Evaluating the Design of Accounting Information System and its Implementation in Ethiopian Manufacturing Industries

Evaluating the Design of Accounting Information System and its Implementation in Ethiopian Manufacturing Industries Dr. Yuvaraj Sambasivam, Associate Professor, Department of Management, College of Business and Economics, Debre Morkos University, Debre morkos, Ethiopia Mr. Kibret Baye Assefa, Head, Department of Accounting, College of Business and Economics Debre Morkos University, Debre morkos, Ethiopia Abstract The purpose of this research is to evaluate the effectiveness of accounting information system design and implementation. This study give an insight in identifying better and poor performance of the AIS, and a clue of measurements to be taken in order to improve the AIS design and implementation. Data were collected from primary sources while Z-Test statistics and multiple comparison tests were used for analysis of data. The results indicate that the accounting information system design and implementation of these firms is effective at the same time as it could: enhance quality of financial reports, control and safeguard assets. The results did not indicate that the accounting information system design and implementation is effective, as it could not improve performance evaluation. It was concluded that for accounting information system design and implementation to be effective, firms accounting information system stakeholders are supposed to focus on: enhanced AIS design and implementation criteria and increased attention towards professional and operational standard. Key Words: effectiveness of accounting information system, AIS design and implementation, manufacturing industries, quality of financial reports, professional and operational standard Introduction 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. Nowadays, more and more digital and on-line information is utilized in the accounting information systems. Organizations need to take an action, which put such systems at the forefront, and consider both the system and the human related factors while managing their accounting information systems. In managing an organization and implementing an internal control system, the role of accounting information system (AIS) is crucial. The evaluation of accounting Information system design and its implementation idea of the research study can be viewed from two points. First, AIS installation process should consider the cost that is cost of designing should be lesser than the benefit. It is also important for organizations to focus on the fitness of the design to the firms need. Second, the data quality issue and critical success factors for the system s effectiveness. The Decentralization Support Activity (DSA) of USAID commenced its activities in January, 1997in Ethiopia, found from the report of evaluation of The in Service Training Program in Financial Management- September 2006 that the budgets of the federal and regional governments were using a single-entry, cash-basis accounting system based on the chart of accounts extant at this time, reflected the level of human capital administering the system. Although Budget Disbursement and Accounts (BDA) were developed using Visual Basic and used relational industrycompatible database systems, they had significant weaknesses (e.g., lack of security features and integration capability, a basic database system, no online capability, etc.). In 1998, DSA outsourced the task of converting the Common Business Oriented Language (COBOL) mainframe system to a Windows based MS Access database application to a private company. In 1997, the project recognized the need to automate the budget preparation and consolidation activities. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 16

All the above country level weaknesses are most likely similar with Ethiopian manufacturing firms financial preparations and reports weaknesses, which are characterized by poor quality, incompatible, inaccessible, inefficient in controlling and safeguarding the entities asset (ROSC, 2007). The reason for such outcomes may be because of inefficient AIS design and implementation; this is why it captures an attention to be studied. So, being in the developing economy, Ethiopian manufacturing enterprises failure to have efficient design and effective implementation of the system can have a negative impact on the desired achievement, that is, poorly designed and ineffectively implemented AIS may have adverse effects on decision making. The evaluation of accounting Information system design and its implementation is aimed to assess performance of the AIS of medium and large-scale manufacturing firms. Statement of the Problem An important question in the field of accounting and management decision-making concerns the fit of AIS with organizational requirements for information communication and control. Manufacturers need fittest financial and non-financial information such as financial statements, price changes, market trends, and customer behaviors to survive and grow (Chen hall & Morris, 1986). Without which it is extremely difficult to make good decisions. According to USAID-Ethiopia, (2006) Ethiopian firms have poor accounting records for the purpose of to avoid tax and other obligations. This creates twofold problem. Poor records make it difficult for companies to get reasonably priced credit and then to manage their affairs effectively if they do get credit. Failure to make better decision based on financial reports is a feature of firms in Ethiopia due to multiple books kept by businesses in order to avoid taxes