The University Sports Centre - Essay Example

A REPORT BASED ON ANALYSING DATA FROM A SURVEY OF SERVICE QUALITY AT A SPORTS CENTRE and number: Instructor’s name: Date submitted: Contents Introductions 3 Evaluation of Questionnaire Design 3 Analysis of survey data 5 Sample Composition 5 Analysis of satisfaction levels reported in Question 1 of the Questionnaire 8 Analysing the importance given to different dimensions of service quality 14 Summary, Conclusions and Recommendations 17 References 19 Introductions People providing service of different forms have always aspired to please their customers or service users by providing high quality services that meet the expectations of users. Once this goal is achieved, it is said that service quality has been met (Agus, Barker and Kandampully, 2009). Service quality is important and necessary for both profit based service delivery and non-profit service delivery. This is because in whatever case a service may be delivered, there are often alternatives and options for service users such that once they are not satisfied with the service they receive from one point, they may switch to other places where they will get the expected satisfaction (Bloemer and Kasper, 2013). This means a lot to service providers in ensuring that they provide services that meet the service expectations of their users and therefore lead to service satisfaction. According to Williams & Buswell (2013), service satisfaction is mostly attained when there is high level of service quality in the service provided. To this end, service providers have used various means to measure and evaluate the extent of quality in the service they provide. One of these is the use of the data collection instrument known as SERVQUAL (Ndubisi, 2012). In this paper, the outcome of one such instrument is subjected to critical analysis. SERVQUAL is an instrument that seeks to give a quantitative description to the level of service quality that prevails within a given service setting (Bluestein, Moriarty and Sanderson, 2013). For this paper, the emphasis is on the outcome of service quality among students using a sports facility at a University. Evaluation of Questionnaire Design Generally, the questionnaire used can be commended for its quantitative approach. As it has been stressed already, this was necessary in quantifying quality and satisfaction, which otherwise would have remained highly relative and subjective to individual differences (Newman, 2011). Meanwhile, the use of quantitative measures has been praised as highly innovative ways by which empirical outcomes are achieved with various research findings (Wirtz and Bateson, 2012). The reason this is said is that most of the outcome with quantitative measures such as percentages, means and standard deviations are things that have a common universal interpretation. In effect, the interpretation to the outcomes of a study always remains the same no matter where it is taken to for analysis. With this said recommendation that will be made for improvement on the questionnaire has to do with the number of areas for which variables were measured. The 3 parts of the questionnaire seem comprehensive on the outside but it could be made of a mixed approach where respondents could give open ended recommendations and rationale to their quantitative scores. The sampling approach used in this study was the probability sampling. As the name suggests, this is a type of sampling approach where all subjects within the population has an equal probability of becoming part of the sample size. Probability sampling is certainly a very fair way of undertaking a sample for research of this nature. This is because of the extent of fairness it offers and absence of biases with the selection of respondents. As the researchers were aiming to measure the outcome of a service facility, it was important that every necessary avenue will be created to ensure that the outcomes produced were those that gave very fair reflection of the prevailing situation at the University Sports Centre. It was against this backdrop that the use of the probability sampling method was seen as a step in the right direction as it partly helped in achieving such as goal. With this said, the 9% error margin of sampling approach is one that can be seen to be very high and could have been controlled downwards. Analysis of survey data In this section of the paper, the actual data that were produced from the questionnaire are subjected to critical analysis. Until such analysis is done, the outcomes that have been produced in this study will only remain raw information that cannot be effective for any decision making on service improvement. The section therefore looks into the sample composition, satisfaction levels, and different dimensions of service quality. Sample Composition In every survey study, the sample serve as the contact people whose opinions and ideas represent that of the other people within the population or research setting who were not contacted directly. Because of this, knowing the composition of the sample is very important in ensuring that there is as much balance and fairness in the representation of members within the population as possible. Very often, the balance and fairness in the representation of members within the population is detailed by several conditions and factors. In the current study, since service quality was being measured from the perspective of a university sports facility, it was important to look into such aspects of sample composition such as gender, subject area studied and number of years of service usage. Composition in gender is referred to, as males and females are most likely to have different needs from the sports facility. Example of this includes the forms of exercises that males and females may be involved in. Subject area studied is another important issue because people are also likely to have different needs from a sports facility based on their subject area studied. What is more, the period of time within