Proceedings of the 4th International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN 978-983-40482-6-6
THE RELATIONSHIP BETWEEN EXECUTIVE VISION, COMPUTERISED ACCOUNTING INFORMATION SYSTEM CAPABILITY, EMPLOYEE IT SKILLS AND FIRM PERFORMANCE 1
2
3
Mohamad Azmi Nias Ahmad , Malcolm Smith , Zubaidah Ismail and 4 Mohd Saiyidi Mokhtar Mat Roni 1
Faculty of Accountancy and Law, University Teknologi MARA (UiTM), Pahang, Malaysia
[email protected] 2 Faculty of Business and Law, Edith Cowan University, Joondalup, Western Australia
[email protected] 3 Faculty of Business and Law, Edith Cowan University, Joondalup, Western Australia
[email protected] 4 Faculty of Accountancy, University Teknologi MARA (UiTM), Melaka, Malaysia
[email protected]
ABSTRACT This study uses a resource-based view (RBV) to explain firm performance of 192 small and medium enterprises (SMEs) in Malaysia. Three explanatory variables are examined: Executive vision (EV) at the business and strategic level, computerised accounting information systems (CAIS) capability at the organizational level and employee IT skills (EITS) at the individual level. The study tests for the direct relationships of each of these variables to firm performance. Three aspects of firm performance measures firm efficiency and effectiveness, acceptance by customers and quality of decision made. A survey method was used to collect data and hierarchical regression analysis is used to test this relationship. Results show positive impacts of EV and CAIS, respectively on firm performance while EITS appear to have no effect in firm performance for the firms sampled.
Keywords: Computerised Accounting Information Systems, Employee IT Skills, Executive Vision, Firm Performance, Small and Medium Enterprises, INTRODUCTION SMEs form a significant segment in most countries’ economy. What drives performance in SMEs has been largely investigated (Athanassiou, Crittenden, Kelly, & Marquez, 2002; Bharadwaj, 2000; Cragg, King, & Hussin, 2002; Kim, Shin, Kim, & Lee, 2011). In Malaysia, in particular the importance of ICT as a pre-requisite for competiveness has been highlighted to the extent that the government has willingly provided financial assistance to SMEs in this regards. A data processing system is needed to process raw data into understandable information for decision-making. Financial reports produced by computerized accounting information system (CAIS) assists decision makers of small and medium enterprises (SMEs) to make routine or non-routine decisions (Levy & Powell, 1998). A firm that is capable of optimising its information usage can have a competitive edge over competitors in the industry. However, many benefits of CAIS do not seem to be attractive to some SMEs. The notion stems from various factors. Notably, there is no proper planning or vision among managers resulting in CAIS being considered as a lavish item instead of an indispensable planning and control tool. Limited employee expertise could explain why SMEs are also unable to correctly align their accounting information system (AIS) needs with firm-wide requirements. And
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN finally, SME employees are lacking inappropriate IT skills to allow for the adoption of comprehensive CAIS. Resource-based view (RBV) theory is used in this study to map how three elements impact on firm performance. This includes executive vision at business & strategic level, CAIS capability at organizational level and employee IT skills at individual level. The findings of this study will contribute to the body of literature on AIS and SMEs and encourage among SMEs to consider carefully and plan for their CAIS, to incorporate long-term goals and ensure that all components of CAIS are in place for both firm efficiency and effectiveness.
