Abdullah Afzal

Factors affecting customer satisfaction in fast food sector Abdullah Afzal German edition

Masterarbeit aus dem Jahr 2013 im Fachbereich BWL - Marketing, Unternehmenskommunikation, CRM, Marktforschung, Social Media, Lovely Professional University, Punjab, Sprache: Deutsch, Abstract: Prior research has shown that customer satisfaction is the most important means for fast food restaurant. The main objectives of the study were to enhance the fast food service quality impact on overall customer satisfaction, to study purchaser behavior towards fast food places, to identify various key factors used by clients in the selection of fast food restaurants; and to analyze the particular differences/similarities in critical factors deemed by consumers for the selection of fast food restaurants. Our objective should be to look into the particular crucial elements that really help to determine the expectations which buyers have regarding the fast food market and his or her perceptions of good quality through experience. The organizations under study were Pizza Hut, Hardees, KFC, McDonald's and Subway located in Lahore, Pakistan. An extensive review of the literature was carried out by reviewing research studies, books, site pages and journals etc. On the basis of that literature review and its inferences, a questionnaire was developed which was needed for this quantitative type of research. The data was collected from the customer of these restaurants. A sample of 407 customers was selected randomly. Data was compiled and statistically analyzed using SPSS and Microsoft Excel. On the basis of their responses correlation test and analysis of variance (ANOVA) was applied through IBM SPSS. Results of each question were thoroughly analyzed and discussed by the researcher. Graphical representation of all the data has been shown. Conclusions of the study include the strengths of the organization as well as a few deficiencies in performance. Recommendations have been made for fast food restaurants to overcome those deficiencies for enhancing performance through statistical tec