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Consumer Behaviour Analysis in Wendy’s International, INC. Report

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Introduction

Researches in consumer behavior posit that consumers constantly process the available information to make informed choices regarding purchase decision (Zaichkowsky, 1985). The fast-food industry has posted considerable growth in the last decade (Meyers & Wallace, 2003). Customer perception regarding a fast-food chain is a determinant factor in their decision-making process of selecting the services of the chain. Research has shown that fast-food chains are preferred by customers to full-service restaurants (Brumback, 2002). But in the face of increasing competition, the chains have to be constantly aware of the changing customer presences and demands which mold their criteria of choosing a service.

The increase in competitive pressure from other industry segments poses serious challenges for traditional fast-food chains. Even McDonald’s, the largest restaurant chain in the world, has been struggling of late. McDonald’s has posted declines in profits for six of the last seven quarters (Zuber, 2001, p. 55). A number of chains have responded with the introduction of new products. Burger King recently added the enormously popular Chicken Whopper to its menu. Taco Bell pioneered the Zesty Chicken Bowl while Hardees currently is pushing its new Six Dollar Burger which sells for $3.95 (Horovitz, 2002, p. 2A).

As a strategy, new product introductions are notoriously risky (witness McDonald’s Arch Deluxe) and often do not tackle the core problems that fast-food chains confront. In order to address the faltering share in the food business, fast-food establishments need to evaluate consumer preferences in an ever-changing competitive environment. So it is important to find out the factors that influence the customer perception and the factors that influence purchase decisions in fast-food joints. Apart from this, the fast-food chains need to identify a target segment that they feel will be more loyal and easier to capture in this highly competitive market.

A number of studies have attempted to identify the attributes that influence consumer choices. An economic analysis of the fast-food sector explored the growth in demand for fast food. The study found that “convenience and accessibility” were two important factors that fueled industry growth. Fast-food joints are typically characterized by the convenience it offers. In today’s pervasive marketplace, consumers need not travel far to find a fast food outlet. This greater availability of fast-food outlets results in a decrease in the full price of obtaining a meal, which induces greater consumption (Jekanowski, Binkley, & Eales, 2001, p. 58).

Other studies have been narrower, focusing on those factors that affect consumer choices over individual fast-food chains. A recent study analyzed the role “corporate identity cues” plays in creating a corporate image in the minds of consumers of fast food in South Africa. “A key finding was made that joint customer service and employee dimension, was rated as the most important factor in the choice of fast-food restaurants” (Van Heerden, Schreuder, & Gouverneur, 2000, p. 125).

This paper tries to ascertain the factors that determine customer’s preference and choice of a fast-food chain. The constructs that are used to determine the customer perception influencer are quality of service, cleanliness, the services that are provided, price, and convenience. These are used to determine how these factors influence a customer’s decision to choose Wendy’s fast-food chain over and above other fast-food restaurants. Demographic segmentation is done in order to ascertain the customer’s purchase decisions from a fast-food chain.

The focus of this research paper is Wendy’s International, Inc., which is one of the world’s most successful restaurant operating and franchising companies, with more than 6,300 Wendy’s Old Fashioned Hamburgers restaurants in North America and more than 300 international Wendy’s restaurants. The research questions that are posed from our analysis are:

  • Analyze the most important factors for choosing a fast-food restaurant
  • Analyze differences in customer perceptions of Wendy’s competitors
  • Analyze Wendy’s customers’ profile
  • Make recommendations on how the fast-food market could be segmented and what should be Wendy’s target group
  • Compare Wendy’s major competitors and prepare a customer profile of each competitor
  • Determine the relationship between fast food selection factors and frequency of fast food purchasing.

In the next section, we do a brief study of the previous researches on fast-food restaurants through a literature review.

Literature review

Customer’s decision making regarding restaurants depend primarily on service encounters and involve their interaction between quality of the food, quality of service, cleanliness of the restaurant, service personnel, etc., prices of the product and services, and the convenience with which the product and service are received (Edwards & Meiselman, 2005). In consumer research, particular attention is paid to the role of individual characteristics (e.g., age, gender, income, education) in consumer decisions such as brand and store choice.

