Abstract

This dissertation consists of three studies investigating the relationship between business analytics and decision making in accounting. In an effort to improve performance, organizations increasingly emphasize fact-based decision making supported by business analytics, which translate complex data into manageable information through statistical analysis. While the recent focus on business analytics is transforming how managers make decisions, analytics alone do not generate increased performance; the synergy between business analytics and user judgments is a vital component of realizing value. To this end, Study I experimentally investigates how various characteristics of business analytics affect individuals' reliance and perceptions of the analytic. Through the lens of cognitive fit a 2×2 between-subjects experiment is conducted examining business analytics effects of input and process attributes on users' reliance. Cognitive fit theory posits that effective problem solving depends on the match between the technology and the decision process. The second study investigates the impact of management interventions (i.e. actions influencing adoption) toward improving reliance on business analytics. From an organizational perspective, an important concern for management is promoting greater employee acceptance and utilization of business analytics. Building on the Technology Acceptance Model, Study II experimentally examines the effect of management support and consensus of multiple analytics on increasing reliance and on participants' evaluation of the business analytic. Study III further explores the relationship between characteristics of business analytics and the decision maker by developing a theoretical model regarding the effects of perceived decision similarities between the user and the business analytic on users' perceived usefulness. Overall, the results reported in this dissertation suggest that 1) characteristics of business analytics influence users' judgments and decision making, 2) management can take actions to influence the relationship between users and business analytics, and 3) users are likely to evaluate their cognitive similarity to these business analytics, and these perceptions influence perceived usefulness of the business analytics.

Notes

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Graduation Date

2018

Semester

Summer

Advisor

Trompeter, Gregory

Degree

Doctor of Philosophy (Ph.D.)

College

College of Business Administration

Degree Program

Business Administration; Accounting

Format

application/pdf

Identifier

CFE0007578

URL

http://purl.fcla.edu/fcla/etd/CFE0007578

Language

English

Release Date

February 2022

Length of Campus-only Access

3 years

Access Status

Doctoral Dissertation (Campus-only Access)

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