The Contribution of Security, Trust, and Ease of Use to Customers Satisfaction - Essay Example

Table of Contents List of Tables and Figures 2 Introduction 3 Objectives 3 The Sample 4 The Sampling Technique 4 Sample Size 4 Descriptive Statisticsof the Variables 6 Normality Tests 11 Reliability Test for Total Customer Satisfaction 15 Hypothesis Testing 16 Correlations 18 References 23 Appendix 24 List of Tables and Figures Table 1 Sex Distribution of the Population 4 Table 2 Total Customer Satisfaction 5 Figure 3 Histogram of Total Customer Satisfaction 6 Table 4 Sex 6 Table 5 Marital Status 6 Table 6 Highest Education Completed 7 Table 7 Age Statistics 7 Figure 8 Age 8 Table 9 Descriptive Statistics 8 Figure 10 Total Online Features 8 Figure 11 Total Ease of Use 9 Figure 12 Total Trust 9 Figure 13 Total Security 10 Figure 14 Total Aesthetics 11 Table 15 Tests of Normality 11 Table 16 Reliability Analysis 15 Table 17 ANOVA Table 16 Table 18 Coefficients (a) 16 Table 19 Independent Samples Test-sex and customer satisfaction 17 Table 20 Total Customer Satisfaction by Marital Status 17 Table 21 Total Customer Satisfaction by Age 17 Table 22 Correlations of customer satisfaction and online features 18 Table 23 Correlations of customer satisfaction and Ease of use 19 Table 24 Correlations of customer satisfaction and Trust 19 Table 25 Correlations of customer satisfaction and Security 20 Table 26 Correlations of customer satisfaction and Aesthetics 21 Introduction Marketing is about continuity in meeting the needs of your customers while at the same time getting value in return (Clement, C et al. 1999). According to David, K. H (1998), analyzing a market involves understanding the various groups of customers who exist, their needs, your preferred customers, the products/services which you have and which are aimed at meeting their needs, their preferences, what competitors have and how they market their products and services, pricing criteria and how the products and services will be distributed to the targeted customers. According to McNamara, C (2008), marketing analysis is carried out by an organization or business venture in order to gauge the market niche. To Hunt, N & Tyrrell S (2004), marketing is all about advertising the products one has, enhancing public relations and efficient customer service. Effective marketing of products generally depends on many aspects ranging from security, trust, usability of the product, its appearance and its ability to satisfy customer requirements. The kind of business one is doing does not matter, the first thing to consider is the nature of products and services which you plan to offer your targeted customers and the best way to market it to them (Field, A 2009). Each and every business needs a marketing plan which is reliable and attainable. Customer trust is built through; Entire research and comparisons of your products with those of your competitors; Ensuring that the products are up to standards so that customers can recommend others; Warranties and security policies while purchasing products assures customers. This is mainly to raise the customer trust which ensures continuity (Torgersen, E 2009). Products need to be test-retested to ensure security of the consumers. Side effects and other negative perceptions by customers drive them away (James, T.F Et al. 2001). Again, if a product is not easy to use, then continuity is impossible. According to Morris, C (2008), gender is an important aspect in marketing since some forms of marketing suits females while others are meant for males. Objectives The objectives of this study are; To critically analyze and understand the contribution of security, trust and ease of use to Customers’ satisfaction; To analyze customer satisfaction and each individual aspect of service quality; and To confirm how the females and males respond to products quality, the behaviours of the different age groups and finally the effects of marital status in customer satisfaction. In order to ascertain this, a random sample will be selected from the database given and a new one will be developed based on the selected sample. Random sampling, stratified sampling and cluster sampling are some of the methods used to sample data. Random sampling is used in case the database to be used is made up of homogenous data; data with same character traits and the elements are selected randomly from the entire database. On the other hand, stratified sampling is used when the database is heterogeneous. In this case, elements with the same character traits are put together and then a random sample is selected. The different data groups are then combined to for the stratified sample. This sampling technique will be used in this case. Lastly, cluster sampling is the technique where the data is subdivided into