These are mostly impressionistic statements or phrases that are subject to individual interpretation. The former have been called subjective claims, which contain emotional or subjective claims of both tangible and intangible aspects of a product, 17 whereas the latter are considered to be more objective claims, that are verifiable by the marketers, consumers or a third party.
H1a: Objective messages will show higher recognition scores than descriptive messages. H1b: Objective messages will show higher actual coupon redemptions than descriptive messages. H1c: Objective messages will show higher future purchase intentions than descriptive messages. On the other hand, it is also expected that some amount of incongruity in the situation such as interruption can provide enough motivation and arousal to the user to be able to remember, process, positively evaluate and respond to the message. Hence, messages that reach and interrupt the consumer when they are actively engaged will be more likely to be remembered and responded to.
For the rest of the paper, messages sent in active situations will represent the interruptive and messages sent in passive situations the non-interruptive messages. H2a: Messages in active situations will show higher recognition scores than messages in passive situations. H2b: Messages in active situations will show higher redemptions than messages in passive situations.
H2c: Messages in active situations will show higher purchase intentions than messages in passive situations. In Active Situations, H3a: Objective messages will show higher recognition scores than Subjective messages. H3b: Objective messages will show higher redemptions than Subjective messages. H3c: Objective messages will show higher future purchase intentions than Subjective messages. In Passive Situations, H4a: Subjective messages will show higher recognition scores than Objective messages.
H4b: Subjective messages will show higher redemptions than Objective messages. H4c: Subjective messages will show higher purchase intentions than Objective messages. Customers of two major national fast food chains were signed up for receiving text coupons on their mobile phones, and users agreed to receive between four and six messages a month. Each message contained coupons for redemption at the company outlets. A sample of responded to this survey.
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Sample description. The sample of customers who participated in the field experiment was 47 per cent men and 53 per cent women. The age ranged from 18 to 63, with a mean of Educationally, 17 per cent had high school or less education, 57 per cent had undergraduate degrees or vocational training, and 25 per cent had graduate education.
In addition, Stimulus material. Sm Chips with filling and nutritious Queso! Sm Chips with 4oz Queso that has 9g of Protein! Understanding message impact. The individual customer choice decision, whether to redeem a coupon or not, is a binary choice variable and thus we use logistic regression to model the binary decision.
Utility for consumer. The indirect utility obtained by a customer i from redeeming a coupon , U i , is expressed as follows: Open image in new window. The representative utility, V i , of a customer i redeeming a coupon is given as follows: Open image in new window.
The models for memory and future purchase intention are expressed by the following equation: Open image in new window. Probability of redemption. We model the probability that a customer will redeem a coupon as a binary logit model. Accordingly, the probability that a customer i will redeem the mobile coupon j can be expressed as follows: Open image in new window. The likelihood, L , can be written as follows: Open image in new window. The overall redemptions, recognition scores and future purchase intentions of customers in different experimental conditions are summarized in Table 1.
From Table 1 , we note that objective advertising messages or marketing messages that contain factual content have a greater percentage of coupon redemptions. In particular, objective messages have a 7. These summary statistics present model-free evidence that objective messages have a greater coupon redemption rate and also aid in better recall of the products, product attributes and product price. Table 1 Effect of message type and situation on redemption, recognition and intentions. Turning our attention to the effect of the situation a consumer is in at the time the marketing message is received, we find from Table 1 that when consumers are engaged in active situations at the moment the mobile message is received, coupon redemption rate is significantly higher than when consumers are engaged in passive situations Average recognition of the product, attributes and price is also greater when consumers receive mobile coupons in active situations than when they receive coupons in passive situations 2.
Interaction effect. Table 1 also provides summary statistics related to the interaction effect between type of message objective versus subjective message and type of situation active versus passive situation. Objective messages that were received in active situations yield a greater number of coupon redemptions than objective messages in passive situations Furthermore, subjective messages received in active situations also result in more coupon redemptions than subjective messages received in passive situations In a similar vein, objective messages received when consumers are involved in active situations led to higher average recognition scores spanning product, attribute and price recall variables than the corresponding consumer recognition scores for objective messages received in passive situations 3.
For this interaction effect, future purchase intentions were also higher when objective messages were received in active situations 6. Effect of message and situation. Parameter estimates. As described in the model section, we estimate three models to assess the effect of message type and situation on 1 likelihood of coupon redemption, 2 recognition and 3 future purchase intentions.
