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“Discounted products and purchase intention:

The moderating role of the delivery channel, and the product type

University of Amsterdam Faculty of Economics and Business

Student: Despoina Papadopoulou Student Number: 11375701

Date of Submission: 23-06-2017 (Final Draft)

Study Field: MSc Business Administration – Marketing Track Thesis Supervisor: Kristopher Keller

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1

Statement of Originality

This document is written by Despoina Papadopoulou who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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2 ABSTRACT

Currently, the majority of retailers give consumers the opportunity to purchase their products from more than one channel; the most popular ones are the physical stores (offline) and the online stores. In many cases, the pricing strategy of the products differs across these channels, due to the different effectiveness that each one offers in terms of consumers’ purchase intention. A major part of the pricing strategy though is discounts. Price discounts have always been a common practice that managers follow in order to increase short-term product sales. However, the plethora of options that consumers have, has led them to deliver them in all channels and for every product type, in their effort to foster the responsiveness of as many consumers as possible. This study explores which channel is more effective promoting price discounts, while additionally tries to identify which product type – hedonic or utilitarian – has the most optimal fit in each channel. An online experiment was conducted and the 214 participants had to declare their purchase intention for a product in one of the eight designed conditions, where a brochure was used for the offline case and digital influencers on social media were used for the online one. Their answers were analyzed through a multiple regression process, but the main hypotheses did not give significant results. Nevertheless, the most important implication for managers is that eventually the multichannel approach of discounts delivery is the most effective one, and they should not spend the available budget to tailor promotions. Alternatively, it is better to optimize each offer to reach a greater pool of consumers. As can be expected, this research is subjected to several limitations and suggestions for further research.

Keywords: discounts, online, offline, delivery channel, utilitarian, hedonic, social media, digital influencers, purchase intention.

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3 TABLE OF CONTENTS Statement of Originality………...1 Abstract………..2 1. Introduction………...……….4 2. Theory Development………..8 3. Hypothesis Development……….13

3.1 The moderating role of the delivery channel of discounts……….13

3.2The moderating role of the product type………15

4. Methodology………....17 4.1Sample……….17 4.2Pretest………..18 4.3Procedure……….19 4.4Data Analysis………..22 5. Results………..23 6. Discussion………26 6.1 Managerial Implications……….……28

6.2 Limitations and Further Research………..29

7. References………32

8. Appendices………...39

8.1Online experiment questionnaire………...…….………39

8.2Descriptive Statistics………..49

8.2.1 Utilitarian/Hedonic Value……….49

8.2.2 Channel of Promotion………...50

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4

1. INTRODUCTION

Profitability is considered as one of the dominant objectives of a business (Narver and Slater, 1990) and the main determinant of profitability is the price strategy that is followed (Marn and Rosiello, 1992). As a major part of the pricing decisions consists of price discounts, which also result in a change of sales and profits, managers should handle them carefully, as a separate marketing process (Dekimpe et al., 2002).

Alongside with the increasing competition, retailers have to face the expansion of the delivery channels of discounts which create even more options to promote their products and scale up sales. Unfortunately, in most cases, managers choose inefficient ways to leverage these channels concluding in greater loses than gains. According to Nielsen (2015), 67% of the annual promotions performing in U.S. do not break even. Additional evidence from the Boston Consultancy Group (2015) suggests that 20-50% of promotions do not remarkably increase sales, while 20-30% of those do not even provoke the sufficient amount of sales to cover the costs. Therefore, greater attention should be paid in the topic of price discounts in order to determine the appropriate environment where each discount strategy can yield the desirable results.

The rapid expansion of new Internet technologies has forced companies to promote their products online as well. In fact, about 76% of all customers’ shopping journeys start online, irrespectively of the actual point of sale- online or offline (IRI, 2017)

.

Hence, managers should also be aware of the effect of corresponding promotional actions performed in the digital channel. While some fears of cannibalization of the traditional channel exist, Deleersnyder et al. (2001) suggest that this is rarely the case. The explanation for this phenomenon is the variety of the target groups that prefer the one channel over the other. Consequently, more revenues can be obtained by the exploitation of both options-the offline and online channel. The point of difference of these two channels is that consumers can gain

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5 more information about price and non-price characteristics when searching online rather than offline. As a result, the price sensitivity factor is affected by the type of the product (Degeratu et al., 2000).

Besides the expansion of promotions to websites, businesses have started to focus on the promotion of their products through social media platforms. Social media have been acknowledged as one of the most useful marketing tools of 21st century since they have become not only a space for social networking, but also a unique promotion channel, giving companies the opportunity to establish their presence and increase their sales. Apart from their presence by fan pages and the general firm-generated content that they create, a relatively new phenomenon constitutes their collaboration with public figures that became popular through these platforms. As the social media trends suggest, influencer marketing and generally the collective creation of experience are gaining ground, with trust being the cornerstone among the members of the social media society (uk.kantar.com, 2017).