and other obligations, so that most companies do not have audit-worthy financial records. Thus, poor accounting increases the likelihood of bankruptcy and makes bankruptcy administration more difficult as well (USAID Ethiopia, 2007). As ROSC, (2007) studies, manufacturing companies in Ethiopia has exercising inefficient accounting system Due to poor implementation of the International Accounting Standards and the study also shows limited number of professional accountants contributed to the problem. However, studies mentioned above indicated that the AIS design and implementation is inefficient, the measurement criterions are not in compliance with the roles of AIS for virtual manufacturing firms of Ethiopia. This initiates the research study in light shading knowledge of existing literatures towards the AIS s actual performance. Sajady. H, (2008) studied accounting information system performance can be best evaluated on the point view AIS roles or criteria in addition to evaluation criteria set by ROSC and USAID. Therefore, aim of this study is to evaluate the AIS design and implementation based on the roles or criteria of effective AIS. Research Hypothesis Hungjiang Xu, (2003) studied that AIS s quality is affected by different factors. Accordingly, it is critical to consider success factors while implementing AIS like quality of financial reports and quality of decisions by managers. Sajady. H, Dastgir. M.et al, (2008) showed that, accounting information system can be effective as, if it can improve performance measures. Better, AIS performance enable to strengthen the internal control (Lembi Noorve, 2006). More over fittest accounting information system comes true as far as business firms can implement appropriate system design in line with organizational objective. After reviewing relevant literatures, in addition to focuses of studies mentioned above, the following research ideas were developed in order to measure four main variables that are hypothesized in line with research questions. Hypothesis 1: Accounting information systems enhance the quality of financial reports. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 17

Hypothesis 2: Accounting information systems is affected by the system design. Hypothesis 3: Accounting information systems improve performance measures. Hypothesis 4: Accounting information systems lead to more effective internal control system. Objective The research had a general objective of evaluating the design of AIS and its implementation by medium and large scale manufacturing firms in and around Addis Ababa. Specific objectives The specific objectives of the research were to: Evaluate effectiveness of firms accounting information system to provide adequate control. Estimate accuracy of AIS designing in determining data and report qualities. Evaluate firm s devotion towards the continuous redesigning of AIS s weakness if any. Significance of the research The research study as it had evaluated AIS effectiveness of manufacturing firms, It provides an insight on the prevailing performance of AIS and the status of system design, to concerned parties, because of the presence of little documentation. In identifying better and poor performance of the AIS, the study gives a clue of measurements to be taken in order to improve the AIS design and implementation. The study also provides some information regarding the gap exists in the field to be studied. Scope and Limitations of the study The research study had focused on the AIS effectiveness of medium and large scale manufacturing firms found in and around Addis Ababa. The study covers a period of six months since identifying problems while reviewing literatures. The effectiveness was on the design and implementation of the AIS. Manufacturing firms are selected because the AIS functions can be best explained by operations of such firms. Limitations of the research study were: The study is confined to in and around Addis Ababa, since it should include wider range of the economy. The limited number of sophistications AIS user manufacturing firms in the study area. Studies shows that the extent of accounting information system implemented by private and public companies in Ethiopia needs to be improved in quality (USAID,2006), this shows that, firms which are implementing the AIS lack modernity. In addition, manufacturers, which cover only 12% of the total economy (World Bank 2008), are obviously limited in number. Shortage of related literature review in Ethiopian context Its exclusion of service delivery firms Review of Literature Information system: An information system is a set of formal procedure by which data are collected and processed into information and distributed to user (Romney et al., 1997). Accounting information system is a system that collects, records, stores, and processes data to produce information for decision makers. It can use advanced technology or be a simple paper-and- pencil system: or be something in between. Accounting information system is a specialized subsystem of the information system that collects, processes, and reports information related to the financial aspects of business events (Ulrich J. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 18

