Abstract
PurposeThe paper focuses on how knowledge visualization supports the development of a particular multiobjective decision-making problem as a portfolio optimization problem in the context of interorganizational collaboration between universities and a large automotive company. This paper fits with the emergent knowledge visualization literature because it helps to explain decision-making related to the development of a multiobjective optimization model in Lean Product Development settings. We investigate how using ad hoc visual tools supports knowledge translation and knowledge sharing, enhancing managerial judgment and decision-making.Design/methodology/approachThe empirical case in this study concerns the setting up of a multiobjective decision-making model as a portfolio optimization problem to analyze and select alternatives for upgrading the lean production process quality at an FCA plant.FindingsThe study shows how knowledge visualization and the associated tools work to enable knowledge translation and knowledge sharing, supporting decision-making. The empirical findings show why and how knowledge visualization can be used to foster knowledge translation and sharing among individuals and from individuals to groups. Knowledge visualization is understood as both a collective and interactional process and a systematic approach where different players translate their expertise, share a framework and develop common ground to support decision-making.Originality/valueFrom a theoretical perspective, the paper expands the understanding of knowledge visualization as a system of practices that support the development of a multiobjective decision-making method. From an empirical point of view, our results may be useful to other firms in the automotive industry and for academics wishing to develop applied research on portfolio optimization.
Highlights
Lean Production Development (LPD) can be described as the application of lean principles to product development
According to Dombrowski et al (2012), the management of knowledge plays a critical role in LPD settings: a lean production system requires the creation and distribution of information, and the identification, acquisition, development, transfer, application and preservation of knowledge
This paper fits with the emergent knowledge visualization literature (Eppler and Pfister, 2014; Eppler and Platts, 2009; Gavrilova et al, 2017a) because it helps to explain decisionmaking related to the development of a multiobjective optimization model in LPD settings
Summary
Lean Production Development (LPD) can be described as the application of lean principles to product development. LPD relies on a set of engineering and work organization principles and techniques, many of which were first popularized by Toyota (Canonico et al, 2020). These are designed to achieve shorter lead times, reduced costs and higher quality than traditional product development. In LPD settings, this approach provides decision-makers with the information needed to interpret data on production processes (Canonico et al, 2018). The complex formulation of decision support systems such as the multiobjective optimization model means they need to use graphs to communicate with decision-makers to refine the model and improve the results (da Silva et al, 2017). There is, a growing need to make use of knowledge visualization to overcome interpretative biases of decision-makers
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