clusters each composed of same number of elements. Then like in stratified sampling, a random sample is collected from each cluster and then the entire data combined. Once the sample is selected and the data coded and cleaned, tables of frequencies and other descriptive statistics on gender (sex), age, marital status and educational level of the new sample will be developed. Normal test of the dependent; in this case total customer satisfaction will be carried out. The Sample The Sampling Technique Since this data is not homogenous, then stratified sampling will be used. According to Hunt, N and Tyrrell S (2004), it is advantageous than simple random sampling in that; The population is better covered than it is in other sampling techniques; Has greater scope; The results are accurate in that the data is sub-divided into non-overlapping stratas from which a random sample is collected and the results combined; Sample Size Sample size generally depends on the following factors; The size of the population; the larger the population, the larger the sample size; The bound on the error of estimation. For a good precision, then the sample size is greater (Richard, L.S et al. 2001). Table 1 Sex Distribution of the Population Frequency Percent Valid MALES 193 42.9 FEMALES 257 57.1 Total 450 100.0 The population is made up of 193 males (42.9%) and 257 females (57.1%). The strata sample size in this study was calculated using the following formula (Simar, L et al. 2007). Where Wk is the stratum weight, Sk2 is the population variance of stratum and V0 is the assumed variance. The sanple size, is 167 representing 37.1% of the total population. The individual strata sample size is calculated as below; nh = (Nh / N ) * n Given nh is the sample size for strata h, Nh is the population size for strata h while N is total population size and n is total sample size. The result is 72 (43.1%) males and 95 females (56.9%) Table 2 Total Customer Satisfaction N Valid 167 Missing 0 Mean 22.15 Std. Error of Mean .303 Median 22.00 Mode 25 Std. Deviation 3.911 Variance 15.297 Skewness -.345 Std. Error of Skewness .188 Kurtosis -.707 Std. Error of Kurtosis .374 Percentiles 25 19.00 50 22.00 75 26.00 The mean of the selected sample is 22.15 while the standard deviation is 3.911. The population mean is 22.06 while the standard deviation is 3.914. The two measures show that the sample is an un-biased representative of the whole population. The data is negatively skewed (skewness is -.345). This is evident from the figure below; Figure 3 Histogram of Total Customer Satisfaction According to Barnes, E (2006), the normal curve in figure 1 represents the distribution of the data. The mean value of the sample is represented by the highest concentration of the curves while the standard deviation is represented by the spread of the curves. Descriptive Statistics of the Variables Table 4 Sex Frequency Percent Valid MALES 72 43.1 FEMALES 95 56.9 Total 167 100.0 Males form 43.1% of the sample population while females are 56.9% (table 3) Table 5 Marital Status Frequency Percent Valid SINGLE 35 21.0 STEADY RELATIONSHIP 20 12.0 LIVING WITH PARTNER 9 5.4 MARRIED FIRST TIME 74 44.3 REMARRIED 7 4.2 SEPARATED 3 1.8 DIVORCED 16 9.6 WIDOWED 3 1.8 Total 167 100.0 Of the 167, 35 (21%) are single, 20 (12%) are in steady relationships, 9 (5.4%) have a partner, 74 (44.3%) are married, 7 (4.2%) have remarried, 3 (1.8%) have separated with their partners, 16 (9.6%) have divorced while 3 (1.8%) are windowed Table 6 Highest Education Completed Frequency Percent Valid SOME SECONDARY 22 13.2 COMPLETED HIGHSCHOOL 30 18.0 SOME ADDITIONAL TRAINING 30 18.0 COMPLETED UNDERGRADUATE 62 37.1 POSTGRADUATE COMPLETED 23 13.8 Total 167 100.0 On highest education completed, 22 (13.2%) have undergone some secondary school education, 30 (18%) have completed high school, 30 (18%) have some additional training in addition to high school training, 62 (37.1%) have an undergraduate degree while 23 (13.8%) have completed postgraduate studies. Table 7 Age Statistics N Valid 167 Missing 0 Mean 37.78 Median 37.00 Mode 22 Std. Deviation 12.652 Skewness .493 Std. Error of Skewness .188 Kurtosis -.304 Std. Error of Kurtosis .374 Percentiles 25 27.00 50 37.00 75 46.00 51 (30.5%) are 18-30 years old, 45 (26.9) have 31-40 years, 49 (29.3%) have 41-50 years while 22 (13.2%) have 51-75 years. The mean age is 37.78 years with the median being 37 and the mode 22. The data is positively skewed (skewness is .493). Figure 8 Age Table 9 Descriptive Statistics Total Customer Satisfaction Total online features Total Ease of Use Total Products Total Trust Total Security Total Aesthetics N Valid 167 167 167 167 167 167 167 Missing 0 0 0 0 0 0 0 Mean 22.15 103.20 15.68 23.07 17.81 24.27 22.37 Median 22.00 105.00 17.00 23.00 18.00 25.00 23.00 Mode 25 110 