Achieving Sustainable New Product Development by Implementing Big Data-Embedded New Product Development Process

Yufan Wang,Haili Zhang

doi:10.3390/su12114681

Abstract

Literature suggests that new product development (NPD) has an impact on sustainable organizational performance. Yet, previous studies in NPD have mainly been based on “experience-driven”, not data-driven, decision-making in the NPD process. We develop a research model to examine how the big data-embedded NPD process affects the sustainable innovation performance of NPD projects. We test the proposed model and conduct the cross-national comparison using data collected on 1858 NPD projects in the United States of America (USA), the United Kingdom (UK), and Australia. The research findings suggest that big data-embedded business analysis, product design, and product testing increase sustainable innovation performance in all three countries. The study findings also reveal several surprising results: (1) in the USA, big data-embedded product testing has the highest effect on sales growth and gross margin, (2) in Australia, big data-embedded commercialization has the highest effect on sales growth and gross margin, and (3) in the UK, big data-embedded commercialization has the highest effect on second-year sales growth, first-year, and third-year gross margin; in addition, big data-embedded product testing has the highest effect on third-year sales growth and second-year gross margin.

Highlights

The role of the new product development (NPD) process in driving sustainable growth and performance has been the central focus of many innovation scholars [1,2,3,4,5,6,7,8,9,10,11]
In the United States of America (USA), big data-embedded commercialization has no impact on sustainable innovation performance, and in Australia, big data-embedded idea development has a partial impact on sustainable innovation performance
In order to empirically test five research hypotheses, we collected project-level data which include 1858 NPD projects with the following characteristics: (1) 497 NPD projects were from the USA, 510 NPD projects were from the United Kingdom (UK), and 851 NPD projects were from Australia, (2) the projects include five product industries, and (3) to be included in this study, all project-level data must include sales growth and gross margin for the first three years after the commercialization

Summary

Introduction

The role of the new product development (NPD) process in driving sustainable growth and performance has been the central focus of many innovation scholars [1,2,3,4,5,6,7,8,9,10,11]. We develop the following research questions for this study: RQ1: Does a big data-embedded NPD process increase sustainable innovation performance? RQ2: Do different stages of the big data-embedded NPD process have different effects on sustainable innovation performance? RQ3: Which stage of big data-embedded NPD process has the highest effect on sustainable innovation performance? Based on the NPD theory, we propose a research model and focus on five key stages of big data-embedded NPD process: big data-embedded idea development, business analysis, product design, product testing, and commercialization. We find that big data-embedded business analysis, product design, and product testing increase sustainable innovation performance in the USA, UK, and Australia. We advance extant NPD literature by empirically testing the effect of big data-embedded NPD process on sustainable innovation performance. We provide managerial implications for creating a big data-embedded NPD process

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Discussion

Conclusion