Segment Disclosures Decision-Context Framework and Decision-Usefulness Prediction Model

• In Event: Financial Accounting and Reporting 9

Abstract

Fundamental analysis investors are of the opinion that improved accounting standards would increase their confidence in employing financial disclosures. They maintain segment disclosures are crucial to their decision processes. For these reasons, research into defining and modeling decision usefulness warrants greater attention. We developed a segment disclosures decision-context framework, decision-usefulness prediction model, and definitions for the data qualities that compose our model. We developed these tools using the classical grounded theory methodology and data from these literatures: value-focused thinking, segment reporting, investment professionals, and data qualities. We find that decision usefulness is a general measurable construct that pertains to all data—financial and non-financial. Future accounting researchers and standard-setters could modify our tools to test and improve standard-setting. Furthermore, researchers in other disciplines could modify them to test and improve the decision usefulness of crucial data employed by decision-makers in their fields.

Authors

• Cynthia Tollerson, Morgan State University

• Wynne W Chin, University of Houston

• George O Gamble, University of Houston-Houston