18 25 20 24 21(a) Std. Deviation 3.911 18.503 3.736 6.734 2.238 4.896 4.452 Skewness -.345 -.659 -.980 -.307 -1.087 -.763 -.362 Std. Error of Skewness .188 .188 .188 .188 .188 .188 .188 Kurtosis -.707 .413 .242 -.347 1.025 .685 -.078 Std. Error of Kurtosis .374 .374 .374 .374 .374 .374 .374 Percentiles 25 19.00 92.00 13.00 19.00 17.00 21.00 20.00 50 22.00 105.00 17.00 23.00 18.00 25.00 23.00 75 26.00 118.00 18.00 28.00 20.00 28.00 26.00 From table 7 above, the mean of total customer satisfaction is 22.15 with a standard deviation of 3.911. Total online features had a mean of 103.2 with a standard deviation of 18.503. Ease of use had a mean of 15.68 and a standard deviation of 3.74. Total trust had a mean of 17.81 and a standard deviation of 2.24 while total security had a mean of 24.27 and a standard deviation of 4.89. Figure 10 Total Online Features Figure 11 Total Ease of Use Figure 12 Total Trust Figure 13 Total Security Figure 14 Total Aesthetics Normality Tests Table 15 Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig. Total Customer Satisfaction .132 167 .000 .957 167 .000 Total Aesthetics .080 167 .010 .975 167 .004 Total Security .125 167 .000 .955 167 .000 Total Trust .164 167 .000 .867 167 .000 Total Products .066 167 .077 .981 167 .024 Total Ease of Use .165 167 .000 .897 167 .000 Total online features .072 167 .032 .970 167 .001 a Lilliefors Significance Correction According to Mailu, S (2004), if significance is less that .05 (significance level), then a variable is not normally distributed. Total customer satisfaction is not normally distributed. In addition total aesthetics, total security, total trust, total ease of use and total online features are also not normally distributed. An only total product is normally distributed. Reliability Test for Total Customer Satisfaction Table 16 Reliability Analysis Variable Cronbachs Alpha Cronbachs Alpha Based on Standardized Items N of Items Customer Satisfaction .8153 .9178 Total Security .6094 .6201 Total Trust .5197 .5788 Total Aesthetics .7113 .7151 Total ease of use .5646 .5651 From research, it is agreed that a Cronbachs Alpha coefficient of a variable which is above .70 means that the variable is reliable and cannot be deleted from the analysis; the results will be affected if the variable is removed (Weiers, R.M 2006). In this case, total aesthetics and customer satisfaction are reliable variables while the others are not. However, when considered together, the variables are reliable and valid and should all be included in the analysis. Hypothesis Testing The objective of the study was to; To critically analyze and understand the contribution of security, trust and ease of use to Customers’ satisfaction; To analyze customer satisfaction and each individual aspect of product marketing; and To confirm how the females and males respond to products quality, the behaviours of the different age groups and finally the effects of marital status in customer satisfaction. The first hypothesis formulated is; H0: The contribution of service quality attributes is not significant H1: The contribution of service quality attributes is significant Table 17 ANOVA Table Model Sum of Squares df Mean Square F Sig. 1 Regression 947.546 5 189.509 19.169 .000(a) Residual 1591.712 161 9.886 Total 2539.257 166 a Predictors: (Constant), Total Ease of Use , Total Products, Total Trust, Total Aesthetics, Total Security b Dependent Variable: Total Customer Satisfaction The contribution of service quality attributes is significant (table 10 above). The second hypothesis is; H0: Each attribute is not a significant contributor to customer satisfaction H1: Each attribute is a significant contributor to customer satisfaction Table 18 Coefficients (a) Model Standardized Coefficients t Sig. B Std. Error 1 (Constant) 8.349 2.083 4.008 .000 Total Aesthetics .371 .075 4.956 .000 Total Security -.142 .105 -1.349 .179 Total Trust .261 .145 1.797 .074 Total Products .188 .067 2.824 .005 Total Ease of Use -.003 .095 -.033 .974 a Dependent Variable: Total Customer Satisfaction From table 11 above, total aesthetics and total products are significant contributors towards customer satisfaction while total security (sig.05). Then we accept the null hypothesis that ach attribute is not a significant contributor to customer satisfaction and reject the alternative hypothesis. The third hypothesis is; H0: Females and males are equally satisfied H1: Females are more satisfied than males Table 19 Independent Samples Test-sex and customer satisfaction Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Total Customer Satisfaction Equal variances assumed 1.840 .177 .447 165 .655 .27 .613 -.936 1.484 Equal variances not assumed .454 160.644 .650 .27 .603 -.917 1.465 Table 10 shows that both males and females are equally satisfied (sig. > .05) The fourth hypothesis is; H0: The aged and the married (or ever married) are more satisfied than the young and singles; H1: There is no difference in satisfaction between the aged and the married (or ever married) the young and singles; Table 20 Total Customer Satisfaction by Marital Status Marital status Mean N Std. Deviation SINGLE 21.54 35 3.752 STEADY RELATIONSHIP 22.35 20 3.990 LIVING WITH PARTNER 21.89 9 4.137 MARRIED FIRST TIME 22.23 74 3.877 REMARRIED 21.86 7 3.976 SEPARATED 22.67 3 1.528 DIVORCED 22.56 16 5.006 WIDOWED 24.67 3 2.309 Total 22.15 167 3.911 Table 21 Total Customer Satisfaction by Age age last birthday Mean N Std. Deviation 18-30 Yrs 21.25 51 4.161 31-50 Yrs 22.38 94 3.652 51-80 Yrs 23.23 22 4.151 Total 22.15 167 3.911 From table 13 and 14 above, it is evident that the aged and the married are more satisfied than the singles and the young. We accept the null hypothesis and reject the alternative hypothesis. Correlations Table 22 Correlations of customer satisfaction and online features Total Customer Satisfaction Total online features Total Customer Satisfaction Pearson Correlation 1 .559(**) Sig. (2-tailed) . .000 N 167 167 Total online features Pearson Correlation .559(**) 1 Sig. (2-tailed) .000 . N 167 167 ** Correlation is significant at the 0.01 level (2-tailed). Customer satisfaction and online features have a positive correlation which is not strong (.559). Table 23 Correlations of customer satisfaction and Ease of use Total Customer Satisfaction Total Ease of Use Total Customer Satisfaction Pearson Correlation 1 .394(**) Sig. (2-tailed) . .000 N 167 167 Total Ease of Use Pearson Correlation .394(**) 1 Sig. (2-tailed) .000 . N 167 167 ** Correlation is significant at the 0.01 level (2-tailed). The correlation between customer satisfaction and ease of use is a weak positive relationship (.394) Table 24 Correlations of customer satisfaction and Trust Total Customer Satisfaction Total Trust Total Customer Satisfaction Pearson Correlation 1 .407(**) Sig. (2-tailed) . .000 N 167 167 Total Trust Pearson Correlation .407(**) 1 Sig. (2-tailed) .000 . N 167 167 ** Correlation is significant at the 0.01 level (2-tailed). The correlation between customer satisfaction and trust is a weak positive relationship (.407) Table 25 Correlations of customer satisfaction and Security Total Customer Satisfaction Total Security Total Customer Satisfaction Pearson Correlation 1 .449(**) Sig. (2-tailed) . .000 N 167 167 Total Security Pearson Correlation .449(**) 1 Sig. (2-tailed) .000 . N 167 167 ** Correlation is significant at the 0.01 level (2-tailed). The correlation between customer satisfaction and trust is a weak positive relationship (.449) Correlations Table 26 Correlations of customer satisfaction and Aesthetics Total Customer Satisfaction Total Aesthetics Total Customer Satisfaction Pearson Correlation 1 .557(**) Sig. (2-tailed) . .000 N 167 167 Total Aesthetics Pearson Correlation .557(**) 1 Sig. (2-tailed) .000 . N 167 167 ** Correlation is significant at the 0.01 level (2-tailed). The correlation between customer satisfaction and trust is a positive relationship which is not strong at all (.557) References Barnes, E (2006). Introduction to Analysis: What you should know. Nairobi: Government Press Clement, C et al. (1999). Introduction to the Practice of Statistics: W H Freeman & Co  David, K. H (1998). Statistical Thinking for Managers: South-Western Pub Field, A (2009). Discovering Statistics Using SPSS (Introducing Statistical Methods: UK. Cambridge University Press Hunt, N & Tyrrell S (2004). Stratified Sampling. Available online from: http://www.coventry.ac.uk/ec/~nhunt/meths/strati.html James, T.F Et al. (2001). First Course in Statistics: Thomson Learning Ken. B (2006). Outlines & Highlights for Business Statistics: Academic Internet Pub Inc   Mailu, S (2004). Normal Distributions and Non-Parametric Tests: Nairobi. General Printers McNamara, C (2008). Marketing Your Products/Services and Promoting Your Organization. Available online from: http://managementhelp.org/fp_progs/mkt_mod/market.htm Morris, C (2008). Quantitative Approaches in Business Studies: Financial Times Management  Richard, L.S et al. (2001). Mathematical Statistics with Applications: Thomson Learning Simar, L et al. (2007). Applied Multivariate Statistical Analysis: Mary Land. Springer Verlag Torgersen E (2009). Comparison of Statistical Experiments: UK. Cambridge University Press Weiers, R.M (2006). Outlines & Highlights for Introduction to Business Statistics. Academic Internet Pub Inc William, C.B et al. (2008). Multivariate Data Analysis: UK. Prentice Hall  Appendix Table 1: Total Customer Satisfaction N Valid 450 Missing 0 Mean 22.06 Std. Deviation 3.914 Skewness -.476 Std. Error of Skewness .115 Kurtosis -.203 Std. Error of Kurtosis .230 Read More