The Transparency of Country-of-Origin
Information and Product Attitude: an Experimental
Analysis
Rhoxane Zois
11406526
26
thof January 2018
MSc Business Administration – Marketing Track
Amsterdam Business School, University of Amsterdam
Statement of originality
This document is written by Rhoxane Zois, who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is 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.
Abstract
In our current globalized society, the demand for greater transparency of information is growing. Specifically, with regards to companies’ global supply chains, consumers want to know which countries their products have gone through throughout the production process. This thesis investigates whether the transparency of Country-of-Origin (COO) information has an effect on product attitudes and whether this effect is moderated by consumers’ product involvement. For this examination, an online experiment was conducted to detect variances in product attitudes between different degrees of transparency of COO information. It was found that both the higher and lower levels of transparency of COO information, representing respectively the appearance of just the Country of Design or both the Country of Design and Country of Manufacture on a product’s label, lead to significantly higher product attitudes. The medium level of transparency of COO information, in which merely the Country of Manufacture was presented, did not have any statistically significant effect. Moreover, involvement was found not to influence the relationship between the transparency of COO information and product attitude.
Table of Contents:
Chapter 1: Introduction 6
Chapter 2: Literature review 12
2.1: The Consumer Decision-Making Model 12
2.2: The Theory of Reasoned Action 12
2.3: Country of Origin 13
2.4: Transparency 17
2.5: Involvement 19
Chapter 3: Theoretical Gap, Hypotheses and Conceptual Model 22
3.1: Theoretical Gap 22
3.2: Hypotheses and Conceptual Model 22
Chapter 4: Methodology 25 4.1: Research Design 25 4.2: The Pretest 26 4.3: The Experiment 27 4.4: Sample 28 4.5: Measures 29 Chapter 5: Results 30 5.1: Preliminary Steps 30 5.2: Scale Reliabilities 31 5.3: Hypothesis 1 32 5.4: Hypothesis 2 36
Chapter 6: Discussion, Limitations and Future Research 38
6.1: Discussion 38
6.2: Implications 41
6.3: Limitations and Future Research 42
6.4: Conclusion 44 Bibliography 46 Appendices 57
List of Tables and Figures:
Figure 1: Conceptual Model 23
Table 1: Descriptive Statistics 29
Table 2: Descriptive Statistics per Condition 29
Table 3: Scale Reliabilities 30
Table 4: ANOVA 33
Table 5: Dunnett’s Test (one-sided) 33
Table 6: Dunnett’s Test (two-sided) 34
Table 7: PROCESS Moderation Effect 35
Appendix 1: Pretest 57
Appendix 2: Experiment Questionnaire 59
Appendix 3: Normality of Data 61
3A: Histogram 61
3B: Q-Q Plot
Appendix 4: Mean Plot 62
Appendix 5: Involvement after Median Split 62
Chapter 1: Introduction
The impact of globalization on the industrialized world, including rapid growth in international trade, has had a major effect on businesses. International competitiveness has become a necessity for the survival of firms, as the abundance of product offerings has granted consumers all over the world access to a wide variety of products. For businesses, this has given rise to a global supply chain with the creation of products in various countries and has caused many firms to move their manufacturing locations to developing countries in order to take advantage of lower wage rates and operation costs. While this is financially enticing for businesses and can provide them with a competitive advantage (Prendergast et al., 2010), the production of a single product in different countries renders consumers’ evaluation processes and subsequent purchase decisions of these so-called ‘hybrid’ products more complex (Hamzaoui and Merunka, 2006; Essoussi and Merunka, 2007). This evaluation of products and the consequent purchase decision is brought about by beliefs, which are generated through the processing of information in the form of intrinsic and extrinsic cues (Ajzen and Fishbein, 1980).
One such extrinsic cue is the Country-of-Origin (COO) of a product, which is, especially on apparel products, often presented on the label by the words ‘made in’ followed by the name of a country. However, in today’s global business environment, this concept can encompass multiple countries along the supply chain, thus making the reliance of consumers on COO information to make evaluations and decisions harder (Chao, 2001).