A recent study of TapInfluence in collaboration with Nielsen Catalina Solutions (2016) indicated that the content that digital influencers create, leads to 11 times higher sales than that of a regular digital marketing campaign. In the majority of the cases, the discounts offered through such collaborations are often presented as an exclusive advantage for the followers of the digital influencer. Shane Barker (2016), one of the most successful digital marketing consultants, demonstrates in his blog the strategy that Loot Grate and Daniel Wellington followed. In the first case Loot Grate, a company which sells subscription boxes concerning gaming and comic books, decided to collaborate with PweDiePie, the owner of the most successful gaming channel on Youtube. PewDiePie promoted a 10% discount code of a Loot Grate subscription, which eventually surged sales. Another similar example is that of Daniel Wellington watches and the firm’s collaboration with digital influencers on Instagram, following the same discount strategy. The outcome was positive as it led to sales

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6 increase, since in this way the brand reached the maximum of its target audience. Although this is a tactic that tends to become ingrained by marketers, researchers have not paid the necessary attention in the effect of price discounts on people’s purchase intention when these discounts are promoted through social media influencers. A research by Burst Media showed that marketing programs where social media influencers were involved earned $6.85 in media value on average for every $1 spent. Nevertheless, differences in product categories existed, stating that although retailers and the apparel category earned $10.48, grocers and supermarkets earnings were below average, at $4.80 (Emarketer.com, 2015). Consequently, this strategy may not be appropriate for all product types, namely utilitarian and hedonic products.

Generally, little is known so far about the effect of price discounts on consumers’ purchase intentions of utilitarian and hedonic products when they are promoted through new, non-traditional channels. Although some researchers experimented with the impact of a new channel addition on sales, no one examined the case of price discounts in these new channels and how purchase intention could be affected. Moreover, literature has paid little attention on the collaboration of firms with social media influencers to promote their products. In addition, besides the product promotion through social media per se, firms provide these people with discount codes only for their followers, but it is not scientifically tested whether this practice results in higher purchase intention and for which product type (utilitarian or hedonic) this works better.

Thus, the literature gap, that my research intends to fill, is formed in the following research question:

“How is the effect of price discounts on purchase intention influenced by the delivery channel and how is this effect different for utilitarian vs. hedonic products?”

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7 The results of this study will have significant contributions to both academic and managerial society. In the first place, literature in the field of strategic decision making will be enriched, since price discounts are a very important element of the two of the four Ps, price and promotion, the other two being product and place. Moreover, if the results are notable, they will have application in the market segmentation field, since they will help academics and researchers understand more about their target audience concentration –offline and online– and its purchase intention. What is more, given the high managerial relevance of the topic, it is likely that academics will be challenged to explore various practices that are used in social media, designed to increase sales. In this way, future marketers will have an integrated knowledge background about a medium whose potentials and advantages are still barely explored. In addition, this thesis will also contribute to the consumer behavior and psychology discipline because it will trigger the research and analysis of the reasons that an additional channel such as social media, works differently –if so– for one category of products and not for others.

As far as the business world is concerned, the contribution to managers is expected to be significant, too. Marketers will have scientific evidence of how to promote discounts through different channels and for which product category do these channels work, changing the whole marketing approach in specific discount periods. Furthermore, an increase in sales and a decrease of expenses are expected, since the online channel of the business will be exploited in an optimal way. This will also aid managers in defining a better target group for their products or even a niche market to promote them. Finally, apart from the financial benefits, all these results can potentially create a stronger bond between the customers and the brands resulting in loyalty and achievement of brand resonance.

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8

2. THEORY DEVELOPMENT

One of the most important and popular variables that both business world and academics are interested in is consumers’ purchase intention. Although purchase intention is actually a perception and not an action of the consumer, it is of a great importance, because it represents the best predictor of actual behavior (Fishbein and Ajzen, 1975). Due to its substantial significance, many academics and researchers studied this variable in a great extent in various fields (Chang and Wildt, 1994; Mela et al., 1995), as well as in the price discounts field (Neslin, 2002), aiming to contribute to its managerial implications.

Price discounts are perceived as a useful marketing instrument in order to augment both consumers’ perceptions of product value and their purchase intentions (Teng, 2009). Price discounts are defined by Mishra and Mishra (2011) as a price-based sales promotion strategy in which customers are offered the same product at a reduced price. The immediate and strong impact of price discounts on sales (Blattberg et al., 1995) classifies them as one of the few tools that are so highly effective (Heerde and Neslin, 2008). The most common types of price discounts given to consumers are coupons, rebates, in-store temporary price cuts, feature advertising, and in-store displays. The impact of these kinds of discounts is represented in a twofold aspect; the immediate sales promotion bump and the effects beyond the immediate bump (Heerde and Neslin, 2008). Moreover, besides this effect, such economic benefits can also foster favorable attitudes towards the brand and increase its awareness (Teng, 2009). In addition, when the duration of these discounts is relatively short, a significant increase in sales is observed (Blattberg, 1995). Consequently, price discounts constitute an implement that benefits not only consumers, but also retailers. Although researchers have already reached a verdict about the positive effect of price discounts on consumers purchase intention, and by extension on sales, most studies are only confined to

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9 the case of the offline delivery of discounts, meaning the physical stores. In the online world, consumers tend to be more price-sensitive since they have many tools at their disposal in order to detect deals and compare prices, hence price discounts in this context have a more positive effect (Degeratu et al., 2000). Therefore, the adoption of the online channel as a source of providing discounts and benefits to customers is necessary.

