Data-driven public policy for electric vehicles (EV) through open innovation and dynamic consumer preferences: A time-series social media analysis using integrated IPA-product improvability model - Dwi Adi Purnama; Distian Pingkan Lumi; Atik Febriani; Ar Royyan Utama T; Samaya Dhiya Salindri; Adhe Rizky Anugerah; Nashtiti Aliafari (Journal of Open Innovation: Technology, Market and Complexity, 2025)
Transport emissions play a crucial role in the accumulation of greenhouse gases (GHG) and the progression of climate change. Electric vehicles (EV) present a viable solution to this issue, aligning with the sustainable development goal through affordable and clean energy. However, in numerous countries, electric vehicle adoption accounts for only around 1 % of total sales. Investigating open innovation and surveys on electric vehicle adoption and public policy development is essential. This study proposes a data-driven public policy for EV through open innovation and dynamic consumer preferences using the macrolevel (big data social media) for decision making. The case study on the adoption of electric vehicles in Indonesia, a populous developing nation with significant transportation ownership, demonstrates the method's feasibility and effectiveness. Textual big data modeling and dynamic analysis were developed using the Latent Dirichlet Allocation (LDA), Sentiment Analysis, and a time series analysis. Then, open innovation strategies and public policy development were developed by integrating the Dynamic-Product Improvability Index-Importance Performance Analysis (D-PII-IPA), a novel method. Finally, this study discovers improvement ideas and innovation priorities consist of always-priority attributes (battery), changing attributes (EV cost/price and comfortable facilities), and unique attributes, such as entertainment events of EVs and electricity for online drivers. The government can enhance this public policy by offering incentives, improving battery and charging infrastructure, investing in user-friendly facilities, and streamlining the distribution of electric vehicles. These insights could offer significant direction to the government and industry stakeholders concerning the issues related to dynamic EV adoption.