Although in the United States it is mandatory to specify the COO information on each apparel product, no such regulation exists within the European Union. While there is a European
Regulation1 stating that the marking and labeling of the composition of the fibers of the product is compulsory, this Regulation does not include any provision regarding the inclusion of the country of origin of the product on the label.
Thus, with country of origin labels being voluntary in the European Union, businesses are not bound by rules and are able to use COO as a strategic and marketing tool in order to profit from country equity, to enhance a specific product attribute or simply to take advantage of country images and perceptions (Lin and Chen, 2006). For instance, when a firm’s product can be associated with a country that has a favorable image, businesses can take advantage of this by including the COO information on the label and hence influence the consumer’s product evaluation favorably. Similarly, when a product is associated with a country that has an unfavorable image, firms can simply leave this information out and not communicate it to the consumer. This flexibility in the communication of COO information on products by businesses is, however, not favored by everyone. As a matter of fact, two different proposals to make COO labeling compulsory within the EU have been put forward in 2005 and 2014, but were both blocked by some EU governments (Grubler and Schidler, 2014). EU member states with companies relying on global supply chains and thus outsourcing the majority of their production process to developing countries, which often have a more negative image, fear that mandatory labeling will negatively affect their exports (Kuik, 2004) and argue that imposing rules would be anti-free-trade and protectionist (Grubler and Schidler, 2014). On the other hand, European countries with a more favorable image and production capabilities such as Italy, Spain and France, are in favor of mandatory labeling, as they hope it will provide them with a market advantage against cheaper products from India or Asia (Grubler and Schidler, 2014).
Considering the above, opinions about compulsory COO labeling may have been divisive between EU member states in the past, but recently there has been a greater demand by consumers for information about the countries in which the products they consume have gone through throughout the production process (Bhaduri and Ha-Brookshire, 2011). Recent occurrences like the tragic factory accident in Bangladesh in 2013 and the cries for help from Turkish factory workers on Zara’s labels in 2017 have increased attention to how products are made in terms of labor and factory conditions. Furthermore, they have enhanced consumers’ desires to acquire more information about products’ origins and have thus triggered the demand for greater transparency of COO information (Bhaduri and Ha-Brookshire, 2011). What is surprising, however, is that whereas many recent studies have been tackling the transparency of information relating to factory, wage and labor conditions, no previous study has examined the transparency of COO as the sole informational cue available to consumers.
Research shows that COO information and its transparency affect consumers’ product evaluations such as product attitude, which consequently influence the consumer’s purchase decision and behavior (Bhaduri and Ha-Brookshire, 2011; Verlegh and Steenkamp, 1999; Engel et al., 1968). The fact that a single product can now originate from different countries, combined with the freedom businesses have in labeling their products with COO information, gives rise to an interesting question, namely whether the amount of COO information, representing different degrees of transparency, actually influences consumers’ product attitude and, if so, whether it does this in a favorable or unfavorable manner. Moreover, literature has demonstrated that involvement, most simply defined as a person’s level of interest in a product (Michaelidou and Dibb, 2008), influences the relationship between COO and product attitudes, depending on how personally relevant a specific product is to the consumer (Michaelidou and Dibb, 2006; O’Cass 2000,2004). As such, it is both interesting
and relevant to examine whether this relationship holds true for various degrees of COO information. Hence, the research question of this paper is as follows:
What is the effect of the transparency of Country-of-Origin information on product attitude and how is this effect moderated by involvement?
