ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS Volume 65 33 Number 1, 2017 https://doi.org/10.11118/actaun201765010293 IMPACT OF CONSUMER PREFERENCES ON FOOD CHAIN CHOICE: AN EMPIRICAL STUDY OF CONSUMERS IN BRATISLAVA Pavol Kita1, Andrea Furková2, Marian Reiff2, Pavol Konštiak1, Jana Sitášová1 1Marketing department, Faculty of Commerce, University of Economics in Bratislava, Dolnozemská cesta 1, 852 35 Bratislava, Slovakia 2Department of Operations Research and Econometrics, Faculty of Economic Informatics, University of Economics in Bratislava, Dolnozemská cesta 1, 852 35 Bratislava, Slovakia Abstract KITA PAVOL, FURKOVÁ ANDREA, REIFF MARIAN, KONŠTIAK PAVOL, SITÁŠOVÁ JANA. 2017. Impact of Consumer Preferences on Food Chain Choice: An empirical study of consumers in Bratislava. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 65(1): 0293–0298. The objective of this paper is to highlight the use of multiple criteria evaluation methods as a tool for the rating and selection of retail chains from the customers and suppliers perspective. We provide an assessment on the attractiveness of active retail chains on the Slovak market through multiple criteria methods used for the analysis of customer preferences. An analysis was conducted on a sample of consumers in Bratislava involving 11 389 respondents interviewed. The multi-attribute decision-making methods PROMETHEE II and V were used to assess the variants. In the first part of analysis the collected data uncover customers’ preferences in the selection of retail chains. Findings suggest a ranking of evaluated retail chains and thus of customer preferences. Based on the obtained evaluation, in the second part of analysis, a set of retail chains was chosen under constraints concerning the effectiveness of advertising, market share of sales and the maximum number of chosen retail chains and a binary linear programming model was formulated as an outcome. Proposed procedure aims to assist the decision maker in selecting which retail chain to choose for distribution of supplier’s products, and thus maximize benefits, which will result from consumer preferences and service satisfaction level in retail chain. Keywords: Consumer preferences, food chain, store choice, multi-attribute decision-making problems, binary linear programming models INTRODUCTION the imbalance between foreign retailers and weaker Retail markets are highly saturated which stresses national retailers (Colla, 2004). the need for managers to understand the existing Retailers in general focus on their effort to attain competitive structure for putting in place strategies, economies of scale and an improved asset utilization which will allow retail chains to survive (Križan, all with the goal of satisfying demanding needs and Bilková, Kita, 2014; Sinha, 2000). wishes of consumers (Thang, Tan, 2003). An important shift in many European retail Consumers on the other hand are influenced by markets has been in terms of acquisitions, joint numerous elements in their choice of a grocery store ventures and mergers in the last few years. These (Thang, Tan, 2003). Research realized in this area has have made it possible for market leaders to enter demonstrated that their loyalty to one specific store countries where access was difficult. However, is at a low level and their decision making process Slovakia has its own specifics from other central when deciding for a grocery store is not repetitive European countries. An important specificity is (Keng and Ehrenberg 1984; Ehrenberg, Uncles 293 294 Pavol Kita, Andrea Furková, Marian Reiff, Pavol Konštiak, Jana Sitášová and Goodhardt, 2004; Leszczyc and Timmermans, where X1, X2, ..., Xn is the set of n alternatives, 1997). Y1, Y2, .., Yk is the set of k criterions, Consumers’ reactions to a rapidly changing retail yij is the criterion value of the alternative Xi, environment will depend upon their preferences i = 1,2,...,n, j = 1,2,...,k. and the environment in which they are made. As In the matrix, each column belongs to a criterion stressed by Leszczyc, Sinha and Timmermans (2000), and each row describes the performance of for the retailers, the problem is how to cope with an alternative, i.e. each element of the matrix the increased competition in light of the dynamics yij is a single numerical value representing of consumer shopping behavior (see also Maryáš, the performance of alternative i on criterion j. et al. 2014). We address this topic by proposing The essential part of the multi-attribute decision- a unique view on consumer preferences based on making problem is setting the type of the criteria six factors: purchase time of customers, customers’ (minimization or maximization) and assigning willingness to travel to