**COMPANIES’ PERSPECTIVES ON FACTORS AFFECTING CONSUMER SATISFACTION IN FAST-FOOD RESTAURANT USING FUZZY AHP** \*\*Double blind review, please do not include authors information in this version \*\* Received Date: \*date Accepted Date: \*date Published Date: \*date **HIGHLIGHTS** - This study concentrates on the factors that satisfied customers' demands for the restaurants to gain customers' loyalty. - The pricing, quality of food, quality of service, and atmosphere of the selected fast-food restaurants all influence customers' impressions. - This study needs to help them identify the factors that affect customer satisfaction towards their fast-food restaurant to prevent them from losing their customers and avoid financial losses. ABSTRACT *In today's world, the fast-food restaurant has become a popular sort of eatery. The fast-food industry's expansion is always changing in response to customer requests in order to meet their needs. As a result, clients have a wide range of fast-food restaurants to choose from in order to satiate their hunger. Clients' contentment with restaurants will influence not just the image of the establishments, but also the services offered by their employees as they strive to entertain and deliver the best possible service to their paying customers. However, the competition between the restaurants have caused certain restaurants to gain lower profits as the customers’ satisfaction is not fulfilled for certain factors. Price, food quality, service quality, restaurant atmosphere, promotion, customer expectations, and brand are all elements to consider. This study was conducted to analyse the importance of factors in customer satisfaction in a fast-food restaurant in Perlis. In this study, the method applied is the Fuzzy Analytical Hierarchy Process (AHP) to rank the factors that have a high impact on customer satisfaction. The* *selected fast-food restaurants were McDonald (McD), Kentucky Fried Chicken (KFC), Pizza Hut, Domino’s Pizza, Marrybrown, and Subway. The primary data collected through the questionnaire were analysed by experts, the manager of the fast-food restaurant selected. The findings show that in a fast-food restaurant, the quality of service with 0.2188 of normalized weight is the most important factor in customer satisfaction, and the price with 0.0436 of normalized weight is the least significant. The role of the manager and the staffs were thus evidently more important in customer satisfaction than the price offered.* *Keywords: Fuzzy AHP, customer satisfaction, fast-food restaurant, price, quality of food, quality of service, atmosphere of the restaurant, promotion, customer expectation, brand.* # INTRODUCTION In the current marketing trend, all businesses have competitors include the fast-food industry, and in some cases, industry competition is so fierce that companies have to fight for the business of potential customers. The expansion of the fast-food industry rapidly changes according to the demands of the customers to satisfy their needs. Customers’ satisfaction with the restaurants will influence not only the image but also the services provided by the staff of said fast-food eateries as they seek to entertain and give the best possible service to their paying customers. Management and staff must evaluate customer satisfaction elements in order to keep their customers happy. Instead of investing more resources to gain potential new consumers, companies attempt to gain a high level of customer loyalty and keep their current clients. The producers and advertisers, therefore, try to keep their consumers happy so that they would stay loyal to the group and so that corporations could gain full market share (Akhtar & Rehman, 2014). The fast-food sector has become one of the most well-known food establishments because the food served is in line with current trends, particularly among young people who are always up-to-date on the latest fashions. Buying food from fast-food restaurants is convenient and gratifying for teenagers because the food preparation is quick, especially for those hurrying to work or class or those on a tight schedule. To meet client demand, numerous sorts of fast-food restaurants have been introduced in this era. As a result, it raises competition among fast-food establishments, preventing them from losing consumers. Aside from that, these fast-food restaurants must come up with a variety of new items or services to keep their consumers entertained and avoid financial losses. In order for a restaurant's senior management to establish client loyalty, a study must be undertaken to assist them in identifying the aspects that influence consumer satisfaction with their fast-food business. # METHODOLOGY **The primary data was gathered by sending a questionnaire to the upper management of Perlis' fast-food establishments. The survey asked about factors that influence customer happiness. The specialists were given the task of evaluating, ranking, and comparing all of the factors from their point of view. Fuzzy AHP was used to evaluate the data in order to determine which factor had the greatest impact on customer happiness.