The importance of product information transparency in the purchase decision and its relation to the other product attributes

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The importance of product information transparency in

the purchase decision and its relation to the other product

attributes

Master Thesis Business Studies Specialization Marketing Name: Stefan van der Kuijl Studentnr: 6288448

Supervisor: Joris Demmers Academic Year: 2013 - 2014

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Abstract

Purchase decisions are part of everyday life and always involve a trade off. Transparency is becoming increasingly important nowadays since people demand more information from companies and therefore an interesting field of study. It is interesting to know the implications of transparency and how it affects the decision making process of consumers. Therefore, this research answers the research question that aims to find out how important transparency is in the decision making process and how it relates to other product attributes that consumers consider. In order to answer the research question, a survey was conducted among Dutch participants. With the use of a choice-based conjoint analysis, it was possible to see which product attributes were the most influential in the decision making process. The most

important finding of the research shows that transparency is more important than the brand itself but price remains the most important factor. This study contributes to the current literature by giving more insight in the importance of product information transparency with low cost grocery products and its relation to other product attributes.

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4 1. Introduction

The introduction of the World Wide Web (WWW) opened opportunities for the average consumer to gain access to any (kind of) information one might desire. It has become normal nowadays to have an Internet connection and therefore be able to look up information about brands, companies or products and find out when the truth has been misrepresented (Fournier & Avery, 2011). We live in a world where no action goes unnoticed and therefore companies continuously face the ticking time bomb of publicity. Companies are more forced than ever to adopt a full disclosure strategy or at least adopt a proactive position (Fournier & Avery, 2011).

Tapscott and Ticoll (2003) state that today’s business leaders see transparency as either a threat or an opportunity. Some companies fight it while others tend to hide from it. Luckily, more and more companies these days embrace it. Transparency is defined as “‘the visibility and accessibility of information especially concerning business practices’’ (Merriam-Webster, 2010). Companies that are actively

transparent acknowledge that transparency is based on openness (Tapscott & Ticoll, 2003). Openness, subjectively, is based on honesty (Macmillan Dictionary).

Therefore, transparent companies understand that transparency is a corporate value that is to be connected to honesty, accountability and consideration to sustain trust (Tapscott & Ticoll, 2003). The Internet has given openness a new meaning by exposing any company to public scrutiny.

According to Tapscott and Ticoll (2003), companies can either be transparent with the use of forced transparency or purposely choose to be transparent and thus with active transparency. Forced transparency can be of a particular negative nature since the cause for which it was needed is typically not a pleasant one. Active

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5 transparency means that companies actively disclose information that previously was not shared but is of interest to the company’s stakeholders.

Authenticity is an important factor in establishing transparency (Fournier & Avery, 2011). Authentic brands are defined as brands that demonstrate genuineness in their positioning and message they sent and justifiably are what they say they are (Fournier & Avery, 2011). Brands that adopt authenticity as one of their main values are more open and honest and therefore better at sustaining trust (Fournier & Avery, 2011). Simply put, authentic brands have nothing to hide and therefore what the consumer sees is what the consumer gets.

As previous literature shows, transparency is beneficial for the consumers since it results in disclosure of interesting and previously not shared information. Bhaduri & Ha-Brookshire (2011) state that consumers nowadays demand transparent products because they are conscious about the society and environment around them. Slavin (2009) states that the market for transparent and sustainable products will grow substantially to an increase of 14% by 2014. As a result, businesses are more openly communicating their sustainable business activities with their stakeholders in order to maintain legitimacy and above all their reputation (Bhaduri & Ha-Brookshire, 2011). Information about business transparency can be of particular importance to consumers who, as Bhaduri & Ha-Brookshire (2011) state, are concerned about the environment and society. This transparent information can be used for their purchase or

consumption choices. But how important is transparency to the consumer? In other words, to what extent does transparency influence the consumption choice of consumers?

As can be seen, the concept of transparency is relevant in today’s society and therefore an interesting field of study. Current literature states that consumers demand

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6 more transparency and use this to make their purchase or consumption decisions. There, however, exists a clear gap in the existing literature concerning to what extent product information transparency is important for the purchase decision when

choosing between different product alternatives. Therefore, this study will focus on the importance of product information transparency in the purchase decision and its relation to other product attributes such as price or brand. This research will

contribute to the debate of whether transparency is actually beneficial and value adding or simply a new trend that does not offer much added value for the consumer. In conclusion, this study aims to research how important transparency is in the final purchase decision when compared to the other product attributes such as price or brand. In order to contribute to the to the literature and fill the gap, the research question is formulated as follows: “How important is product information

transparency for the purchase decision and how does it compare to the price and brand product attributes in the purchase decision-making process?”

This study will contribute to the existing literature by giving more insight in the importance of product information transparency in low cost grocery products. Even more so, there will be a specific focus on how the different product attributes (price, brand and product information) are interrelated. In other words, the

relationships between the different product attributes will be examined so that this study can contribute to the existing literature by giving more insight into for example the degree that product information transparency justifies a higher price or the brand neglects the importance of transparent product information.

The paper will continue with a literature review. After that, the research design and methodology are explained, followed by the results of the survey. The paper will end with a discussion of the research and a short conclusion.

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7 2. Literature Review

The choice behaviour of consumers depends on the various different attributes of a product. This chapter aims to define three different product attributes used in this study that affect the consumer’s choice behaviour. Product information, brand and price are each discussed in a separate paragraph together with the research

hypotheses. First, transparency in general is explained and the importance of transparency in the purchase decision. Afterwards, the three product attributes are reviewed.

2.1 Transparency

It is important to note what has been written about the importance of transparency in the purchase decision and about transparency in general since this distinction shows how this study aims to differentiate itself from the existing literature. Most literature is focused on transparency in a broader general context. The following subsections will discuss the existing literature on both.

2.1.1 Transparency in general

In this subsection, a clear overview is given of what transparency means nowadays and how companies and consumers deal with this phenomenon. Transparency in the general sense is defined as “‘the visibility and accessibility of information especially concerning business practices’’ (Merriam-Webster, 2010).

