CHAPTER IV
Introduction
Overview
The previous chapter presents the theoretical framework for the research study as well as the research design and methodology employed in carrying out the study. The respective research questions and hypotheses were outlined. Reviews of the instrument development and screening procedure employed in developing the construct were outlined. The sample plan and data collection methods were presented and the planned hypotheses tests were provided.
Purpose
The purpose of Chapter Four is to present the analysis of the data and the resultant findings from the tests conducted on each of the respective hypotheses. An overview of the data collection, survey population responses, coding procedures and descriptive statistical summaries followed by validity and reliability testing opens the chapter. Since all of the research questions address the relationships of individual dimensions, a summary report of each hypothesis will report findings to support or reject each hypothesis.
The data collected were used to determine the impact of occupational stressors on job satisfaction among human service providers specifically, though not exclusively, among those working at a housing agency. In this chapter, the research also examined the impact of occupational stressors on different personality types; how some providers may be temperamentally predisposed to this type of work more successfully than others. Data indicating the relationship between job satisfaction, personality type and quality of service were also provided from survey results that measured service quality from the clients’ perspective. The gap between service quality expected and service quality received from the view point of this demographic group was identified, as were survey results measuring the relationship between job satisfaction, and personality type; in this way service quality was determined.
The purpose of this study was to identify what, if any, factors impacted service quality from the clients’ perspective. This information could then be used to determine whether the overall impact was positive or negative as it impacted the organizational structure of human service agencies and providers’ level of job satisfaction. This latter, it was hypothesized, had direct bearing on the quality of service provided from the perspective of the recipients of these services and therefore, was a valid measure of how well agencies were fulfilling their mission and purpose.
The results of this study are presented in three sections. The first section provides an analysis of the demographic data collected from each of the surveys. The second section is an interpretation and analysis of the survey data for each section of the two surveys conducted. The final section includes a sequential interpretation and analysis of data collected in the context of the five research questions that form the basis of this study.

Reliability Analysis Cronbach's α (alpha) is a coefficient of internal consistency. It is commonly used as an estimate of the reliability of a psychometric test for a sample of examinees. It was first named alpha by Lee Cronbach in 1951, as he had intended to continue with further coefficients.
Internal consistency is usually measured with Cronbach's alpha, a statistic calculated from the pairwise correlations between items. Internal consistency ranges between zero and one. A commonly-accepted rule of thumb is that an α of 0.6-0.7 indicates acceptable reliability, and 0.8 or higher indicates good reliability. High reliabilities (0.95 or higher) are not necessarily desirable, as this indicates that the items may be entirely redundant. The goal in designing a reliable instrument is for scores on similar items to be related (internally consistent), but for each to contribute some unique information as well.
Missing Value Analysis
Proper handling of missing values is important in all statistical analyses. Improper handling of missing values will distort analysis because, until proven otherwise, the researcher must assume that missing cases differ in analytically important ways from cases where values are present. That is, the problem with missing values is not so much reduced sample size as it is the possibility that the remaining data set is biased. The imputation of values where data are missing is an area of statistics which has developed much since the 1980s
Results and discussion

Hypothesis testing

In order to test the first set of hypotheses (H1.1 to H1.5), a paired ``t'' test has been carried out to check for differences between service quality and customer satisfaction with respect to the five factors. The results are summarized in Table III. The results indicate that service quality and customer satisfaction vary significantly with respect to all the five factors. This underscores that fact that service quality and customer satisfaction are two different constructs and are indeed distinguishable from the customers' point of view.
In order to test the second set of hypotheses (H2.1 to H2.5), correlations between service quality and customer satisfaction with respect to the five factors have been computed. The results are tabulated in Table IV. All the above correlations are statistically significant at the 0.01 level. Moreover the correlations are also reasonably high, thereby demonstrating high relationships between service quality and customer satisfaction.

Core service or service product | 0.626* | Human element of service delivery | 0.831* | Systematization of service delivery: non-human element | 0.734* | Tangibles of service ± servicescapes | 0.697* | Social responsibility | 0.534* |
Table. Correlation between service quality and customer satisfaction

In order to further illustrate the relationship between service quality and satisfaction a cross-tabulation procedure has been employed. The service quality data (originally in seven-point scale) have been collapsed into a three-point ordinal scale (low, medium and high). Similarly, customer satisfaction data (originally on a seven-point scale) have also been collapsed into a three-point ordinal scale (low, medium and high). Customer Satisfaction | Service Quality | Low | Medium | High | Total | Low | 9 | 3.2 | 2 | 0.7 | - | - | 11 | 4.0 | Medium | 46 | 16.6 | 106 | 38.3 | 52 | 18.8 | 204 | 73.6 | High | - | - | 20 | 7.2 | 42 | 15.2 | 62 | 22.4 | Total | 55 | 19.9 | 128 | 46.2 | 94 | 33.9 | 277 | 100 |