The digital era that companies are going through, commands the enrichment of their online presence; thus, firms should try to keep up with the fast pace of technology and invest in the exploration of new channels to promote their products. Evidence of prior research has shown that the Internet channel addition results in positive net-present-value-investments. This is supported by the fact that an established firm can achieve a greater financial performance if it owns only a few direct channels and adds a new online one (Geyskens et al., 2002). Moreover, research showed that the potential of an Internet channel’s performance is higher, if the channel is supported by publicity (Geyskens et al., 2002). Although most studies indicate a similar effect of both online and offline promotions on consumers’ purchase intention, specifically for the case of cross-channel ownership, online promotions significantly increase offline store traffic, but not vice-versa (Breugelmans et al., 2016). Even though managers try to retain and improve the online presence of their firm by running a website or being advertised online, new marketing communication channels thrive by the advent of Internet, namely social media.

Moving forward from traditional online and offline channels, social media play a crucial role in the marketing communication. Companies are forced-in a way- to use them in order to increase customer engagement and enhance the relationship with their target audience. Furthermore, social media can be considered as a useful tool to support or even boost sales (Karjaluoto et al., 2015). One of the most common practices is the firm-generated content in the social media platforms, which by evidence has a positive impact on customers’

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10 behavior since it increases the share of wallet, cross-buying, and the firm’s profitability (Kumar et al., 2016).

Apart from that kind of content, the user-generated one from various bloggers and digital influencers in general, who share experiences about products and brands, has already started to attract the marketers’ attention from a consumer engagement perspective. Depending on the target audience, these influencers can easily shape their followers opinion, and hence they operate as intermediates between brands and consumers. For that reason, managers can take advantage of their growing power and utilize them in order to introduce new products or to get their audience acquainted with existing ones (Uzunoglu and Kip, 2014). This study though, is going to examine the effect of consumers’ purchase intention when they are exposed not only to a simple product promotion through social media, but also to a discount code. Consequently, given the positive relationship between discounts and purchase intention and the fact that social media offer businesses the opportunity to increase their sales, this study will emphasize on the different effects that can be observed under different product types, namely hedonic and utilitarian products, in order to determine which discount strategy- online or offline- is optimal for each one. In this way managers will have scientific evidence of which channel is the most appropriate to promote price discounts for each particular product type, in order to result in sales increase due to low profit margins during promotion periods (Teng, 2009).

To begin with, utilitarian products are those which consumers purchase for their functionality in order to serve a particular purpose (e.g. microwave, toothbrush). These purchases are driven by the necessity to meet a basic need or the research of a more convenient solution to a practical problem. On the other hand, hedonic products are purchased in order to indulge oneself by means of entertainment or desire. Such products can be smartphones, designers’ brands, luxurious cars etc. (Dhar and Wertenbroch, 2000). Hence,

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11 the effects of price discounts differ in each category due to the distinctiveness of the motives that drive each purchase.

Following Chandon et al. (2000), these motives can be identified by the benefits that consumers obtain when they purchase a discounted product. In their research they illustrate six distinct benefits; three as hedonic benefits and three as utilitarian ones. In the hedonic benefits category, the opportunity of value expression is one of the components, meaning that the redemption of a discount increases ones feeling of being a smart or a good shopper and in this way it declares its personal values. Second, entertainment is another feeling that can be detected as a hedonic benefit, because discounts are fun to see or use. Third, discounts give the opportunity to satisfy the need of information and exploration. As a utilitarian benefit, the monetary savings are the most obvious one. Apart from that, discounts can also ameliorate choice convenience, since they reduce the research time and decision costs. Last but not least, the redemption of discounts can result to the acquirement of higher quality products due to their more affordable current price. In consequence, depending on the product type, some benefits are perceived as more important than others in a purchase situation.

To conclude, even though social media are a state-of-the-art tool, researchers and managers still lack the knowledge over their use and the accurate results that their strategies may have. Therefore, this study aims to analyze the effects that price discounts presented online through social media, have on purchase intention, and the product category which this strategy can potentially maximize the revenues of a firm. Figure1 visualizes the interaction of the variables that are going to be examined.

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Figure 1- Conceptual Framework

Discount price Purchase Intention

Delivery channel of discount (Online vs. Offline) Product Type (Utilitarian vs. Hedonic)

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13

3. HYPOTHESES DEVELOPMENT

3.1 The moderating role of the delivery channel of discounts

In most cases, the strategic decision to apply discounts on products aims to increase of the company’s short-term sales and it is considered as the most attractive and effective way to do so (Neslin, 2002). The direct impact of discounts on consumers is the creation of extra inventory of products that are consumed in a higher rate; a rate that varies over time (Ailawadi and Neslin, 1998). Thus, stockpiling is the most common result of purchasing discounted products.

The mechanism behind this strategy relies on four cases that lead to sales increase. The first one is cannibalization, which occurs when the consumer switches from the product of a certain brand to the same product of the brand, but with a different function. For example, the consumer switches from shampoo B for shiny hair to shampoo B for more volume, which is on discount. The second case is the brand switching, which occurs when the consumer purchases the product of brand B instead of the product of brand A due to its reduced price. The penultimate case regards category switching, meaning that the consumer switches from a product from another category to brand B, which can also enshrouds a complementarity effect. In other words category switching may also imply increase of sales for products that are bought together. So if the one of the two is on discount, the sales of the other one will rise as well. The last case is the store switching case, where the consumer prefers the store that offers the discount (Heerde and Neslin, 2008).