As is seen, transparency in general is undoubtedly one of the most popular business trends in the recent years. Companies must be able to justify their actions and wrongdoings of companies cannot longer be held from the general public without

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8 consequences (Carter & Rogers, 2008). Disclosing financial information can guide capital to where it is most effective leading to efficiency and growth (Vishwanath & Kaufmann, 2001). Withholding this information from the general public to keep in secrecy can generate staggering economic costs since it adversely affects investments and economic growth (Vishwanath & Kaufmann, 2001). Today’s consumer is more aware of the impact companies have on the environment and society at large and are demanding more sustainable and above all transparent products (Bhaduri & Ha-Brookshire, 2011). In order for companies to build a sustainable customer base and maintain legitimacy, transparency is key.

Try as they might, some companies are simply having a difficult time letting untethered information flow or come clean about their strategies (Fournier & Avery, 2011). The last few years have revealed that companies sometimes do everything in their power to ensure that their reputation is not at stake. Managing fake blogs, ghost twitter accounts or teaching employees how to misrepresent information are some of the examples by which companies tend to defend themselves (Thomaselli, 2007). Of course, this kind of corporate behaviour puts the information reliability and

subsequently relevance for the consumer in a rather dangerous position. In other words, information becomes less relevant to the consumer when the company behind is has a questionable trustworthiness and transparency.

Vishwanath & Kaufmann (2001) identified the four dimensions of

transparency as access, relevance, quality and reliability of information. Consumers in today’s society seem to have insufficient access to information about sustainability efforts that are being carried out by the companies (Burchell & Cook, 2006). It is therefore not without reason that a majority of companies are faced with demands for more detailed information on their social and environmental impacts of their business

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9 activities. Lafferty and Goldsmith (1999) found that transparency efforts of a

company can have a significant impact on the consumer’ judgement and evaluation of products or brands. This is a clear indication that the relevance of product information increases when brands are more transparent. Consumers have a better judgement of the brand or product when it is more transparent (Lafferty & Goldsmith, 1999).

Transparency relevance seems to be for different reasons than most companies think. Christensen (2002) states that customers demand more transparency and

therefore more communication with the external audience. Since communication is done by the means of sharing information, customers demand more information. However, customers are not always interested in all the information of a company or a product (Christensen, 2002). In that sense, customers can be reluctant about the

transparency efforts of a company and just want some assurance that the company behaves in a ‘socially desirable manner’. Information transparency therefore does not always add value for the consumer. In other words, customers care about transparency since customers care about buying products that are honest and responsible.

Therefore, the degree of information relevance is linked to the degree of relative reassurance or trust it gives.

Christensen (2002) argues that information disclosure by companies should not flow freely just because it is a means of communication. Information disclosure is a prerequisite for the knowledge and insight that consumers have about a product or brand but not a solution. In other words, the knowledge of the consumer is not only limited by a lack of information but also by their capacity to handle and process it (Christensen, 2002). It is not straightforward that sheer availability of information will produce a more sophisticated image of companies in the mind of the consumer.

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10 not directly lead to a better, more transparent brand image in the mind of the

consumer. This is the case since ultimately, transparency lies in the hands of the external audience (Christensen, 2002).

Dishonest reporting or deliberate distortion of business information is in conflict with the reliability of transparency (Vishwanath & Kaufmann, 2001). Reliability of transparency is defined as the fair, consistent, complete and timely presentation of business information (Vishwanath & Kaufmann, 2001). Transparency reliability is not always well aligned with transparency relevance (Chiu, Hsieh & Kuo, 2012). Some companies choose not to be transparent on purpose. These companies build brands through telling authentic stories. Authenticity does not necessarily mean genuineness or the truth (Grayson and Martinec, 2004). Consumers judge authenticity on the basis of their own experiences and when a consumer

subjectively perceives an object to be objective, it exists in the mind of the consumer (Lewis and Bridger, 2000). Chiu et al. (2012) define authenticity as a sense that readers obtain from material that makes them believe the story and associate it with reality. A brand story that includes factual cues that the consumer believes is

perceived as being authentic. These so-called ‘brand stories’ increase the information relevance with factual and detailed cues while transparency is low. Transparency is low in a sense that while the brand story is transparent with a lot of information, it is not the real information but that of a made up narrative and therefore not reliable. Stories can create emotional connections with the consumer and enhance the

comprehensiveness, communication and judgement of the product information (Chiu et al., 2012). In this fashion, companies create non-transparent narratives to partially and purposely hide the negative aspects of a brand (Chiu et al., 2012). While this might add to the relevance of information, it might lower the reliability of information

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11 for the consumer. It seems that while information can be relevant to the consumer is does not mean that it is also reliable.

2.1.2 The importance of transparency in the purchase decision

Cohn & Wolfe (2013) found that transparency was important in making purchase decisions with 66% of all consumers in the UK. In comparison, these numbers were 86% and 83% for quality and price respectively. In addition, 79% of the Chinese consumers found transparency to be important whereas price had a lower score of 65%. According to Cohn & Wolf (2013), the average Chinese customer’s judgement and valuation of a product depends greatly on transparency. Transparency has a stronger stamp than price in their judgement. This, however, took place in China and thus with a Chinese population. As Cohn & Wolfe (2013) rightfully mention, it is not strange that these results differ for the Western world. People in China are confronted with air pollution and other environmental concerns every day and thus are more aware of the importance of transparent products (Cohn & Wolfe, 2013).

Furthermore, Creyer & Ross Jr. (1997) conclude that consumers are willing to reward ethical behaviour of businesses with a higher willingness to pay for the

product. Ethics is generally defined as the set of moral principles or values that are at the core of responsible behaviour (Sherwin, 1983). In this sense, ethical behaviour of businesses is judged by the effect it has on the overall welfare of its environment (Creyer & Ross Jr., 1997). Transparency and ethics are interrelated since they both origin from the need for businesses to act responsible and with respect for those around them. In contrast, consumers are less willing to buy products from unethical firms or non-transparent firms and will only do so at a lower price (Creyer & Ross Jr., 1997). It therefore can be seen that transparency is important when choosing among

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12 product offerings.

In addition, Carter & Curry (2010) argue that consumers care about an equal allocation of proceeds among different agents within the supply chain. Consumers show to prefer a ‘fair share’ allocation of the retail price to any other unequal allocation alternative. Carter & Curry (2010) argue that price information disclosure and thus price transparency has a positive effect on the choice behaviour of a

consumer. More particularly, consumers tend to select the higher priced of two identical products based on the incremental information that the transparent pricing communicated. This contradicts with classical literature that states that price transparency has little to no effect on consumer behaviour since consumers will consistently demonstrate self-interested behaviour and thus select the lowest-priced option (Fehr & Schmidt, 1999). The findings of the study of Carter & Curry (2010) are of particular importance since they make an important contribution to the existing literature by showing how incremental (price) information disclosure is highly valued by the consumer and that it indeed results in consumer expressing a stronger

willingness to buy the more expensive of the two. The first hypothesis goes as follows:

H1: Transparent product information is preferred to non-transparent product information.