GeLinas, Jr, 2008). Accounting information system is a computer-based system that increases the control and enhances the corporation inside the organization (Essex, P. A. and Magal, S. R., 1998,). AIS Modeling According to Steve (2003) are based on the tools that are used to collect, process, manage data and generate information for the system implemented. Data collection (Capturing transaction data, Recording data onto forms, Validating and editing the data), Data processing (Classifying, Transcribing, Sorting, Batching, Merging, Calculating, Summarizing, Comparing), Data management (Storing, Retrieving, Deleting) and Information generation (Compiling, Arranging, Formatting, Presenting) As Ulric J. and GeLinas, Jr, (2008) pointed out diagrammatically documenting organizational data flows (data flow diagrams-dfds) and business processes (systems flowcharts); Data storage methods; The role of databases in data management; and the various business intelligence tools that are important for making sense out of the vast enterprise databases to enhance strategic decision making. Entity relationship (E-R) diagrams (used to model database structures); modeling information systems using the REA (Resources, Events, and Agents) method, creating E-R diagrams, mapping these diagrams to relational databases, and using SQL (Structured Query Language) to manipulate and retrieve data from relational databases. AIS for Internal Control According to Hall, J. A. (2004), internal control is the process implemented by the board of directors, management and those under their direction to provide reasonable assurance that the following control objectives are achieved. Asset (including data) are safeguarded Records are maintained in sufficient details to accurately and fairly reflect assets. Accurate and reliable information is provided There is reliable assurance that financial reports are prepared in accordance with Generally Accepted Accounting Principle (GAAP) Operational efficiency is promoted and improved. Adherence to prescribed managerial policies is encouraged The organization is complies with applicable laws and regulations. Internal control is designed to assist organizations in achieving their objectives. The five components of COSO s Internal Control - Integrated Framework (the COSO Framework) work in cycle to alleviate the risks of an organization s failure to achieve those objectives. Internal control performs three important functions, preventive controls, detective controls, and corrective controls (Romney, Marshall B et al, 1997). Control Frameworks A number of frameworks have been developed to help companies develop good internal control system. Three of the most important are: The COBIT (control objective for information and related technology) framework, the COSO (Committee of sponsoring organization) internal control framework. In addition, the COSO s enterprise risk management framework (ERM). The COSO framework addresses the issue of control from the vantage points or dimensions: business objectives, Information Technology resources, Information Technology processes. COSO internal control model has five crucial components: control environment, control activities, risk assessment, information and communication, and monitoring. The COSO Enterprise Risk Management integrated framework can provide enhanced corporate governance document, enable business to achieve its financial and www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 19

performance target, provide reasonable assurance that company objectives and goals are achieved and problems and surprises are minimized (Romney, Marshall B et al, 1997). AIS in Value Chain As described by Romney, Marshall B. et. al., the value chain the full range of activities, which are required to bring a product or service from conception, through the different phases of production (involving a combination of physical transformation and the input of various producer services), delivery to final consumers, and final disposal after use. Value chain can be one or many. The objective of many organizations is to provide value to their customers. A business will be profitable if the value it creates is greater than the cost of producing its products or services. An organization s value chain consists of nine activities that collectively describe everything it does. The first five (Inbound logistics, operations, outbound logistics, marketing and sales, and services) are performed in order to create market and deliver products and service to the customers and to provide post sales service and support. The remaining four (firm infrastructures, human resource, technology, and purchasing) activities in value chain make it possible for the primary activities to be performed efficiently and effectively. AIS add value by providing accurate and timely information so that five primary value chain activities can be performed more efficiently and effectively. AIS can also adds value by improving the quality and reducing the cost, or services, improving efficiency, improving decision making capabilities, increasing the sharing of knowledge. Well-designed AIS can also an organization profit by improving the efficiency and effectiveness of its supply chain (Hall, J. A., 2004). Manufacturing Industries in Ethiopia Compared to industrialized nations Ethiopians history of industrialization is a recent one. According to Eshetu Chole (1985), Manufacturing started to develop in Ethiopia around the turn of the century with the emergence of a strong central government, political stability, the installation of the railway to Djibouti and the strengthening of Ethiopian foreign relations. The increasing settlement of foreign citizens from Armenia, Greece, Italy and India also brought entrepreneurial capacity. Industry in Ethiopia was, before 1957, dominated by cottage and handicraft industries, which met most of the population's needs for manufactured goods such as clothes, ceramics, machine tools, and leather goods. Eshetu also finds that, including