Another important aspect of the price discounts effect on purchase intention, besides product substitution, is time. The period that a discount occurs can result to purchase displacement in two ways; acceleration and deceleration, meaning that the consumer either expedites the purchase or postpones it in order to benefit from the discount. So we can realize that the consumers’ purchase intention of discounted products is influenced in three ways;

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14 category incidence, brand choice and purchase quantity (Heerde and Neslin, 2008), with time being an important factor that controls them.

In an online environment, the influence of price discounts on consumers’ purchase intention can be much more augmented due to several reasons. Firstly, the perceived transaction costs are mitigated online (Kohli, Devaraj and Mahmood, 2004). These costs comprise time saving and the zero transfer costs that occur when shopping in physical stores, while they can lead in a larger purchased quantity (Stone, Hobbs and Khaleeli, 2002). Secondly, due to the absence of time constraints, consumers are more relaxed, since they are not under the pressure of the opening and closing hours of physical stores (Kim, Fiore and Lee, 2007), and that can lead to a proper evaluation of products, which can consequently result in brand or category alteration. Furthermore, the available information online is diffused and consumers can obtain knowledge for both price and non-price related characteristics of products (Alba et al., 1997), which can also result in a better deliberation of them. Finally, the easy access to online reviews can enhance the probabilities of purchase because trust in the online retailer can be based on objective critiques and that in turn decreases the perceived risk of an online transaction (Jarvenpaa et al., 2006; Kim and Peterson, 2017). Therefore, if businesses target at securing long-term sales, trust building with potential customers is an imperative component of repeated purchase intention (Hu et al., 2003). Consequently, managers strive to achieve this gain of trust in order to form favorable opinions about their products and influence consumers’ purchase decisions.

This change of influence and opinion in a social context has been studied by Kelman (1961), who suggests that compliance is the surface level of opinion change. In this situation a person desires a favorable outcome from the source of influence and for that reason adopts the influencer’s opinions and beliefs. Another aspect that the researcher proposes is the identification process, in which an individual aspires to become like the influencers, and so

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15 they embrace anything related to them, from attitudes and lifestyle to products use. In support of this theory, literature has illustrated that credibility mainly derives from peer endorsers and experts, who in turn enhance consumers’ perceptions of the quality of the products (Kang and Herr, 2006, Kapitan and Silvera, 2015).

Regarding the case of social media, digital influencers fall in the category of “authority”, as a strategic weapon of influence (Cialdini, 2001); hence they are perceived by consumers as a credible source of information. The influence that they have on their followers, can lead the latter to easily embrace their advices and recommendations, and result in an increase of purchase intention of the products that they promote. Especially in the case of discount offering, the followers feel more exclusive and thus it is easier to proceed to a purchase (Djafarova and Rushworth, 2017). According to Modigliani and Rochat (1995) this tactic is yielding because the concept of obedience to the authority is one of the basic components of a social community. Consequently, taking into account all the aforementioned theories, the main expectation of this research is to observe a higher purchase intention when a discount in a product’s price is delivered through an online channel than when it is presented in an offline one.

H1: The effect of a price discount on purchase intention is stronger when this discount is

presented in an online context, compared to an offline context.

3.2 The moderating role of product type

An additional aspect that this research seeks to explore is whether this effect is different over the two product types; utilitarian and hedonic products. In order to find support for this phenomenon we will analyze the benefit congruency framework of sales promotion effectiveness (Chandon et al., 2000). This framework proposes that the sales promotion effectiveness is determined by the utilitarian or hedonic nature of the benefits it delivers and the congruency these benefits have with the promoted product. Accordingly, if someone

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16 delves for value expression, entertainment or exploration (hedonic benefits) and through the price discount is given the opportunity to achieve one of these three, the purchase intention will be higher. This is also the case for individuals, who seek for financial savings, higher product quality or improved shopping experience (utilitarian benefits). Moreover, the purchase of a product with a stronger hedonic dimension offers mostly hedonic benefits, and as can be expected, utilitarian products offer utilitarian benefits (Chitturi et al., 2008).

The analysis of this framework can also be extended to the exploration of the value perception of the social media channel versus the offline one. In the context of social media people seek for identification and express their need for belongingness and cognition with other individuals who share common values, beliefs and interests (Gangadharbhatla, 2008). Furthermore, it is a medium for entertainment which encourages members to become actively engaged in communities (Tardini and Cantoni, 2005). Given these characteristics, the conclusion drawn is that social media present a hedonic value as a channel. On the contrary, offline channels are perceived to have a more utilitarian value, since they satisfy mainly functional needs and target in efficiency (Scarpi et al., 2014). In line with these considerations, and taking into account the congruency framework of sales promotion effectiveness (Chandon et al., 2000), the second expectation of this study is that when a price discount on a hedonic product is promoted online through a social media channel, which offers hedonic benefits, the purchase intention will be higher than through an offline channel.

H2: The effect of a price discount which is presented in an online channel, on purchase

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4. METHODOLOGY

To provide empirical evidence for the hypotheses drawn above, a 2 x 2 x 2 between-subjects experiment design was performed. As it is illustrated in the conceptual framework, the variables of this experiment are the existence of a discount in the offer (no vs. yes), the channel that this discount is delivered in (offline vs. online), and the product type (utilitarian vs. hedonic). Each of these variables was manipulated in two levels.

