# comprehensive analysis of data obtained from questionnaires

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This section presents a comprehensive analysis of data, which have been obtained from questionnaires. To determine whether the aim and objectives of the research have been met, data have been analyzed and hypotheses have been tested. Private and Public sectors are found to have a combination of data where each is put side by side in the study. Hence, to support observations and analysis, diagrams and tables are designed by means of SPSS and Microsoft Excel as well as additional information are included in Appendix.

## 4.2 NATURE OF COMPANY

30 questionnaires were administered to private companies and 20 questionnaires were delivered to public companies. Thus, the analysis is a comparative one. Out of 30 questionnaires that were administered to private companies, only 25 responses were collected, and 15 responses were received from public companies. The composition of private and public respondents can be observed in FIGURE 1. From the 25 respondents, private companies represent 62.5% of the total respondents whereas 37.5% remaining respondents are public companies.

## 4.3 USE OF CAS

FIGURE 2 below provides a clear representation of the percentages of CAS adoption by private and public companies. It shows 62.5% used CAS in private sector and 37.5% in public sector. Despite, the cross tabulation of Nature of Company and CAS, the percentage have remained constant as no statistics have been entered in the manual system.

## Hypothesis:

Ho: There is no relationship between Nature of company and CAS.

H1: CAS depends on nature of company

## Chi-Square Tests

Value

Pearson Chi-Square

.a

N of Valid Cases

40

No statistics are computed because cas is a constant.

## Symmetric Measures

Value

Nominal by Nominal

Phi

.a

N of Valid Cases

40

No statistics are computed because cas is a constant.

Hypothesis that has been developed to test this assumption shows from the tables above that it cannot be said whether to accept or reject (Ho or H1) since CAS is a constant. Otherwise, at 5% level of significance, if it was (<0.05), H0 would have been rejected and H1 would have been accepted and vice-versa. Besides, it cannot be concluded how much is the degree of confidence that is whether the relationship between Nature of company and CAS is strong or weak. Else, again the 5% level of significance would have been needed that is weaker when it is (<0.05) and stronger when it is (>0.05). Hence, it can only show about the percentages CAS adoption in Private and Public companies.

## 4.4 INDUSTRIAL SECTOR

FIGURE 3 below shows the percentage of CAS that has been applied to the different private sectors. Leisure and hotels, Service, Insurance, Banking and Investment use the highest percentage of CAS (12%). Wholesale & Retail trade, Manufacturing and Transport sectors use 8% of CAS. On the other hand, Agricultural, Construction, Electricity, Gas & water supply and other sectors make use of the lowest percentage of CAS (4%).

## Hypothesis:

H o: There is no relationship between the industrial sectors and CAS.

H1: CAS depends on the industrial sectors.

## Chi-Square Tests

Value

Pearson Chi-Square

.a

N of Valid Cases

25

No statistics are computed because cas is a constant.

## Symmetric Measures

Value

Nominal by Nominal

Phi

.a

N of Valid Cases

25

No statistics are computed because cas is a constant.

The hypothesis from the Chi-Square Tests and Symmetric Measures above indicate that it cannot suggest if there is a relationship between industrial sectors and use of CAS, as CAS is a constant. Therefore, at this stage of analysis, it can only be concluded about the level of percentages use of CAS in each private sector.

## 4.5 RECOGNIZED ON STOCK EXCHANGE

FIGURE 4 is a pie chart viewing the percentage of public sector which is recognized on the stock exchange market (CAS 66.7%) and the percentage of public sector which is not recognized on the stock exchange market (CAS 33.3%)

## Hypothesis:

Ho: There is no relationship between public sector recognized on SEM and CAS.

H1: CAS depends on the public sector recognized on SEM.

## Chi-Square Tests

Value

Pearson Chi-Square

.a

N of Valid Cases

15

No statistics are computed because cas is a constant.

## Symmetric Measures

Value

Nominal by Nominal

Phi

.a

N of Valid Cases

15

No statistics are computed because cas is a constant.

The analysis from the above tables illustrates that information on use of CAS cannot be assumed whether or not it is related to public sector recognized on SEM.

## 4.6 TURNOVER

FIGURE 5(a) shows that when annual sales turnover in preceding financial year is less than Rs 30 millions, only 20% of private sectors use it. Also, this gives a result of 12.5% use of CAS. However, when annual sales turnover in preceding financial year is more than Rs 30 millions, 80% of private sectors apply it. Thus, it provides an outcome of 87.5% use of CAS.

