Marketing Technology for Advanced Engineering Innovations: Intelligent Sustainable Commercialization Framework
Abstract
Advanced engineering innovations - such as intelligent manufacturing systems, robotics-enabled production assets, green process technologies, and digitally connected industrial products - often underperform commercially despite technical superiority. A central reason is weak integration between engineering development and marketing technology (martech) systems that translate complex technical value into customer adoption, ecosystem legitimacy, and scalable revenue. Building on the conceptual logic linking intelligent machines, information and communication technology (ICT), sustainable marketing practices, and business performance, this paper develops a PhD-level framework for the marketing technology of advanced engineering innovations. A structured conceptual synthesis methodology was applied, integrating scholarship on intelligent machines, industrial innovation commercialization, B2B marketing, sustainable value creation, digital transformation, and AI governance. The results propose an integrated framework in which intelligent-machine-enabled martech capabilities - market sensing, technical-value translation, opportunity discovery, commercialization analytics, and lifecycle orchestration - strengthen sustainable commercialization capability and improve business performance. The framework further specifies the mediating role of sustainability evidence orchestration and the moderating roles of explainability governance and market-regulatory turbulence. The paper concludes that martech in engineering-led firms should be designed as a commercialization infrastructure rather than a promotional toolkit, requiring interoperability across engineering, sales, service, compliance, and sustainability reporting functions. The manuscript contributes a testable proposition-based model, implementation architecture, and a multi-stage empirical validation pathway suitable for engineering-intensive firms operating in uncertain and sustainability-sensitive markets.
Fields of Study & Subjects
Innovation Diffusion and Forecasting
Digital Transformation in Industry
Impact of AI and Big Data on Business and Society
Publication details
- Journal / source
- Pacific Journal of Advanced Engineering Innovations
- Publisher
- Ordient Publishers
- Volume
- 3
- Issue
- 1
- Pages
- 13–27
- Publication date
- 28 February 2026