The Data Decision-Usefulness Theory: An Exploration of Post-1998 Reported Products and Services Segment Data Decision Usefulness
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This study sets forth a conceptual theory–the Data Decision-Usefulness Theory–and explores it by surveying fundamental-equity analysts, to assay their decision-usefulness perceptions of post-1998 reported products and services segment data. Accordingly, a two-phased sequential exploratory mixed methods research design is employed. The initial phase is qualitative in nature comprising theory generation and questionnaire and taxonomy development. The conceptual theory is generated by drawing on prior accounting literature and two paradigms: formal classical grounded theory and value-focused thinking. The former is the theory development methodology and the latter is the over arching abstract model. The mail questionnaire is developed with the aid of Dillman’sTailored Design Method. Our fundamental-equity analyst taxonomy is developed, by drawing on: the descriptive literature about investment professionals, the United States security exchange regulations, and a non-public database, as well as the grounded theory paradigm. The second phase is quantitative in nature. One hundred and sixty-three questionnaire recipients mailed back their questionnaires (10% response rate). Fifty-five answered questions that measured their decision-usefulness perceptions. Overall, the measurement model findings for the questionnaire measures of the materiality and decision-usefulness models are moderately to highly reliable, exhibit both convergent and discriminate validity, and each has predictive relevance. In comparing our results for the two models, our most significant finding is that Ease of Comparing is the most important predictor for both Materiality and Decision Usefulness. However, surprisingly the relative importance of Relevance and Reliability shifts dramatically. Our Materiality model predicts that Relevance is the second most important predictor and Reliability is the least important. In contrast, our Decision Usefulness model predicts just the opposite Our results suggest that to have an impact on analysts’ understanding of firms, relevant disclosures are more important than reliable disclosures. However, to increase analysts’ understanding of firms, reliable information is more important than relevant information. Furthermore, the amount of post-1998 reported products and services segment data being disclosed is insufficient to improve analysts’ understandings of firms. These findings seem to support the dissenting FASB board member’s assertion that post-1998 reported segment disclosures are unlikely to facilitate better understanding firms’ performance, better assessing their prospects for future net cash flows, and making more informed judgments about firms as a whole.