which a person has used the sports facility is very likely to influence the person’s understanding of the operation of the facility and can therefore affect their opinions on quality and satisfaction. Based on these, the following breakdown in frequencies for sample composition is made. Table 1: Composition of Sample according to Gender From table 1, it can be seen that there is a form of imbalance in the composition of the sample according to the gender of respondents. This is because the males used in the study outnumbered the females by more than 25 percentage points. This is because as there are 62.4% of males, there were only 37.1% of females. In such an instance, it can be difficult to expect that the needs of respondents in measuring service quality will be met according to their gender. Table 2: Composition of Sample according to Subject Area Table 2 indicates that somehow, the needs of people from different subject areas may be reflected in the overall data that was collected. This notwithstanding, the extent of representation cannot be said to be very detailed or balanced. This because whiles 33.7% of the sample was made up of those studying sports, business students were represented by 20.3%, media studies by 11.9% and those in all other subject areas combined formed 34.2%. Table 3: Composition of Sample according years of service In table 3, it can be said that as far as years of service usage is concerned, the respondents are in a very good position to contributing to the assessment of the sports facility. This is because most of them have used the centre for more than a year. Such people certainly have seen the facility go through various transitions and can therefore give assessments on quality that can be trusted to be highly credible. From the table, those that had possibly used the facility for less than a year because they were in their 1st year were 33.4%. All the rest had probably used the facility for more than a year because they were in the 2nd year or beyond. It was in line with this that Muenz (2009) mentioned that the length of service reception is very important in critiquing the quality of service output. Analysis of satisfaction levels reported in Question 1 of the Questionnaire Question 1 in the questionnaire gave various variables based on which the satisfaction levels of customers were measured. There were a total of 21 variables which were scored by each respondent using scale from 1 to 5. 1 to 3 represent low satisfaction, and 4 and 5 represent high satisfaction. To get the real outcome of satisfaction level for each variable, it was important to use SPSS to find the mean and standard deviation of each variable that was scored by respondents. This was important to do because not all the variables were answered by the same number of respondents. Using the means and standard deviation therefore gave the real or holistic score given to each variable. In table 4, the mean scores that were obtained for each variable has been ranked in a descriptive statistics. From the ranking obtained, all variables that were scored above 70 in terms of mean score can be said to have been scored highest or rated highly by respondents. Such variables are equipment rating weighted, appearance weighted, changing facility weighted, smart staff weighted, convenience weighted, information weighted, staff with good customer care weighted, and attending to needs of every customer weighted. Table 4: Satisfactory Ranking produced for Variables Descriptive Statistics N Minimum Maximum Mean Std. Deviation Equipment Rating Weighted 201 10.00 384.00 95.4378 51.10232 Appearance Weighted 200 15.00 384.00 94.4850 52.34568 Changing Facilituies Weighted 200 15.00 384.00 93.8000 51.14547 Smart staff weighted 202 20.00 480.00 91.9554 53.12112 Convenience weighted 202 10.00 384.00 89.2624 48.78010 information weighted 200 10.00 384.00 87.6250 50.05800 Staff with good customer care weighted 199 .00 175.00 73.0251 36.84111 Attending to needs of every customer weighted 197 .00 175.00 70.8376 36.25356 Reliable Serice weighted 200 4.00 200.00 67.4650 31.25288 readiness to respond to user requests weighted 199 2.00 195.00 67.2915 33.01401 Informing Customers pf changes weighted 200 4.00 240.00 66.7500 32.74736 willingness to help users weighted 201 4.00 195.00 66.7214 33.83285 Service carried out 1st time weighted 198 2.00 240.00 66.3485 31.58109 Service provided as promised weighted 200 2.00 240.00 66.1100 32.25196 dealing with customer complaints weighted 198 3.00 240.00 65.7551 35.55195 well mannered and informative staff weighted 202 4.00 200.00 65.1832 32.41078 secure transactions weighted 201 3.00 200.00 63.2289 32.59459 knowledgeable and reliable staff weighted 198 4.00 160.00 60.8763 28.91632 prompt service to users weighted 191 3.00 240.00 60.7199 32.42134 prompt actions on customer feedback weighted 191 3.00 240.00 60.5471 31.46946 highly motivated staff weighted 199 3.00 160.00 60.0578 28.65315 Valid N (listwise) 177 Also from the descriptive statistics in table 4, it can be noted that the variable that were scored below 61 can be said to be the least rated or those scored lowest. Such variables include knowledgeable and reliable staff weighted, prompt service to users weighted, prompt actions on customer feedback weighted, and highly motivated staff weighted. From the trend of ranking done for highest rated and lowest rated variables, it can be indicated that most forms of service that focus on the physical presence or appearance of the sports centre are those with the most remarkable forms of ratings. Those that deal with staff output on the other hand were those that had the lowest forms of ratings. It would be noted that the questionnaire was prepared based on five dimensions of service quality. The figure below gives a representation of the number of variables under each dimension that was ranked highest and those that were ranked lowest. Figure 1: Highest and Lowest Scores based on dimensions of service From figure 1, it is realised that out of