Chapter 5
Conclusion and Discussion
Over the past few years there has been a heightened accentuation on service quality and customer satisfaction in business and academia alike. Superior service quality and high levels of customer satisfaction are seen as two major goals by service provides in order to enhance their business performance.
The present study is an attempt to throw some more light on the distinctiveness of the constructs of service quality and customer satisfaction, and the relationships between them. The study adopts a different approach by operationalizing customer satisfaction on the same grounds (factors and their corresponding items) as done for service quality. The results reveal that service quality and customer satisfaction do exhibit independence and are indeed different constructs from the customer's point of view. It is also observed that these two are closely related as can be seen from the high correlations between them with respect to the five factors. This is also re- emphasized by the cross-tabulation analysis. The study is just a small step in unearthing and understanding the two constructs of service quality and customer satisfaction and their implications on competitive fruition. The causal relationships between the two have not been investigated as it is outside the purview of the present research work. Continued study of research models that portray the causal link between service quality and customer satisfaction and their effect on such desired later outcomes such as purchase intentions, fewer complaints, emotional bonding, word of mouth, etc. would help to further illuminate the subject
Theoretical Implications
Cross-cultural research could be very valuable in terms contributing to the theory development by applying and testing existing relationships among constructs in culturally different market environments. Accordingly, researchers during the past several decades used both etic and emic approaches to provide support for the conceptualized relationships among marketing variables (Brislin, 1976). The objective of the etic approach is to make generalizations across cultures that take into account all human behavior while the objective of emic approach has been to document the valid principles that describe consumer behavior in specific cultures. In other words, researchers have attempted to justify whether they should develop a single core approach to measure consumer behavior in all cultures or instead focus on culture-specific items which are designed to measure the phenomenon of interest in each culture.
In this study, we have attempted to understand the applicability of the previously developed service quality measurement scale (SERQUAL) proposed by Lin and Hsieh (2011) in assessing service quality of supermarket self-checkout systems in Turkey. Our findings provided further support for the dimensionality of the measure but with a reduced number of dimensions that would be considered more applicable in measuring service quality of the supermarket self-checkouts. Several hypothesized relationships among the service quality and the other constructs appeared to be holding in Turkish environment. Future studies are needed to further validate and clarify the relationships between SCS service quality, satisfaction and loyalty by perhaps utilizing emic approaches in understanding the relationship between these variables. To this end, specific measurement scales in measuring service quality for the self-checkout systems could be developed for different cultural environments and the relationships between the relevant constructs should be reassessed.
Managerial and public policy implications
For practitioners, the findings of this study suggest that supermarket self-checkout service quality has an important positive role on customer satisfaction and ultimately on customer loyalty. It is important for providers of SCSs to investigate their customers' experiences and evaluations of such technologies and identify different factors that might influence dis/satisfaction with technology-based service encounters. For the firms that currently offer or contemplate to offer or plan to expand self-checkout systems, identification of such factors could provide valuable insight about the role of self-checkouts on customer satisfaction and loyalty. Consumer complaints and dissatisfaction with the self-checkouts could contribute significantly in accounting the variation in consumer behavior. Therefore, rather than simply offering such services because everybody else does it,” supermarkets need to assess service quality of such offerings periodically and customer complaints and dissatisfactions need to be resolved timely
Limitation and Future Recommendation
It should be noted that this study has certain limitations. Perhaps the main limitation is the representativeness of the samples used in this study. First, it was a convenient sample collected from a single supermarket in the south eastern part of Turkey; therefore, its generalizability to the entire population is limited. However, please note that the data was collected during the shopping process and the supermarket chain used in the study was one of the supermarkets that had the largest market share in the Turkish market. Although the sample size was adequate for this study, our findings should be replicated using larger samples taken from different supermarkets and from different parts of the country.
Second, although we have used a valid SST service quality measurement instrument (SSTQUAL), some dimensions of the original scale had to be pruned due to its applicability (or lack thereof) to the supermarket self-checkout environment and low factor loadings. Hence, our study results did not provide strong confirmation of the stability of the SSTQUAL factor structure in the supermarket setting. The reduced number of service quality dimensions of the SSTQUAL needs to be tested and further validated in the supermarket SCS contexts. We recommend the development of more specific measurement instruments for the SCSs used in the supermarkets.
Third, while we mainly focused on the role of the service quality during customers' self-checkout encounter, it must be acknowledged that other factors may also drive satisfaction. It may be emphasized that behind each service experience–of assurance, responsiveness, etc.,–there are actors who may or may not be recognized or named by the service recipient. But that does not negate their contribution; it only established their relative importance to the service seeker.
Finally, the supermarket chain used in this study is considered one of the largest supermarket chains in Turkey and has a very good image among Turkish consumers. Such a strong market position or image might have introduced a bias into consumers' evaluations of self-checkouts. It is important that future studies incorporate other moderating and mediating factors in examining the impact of SCS service quality on customer satisfaction and loyalty. The role of corporate image on customer satisfaction may be used as a moderating factor. To enhance the generalizability of the research findings, future inquiries could employ more diversified samples and diverse national customer environments.