There is a strong emergence of new spaces to foster innovation all over the world (Fablabs, Living Labs and Design Factories, among others). Past experiences have shown these types of projects involving “innovation laboratories” are at risk of not succeeding in their goals. Although several studies have tackled the problem of design, development and sustainability of innovation laboratories, there is still a gap in understanding how the capabilities and performance of these environments are affected by the strategic intentions at the early stages of design and functioning. Throughout this work, eight frameworks from the literature that analyze innovation laboratories are identified and compared. Then, based on both literature and the authors' experience, an updated framework is proposed as the basis for a guidance tool for researchers and practitioners aiming to assess or to adapt an existing project. As part of the operationalization process of the framework, a maturity grid‐based assessment tool is proposed to evaluate the maturity degree of an innovation laboratory. Afterwards, to evaluate the viability and to integrate the perception of innovation laboratory managers, an exploratory study with answers from fifteen laboratories from five different countries is performed. Insights and implications for emerging and already existent projects of innovation laboratories are then discussed.
Purpose
The purpose of this paper is to propose a quantitative methodology for the identification of the causal relationships between strategic objectives in a strategy map of a balanced scorecard. This is done to face the possible weaknesses described in the literature regarding the causal links and the difficulty in validating the relationships.
Design/methodology/approach
The proposed method combines the multi-criteria decision-making method called decision-making trial and evaluation laboratory (DEMATEL) and an optimization model. DEMATEL is used to establish the importance of the strategic relations between strategic objectives, and the optimization model is used to find the relations that are more “important” and should be included in the strategy map. The method was created by reviewing the existing literature, modeling the problem, and applying it in a company.
Findings
The most important results of applying this methodological design include that the proposed method maintains the BSC classical structure; it also enables the generation of several alternatives to support the decision-making process in terms of strategic objectives for a better organizational performance.
Practical implications
The method facilitates the decision-making process by presenting several alternatives of strategy maps according to different levels of organizational criteria. In fact, these alternatives help the organization in focusing on the most important aspects of the strategy map. Consequently, managers may identify where to pay more attention and resources in order to achieve the most important objectives of the company. Hence, this method, as a support for decision makers, enables (and requires) the active participation of senior managers and any kind of decision makers in creating and valuating objectives, relations, constraints, importance, and parameters of the optimization model.
Originality/value
DEMATEL has been used to design strategy maps. The contribution of the paper is the use of a linear programming model to select those relationships that should be included in the strategy map. It allows manager to focus on those strategic elements that are important from a strategic point of view. The application in a company showed that the contribution is not only theoretical but practical as well.
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