4.1 Sample

For the main experiment a total of 214 people participated in an online survey. Data were collected in ten days; the distribution of the survey began on 19 April 2017 and ended on 28 April 2017. The majority of the sample came from Greece (74.3%) and the Netherlands (12.1%). Respondents were primarily female (61.7%), and the largest part belongs to ages from 25 to 34 years old (56.1%). Table 1 summarizes all the demographic data that has been collected from the experiment.

Table 1 – Demographic Data Report

Frequency Percentage (%) Nationality Dutch 26 12.1 German 6 2.8 Greek 159 74.3 Other 23 10.8 Age 18-24 58 27.1 25-34 120 56.1 35-44 23 10.7 45-54 9 4.2 55-64 3 1.4 65+ 1 0.5 Gender Male 82 38.3 Female 132 61.7 N 214 100

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18 4.2 Pretest

A pretest was conducted in order to conclude to the products that will represent the utilitarian and hedonic one. In the first place, participants had to read the definitions (Hirschman and Holbrook 1982) of what a utilitarian and a hedonic product is (Voss et al., 2003). Afterwards, ten products were presented, five utilitarian and five hedonic ones, and they were asked to score them as more utilitarian or hedonic according to their perception, in a bipolar matrix table. The product with the highest mean was used as the hedonic, while the one with the smaller mean as the utilitarian. The results of the 24 responses (N=24), pointed out stationery as the most utilitarian product (Mu=0.64) and literature books as the most hedonic one (Mh=9.6), and thus these products were used as inputs in the experiment. All the results from the pretest are presented in Table 2 below.

Table 2-Utilitarian and Hedonic product selection

Products Min Mean Max Std. Deviation

Literature Books 6 9.6 10 0.913 Socks 0 2.48 7 1.873 Shampoos 0 3.4 7 2.111 Perfumes 0 6.36 10 2.464 Stationery 0 0.64 7 1.604 Shoes 0 4.44 9 2.434 Designer Clothes 1 6.92 10 2.344 Kitchen Appliances 0 3.04 8 1.814 Sunglasses 1 4.48 9 2.124 Groceries 0 2.72 9 2.716

This table presents the mean score of 5 hedonic (literature books, perfumes, shoes, designer clothes, sunglasses) and 5 utilitarian (socks, shampoos, stationery, kitchen appliances, groceries) products that were presented in the pretest. The product with the highest mean was selected to represent the hedonic product type in the main experiment and the one with the lowest mean to represent the utilitarian type. Accordingly, literature books (M=9.6) were selected for the first category and stationery (M=0.64) for the second one.

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19 4.3 Procedure

The participants were randomly assigned to one of the eight conditions that were designed. The randomization occurred in all three levels of the experiment. The participant could be assigned to the utilitarian (stationery) or the hedonic (literature books) product. First, individuals were presented with a picture of stationery or literature books and asked to complete the 10-item product involvement semantic scale, validated by Zaichkowsky (1994). The purpose of this measurement was to test the consumers’ evaluation of the products shown (Batra and Ahtola, 1991). The means of the participants’ perceived value of the presented products across all conditions are illustrated in the following figure (Figure 2).

Figure 2. Evaluation of hedonic and utilitarian products

This figure illustrates whether the participants evaluate the presented products as hedonic or utilitarian correspondingly in every possible condition. The results suggest that the majority of participants found both products almost equally representative of each category.

Afterwards, in order to determine whether the channel of promotion is important for consumers and affects them when purchasing products, participants had to watch a video of a digital influencer promoting a product in the online channel case, while in the offline channel case, they were presented with a brochure of a product. Next, they were requested to indicate the degree to which they agree with four statements regarding their perception of the channel

1 2 3 4 5 6 7 8 9 10

Online-ND Online-D Offline-ND Offline-D Utilitarian/Hedonic Value

Utilitarian Hedonic

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20 of promotion in a 7-point Likert scale (1=Strongly Disagree - 7=Strongly Agree). To ensure the reliability of the construct, the measurement items of the research of Jafaar (2012) were used and modified to fit this experiment. The following figure presents the means of the importance of each channel for the participants in the 8 conditions.

Figure 3. Perception of the importance of the channel of promotion

This figure presents how important is the channel of promotion for participants in order to purchase a product. The chart depicts no significant difference between online and offline channel, except for the case of the hedonic products, where the offline channel seems to have a slightly higher importance for the participants purchase intention compared to the online one, independently of the existence of a discount or not.

The last part of the experiment included the measurement of the participants’ purchase intention for the product. There were two possible scenarios; either the product was presented with a 10% discount which was given from the digital influencer or the brochure, or it had no discount and was presented in the form of informational material. The determination of the items that measured this construct relied upon the paper of Sweeney and Soutar (2001). The items were measured in a 7-point Likert scale (1=Strongly Disagree - 7=Strongly Agree) as well. Figure 4 illustrates the means for this variable.

1,00 2,00 3,00 4,00 5,00 6,00 7,00

Online-ND Online-D Offline-ND Offline-D

Channel of Promotion Perception

Utilitarian Hedonic

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Figure 4. Purchase Intention

This figure shows the participants’ purchase intention of utilitarian or hedonic products across the different conditions in the experiment. These observations suggest that people tend to purchase hedonic discounted products when this discount is presented in an online channel, but also utilitarian discounted products in the same condition, in a slower rate though. Moreover, in the absence of discount people are more reluctant to buy offline rather online.

