Content Validity

A committee approach for establishing content validity was not used for this research. However, a pilot study was conducted and the opinions of pilot study respondents were gathered regarding the relevance, practicality and validity of the survey.

142 The pilot study involved pre-testing the survey and conducting face-to-face interviews with selected owners/managers of SMEs in Saudi Arabia. A total of 15 owners/managers from diverse economic sectors were engaged in the pilot study. The feedback from participants was mostly positive and included a reduction in the length of the survey and the inclusion of more closed-ended questions to substantiate the open-ended ones. This reduced the average length of time needed to complete the survey, while reducing the ambiguity of some questions.

The feedback obtained from participants in the pilot study was addressed by reducing the length of the survey from 12 to 8 pages and by redesigning it to include more open-ended questions. In addition, some of the questions were re-phrased to reduce their ambiguity.

A certified translation officer translated the survey questions into Arabic. This was done to ensure accurate translation especially of technical terminologies. Copies of the survey in the two languages are provided in Appendix 1.

The contents of the survey were validated through a statistical reliability analysis and an exploratory factor analysis (EFA). As these tests can only be carried out after conducting the survey, they are confirmatory in nature. There are two scales in the survey, namely the attitude to business plan scale (Question 17) and obstacles to growth of business scale (Question 23).

5.11.1.1 Reliability Analysis

To validate consistency, reliability tests were carried out on the scale items using Cronbach’s alpha as a measure. A Cronbach’s alpha value of 0.7 or above is considered reliable, indicating that the sets of items were internally consistent in measuring the intent of each factor.

The reliability coefficient for the attitudes to business plan scale was found to be 0.72 (n=6); and the reliability coefficient for the obstacles to growth of business scale was found to be 0.89

143 (n=22). As both these values are greater than 0.7, the items in the scales were deemed fit (reliable) to be used in the analysis.

5.11.1.2 Exploratory Factor Analysis

EFA was performed on the six items from the attitude to business plan scale and the 22 items from the obstacles to business growth scale. The aim was to discover if the variables could be explained in terms of a smaller number of inter-correlated variables, called factors. Here, each factor could measure a different aspect of attitude to business plan or obstacles to business growth. The solution to EFA depends on the sample size, the number of variables and the structure of the correlation matrix. Less than 100 cases is a small sample for EFA and unlikely to produce a meaningful solution. A sample of 100–200 is considered fair, whereas 200 or more, as used in this study (270), is likely to produce a meaningful solution (Hair et al. 2010).

This study aims to explore the structure of the dimensions indicated using principle factor analysis (PFA) by inter-correlations between the questionnaire items.

The dimensional structure of the six items used to record the attitudes of the survey respondents towards a business plan was extracted from the pattern matrix using principal axis factoring which assumes that all items measured attitudes of survey respondents on various aspects of a business plan in the same logical direction, and that the factors would be inter-correlated. As Table 5.1 shows, a solution with two factors—each with Eigenvalues >1—was extracted, which explains 62.14 per cent of the variance.

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Table 5.1: Structure of the Attitudes to Business Plan Scale Extracted from the Pattern Matrix by Principal Axis Factoring with Direct Oblimin Rotation and Kaiser

Normalisation (n=270)

Loadings from the pattern matrix Factor 1 Factor 2

Per cent variance explained by each factor (%) 43.32 18.82

Cumulative percentage 43.32 62.14

Eigenvalues 2.599 1.129

Item FACTOR 1: Positive attitudes towards a business plan

1 Gives clear vision for the future of the business 0.596 –0.310

2 Useful to obtain finance 0.753 0.041

5 Useful to determine demand for product and customer needs 0.591 –0.273 6 Reduces manager decision-making power and ensures

commitment at the top level 0.814 0.183

FACTOR 2: Negative attitudes towards a business plan

3 Takes time to prepare and costs money 0.046 –0.839

4 Can’t be prepared while the business is running –0.044 –0.881

The dimensional structure of the 22 items used to collect the views of the survey respondents about obstacles to business growth was extracted as per the attitudes to business plan items. As shown in Table 5.2, a solution with five factors—each with Eigenvalues >1—was extracted, explaining 62.73 per cent of the variance.

