209 Int. J Sup. Chain. Mgt Vol. 7, No. 4, August, 2018 Evaluation on the Preference of Coffee Shop among the Undergraduate Students with Analytic Hierarchy Process Model #*1 #**2 #*3 #4 #5 Lam Weng Siew , Mohd Abidin Bin Bakar , Lam Weng Hoe , Chen Jia Wai , Ma Hui Lee # Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia * Centre for Mathematical Sciences, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia ** Centre for Business and Management, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia [email protected] [email protected] [email protected] [email protected] [email protected] Besides that, it is proven that coffee helps to Abstract— Emergence of coffee shop in recent years improve mental health and extending human’s has proven the demand of coffee shop in modern lifespan [2]-[4]. Coffee drinking is an important lifestyle. Nowadays, visitation to coffee shop has part of modern daily life [5]. Nowadays, many become a common trend for most of the undergraduate students for group discussion or coffee lovers are willing to spend for good chatting. This study aims to evaluate the preference of quality coffee. Coffee shops or coffee houses undergraduate students from Universiti Tunku Abdul offer varieties of food and drinks such as latte, Rahman in selecting the coffee shop based on multiple espresso, mocha, chocolate beverages, brewed criteria. There are 19 respondents participating in tea, shaken tea, muffin, breads and cakes. The this study who have visited all the 4 selected coffee emerging of coffee shop has become one of the shops which are Simple Coffee, Bean Café, Starbucks popular trends in food services [6]. Meanwhile, and Old Town White Coffee. An Analytic Hierarchy many researchers have started their investigation Process (AHP) model is proposed to determine the on coffee related business such as determining weight of criteria, priority of coffee shop selection in coffee shop location [7]-[8], selecting coffee terms of each criterion and the overall performance growth location [9], ranking of coffee suppliers of the coffee shop. The findings show that the most important criterion is cleanliness, followed by flavor, [10] and determining customers’ preference on store atmosphere, sales promotion, speed of service, coffee selection [11]. University is one of the price and location. Starbucks is the most preferred strategic location for operating coffee shops [7]- coffee shop while the followings are Simple Coffee, [8]. Therefore, the objective of this study is to Bean Café and Old Town White Coffee. The evaluate the preference of coffee shop among the significance of this study is to propose a conceptual undergraduate students by using Analytic framework to identify the most preferred coffee shop Hierarchy Process (AHP) model. The proposed and the most important criteria in coffee shop conceptual framework is illustrated with a case selection among the undergraduate students by using study in Universiti Tunku Abdul Rahman AHP model. (UTAR) Kampar Campus, Malaysia. In Kampar, Keywords— Priority; Multi-Criteria Decision Making; Starbucks, Simple Coffee, Bean Café and Old Conceptual Framework; Coffee Shop Town White Coffee are the most frequent visited 1. Introduction coffee shops by UTAR undergraduate students. The objective of this study is to determine the Coffee is one of the common yet popular beverages weight of criteria, priority of coffee shop in the world. There are studies showing that coffee selection in terms of each criterion and the is able to enhance human brain function [1]. overall performance of the coffee shop. AHP is a ______________________________________________________________ popular decision tool which helps to solve International Journal of Supply Chain Management IJSCM, multiple criteria decision making (MCDM) ISSN: 2050-7399 (Online), 2051-3771 (Print) Copyright © problem. Based on the past studies, the decision ExcelingTech Pub, UK (http://excelingtech.co.uk/) criteria identified in this study are price [12], 210 Int. J Sup. Chain. Mgt Vol. 7, No. 4, August, 2018 flavor [13], store atmosphere [13], sales promotion Price, customer service as well as cleanliness [14], location [15], speed of service and cleanliness were the most influential criteria in selection of [16]. fast food restaurant. In their study, McDonald From the past studies in food and beverage, AHP was once again identified as the most preferred has been applied in a tea-based drink in Indonesia. fast food restaurant. Besides that, AHP has been Pangkey [17] investigated the bubble tea shop in widely used in other sectors such as mobile Manado and found out that customers concern the network operators [20]-[21], social network sites flavor of the tea more than the price, store [22] supermarket [23], team leader [24], job [25], atmosphere, sales promotion and experience. A futsal court [15] and machine-tool [26]. All these research was performed in Taiwan landscape coffee studies have showed the robustness of AHP shops by Huang & Hou [11]. The study aimed to model in solving MCDM problems. determine the customers’ coffee taste using AHP The next section describes the data and model. Customers preferred Italian coffee and methodology. Section 3 presents the empirical Americano coffee the most compared to hand results of this study and section 4 concludes the dripping. Similar research was done on fast food paper. franchises by Wibowo & Tielung [18] who investigated the criteria that influenced customers’ 2. Data and Methodology intention in fast food selection. Their findings indicated that the most important criterion was AHP is a decision-making model which helps to price followed by cleanliness and atmosphere. solve MCDM problem [27], [23]. Figure 1 McDonald’s was identified as the most preferred presents the proposed conceptual framework to fast food restaurant followed by KFC and A&W. evaluate the preference of coffee shop among the Meanwhile, an empirical study was performed by undergraduate students with AHP model. Lam et al. [19] who studied the preference of fast food selection among the undergraduate students. Coffee Shop Selection Price Flavor Store Sales Location Speed of Cleanlines Atmosphere Promotion Service ss Simple Coffee Bean Café Starbucks Old Town White Coffee Figure 1. Proposed conceptual framework with AHP model In this study, the proposed conceptual coffee shops in Kampar. Survey has been framework is illustrated with a case study in conducted in this study through questionnaire. Universiti Tunku Abdul Rahman (UTAR) The methodology for AHP model is divided Kampar Campus, Malaysia. The decision criteria into the following steps: identified in this study are price, flavor, store Step 1: Develop a conceptual framework to atmosphere, sales promotion, location, speed of decompose the problem into main objective, service and cleanliness. Simple Coffee, Bean Café, decision criteria and decision alternatives as Starbucks and Old Town White Coffee are the shown in Figure 1. decision alternatives in this study. The target Step 2: Data collection from the experts or respondents are the UTAR Kampar decision makers. A pairwise comparison will be undergraduates who have visited all selected performed on the decision criteria as well as decision alternatives in terms of each criterion. 211 Int. J Sup. Chain. Mgt Vol. 7, No. 4, August, 2018 Table 1 shows the definition of pairwise comparison ratio scale. The best decision alternative will be the element with greatest weight in matrix F. Table 1. Ratio scale used for pairwise comparison Step 6: Checking for consistency ratio ()CR . CR value is calculated to determine the Scale Definition consistency of the results. If is smaller than 1 Equal importance 3 Somewhat more important 0.10, degree of consistency is satisfactory. 5 Much more important Formulation of value is as below: 7 Very much more important 9 Absolutely more important CI CR (2) 2, 4, 6, 8 Intermediate Values RI max n Step 3: Formulate pairwise comparison matrix CI (3) n 1 based on collected data. Given n decision criteria, there should be one ()nn matrix for pairwise CI is the consistency index, max is the comparison between decision criteria. Given m maximum eigenvalue and n is the number of decision alternatives, there should be numbers decision criteria. of ()mm matrixes for pairwise comparison Random index (RI) is determined empirically as between decision alternatives with respect to each the average value of CI of a large sample of decision criterion. randomly generated comparison matrices. Table 2 Step 4: Normalization of pairwise comparison indicates the random index ()RI with respect to matrix. Normalization is performed through number of decision criteria. division of column’s elements over column’s sum. Weights for each criterion and decision Table 2. Random Index alternatives are calculated from the row’s average of normalized matrix. Excel software is used in n 2 3 4 5 6 7 8 9 10 this study to calculate the weight for each RI 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.51 criterion. Step 5: Calculate the overall weights of matrix F by multiplying matrix Q and matrix w. Matrix 3. Result and Discussion F is the overall weights of decision alternatives, Figure 2 indicates the weightage of each decision matrix Q is the weights of decision alternatives criterion according to the preference of with respect to each decision criterion and matrix undergraduate students. w is the weights of decision criteria. The formula is as shown: F = Q x w (1) Priority of Decision Criteria Cleanliness 0.2454 Flavor 0.1954 Store Atmosphere 0.1603 Sales Promotion 0.145 Speed of Service 0.0909 Price 0.0864 Location 0.0766 0 0.05 0.1 0.15 0.2 0.25 0.3 Weight Figure 2. Priority of decision criteria 212 Int.