the current territory of Eritrea, Ethiopia had 25 companies by 1927. By the time of the overthrow of the imperial regime, however this figure raised to 273 establishments.various factors - including the lack of basic infrastructure, the dearth of private and public investment, and the lack of any consistent public policy aimed at promoting industrial development - contributed to the insignificance of manufacturing (Theo van der Loop, 2003). After the overthrown of the imperial regime manufacturing was facing stagnation, According to Theo van der Loop, after the Derg regime, EPRDF s liberalization policy, since 1991 has opened up the country for competition from outside to a previously protected industrial sector. This led to a rather fast increasing influx of cheap, second-hand and new consumer goods (from watches, through fashionable, leather ladies shoes, to used clothing and brand-new T-shirts), especially from China. Numerous factories and workshops were pushed out of business and others had to reorient themselves. The manufacturing sector contributed 5% of GDP and 37.8% to the total value of industrial production in 2008 09 (Theo van der Loop 2003). The major manufacturing activities are production of food, beverages, tobacco, textiles and garments, leather goods, paper, metallic and non-metallic mineral products, cement and chemicals. Under the export-led industrial development strategy, production of textile and garments, leather products and agro-processing are priority areas for investment. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 20

IMPORTANCE OF ACCOUNTING INFORMATION SYSTEM ADOPTION Implementing the AIS is becoming inevitable to be competent in the current time with the globalization of trade and investments, as well as dynamic technological changes taking place, there for manufacturing firms need to gear themselves to face harder competition in the future. These firms there for need to recognize that IT has the potential to improve productivity, quality and performance - areas that are essential for their survival and success. In addition to the basic financial reports, Manufacturers also need non-financial information such as price changes, market trends, and customer behaviors to survive and grow (Chen Hall & Morris, 1986). Therefore, it is believed that for the owners/managers it is becoming extremely difficult to make good decisions without the use of IT. Even though there is a limitation of prior researches that are done in Ethiopia, there are empirical evidences done on developing countries, like on Saudi Arabia (Ahmad A. Abu-Musa, 2006), Nigeria (A. A. Owojori and T. O. Asaolu, 2010), Malaysia (Noor Azizi ismail, and Shamsul Nahar Abdullah,2003), Iran (H. Sajady, M. Dastgir,et al,2008), Jordan (Mahmoud Al-Eqab1 and Noor Azizi Ismail, 2011), which discussed and found inefficient accounting information system has multidimensional effect on the respective countries economy, and asserted the importance of evaluating the AIS design, adoption, implementation effectiveness. Evaluation of Effectiveness To implement the accounting information system successfully the system should consider contingency factors like dominant view of the organization, problems to be solved and norms of the organization in addition to the purpose of the system (Ives, B., et al., 1983). Accounting information systems are said to be effective if the information provided by them serves widely the requirements of the system users. Effective systems should systematically provide information that has potential effects on decision-making process. Coordination of the organization is the result of integration of the system, there for coordination of the organization in turn increases the quality of the decisions (Huber, 1990). Simon R. (1987) also AIS provide financial report on a daily and weekly basis which enable in turn provides a measure of control for management (Mia, L., 1994). Accessibility to information related to the main transactions of an organization leads to a categorized detailed information, which facilitates decision making in any difficult situation. In addition, AIS provide use full information for monitoring decision-making process and performance of the organization, which enable to evaluate the effectiveness. Choe,J. M, (1998), wrote that effective accounting information systems can be analyzed on three bases: 1) information scope, 2) timeliness, 3) aggregation. Evaluation Criterions of AIS Effectiveness The goals of evaluation are to learn from experience, to provide an objective basis for assessing the results of the work done, and to provide accountability in achieving its objectives. It is therefore to improve entities work by identifying and disseminating lessons learned from experience and by framing recommendations drawn from evaluation findings. Therefore, the criterions of evaluation of the effectiveness of AIS are the role/benefits of the AIS. The alignment between the role of AIS and implemented AIS in the organization has a positive effect on companies performance (Cragg et al., 2002). Research Design and Approach The research paper followed a survey design in order to evaluate the AIS design and implementation of medium and large scale manufacturing firms. More than 60% of manufacturing firms of the country are found in and around Addis Ababa, Ethiopia. The firms are actively operating and owned by different investors from every part of the country and from abroad. Different types of manufacturing firms throughout the country are almost found in the study population area (Addis Ababa chamber of commerce). Therefore, the survey design is suited to evaluate medium and large www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 21