THEORETICAL BACKGROUND The resource based theory (RBV) has received increase attention in recent years among AIS researchers. RBV was first introduced by Penrose’s (1995) publication entitled ‘The theory of the growth of the firm’. She mentioned that most firms utilised a combination of various resources in order to operate successfully. According to (Barney, 1991), these resources are said to be ‘valuable, rare, imperfectly imitable, and non-substitutable’. When all these are in place, it is presumable that the firm will have continuous competitive advantage as long as it remain distinguishable from competitors (Serra & Ferreira, 2010). Recently, many studies have adopted RBV to explain the relationship between IT and firm performance (Barney, 1991; Bharadwaj, 2000; Kim et al., 2011; Powell & Dent-Micallef, 1997). This study examines three levels of resources on firm performance: EV at the business and strategic level, CAIS capability at the organizational level and EITS at the individual level. EV is related to how well those resources are managed and optimised by the top management, capability is refers to how SMEs manage their resources such as CAIS capability, and skills are associated with employee’s IT skills as depicted in figure 1. Figure 1: Conceptual framework Executive vision CAIS capability
H1 H2
Firm performance
H3 Employee IT skill
LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT The importance of CAIS as a business tool has been highlighted in much of the literature. Many have begun to see significant relationship between IT/IS/CAIS success and firm performance (Bharadwaj, 2000; Kim et al., 2011). SMEs purchase accounting software to fulfil its reporting needs although some view it as a costly investment (Cragg et al., 2002), while some firm make ad hoc decision on CAIS to manage its reporting and monitoring (Ismail & King, 2005). In more recent study, however, it was reported that SMEs have made full use of the CAIS output and incorporated it into the organization’s long-term plans (Al-
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN Qudah, 2011). CAIS in most SMEs is generic and mostly off-the-shelf applications, although some are programmable to suit differing and unique operations of firms. EV reflects top management belief and confidence in the usefulness of ICT/CAIS (Teo & Ranganathan, 2003; Ussahawanitchakit & Yeunyong, 2009). According to Ussahawanitchakit and Yeunyong (2009), if executives are confident that CAIS is a useful tool, it will translate into action plan towards achieving organizational goals. Several studies confirmed that executive vision is associated with firm performance (Athanassiou et al., 2002; Jayaraman, Khorana, Nelling, & Covin, 2000; Lee & Peterson, 2000). Therefore, the following hypothesis is developed: H1: There is a positive relationship between executive vision and firm performance CAIS refers to the collection, classification and processing of raw transactions to produce meaningful and readable financial reports to users. The integration, speed, accuracy, automatic document production and back-up capability will improve SMEs' strategic decision making. CAIS capability is also affected by other firm-specific elements such as the use of AIS as a control mechanism and general IT internal control weaknesses of a firm. In so far as there is system fit (Abernethy & Guthrie, 1994) and alignment of system to goals (Ismail & King, 2005) CAIS has a positive impact on firm performance. Therefore, the following hypothesis is proposed: H2: There is a positive relationship between CAIS capability and firm performance In this study, employee skills refer to skills relating to how competent employees perform tasks in CAIS (Kahn, 2007). Greenstein and McKee (2004) stated that employee's IT knowledge if combined with appropriate IS/IT capability can maximize CAIS success. This in turn, promotes accounting system output to be more accurate, fast and relevant (Ussahawanitchakit & Yeunyong, 2009). Therefore, the following hypothesis is proposed: H3: There is a positive relationship between employee IT skills and firm performance
RESEARCH METHODOLOGY The study used a survey approach. The survey instrument was pilot tested on 42 middle managers. Minor modifications were made based on several comments regarding how the questions were structured. The questionnaires were then sent to a sample of 1000 SMEs in Malaysia. The subjects were randomly selected from the SME Corp website. There were 201 respondents. Nine were excluded from analysis because they were incomplete. The response rate was 19.2%. This is quite low but is considered common for mail survey (Dillman, 2000). The instrument has forty three items which measured of both dependent and independent variables. The dependent variable in this study is firm performance. This study emphasized non-financial indicators of firm performance. Firm performance is measured by 8 items about firm's efficiency and effectiveness, acceptance by the customers and quality of decisions. These items are adopted from Kim, Shin, Kim and Lee (2011), Ravarini (2010), Ussahawanitchakit & Yeunyong (2009), Cragg, King and Hussin (2002) and Powell and Dent-Micallef (1997). Respondents were asked to indicate their belief of the effects of CAIS on the firm's performance in the past two years. A five-point Likert scale is used.
