Integrating Competitive Intelligence into Product Requirements Engineering: A Structured Decision Framework for Enterprise technology development
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V4I3P119Keywords:
Competitive Intelligence, Requirements Engineering, Product Management, Enterprise Technology, Comparative Research, Multigroup Structural Equation Modeling, Contextual Moderation, Market-Driven Requirements, Decision Quality, Digital CapabilityAbstract
Enterprise technology products are rarely specified in informational isolation. Product teams monitor competitors, substitute technologies, platform moves, regulatory trajectories, customer switching behavior, and ecosystem signals, yet requirements engineering (RE) research has not been established when such competitive intelligence (CI) improves requirements decisions across heterogeneous institutional and industry environments. This study develops and prespecifies a comparative empirical test of a structured decision framework linking competitive-intelligence integration (CII) to requirements decision effectiveness (RDE). The unit of analysis is the enterprise technology product team. A multi-wave, multi-informant survey is designed for ten national contexts United States, Canada, Germany, Sweden, Ireland, Brazil, India, Malaysia, South Africa, and Poland and four industry settings: enterprise software/cloud, financial-services technology, health/life-sciences technology, and industrial/manufacturing technology. CII is theorized to improve RDE primarily through requirements evidence assimilation (REA), defined as the disciplined conversion of competitive signals into traceable requirement rationales, priorities, acceptance conditions, and release decisions. Environmental dynamism, regulatory intensity, organizational digital-analytics maturity, and national institutional quality are modeled as contextual moderators. Competing explanations based on generic market orientation, requirements-process maturity, resource slack, and reverse causality are explicitly tested. The empirical strategy combines confirmatory factor analysis, cross-country and cross-industry measurement-invariance assessment, multigroup structural equation modeling, clustered comparative regression, moderated mediation, and matched robustness analyses. Public pre-August-2023 sources including World Bank governance and enterprise indicators, OECD/UNCTAD business-ICT indicators where coverage permits, and the open NaPiRE requirements-engineering benchmark are used only for contextual characterization and robustness, not as substitutes for firm-level CII measures. Because no observations from the proposed primary survey are supplied here, the article does not report invented coefficients or significance tests; instead, Section 4 provides a fully specified results protocol and falsification logic. The study’s central proposition is contextual rather than universal: competitive intelligence creates requirements value only when teams possess mechanisms that translate external signals into evidence-governed product decisions, and the strength of that mechanism varies systematically across regulatory, technological, institutional, and industry environments.
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