scale manufacturing firms in Ethiopia based on the evaluation of medium and large scale manufacturing firms found in and around Addis Ababa. There is some evidence suggested that the differences of accounting information system performances are likely to be minor in Ethiopia. Although the results of this study are only drawn from manufacturers in and around Addis Ababa, there might be similar results, if a study was conducted in other parts of Ethiopia (USAID Ethiopia 2006). Sample Size: - From a survey of 555 medium and large-scale manufacturing firms in Addis Ababa Ethiopia, 105sample manufactures were taken out of which 79 firms return the questionnaire. Data Collection Method As the main data collection instrument, in this study, consists of both open ended and closed ended questions. A questionnaire was designed after reviewing the relevant literature. It was distributed to major AIS stakeholders, throughout 105 sample manufacturing firms. Distribution was conducted both in person delivery and through e-mail addresses compiled by Addis Ababa Chamber of commerce. The questionnaires from respondent firms were filled or replied by 33 accountants, 15 IT officers, and 25 finance manager, and 6 executive managers. Method of Data Presentation and Analysis A total of 79 valid responses were collected from different types of industries categorized in to four for the sake of clustering. The questionnaire had both open ended and five likert- scale questions were designed to measure moderator and main hypothesis of the study, based on roles of AIS. The data collected has two features of information, the first is demographic information and the second is study objective based. A total of 32 questions are categorized into four, as they were prepared to address four theoretical hypothesis of the study. Under each group the mean of each questionnaire were computed because of similarity towards a grouping variable, the mean can be used as representative of one questionnaire, with similar fashion means of the grouping variables were determined. One-tail Z test, to measure the probability that the sample mean would be greater than the average of observations in each hypothesis, by measuring proportion of actual average and a likert mean of 3 as if a population mean, using spreadsheet, Microsoft office excel 2010. In addition Software Package for Social Science (SPSS 16.0) was used to measure central tendency, dispersion, and one way Analysis of Variance (ANOVA), the data out puts are presented in tabulation. Data Presentation and Result Analysis A total of 32 questions were categorized into four, as they were prepared to test four theoretical hypothesis of the study. Mean for each hypothesis were computed based on similarity of questions towards a grouping variable, Mean of a question is used as a representative from one questionnaire, with similar fashion means of the grouping variables were determined. We have applied a one-tail Z test, to measure proportion of actual average and a Likert mean of 3 as if a population mean, using Spreadsheet of Microsoft Office Excel. In addition SPSS 16.0 was used to measure central tendency, dispersion, and one way ANOVA. The data out puts are presented in tabulation. Performance Analysis Suitable analysis of effectiveness evaluates actual performance through the comparison of AIS s importance. An importance of AIS can be evaluated based on the likert scale of 5 points, 1 for no importance, 2 for less importance, 3 for medium importance, 4 for very good importance and 5 for highest importance. Therefore actual performance is compared with the mean value µ > 3 for better www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 22

performance and µ 3 weaker performance. The likert mean therefore used as of the population mean computed as: Table 1 Statistical means compared with a Likert mean. Variables Mean Std. Pop. Differen Rank Quality of Data Used 3.52 1.096 Dev. Mean 3 0.52 ce Extent of AIS Designing Accuracy 3.62 1.066 3 0.62 Reliance of Auditors on FOut put 3.48 0.945 3 0.48 Automatically Performs Many Data 3.33 1.227 3 0.33 Ease of Modification of the System 3.54 1.107 3 0.54 System Maturity 3.59 0.927 3 0.59 AIS enhance the quality of financial reports 3.514 3 0.514 1 st Compatibility of Software 3.34 0.766 3 0.34 Security Level of the System 3.44 0.764 3 0.44 Validity of the System 3.46 0.765 3 0.46 Integrity of the System 3.28 0.876 3 0.28 Recovery Ability of the system 3.39 0.898 3 0.39 AIS Redesigning Custom of the Company 3.11 0.832 3 0.11 AIS is affected by the system design 3.337 3 0.3367 2 nd Educational Fitness Level of Accountants 3.3366 2.59 0.840 3-0.41 Training Taken for Better Performance 2.62 7 0.773 3-0.38 Need of Future AIS Improvement 3.04 0.912 3 0.04 Up to Date System Usage 2.73 0.843 3-0.27 Communication Between Different Professionals 2.73 0.902 3-0.27 AIS improve performance measures 2.744 3-0.256 4 th Reliability of the AIS in Controlling Assets of the 3.29 0.736 3 0.29 Business Level of the Integration and System Interpretability 3.34 0.783 3 0.34 Effective Data Management Approach 3.41 0.840 3 0.41 Communication Between Different Departments 3.28 0.767 3 0.28 Suitable Organizational Structure 3.32 0.777 3 0.32 Accounting information systems lead to more effective internal control systems 3.326 3 0.326 3 rd Source: Table of means output from ANOVA SPSS The whole questionnaire is divided into the four categories that are considered as research hypothesis, therefore, means of each question under each