supermarkets, customers’ weights to the criteria. The weight wi reflects dissatisfaction of any kind with the supermarkets the relative importance of the criteria and is (share of customers wishing for improvement), assumed to be positive. The weights of the criteria improvements noticed by customers, effectiveness are usually determined on a subjective basis. They of advertising through leaflets and the market represent the opinion of a single decision-maker or share of sales. This will be made under predefined synthesize the opinions of a group of experts using constraint assumptions on the advertising a group decision technique as well. The main goal of effectiveness, market share of sales and the number the multi-attribute decision-making techniques can of chosen retail stores. As a result of the analysis be complete or partial ranking of alternatives. of consumer preferences and service satisfaction, Multi-attribute decision-making methods are a recommendation to retail investors will be stated based either on the Multi-attribute Utility Theory for cooperation with chosen retail chains under or Outranking Methods (Behzadian et al.,2010) . given constraints (Pohekar, Ramachandran, 2004). In this paper, we focus on outranking methods. The analysis will be made through multi-attribute These methods are based on pair-wise outranking decision-making methods. assessments and, having determined for each pair of alternatives whether one alternative outranks MATERIALS AND METHODS another, these pair-wise outranking assessments can The multi-attribute decision-making methods be combined into a partial or a complete ranking were used as the main scientific methods. (Corrente, et al., 2013). The most popular families of Multicriteria decision-making problems can be the outranking method are ELECTRE, TOPISIS or divided into certain main groups according to PROMETHEE. In this paper, PROMETHEE II and V the definition of the feasible set of alternatives. are used for our analysis of customers’ preferences The first is the case when we have a finite number and also a customers’ preferences model under of criteria, but the number of feasible alternatives constraints is presented. The PROMETHEE is infinite (the alternatives being determined methods used in our analysis will be briefly outlined by the system of the requirements constraints). in the following section. These problems belong to the field of multiple The implementation of the PROMETHEE criteria optimization. On the other hand, the type (Preference Ranking Organization Method of problem, when the number of criteria and for Enrichment Evaluation) method requires alternatives is finite, and the alternatives are knowledge of the criterion matrix (1), weights of explicitly given, are called multi-attribute decision- the criteria and preference functions of criteria making problems (MDMP). The theory of MDMP with their parameters for measuring the strength is very well-established, and the possibilities of real of the preference of the pairs of alternatives with applications (evaluation of investment alternatives, respect to the given criterion. The PROMETHEE evaluation of the credibility of bank clients, method can provide a partial ranking of alternatives the rating of companies, consumer goods evaluation (PROMETHEE I) or complete alternative and many others) are very large. We know relatively rankings (PROMETHEE II, III). The procedure of many different methods e.g. PROMETHEE, the PROMETHEE II method can be summarized as ELECTRE, (see e.g. Leyva-Lopez, Fernandez- follows. First, the alternatives are compared in pairs Gonzalez, 2003; Cheng et al. 2014). The multi- for each criterion. The preference for the alternative attribute decision-making problem is usually is expressed by a number from the interval [0, defined by a criterion matrix as shown below: 1] (0 for no preference or indifference and 1 for strict preference). The preference function YY12 Yk Fi relating the difference in performance to Xyy1 11 12 y1k preference is selected by the decision-maker. Next, a multicriteria preference index is formed for X2 yy 21 22 y2k (1) each pair of alternatives as a weighted average of the corresponding preferences for each criterion. X yy y n n12 n nk Impact of Consumer Preferences on Food Chain Choice: An empirical study of consumers in Bratislava 295 The PROMETHEE V method procedure can be π The index (X i , X j ) expresses the preference summarized as follows: of alternative Xi over alternative Xj considering all Let {X i ,i =1,2,...n} be the set of possible criteria and can be defined as: alternatives and let us associate the following variables to them: k w F X , X ∑ i i ( i j ) 1 if X is selected, = π = i 1 (2) x = i (X i , X j ) k i (6) 0 if not. ∑ wi