Forough Zarea, Jan Henrik Gruenhagen, Timothy Rose, Anna Wiewiora, Nicholas Johnson, Bahram Farhadinia
Industry 4.0 technologies, such as artificial intelligence, machine learning, and the Industrial Internet of Things (IIoT), are reshaping industries and hold considerable promise for advancing productivity and sustainable economic development. However, their adoption is fraught with risks, particularly for small and medium-sized enterprises (SMEs) that play a pivotal role in driving entrepreneurship, innovation, and the circular economy. Based on survey data collected between May and July 2020 from 307 professionals in mining, automotive manufacturing, and construction industries, this study examines critical risks across three stages of technology adoption: identification and selection; pilot testing, and full-scale implementation. Using the fuzzy analytical hierarchy process, the analysis reveals that technical risks dominate across stages and industries, while key social and environmental risks for achieving sustainability goals remain consistently deprioritized. However, risk profiles diverge by firm size and industry: SMEs are disproportionately affected by organizational and financial risks, whereas larger firms demonstrate consistent approaches through established risk management and economic policy frameworks. These findings demonstrate the necessity of a staged, context-sensitive, and sustainability-oriented adoption strategy. This study contributes to understanding how SMEs can balance economic efficiency and sustainable technology adoption in the transition toward Industry 4.0 by offering industry-specific propositions and managerial implications.