Author Topic: An Assessment model for Intelligence Competencies of Accounting Information Sys.  (Read 2712 times)

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Author : Mehdi Ghazanfari, Mostafa Jafari, Saeed Rouhani
International Journal of Scientific & Engineering Research, IJSER - Volume 2, Issue 4, April-2011
ISSN 2229-5518
Download Full Paper - http://www.ijser.org/onlineResearchPaperViewer.aspx?An_Assessment_model_for_Intelligence_Competencies_of_Accounting_Information_Systems.pdf

Abstract— Accounting Information Systems (AIS) as computer-based systems that processes financial information and supports decision tasks have been implemented in most organizations but, but they still encounter a lack of Intelligence in their decision-making processes. Models and methods to evaluate and assess the Intelligence-level of Accounting Information Systems can be useful in deploying suitable business intelligence (BI) services. This paper discusses BI Assessment criteria, fundamental structure and factors used in the Assessment model. Factors and the proposed model can assess the intelligence of Accounting Information Systems to achieve enhanced decision support in organizations. The statistical analysis identified five factors of the Assessment model. This model helps organizations to design, buy and implement Accounting Information Systems for better decision support. The study also provides criteria to help organizations and software vendors implement AIS from decision support perspectives.

Index Terms— Business Intelligence; Decision Support; Accounting Information Systems; Assessment Model. 

Introduction                                                                     
Information and knowledge represent the fundamental wealth of an organization. Enterprises try to utilize this wealth to gain competitive advantage when making important decisions. Enterprise systems like Accounting Information Systems (AIS) converts and store the data. Therefore, it is important to integrate decision-support into the environment of these systems. Business intelli-gence (BI) can be embedded in these enterprise systems to obtain this competitive advantage.

Today, approaches using an individual system for de-cision-support, such as decision-support systems (DSS), have been replaced by a new, environmental approach. In the past, DSS were independent, separate systems in an organization (island systems). However, enterprise systems are now the foundation of an organization, and practitioners are designing BI as an umbrella concept to create a decision-support environment for management (Alter 2004). The increasing trend to use intelligent tools in business systems has increased the need for Intelli-gence Assessment of Accounting Information Systems (AIS).

There have been some limited efforts to assess BI, but they have always considered BI as a system that is iso-lated from the enterprise systems like AIS. Taking a global view, Lönnqvist and Pirttimäki (2006) have de-signed BI performance measures, but before their effort, the measurement and the evaluation in the BI field were restricted to proving the worth of BI investment, and the value of BI. Elbashir et al. (2008) have discussed measur-ing the effects of BI systems on the business process, and have presented effective methods of measurement. Lin et al. (2009) have also developed a performance evaluation model for BI systems using ANP, but they have also treated BI as a separate system.

ANP, but they have also treated BI as a separate sys-tem.
Organizations usually utilize functional and non-functional requirements to assess and select enterprise systems like AIS, so the consideration of their decision-support environment as a non-functional requirement, raises the following questions.
1. Which criteria are suitable and effective in the Intel-ligence assessment of Accounting Information Systems (AIS)?
2. What is the fundamental structure of these criteria?

This research was carried out to find answers to the above questions and to provide a model for efficient decision-support by evaluating systems and making BI an integral part of these systems. The rest of this paper is organized as follows. Section 2, describes brief literature about AIS. Section 3 is about attempts in previous studies to define Business intelligence (BI). A wide-ranging literature review about BI and decision-support criteria to assess systems is also summarized in Section 3. Research methodology and research stages are discussed in section 4. Section 5 discusses the design of the questionnaire, data collection, reliability analysis, factor extraction, and labelling and assessment model. Finally, Section 6 concludes the research work, its findings and proposed future research.