Examining this topic is relevant for several reasons. First of all, it will add to the already extensive academic literature about COO by exploring an aspect that has not yet been studied, namely the transparency of COO information, and its relationship with product attitude. Given that COO is a topic that has a significant impact on consumer behavior and transparency is a societally relevant and current topic gaining increasingly more attention and importance, the outcomes of this study can prove to be of interest to both academics and managers, especially in an era where dynamics in the global marketplace are constantly changing. Secondly, businesses, especially European ones, can profit from the results of this study by gaining a deeper understanding of the effect of the transparency of COO information on consumers’ product attitudes, which will allow them to comprehend what degree of transparency of COO information will have a more favorable effect on consumers’ product attitudes. As long as there is no EU regulation concerning origin labeling, the results will provide marketing managers with applicable insights into which COO information is meaningful to customers. Consequently, this acquired knowledge can influence competitive positioning and success in the marketplace (Prendergast et al., 2010) and will allow businesses to promote their products more effectively. Moreover, having a better understanding of consumer interest and motivation to process product information and thus understanding the way in which consumers evaluate products, will enable businesses to adjust their international marketing strategies and marketing efforts in such a way that they will be
able to better reach their consumers and provide them with a better, more personalized experience (Kuik, 2004; Samiee et al., 2016; Aboulnasr, 2007).
For this research, an online experiment was conducted, in which different degrees of transparency of COO information on a label were presented to respondents, after which both their involvement and product attitudes toward the product were measured.
For the scope of this study, the particular product category that was chosen is one that is present in everyday consumer decisions, that provides meaning in consumers’ lives and the consumption of which has a defining role in society: apparel (O’Cass, 2001, 2004; Hourigan & Bougoure, 2012). This category is interesting to examine not only because it is a “high profile and economically important sector, attracting considerable marketing spend” (Michaelidou and Dibb, 2006, p.443), but also because it is a product category that is heavily susceptible to trends, constantly changing and dynamic (Naderi, 2011). Especially with regard to its production processes and global supply chains, the apparel industry is said to be “the most globalized of all modern industries” (Bhaduri and Ha-Brookshire, 2011, p.136), which becomes apparent through the fact that a great majority of apparel is produced in multiple countries.
Furthermore, each individual can give a different meaning and personal attachment to an apparel product, suggesting that there is variation in the personal relevance attributed by consumers to such products. Hence, each apparel product can induce higher or lower involvement from consumers. This, combined with its global production process, makes apparel an interesting category to use for this research.
This thesis will start off with an examination of existing literature regarding product attitude, COO, transparency, involvement and the consumer decision-making model, after which the
design and method of the research will be explained. Next, the results will be presented, followed by their discussion and analysis. Lastly, the limitations of this study will be acknowledged and some suggestions for future research will be given.
Chapter 2: Literature Review
This chapter will give an overview of the existing literature and discuss important findings regarding the core concepts of Country-of-Origin, product attitude, transparency and involvement.
2.1: The Consumer Decision-Making Model
In order to understand the relationship between the transparency of COO information and product attitude, this thesis will use the consumer decision-making model as a broader framework through which the aforementioned concepts, together with their underlying processes, will be interpreted. Within the consumer behavior literature, the consumer decision-making process, originally conceptualized in 1968 by Engel, Kollart and Blackwell, is the most widely used model explaining the different stages a consumer goes through when making a decision to purchase a good or service. According to the five-step model of Engel et al. (1968), a consumer’s motives to purchase originate from the recognition of a particular need or problem. In order to respond to these, the consumer goes through a process of searching for information, after which he or she forms evaluations about the good or service and compares it to alternative options. Next, the consumer makes the decision to purchase, followed by a post-evaluation of the acquired product (Henderson and Hoque, 2010; Engel et al., 1968).