The following subchapters will focus on the three different attributes used in this study and hypotheses will be formulated based on the existing literature.

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13 2.2 Product information

Chang & Wildt (1994) state that product information is generally agreed to be an important aspect of a product on which consumers base their judgement. This study has limited the product information attribute to only include information related to the ingredients, artificial additives and country of origin of a particular grocery product. This decision was made due to the simple nature of the grocery product label that respondents were shown in the experiment. The product label only conveyed

information about these three constructs (see appendix A). Brand and price are stand-alone product attributes in this particular research and therefore not included in the product information attribute. Grewal et al. (1998) mention that the importance of product information differs among consumers. Consumers with a lot of knowledge about the particular product category are less influenced by product information and base their choice behaviour more on aspects such as brand and price. However, when consumers are less familiar with the particular product category, they tend to gather as much information as they can in order to make the purchase choice trade-off (Grewall et al., 1998).

2.3 Brand

Brand is commonly defined as “a name, sign, symbol, or design or a combination of them, intended to identify the goods or services of one seller or group of sellers to differentiate from those of competitors” (Kotler, 2000). Walley, Custance, Taylor, Lindgreen and Hingley (2007) argue that the brand is more than a name and

introduces the opportunity to create a deep set of associations for the brand. This so-called brand image, however, exists in the mind of the consumer and is therefore the consumer’s perception of the firm’s brand message (Walley et al., 2007). Haque and

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14 Jackson (1994) state that consumers might expect things from a brand without any kind of objective evidence and therefore hold an opinion based on their beliefs. The brand image is therefore the consumer’s interpretation of a brand and not necessarily fact.

Brand image is an important attribute that consumers take into account in the decision-making process (Nevin & Houston, 1980). Consumers tend to use the brand image and in particular the store/brand name as a source of information (Grewal et al., 1998). Buckley (1991) states that there exists a direct positive relationship between brand image and purchase intention. Grewal et al. (1998) state that this link occurs because the consumer’s perception of the value of the product is enhanced because of the brand image. For example, customers buy shoes from a prestigious brand because they perceive it to be a better value. Consumers therefore might pay extra money for products with a high brand image. It seem that the brand image enhances the product valuation. We therefore propose that:

H2: Brand image has a positive effect on product valuation.

Dodds et al. (1991) state that the positive effect of brand information on the

perception of quality and willingness to buy is significant. Dodds et al. (1991) also show that the price has a negative effect on the willingness to buy but that this effect is moderated by the brand information component when it is included. In other words, the brand is important since it positively enhances the willingness to buy and

moderates the negative effect of a higher price. Degeratu, Rangaswamy & Wu (2000) state that the brand name becomes more like a surrogate for attribute information when the information itself is missing or too costly to acquire. In other words, people

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15 tend to focus more on the brand name when there is not much other information available.

In contrast, Degeratu et al. (2000) also argue that the brand name becomes less important when other (new) information about the product becomes available. In other words, a brand name is seen as important but new product information that might show a higher level of transparency can diminish the effect of the brand name. Cohn & Wolfe (2013) state that the brand is becoming less important. In their study, only 27% found brand to be important whereas this was 43% the year before. In a similar trend, transparency is becoming more important. The same study of Cohn & Wolfe (2013) state that 66% found transparency to be important whereas this was 53% the year before. As a result, the following hypothesis is formed:

H3: Product information transparency is more important in the purchase decision-making process than the brand attribute.

As is seen, the existing literature seems to be in two-fold concerning the brand. Brand is seen as indeed important by the earlier literature (Buckley, 1991; Grewal et al., 1998; Nevin & Houston, 1980; Dodds et al., 1991). More current literature states that the brand is becoming increasingly less important (Degeratu et al., 2000; Cohn & Wolfe, 2013). This would indicate that the brand is indeed becoming less important.

2.4 Price

Price is the third product attribute that is important when making a purchase decision and the last to be discussed. According to Reed (1999), 85% of the consumers are mostly focused on price information when they shop. It is clear that price is an

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16 important attribute when choosing a particular product. This is also confirmed in the study of Chang & Wildt (1994) who confirm that the perceived price influences the purchase intention. Interestingly, however, Dickson and Sawyer (1990) found that when doing grocery shopping in regular supermarkets consumers are less focused on price due their short time period in which a selection is made. Even more so, more than half of the consumers could not name the price of the product just placed in the shopping cart.

While this is true, one of the most important product attributes that consumer consider during the decision-making process remains to be the price (Chian &

Dholakia, 2003). Cohn & Wolfe (2013) confirm this notion by stating that 83% of the respondents in the UK valued price to be important. This is a higher value than the values of transparency (53%%) or brand (43%) of the same. This study aims to find out the importance of transparency when customers have to decide upon different product offerings in the Netherlands and especially how it relates to other product attributes such as the price. To do so, the following two price hypothesises are formed:

H4: Price is the most important attribute in the purchase decision-making process.

H5: Product information transparency is the second most important attribute in the purchase decision-making process.

Even more so, Gabor & Granger (1970) state that consumers tend to have a set of acceptable prices in their minds for a given product category. The judgement of the actual price of a product is based on these internal standards and the actual price is

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17 seen as low, fair or high. In that sense, consumers interpret the actual price in a way that is meaningful to them (Ziethaml, 1982). According to Fehr & Schmidt (1999), consumers select the lowest-priced option when the two products are identical. It is therefore assumed that a low price will be preferred over a high price. The following hypothesis is proposed:

H6: A low price will be preferred to a high price.

As can be seen in the literature review, the majority of the existing literature is focused on how important transparency in the general sense has become in recent years and how important it is for companies to join the transparency bandwagon. The three product attributes that are being manipulated in this study have also been described and their importance is shown with the existing literature. The research hypotheses are discussed with the use of the current literature and the paper will continue with the methodology concerning the research design, sample and measures used in this study.

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18 3. Methodology

The methodology will explain the overall structure and layout of the research conducted. Just as with the literature review, this methodology is also divided into different sections. First, the research design will be discussed followed by the sample used and means of data collection. Afterwards, the sample used and data collection tool will be described as well as the measures used in the last section.