the five aspects of service, the area that had a lot of variables coming under the highest scores was tangibles. This had 6 variables, representing 100% of all variables in that category. The next was empathy, which had 1 variable out of the total of 2 variables, representing 50%. The next was responsiveness, which had 1 variable out of a total of 5 variables representing 20%. Assurance had no variable as part of the highest scored, so as reliability. In terms of those with most variables in the least scored, assurance and responsiveness each had 3 variables. The Sports Centre Management wanted to know the differences in levels of satisfaction between respondents that are members of the centre and those that are not. Further, the significance in the differences in levels of satisfaction expressed by these two groups of people is a concern for the management. To measure such differences, cross-tabulation was made on levels of satisfaction against the membership variable. Chi-squared tests were also used to identify statistical significance of the difference that was measured. A very straight forward procedure was used in going about all these. First a null hypothesis was identified. Based on the assumption of the management, the null hypothesis was that there is no significant difference between the level of satisfaction in members of the centre and non-members of the centre. The second process was to group all respondents according to members and non-members. This led to the third stage, where each respondent’s overall satisfaction was calculated. Here, a simple average was computed for each respondent’s responses by putting all scores together and dividing it by 21. By so doing, a range of score from 1 to 5 was obtained for each respondent. Respondents whose scores were from 1 to 3 were regarded as not satisfied and those whose score were from 4 to 5 were regarded as satisfied. The last stage was to use the SPSS to compute for the chi square, which made it possible to find the p-value and significance level. The table below shows the outcome satisfaction levels among the members and non-members of the sports centre. Table 5: Satisfaction level among members and non-members How satisfactory modern sports/gym equipment * are you a member or do you pay each time Crosstabulation Count are you a member or do you pay each time Total member pay each time How satisfactory modern sports/gym equipment dissatisfactory 8 8 16 neutral 23 24 47 satisfactory 53 50 103 very satisfactory 13 10 23 Total 97 92 189 The table shows that there were a total of 189 respondents, out of which 97 (51.32%) were members and 92 (48.68%) were non-members. Among the members those that scored either satisfactory or very satisfactory were 66 (68.04%) in all. 31 (31.96%) members on the other hand rated their service as dissatisfactory and neutral. On the part of non-members or those that pay anytime they used the facility, it was noted that 60 (65.22%) of them were either satisfied or very satisfied. 32 (34.78%) on the other hand were either dissatisfied or neutral. Table 6: Chi square outcome for members and non-members Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square .368a 3 .947 Likelihood Ratio .369 3 .947 Linear-by-Linear Association .255 1 .614 N of Valid Cases 189 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 7.79. From table 6, the chi-square statistic was 0.368 for N of valid cases of 189. The implication from this was that the result is not significant at p < 0.05. The Pearson chi-square shows a large value which is greater than 0.05. By implication, there is weak evidence against the null hypothesis, which means that the null hypothesis cannot be rejected. If the null hypothesis is not rejected, the Sports Centre Management can conclude that there is no significant difference between the level of satisfaction in members of the centre and non-members of the centre. There are a number of things that his analysis tells the managers of the sports centre. Particularly, since there is no significant difference between the level of satisfaction in members and non-members of the centre, it proves to the managers that the outcome of quality service as evidenced by the data collected can be regarded as realistic (Sapsford and Jupp, 2006). This is so because not just members of the centre have noted the outcomes with the services but non-members also. Another implication for the managers is to take comments of members as seriously as they would take that of non-members. Analysing the importance given to different dimensions of service quality Based on table 7, 5 performance dimensions were set for respondents to score between 0 and 100 in determining the levels of importance they attached to each of these 5 dimensions. Giving a descriptive analysis to the 5 dimensions, it can generally be said that there are those that are of more importance to the users and dimensions that were of less importance to the respondents. The procedure used in breaking the dimensions down was to find the mean scores and standard deviation of the various weightings performed by the respondents. By dividing the summation of scores by 202, it was possible to get the mean score for each category of service. Based on this, the area where respondents attach a lot of importance is the appearance of the sports centre, physical facilities such as staff, gym equipment, the sports hall, and changing rooms. The mean score for this area was 25.34. The two areas with least importance attached is the knowledge and manners of the sports centre’s staff and their ability to supply and maintain confidence and trust within the customers. The mean score for this area was17.26. Table 7: Distribution of dimensions as high importance and low importance Descriptive Statistics N Minimum Maximum Mean Std. Deviation the appearance of the sports centre, physical facilities such as staff, gym equipment, the sports hall, and changing rooms. 202 5 96 25.34 11.399 the ability of the sports centre and its staff to implement the service promised reliably and accurately. 