1.1 BACKGROUND OF THE STUDY
Quality information is one of the competitive advantages for an organization. In an accounting information system, the quality of the information provided is imperative to the success of the systems. Accounting Information System (AIS) as one of the most critical systems in the organization has also changed its way of capturing, processing, storing and distributing information. Information has become a key resource of most organizations, economies, and societies. Indeed, an organization’s basis for competition has changed from tangible products to intangible information. More and more organizations believe that quality information is critical to their success (Wang, R.Y 2006).
However, not many of them have turned this belief into effective action. Poor quality information can have significant social and business impacts (Strong, Lee and Wang, 1997). There is strong evidence that data quality problems are becoming increasingly prevalent in practice (Redman, T.C 1998). Most organizations have experienced the adverse effects of decisions based on information of inferior quality (Huang, Lee and Wang, 1999). It is likely that some data stakeholders are not satisfied with the quality of the information delivered in their organizations. In brief, information quality issues have become important for organizations that want to perform well, obtain competitive advantage, or even just survive in the 21st century.
In particular, Accounting Information Systems (AIS) maintain and produce the data used by organizations to plan, evaluate, and diagnose the dynamics of operations and financial circumstances (Anthony, Reese and Herrenstein, 2005). Providing and assuring quality data is an objective of accounting. With the advent of AIS, the traditional focus on the input and recording of data needs to be offset with recognition that the systems themselves may affect the quality of data (Fedorowicz and Lee, 1998). Indeed, empirical evidence suggests that data quality is problematic in AIS (Johnson, Leith, and Neter, 1981). AIS data quality is concerned with detecting the presence or absence of target error classes in accounts (Kaplan, Krishnan, Padman and Peters, 1998).
Thus, knowledge of the critical factors that influence data quality in AIS will assist organizations to improve their accounting information systems’ data quality. While many AIS studies have looked at internal control and audit, Data Quality (DQ) studies have focused on the measurement of DQ outcomes. It appears that there have been very few attempts to identify the Critical Success Factors (CSFs) for data quality in AIS. Thus, there is a need for research to identify the critical success factors that affect organizations’ AIS DQ.
Information technology has changed the way in which traditional accounting systems work. There is more and more electronically captured information that needs to be processed, stored, and distributed through IT-based accounting systems. Advanced IT has dramatically increased the ability and capability of processing accounting information. At the same time, however, it has also introduced some issues that traditional accounting systems have not experienced. One critical issue is the data quality in AIS. IT advantages can sometimes create problems rather than benefiting an organization, if data quality issues have not been properly addressed. Information overload is a good example. Do we really need the quantity of information generated by the systems to make the right decision? Another example is e-commerce. Should the quality of data captured online always be trusted?
Data quality has become crucial for the success of AIS in today’s IT age. The need arises for quality management of data, as data processing has shifted from the role of operations support to a major operation in itself (Romney, M. and Steinbart, P. J., 2009). Therefore, knowledge of those factors impact on data quality in accounting information systems is desirable, because those factors can increase the operating efficiency of AIS and contribute to the effectiveness of management decision making.
- STATEMENT OF THE PROBLEM
The proliferation of computerized database with relative increase in errors of such stored data base in organizations which depend on them to support business process and decision making has been questioned by many analysts.
The number of errors in stored data and the organizational impact of these errors is likely to increase (Klein 1998).
Also, inaccurate and incomplete data may adversely affect the competitive success of an organization (Redman 1992). Indeed, poor quality information can have significant social and business impacts. For example, NBC News reported that “dead people still eat!” Because of outdated information in US government databases, food stamps continued to be sent to recipients long after they died. Fraud from food stamps costs US taxpayers billions of dollars.
Equally, losses in millions incurred by business organizations who were caught unawares by dramatic changes in interest rates is of great concern to both owners and management.
In particular, there are consequences of poor data quality in AIS. For example, errors in an inventory database may cause managers to make decisions that generate overstock or under-stock conditions (Bowen 1993). One minor data entry error, such as the unit of product/service price, could go through an organization’s AIS without appropriate data quality checks, and cause losses to an organization and / or harm its reputation.
More so, most of the information system research into data quality focuses on the theoretical modeling of controls and measurement while few studies have attempted to understand what causes the difference in AIS data quality outcomes, and what should be done to ensure high quality accounting information.
Most organizations have experienced the adverse effects of decision based on information of inferior quality. However, not many of them have turned this belief into effective action. Poor quality information can have significant social and business impacts.
Therefore, there is lack of knowledge of the CSF for data quality in AIS that can assist organizations to ensure and improve accounting information quality.
These has necessitated the conduct of this research.
