Data analysis and reporting
Assessment 3
This report has been developed at the request of senior management to understand the relationship between customer participation and service firm performance to help improve business practices. Preliminary Analysis The sample for this study is drawn from data collected from the data service industry. In total there were 1430 questionnaires distributed. Prior to conducting any analysis, the data set was cleaned to ensure the data could be used appropriately to conduct the analysis. After defining the values and unit of measurement for each individual dataset, the data was reviewed to remove any mistakes in the data. Upon review of the data there were errors noted in the demographic categories these inaccuracies were simply deleted from the dataset. When reviewing the frequency for each construct there
d With the maximum value of 9 this highlighted an error in the data as the values should have been between 1 and 7 based on the scale range, this entry was simply deleted. Of the 1430 respondents who participated in the survey 43 did not provide information related to their gender, from the remaining 1387 participants who provided a response 757 were female and 630 were male representing 55% and 45%, respectively of the population of total respondents as shown in graph 1. Of those that provided a response majority were aged over 60 years, representing 42% of the total respondents. The second highest age group represented by respondents were those aged between 55 and 59 which represented 11% of the total respondents. A complete breakdown of the age brackets can be seen in graph 2. Due to incomplete data for the highest level of education, 30 surveys were omitted. Of the total 1400 respondents who provided a response majority had achieved the high school certificate as their highest level of qualification, representing 52% of the total respondents. Specific itemisation for each education level of the total respondents can be seen in table 1 and graph 3. Of the 1390 who provided a response to the frequency for use of service brand majority indicated they used the brand on a weekly basis representing 38% of total respondents. The survey captured information relating to customer perception of employee customer orientation, customer participation, customer satisfaction, customer willingness to pay and customer perception of brand image. The constructs were measured using a 7 point Likert scale which is the most common scale used for data collection. The results of kortosis and skewness show that some items are normally distributed. These items are customer participation (CCP1-CCP5), customer willingness to pay (WP1-WP2) and customer perception of brand image (B11-B17) as the kurtosis indices fitted between 3 and skewness indices fitted between 1 we can conclude these items have normal distributions. Items including customer perception (EC01-EC06) and customer satisfaction (CS1-CS2) are not normally distributed although the kurtosis indices fitted between 3 the skewness indices do not fit between 1. The complete results of kortisis and skewness testing as well as the mean and standard deviation for each construct can be seen below in table 2, descriptive statistics. The factor loading for each construct was measured as part of the preliminary analysis of data. As a well accepted rule, the factor loading for all items should be over 0.5 and no cross loading should be detected. As shown in table 3, preliminary analysis all of the factor loading
scores for all constructs are greater than 0.5, which shows the measures used in this study have acceptable convergent validity. The composite reliability for all constructs was calculated, as detailed in table 3, preliminary analysis. The results show that composite reliability scores for customer perception of employee customer orientation, customer participation and customer perception of brand image were all higher than 0.7 the accepted benchmark, this result supports the reliability requirement of the above measures. For construct customer satisfaction and customer willingness to pay the results were on the lower side within the 0.4 range. In addition, the average variance extracted (AVE) score was calculated for each construct to further test the validity, the results are shown in table 3, preliminary analysis. The AVE for all constructs range between 0.59 and 0.81 and support convergent validity as results exceed the 0.5 benchmark. The correlation coefficient is a statistical measure used to calculate the strength of the relationship between two variables. The correlation is a measurement between 1. The smallest correlation coefficient was between customer satisfaction(CS1-CS2) and customer participation (CCP1-CCP5) with a score of 0.154, which indicates a positive, weak linear relationship. The highest correlation co-efficient was between customer perception of brand image (B11-B17) and customer perception of employee customer orientation (EC01-EC06) with a score of 0.659 representing a moderate, positive linear relationship. Discriminate validity was tested and the square root of the AVE for each construct is shown in table 4, (correlation). The square roots of the AVEs were greater than the correlations between variables, highlighting discriminant validity for all constructs. As shown in table 3, preliminary analysis Cronbach Alpha exceeds 0.7 and all factor loading scores exceed the 0.5 benchmark. These results above support the overall reliability and validity of the measurement model. Hypothesis Testing and Data Analysis The model as shown in table 5, provided by the manager was instrumental in formulating a set of appropriate hypothesis to be tested statistically with the aim of using results to improve general business practices and performance within the service firm industry. The following hypotheses were developed:
H1: Customer perception of brand image is positively related to customer participation
H2: Customer perception of employee customer orientation is positively related to customer participation
H3: Customer participation is positively related to customer satisfaction H4: Customer participation if positively related to customer willingness to pay
Prior to testing the hypotheses, the data was standardised to ensure appropriate analysis of regression. As breakdown of the model summaries can be seen in table 6. The R square figure which represents a statistical measure of how close the data is to the fitted regression line for all hypotheses were recorded. The R square values include: H1 0.163, H2 0.163, H3 0.024 and
