Technology Commercialization Readiness in Knowledge-Based SMEs: A Structured Review of Dimensions, Barriers, and Investment Criteria

سال انتشار: 1405
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 57

فایل این مقاله در 13 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

IMPEB01_0431

تاریخ نمایه سازی: 10 آبان 1405

چکیده مقاله:

Knowledge-based small and medium-sized enterprises (SMEs) must make several decisions when bringing a technology to market. These decisions concern testing, production, market entry, licensing, partnerships, and finance, often when the available evidence is uneven. This structured, non-exhaustive review examines how commercialization readiness is defined, assessed, constrained, and used in such decisions. Forty candidate records were assessed; ۲۹ verified sources were retained, comprising ۲۶ inspected full texts and three inspected official abstracts. The synthesis shows that technical maturity is necessary in many settings but cannot establish customer acceptance, manufacturability, viable economics, legal freedom, organizational capability, ecosystem support, or financing sufficiency. Direct SME and hardware evidence particularly exposes customer-validation and production-scale-up gaps, while investor, patent, funding, and programme evidence functions as context-dependent decision input rather than proof of commercial success. Technology commercialization readiness is therefore defined as the sufficiency, alignment, and credibility of evidence for a specified decision in a specified context. The review proposes an evidence-grounded framework that separates eight readiness domains, evaluates dependencies and potential bottlenecks, assigns evidence and risk ownership, identifies the next validation action, and records a context-specific gate decision with feedback. The evidence remains geographically, sectorally, and methodologically heterogeneous, and neither a universally validated commercialization-readiness construct nor general weights, thresholds, or predictive rules were identified.

نویسندگان

Moeen Sammak Jalali

Assistant Professor, Department of Industrial and Systems Engineering, Fouman Faculty of Engineering, College of Engineering, University of Tehran, Iran.

Aryan Azimi

Assistant Professor, Department of Industrial and Systems Engineering, Fouman Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran

Salman Nazari-Shirkouhi

Associate Professor, Department of Industrial and Systems Engineering, Fouman Faculty of Engineering, College of Engineering, University of Tehran, Iran.