Purpose Data retrieval systems remain constrained by the theoretical and technological limitations of the traditional information retrieval (IR) paradigm. These systems—largely derived from this paradigm—provide inadequate support for the inherently complex process of data discovery, which demands innovative and integrated technological solutions. Prior research has focused on distinguishing interactive data retrieval (IDR) from interactive information retrieval (IIR), leading to incremental system improvements within the existing paradigm. To address these limitations, this study differentiates IDR from interactive information technologies (IIT) to inform the development of a more expansive technological ecosystem capable of fully supporting effective data discovery. Design/methodology/approach Grounded in multidisciplinary theories, this study proposes the “Multi-dimensional Interaction-Attitude-Usage Model” (MIAU Model). It validates and comparatively analyzes this model across IDR and IIT contexts using a multi-method approach. Findings This study identifies key distinctions between IDR and IIT. In the context of IDR, system quality—representing the core strength of data retrieval systems—replaces resource quality as the most influential factor shaping user cognition and attitudes. In contrast, limited social support emerges as the primary system weakness, triggering negative emotional responses yet exerting minimal influence on reasoned evaluations or overall attitudes. This asymmetrical effect is interpreted through the lens of the “default–intervention” cognitive framework, wherein reasoned evaluations grounded in system strengths override affective reactions to system weaknesses during attitude formation. Practical implications This study provides design recommendations for intelligent data retrieval systems. Through technological fusion, such systems can facilitate both digitally and socially mediated data discovery, thereby transcending the limitations of traditional IR paradigms. Originality/value This study introduces the MIAU Model as a generalizable and extensible theoretical framework to advance IDR research. It identifies and explains the distinctive characteristics of IDR and uncovers the underlying cognitive mechanisms through which user–system interactions shape overall user attitudes.
Wang et al. (Thu,) studied this question.