Methodology

The research is a quantitative type of research. Data has been collected through a survey questionnaire. The sample of the survey has been selected randomly from the population. In total 100 responses were collected. The questionnaire was highly structured and contained standard itemized rating scales measuring the importance of store and product attributes (Zikmund, 1997) as well as categorical indicators of individual characteristics.

The questionnaire has been divided into two sections. The first section gathers information regarding the respondent’s eating out habits, restaurant choices, and the factors that influence his/her preference of a food chain based on quality, service, price, cleanliness, and preference of location. The second section asks for demographic information for segmentation analysis. Demographic information includes age, income level, gender, family size, educational level, and occupation.

In order to ascertain which factors are ranked best in which food chain, the questionnaire asks the respondents to indicate the level of importance of a variety of attributes in selecting a fast food restaurant on a 5-point Likert scale ranging from 1 to 5 (1 is very unimportant and 5 is very important). The variables are quality, cleanliness, service, price, and convenience of location. The survey also asks the respondents to measure their level of satisfaction for the fast-food restaurant that they patronize most often for the same twelve variables on a scale of 1 to 5 (1 is poor and 5 is excellent). Respondents are also asked to identify which fast food restaurant they visit most often.

Then respondents were instructed to rank their preference of the fast-food joints vis-à-vis the food chains under consideration. The fast-food restaurants that were selected are Burger King, McDonald’s, and Wendy’s, Arby, and Checkers.

Variables are not measured in strict quantitative methods. In addition, the variables exhibit different metric properties. More specifically, the two groups of important variables have an ordinal operationalization while some individual characteristics (e.g., gender) have a purely qualitative character.

Factors influencing customer perception and decision choosing a fast-food restaurant are done by analyzing the reasons which are perceived to determine the choice of service.

Data Analysis

The demographic details of the sample are shown in table 1. The sample thus collected has a higher percentage of female respondents which comprised of 65 percent of the respondents. 71 percent of the respondents are married, rest are either unmarried or divorced. The majority of the respondents have a family size of three or above. The age group of the respondents is clustered more for 25-40 years of age. The level of education is specifically high school graduates or belongs to some college.

Table 1: Sample Demographics.

Frequency
Gender Male 35
Female 65
Marital Status Married 71
Never married 23
Divorce/separated/widowed 6
Family Size One person 14
Two people 10
Three people 26
Four people 29
Five or more people 21
Age 18-24 6
25-40 85
41-60 5
60+ 4
Formal Education Less than high school 19
High school graduate 38
Some college 29
College graduate 14

The first part of the analysis deals with determining the factors which affect a customer’s decision in choosing a fast-food chain. The analysis is done by simple descriptive statistics. The mean scores of the factors which affect the choice of fast-food chain selection are shown in the ascending order of customer preference in table 2. The results show that convenience of location has the lowest mean of 3.32 and price has the highest mean of 3.40.

Table 2: Descriptive Statistics.

Mean Std. Deviation
Convenience of Location 3.32 1.270
Service 3.36 1.283
Cleanliness 3.39 1.127
Quality 3.40 1.155
Price 3.40 1.303

Table 3.

Quality Cleanliness Service Price Convenience of Location
Mean Mean Mean Mean Mean
How often do you eat in fast-food restaurants? Once a month or less often 3 4 3 3 3
2 or 3 times a month 3 3 3 3 3
once or twice a week 4 4 4 4 3
three or more times per week 3 3 3 3 3
Which meals do you typically eat in a fast-food restaurant? breakfast 3 3 3 3 3
lunch 3 3 3 3 3
dinner 4 3 4 4 3
other 4 4 4 4 4
do not eat in a fast-food restaurant 4 4 3 4 3

Table 3 compares the means of the frequency of eating in fast-food restaurants and the meal which customers have in a fast-food chain is analyzed with the five factors of customer perception influencers. The table shows that cleanliness of the restaurant is the most important factor for customers who visit the stores once a month, and for customers who visit the stores once or twice a month, they believe that quality, cleanliness, service, and price are the most important factors on which their decision of a choice of a fast-food chain would rest on. The other two categories did not provide any significantly different results.

While analyzing the choice of the meal of a customer and factors influencing their decision, we see that their customers who visit the restaurants to have breakfast or lunch do not have any preference amongst these factors. But customers who have dinner, other categories, and those who do not eat at fast-food restaurants feel that quality, service, and price are the main determining factors of choosing a fast food joint. The category ‘others’ only feel that convenience of location is also an important influencer.

