Competitive Intelligence as a Strategic Framework for IOT Smart-Home Adoption: Evidence from Shenzhen Consumers

Abstract

Purpose: This study develops a process-based Competitive Intelligence (CI) framework for IoT smart-home providers, examining which consumer perceptions are associated with adoption intention among surveyed Shenzhen consumers and how this consumer-derived evidence is transformed, through the complete CI cycle, into governed strategic decision support.

Methodology/Approach: A quantitative cross-sectional survey embedded within a process-based CI framework. A 106-response pilot supported instrument screening; a formal data set of 375 responses was analysed through reliability analysis (Cronbach’s alpha), descriptive statistics, Pearson correlation, multiple regression with collinearity and robustness (HC3) diagnostics, and Personal-Innovativeness moderation analysis with multiple-testing correction. An additional Consumer-Derived Competitive Intelligence Actionability Index was developed to convert statistically supported consumer signals into ranked CI priorities for strategic decision support. CI is operationalized as an organizational process—planning, collection, analysis, dissemination, utilization, feedback and governance—rather than as a consumer-level scale.

Originality/Relevance: Existing smart-home adoption studies identify perceptual antecedents of adoption but rarely explain how consumer-derived evidence becomes product, communication and market decisions. The study addresses this gap by connecting consumer-adoption analytics with the complete CI cycle, a strategic-priority matrix and a governance and feedback protocol for the surveyed Shenzhen context.

Key Findings: The data were complete and clean (N = 375). All nine constructs showed good-to-excellent internal consistency (α = 0.876–0.946). All seven perception constructs correlated positively and significantly with adoption intention (r = 0.43–0.54) and remained significant in multiple regression, jointly explaining 57.9% of the variance (adjusted R² = 0.571; F(7, 367) = 72.17, p < .001), with Clear Interface (β = 0.221) and Consistency (β = 0.200) carrying the largest weights and Perceived Security (β = 0.128) the smallest significant weight. Personal Innovativeness significantly moderated five of the seven relationships in exploratory tests, most strongly for Information Completeness (ΔR² = 0.077) and Information Accuracy (ΔR² = 0.064).

Theoretical/Methodological Contributions: The study develops a process-based operationalization of Competitive Intelligence that connects consumer-derived market signals with intelligence planning, collection, analysis, dissemination, strategic utilization and feedback. Methodologically, it distinguishes the measured consumer-adoption constructs from the organizational CI process and demonstrates how regression and moderation evidence can be converted into a governed strategic decision-support framework.