## 5 Discussion  
From an academic perspective, the study led to the establishment of a systematic and integrated methodology for setting and adequately grounding a PLM strategy for companies aiming to enhance their innovation potential. The proposed framework has been designed to include quantitative and objective guidelines for PLM implementations, whereby the main focus has been on mapping the company's specific needs. The research was predicated on the assumption that evaluating an organization's NPD capabilities could provide a basis for identifying the company's latent needs, in alignment with the PLM strategy's orientation toward enhancing innovation potential. Hence, a novel methodological approach has been conceived and proposed to analyze the NPD process systematically, identify priority areas for focusing improvement efforts, and map them with specific PLM functional aspects. The proposed methodology employs a QFD analytic process enhanced by MCMD methods. Moreover, since accurately predicting the exact values of variables existing in PLM implementation problems is difficult due to various sources of uncertainties and vagueness, the proposed methodology incorporates IT2F sets as a suitable tool for addressing these issues. The key contributions of this study are highlighted below:  
* A new PLM functional model is established, providing a reference frame for defining the scope of the PLM strategy, emphasizing the need to adapt the reference model for application in specific contexts, including dedicated functionalities aligned to company needs instead of standard ones. * A new normative-contingent NPD evaluation model is established, grounded in best practice frameworks, providing a consistent methodology capable of capturing the company's latent needs related to enhancing NPD capabilities. Proceeding from the premise that using product development best practices is context-dependent, the evaluation model introduces the principles of coherence, considering NPD practices' relative importance by evaluating how well they align with the company's NPD strategy. Based on the findings of NPD evaluations, companies become aware of the gap between the actual and best practices available to be used. These insights are significant for comprehending where to focus enhancement initiatives to bolster the company's NPD performance. * A QFD-based methodology is proposed to quantify the impact of specific PLM functional aspects on NPD capability, assisting companies in understanding their implementation priorities. In this way, they could gain objective guidance for establishing a PLM competence development model that effectively supports the continuous improvement of their NPD capabilities. This also could lead to reducing the implementation failure risk by including dedicated PLM functionalities instead of standard ones. From a theoretical perspective, the proposed QFD model is proved to be advantageous in the following aspects:
* The quality attribute prioritization phase relies on the EDAS method instead of employing a straightforward weighted averaging technique, allowing more precise quality attribute-relative priority rankings. * The [PERSON]'s AHP model is used to prioritize the request attributes, which could yield more consistent and reliable importance degrees. * The use of IT2F sets provides a simple representation of qualitative concepts that can describe vagueness and ambiguities with less information loss. The NPD evaluation findings highlight that the key areas for implementing improvement initiatives to enhance the company's NPD performance include (i) internal integrationwith a focus on establishing better cross-functional coordination mechanisms, etc. ; (ii) adopting a product lifecycle perspective during product development; (iii) setting up efficient mechanisms for integrated product knowledge management and fostering the reuse of previously accumulated knowledge; and (iv) establishing processes for planning, managing, and continuously improving quality from the early phases of product development.