Playing chess or playing poker? Assessment of uncertainty propagation in open innovation projects

How does risk-taking affect the green technology innovation of high-tech enterprises in China: the moderating role of financial mismatch

As a core driver for the high-tech enterprises, green technology innovation is crucial, even with high financial risk. Against this background, this paper empirically examines the impact of risk-taking on green technology innovation of high-tech enterprises, taking Chinese A-share listed companies from 2007 to 2020 as the research sample and considering the moderating effect of financial mismatch. Findings show the following: First, the effect of risk-taking on green technology innovation of high-tech enterprises is insignificant in most cases, and the inhibitory effect of financial mismatch is partly supported. Second, financial mismatch only counter-regulates the inhibitory effect of systematic risk-taking on the number of invention patents granted in the eastern sample. Third, the effect of risk-taking on green technology innovation is significantly heterogeneous in terms of property rights and regional heterogeneity, regardless of considering the moderating effect of financial mismatch or not. Finally, the policy implementations point out that the government should create a favorable investment environment, financial institutions should adjust the way of capital allocation, while high-tech enterprises should broaden the financing channels to enhance their risk-taking ability, and promote green technological innovation to achieve high-quality economic development.

A new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps

Purpose

New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project portfolio selection is a complex and challenging task. Despite the management's efforts to implement the best project portfolio selection practices, many projects continue to fail or miss their target. The problem is that selecting R&D projects requires a deep understanding of strategic vision and technical capabilities. However, many decision-makers lack technological insight or strategic vision. This article aims to provide a method to capitalize on the expertise of R&D professionals to assist managers in making informed and effective decisions. It also provides a framework for aligning the portfolio of R&D projects with the organizational vision and mission.

Design/methodology/approach

This article proposes a new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps.

Findings

The proposed strategy plane helps decision-makers align R&D project portfolios with their strategies to combine a strategic view and numerical analysis in this research. The proposed strategy plane consists of four areas: Exploitation Zone, Challenge Zone, Desperation Zone and Discretion Zone. Mapping the project into this strategic plane would help decision-makers align their project portfolio according to the corporate perspectives.

Originality/value

The new approach combines the efficiency and uncertainty dimensions in portfolio selection into an integrated framework that: (i) provides a complete representation of the stochastic decision-making processes, (ii) models the endogenous uncertainty inherent in the project selection process and (iii) proposes a computationally practical and visually unique solution procedure for classifying desirable and undesirable R&D projects.

The Relationship BetweenUncertainty and Task Execution Strategies in Project Management

Common project management methodologies do not consider project task uncertainty for determining appropriate task execution strategies. This article proposes an actionable task-model based approach to integrating uncertainty considerations in project management. The authors developed the article in an industrial setting, interviewing experienced project managers, and observing 12 innovation projects. The resulting models were validated in four innovation projects. This process also revealed recurring patterns of how projects deal with high levels of uncertainty. The heightened awareness of uncertainty levels of project tasks, combined with four fundamental task execution strategies, has a significant impact on project managers’ decisions.

Dispersed knowledge management in ecosystems

Purpose

Accessing and sharing dispersed knowledge in ecosystems is neither easy nor automatic. In ecosystems, focal firms should purposely create the right conditions and act to deal with dispersed knowledge. This study aims to investigate how focal firms manage dispersed knowledge in ecosystems characterized by a set of autonomous, heterogeneous, yet interdependent actors involved in experimentation under uncertainty.

Design/methodology/approach

Following a conceptual framework based on preceding literature, this study conducted a broad qualitative case study of 6 firms and 12 projects, with 43 semi-structured interviews to identify the patterns of actions associated with dispersed knowledge management (KM) in ecosystems. This paper combines coding and multiple case comparisons to examine the processes and strategies used by the firms to strategically manage dispersed knowledge in ecosystems.

Findings

This paper proposes a framework that articulates a new type of orchestration (dispersed knowledge orchestration) and offers a new set of dispersed knowledge strategies (transfer, modularity and circular) for ecosystems.

Practical implications

Innovation and knowledge managers play the roles of dispersed knowledge orchestrators. The study offers guidance on how focal firms should carefully use a particular set of approaches (e.g. integrative theorization) including a portfolio of dispersed knowledge strategies in ecosystems.

Originality/value

Current literature on KM and ecosystem management offers a limited understanding of how organizations manage dispersed knowledge in ecosystems. The research provides three major original contributions. First, the framework contributes to broadening the current understanding of ecosystem orchestration by identifying the micro-foundations of dispersed knowledge orchestration: integrative theorization, nurturing distributed sensemaking and a new chapter for ecosystem governance (i.e. dispersed knowledge governance). Moreover, the framework proposes a new type of strategy, the dispersed knowledge strategy. Finally, by exploring the interplay between the micro-foundations of dispersed knowledge orchestration and dispersed knowledge strategy, the results contribute to a multi-level approach in the field.