category are further used to compute mean of each hypothesis or category. As shown in the Table 1 above, means of actual performance of AIS of five measuring criterions for effectiveness are above the mean value assigned for importance of AIS. One is below the mean of importance. Based on mean of the effectiveness and mean difference AIS s role of enhancing the quality of financial reports is highest with 3.51 mean and 0.51 mean difference. System design impact on AIS is the second highest with mean 3.337 and mean difference 0.337. The third effective criterion of AIS performance measurement is implementation of AIS lead to effective internal control system with mean value of 3.326 and mean difference with importance mean of 0.326. Among effectiveness evaluating criterions of AIS s role, the actual performance of performance evaluation measures, whose mean and mean difference were 2.74 and (-0.26). www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 23

Statistical tests To test four hypotheses of the study statistical hypothesis are set as follows: H0: μ 3 H1: μ > 3 Z test was used, in order to accept and reject hypotheses, by comparing proportions of actual means of each hypotheses and a five-scale likert mean as a population mean. Z test was computed using spreadsheet-excel-function reference-statistical- Z test, with a Z test formula of one-tail normal distribution as: =ZTEST(array,μ 0 ). Excel formula can be used to calculate the one-tailed probability that the sample mean would be further from μ 0 than Average(array), when the underlying population mean is μ 0. Z test represents the probability that the sample mean would be greater than the observed value average (array), when the underlying population mean is μ 0. From the symmetry of the normal distribution, if average or array < μ 0, Z test will return a value greater than 0.5. The test was conducted at a 95% confidence level, with a 5% critical level, for which a Z value is 1.645, so that, Z value of the average compared against the critical value. Therefore, we have tested whether the mean value of each question was less than or greater than 3. Number 3 was the average number of the five choices in each question. Hypothesis Testing and Result Analysis Four major roles of AIS, those were described in the literature part and observed in Table 2, are hypotheses, whose averages were tested. Table 2 Hypothesis Representations S. No. Hypothetical theory of the role of AIS No. of questions Representative 1 AIS enhance the quality of financial reports 6 Hypothesis 1 2 AIS is affected by the system design 6 Hypothesis 2 3 AIS improve performance measures 5 Hypothesis 3 4 AIS lead to more effective internal control 5 Hypothesis 4 Hypo thesis Median Mini. Maxi. Mean Statistic Statistic Statistic Statistic Table 3 Descriptive Statistics Std. Devi. Variance Skewness Kurtosis Std. Error Statistic Statistic Statistic Std. Error Statistic Std. Error 1 3.5 2.3333 4.6667 3.514 0.0639 0.5687 0.323 0.121 0.271-0.576 0.535 2 3.333 2.1667 4.6667 3.337 0.0573 0.5098 0.260 0.210 0.271 0.295 0.535 3 2.8 1.2000 3.8000 2.744 0.0593 0.5271 0.278-0.470 0.271 0.231 0.535 4 3.4 2.4000 4.4000 3.326 0.0560 0.4983 0.248 0.136 0.271-0.283 0.535 Source: Summarized from Table of Descriptive Statistics of ANOVA analysis Table 4 Z Test Computation Hypothesis Average Z-VALUE CALCULATED P Value 1 3.514 4.441 0.0000045 2 3.337 1.997 0.0229 3 2.744 0.999 0.1589 4 3.326 2.868 0.0021 Source: Z calculation Procedure on Excel www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 24

Using the descriptive statistics output of each hypothesis Z test, shown in Table 3, were analyzed in comparison with the average, standard deviation of the average, skewness, and kurtosis. Z test is used to compare the proportion of a five point scale likert mean, here after 3 and averages of actual observations. Result of the First Hypothesis AIS Enhance the Quality of Financial Reports: Average value of the hypothesis is 3.514 with kurtosis of -0.576 and skewness of 0.12, which shows the distribution of data, is shorter than the normal distribution curve compared to the hypothesis 1 standard deviation of 0.569. The statistics also shows, the data are distributed not far from the mean than the standard deviation and large proportion of the data variables are found to the right side of the mean, that is larger respondents reply were above the average. One-tail Z test, shown in Table 4, conducted for the hypothesis resulted 4.441 Z value, which is larger than the critical value 1.645 for a critical level of alpha = 0.05, by 2.796. The test represents the probability that the sample mean is greater than the observed value 3.514 with p (< 0.0001), considering the underlying population mean is 3. So, the test rejects H0: μ 3 and accept H1: μ > 3. Therefore, according to the respondents reply, Accounting Information System enhances the quality of financial report. So that, it is possible to conclude that the AIS design and implementation by the respondent firms is effective, in providing quality financial report. Result of the Second Hypothesis The System Design affects AIS: The hypothesis has a mean 3.337 with a standard deviation of 0.5098, skewness of 0.210 and kurtosis 0.295, which shows, the data variable distribution is a little shorter than the normal curve and larger proportion of the respondents views are lied to the right of the mean, that is more than the hypothesis average. Z test conducted for the second hypothesis resulted 1.997 calculated value, shown in Table 4, greater than the critical value 1.645. The difference between Z calculated and the