3.1 The conceptual model

The research aims to find out how much each of the different product attributes influence the final purchase decision. Specifically, the focus lies on how transparency (manipulated in product information) influences the purchase decision and its relative importance compared to the other attributes. Figure 1 shows the conceptual model used in this research.

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19 3.2 Research Design

This research will use an online survey-based experiment in order to collect sufficient data. In order to compare the results of the survey with sufficient reliability or to be able to generalize, it is important that the survey contains standardized and closed questions (Saunders et al., 2009, p. 373). This is the only way to have sufficient consistency among the sample group used. The set of questions that will be offered to every participant will be based on a choice-based conjoint analysis (CBC). This offers a simple to interpret question layout that is easy to understand for the respondent.

Fagerstrom & Ghinea (2011) use a conjoint analysis to classify the relative importance of multiple attributes of an object. As can be seen, this is quite similar to what this study will entail. Participants will evaluate the overall desirability of a set of choice alternatives by choosing the one they prefer the most (Green & Wind, 1975). Choice-based conjoint analysis offers some important advantages. First off, data collection is done by simulating purchase decisions over and over again, thus giving a more realistic image (DeSarbo, Ramaswamy & Cohen, 1995). A second advantage is that product-specific attributes (price, brand and product information) can easily be accommodated and thus easily measured as they were to be constructs on their own which is of particular interest to this study (DeSarbo, Ramaswamy & Cohen , 1995). In other words, it is possible to examine the effect of a particular price level on the overall valuation of that particular product scenario. Being able to examine the individual effects of the different attributes and their levels is of great importance. Unlike traditional conjoint analyses, the choice-based conjoint analysis offers a wide range of choice contexts in its questions. In this study, the emphasis lies on making choices between competing products of two chocolate bar brands within a

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20 particular scenario (choice option) is measured on its own.

An online survey will be spread among a large social group (people within the social network of the researcher). Self-administered online surveys require less time for collecting the data and are therefore more convenient. An online survey reduces participant bias by guaranteeing autonomy for the participant. People tend to be more honest in their answers when their identity remains hidden (Saunders et al., 2009, p.56).

The experiment survey will focus on the importance of different product attributes in the purchase decision. Participants are given 4 scenarios in each question for which they must choose one every time. Each scenario is a combination of the product attributes and its corresponding levels and acts as a viable purchase option that the participant can choose.

3.3 Sample

The sample consists of people who live in The Netherlands. Since it is important to gain insight in the perceptions of the average consumer that is confronted with similar purchase choices daily, there is no particular age or type of person selected for the sample.

Most, if not all, participants were derived with the use of the researcher’s own social network. Since it is difficult to get sufficient participants, a small portion of the sample has been derived with the use of snowball sampling. Snowball sampling concerns people within the social network that share the survey within their social network. This is a way to gain a larger sample as to what otherwise could be reached. In order to be able to generalize and ensure the validity of our research, it is important for the sample to be as large as possible (Saunders et al., 2009, p. 218).

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21 This study is limited due to the relative short period of time in which the survey can be distributed. Therefore, the sample used cannot be as large as desired. The online experiment was distributed to as many people as possible in just under three weeks time.

Johnson & Orme (1996) have formulated a rule of thumb called the Johnson’s rule for estimating the minimal sample sized needed for a choice-based conjoint analysis. The formula goes as follows:

nta / c >= 500

where n is the number of respondents, t is the number of tasks (total amount of questions), a is the number of alternatives per task and c is the number of analysis cells. The final sample consisted of 194 responses, of which 102 participants

completed the survey. Only the completed responses were taken into account when analysing the results. The choice-based conjoint experiment included ten tasks (questions) in which respondents had to choose a particular scenario. Within each task, there were four alternatives that the respondent could choose. According to Johnson & Orme (2006), c is equal to the largest number of levels for any one attribute and c in this study is three. When performing the calculation it can be concluded that n(102) * t (10) * a (4) / c (3) is indeed larger than 500. Therefore, the minimum requirement was met and enough respondents were included in the sample size.

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22 3.4 Data collection

In order to administer and distribute the questionnaire in a quick, easy and cost effective manner, an internet-mediated method has been used. The questionnaire has been developed and distributed with the use of Sawtooth Software.

Sawtooth Software was found to be the only method that could be used to easily make a choice-based conjoint analysis without significant cost expenditures. Sawtooth Software made it possible to develop a choice-based conjoint analysis survey with easy means of distributing it since it is an online tool and therefore all digital. In addition, a lot of savings in time were made since no manual data collection had to be done (Saunders et al., 2009, p. 365). The software tool made it possible to export the data into Excel and from there into SPSS using the syntax. This is a reliable and convenient way of making sure the data is set up the right way before analysing it. SPSS is a reliable tool for performing the conjoint analysis that was described earlier.

Participants were, as told before, derived with the use of Facebook and e-mail. The website link could be opened on the go with the use of a smartphone or via a standard computer. This helped to spread the survey to enough participants in under three weeks.

It is of importance to collect data in a cost effective manner. With the use of Sawtooth Software, the whole research was done with reasonable cost expenditures. The software is free since it is still in a beta stage, which led to significant cost savings. The most evident reason for choosing Sawtooth Software remains the fact that no other (other than by hand) software tools were available to conduct the choice-based conjoint analysis.

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23 The Internet is a good medium when looking for a quick, easy and cost effective way of doing the research. Despite this, the Internet is subject to self-selection bias (Wright, 2005). People decide whether they want to participate in the survey, complete the survey when started or just ignore the invitation. This can result in a high percentage of uncompleted surveys with can be of annoyance to the researcher. Out of a total of 194, 92 respondents did not finish the survey. This resulted in a high drop-out rate of 47%. While this is high and undesirable, the 102 completed surveys still met the minimal sample size requirement. Since the study is performed in The Netherlands, the experiment is written in Dutch. Sawtooth provides an attractive and simple layout that is easy for the participants (and researcher) to use with less of a learning curve. In order to make sure most people fill in the survey or complete the survey, the layout is particularly important (Saunders et al., 2009, p. 387).

The experiment includes an introduction letter that clearly emphasizes the importance and purpose of the survey. It also states the approximate duration in minutes required as well as stating that anonymity is guaranteed. The end of the survey shows a short note in which the participant is thanked for his contribution as well as giving the opportunity to ask questions or share comments about the survey with the researcher (Saunders et al., 2009, p. 393).