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN
Independent variables consisted of executive vision, CAIS capability and employee IT skills. Executive vision is measured by 5 items. Following Ussahawanitchakit and Yeunyong (2009), executive vision is measured in terms of its inspiring, optimizing and belief in computerized AIS (both software and hardware). Respondents were asked their perception and responses on top management's visions in providing adequate capital, human resource, IT/IS infrastructure, training and system security. For CAIS capability , the measure was adopted from Ismail and King's (2005) nineteen AIS capacity items. CAIS capability was measured with respect to precision of information, information content, provide adequacy of reports and provision of sufficient information. For Employee IT skills, it was measured by a 13 items scale that has four measurement factors (Chui Young, Young Ju, Soon Suk, Ji Chul, & Seung Kweon, 2010). The four factors are IT perception, IT knowledge, IT operation and IT endeavour. Chui Young, Young Ju, Soon Suk, Ji Chul, and Seung Kweon (2010), based their 13 items scale on previous literature and performed a validity and reliability test. RESULTS The population of the study is SMEs listed on the SME Corp website. From this sampling frame, 300 SMEs were selected using simple random sampling techniques. The questionnaires were mailed and 192 were returned and uses for analysis. Of those who completed the survey, 55 percent were in service, 29 percent manufacturing and 16 percent agriculture industry. Respondents’ job function were predominantly accounting (62%), followed by Information Management/Technology (22%) and others (16%). About 70 percent of the sample is middle manager and 30 percent are top management who had been in the firms for below 3 years (51%), between 3 to 5 years (32%) and over 5 years (17%) Prior to conducting any formal statistical analyses, preliminary steps were taken to ensure the quality of data (Sekaran, 2003). Firstly, inspection of missing data was conducted. Hair (2006) suggested four step process to identify missing data. Step one is to determine the type of missing data. It was found that the missing data was not caused by the research design but it was due to ignorable missing data. Step two is to determine the extent of missing data. The statistics showed that each variable have missing values of 0.5%. Therefore the extent of missing data is not substantial enough to warrant any action. According to Hair (2006), less than 10% of individual case of missing data can be ignored. Step three is to diagnose the randomness of the missing data. It was examined using missing value analysis (MVA). The purpose of using MVA is to detect any possible systematic missing data. Little’s missing completely at random (MCAR) was used to observe whether the missing value is at random way. MCAR outcome is required because it allows researcher to remedy it using imputation methods. The H0 was established where the data is said to be missing completely at random. The test showed that, Little’s MCAR is not significant (p = 0.710). Therefore, we fail to reject H0. The final step is to select the imputation method. This study is using expectation maximum (EM) imputations technique because it predicts the best value for the missing data and determines the most likelihood values. Secondly, construct reliability test using Cronbach’s Alpha was conducted using SPSS version 20. The purpose of this test is to assess the internal consistency reliability of the instrument used. The outcome of the test is presented in Table 1. The results clearly shows that the Cronbach’s Coefficient Alpha values for the four constructs are above 0.7 which is
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN considered as acceptable, hence the instrument is appropriate for use in this study (Field, 2009; Hair, 2006; Nunnally, 1978; Sekaran, 2003; Smith, 2011) Thirdly, the test of normality was performed. Although Kolmogorov-Smirnov statistics indicated that all variables were significant hence non-normal, test of normality is sensitive and “often signal departures from normality that do not really matter (p.46)” (Tabachnick & Fidell, 2007). To make sure, that the data is approximately normal, we identified outliers using boxplot. Windsoring technique was later used to correct the outliers. Skewness and kurtosis statistics showed that the z-scores of the variables were within +/-1.96 suggesting approximate normal distribution. This was later confirmed through visual indicator of histogram and normal Q-Q plot. Finally, to test the validity of the instrument, the 43 items in the questionnaire were subjected to principal axis factoring with varimax rotation to demonstrate validity of the research tool. According to Nunnally (1978), varimax rotation is suitable since it minimizes the ‘correlation across factors and maximizes within factors in order to yield ‘clear’ factors. He suggested that factor with loading higher than 0.50 for further analysis. However, factor loading higher than 0.40 is considered sufficient to be retained (Gorsuch, 1974). The analysis result showed that the KMO value was 0.872 suggesting that the data was suitable for factor analysis. Factor loading for each construct had values of greater than .50 and items loaded onto the same components. Table 1: Reliability and validity of variables understudy Number of Cronbach’s Construct items Alpha Executive vision 5 .741 CAIS capability 17 .891 Employee IT skills 13 .905 Firm performance 8 .801 Total 43 .918