202 1 60 18.25 7.425 the knowledge and manners of the sports centres staff, and their ability to supply and maintain confidence and trust within its customer. 202 1 41 17.26 7.133 the attention to detail given when dealing with a customer on a one to one basis , though being caring and sympathetic to any problems that may have arisen. 202 0 51 20.95 10.101 the sports centres willingness to help users and provide a prompt and friendly service. 202 1 60 18.29 8.075 Valid N (listwise) 202 Based on a self-introduced criteria that those with mean higher than 20 are of high importance and those with mean of less than 20 are of low importance, the number of categories with high importance and those with low importance turns out to be the following. Figure 2: Importance attached to performance dimensions From figure 2, it can be seen that there were a lot of the 5 dimensions of performance that were of low importance to the respondents. The implication of these findings to the overall research objective is for the service providers to emphasise more on these areas that are noted to be of importance to the customers. From the trend of the findings, it can be noted that the users are mostly concerned with physical aspect of the centre and the state of its equipment than the attitude of the staff. From table 4, it is possible to rank the mean values of the weighted variables t1 to E2 into 5 dimensions which are tangibles, empathy, assurance, reliability, and responsiveness. For the tangibles, there were 6 variables and so the total weighted value was divided by 6. For empathy, there were 2 variables and so the weighted value was divided by 2. For assurance, there were 3 variables and so the weighted value was divided by 3. For reliability, there were 4 variables and so the weighted value was divided by 4. For responsiveness, there were 5 variables and so the weighted value was divided by 5. After doing this, the following rankings were produced for each. Figure 3 below gives a ranking of the mean scores for the various categories of services offered. Figure 3: Ranking of Categories Summary, Conclusions and Recommendations The analysis of the data produced so far has showed that there are different levels of satisfaction among respondents in terms of the performance dimensions from which the sports centre provides services to the users of the centre. The research aim for this survey exercise was to measure the extent of satisfaction among service users of the University Sports Centre. It is understood that service satisfaction is directly linked to the extent of quality in the service provided (Anderson and Fornell, 2012). What this means is that the higher the quality of service, the higher the level of satisfaction that will be produced among the service users. Meanwhile, quality is generally a qualitative and relative measure, which is very difficult to itemise (Morgeson & Petrescu, 2011). Because of this, most service providers have had challenges in determining the real value of the quality that they provide to their customers. It was for this reason that in this study, the method used in measuring service quality was based on one that sought to quantify the level of satisfaction of customers by assigning scorings or weightings to various variables that are likely to be produced from the use of the sports facility. The method used therefore helps to achieve the aim by giving quantitative values to both service quality and customer satisfaction. The summary of the data collected shows that two areas where the sports centre provides the best of service to users are tangibles and empathy. Two areas where there is least quality are reliability and assurance. Meanwhile, the tangibles happen to be one area where respondents attach high importance and assurance is an area where the respondents attach low importance. The conclusion that can be drawn from this is that the centre has rightly matched the outcome of it service quality with the needs of the respondents. This is because it is in the areas that respondents attach a lot of importance that the highest scores on satisfaction was made. It is therefore important that the centre will continue focusing more on tangibles whiles ensuring that the level of satisfaction with assurance does not drop further. For researchers undertaking further research, it is recommended that they will use systematic sampling in their sampling approach. This will ensure that there is much balance with gender, subject area studied, membership and length of time within which a person has used the service of the facility. Even though the probability sampling was good in avoiding bias, it could not guarantee balance with the composition of the sample size. Using a systematic sampling will ensure that the researchers can combine purposive sampling with probability sampling to ensure both balance and fairness (Saunders, Lewis and Thornhill, 2003). References Agus, A., Barker, S., and Kandampully, J. (2009). An exploratory study of service quality in the Malaysian public service sector. International Journal of Quality & Reliability Management, 24(2), 177-190. Anderson, E.W. and Fornell, C. (2012). A customer satisfaction research prospectus. In : R.T. Rust and R.L. Oliver (eds.), Service Quality: New Directions in Theory and Practice. CA: Sage, Thousand Oaks, pp. 241-268. Bloemer, J.M.M., and Kasper, H.D.P. (2013). The complex relationship between consumer satisfaction and brand loyalty. Journal of Economic Psychology, 16, 311-329. Bluestein, A, Moriarty M. and Sanderson R. J. (2013). 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Harlow: Pearson Education Limited. Williams, C. & Buswell, J. (2013). Service Quality in Leisure and Tourism. Cambridge, MA: CABI Publishing Wirtz, J. and Bateson J. E. G. (2012), “An Experimental Investigation of Halo Effects in Satisfaction Measures of Service Attributes,” International Journal of Service Industry Management, 6 (3), 84-102. Read More