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24 3.5 Measures

The survey is based on a choice-based conjoint analysis. Therefore, the survey first defines the individual product attributes that are being used in the experiment followed by a set of questions in which the participant had to choose a particular scenario out of four. Each scenario illustrated a purchase choice and was different from the others.

3.5.1 Brand, price and product information

After a short introduction part, all the individual product attributes were explained. The aim is to measure the relative importance of the different product attributes and their relative share in the purchase decision. Different scenarios were established in which each attribute was assigned different levels. Participants were shown a set of 4 scenarios per question in which every scenario consisted of a mix of different levels of the product attributes. All scenarios illustrated a purchase choice of a 100gr

chocolate bar that differed on price, brand and product information. Table 1 shows the product attributes that were used in this study with their corresponding levels.

Table 1 product attributes and levels in this study

Product attributes Levels

Price 1. €0,50 (low)

2. €0,95 (normal) 3. €1,95 (high)

Brand 1. AH

2. AH Puur&Eerlijk

Product Information 1. Transparant

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25 As an example, the participant might see a chocolate bar from AH with transparent product information that costs €1,95 as one of the scenario purchase options.

Price

The price attribute has also been described in the literature review and it is obvious that it is of importance for the purchase decision. According to Chang & Wildt (1994), the perceived price influences the purchase intention. And as Reed (1999) states, 85% of the customers look for price information when they shop. The price attribute levels are €0,50, €0,95 and €1,95. Since the product in question is a

chocolate bar, these levels were seen as being the most viable and correspond to the current supermarket pricing of 100gr chocolate bars in the Netherlands.

Price is a justifiable attribute to manipulate and has been used in the research of many (Fagerstrøm & Ghinea, 2011; Carter & Curry, 2010; Okechuku, 1994;

Haddad, Y., Haddad, J., Olabi, A., Shuayto, N., Haddad, T., & Toufeili, I., 2007). In all of these studies the price attribute was manipulated with the use of different price levels for different scenarios.

Brand

The importance of the brand attribute has also been described in the literature review. In essence, the brand has a positive relationship with the purchase intention since it enhances the consumer’s perception of value. In other words, consumers tend to believe they get better value when purchasing a familiar or prestigious brand.

Contradicting literature states that brand is becoming increasingly less important than before (Cohn & Wolfe, 2013) and other product attributes are becoming more

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26 important than brand. In addition, the importance of the brand diminishes when other product information becomes available (Degeratu et al., 2000).

The brand attribute is measured with the use of two levels. These two levels are Albert Heijn (referred to as AH in the continuation of this study) and Albert Heijn Puur&Eerlijk (referred to as AH P&E in the continuation of this study). By

manipulating the brand attribute, it can be seen whether consumers have a particular brand preference and also how strong the preference weighs in the purchase decision.

It is important to note that the consumer can indeed see these two brands as separate brands. Albert Heijn (2014b) stresses that their P&E brand is significantly different from their regular offerings. AH P&E is the umbrella label that covers all independent quality ‘keurmerk’ labels products in the biological, Fairtrade,

sustainable fish, free range (scharrel) and ecological food labels. This brand stands for offering more sustainable products with extra care for men, animal, nature and the environment (Albert Heijn, 2014b). In other words, AH P&E product promises that the animals were treated correctly with sufficient space and fresh air for example whereas no information can be derived from how the animals were treated in a regular AH brand product. In addition, the AH P&E is more expensive since it involves greater care and more responsible products.

Albert Heijn strives to make the everyday affordable and the special reachable (Albert Heijn, 2014a). The AH brand is focused on affordability and therefore less on the quality labels and biological or ecological products (Albert Heijn, 2014a).

Consumers who are indifferent about those efforts will choose the regular AH brand whereas environmental conscious consumers will be more focused on the AH P&E brand.

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27 Product Information

The attribute product information has been described in the literature review together with transparency. This is perhaps the most important attribute in this study since transparency is being manipulated as a level of this attribute.

In this research, product information disclosure and thus transparency only concerns the ingredients and artificial additives used and the country of origin of the product. As was stated earlier in this paper, the respondent was shown a grocery product label. A grocery product label only conveys information about the above mentioned constructs and these are therefore the only constructs in which

transparency could have been manipulated. With the use of the transparency

dimensions of Vishwanath & Kaufmann (2001), it is possible to evaluate the previous mentioned constructs.

The ingredients are a valuable component of product information since it shows a high degree of relevance for the consumer. Product information can become more relevant when there is full disclosure of the ingredients used. Ingredients are such a vital component of the product itself that information disclosure concerning ingredients comprises true transparency.

Just as with the ingredients, artificial additives are also an important component of product information. Artificial additives are often subject to a low degree of comprehensiveness since the majority of the consumers do not know what each E number means. By fully disclosing this information, it becomes possible for consumers to understand what artificial additives might be included in the product. It is therefore that information disclosure about artificial additives leads to transparency.

The country of origin is known to have a direct influence on the product evaluations (Hong & Wyer, 1989). Information about the country of origin stimulates

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28 consumers to think more extensively about other product information and is therefore particularly important (Hong &Wyer, 1989). By disclosing information concerning the country of origin, the product information in total becomes more transparent and valuable to the consumer.

The product information attribute has two levels. The transparent level

indicates that there is product information disclosure concerning the before mentioned constructs. Similarly, non-transparent product information indicates that information is lacking concerning any of the before mentioned constructs.

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29 4. Results

In this section, the results are shown of the research. First, the individual utility scores are calculated and discussed with the t-statistics. Afterwards, the total utility scores are discussed followed by the willingness to pay (WTP) results. This chapter will end with findings concerning the importance values of each attribute.