Before discussing the results from our estimation of these three main models, we estimated a series of alternative models wherein instead of all the variables of the proposed models, we included control variables only and compared the model fit from this model with the ones wherein we add the main effects and the proposed interaction effects in our models.
This allows us to assess the model fit of the various models and ensures that the variables that are added to the control variables improve the model fit and thus the performance of the models. Control effects. We include several control variables in the models we estimate. These include demographic characteristics of consumers such as gender, age and income level. These control for any differences in coupon redemption, memory and future purchase intentions that may occur across males and females, different age groups and income levels. We believe these control effects sufficiently capture differences in response to marketing messages that occur across different segments of population.
In the memory and future purchase intention models, we also include a control variable for coupon redemption that controls for any differences in recognition and purchase intentions across consumers who have redeemed the coupon received and the consumers who have not redeemed the coupon received.
After controlling for these variables, we are able to examine in a clean manner the main effects of our variables of interest, namely, type of mobile messages and type of consumer situation. Model performance improvement. As we can observe from Table 2 , the model fit in terms of log likelihood numbers improves for all three models ie coupon redemption, average recognition and future purchase intentions as we include the main effects and interaction effects that test our hypotheses in an incremental fashion.
In other words, results from Table 2 demonstrate that the inclusion of main and interaction effects in control variables-only models helps improve the performance of the models, and that these variables truly help capture the underlying effects of message type and situation on our dependent variables. Table 2 Model fit statistics. We now present results from the estimation of our proposed models.
These results are presented in Table 3.
Our first set of hypotheses H1a—c state that customers who receive objective messages that contain more factual information as opposed to information that is open to subjective interpretations will exhibit higher coupon redemption rates, demonstrate greater recognition and have increased future purchase intentions. From Table 3 , we observe that the coefficients corresponding to the message type which is coded as 1 if the message received is objective in nature and 0 otherwise are positive and significant for all three models.
Thus, H1a—c are strongly supported. This suggests that consumers exhibit greater positive response to messages with more objective content and may therefore prefer to receive such messages. This finding is also in conformance with the finding from the model-free evidence presented earlier in the paper. Table 3 Effect of objective versus subjective messages on coupon redemption, memory and future purchase intentions.
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Hypotheses H2a—c state that in active situations, consumers are more likely to respond to mobile coupons and thus are likely to exhibit a greater likelihood of positive behaviours such as coupon redemption, recall and future purchase intentions. Our argument for this set of hypotheses rests on the premise that in active situations, consumers may be more stimulated and thus may be more aware of information presented to them. This increased awareness and arousal can lead to more positive behaviours that a marketer may be able to take advantage of by sending appropriate messages to consumers in such situations.
We indeed observe such effects, as shown in Table 3. The coefficients corresponding to the variable active message are indeed positive and significant for our three models, thus providing strong support for our second set of hypotheses. Objective messages in active situations. Our final set of hypotheses relate to the interaction effects between message type and individual situation H3a—c. In particular, we hypothesize that effect of objective messages is greater when consumers receive these messages in more active situations. We indeed find support for this set of hypotheses. Our results from Table 3 suggest that the effect of objective messages is enhanced when these messages are consumed in active situations.
The interaction coefficients between objective message and active situation are positive and significant for all three models.
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Since both message type and situation are indicator variables that take the value 1 for objective message and active situation and 0 otherwise, we cannot include interaction effects between subjective message and passive situation, which could lead to multicollinearity issues and, hence, we are unable to test hypotheses H4a—c using our models. Redemption and recognition. However, we can gather some insight from the summary statistics table, Table 1 , on the interaction between subjective messages and passive situations.
We find limited evidence for this set of hypotheses from the information presented in Table 1. In passive situations, while subjective messages can lead to greater future purchase intentions than objective messages, it is the objective messages that yield greater coupon redemption rates and average recognition scores. Thus, we have model-free evidence for only H4c, while H4a—b are not supported in our data. Purchase intentions.
As for the results regarding our control variables, we find no differences across age and income level across the three models. Gender is significant for coupon redemption and memory models while it is insignificant for future purchase intention models. Coupon redemption is positive and significant for memory and future purchase intentions, which means consumers who have redeemed the received coupon are likely to have better recognition scores regarding product, attributes and price, and are also likely to report positive future purchase intentions.
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