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Zero-value attributes

First, we checked whether reducing the value of undesirable attributes (such as fat and sodium) to zero, while holding desirable attributes constant, would lead to a higher purchase intention for this product. The focal product’s choice share with zero-value attributes was compared against the choice share of the product when the undesirable attributes were increased to one.

The results were in fact, as expected aligning with the assumptions made in this research earlier;

when attributes were increased to one, the product got bought less. Choice share of focal product Zed decreased from 39.51% to 37.78% (figure 4), moving from zero to one condition.

However, the analysis showed that the results were insignificant, therefore, hypothesis 1 is rejected.

In any case, the focal product was always compared to other option(s) which were technically objectively worse, if one was to make the trade-off, based solely on the unfavorable attributes (Appendix A).

These results go against the Zero-Comparison effect that Palmeira (2011) explains in his study, which says that a product can increase its choice share by becoming objectively inferior, increasing the level of an undesirable attribute such as fat from zero.

The main effect of attribute value on consumer choice proved insignificant, thus we will look at some alternative explanations why the focal product, did get chosen more in the zero-value condition.

A possible explanation could be based on consumer decision-making psychology research.

When the information available regarding choices increases, consumers tend to process less information and opt for a shortcut in decision making (Hauser & Wernerfelt, 1990). This trace of thought is also supported by the information overload theory which states that with the increase of available information, individuals and organizations become overwhelmed as their capacity and time to process it, is not sufficient (Schick, Gordon, & Haka, 1990).

In the one-value condition, the amount of information provided was more (every attribute had a value). This could have accounted for difficulties in making meaningful comparisons between products, thus the value of the focal product was not distinct, leading to it not being chosen.

Participants were provided with information regarding several nutritious ingredients, which may not necessarily have the same importance to the consumer’s mind as according to the

review of 59 articles from Plasek et al. (2020). This could have caused a chain effect, where people were paying less attention to the values and more to the name of the ingredient.

Perceived Healthiness

In the second analysis, Perceived healthiness was tested, to check if it mediates the relationship between having zero-value attributes and the purchase decision for this product.

The results unfolded in two ways.

Firstly, the effect of Attribute value on Perceived healthiness was not significant, therefore hypothesis 2a was rejected. We cannot conclude that having zero-value attributes will make a product perceived as healthier. Participants did not follow the ‘’the more the better’’ intuition, previously introduced by Petty and Cacioppo (1984) and later on in Berger, Draganska, and Simonson (2007). According to this line of research, the multiple components serve as a heuristic cue, affecting the consumer’s perception and decision-making. Jeong et al., (2020) state that the number of ingredients affects health perceptions. Two un-favorable attributes were reduced to zero in this research to create this line of logic in consumers’ minds, however, this was not the case.

Two possible explanations can account for these results.

First, as explained in the previous research (Tverskyand Kahneman 1991; Wong and Kwong 2005), the number zero removes a reference point, and consumers cannot compare between options in relative terms. Even though 0 grams of fat and sodium is clearly better than 5 and 72, they have trouble understanding how much better this is. The only meaningful trade-off they can do is based on the other favorable attributes (protein and fiber), which the comparing products always scored higher than the focal product. Thus, the link of which product is healthier created in the participants' minds was based on favorable attributes instead.

Second, even though the choice of unfavorable attributes to be used in this study was based on previous research by Plasek et al., (2020), participants could have had trouble understanding the meaning of these definitions such as saturated fat and sodium and their effect on healthiness.

However, an interesting note, in this case, is the result from the paired t-test. The focal product Zed did receive a higher rating overall compared to the other options. Since we already removed the explanation that zero value attributes caused this, an educated guess can be that low values (0,1) lead to a higher perceived healthiness. All the other products had higher values than 1, on the two manipulated attributes (Appendix 1). Further research can explore the validity and boundary conditions of this assumption.

The second part of the analysis, however, revealed that a higher Perceived healthiness does lead to a higher choice share, so hypothesis 2b was supported. Important to note that consumer's Health concern did not have an impact on this result, as assumed. Specifically, a difference by one unit in perceived healthiness will lead to a .677 unit increase in choice share for this product. The correlation between these two variables was significant. These results fall in line with the results from Graham, D. J., and Mohr, G. S. (2014) who state that perceived healthiness is positively related to purchase intention, which in our case is measured through consumer choice.

Choice set size

The effect of Attribute value on Perceived healthiness was not moderated by Choice set size, as the analysis discovered that there was no significant interaction between XW in the model of Y (c’4 = .017, p = .955). Therefore, hypothesis 3 was rejected. This was not as expected. It was predicted that bigger choice sets than 2, specifically 4 in this case, would lead to a higher perceived healthiness evaluation. These assumptions were based on the previous study of Levav et al. (2012) who demonstrated the significant impact that set size has on decision

making. Specifically, this study aimed to replicate the findings of Wen Mao(2020) who demonstrated that as long as the set size was bigger than two, the Zero-Comparison effect would be reduced. The goal was to reduce the zero-comparison effect, as that went against our assumptions made in this research.

Based on the Iyengar and Lepper (2000) study, people are more likely to purchase gourmet or chocolates when they are offered a limited array of 6 choices. The set size used in our research falls under this scope, therefore the Choice set size cannot be the explanation for why the purchase frequency of the focal product was lower and did not follow the intended path.

A possible explanation could be the fact that, as the number of options the participants were facing increases, consumers’ ideal points shift in a way that makes it harder for them to attain (Chernev, 2003b; Schwartz et al., 2002). Therefore, consumers in this study could have reached the point where none of the products were fulfilling their expectations, making them engage in rushed decision-making, not fully evaluating the choice sets.

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