Now we analyze the second research area which tries to analyze the perception that Wendy’s competitors have in customers’ minds. To do this we analyze the questions related to the factors that influence the overall choice of fast-food chains. Here the responses were taken as 1 as not at all preferred to 5 as very much preferred. First considering the case of McDonald’s in table 4 which shows that quality is the main factor that influences the choice of the customer while considering the fast-food chain.

Table 4.

Mean Std. Deviation
McDonald – Price 3.25 1.336
McDonald – Cleanliness 3.28 1.303
McDonald – Convenience of Location 3.29 1.175
McDonald – Service 3.42 1.257
McDonald – Quality 3.47 1.352

Second, we consider table 5 in analyzing the factors which gain prominence in choosing Burger King. The mean scores for the factors show that quality, cleanliness, and convenience of locations are the main reasons for choosing Burger King.

Table 5.

Mean Std. Deviation
Burger King – Price 2.96 1.247
Burger King – Service 3.06 1.399
Burger King – Convenience of Location 3.15 1.282
Burger King – Cleanliness 3.48 1.227
Burger King – Quality 3.66 1.183

Third, as table 6 shows, cleanliness, the convenience of location, and quality are the main three factors that influence customer choice while considering Checkers.

Table 6.

Mean Std. Deviation
Checkers – Price 2.96 1.255
Checkers – Service 3.29 1.149
Checkers – Quality 3.30 1.202
Checkers – Convenience of Location 3.30 1.219
Checkers – Cleanliness 3.32 1.230

Table 7 shows that the top three reasons for choosing Arby’s are contingent on factors such as quality, cleanliness, and service.

Table 7.

Mean Std. Deviation
Arby’s – Price 2.96 1.392
Arby’s – Convenience of Location 3.24 1.240
Arby’s – Service 3.32 1.238
Arby’s – Cleanliness 3.37 1.244
Arby’s – Quality 3.39 1.246

Clearly, after analyzing the factors that influence the decision of customers in choosing Wendy’s competitors most common reasons that we derive in all the cases are quality and cleanliness. so it can be said that convenience of location is no longer a determinant factor for choosing a fast-food chain anymore. Due to increased competition and increased availability and options, customers vie for other factors such as quality and cleanliness which influenced the customer’s decision in choosing a full-service restaurant.

The next area of research is Wendy’s customer profile. This is done by comparing the

Table 8.

Frequency of eating at Wendy’s
once a month or less often 2 or 3 times a month once or twice a week three or more times per week
Column N % Column N % Column N % Column N %
Gender male 21.1% 38.5% 39.5% 33.3%
female 78.9% 61.5% 60.5% 66.7%
Marital Status married 73.7% 73.1% 72.1% 58.3%
never married 15.8% 19.2% 23.3% 41.7%
divorce/separated/widowed 10.5% 7.7% 4.7% .0%
Employment Status fulltime 31.6% 46.2% 34.9% 16.7%
part-time .0% 3.8% 7.0% 16.7%
retired .0% .0% .0% .0%
student 63.2% 34.6% 53.5% 41.7%
homemaker .0% 3.8% 2.3% 25.0%
unemployed 5.3% 11.5% 2.3% .0%
Household Annual Income $30,000 or less .0% 3.8% 2.3% .0%
$30,001 to 50,000 5.3% 3.8% 18.6% 33.3%
$50,001 to 75,000 89.5% 57.7% 55.8% 41.7%
$75,001 to 100,000 5.3% 30.8% 18.6% 16.7%
$100,001 to 150,000 .0% 3.8% 4.7% 8.3%
$150,001 and over .0% .0% .0% .0%

From the sample under study, we see that the profile of the customers who visit Wendy’s mostly are married females, working full-time or a student and belonging to a household with income $50,000 to 75000. But this cannot be statistically confirmed.

When the goal is to group similar data items into subsets clustering or segmentation are used. For example, one may want to group data elements by variables such as sex, race, age, income, etc. Or one may want to summarize several such demographic variables into two or three conceptual ones that provide the same information. Cluster and factor analyses are two statistical methods frequently employed in these types of problems. On the other hand, groups or clusters may be pre-specified. In such case, specific group characteristics (variables) may be sought instead, and discriminate analysis becomes an appropriate method.