H4 0.145 all of the results represent a weak measure as the scores are below the standardised 0.25 benchmark. H1 hypothesised there is a strong, positive relationship between customer perception of brand image and customer participation. The results support this hypothesis at confidence level 0.99. The t-value is 16.700 which is greater than the threshold of 2.58 and coefficient is strong ( 0.404, <0.01). H2 hypothesised there is a strong positive relationship between customer perception of employee customer orientation and customer participation. The results support this hypothesis at confidence level 0.99. The t-value is 16.700 which is greater than the threshold of 2.58 and coefficient is strong ( 4.404, <0.01). H3 hypothesised there is a strong, positive relationship between customer participation and customer satisfaction. The results support this hypothesis at confidence level 0.99 the t-value is 5.902 which is greater than the threshold of 2.58 and coefficient is strong ( 0.154 and
<0.01). H4 hypothesised there is a strong, positive relationship between customer participation and customer willingness to pay. The results support this hypothesis at confidence level 0.99. The t-value is 15.570 which is greater than the threshold of 2.58 and coefficient is strong ( 0.381 and <0.01). Interpretations of Findings The results of the data analysis can be use to improve business processes and the overall success of the service firm company. The analysis of data and the statistical testing has methodically analysed the relationship between different variables based on results from the questionnaire survey. Although some data was omitted due to inaccuracies the initial sample size of 1430 was a large enough sample to provide some constructive insight into how customers are associated with service firm outcomes. The service firm is a very large industry that provides services to many consumers and many jobs to employees. The service firm includes but is not limited to medial services, professional services (accounting, legal), telecommunications, banking, restaurants, retailers, personal services (hairdressers, beautician), airlines, childcare and education. The large variety of service firms can make it challenging for marketing managers to target the service firm correctly. The key result of the data analysis shows the relationship model between the different variables that positively influence the outcome of a service firm. That being customer perception of brand image and customer perception of employee customer orientation has a positive influence on customer participation. As a flow on customer participation has a positive association with customer satisfaction and customer willingness to pay which is the anticipated end result of service firm industries. Analysis of the data is supportive of the four different hypotheses generated from the model. There was a lot that when into analysis of the data to draw conclusions based on statistical testing. The reliability and validity were assessed through a few different measures this was an important step in ensuring the questionnaire produced stable and consistent results as well as assessing that the constructs
measured what they were suppose to. The importance of this means results obtained from the analysis is most likely reflective of the greater population and service firm industry. The whole purpose of the data analysis was to make recommendations to management to develop their marketing strategies to improve business processes and the overall success of the business. The following recommendations have been made based on the demonstrated importance of customer perception of brand image and customer perception of employee customer orientation on customer participation as well as the importance of customer participation on customer satisfaction and customer willingness to pay. The recommendations to improving and customer perception of employee customer orientation come from principles widely studied in consumer behaviour. The complexity of understanding perceptions is that they are not something that is developed suddenly rather developed overtime. Perceptions can be evolved by a number of different methods including through formal marketing and advertising, previous experiences, reviews from well regarded sources and through informal word of mouth. The first stage in improving perceptions associated with a brand comes from understanding the actual and perceived perceptions consumers have. Only then can you take the appropriate measures to change these perceptions, a key factor in influencing perception comes from exposure and customer retention. It is important for ongoing review of perceptions as brands continue to evolve overtime businesses need to keep up to influence perceptions to elicit profitable consumer behaviours. Another recommendation for management of the service firm is to if they have not already implement programs to encourage customer participation and if already implemented build on these existing programs. An example of this could include the set up of an online interest forum group related to the service industry, this is particularly important in the current environment which is dominated by social media, technology and 24/7 access. An interest group not only creates a flow of dialogue between the firm and customers but also connects like minded consumers. The personable nature of such an approach will aid to increase customer satisfaction and the demand for a services. As highlighted in the analysis a focus on customer participation has a positive association with a willingness to pay which will increase revenue for the firm. The above recommendations are just a few suggestions to increase customer perception of brand image, customer perception of employee customer orientation and customer participation, there are many alternative ideas that will be appropriately suited to the service a firm is providing. The important recommendation that has come out of the analysis of data and the positive relationships between the model is the recommendation for management to continue or increase resource allocation and expenditure in the marketing department. This is the sector that will develop different strategies employee customer orientation, participation and in turn satisfaction and willingness to pay.