## FIGURE 5(a) - Turnover and CAS in Private

On the other hand, FIGURE 5(b) demonstrates that when annual sales turnover in preceding financial year is less than Rs 30 millions, 0% of public sectors use it. Subsequently, there is no CAS. Nevertheless, when annual sales turnover in preceding financial year is more than Rs 30 millions, 100% of public sector used it and as a result of 100% use of CAS.

## Hypothesis:

Ho: There is no relationship between the annual Turnover and CAS.

H1: CAS depends on the annual Turnover.

## Chi-Square Tests

Value

Pearson Chi-Square

.a

N of Valid Cases

40

No statistics are computed because cas is a constant.

## Symmetric Measures

Value

Nominal by Nominal

Phi

.a

N of Valid Cases

40

No statistics are computed because cas is a constant.

The hypothesis from the Chi-Square Tests and Symmetric Measures above again indicate that it cannot suggest if there is a relationship between Turnover and use of CAS, as CAS is a constant. Hence, at this stage of analysis, it can only be concluded about the level of percentages use of CAS in private and public companies where their Turnover is below and above RS 30 millions.

## 4.7 SOFTWARE USED BY PRIVATE AND PUBLIC COMPANIES

It has been observed that wide-ranging software used in a computerized accounting system differs from Private and Public sectors. This is possibly for the reason that businesses would prefer software by bearing in mind its long term costs and benefits. Information about the variety of software used in a CAS of private and public sectors can be seen from the following diagram:

## 4.7.1 MICROSOFT ACCESS

The above FIGURE 6(a) and FIGURE 6(b) indicate that private companies use MS Access fully (100%) in the field of accounting, and in public companies (86.7%) apply it in order to store information about the debtors, creditors and stocks.

## 4.7.2 MICROSOFT EXCEL AND MICROSOFT WORD

However, MS Word and MS Excel are totally employed in both sectors. This is perhaps because these are two basic tools which are essential for accounting works and easy to learn compared to other accounting software packages.

## 4.7.3 ACCOUNTING PACKAGE

Accounting package is entirely used in private companies compared to public companies which are only (66.7%). This is possibly because private firms are more competitive than public firms, thus adopting such accounting package.

## 4.8 ACCOUNTING PACKAGES USED

FIGURE 7 below supports with evidence the use of accounting packages adopted in both private and public companies. It shows that out of 35 questionnaires, 10 used Oracle and Pastel in private sector compared to public sector where none employed these accounting packages. Moreover, QuickBooks vary from 5 in private sector to 3 in public sector. However, Sage is not utilized in private firm but in public firm it consists of 2 responses. In addition, Scala also is not employed in private organizations, except in public one where it has only 1 utility. Nevertheless, public company makes use of 4 Tailor-made software contrasted to private one where it is not exercised. The fact that it can be understood that this software is expensive for private firms to purchase or simply the structure of their accounting systems do not necessitate these kinds of accounting packages.

## 4.9 FACTORS INFLUENCE CAS

There are some factors below which demonstrate how management's decisions to use CAS are being influenced.

## 4.9.1 COMPETITION

Ives & Learmonth (1984) and Link & Bozeman (1991) quoted in Thong (1999) confirmed that it is usually assumed that competition will enhance the possibility of CAS adoption. FIGURE 8(a) below shows that this analysis is consistent as 100% strongly agree in private companies, while in public companies 86.7% strongly agree and 13.3% simply agree that competition has forced them to implement CAS.

## 4.9.2 INNOVATION

Kirton (1976) quoted in Thong (1999), suggests that there is not anything that other associates of the business can do to use computers for accounting works if the owner-manager has not the willpower to innovate. Therefore, this has proved rightly as there is 100% strongly agree in private companies. However, there is a slight difference in public companies where 86.7% strongly agree and 13.3% agree.

## 4.9.3 ABILITY TO USE CAS

Delone (1988) and Raymond (1988) state that small businesses' owners or managers who have commenced computer training and possess computer self-efficacy are more liable to implement IT. The analysis is reliable in FIGURE 8(c), as 100% strongly agree in private sector compared to public sector where 66.7% strongly agree and 33.3% agree. Hence, this shows that IT skills are a vital factor influencing companies' decisions to use CAS.

