a refined definition of a pivot that bridges elements from the four research streams identified: a pivot comprises strategic decisions made after a failure (or in the face of potential failure) of the current business model and leads to changes in the firm's course of action, resource reconfiguration and possible modifications of one or more business model elements. This study proposes a framework that elaborates the pivot literature by identifying four stages of the pivot process addressed in the existing literature: recognition, generating options, seizing and testing and reconfiguration.Originality/valueThis study provides a comprehensive review, enabling researchers to establish a baseline for developing future pivot research. Furthermore, it improves the conceptualization of pivots by summarizing prior definitions and proposing a refined definition that places decision-making and judgment at its center. That introduces new contextual and behavioral elements, contributing to a better understanding of how entrepreneurs assess alternative courses of action and envision possible outcomes to redirect a venture after failure.
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