Appendix Graph 1: Gender of Respondents
Graph 2: Age of Respondents
Table 1: Highest Educational Qualification of Respondents
Education
Frequency Percent Valid Percent Cumulative
Percent
Valid High school certificate 722 50.5 51.6 51.6
Undergraduate degree 219 15.3 15.6 67.2
Postgraduate degree 222 15.5 15.9 83.1
Other 237 16.6 16.9 100.0
Total 1400 97.9 100.0
Missing System 30 2.1
Total 1430 100.0
Graph 3: Highest Educational Qualification of Respondents
Graph 4: Use of Service Brand
Table 2: Descriptive Statistics
Mean Standard Deviation
Skewness Kurtosis
Statistic Std. Error Statistic St. Error
Customer Perception of Employee Customer Orientation
EC01 Understand the specific needs of customers
5.985 1.0787 -1.116 .065 1.457 .129
EC02 Are able to put themselves in the customers place
5.747 1.2970 -1.276 .065 1.879 .129
EC03 Are able to tune in to each specific customer
5.781 1.2438 -1.190 .065 1.691 .129
EC04 Surprise customers with their excellent service
5.608 1.4413 -1.115 .065 .971 .129
EC05 Do more than usual for customers 5.690 1.3538 -1.157 .065 1.315 .129
EC06 Deliver excellent customer service quality that is difficult to find in other firms
5.159 1.7315 -.851 .065 -.062 .129
Customer Participation
CCP1 I spend a lot of time sharing information about my needs and opinions with the staff during the service process
4.780 1.8283 -.491 .065 -.762 .129
CCP2 I put a lot of effort into expressing my personal needs to the staff during the service process
4.372 1.9455 -.266 .065 -1.098 .129
CCP3 I always provide suggestions to the staff for improving the service
3.541 2.0521 .275 .065 -1.184 .129
(CCP4) I have a high level of participation in the service process
4.433 1.8611 -.308 .065 -.914 .129
(CCP5) I am very much involved in deciding how the services should be provided
3.947 2.0042 -.036 .065 -1.199 .129
Customer Satisfaction
(CS1) I am satisfied with the service provided 5.482 1.7197 -1.228 .065 .662 .129
(CS2) Overall, l am satisfied with the service provided by this service brand
5.521 1.5228 -1.195 .065 1.011 .129
Customer Willingness to Pay
WP1) I am willing to continue to do business with this service brand, even if its prices increase
4.240 2.0022 -.217 .065 -1.142 .129
(WP2) I am willing to pay a higher price for the services l buy from this service brand compared to other service brands because of the benefits l receive from it
3.660 2.0023 .123 .065 -1.198 .129
Customer Perception of Brand Image
(B11) This firm is known as a company that takes good care of its customers
5.197 1.6445 -.838 .065 -.028 .129
(B12) In comparison to other service providers, this brand is highly respected
5.404 1.4803 -.910 .065 .464 .129
5.148 1.6188 -.769 .065 .029 .129
positive 5.482 1.4509 -.979 .065 .550 .129
characteristics and associations are unique
4.854 1.6644 -.568 .065 -.340 .129
(B16) Information communicated about the brand is believable
5.364 1.4333 -.874 .065 .465 .129
impressions in my mind are likeable 5.400 1.4085 -.858 .065 .453 .129
Table 3: Preliminary Analysis
Constructs Factor
Loadings
CR AVE Cronbach Alpha
Customer Perception of Employee Customer Orientation
0.940586557 0.661432167 0.885
(EC01) Understand the specific needs of customers 0.819
0.858
0.898
(EC04) Surprise customers with their excellent customer
services
0.800
(EC05) Do more than usual for customers 0.808
(EC06) Deliver excellent service quality that is difficult
to find in other firms
0.680
Customer Participation
0.879631055 0.5947584 0.828
(CCP1) I spend a lot of time sharing information about
my needs and opinions with staff during the service
process
0.777
(CCP2) I put a lot of effort into expressing my personal
needs to the staff during the service process
0.791
(CCP3) I always provide suggestions to staff for
improving the service
0.771
(CCP4) I have a high level of participation in the service
process
0.679
(CCP5) I am very much involved in deciding how the
services should be provided
0.830
Customer Satisfaction
0.4812126 0.7921 0.734
(CS1) I am satisfied with the service provided 0.890
