Влияние маркетинговых стимулов на потребителя

Results

Sample

42 respondents answered the questionnaire distributed via a social network in March 2015. At the first interaction there were identified 4 observations with considerably lower ratings on all the dependent variables. At the consequent interactions these observations showed the same pattern. These 4 outliers all being in the control group were deleted from the sample. The analyses proceeds with 38 observations: 12 observations in the Control group, 12 observations in the Treatment 1 group, and 14 observations in the Treatment 2 group.

ANCOVA

To analyze the data, ANCOVA is used. The choice of the analytical tool is driven by the fact that there may be baseline differences between those in treatment and control groups at the Interaction 1. An imbalance between groups at baseline leads to the biased estimation of treatment effects at the following interaction when the data are analyzed using mixed-design ANOVA. Thus, a set of 3 (control and 2 treatment groups) x 3 (interaction) repeated-measures ANCOVAs was run on each of the consumer response indicators to test hypotheses using methods appropriate to longitudinal studies of relationship development in the marketing literature (Aaker, Fournier, Brasel, 2004). Simple effects that examined the nature of each interaction at single points in time were run; two-tailed tests were used. Means are provided in Table 2; Table 3 presents the simple effects tests.

Table 2. Descriptive Statistics on Consumer Response Measures (Means and Standard Deviations)

Table 3. Simple Effects Analysis Using A General Linear Model (With Repeated Measures) Procedure

The analysis reveals that the Treatment 1 group reacts less negatively to price increase than the Control group (.55**). While the Treatment 2 group rapidly shrinks their buying intentions only when they are notified of the tactic usage (- .47*).

The Treatment 1 group modifies their product attitude in a more negative direction when faced with downsizing (- .35*), and do not change their response when they get external information which confirms the usage of a tactic. The Treatment 2 group did not show a significant differences from the Control group in product attitude throughout the interactions (coefficients before the product attitude variable is insignificant in all regressions).

Price unfairness have a tendency to raise in all three groups equally from Interaction 1 to Interaction 2. There are no significant coefficients before both treatment dummy variables, which shows that treatments do not deviate from the main tendency. Secondly, there is significant leap in pricing unfairness perception in the Treatment 2 group (1.33***) as compared to the Control group, which means that consumers who do not immediately detect the product downsizing increase their pricing unfairness perceptions rapidly upon an external notification.

t-test

To test whether there are differences in the persuasion knowledge among consumer treatment groups, a simple t-test for mean difference between two independent groups was accomplished. Two-tailored t-test for two independent groups provides the following statistics: t = - 0.35, df = 24. The null hypothesis about mean equivalence is not rejected (p >.10). Thus, there are no significant differences in the persuasion knowledge between consumers who are able and unable to detect the product downsizing by themselves. So the hypothesis 7 is not supported for the current sample.

In general, the study can contribute to the existing research in several ways. Firstly, it deepens the understanding of price framing by interpreting the existing research contradictions through the introduction of consumer ability to detect a misleading tactic (i.d. product downsizing) as a moderating variable. Secondly, it links a consumer ability to detect a misleading tactic with the level of consumer persuasion knowledge.

In particular, the analysis revealed that even when consumers are able to detect the product downsizing, they tend to err in their judgments regarding the price change and underestimate the scope of price increase. That could be driven by the limited abilities to conduct valid mathematical calculations when both the nominator and denominator (that is, product size and total package price) change. Even in the absence of product downsizing, consumers did not provide a valid evaluation of price change scope, and product downsizing being a more mentally challenging way to frame a price change accelerates the tendency to make mistakes among consumers.

The study identified that consumers who do not immediately detect the product downsizing increase their pricing unfairness perceptions and decrease buying intentions rapidly upon an external notification. As the same effect is not observed for the price unfairness construct, it can be assumed that price and pricing unfairness should really be treated as separate constructs, which is propagated in some academic literature on consumer fairness judgments (Haws, Bearden, 2006).

The study did not reveal a significant difference in the level of consumer persuasion knowledge among consumers who were able and unable to detect a product downsizing. That could raise the questions on the validity of the persuasion knowledge scale used in the study and appeal to the development or adaptation of other scales which are more relevant to the purposes of the study. The possible alternative is the Pricing Tactic Persuasion Knowledge (PTPK) scale developed by Hardesty, Bearden, and Carlson (2007) which tests more objective, rather than subjective persuasion knowledge in the domain of pricing by testing consumer knowledge of concrete pricing tactics used in a particular market.

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