Artificial intelligence and the reconfiguration of NPD Teams: Adaptability and skill differentiation in sustainable product innovation

IF 11.1 1区管理学 Q1 ENGINEERING, INDUSTRIAL

Technovation Pub Date : 2025-05-22 DOI:10.1016/j.technovation.2025.103254

Giacomo Marzi , Marco Balzano

{"title":"Artificial intelligence and the reconfiguration of NPD Teams: Adaptability and skill differentiation in sustainable product innovation","authors":"Giacomo Marzi , Marco Balzano","doi":"10.1016/j.technovation.2025.103254","DOIUrl":null,"url":null,"abstract":"<div><div>Sustainable product innovation (SPI) is increasingly central to New Product Development (NPD) teams, aligning with global sustainability goals and industry expectations. However, the factors associated with SPI at team level remain underexplored. This study examines the roles of team skill differentiation and team adaptability in fostering SPI, proposing that these factors support teams in the pursuit of sustainability-oriented innovation more effectively. Furthermore, we investigate the moderating role of generative artificial intelligence (GenAI) in shaping the strength of these relationships. Drawing on the double diamond framework and its AI-augmented adaptation, we hypothesize that skill differentiation expands the range of potential solutions in the divergent phase of innovation, while adaptability enhances responsiveness in the convergent phase. GenAI is posited to enhance these effects by augmenting knowledge recombination and real-time strategic adaptation. To test our hypotheses, we conducted a multi-industry survey of NPD teams engaged in sustainability initiatives, applying multiple regression analysis to assess the proposed relationships. All our hypotheses were empirically supported. Overall, this study contributes to SPI research by integrating team capability theory with AI-driven innovation frameworks. The findings highlight the need for firms to cultivate multidisciplinary teams with adaptive capacities while leveraging GenAI as an amplifier rather than a substitute for human expertise. The results also underscore that effective SPI requires both internal knowledge diversity and external responsiveness, alongside AI tools that enhance creativity and sustainability-driven decision-making. Finally, this research provides insights into how NPD teams can enhance their engagement in sustainable innovation, aligning with the broader objectives of Sustainable Development Goals (SDGs) 9 and 12.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"145 ","pages":"Article 103254"},"PeriodicalIF":11.1000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technovation","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166497225000860","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}

引用次数: 0

Abstract

Sustainable product innovation (SPI) is increasingly central to New Product Development (NPD) teams, aligning with global sustainability goals and industry expectations. However, the factors associated with SPI at team level remain underexplored. This study examines the roles of team skill differentiation and team adaptability in fostering SPI, proposing that these factors support teams in the pursuit of sustainability-oriented innovation more effectively. Furthermore, we investigate the moderating role of generative artificial intelligence (GenAI) in shaping the strength of these relationships. Drawing on the double diamond framework and its AI-augmented adaptation, we hypothesize that skill differentiation expands the range of potential solutions in the divergent phase of innovation, while adaptability enhances responsiveness in the convergent phase. GenAI is posited to enhance these effects by augmenting knowledge recombination and real-time strategic adaptation. To test our hypotheses, we conducted a multi-industry survey of NPD teams engaged in sustainability initiatives, applying multiple regression analysis to assess the proposed relationships. All our hypotheses were empirically supported. Overall, this study contributes to SPI research by integrating team capability theory with AI-driven innovation frameworks. The findings highlight the need for firms to cultivate multidisciplinary teams with adaptive capacities while leveraging GenAI as an amplifier rather than a substitute for human expertise. The results also underscore that effective SPI requires both internal knowledge diversity and external responsiveness, alongside AI tools that enhance creativity and sustainability-driven decision-making. Finally, this research provides insights into how NPD teams can enhance their engagement in sustainable innovation, aligning with the broader objectives of Sustainable Development Goals (SDGs) 9 and 12.

查看原文本刊更多论文

人工智能与新产品开发团队的重构：可持续产品创新中的适应性和技能差异化

可持续产品创新（SPI）越来越成为新产品开发（NPD）团队的核心，与全球可持续发展目标和行业期望保持一致。然而，在团队层面上，与SPI相关的因素仍未得到充分探讨。本研究考察了团队技能差异和团队适应性在促进可持续创新中的作用，提出这些因素更有效地支持团队追求可持续导向的创新。此外，我们研究了生成人工智能（GenAI）在塑造这些关系强度方面的调节作用。利用双菱形框架及其人工智能增强的适应性，我们假设技能差异化在创新的发散阶段扩大了潜在解决方案的范围，而适应性在收敛阶段增强了响应性。基因人工智能被认为可以通过增加知识重组和实时战略适应来增强这些效应。为了验证我们的假设，我们对参与可持续发展计划的NPD团队进行了多行业调查，应用多元回归分析来评估所提出的关系。我们所有的假设都有经验支持。总体而言，本研究通过将团队能力理论与人工智能驱动的创新框架相结合，为SPI研究做出了贡献。研究结果强调，企业需要培养具有适应能力的多学科团队，同时利用GenAI作为放大器，而不是人类专业知识的替代品。结果还强调，有效的SPI需要内部知识多样性和外部响应能力，以及增强创造力和可持续性驱动决策的人工智能工具。最后，本研究为NPD团队如何加强可持续创新的参与提供了见解，并与可持续发展目标（sdg） 9和12的更广泛目标保持一致。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Technovation 管理科学-工程：工业

CiteScore

15.10

自引率

11.20%

发文量

208

审稿时长

91 days

期刊介绍： The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.