4.1 The individual utility scores of the brand attributes

The experiment used three product attributes (brand, price and product information) each having their own set of levels (two, three, two respectively). After putting all the commands in the Syntax, the analysis was run in SPSS (syntax command in Appendix B). A conjoint analysis is aimed at determining how much each product attribute contributes to the overall preference of the consumer. This contribution is called the part-worth or utility of the attribute. These utility scores indicate the positive or negative effect the attribute level has on the total preference. The part-worths are the regression coefficients and can be used to calculate t-statistics in order to validate the significance level of each utility (Hauser, n.d.). The following formula is presented:

t = Ut – 0 / se

ut

Where Ut = utility estimate of attribute level

Se

ut = Standard error of the utility estimate

The utilities are scaled to sum to zero within each attribute. That is, a positive utility shows that the particular attribute level increases the overall desirability of the

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30 product scenario whereas a negative utility decreases its overall desirability. In order to calculate the correct t-values, it is important to subtract the utility with zero since it is compared against no effect (neither positive or negative). The research has N=102 respondents which results in df (N-1) = 101. Since the model includes 8 parameters that have to be estimated by OLS (see results section 4.3), it must be that df1=8. In

order to determine the critical values of this model, df2=93 is used. The critical values

are 1,9858 and -1,9858 with this two-tailed test and significance level of 5%. Table 2 shows the individual utilities of all the attribute levels including the t statistics and p-values.

Table 2 Utilities Scores of the Attributes

Attribute levels Utility Estimate Std. Error t-statistic p-value

Brand AH 0,030 0,091 0,33 p>0,05 AH P&E -0,030 0,091 -0,33 p>0,05 Price €0,50 2,141 0,129 16,60 p<0,05 €0,95 1,342 0,129 10,40 p<0,05 €1,95 -3,483 0,129 -27.0 p<0,05 Product Information Transparent 1,008 0,091 11,08 p<0,05 Not Transparent -1,008 0,091 -11,08 p<0,05 (Constant) 6,500 0,091

The t-statistics indicate that the effects found in the brand attribute level are not significant and therefore neglectable. It can therefore be concluded that the brand attribute does not effect the purchase decision. The continuation of this paper will reflect on the brand attribute again when looking at the importance values.

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31 The price attribute is of a somewhat different nature. Price is something that introduces cost and therefore has a different relationship with its corresponding levels. A price of €0,95 is known to be higher than a price of €0,50. In contrast, such a relationship does not exist with the other two product attributes. As can be seen in Table 2, a price of €0,50 is most preferred and thus has the highest utility of 2,141. A utility estimate of 2,141 means that a price of €0,50 significantly improves the

valuation of that particular product scenario. As can be expected, the two other higher price levels have lower utility scores of 1,342 for €0,95 and -3,483 for €1,95. These results show that, everything else being equal, a price of €0,50 and €0,95 both have a positive influence on the total utility and add to the total valuation of the particular product scenario. A price of €1,95, however, has a significant negative influence on the valuation of that particular scenario and significantly lowers its total utility. Even more so, the negative effect of a high price is larger than the positive effect of a low price. These findings support H6 that states that a low price will be preferred to a high price. All effects of the price attribute where found to be significant since all

t-statistics are far larger than the critical values.

The product information attribute manipulates the transparency level of the ingredients, artificial additives and country of origin of the chocolate bar. As the utility levels show, transparent product information is the better option when compared to non-transparent product information. Transparent product information has a utility of 1,008 and therefore increases the total valuation of the product scenario whereas non-transparent product information, with a utility of -1,008, has a negative influence of the total valuation of a product scenario. In other words, consumers favour transparent product information over non-transparent product information. This supports H1 that states that transparent product information is

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32 preferred to non-transparent product information. Again, the effects of transparent and non-transparent product information show to be significant since the t-statistics far exceed the critical values.

4.2 Willingness to pay (WTP) for each attribute

It is also interesting to look at the participant’s willingness to pay (WTP) concerning each attribute used in this study. In order to do so, it is important to first calculate the value of one utility point (=1,00). That is, the value when the utility estimate increases by 1. The regression shows that the consumer gains 5,624 (utility range of price) in part-worths when the price drops from €1,95 to €0,50. It is possible to calculate the willingness to pay for each attribute. The respondent gains 5,624 utility when the price drops from €1,95 to €0,50, so therefore the value of each utility (=1,00) point is €0,267. This value is obtained by comparing the difference in price to the difference in part-worths of the price attribute: €1,50/5,643 (Hauser, n.d.).

As a result, it is possible to compute the WTP for transparency. The WTP for transparency is estimated to be €0,54 which is calculated by 2,016 (utility range of transparency) * €0,267 (value of one utility point). In other words, respondents are estimated to be willing to pay up to €0,54 more for a transparent product when

compared to a non-transparent product. Similarly, the brand attribute does not show to be subject to a increase in the WTP of the respondent. 0,06 * €0,267 results in a low €0,016 WTP for buying the AH PE product instead of the AH product. This, however, was to be expected. Table 3 shows the WTP for all attributes:

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33 Table 3 Willingness to pay (WTP) for each attribute

Attribute levels Utility Range Willingness to Pay (WTP)

Brand AH vs. AH PE 0,06 €0,016 (0,06 * €0,0266) Price €0,50 vs €1,95 5,624 Product Information Transparent vs. N-Transparent 2,016 €0,536 (2,016 * €0,266) The value of one utility point = €0,266 (1,50/5,624) *

* based on the different between the high and low price

When the value of one utility point is calculated using €0,95 and €0,50, the results differ. The value of one utility point is €0,563 (0,45/0,799) in this scenario. It is therefore better to indicate that the value of one utility point ranges from €0,266-0,563. Either way, transparency shows to be subject to a higher willingness to pay than the brand.

These WTP values are approximate rather than exact numbers due to an existing measurement error when the consumer fills in the questionnaire. As a result, the utility estimates found are less accurate than would optimal be the case. Having a larger sample size (N) could increase the accuracy of these findings.

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34 4.3 The total utility scores of each product scenario

In this conjoint analysis model, the part-worth utilities are estimated using an ordinary least-squares (OLS) regression with the participant’s preferences as the dependent variable and dummy variables for levels of attributes as the independent variables (Bak & Bartkomowicz, 2009). As a result, the before mentioned regression coefficients or utility scores were found.

The utilities estimates determine the degree of preference for each scenario. Therefore, each scenario has a total utility (U) that is the sum of a constant variable and the positive or negative conjoint utilities or part-worths of the individual attributes levels within that scenario. In order to calculate the total utility of a

particular product scenario, a formula has been created. The total utility of a particular scenario is computed as:

U = b0+b1* Dah+b2 * Dahpe+ b3 * DP1 +... + b7 * Dnot-transparent

Where U = total utility perceived by respondent, b0 = intercept

b1,… b7 = parameters of regression model (part-worth utility scores) Dah,... Dnot-transparent = dummy variable of either 1 or 0

The intercept (b0) is the base utility (6.5), which the other regression coefficients contrast with, in a positive or negative direction. For AH P&E, the corresponding beta (regression coefficient) value (b2) is -0,030 as can be seen in Table 1.