critical value is 0.352. This test represents the probability that the hypothesis s mean is greater than the observed average value 3.337 with a significance of p = (0.0229), taking into account the underlying population mean is 3. The test rejects H0: μ 3 and accept H1: μ > 3. Therefore, from the respondents point of view, the system design quality has direct relationship with the AIS. From this it is possible to conclude that the AIS they implement, is effective. Z test formula for one tail which results Z values for each hypothesis, is based on the column array of the excel sheet which contains 79 means of clustered questions for each hypothesis. Result of the Third Hypothesis AIS Improve Performance Measures: The hypothesis has a mean 2.744 with a standard deviation of 0.527, skewness of -0.470 and kurtosis 0.231. It shows, the data variable distribution is a little shorter than the normal curve. The larger proportion of the respondents views are laid to the left of the mean that is more than the hypothesis average. As shown in Table 4, Z test conducted for the third hypothesis resulted 0.999, which is lesser than the critical value 1.645. The difference between Z calculated and the critical value is -0.646. The test represents the probability that the hypothesis s mean is not greater than the observed average value 2.744 with p value 0.1589, referring the underlying population mean 3. The test accepts H0: μ 3 and rejectsh1: μ > 3. Therefore, from the respondents point of view the AIS did not enable them to improve performance measures. From this, it is possible to conclude that the AIS they implement, is ineffective. Empirical studies also support the result found, and concluded that their respondents on average do not believe that accounting information systems improve performance measures www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 25

Result of the fourth Hypothesis: AIS Lead to More Effective Internal Control: Z test conducted for the six hypothesis resulted 2.868, shown in Table 4, which is higher than the critical value 1.645. The difference between Z calculated and the critical value is 1.223. This test represents the probability that the hypothesis s mean is greater than the observed average value 3.326 with p value 0.0021, considering the underlying population mean is 3. The test rejects H0: μ 3 and accept H1: μ > 3. Therefore from the respondents point of view the accounting information systems lead to more effective internal control. From this it is possible to conclude that the AIS they implement, is effective in leading to a more effective internal control. The hypothesis has a mean 3.326 with a standard deviation of 0.498, skewness of 0.136 and kurtosis -0.283, which shows, the data variable distribution is a shorter than the normal curve, and larger proportion of the respondents views are laid to the left of the mean that is less than the hypothesis average. Table 5 Hypothesis Conclusion Hypothesis H1 H2 H3 H4 Average 3.514 3.337 2.744 3.326 Standard Deviation 0.569 0.5098563 0.527 0.498 Z value calculated..zv* 4.441 1.997 0.999 2.868 Alpha (0.05) Z value..av** 1.645 1.645 1.645 1.645 (ZV*)-(AV**) 2.796 0.352-0.646 1.223 P value < 0.0001 0.0229 0.1589 0.0021 Conclusion Accept Accept Reject Accept (ZV*)-(AV**) = Z value calculated- Alpha (0.05) Z value Analysis of Moderator Variables Test The external (moderator) variable test on levels of respondents' education was applied. It is to test whether it has any impact on averages of each hypotheses, the SPSS 16.0 software of compare meanone way ANOVA- descriptive statistics and TUKEY HSD with alpha 0.05 was used. Result of the External Variable Test There is a relationship between the levels of respondents' education and evaluation of the effectiveness of accounting information system. As shown in Table 6, there were 3, 25, and 51 respondents whose education levels are certificate, diploma, and 1st degree, respectively. To test whether the variation in education also reflected on the average values that they have towards the AIS effectiveness, the education level used as independent variable and four hypothesis used as dependent variable. Post Hock test for multiple pair-wise comparisons showed in detail no significant difference between means of each education level. The mean difference could be significant at the 0.05 level, but the multiple comparison tests showed as in Table 6, p values of mean difference between certificate, diploma, and 1 st degree is ranged from 0.137 to 1.000, with mean difference ranged from 0.00094 to 0.6311. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 26

Table 6 Multiple Comparisons of education levels Tukey HSD Dependent Variable (I) Education Level (J) Education Level Mean Sig. of the Respondent of the Respondent Difference (I-J) AIS enhance the Certificate Diploma 0.6311111 0.166 quality of financial 1st degree 0.6143791 0.165 reports Diploma Certificate -0.6311111 0.166 1st degree -0.0167320 0.992 1st degree Certificate -0.6143791 0.165 Diploma 0.0167320 0.992 AIS is affected by the Certificate Diploma -0.1333333 0.904 system design 1st degree 0.0588235 0.979 Diploma Certificate 0.1333333 0.904 1st degree 0.1921569 0.275 1st degree Certificate -0.0588235 0.979 Diploma -0.1921569 0.275 AIS improve Certificate Diploma -0.2186667 0.780 performance measures 1st degree -0.2196078 0.767 Diploma Certificate 0.2186667 0.780 1st degree -0.0009412 1.000 1st degree Certificate 0.2196078 0.767 Diploma 0.0009412 1.000 AIS lead to more Certificate Diploma -0.5626667 0.148 effective internal 1st degree -0.3333333 0.485 control systems Diploma Certificate 