The reliability of the model used in order to investigate the difference in purchase intention through the various conditions in the experiment was tested using the Cronbach’s alpha as a comparison measure. In this way we can be ensured that the items measure a reliable scale. In this case the scales measuring the Evaluation of products, the Perception of the channel of promotion and the Purchase Intention were all reliable (a>0.7) and no significant increase in the value of Cronbach’s alpha was observed if any item was deleted. Table 3 illustrates the values of Cronbach’s alpha for every measurement.

Table 3 – Reliability Analysis

Measurement Number of items Cronbach’s alpha

Evaluation of product 10 a=0.924

Perception of the channel of promotion 4 a=0.825

Purchase Intention 3 a=0.814

The table presents the number of the items that formed each construct’s measurement and the corresponding Cronbach’s alpha value. The scales are all reliable (a>0.7).

1,00 2,00 3,00 4,00 5,00 6,00 7,00

Online-ND Online-D Offline-ND Offline-D

Purchase Intention

Utilitarian Hedonic

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22 4.4 Data Analysis

A regression analysis was used for hypotheses testing, in order to define the relationship between the predictor variables and the outcome variables. All the independent variables are categorical, and more specifically dichotomous, whereas the dependent variable is numerical (interval). A multiple regression analysis was performed to analyze how the existence of a discount (No discount/Discount), the channel where the discount is presented (Offline/Online) and the product type (Utilitarian/Hedonic) are able to predict consumers purchase intention. The regression equation used for this analysis is:

Y= α+ β1*Χ1 + β2*Χ2 + β3 (Χ1*Χ2) + β4*Χ3 + β5*(Χ1*Χ3) + β6*(Χ1*Χ2*Χ3) + ε

The outcome variable in this model is the purchase intention (Y), α is the constant and

ε is the estimated error, meaning the part that cannot be explained by the model. The

predictors are the discount existence (X1; 1= yes), the channel of promotion (X2; 1=online),

and the product type (X3; 1=hedonic). All the β represent the parameters. In the first place the

direct effect of price discounts on purchase intention is examined (β1). Then we identify the

direct effect of the channel of promotion on purchase intention (β2), as well as the direct

effect of the product type on purchase intention (β4). Afterwards, we examine the interaction

effect between the existence of a discount and the channel of its promotion on purchase intention (β3), and also the same effect from the product type point of view (β5). Finally, we

have to determine the three way interaction effect of price discounts moderated by the channel of promotion and the product type on purchase intention (β6).

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5. RESULTS

To begin with, all of the predictors and their in-between interactions were entered in the analysis. This model was statistically significant F (6, 207) = 21.44; p<.05 and explained 38.3% of variance in purchase intention (R2=0.383).

Table 4 – Multiple Regression Model of Purchase Intention

Hypotheses β t

Constant 3.639 23.041

Discount (Yes=1) .885* 3.737

Channel of promotion (Online=1) .736* 4.070

Product type (Hedonic=1) .210 1.16

Discount*Channel H1 (+) -.198 -.637

Discount*Product type .585*** 1.854

Discount*Channel*Product type H2 (+) .220 .609

Note: Statistical Significance: *p<.01; **p<.05; ***p<.10

The logarithm of purchase intention (dependent variable) was computed in order to identify its percentage increase/decrease. In this way, the model predicts that the change of the independent variable from 0 to 1 leads to an increase/decrease in the dependent variable by 100·βA %.Table 5 indicates the results.

Table 5 – Multiple Regression Model of ln (Purchase Intention)

Hypotheses βA t

Constant 1.265 29.994

Discount (Yes=1) .225 3.557

Channel of promotion (Online=1) .172* 3.565

Product type (Hedonic=1) .040 .836

Discount*Channel H1 (+) -.055 -.664

Discount*Product type .127*** 1.529

Discount*Channel*Product type H2 (+) .024 .248

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24 As seen in Table 4, the existence of a price discount has a positive impact on consumers’ purchase intention of a product and that is highly statistically significant (β=0.885, p=0.000). Particularly, if a product has discount, the purchase intention will have an increase of 0.88 units, which is 22.5% higher compared to the case of no discount (βΑ=0.225). The second predictor of the model, the delivery channel of the discount, also

plays a high significant role in our dependent variable (β=0.736, p=0.000). Consequently, the online channel fosters purchase intention by 17.2% more than the offline channel (βΑ=0.172).

Finally, the product type does not generate statistically significant difference on purchase intention (β=0.21, p=0.247).

Moving forward to the interpretation of the interaction terms, the delivery channel of a discount does not seem to moderate the relationship of the discount and the corresponding purchase intention, so this moderation is not significant (β=-0.198, p=0.525). In other words, even though there is a statistical significance for both discount and its delivery channel separately, when a discount is presented in an online channel is not more effective than when it is presented in an offline channel. Conversely, the product type of discounted product is marginally significant (p< .10) for consumers’ purchase intention (β=0.575, p=0.065). Accordingly, when a hedonic product is on discount the purchase intention is increased by 0.57 units or 12.7%, compared to a utilitarian discounted product (βΑ=0.127). Surprisingly,

the three way interaction effect of a discount, its delivery channel and the different product type does not present any statistically significant results as the increase on purchase intention is only by 0.22 units (β=0.22, p=0.543).