## 4.9.4 EXTERNAL AGENTS' ADVICE

Wenzler (1996) suggests that external agents have influenced small businesses for implementing IT. This analysis is true as FIGURE 8 (d) illustrates that 40% agree in private sector and 60% neither agree nor disagree. However, there is 100% external agent's advice which influences the adoption of CAS in public sector.

## 4.9.5 EXTERNAL ACCOUNTANT'S ADVICE

Davis (1997) noted that small and medium businesses depend a lot on accounting firms as their most faithful business advisors. FIGURE 8 (e) shows the study is consistent as private sector 32% agree and 68% neither agree nor disagree. However, it is noticed by public sector that 100% neither agree nor disagree with the analysis that external accountant's advice influence CAS.

## 4.9.6 SAVE TIME AND MONEY

Head (2000) confirmed that small business cries poor when it comes to buying computers as it seems to be costly. However, FIGURE 8 (f) does not support this view. In fact, it shows that 100% strongly agree in private sectors and 93.3% in public sectors as well as 6.7% just agree. In addition, this also applies to Proudlock et al (1999) research who said that businesses owners lack of time to locate and acquire particular accounting software that satisfy their business necessities. This analysis has proven to be wrong in the diagram below.

## 4.9.7 INFORMATION INTENSITY

Porter and Millar (1985) have reported that greater uses of IT in businesses are due to greater information intensity. FIGURE 8(g) maintains this outlook as it indicates that 100% strongly agree in private sectors and 53.3% strongly agree in public sectors while the differences 46.7% simply agree. Thus, it can be noticed that information intensity is a crucial factor for both sectors to implement CAS.

## 4.9.8 BUSINESS SIZE

Alpar and Reeves (1990) quoted in Thong (1999) suggested that even among small businesses, the larger the business, the more able it is to employ CAS to avoid increasing paperwork. This analysis is consistent in FIGURE 8 (h) which points out that 100% strongly agree in private companies while 100% simply agree in public companies. Hence, it can be deduced that business size is an essential factor to influence the decision of managers to use CAS.

## 4.10 TRAINING

IT Training is analyzed in the private and public sectors and to consider whether it was free or not.

## 4.10.1 PRIVATE SECTOR

FIGURE 9 (a) below shows that Training given to adopt CAS in private sector is 60% free of charge and the difference 40% is payable.

## 4.10.2 PUBLIC SECTOR

FIGURE 9 (b) below shows that Training given to adopt CAS in public sector is 100% freely.

## FIGURE 9 (b) - Public Sector and Training

Hence, it can be concluded that in both private and public sectors, training is being given mostly free of charge. This is maybe because companies want to motivate their employees to be more competent to use CAS.

## 4.11 FACTORS FOR NOT USING CAS

There are some factors that put off the use of CAS in the private and public sectors. The reasons for not using software to prepare accounting records are acknowledged as follows:

Favor Manual System Paperwork

Lack of Computer Literacy

Lack of Training

Software is Expensive

Lack of Time to search for software

Lack of Financial Resources

Outsourcing

However, from the findings of this study, none of the private and public companies has opted for the manual system, which means they all have favoured the computerized accounting system. In addition, a fundamental fact about the analysis has proved that there were no companies which disagree or strongly disagree about the factors influencing the decision to adopt computer software. Thus, this shows that despite some of the shortcomings of computerized accounting system, none chooses the manual system.

Nevertheless, despite companies employ CAS, the manual accounting system is still present. This is so perhaps because no one can be 100% confident about the reliability of the modern technology. In the future, such a technology can be risky and have a drastic effect on businesses where some organizations will prefer to use the manual system for their survival. Hence, it can be concluded that the manual accounting system remains an alternative option in case of breakdown of computerized accounting system.

## 4.12 LIMITATION OF THE STUDY

The major constraint of this research is that no chance is available to acquire an insightful interview with a chosen group of organizations that employed CAS effectively. The respondents of those firms are unreachable as they lack time and are overloaded with intra-firm activities. In addition, they are reluctant to disclose confidential information concerning their businesses which is necessary for the study. Furthermore, there are barely 37.5% public sectors' responses contrasted to 62.5% private sectors' responses. Therefore, this shows that it is not a representative sample. Consequently, it should be noted that this might have an effect on the SPSS data where analysis between private and public sectors were put side by side and as such this fails to reflect an appropriate picture of the results obtained.