Management accounting and data analytics: technology acceptance from the educational perspective

Figures & data

Figure 1. Workflow for the descriptive and diagnostic analytics.³

Figure 2. Predictive analytics workflow.⁴

Figure 3. Prescriptive analytics workflow.⁵

Figure 4. TAM components.⁶

Figure 5. Distribution of sampled papers across years.

Figure 6. Distribution of sampled papers across countries (based on first author).

Table 1. Example of introducing the data analytics within the Management Accounting course with domain knowledge alignment.

Data analytics inclusion within the Management Accounting course	Management accounting area	Data analytics area	Sample paper
1. Introduction of the skillset required to use data analytics with a focus on broader skill categories (i.e. critical thinking, analytical skills, programming skills): - identifying relevant data sources and data types, including structured and unstructured data, - using data wrangling techniques to transform data into formats and presentation suitable for further application of data analytics solutions. - formulating management accounting problem with reference to available data sources and data analytics approaches and solutions - developing steps required for data transformation and analysis to address the management accounting problem	Inventory management Management of accounting information Costs classifications Costs centers Customer Analytics	Data-cleansing, including extract, transform, load procedures Creating datasets for data analytics	Tadesse and Vincent (2022), Vasarhelyi et al. (2015)
2. Incorporation of data management in accounting, including working with different formats of data and presentation formats: - identifying relevant data attributes, formats and sources to develop integrated data workflows - using descriptive analytics solutions to understand cost classification - using diagnostic data analytics solutions to evaluate costs and variances - using predictive data analytics solutions for CVP analysis and decision making	Cost analysis and techniques, CVP analysis Decision making	Data workflows Descriptive analytics solutions Predictive data analytics solutions	Using Data Analytics to Evaluate the Drivers of Revenue: An Introductory Case Study Using Microsoft Power Pivot and Power BI 10.2308/ISSUES-2021-057
3. Implementation of business intelligence solutions, including working with software applications (i.e. Microsoft Excel, Microsoft PowerBI, Tableau, etc): - employing descriptive, diagnostic, and predictive analytics for capital budgeting. - integrating the structured and unstructured data from different data sources to provide information necessary for financial and operational analysis and decisions. - using data analytic techniques to identify patterns and trends to explain an entity’s results - communicating the results of the data analytics solution to decision makers. - developing consistent, persuasive and insightful data stories, leveraging data visualizations and dashboards.	Flexible budgeting Performance measurement Variance analysis	Descriptive, diagnostic, and predictive analytics Data stories Data visualization and dashboards	Vesty and Brooks (2017)
4. Showing the role of management accountants in business transformations, including digital innovation and evolution of business models: - mapping data analytics solutions to the steps in the budgeting cycle - using data analytics for in-time communication and agile decision making - employing prescriptive analytics to prepare and interpret the results of planning techniques (e.g. cost benefit analysis, sensitivity analysis, what-if scenarios, breakeven analysis).	Balanced scorecard Cost-benefit analysis Breakeven Analysis Performance management	Agile decision making Data prescriptive analytics	Moore et al. (2001)
5. Using emerging technologies (i.e. machine learning and AI, blockchain, etc): - evaluating predictive analytics solutions to assess risk and uncertainty - developing prescriptive analytics solutions for managing risk and uncertainty. - addressing management accounting tasks using data storytelling to communicate the results to decision makers	Risk and uncertainty analysis Risk management Decision making process	Prescriptive analytics Predictive analytics Data storytelling	Presley (2019)

Table 2. Demographic information about participants.

		Frequency	Percent
Gender	Female	55	61%
	Male	35	39%
Age	<21	68	75%
	21–30	22	25%
IT skill level (self-assessed)	Average	56	62%
	Proficient	25	28%
	Expert	9	10%

Table 3. Survey results.

Construct	Items	Factor loadings	Composite reliability	Cronbach alpha	AVE	Mean	Standard deviation
DAU	DAU1	0.872	0.759	0.824	0.799	3.541	1.21
	DAU2	0.768
	DAU3	0.702
	DAU4	0.802
	DAU5	0.651
PEU	PEU1	0.845	0.832	0.811	0.804	3.210	1.52
	PEU2	0.811
	PEU3	0.722
	PEU4	0.803
	PEU5	0.745
	PEU6	0.698
PEOU	PEOU1	0.922	0.831	0.855	0.817	3.011	1.78
	PEOU2	0.850
	PEOU3	0.780
	PEOU4	0.802
	PEOU5	0.848
	PEOU6	0.749

Table 4. Perceived usefulness and ease of use determination.

Path	Beta	P-value
DAU -> PU	0.867	p < 0.001
DAU ->PEOU	0.732	p < 0.001
PEOU > PU-	0.654	p < 0.001

Table

Section 1: Data analytics use (ETAM components: Attitudes toward using and Use in the professional settings) Participants were presented with multiple choice questions related to management accounting problem and asked to select the most appropriate answer in relation to the suggested scenario.
1	Inventory management: identification of applicable data analytics approaches and tools (theme 1)
2	Cost analysis: working with different data formats and tools (theme 2)
3	Variance analysis using PowerBI (theme 3)
4	Performance management: using dashboards and visuals for communication with stakeholders with PowerBI/Tableau (theme 4)
5	Risk management in short term and long-term decision making: using basic machine learning for forecasting (theme 5)
Section 2: Perceived usefulness
Mean score on 5 point scale: strongly agree = 5 to strongly disagree = 1
6	Using data analytics within the management accounting course would enable me to accomplish tasks more quickly.
7	Using data analytics would improve my future job performance.
8	Using data analytics in my job would increase my productivity.
9	Using data analytics would enhance my effectiveness on the job.
10	Using data analytics would make it easier to do my job.
11	I would find data analytics useful in my job.
Section 3 Perceived ease of use
Mean score on 5-point scale: strongly agree = 5 to strongly disagree = 1
12	Learning how to apply data analytics in management accounting would be easy for me.
13	I would find it easy to get data analytics to do what I want it to do.
14	My interaction with data analytics would be clear and understandable.
15	I would find data analytics to be flexible to interact with.
16	It would be easy for me to become skillful at using data analytics in management accounting.
17	I would find data analytics easy to use