Factor loading .53-.72 .42-.77 .47-.77 .67-.76
To test for the impact of executive vision, CAIS capability and employee IT skills on firm performance, a hierarchical multiple regression analysis (MRA) was used. Before interpreting the results of the MRA, several assumptions were tested, and checked. First, stem-and-leaf plots and boxplots indicated that each variable in the regression was normally distributed and free from univariate outliers. Second, an inspection of the normal probability plot of standardized residuals and the scatterplot of standardized residuals against standardized predicted values indicated that the assumptions of normality, linearity and homoscedasticity of residuals were met. Third, Mahalanobis distance, as in table 2, did not exceed the critical χ2 for df = 3 (at α = .001) of 16.27 for any case in the dataset, indicating that multivariate outliers were not of a concern. Finally, relatively high tolerances for all three predictors in the final regression model were found, indicating that multicollinearity would not interfere with our ability to interpret the outcome of the MRA. Table 2 Residuals Statistics
Mahalanobis Distance Cook's Distance Centered Leverage Value
Min
Max
Mean
Std. Deviation
N
.069 .000 .000
14.27 .090 .075
2.984 .007 .016
2.827 .015 .015
192 192 192
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN It was found that executive vision accounted for a significant 12.5% of the variance in impact to firm performance with R2 = .125, F (1, 190)=27.14, p < .001. CAIS was added to the regression equation, and accounted for an additional of 4.6% in the variance with ΔR2 = .047, ΔF (1, 189) = 10.611, p = .001. Finally, employee IT skills was entered into the MRA model resulting in a non-significant additional 2% in the variation, ΔR2 = .001, ΔF (1, 189) = .291, p = .950. In combination, executive vision, CAIS capability and employee IT skills explained 17.3% of the firm performance with R2 = .173, F (1, 188) =.291, p < .001. Cohen’s f2 was later computed showing a result of f2 = .209. According to Cohen (1988), the combined effect of this value can be considered as medium. Table 3 Unstandardized (B) and standardized (β) regression coefficients, and Squared SemiPartial Correlations (sr2) for each predictor variable on each step of a hierarchical multiple regression predicting the impact executive vision, CAIS capability and employee IT skills on firm performance (N = 192) Variable R R2 B [95% CI] β sr2 Sig F Change Step 1 Executive vision .354 .125 .362 [.225, .499] .354 .125 .000 Step 2 Executive vision CAIS capability Step 3 Executive vision CAIS capability Employee IT skills
.414
.416
.171
.293 [.152, .433] .262 [.103, .420]
.286 .226
.074 .047
.001
.173
.292 [.151, .432] .247 [.079, .415] .037 [-.098, .171]
.285 .213 .038
.074 .037 .001
.590
Note. C1 = confidence interval
The results above indicated that the study supported H1 and H2, that EV and CAIS affect performance positively and H3 was rejected showing that EITS had no effect. DISCUSSION AND CONCLUSION The results of this study clearly suggest that the attributes of AIS success i.e. executive vision and computerised accounting information systems (CAIS) capability are essential to firm performance. This is consistent with the resource based view which states that information can create competitive advantage for the firm and increases firm performance. According to Barney (1991), resources that are considered to be ‘valuable, rare, imperfectly imitable, and non-substitutable’ could be the winning formula for SMEs. This finding provides empirical evidence that executive vision in terms of top management’s involvement in providing capital, human resource, infrastructure, training and security, is essential to produce a quality information system. In addition, the use of CAIS will expedite the process of collecting, classification and processing of raw transactional data to produce meaningful and readable financial and non-financial information for the decision makers to increase in firm performance. However, the finding suggest that employee IT skills is not critical. This may be because CAIS has become user-friendlier and basic computing skill is
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Proceedings of International Conference on Public Policy and Social Science, UiTM Sabah Malaysia, December 2013 ISBN sufficient to accomplish data entry process and basic information retrieval. As CAIS in most SMEs is generic, employees require little training for them to get accustomed to the system. In terms of limitations, the study examines three predictor variables, with an exclusion of other contributing variables such as IS/IT capability and managerial IT skills. The study also looks at only direct relationship between each variable to firm performance but not how they interact with each other. Corporate governance and strategic decision making are two additional predictors that warrant further inspection. Therefore, future study shall look at this context to find how they interact and affect firm performance. Next, the usual limitations associated with mail survey such as response bias and non-response bias is not discussed in this study although these issues were adequately addressed methodologically. Finally, the sample of the study falls within the perimeters of the list available on SME Corp website. There are other SMEs scattered around the country, which are not listed with SME Corp in Malaysia.
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