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35 A product scenario with a total utility that is higher than that of others is preferred and seen as being the better purchase choice. The higher the total utility, the more the scenario is valued or preferred. Table 4 shows the total utility of each of the twelve scenarios of this experiment. The total utility values are estimated using the formula above.

Table 4 Total Utility (U) per Product Scenario Number of

Cards Brand Price

Product Information Total Utility 1 AH €0,50 Not Transparent 7,663 2 AH €0,95 Not Transparent 6,864 3 AH €1,95 Not Transparent 2,039 4 AH €0,50 Transparent _9,679 5 AH €0,95 Transparent _8,88 6 AH €1,95 Transparent _4,055 7 AH P&E €0,50 Not Transparent 7,603 8 AH P&E €0,95 Not Transparent 6,804 9 AH P&E €1,95 Not Transparent 1,979 10 AH P&E €0,50 Transparent _9,619 11 AH P&E €0,95 Transparent _8,82 12 AH P&E €1,95 Transparent _3,995 U = b0 + b1* Dah+ b2 * Dahpe + b3 * DP1 + b4 * DP2 + b5 * DP3 + b6 * Dtransparent + b7 * Dnot-transparent

Where each dummy variable is either 1 or 0 and b0= 6,5

As can be seen in Table 4, the two scenarios with the highest total utility are the ones that have a low price of €0,50 and convey transparent product information. The 3rd and the 4th highest utilities scenarios are the ones that also convey transparent product information but in this case a normal price of €0,95.

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36 Interestingly, there seems to be very little difference in the total utility of similar scenarios that only differ in their brand attribute. For example, a product scenario of AH with a price of €0,50 and transparent product information has a total utility of 9,697. Whereas a similar product scenario that only differs with the brand attribute level, AH P&E, has a total utility of 9,619. These nearly identical utilities indicate that consumers do not attach much value to the brand. According to the literature, the AH P&E should be subject to a better brand image and therefore have a more positive effect on product valuation than the AH brand. The results contradict the literature by showing that the AH P&E brand leads to a lower total utility when compared to the AH brand. The t-statistics of brand show that any effect that might be present is not significant ant therefore of no value. Therefore, H2 was rejected.

4.4 The importance of the different attributes

The importance levels of the different attributes clearly show big the influence of each attribute is in the purchase decision. The importance of each attribute is presented as a percentage when analysing a conjoint analysis.

In order to calculate the relative importance of each attribute, it is needed to look at how much difference each attribute could make in the total utility of a product. The difference is the range in the attribute’s utility values. As is mentioned before, the utilities are scaled to sum to zero within each attribute so it must therefore be that some attribute levels have a negative utility while others have a positive utility. It does not mean, however, that the attribute level with a negative utility was seen as being unattractive. It means that, every else being equal, the attribute levels with the positive utilities are more preferred when the consumer has to choose.

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37 In order to calculate the importance values for each attribute, it is needed to first calculate the attribute utility range of each attribute. The utility range total shows how strong the influence of the product attribute is. In other words, an attribute level can have a positive utility but when it differs little from the other attribute level it is not important (significant). The attribute utility range of an attribute divided by the total attribute utility range of all attributes creates a certain importance value for that attribute. Table 5 illustrates how the importance values are calculated for the brand, price and product information attributes.

Table 5 The importance values

As is seen in Table 5, the range of each attribute is summed to a utility range total. In order to calculate the attribute importance, the attribute utility range is divided by the utility range total and multiplied by 100%.

Price is seen to be the most important attribute when making a purchase decision. With an importance value of 73,03%, it is more than two times as important relative to the second most important attribute. Price has the biggest utility range of 5,624 as can be seen in Table 5. The higher the utility range, the bigger the influence

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38 the attribute has on the valuation of the product scenario. H4 is supported since it states that price is the most important product attribute that consumer consider in the purchase decision.

Product information has an importance value of 26,18% and therefore still has a significant share in the purchase decision. Within the product information attribute, transparency has a utility of 1,008 whereas non-transparency has a utility of -1,008 and thus a total utility range of 2,016. This support H5 that states that product information transparency is the second most important attribute in the purchase decision-making process.

The brand, however, shows to be almost completely unimportant when choosing between the individual product scenarios. The importance percentage of 0,77% or the utility range of 0,06 for the brand attribute is neglectable. The product information attribute, however, has a utility range of 2,016 and is thus significantly more important in the decision making process than the brand attribute. These findings support H3.

As was seen in the previous sections, the individual and total utility scores and importance values all show the same results. The brand attribute is not seen as

important when choosing between the different alternatives. The results show that the brand adds little extra utility and therefore little added value to the consumer when making a purchase decision. Price is the most important attribute, followed by product information.

The design of the experiment shows to be consistently good. A Pearson’s R value shows the correlation between the observed and estimated preferences and in addition the strength of the particular correlation. A Pearson’s R value of 0,996 (p=.00), as was computed, shows that the estimated preferences almost always were

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39 in line with the observed preferences. In other words, almost all of the observed choices were justifiable according to the utility model.

5. Discussion

This section will discuss the findings of the research. The findings of the research are compared to the existing literature, which will show whether or not this research can support the current literature and extend it by filling the gap. In addition, the

theoretical implications and practical implications of the research are mentioned. In the last part of the discussion, the limitations of this study will be noted as well as suggestions for future research.

5.1 The importance of transparency

The existing literature states that transparency has a large influence on the purchase decision (Cohn & Wolfe, 2013). This study finds support for this notion since it was found that transparency is the second most important attribute that consumers consider when making a purchase decision. In addition, when product information was not transparent, the overall valuation of that particular product scenario became lower. The experiment shows that product scenarios that convey transparent product information are preferred when compared to product scenarios that did not convey transparent product information.

The utility range of the product information attribute was the second largest in this study. This means that, regardless of the individual utility values, product

information is seen as being the second most important attribute to consider. The WTP for transparency shows that participants are indeed willing to pay more for the transparent product option when compared to the non-transparent

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40 product option. This is an interesting finding since it shows a monetary value that can be linked to transparency within the context of a chocolate bar.