Factor analysis attempts to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. Factor analysis is often used in data reduction to identify a small number of factors that explain most of the variance observed in a much larger number of manifest variables.

Table 9: Factor Analysis.

Correlation Matrix
Gender Marital Status Family Size Age Formal Education Employment Status Household Annual Income Frequency of eating at Wendy’s
Correlation Gender 1.000 .151 .332 .018 -.171 -.100 .032 -.094
Marital Status .151 1.000 .084 -.015 -.131 -.014 .178 .004
Family Size .332 .084 1.000 -.035 .028 -.174 .031 .026
Age .018 -.015 -.035 1.000 -.116 .062 .165 .242
Formal Education -.171 -.131 .028 -.116 1.000 .175 -.076 .031
Employment Status -.100 -.014 -.174 .062 .175 1.000 -.131 .020
Household Annual Income .032 .178 .031 .165 -.076 -.131 1.000 -.033
Frequency of eating at Wendy’s -.094 .004 .026 .242 .031 .020 -.033 1.000
Sig. (1-tailed) Gender .067 .000 .428 .045 .161 .375 .175
Marital Status .067 .202 .442 .097 .446 .039 .486
Family Size .000 .202 .366 .390 .042 .379 .398
Age .428 .442 .366 .125 .270 .050 .008
Formal Education .045 .097 .390 .125 .040 .225 .379
Employment Status .161 .446 .042 .270 .040 .097 .423
Household Annual Income .375 .039 .379 .050 .225 .097 .372
Frequency of eating at Wendy’s .175 .486 .398 .008 .379 .423 .372
Rotated Component Matrix
Component
1 2 3 4
Family Size .851 .053 -.076 -.022
Gender .724 -.070 .209 -.127
Frequency of eating at Wendy’s .069 .791 -.154 .109
Age -.088 .772 .214 -.103
Marital Status .223 -.084 .774 .133
Household Annual Income -.077 .127 .624 -.262
Employment Status -.217 .070 .160 .788
Formal Education .039 -.048 -.290 .668
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
Communalities
Initial Extraction
Gender 1.000 .589
Marital Status 1.000 .674
Family Size 1.000 .733
Age 1.000 .660
Formal Education 1.000 .534
Employment Status 1.000 .699
Household Annual Income 1.000 .480
Frequency of eating at Wendy’s 1.000 .666
Extraction Method: Principal Component Analysis.
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 1.611 20.143 20.143 1.611 20.143 20.143 1.365 17.056 17.056
2 1.312 16.406 36.548 1.312 16.406 36.548 1.260 15.748 32.804
3 1.108 13.851 50.399 1.108 13.851 50.399 1.218 15.224 48.027
4 1.003 12.538 62.937 1.003 12.538 62.937 1.193 14.910 62.937
5 .954 11.928 74.866
6 .858 10.731 85.597
7 .580 7.247 92.844
8 .573 7.156 100.000
Extraction Method: Principal Component Analysis.
Component Matrix
Component
1 2 3 4
Gender .670 -.203 .278 .148
Formal Education -.472 -.240 .368 .344
Age .080 .786 .185 -.036
Frequency of eating at Wendy’s -.106 .591 .547 -.078
Household Annual Income .391 .395 -.382 .159
Family Size .557 -.256 .594 .060
Employment Status -.493 .095 .082 .664
Marital Status .465 .123 -.238 .621
Extraction Method: Principal Component Analysis.
a. 4 components extracted.
Component Transformation Matrix
Component 1 2 3 4
1 .687 -.025 .493 -.534
2 -.325 .864 .367 -.120
3 .633 .494 -.494 .334
4 .152 -.098 .616 .767
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

The correlation matrix is represented in table 9, in the correlation matrix section. This shows that the matrix of correlation coefficients and their respective significance levels are printed below because it was requested under the “Descriptive” options. Factor analysis uses the correlation matrix to try to determine which sets of variables cluster together. The correlation matrix shows that there is a positive relationship between females is mostly married. The correlation coefficient between a variable and itself is always 1; hence, the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and below the principal diagonal are the same. Looking at the correlation between the frequencies of visiting Wendy’s we see that there is a negative relationship between gender and frequency.

