Abstract
266 fuzzy front-end (FFE) studies in the new product development (NPD) sector were examined. The studies were selected using a bibliometrics method, and chronologically and statistically examined with ten criteria divided into two dimensions. The first dimension is associated with overall attributes of the FFE, consisting of six criteria: the study taxonomy, model type, NPD speed, NPD attributes, model characteristic, and model structure. The second dimension is relevant to the FFE performance structure related to process parameters, comprised of four criteria: the FFE task, activity, performance method, and toolkit. In terms of those two dimensions, the paper looks at previous FFE studies to gain an understanding of features of each FFE study along with related knowledge and theories, as well as identification of evolution trends of FFE studies. Based on the identification, an FFE model development strategy for each criterion is formulated, and this paper proposes possible options for executing those strategies which exert influence on the form of the cluster network. The intention is for the database to be utilised as an overview of all existing FFE studies and allow specific FFE studies to be selected to examine FFE approaches.This paper provides FFE model development guidance on how to deal with the overall attributes and outcomes of the FFE which affect the entirety of the innovation process, and how to manage the performance structure related to process parameters.
Highlights
Researchers have dedicated substantial attention to developing a number of product innovation processes known as New Product Development (NPD) processes and product design processes1 ( Wynn and Clarkson 2018), with more than 600 processes reported (Simms 2012; Reim et al 2015)
This study aims to propose strategies for new fuzzy front end (FFE) model development considering those two factors which make the FFE crucial but vulnerable; (1) overall attributes of the FFE: the study taxonomy, model type, NPD speed, NPD attributes, model characteristic, and model structure and (2) the FFE performance structure related to processing parameters: the FFE task, activity, performance method, and toolkit
There were relatively fewer independent FFE models focusing on FFE studies intensively, which comprised 27.4% of the data, than dependent FFE models extracted from wider product innovation processes, accounting for 52.3% ( Table 2)
Summary
Researchers have dedicated substantial attention to developing a number of product innovation processes known as New Product Development (NPD) processes and product design processes ( Wynn and Clarkson 2018), with more than 600 processes reported (Simms 2012; Reim et al 2015). Research in Engineering Design (2021) 32:377–409 et al 2013; Bacciotti et al 2016; Koen et al 2002; Reid and Brentani 2004; Verworn et al, 2008); (2) the overall attributes and outcomes of the FFE affect the entirety of the product innovation process (Achiche et al 2013; Bacciotti et al 2016; Kim and Wilemon 2002a; Thanasopon et al 2016). The final section concludes this study with a summary of the paper and envisages the expected contributions
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