** **Formulate Fuzzy AHP Saaty’s Scale with linguistic terms** **Table 1:** Linguistic Terms with Triangular Fuzzy Numbers. | **Classic Saaty’s scale** | **Linguistic terms** | **Fuzzy scale (Triangular scale)** | | ------------------------- | ----------------------------------------------------------- | ---------------------------------- | | 1 | Equally Importance | (1, 1, 1) | | 3 | Moderate Importance | (2, 3, 4) | | 5 | Strong Importance | (4, 5, 6) | | 7 | Very Strong Importance | (6, 7, 8) | | 9 | Extremely Strong Importance | (9, 9, 9) | | 2 | Values designed for evaluation of the so-called interphase. | (1, 2, 3) | | 4 | | (3, 4, 5) | | 6 | | (5, 6, 7) | | 8 | | (7, 8, 9) | ![C:\\Users\\HP\\Desktop\\tfn2 crop.jpg](61168d7c89f75_media/media/image1.jpeg) **Figure 1:** Triangular Fuzzy Number Membership The decision-maker employed the specified fuzzy number on the right side of the scale, according to appropriate linguistic terms. If, on the standard Saaty's scale of 7, Factor 1 is more essential than Factor 2, then the fuzzy triangle scale will be (6, 7, 8). In the pairwise comparison matrix of the criteria, if Factor 2 is less essential than Factor 1 on a scale of 1/7, the fuzzy triangular scale will be (1/8, 1/7, 1/6). As illustrated in equation, the pairwise comparison matrix of the factors is represented as a matrix (1). **(1)** Equation (1) shows that the k-th decision-maker prefers the i-th criterion over the j-th criterion when applying fuzzy triangular numbers. The "\~" symbol denotes that the triangular number is being demonstrated. If there were more than one decision-maker, the priority of each decision-maker was multiplied and determined as indicated in matrix (1). (2) **Pairwise Contribution Matrix** The pairwise contribution matrix was updated according to averaged preferences, as shown in equation (3). > **, (3)** **where**represents the pairwise contribution matrix. **Geometric Mean of Fuzzy Comparison Values** **Geometric mean of fuzzy comparison values by using** equation (4). > , (4) > > *i* = 1, 2,…, *n* where is a geometric mean of fuzzy comparison values. Each fuzzy value from a pairwise comparison matrix was multiplied with . **Weights of Criteria Using Fuzzy AHP** The fuzzy weight for each criterion as shown in equation (5) followed by three steps. Step 1: Find the vector summation of each. Step 2: Find the (–1) power of the summation vector. The fuzzy triangular number is replaced to make it an increasing order. Step 3: Multiply each reverse vector to find the fuzzy weight of the criterion . > , (5) where are obtained fuzzy triangular numbers. **Defuzzification and Normalization** The fuzzy weight of each criterion was defuzzied by using equation (6). > (6) The weight of each criterion was normalized if necessary, by implying equation (7). > (7) To find the normalize weights of the criteria, all of the methods were used. The criteria with the highest score was suggested to the decision-maker as the most important consideration based on the results. **RESULTS AND DISCUSSIONS** Step 1: Fuzzy AHP Saaty’s scale was formulated with linguistic terms**.** From the questionnaire obtained, the experts compared criteria that would affect customer satisfaction in the fast-food restaurant. **Table 2** Comparison of Criteria Using Saaty's Scale with Linguistic Terms. | **Factors / Criteria** | **Decision-maker 1** | **Decision-maker 2** | **Decision-maker 3** | **Decision-maker 4** | **Decision-maker 5** | **Decision-maker 6** | | ---------------------- | -------------------- | -------------------- | -------------------- | -------------------- | -------------------- | -------------------- | | Price | | | | | | | | Quality of Food | | | | | | | | Price | | | | | | | | Quality of Service | | | | | | | | Price | | | | | | | | Atmosphere restaurant | | | | | | | | Price | | | 1 | | | | | Promotion | | | | | | | | Price | | | | | | | | Customer expectation | | | | | | | | Price | | | | | | | | Brand | | | | | | | | Quality of Food | | | | | | | | Quality of Service | | | | | | | | Promotion | | | | | | | | -------------------- | | | | | | | | Brand | | | | | | | | Customer expectation | | | | | | | | Brand | | | | | | | | Quality of Food | | | | | | | | --------------------- | | | | | | | | Atmosphere restaurant | | | | | | | | Quality of Food | | | | | | | | Promotion | | | | | | | | Quality of Food | | | | | | | | -------------------- | | | | | | | | Customer expectation | | | | | | | | Quality of Food | | | | | | | | --------------------- | | | | | | | | Brand | | | | | | | | Quality of Service | | | | | | | | Atmosphere restaurant | | | | | | | | Quality of Service | | | | | | | | Promotion | | | | | | | | Quality of Service | | | | | | | | Customer expectation | | | | | | | | Quality of Service | | | | | | | | Brand | | | | | | | | Atmosphere restaurant | | | | | | | | Promotion | | | | | | | | Atmosphere restaurant | | | | | | | | Customer expectation | | | | | | | | Atmosphere restaurant | | | | | | | | Brand | | | | | | | | Promotion | | | | | | | | Customer expectation | | | | | | | Step 2: The pairwise contribution matrix was updated according to averaged preferences. Step 3: Geometric mean of fuzzy comparison values. The geometric mean of fuzzy comparison values was required to find the fuzzy weight for each criterion. Example of calculation in finding geometric mean for price criteria: \= Step 4: The fuzzy weight for each criterion was calculated following three sub-steps: Step 4.1: The vector summation, was found. > \= > > Step 4.2: The (-1) power of the summation vector was calculated. The fuzzy triangular number was replaced to arrange it in increasing order. > > The value obtained needs to be in increasing order, so the value was rearranged. > > **Table 3** The Fuzzy Weight for Each Criterion. | **Criteria** | **Geometric mean** | | ------------------------ | ------------------ | | Price | | | Quality of food | | | Quality of service | | | Atmosphere of restaurant | | | Promotion | | | Customer expectation | | | Brand | | | Total | | | Inverse | | | Increasing order | | > Step 4.3: Each reverse vector of was multiplied with the geometric mean obtained to find the fuzzy weight of each criterion. Example of calculating the fuzzy weight for price criteria is as follows: > > **Table 4** Fuzzy Weight for Average Preferences. | **Criteria** | **Fuzzy weight** | | ------------------------ | ---------------- | | Price | | | Quality of food | | | Quality of service | | | Atmosphere of restaurant | | | Promotion | | | Customer expectation | | | Brand | | Step 5: The fuzzy weight of each criterion was defuzzified. In finding the weightage of each criterion, defuzzification of the fuzzy weightage was required using the average of the value respective to each criterion. Example of calculating the weightage of the price criteria is as follows: **Table 5** Weightage for Each Criterion | **Criteria** | **Weight** | | ------------------------ | ---------- | | Price | | | Quality of food | | | Quality of service | | | Atmosphere of restaurant | | | Promotion | | | Customer expectation | | | Brand | | | Total | | . Step 6: The weight of each criterion was normalized if necessary. As the total weightage of all criteria exceeds the value 1, normalization was necessary. Example of finding the normalization for price criteria is as follows: From the normalized weight, the factors that affect customer satisfaction in the fast-food restaurant were then ranked. **Table 6** The Normalized Weight with Ranking. | **Criteria** | **Normalized weight** | **Rank** | | -------------------------------- | --------------------- | -------- | | Price | | | | Quality of food | | | | Quality of service | | | | The atmosphere of the restaurant | | | | Promotion | | | | Customer expectation | | | | Brand | | | | Total | | | **The factors that affect customer satisfaction in a fast-food restaurant in Perlis the most are the quality of service, followed by quality of food, brand, promotion, the atmosphere of the restaurant, customer expectation, and lastly, price.** **CONCLUSION** The factors that affect customer satisfaction in the fast-food restaurant were ranked according to the experts’ decision by collecting information from the questionnaire distributed to them. 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