5.2 Transparency compared to price

According to Chian & Dholakia (2003), price is the most important product attribute that consumers consider during the decision-making process. Cohn & Wolfe (2013) confirm this by stating that 83% of their respondents found price to be important whereas this was 53% for transparency. With an importance value of 73% it can be confirmed that price is indeed the most important attribute that people consider. This can furthermore be confirmed since the price attribute shows to have the largest utilities estimates. In other words, the most valued price level (€0,50) is still preferred twice as much to the most valued product information level (transparency). The utility range is also more than twice as large as that of the product information attribute.

When transparency would truly be seen as being the most important determinant in the decision-making process, it would mean that people choose transparency over anything. For example, a chocolate bar that conveys transparent product information but also a high price of €1,95 should then always be preferred above any alternative (that conveys non-transparent product information). Logically, compared to a product scenario with the same price level and non-transparent product information, it is preferred higher. But if the scenario is compared to a product

scenario that induces non-transparent product information but also a lower price, it can be seen that consumers switch to the cheaper alternative. This confirms that price is indeed a stronger predictor of the purchase decision than the level of transparency. It makes sense that consumers weigh their purchase decision the most on the price level. Since price is something that introduces cost, it means that something has to be given up in order to acquire the desired product. As Gabor & Granger (1970)

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41 argue in their study, consumers have a set of internal standards (price levels) that they ought to be acceptable. When a product is not within this range, it is perceived as being a less desirable option. Since most people tend to find a price of €0,50 to be low for a 100 gram chocolate bar, it makes sense that this would be the most preferred option. Zeithaml (1982) states that consumers interpret the actual price in a way that is meaningful to them. Therefore, the strong negative influence of a price of €1,95 can be related to the fact that this is seen as being almost three times more expensive than the cheapest alternative. A price of €1,95 might thus not fall within the range of acceptable prices of the consumer as it is seen as ridiculously expensive for a chocolate bar.

5.3 Transparency compared to brand

Degeraratu et al. (2000) state that the brand name becomes less important when new or more product information becomes available. In this sense it would mean that transparent product information causes the brand to be less important. Transparency is becoming more important than ever nowadays and the importance of brand

diminishes quickly. Cohn & Wolfe (2013) show this phenomenon by stating that in 2013 only 27% of the respondent in their study found brand to be important

(compared to the 66% for transparency).

Our findings support this notion as transparency was shown to be significantly more important than the brand attribute. Even more surprising was the fact that the brand itself was found to be completely unimportant. There was found to be a slight preference for Albert Heijn compared to Albert Heijn Puur&Eerlijk although far from significant. The utility range of just 0,06 leads to an important value of just 0,77%. While this is neglectable, there does not seem to exist good reasoning why the AH

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42 brand would be preferred to the more socially responsible option AH P&E. Based on the literature, people would prefer AH P&E since a higher brand image would enhance the consumer’s perception of the value of the product (Grewal et al., 1998). This is not evident in this particular study.

The total utility scores of all the scenarios also confirm that the brand attribute does not significantly influence the valuation of the particular product scenario. All the total utilities were almost the same, regardless of the fact whether the chocolate bar was the AH or AH P&E brand.

5.4 Theoretical implications

The current literature is mainly focused on transparency in a broader context and not so much on transparency in the purchase choice behaviour of consumers. This paper contributes to that gap by showing that transparency is indeed found to be important when deciding between different product offerings. Even more so, it was seen that not being transparent about the product information could even lower the total valuation of a product offering. This is an important finding that contributes to the existing literature.

In addition, the literature that has a more narrow focus on transparency in the purchase decision mainly argues that the brand image has a big influence in the purchase decision. The higher the brand image, which originates from the brand, the more consumers are willing to spend for an identical product. This paper contradicts those findings by showing that the brand is unimportant and not a predictor at all of the purchase choice. Even more so, transparent product information has a significant higher valuation than the brand attribute. This means that consumers value

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43 itself. This is furthermore supported by the WTP for transparency when compared to that of the brand. Consumers are willing to pay a ‘premium’ for a transparent product whereas this would not be the case if the brand itself has a higher brand image. This finding has a significant impact on the current marketing field since it can change the way researchers and marketers think about the influence of transparency and the importance of the brand.

Price was found to be the most important attribute and thus the strongest predictor of the purchase choice. It means that, everything else being equal, price will always be the ultimate factor to consider. This finding is in line with the current literature that also states that price remains to be the most important factor. It can be seen that price acts as a mediator of the effect that transparency has. In other words, the price level of a product offering limits the effect that transparent product

information has. When the price becomes to high, consumer will not buy it despite how transparent the product offering might be.

5.5 Practical implications

It is important to know which product scenario is most preferred so that managers know what to focus on when designing their product. When managers have to make the brand/transparency trade off, it is better to focus on the level of transparency that the product conveys. Having a brand with a good reputation is not enough to make sure that the product is preferred to others. Consumers tend to focus significantly more on how transparent the product is and significantly less on the brand of the product.

Another important implication for managers is that it should be clear that while transparency is becoming increasingly important, price is still the ultimate

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44 decider. It should be clear that having a very transparent product is not a reason to substantially increase the price level. It does not matter how transparent the product is, when the price is just too high it will still not be chosen. This study confirms this by showing that a product of €0,95 will always be preferred to a product of €1,95, regardless of the level of transparency. In addition, the results show that the negative impact of a high price is larger than the positive impact of a low price. This means that managers can lose more when setting a high price than what they could gain with a low or fair price. Managers should therefore always keep in mind that the brand and the level of transparency is not a reason to make the product too expensive.

5.6 Limitations of the research

The sample used within this research had to been gathered within three weeks time. As a result, the sample used is relatively small (N=102). It would therefore be good to do a similar type of research with a larger sample to improve the generalizability of the research.

Besides the sample, it is remarkable that the brand attribute is shown to have such a little impact on the purchase decision in this study. Since the existing literature is in two-fold on this matter, it might be interesting for future research to put a greater emphasis on the brand attribute. This study might have been too limited on the brand attribute. It might be interesting to divide the brand into more categories (brand levels) to see if there truly is no effect on the purchase decision. Participants in this experiment might have not seen enough distinction between the two brand levels and this could have resulted in these low brand importance levels. Since participants might not have seen AH Puur&Eerlijk to be the better brand, it might also not have resulted in a higher brand image. As a result, the influence of brand image on product

The importance of product information transparency in the purchase decision and its relation to the other product attributes