In conclusion, based on the results of the regression analysis, an overview of the hypotheses evaluation is presented. The first hypothesis suggests that when a discount is delivered through an online channel the consumers’ purchase intention will be higher than if it is delivered through an offline channel. However, the regression analysis did not report any

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25 statistically significant difference between the two channels regarding the purchase intention of a discounted product. Consequently, this hypothesis is not supported. The second hypothesis proposes that when a hedonic product’s discount is presented in the online environment it will result in increased purchase intention, compared to a utilitarian’s one. Unfortunately, the results do not suggest that this increase is significant; therefore this hypothesis is not supported as well.

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26 6. DISCUSSION

The dominant target of each business is to create profits by generating sales through the satisfaction of its customers’ needs. However each company is unique and there is no magic recipe for success. Therefore managers have to provide the customers with the most attractive offer of the right product in the right place, and from a business perspective, in the right channel. One of the most popular ways to generate sales is the offer of price discounts. Nevertheless, managers are still uncertain of the proper discount strategy that should follow in different channels and the product type that each strategy is appropriate for (Zhang & Wedel, 2009; Eisenbeiss et al., 2015). Consequently, this research aimed in the identification of the different effect that the online and offline channels have on the purchase intention of discounted products. In addition, this research took the study one step further, as it also tried to identify which product type –utilitarian or hedonic- fits better in each channel in order to maximize the sales and minimize the costs of a possible multichannel discount strategy.

The results of the study indicate that a product on discount will generate sales independently of the channel that this discount will be delivered. In other words, consumers will react positively to a discount; either this discount is given online, in this case by a digital influencer, or offline, by a physical store or a flyer. What is surprising though is that typically consumers search for deals online, and expect that the possibility to find the desired products with a discount in this channel will be higher. That is because of the annihilation of the distance between the consumer and the store and the diminution of all the consequent costs regarding time and money (Chu et al., 2010). In our case, this scenario is not supported and that can be explained by the trust issues and the perceived risks that may arise in the online channel. The decision of a consumer to shop online depends on the degree of trust towards the online store (Van der Heijden, Verhagen and Creemers, 2003). This is mainly due to the absence of sensory attributes, which aid in the evaluation of the products’ quality and

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27 performance (Degeratu, Rangaswamy and Wu, 2000). Hence, consumers probably perceive these factors as more important than cost saving.

Another reason that could explain the results is the amount of information about price and non-price attributes that one can obtain online. Alba et al. (1997) identified this as the main difference between the online and the offline channel, meaning that someone can collect more information about a product online because of the plethora of sources. Despite the fact that more information can increase ones price sensitivity for undifferentiated products, this is not the case for the differentiated ones. In line with this argumentation, for many products the online channel constitutes a deterrent of sales generation through discounts, since the price sensitivity factor is not always augmented.

As far as the effect of the product type is concerned, the main finding was that when hedonic products are on discount their purchase intention is higher than that of the utilitarian’s one. This finding is in line with the research of Kivetz and Zheng (2016), who state that the purchase probability of hedonic products is greater than that of utilitarian ones when it comes to price discounts. This rationale is based on the conception that people cannot easily rationalize the purchase of hedonic products compared to utilitarian. However, no evidence was found concerning the exploration the perfect fit between the product type and the different channels to offer the most effective combination that could result in higher purchase intention. Neither hedonic nor utilitarian products gave significant results of purchase intention when they were presented in different channels. This finding though is partly in line with the research of Pöyry et al. (2013). They suggest that people who have hedonic motivations, and thus are more likely to purchase hedonic products, tend to participate more in the online community, but they do not proceed in purchasing, eventually. On the contrary, consumers with utilitarian motives, are usually limited to skim the webpage but they are more likely to buy the products; an aspect that was not identified by the results of

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28 this study. Unfortunately, this research cannot provide a concrete strategy that should be followed when it comes to the promotion of discounts for different types of products in different channels.

6.1 Managerial Implications

Although this research did not give significant results for the hypotheses drawn, the outcome can be interpreted by managers in various ways. However much surprising, the different channel of delivery of discounts does not affect consumers’ purchase intention respectively. Subsequently, managers should follow a multichannel discount strategy in order to increase sales. Rather than assigning the available budget disproportionately to customize promotions for different channels, all manager’s efforts should concentrate in designing the optimal discount offer and deliver it across all channels consistently. In this way, the online and offline channel will have both the informative and executional aspect of the strategy and this interaction will enhance the convenience of the purchase. Another advantage of this tactic is the higher revenues that can be obtained by reaching a larger target audience and the variety of feedback for further improvement that is possible to be provided by a wider range of customers. Apart from that, the management of the results will be more efficient, due to the ability to directly compare sales across different channels. Alternatively, if managers want to boost sales solely in the online channel, they can optimize it and lead the most loyal offline customers there first, by providing them with more exclusive offers, enhancing their perceived trust in that channel, too.

As it is already discussed, hedonic products are more attractive when they are on discount and they are more likely to increase purchase intention. Accordingly, managers can use them as a bait to generate traffic in their stores, both online and physical stores, in order to increase the sales of other products. An example could be the offering of complementary products next to the ones that are on discount.