This is so because females are coded as 1 and males are coded as 2 and there is a predominance of females in the sample. This implies that more percentage of males visit Wendy’s than women. The correlation with marital status, age, educational level, family size, and household expenditure are all positively related to the frequency of visiting Wendy’s. But it has a negative relation with household income. This shows that the kind of people who visit the fast-food chains. Thus, the customer profile for Wendy’s is men, aged post-forties, who have a high household income.

The factor analysis shows that the segment for Wendy’s is mostly men, who are married and belong to a family which has a lower household income. the loadings of the eight variables on the three factors extracted. The higher the absolute value of the loading, the more the factor contributes to the variable. The gap on the table represent loadings that are less than 0.5, this makes reading the table easier. We suppressed all loadings less than 0.5.

Then we analyze the cluster so formed for Wendy’s competitors. This is done again using the factor analysis method. In McDonald’s’ customers who are older and have higher household income level visit.

Clearly, the study shows that the cluster group of the external world is indecipherable to him. The research findings are thus as follows:

  • Quality and cleanliness are the two drivers which influence customer perception in making purchase decisions.
  • The factors that affect other food-chains which are Wendy’s competitors again show the quality, price, and cleanliness are the most important factors that influence customer perception.
  • From the factor analysis, we may derive that Wendy’s should target men and women who are young (25-40 years) and are married.

In the end, we determine a relation between the fast-food selection factor and fast-food purchase frequency. This is done by doing a correlation analysis of the frequency of visiting a fast-food chain and the fast-food selection.

Table 10 shows the.

Table 10:Correlations
Frequency of eating at McDonald’s Frequency of eating at Wendy’s Frequency of eating at Burger King Frequency of eating at Checkers Frequency of eating at Arby’s
Quality Pearson Correlation -.124 -.007 -.114 -.060 -.092
Sig. (2-tailed) .220 .941 .257 .555 .365
N 100 100 100 100 100
Cleanliness Pearson Correlation -.217* -.025 -.213* -.156 -.021
Sig. (2-tailed) .030 .803 .033 .122 .837
N 100 100 100 100 100
Service Pearson Correlation -.082 -.035 -.090 -.039 -.111
Sig. (2-tailed) .419 .728 .373 .697 .271
N 100 100 100 100 100
Price Pearson Correlation -.110 -.139 -.196 -.136 -.164
Sig. (2-tailed) .277 .168 .051 .179 .102
N 100 100 100 100 100
Convenience of Location Pearson Correlation .160 -.211* -.201* -.172 -.083
Sig. (2-tailed) .112 .035 .045 .087 .414
N 100 100 100 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Table 10 shows that more one eats at a fast-food joint, the quality of food becomes bad. The correlation shows that there is a negative relation between the factors and the fast-food chains.

Works Cited

Brumback, N. (2002). The Go-betweens. Restaurant Business, 101(13), 67-79.

Edwards, J., & Meiselman, H. (2005). The influence of positive and negative cues on restaurant food choice and food acceptance. International Journal of Contemporary Hospitality Management 17(4) , 332-344.

Horovitz, B. (2002). Fast-food Giants Hunt for New Products to Tempt Consumers,. USA Today , pp. 1A-2A.

Jekanowski, M., Binkley, J., & Eales, J. (2001). Convenience, Accessibility, and the Demand for Fast Food. Journal of Agricultural and Resource Economics, 26(1) , 58-74.

Meyers, M. S., & Wallace, S. (2003). FACTORS INFLUENCING THE PURCHASING FACTORS INFLUENCING THE PURCHASING. Allied Academies International Conference (pp. 51-55). Las Vegas: Academy of Marketing Studies, Volume 8, Number 2.

Van Heerden, C., Schreuder, A., & Gouverneur, M. (2000). Factors That Determine Corporate Image of South African Fast Food Restaurants. South African Journal of Economic and Management Sciences, 3(1) , 125-42.

Zaichkowsky, J. L. (1985). Measuring the Involvement Construct. Journal of Consumer Research 12(3) , 341-352.

Zikmund, W. G. (1997). Exploring Marketing Research. Fort Worth: Dryden Press.

Zuber, A. (2001). McD Restructures to Beef Up Performance. Nation’s Restaurant News, October 29, 35(44) , 1-6.

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