2 ACCOUNTING INFORMATION SYSTEMS
An Accounting Information Systems (AIS) is defined as a computer-based system that processes financial informa-tion and supports decision tasks in the context of coordi-nation and control of organizational activities. Extant accounting information systems research has evolved from the source disciplines of Computer science, organizational theory and cognitive psychology. An advantage of this evolution is a diverse and rich literature with the potential for exploring many different interrelationships among technical, organizational and individual aspects of judgment and decision performance. AIS research also spans from the macro to the micro aspects of the information system (Birnberg & Shields, 1989; Gelinas et al., 2005).
The comparative advantage of accounting researchers within the study of IT lies in their institutional accounting knowledge. Systems researchers can contribute insights into the development of systems utilizing technology, and the other sub-areas can contribute insights into the task characteristics in the environment. For instance, systems researchers have extensively investigated group decision support systems (GDSS), but they have only recently been considered in auditing. On the other hand, auditing research has extensively investigated the role of knowledge and expertise. The merging of the two sets of findings may be relevant to AIS design, training, and use.
As comparable term, Management accounting systems (MAS) also are formal systems that provide information from the internal and external environment to managers (Bouwens & Abernethy, 2000). They include reports, performance measurement systems, computerized information systems, such as executive information systems or management information systems, and also planning, budgeting, and forecasting processes required to prepare and review management accounting information.
Research on management accounting and integrated information systems (IIS) has evolved across a number of different research streams. Some research streams put heavier emphasis on the management accounting side, while other research streams put emphasis on the infor-mation systems side. Likewise, different research streams approach the topic from different perspectives (Anders Rom & Carsten Rohde, 2007).
A major stream of research within AIS research deals with the modeling of accounting information systems. Several modeling techniques stay alive within the infor-mation systems literature (e.g. entity-relationship dia-grams, flowcharts and data flow diagrams). Whereas these modeling techniques can be used when modeling accounting information systems (Gelinas et al., 2005), But, the REA modeling technique is particular to the AIS domain. The REA model, which maps resources, events and agents, was first described by McCarthy (1979, 1982) and later developed by an exclusive group of researchers (David et al., 2002). Extensions to resources, events and agents include locations (Denna et al., 1993), tasks and commitments (Geerts and McCarthy, 2002).
An unshakable stream of research exists within the AIS literature that investigates behavioral issues in relation to accounting information systems (Sutton and Arnold, 2002). This stream of research investigates the impact of IT on individuals, organizations and society.
An example of behavioral AIS research is a study car-ried out by Arnold et al. (2004) on the use and effect of intelligent decision aids. The authors find that smart ma-chines must be operated by smart people. If users are inexperienced, they will be negatively impacted by the system. Furthermore, they will not learn by experience. Abernethy and Vagnoni (2004) found that top manage-ment uses the newly implemented system for monitoring. Use of AIS is found to have a positive effect on cost consciousness, but the cost consciousness is hampered if people have informal power. In this context, power is an explanatory variable of AIS use.

3   BUSINESS INTELLIGENCE
Business Intelligence or BI is a grand, umbrella term in-troduced by Howard Dresner of the Gartner Group in 1989 to describe a set of concepts and methods to improve business decision-making by using fact-based computerized support systems (Nylund, 1999). The first scientific definition, by Ghoshal and Kim (1986) referred BI to a management philosophy and tool that helps organizations to manage and refine business information for the purpose of making effective decisions.
BI was considered to be an instrument of analysis, providing automated decision-making about business conditions, sales, customer demand, and product prefe-rence and so on. It uses huge-database (data-warehouse) analysis, as well as mathematical, statistical, artificial intelligence, data mining and on-line analysis processing (OLAP) (Berson and Smith, 1997). Eckerson (2005) un-derstood that BI must be able to provide the following tools: production reporting tools, end-user query and reporting tools, OLAP, dashboard/screen tools, data mining tools and planning and modelling tools.
BI includes a set of concepts, methods, and processes to improve business decisions, which use information from multiple sources and apply past experience to de-velop an exact understanding of business dynamics (Ma-ria, 2005). It integrates the analysis of data with decision-analysis tools to provide the right information to the right persons throughout the organization with the pur-pose of improving strategic and tactical decisions. A BI system is a data-driven DSS that primarily supports the querying of an historical database and the production of periodic summary reports (Power, 2008).
Lönnqvist and Pirttimäki (2006), stated that the term, BI, can be used when referring to the following concepts:
1.   Related information and knowledge of the or-ganization, which describe the business environment, the organization itself, the conditions of the market, custom-ers and competitors, and economic issues;
2.   Systemic and systematic processes by which or-ganizations obtain, analyse, and distribute the informa-tion for making decisions about business operations.
A literature review around the theme of BI shows ‘‘di-vision” between technical and managerial view points, tracing two broad patterns. The managerial approach sees BI as a process in which data, gathered from inside and outside the enterprise and are integrated in order to generate information relevant to the decision-making process. The role of BI here is to create an informational environment in which operational data gathered from transactional processing systems (TPS) and external sources can be analysed, in order to extract ‘‘strategic” business knowledge to support the unstructured deci-sions of management.


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