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29 6.2 Limitations and further research

The growing penetration of the digital technologies in consumers’ lives is the fundamental inducement for academics to conduct further research in the field of online discounts. People spend the biggest part of their day online and they come across various stimuli that influence their decision making process. One of these stimuli is the influencer marketing trend that plays a significant role in the evaluation of products, and generally in the formation of opinions. Successful digital influencers have the ability to create original content and long-lasting relationships with their audience, which result inenhancing consumers’ trust. Furthermore, they reach millions of consumers and thus their influence on them is greater. Managers take advantage of this kind of collaborations in order to establish credibility for their brands and together with discounts, to increase online and in-store sales. Subsequently, the expected effect of discounts delivered in an online channel and especially by digital influencers will generate higher sales than traditional discounts will. Hence, further research in this domain is required in order to illustrate academically this kind of effect.

As can be expected, this study comes with several limitations. First of all the size of discount that was used in the experiment was a 10% for manipulation reasons. A small percentage of a price discount on the one hand can reveal the consumers that are responsive to discounts in general, but on the other hand it does not constitute a significant difference in the price of the product, especially for low priced products such as stationery and books. Therefore, people may not perceive it as a real deal in order to increase their purchase intention, so research in different sizes of discounts is recommended.

As far as the type of the online channel is concerned, YouTube was used so as to provoke a more vivid engagement with the concept of digital influencers and the discount tactic that companies use in collaboration with them. Even though this platform is becoming as powerful as television, many other platforms exist where the digital influencer concept

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30 could apply. For example, Facebook, Instagram and Twitter represent other common social media that consumers use in their everyday life and influence their decisions and attitudes over products. Although the influencer marketing is thriving the last years, many consumers are still not familiar with that concept. A significant number of the research’s sample (16.8%) is over 35 years old and it is possible that these participants cannot completely understand that aspect of promotion. Apart from the social media context, other types of online channels can be researched such as websites, blogs or forums, where people with diverse age range are engaged.

Turning to the factors that have been taken into account in this research, the degree of loyalty in a specific channel was not identified. Despite the fact that multichannel shopping is a trending behavior, some people are still loyal to only one channel, most commonly the offline, regardless of the existence of a discount in another one. Consequently, no manipulation can affect their preference and so they insist on purchasing from the channel they prefer.

Another limitation of the study is its restriction to the products category. The investigation of the proper fit is only between utilitarian and hedonic products. A future research should also take into account the services sector. Will the research generate different results in the case of a consulting or an insurance company? Moreover, the research could be extended in a broader category analysis, by investigating industries instead of specific products.

Finally, the absence of the moderation effect of the delivery channel of a discount and the product type should not be generalized because the dependent variable is the purchase intention. Although it is an indicative measurement of actual behavior, it cannot predict it with accuracy. The research was conducted through an online experiment; a field experiment would have given more realistic results and more confidence to support them. Nevertheless,

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31 actual behavior is a construct that depends on many variables that researchers cannot control and only constant research and experimentation in many different contexts can simulate reality.

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32

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39 8. APPENDICES

8.1 Online experiment questionnaire Dear respondent,

Thank you for taking the time to participate in this survey! The questions in the survey are used to investigate the influence of the delivery channel of a discount on consumers' purchase intention. Please know that answering the questions is anonymous and all data collected will be treated confidentially and only for educational purposes as inputs for my master's thesis in Business Administration (Marketing). It will take approximately 4 minutes to complete the survey. If you have any questions please do not hesitate to contact me via despoina.papadopoulou@student.uva.nl.

Best regards,

Despoina Papadopoulou.

• Utilitarian Products

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40

• Condition 1: Utilitarian/Online/No discount

- You are about to watch a YouTube clip of a digital influencer: https://vimeo.com/211540951

Q2: Please indicate the degree to which you agree with the following statements about this channel of promotion (YouTube):

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41 Q3: Please indicate the degree to which you agree with the following statements after you watched the video:

• Condition 2 - Utilitarian/Online/Discount

- You are about to watch a YouTube clip of a digital influencer: https://vimeo.com/211540951

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42

• Condition 3 - Utilitarian/Offline/No discount - This is a brochure of stationery:

Q4: Please indicate the degree to which you agree with the following statements about this channel of promotion (brochure):

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43 Q5: Please indicate the degree to which you agree with the following statements after you saw this brochure:

• Condition 4 – Utilitarian/Offline/Discount -This is a brochure with 10% discount on stationery:

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44

o Hedonic Products

Q6: Please indicate your feelings about literature books in the following scale. I find literature books:

• Condition 5 – Hedonic/Online/No discount

- You are about to watch a YouTube clip of a digital influencer: https://vimeo.com/211540830

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45 Q7: Please indicate the degree to which you agree with the following statements about this channel of promotion (YouTube):

Q8: Please indicate the degree to which you agree with the following statements after you watched the video:

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46

• Condition 6 – Hedonic/Online/Discount

Q7 and Q8 follow.

• Condition 7 – Hedonic/Offline/No discount - This is a brochure about literature books.

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47 Q9: Please indicate the degree to which you agree with the following statements about this channel of promotion (brochure):

Q10: Please indicate the degree to which you agree with the following statements after you saw this brochure:

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48

• Condition 8 – Hedonic/Offline/Discount -This is a brochure with 10% discount on literature books.

Q9 and Q10 follow.

Q11: What is your gender?

Q12: What is your age?

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