Wal-Mart has quickly become a worldwide retail behemoth. In the wake of their success, however, many of the Wal-Mart patrons have formed a love-hate relationship with the American-based juggernaut. Simply put, there are enough weighted advantages to shopping at Wal-Mart to dilute any ill feelings and incentives for consumers to shop elsewhere. A multiattribute attitude model exposes this phenomenon and helps explain the reasoning behind Wal-Mart’s loyal following.
It Starts With Consumer Attitude
A Wal-Mart consumer—as with any consumer—establishes certain attitudes towards the companies they frequently shop. An attitude, as defined by Solomon (2008), endures over time.
An attitude takes years to evolve, but a moment to change.
Consumers are beginning to realize the impact to the local community and economic state of their neighborhoods resulting from the success of Wal-Mart.
Cognitive dissonance explains the healthy percentage of Wal-Mart patrons that feel the stores are bad for our country, but continue to shop there (Basker, 2007). With 46 percent of Americans living within five miles of a Wal-Mart store, it is easy to understand the mix of love and cynicism towards the company. Many people believe that Wal-Mart, while good for helping consumers save money, is bad for free and competitive enterprise. Small niche retail stores cannot compete with Wal-Mart’s volume buying induced pricing.
The basic multiattribute approach for modeling attitudes uses attributes, beliefs, and weights as the basis for determining the propensity for a consumer to choose one option over another.
The Fishbein model also uses three components of attitude—salient beliefs, object-attribute linkages, and evaluation—for determining a measurable score representing a consumer’s attitude. Several attributes needed to fairly assess the popularity of Wal-Mart over several competitors include environmental responsibility and local economic sensitivity.
Using the Fishbein model, a comparison of Wal-Mart, Target, Kmart, Sears, Costco, and Sam’s Club against nine attributes shows which retail chains have the highest and lowest probability of success in a market based on specific weights assigned to the attributes. The priority, or importance, of each attribute weighted against the scored beliefs is used to calculate an overall score for each chain. The store with the highest score is recognized as having the most perceived differences in overall attitude. Table 1.1 shows how the multiattribute model can used to determine which entity has the most favorable attitude. The lowest score represents the company with a market of consumers with less disparate attitudes.
What does it mean?
The importance of each attribute carries the most impact compared to the other variables used in the Fishbein formula. Quality, variety, and product guarantees are the top three attributes in the hypothetical analysis shown in table 1.1. Companies, such as Wal-Mart, can use the results from a multiattribute analysis to help improve their image. In some situations, the information gleaned using a multiattribute model can be based on biased input. Before setting marketing direction based on multiattribute analysis, it is important to make sure the information is not skewed as a result of the halo effect (Beckwith & Lehmann, 1975).
Wal-Mart can capitalize on their advantages and perhaps add attributes to strengthen their position in the market. However, with the importance of customer loyalty and retention lurking in the shadows, it may just be smarter to concentrate efforts on the attributes deemed the most important by their target audience. There is a certain amount of tolerance with the shopping public which seems to be tested each time a new story is revealed regarding Wal-Mart’s mistreatment of employees. Target is only a few discounted prices away from winning over several Wal-Mart loyalists.
Basker, E. (2007). The causes and consequences of Wal-Mart’s growth. The Journal of Economic Perspectives [Electronic version]. Retrieved January 7, 2015, from http://www.jstor.org/stable/30033740
Beckwith, N., & Lehmann, D. (1975). The importance of halo effects in multi-attribute attitude models. Journal of Marketing Research. [Electronic version]. Retrieved December 28, 2014, from http://www.jstor.org/pss/3151224
Solomon, M. (2009). Consumer behavior buying, having, and being (8th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.