The results of the EFA indicated that the items included in the survey were valid, non-repetitive and representative of the various aspects of attitudes to a business plan or obstacles to business growth being measured. The factor analysis of the attitudes to business plan scale indicated that this scale measured the positive and negative attitudes of the respondents about a business plan. In addition, a factor analysis of the obstacles to business growth scale indicated that this scale measured obstacles related to legal and compliance factors, market factors, business owner/manager demographics, employee quality and technology and government factors. The results of the factor analysis were consistent with the intent of what these scales were designed to measure. Therefore, the EFA confirmed the validity of the items used in the two scales.

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Table 5.2: Structure of the Obstacles to Business Growth Scale Extracted from the Pattern Matrix by Principal Axis Factoring with Direct Oblimin Rotation and Kaiser

Normalisation (n=270)

Loadings from the pattern matrix

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Per cent variance explained by each factor

(%) 33.73 10.19 7.22 6.74 4.86

Cumulative percentage 33.73 43.92 51.14 57.87 62.73

Eigenvalues 7.421 2.241 1.588 1.482 1.069

Item FACTOR 1: Legal and compliance factors

7 Availability of capital –0.694 0.127 0.135 0.438 –0.262 11 Chamber of commercial services 0.523 0.003 0.172 0.186 –0.328

14 Legal issues 0.546 0.073 0.043 0.203 –0.407

16 Advisory services 0.540 0.121 –0.066 0.301 –0.317

17 Training 0.578 0.297 0.079 0.211 –0.003

18 Product and services quality 0.447 0.347 0.119 0.211 –0.132 FACTOR 2: Market factors

1 Sales and marketing –0.065 0.540 –0.128 0.107 0.443

20 Competitors 0.097 0.793 0.149 –0.076 –0.056

21 Customer satisfaction 0.139 0.794 0.043 0.024 –0.050

22 Government regulations (labour) –0.079 0.678 –0.060 –0.070 –0.258

FACTOR 3: Business owner demographics

2 Gender –0.066 0.108 0.879 –0.190 0.054

3 Age of owner 0.038 –0.041 0.819 0.188 0.052

FACTOR 4: Employee quality and technology

4 Education level 0.381 –0.116 0.034 0.619 0.033

5 Management skills –0.123 –0.024 –0.155 0.885 0.076

6 Work experience 0.053 0.047 0.019 0.808 0.076

8 Technology 0.184 –0.087 0.271 0.481 –0.187

9 High cost of labour 0.162 –0.041 0.223 0.518 –0.267

10 Availability of skilled employees –0.083 0.192 0.110 0.477 –0.196

FACTOR 5: Government factors

12 Government bureaucracy 0.037 0.314 –0.385 0.021 –0.494

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15 Government support 0.257 0.123 0.056 0.014 –0.589

19 Financial support –0.134 0.356 0.247 0.097 –0.478

5.12 SUMMARY

This chapter has highlighted the importance of the research methodology and the research design applied in this study. A number of studies of SMEs were reviewed in order to select the most appropriate methods to be used for this study. Accordingly, the mixed methods (quantitative and qualitative) approach was selected for collecting the necessary primary data: questionnaire and interviews. The survey-based research method was conducted with the owners and managers of SMEs through online and face-to-face surveys in order to achieve an adequate response rate. Interviews formed the primary source of data from the financial institutions in order to study the constraints on financing the SME sector from a Saudi financial provider’s perspective. The SPSS software, which is an integrated system of computer programs, was used for analysis of the data. Also, ANOVA was used to examine the association between various business obstacles and business financial performance (ROI, profit margin, leverage ratio, annual sales turnover, market share, and growth rate). Frequency, percentage and correlations were the initial estimates employed, and then statistical techniques were applied, including descriptive analysis, chi-square and contingency tables, hypotheses testing and correlation analysis. The following chapters will present the results of these analyses.

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QUANTITATIVE DATA PRESENTATION AND

ANALYSIS

6.1 INTRODUCTION

Previous chapters laid the foundations for this study via a discussion of the framework to be used for this research. This chapter presents the results gathered from face-to-face questionnaires and online surveys with 270 Saudi SME entrepreneurs. It tests the research hypotheses discussed in Chapter 5. The statistical analyses in this study have been divided into five sections. The first provides an overview of the survey data; the second provides detailed descriptive statistics for all the data collected through the surveys; the third tests hypotheses relating to the association between the owner/manager and business characteristics, and access to finance; the fourth tests for relationships among various factors including access to finance, SME obstacles, owner/manager and business characteristics, and SME performance through a correlation analysis approach; and the fifth validates the relationship between access to finance and SME performance via a multiple regression analysis. This is followed by concluding remarks in a summary section.