(CS2) Overall, l am satisfied with the service provided by
this service brand
0.890
Customer Willingness to Pay
0.491890442 0.815409 0.774
(WP1) I am willing to continue to do business with this
service brand, even if its prices increase
0.903
(WP2) I am willing to pay a higher price for the services l
buy from this service brand compared to other service
brands because of the benefits l receive from it
0.903
Customer Perception of Brand Image
0.948361362 0.645059429 0.905
(B11) This firm is known as a company that takes good
care of its customers
0.717
(B12) In comparison to other service providers, this
brand is highly respected
0.866
other brands
0.833
0.835
unique
0.796
(B16) Information communicated about the brand is
believable
0.704
my
mind are likeable
0.855
Table 4: Correlation
AVE (to 2 decimal places)
Mean Standard Deviation
Mean customer perception of employee customer orientation (EC01- EC06)
Mean customer participation (CCP1- CCP5)
Mean customer satisfaction (CS1-CS2)
Mean customer willingness to pay (WP1-WP2)
Mean customer perception of brand image (B11-B17)
Mean customer perception of employee customer orientation (EC01- EC06)
0.66
5.6615
1.09391
1 (0.81)
Mean customer participation (CCP1- CCP5)
0.59
4.2145
1.49392
.404**
1 (0.77)
Mean customer satisfaction (CS1-CS2)
0.79
5.5013
1.44364
.634**
.154**
1 (0.89)
Mean customer willingness to pay (WP1-WP2)
0.82
3.9500
1.80827
.480**
.381**
.552**
1 (0.91)
Mean customer perception of brand image (B11-B17)
0.65
5.2644
1.22376
.659**
.537**
.618**
.578**
1 (0.81)
Table 5: Research Model
brand image
Table 6: Model Summary Model 1
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .404a .163 .163 .91498488 .163 278.886 1 1428 .000
a. Predictors: (Constant), Zscore: mean customer perception of employee customer orientation
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients t Sig.
95.0% Confidence Interval
for B
Collinearity
Statistics
B Std. Error Beta
Lower
Bound
Upper
Bound
Toleranc
e VIF
1 (Constant) 1.013E-15 .024 .000 1.000 -.047 .047
Zscore: mean
customer perception of
employee customer
orientation
.404 .024 .404 16.700 .000 .357 .452 1.000 1.000
a. Dependent Variable: Zscore: mean customer participation
Model 2
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .404a .163 .163 .91498488 .163 278.886 1 1428 .000
a. Predictors: (Constant), Zscore: mean customer perception of employee customer orientation
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
95.0% Confidence Interval
for B
Collinearity
Statistics
B Std. Error Beta
Lower
Bound
Upper
Bound
Toleranc
e VIF
1 (Constant) 1.013E-15 .024 .000 1.000 -.047 .047
Zscore: mean
customer perception of
employee customer
orientation
.404 .024 .404 16.700 .000 .357 .452 1.000 1.000
a. Dependent Variable: Zscore: mean customer participation
Model 3
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .154a .024 .023 .98836708 .024 34.836 1 1428 .000
a. Predictors: (Constant), Zscore: mean customer participation
Beta T-value Alpha Result
H1 0.404 16.700 0.000 Supported
H2 0.404 16.700 0.000 Supported
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients t Sig.
95.0% Confidence Interval
for B
Collinearity
Statistics
B Std. Error Beta
Lower
Bound
Upper
Bound
Toleranc
e VIF
1 (Constant) -2.155E-15 .026 .000 1.000 -.051 .051
Zscore: mean
customer participation .154 .026 .154 5.902 .000 .103 .206 1.000 1.000
a. Dependent Variable: Zscore: mean customer satisfaction
Model 4
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .381a .145 .145 .92491312 .145 242.438 1 1428 .000
a. Predictors: (Constant), Zscore: mean customer participation
Coefficientsa
Model
Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig.
95.0% Confidence Interval
for B
Collinearity
Statistics
B Std. Error Beta
Lower
Bound
Upper
Bound
Toleranc
e VIF
1 (Constant) 7.757E-15 .024 .000 1.000 -.048 .048
Zscore: mean
customer participation .381 .024 .381 15.570 .000 .333 .429 1.000 1.000
a. Dependent Variable: Zscore: mean customer willingness to pay
Table 7: Hypothesis results
H3 0.154 5.902 0.000 Supported
H4 0.381 15.570 0.000 Supported