Table 1 Target Population Sample Size The target population of this study were chief accounting staff in small and medium business firms operating within NCBD that were registered with KRA. The study population comprised of a total of 782 chief accounting staff from 782 SMEs registered with Kenya Revenue Authority. NCBD was chosen because of its convenience to the researcher and it is also a lucrative business town. The SMEs were categorized as service providers, manufacturing enterprises and merchandisers. The target population was stratified as below: and merchandisers. The target population was stratified as below: Figure 2: Nature of Business Age of Business The findings shows that majority(62%) of the SMEs have been in existence for between 6 to 10 Source of User Knowledge Table 3 Effects of User Training ETR Maintenance Financial Constraint of SMEs and Utilization of ETR Machines Majority of the respondents agreed that there is additional cost in ETR compliance. Among the Table 4 Financial benefits of ETR machines Tax laws Table 5 Effects of Using ETRs in VAT processing in SMEs From the table below, majority (49%) of the respondents agreed that ETR has resulted to easy and fast VAT Processing leading to less risk of prosecution (4.622 mean score), 36% agreed that ETRs have led to reduced cost in tax filing and submitting returns (4.523 mean score), 338% of the respondents agreed that preparation of returns using ETR is fast and efficient (4.447 mean score), according to 42% of the respondents ETR has increased efficiency in sales audit (4.201 mean score), 29% of respondents agreed that ETRs have led to timely preparation of report (4.005 mean score), 35% of the respondents neither agreed nor disagreed on whether ETRs have led to timely preparation of reports (8.000 mean score), majority (45%) of the respondents disagreed that ETR is a waste of funds and has not assisted the business in any VAIQVI respondents disagreed that ETR is a waste of funds and has not assisted the business in any Table 6 Correlation between variables The above table gives the relationship between different sets of variables. The first variable raining in relation to utilization of ETR machine, the finding shows a strong positive correlatior etween training and utilization of ETRs machines as shown by 0.821. There was a positiv elationship between financial constraint and utilization of ETR machines as illustrated by 0.625 here is a positive relationship between tax laws enforcement and utilization of ETR machine: among small has the correlation coefficient 0.635. Similarly perception of tax also had a stron ositive correlation with utilization of ETR machine in small and medium enterprises. Ine uses inferential statistics to try to infer from the sample data what the population might hink or to make judgments of the probability that an observed difference between groups is a Jependable one or one that might have happened by chance in this study. Thus researcher ised inferential statistics to make inferences from the data to more general conditions. The study used factor analysis and correlation of variables using the Pearson correlation analysis to Jetermine the relationship between the variables.