Table

Broad Topic	Management Accounting topic	Data analytics inclusion example (based on Representative tasks from AICPA, 2022)
1. Expectations for management accountants: The purpose of management accounting and the role of the Management Accountant	Financial Accounting, Management Accounting, Cost Accounting, Strategic Decisions and the Management Accountant	Identify relevant data sources and data types, including structured and unstructured data Use data wrangling techniques to transform data into formats and presentation suitable for further application of data analytics solutions. Formulate management accounting problem with reference to available data sources and data analytics approaches and solutions Develop steps required for data transformation and analysis to address the management accounting problem
2. Cost management: cost identification and classification	Cost centres, Cost objects, Classifiсation of costs, Сlassification of costs according to their nature, Classification of costs according to their purpose: direct costs and indirect costs, Elements of cost, Cost behaviour, Essentials of CVP Analysis, Contribution Margins, Cost-Volume-Profit Assumptions, Breakeven Point and Target Operating Income, Using CVP Analysis for Decision Making	Identify relevant data attributes, formats and sources to develop integrated data workflows Use descriptive analytics solutions to understand cost classification Use diagnostic data analytics solutions to evaluate costs and variances Use predictive data analytics solutions for CVP analysis and decision making
3. Capital Budgeting and Cost Analysis	Valuing inventory at cost, First in, first out (FIFO), Last in, first out (LIFO), Cumulative weighted average (AVCO), Undercosting and Overcosting Product-Cost, Cross-Subsidization Design, Manufacturing and Distribution Processes	Employ descriptive, diagnostic, and predictive analytics for capital budgeting.
4. Budgeting for planning and control	The nature and key characteristics of investment appraisal decisions, Stages of Capital Budgeting, Post-Investment Audits, Strategic Considerations in Capital Budgeting, Application of Basic Investment Appraisal Techniques: Payback (PB) and Accounting Rate of Return (ARR), Comparison of PB and ARR, Relevant Cash Flows in Investment Appraisals, Application of Discounted Cash Flow (DCF), Investment Appraisal Techniques: Net Present Value (NPV) and Internal Rate of Return (IRR)	Integrate the structured and unstructured data from different data sources to provide information necessary for financial and operational analysis and decisions. Use data analytic techniques to identify patterns and trends to explain an entity’s results Communicate the results of the data analytics solution to decision makers. Develop consistent, persuasive and insightful data stories, leveraging data visualizations and dashboards.
5. Variance analysis and reconciliation of budgeted and actual profits in a marginal format	Budgets and the Budgeting Cycle, Strategic Plans and Operating Plans, Budgeting Cycle and Master Budget, Advantages of Budgets Coordination and Communication Framework for Judging Performance and Facilitating Learning Motivating Managers and Other Employees, Challenges in Administering Budgets, Developing an Operating Budget, Time Coverage of Budgets, Steps in Preparing an Operating Budget, Static Budgets, Flexible Budgets	Map data analytics solutions to the steps in the budgeting cycle Use data analytics for in-time communication and agile decision making Employ prescriptive analytics to prepare and interpret the results of planning techniques (e.g. cost benefit analysis, sensitivity analysis, what-if scenarios, breakeven analysis).
6. Managing Risk and Uncertainty	Capital Rationing Decisions (soft, hard), The impact of Risk and Uncertainty in decision-making process, Managing Risk and Uncertainty: An overview of Management Accounting techniques such as: Risk map, (likelihood/probability) Expected Values, Sensitivity analysis	Evaluate predictive analytics solutions to assess risk and uncertainty Develop prescriptive analytics solutions for managing risk and uncertainty. Address management accounting tasks using data storytelling to communicate the results to decision makers

Tadesse, A. F., & Vincent, N. E. (2022). Combining data analytics with XBRL: The viewdrive case. Issues in Accounting Education, 37(1), 197–215. https://doi.org/10.2308/ISSUES-2020-048

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Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396. https://doi.org/10.2308/acch-51071

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Vesty, G., & Brooks, A. (2017). St George Hospital: Flexible budgeting, volume variance, and balanced scorecard performance measurement. Issues in Accounting Education, 32(3), 103–116. https://doi.org/10.2308/iace-51588

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Moore, C., Rowe, B. J., & Widener, S. K. (2001). HCS: Designing a balanced scorecard in a knowledge-based firm. Issues in Accounting Education, 16(4), 569–601. https://doi.org/10.2308/iace.2001.16.4.569

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Presley, T. J. (2019). A risk based approach to large datasets: Analysis of time series data for a large merchandising firm. Journal of Accounting Education, 49, 100639. https://doi.org/10.1016/j.jaccedu.2019.100639

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AICPA. (2022). Maintaining the Relevance of the Uniform CPA Examination – Aligning the Exam with the CPA Evolution Licensure Model. https://www.aicpa.org/resources/download/exposure-draft-proposed-2024-cpa-exam-changes

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