1.3 OBJECTIVES OF THE STUDY
The main objective of this study is to examine the critical success factors for accounting information systems data quality. The subsidiary objectives include the following:
- To determine the factors that affects the variation of data quality in accounting information systems.
- To ascertain the variations with regard to the perceptions of importance of those factors that affect data quality in accounting information systems.
- To examine the stakeholder perceptions on importance of critical factors for accounting information systems.
- To investigate the factors that are critical success factors to ensure a high quality of data in accounting information systems
- To examine the organizations perspective in the importance and performance of critical success factors for accounting information system data quality.
1.4 RESEARCH QUESTIONS
In order to explore the research problem, the focus of this project is on five research questions which reflect on the objectives of the study are fielded.
- What factors affect the variation of data quality in accounting information systems?
- Are there any variations with regard to the perceptions of importance of those factors that affect data quality in accounting information systems?
- What are the perceptions of stakeholder groups in importance of critical factors for accounting information systems?
- Which of these factors are critical success factors to ensure a high quality of data in accounting information systems data quality?
- What are organizations perspective in the importance and performance of critical success factors for accounting information system data quality?
1.5 RESEARCH HYPOTHESES
In analyzing the critical success factors for accounting information systems’ data quality, some tentative statements were formed to help answer the research questions hence the following hypotheses that have to be tested were put forward for this study.
Ho: There are no significant factors that affect the variation of data quality in accounting information system.
H1: There are significant factors that affect the variation of data quality in accounting information system.
H0: There are no significant differences between the perceptions of importance of critical factors for accounting information systems’ data quality, and actual performance of those factors.
H1: There are significant differences between the perceptions of importance of critical factors for accounting information systems’ data quality, and actual performance of those factors.
H0: There are no significant differences between different stakeholder groups in their perceptions of importance of critical factors for accounting information systems’ data quality.
H1: There are a significant difference between different stakeholder groups in their perceptions of importance of critical factors for accounting information systems’ data quality.
H0: There are no significant critical success factors to ensure a high quality of data in accounting information systems.
H1: There are significant critical success factors to ensure a high quality of data in accounting information systems.
H0: Different organizations have the same perspective in the importance and performance of critical success factors for accounting information systems data quality.
H1: Different organizations have different perspective in the importance and performance of critical success factors for accounting information systems data quality.
1.6 SIGNIFICANCE OF THE STUDY
Identifying the critical success factors for AIS could enhance the ability of AIS’s to gather data, process information and prepare reports. Outcomes of this research will contribute to the body of knowledge both in AIS and data quality field, and it may benefit other research into these areas. For example, it can help arouse the awareness of data quality issues in AIS field, and to make it possible to establish the linkage of the identified CSFs with the existing data quality dimensions for outcomes assessment.
Thus, understanding how these factors affect organizations’ AIS performance may be useful to practitioners. Focusing on those factors that are more critical than others will lead to efficiency and effectiveness AIS’s procedures. In brief, the results from this research are likely to help the academic community for future researchers, organizations’ top management, accountants, and IT managers obtain better understanding of AIS DQ issues.
1.7 SCOPE OF THE STUDY
This study is limited to four Nigerian companies selected for the case study in this research. Two of them were chosen from banking industry, and two from manufacturing industry. As there is no one set of criteria to distinguish banking industry and manufacturing industry for the purpose of the case study analysis of this research, employee number was use to define the size of the organizations. Although criteria defining organizations as bank, manufacturing vary, in this research organizations with more than 1000 employees were categorized as manufacturing companies while those organizations with fewer than 1000 employees were categorized as banking industries. In order to respect the privacy of the participating organizations and individual interviewees they were not identified by their real names or actual position titles.
1.8 LIMITATIONS OF THE STUDY
As part of the research experience by researchers all over the globe; certain limitations hindered the effective and smooth collection of data for the work. These in specific terms include: inadequate working fund, lack of time and difficulties (minimal) in obtaining needed data relevant to the subject matter of critical success factors for accounting information systems data quality.
Financial Constraint: The finance needed to carry out this work is too much and cannot be afforded by the student. This to an extent hampered the success of this work.
Time Constraint: Time was really a big constraint in carrying out this research study. The researcher had to combine the collection of materials for the study with other academic activities. The study was not easy to carryout due to distant part of the organizations and the huge financial burden involved.
Non-Challant Attitude of Respondents: Another limitation in the course of carrying this study was the non-chalet attitude of the respondents in supplying the necessary information. This was probably due to their ignorance of the main purpose of the study. Also many refused to grant interviews or answer question bordering on the activities of the organizations.
Scope of the Research: The study was constrained to Nigerian organizations; therefore, the conclusions drawn from this study