0.5626667 0.148 1st degree 0.2293333 0.137 1st degree Certificate 0.3333333 0.485 Diploma -0.2293333 0.137 Source: A summary of multiple comparisons Post Hoc test of Education level mean comparison. Conclusion The study had analyzed AIS design and implementation to evaluate the effectiveness based on four hypothetical roles, enhancement of the quality of financial report; effect of system design on implementation, improvement of performance measures and effective internal control systems. There was no evidence for the third hypothesis. Accounting information system designing and implementation would not improve performance measure. Reason for hypothesis rejecting or failure of the result might be improper specifications of questions related with the third hypothesis. Three hypotheses testing on the actual performance resulted, AIS design and implementation could make possible the enhancement of quality of financial report; system design could affect quality of AIS implementation; AIS design and implementation could facilitate financial transaction processes, lead to better decision-making by managers, enable to have more effective internal control systems. Based on identified roles, the AIS designed and implemented were successful, by attaining three out of four, with a more than average actual performance compared with the average importance. Therefore, in fulfilling business objectives the study concluded that accounting information System design and implementation by manufacturing firms in Ethiopia was effective, except achieving the accounting information system s role of performance evaluation measurement. The study also concluded, evaluation of accounting information system design and implementation was not affected by the difference in education level of the respondents. The implication is medium and large-scale manufacturers are implementing effective AIS, which fit their need. www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 27

Continuous AIS design and implementation for high-level data quality management practice is one of the keys to success for many organizations. Adoption of the some criteria for effective design and implementation accounting information system for a better financial data quality management in AIS can permit managers to obtain a better understanding of accounting information system data quality management practices. If firms focus on enhanced AIS design and implementation criteria, they may be able to improve their decision making role, and can ensure better quality of the accounting information in the future. Performance of firms in general and each department of firms in particular can be measured and improved through implementing effective AIS. Manufacturing firms, therefore, are recommended to take an advantage of their AISs role in measuring every segment s performance, to direct operations or tasks, to forecast business. In addition manufacturing firms are recommended to provide necessary training for accountants and financial managers on accounting software packages, in order to update accounting information system, to appreciate performance through incentives. The group effort between different stakeholders can become more important for effective AIS design and implementation. The findings of this research provide firsthand information to AIS stakeholders as the front line practitioner, namely accountants, system designers, financial managers and firm managers that they should take an active approach to improve activities of effective AIS. It is recommended to policy makers to pay attention towards the current actual performance and future improvement of accounting information system of manufacturing firms. Ethiopian Revenue and Custom Authority (ERCA), Ministry of Finance and Development (MFD), The Ethiopian Professional Association of Accountants and Auditors (EPAAA), Accounting Society of Ethiopia(ASE) are recommended to take an action in setting laws or regulations that requires accounting standards and GAAP / IFSR in preparation of financial statements. References: A.A. Owojori and T. O.Asaolu, (2010). Critical Evaluation of Accounting Systems in Multinational Organizations in Nigeria. J Soc Sci, 23(2): pp. 75-82. Ahmad A. Abu-Musa (2006). Evaluating the Security Controls of CAIS in Developing Countries: The Case of Saudi Arabia. The International Journal of Digital Accounting Research, Vol. 6, N. 11, May, pp. 25-64. Chenhall, R. H. and Morris, D.,(1986). The Impact of Structure, Environment, and Interdependence on the Perceived Usefulness of Management Accounting System. The Accounting Review, Vol. 61, pp. 16-35. Choe, J. M., (1998). The Effects of User Participation on Design of Accounting Information Systems. Information & Management, Vol. 34, pp. 185-198. Cragg, P. B. King, M. & Hussin, H., (2002). IT alignment and firm performance in small manufacturing firms. Journal of Strategic Information Systems, 11(2), 109-132. CSA, Central Statistical Authority of Ethiopia, (2011). Statistics of manufacturing industry 2009/2010. FDRE, Addis Ababa, March. Development Economics Development Data Group (DECDG), (2008). Ethiopia at a glance. World Bank. Eshetu Chole, (1985). Constraints to Industrial development in Ethiopia. Mimeo. Addis Ababa. Essex, P. A. and Magal, S. R., (1998). Determinants of Information Centre Success. Journal of Management Information Systems, Vol. 15, No. 2, pp. 95-117. Hall, J. A., (2004). Accounting information Systems, 4 th edition, South-Western College www.theinternationaljournal.org > RJSITM: Volume: 02, Number: 07, May-2013 Page 28

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