2.2: The Theory of Reasoned Action
The road to making purchase decisions can in part be explained by Ajzen and Fishbein’s (1980) Theory of Reasoned Action, a theory that has significantly contributed to the literature about the relationships between attitudes, behavioral intentions and behaviors. These last two
can, in line with the consumer decision-making model, be considered as the decision to purchase and the subsequent act of purchasing. The Theory of Reasoned Action states that behavioral intentions and behavior, or the decision to purchase and the actual purchase, are the outcomes of attitudes, which Ajzen and Fishbein define as the “general positive or negative evaluations of a product” (Ajzen and Fishbein, 1980 in Leclerc et al., 1994, p.264). These evaluations are formed by consumer beliefs about the specific product, which can be favorable or unfavorable (Ajzen and Fishbein, 1980). In turn, these beliefs are generated by consumers’ processing of information usually in the form of intrinsic or extrinsic information cues. Intrinsic cues include less tangible aspects of a product, such as quality and performance. These intrinsic cues are less easy to identify and consumers are often even unaware of them (Henderson and Hoque, 2010). Therefore, consumers often rely on extrinsic cues such as brand or price to evaluate a product and to infer intrinsic cues (Henderson and Hoque, 2010). Country-of-Origin is another widely used example of an extrinsic cue.
2.3: Country of Origin
Country of origin (COO), which can be defined as “the country that a manufacturer’s product or brand is associated with” (Saeed, 1994 in Lin and Chen, 2006, p.249) is considered an extrinsic information cue because the country of origin of a product can be manipulated without changing the physical product (Olson and Jacoby, 1972). COO is commonly communicated to the consumer by means of stating ‘made in’, followed by a specific country. Consumers make use of extrinsic information cues like COO in order to infer intrinsic cues and to process information, which, as mentioned before, then leads to the formation of beliefs, attitudes and purchase decisions (Verbeke, 2009; Henderson and Hoque, 2010; Prendergast, 2010).
The way people process the COO cue can be cognitive, affective, normative, or a combination of these three (Verlegh and Steenkamp, 1999). However, the great majority of COO research focuses mainly on examining the COO cue through cognitive processes (Verlegh and Steenkamp, 1999). In these studies, it is found that the COO cue acts as a ‘signal’ for product quality (Verlegh and Steenkamp, 1999), which involves cognitive processes in consumers’ minds. In these processes, “the use of a cue is determined by consumers’ perception of its predictive value”, which refers to the perceived strength of the relationship between a cue and the attribute which is to be judged (Verlegh and Steenkamp, 1999, p.525). Within COO research, this relationship between cue and product attribute is predominantly formed by consumers’ country images. These country images can differ with context or product and are influenced by many individual factors, such as previous direct or indirect experience with the country or product category or perceived fit between country and product (Josiassen, 2008; Verlegh and Steenkamp, 1999; Roth and Romeo 1992). Generally, country images can be defined as “mental representations of a country’s people, products, culture and national symbols” (Ger, 1991 in Verlegh and Steenkamp, 1999, p.525) or simply as “the overall perception consumers form of the products from a particular country” (Roth and Romeo, 1992, p.480). This perception of a specific country inevitably leads to stereotyping (Lee and Lee, 2005), a psychological process where positive or negative stereotypes are used as standards to evaluate products from foreign countries (Ahmes and D’Astous, 2008; Hamzaoui-Essoussi, 2010). Generally, stereotypes generate a more negative evaluation of products from developing countries (Hamzaoui-Essoussi, 2010).
Besides the cognitive way, the COO cue can add emotional or symbolic meaning to a product, through consumers’ association of the product with social status, authenticity, exoticness or pride (Li and Monroe, 1992; Batra et al., 1999 in Verlegh and Steenkamp, 1999), thus adding
an affective component to how consumers process the COO cue. Moreover, consumers can process the COO cue in a normative way, by holding social and personal norms related to COO (Obermille and Spangenberg, 1989). Consumer ethnocentrism, for example, enhances the motivation for a consumer’s decision to buy domestic products, by including elements like ‘sense of identity’ and ‘feelings of belongingness’ (Shimp and Sharma, 1987).
Overall, a central finding from the extensive existing COO literature is that COO has a strong influence on consumers’ product evaluations such as product attitudes and product quality, and hence also impacts purchase intentions (Schooler, 1965; Verlegh and Steenkamp, 1999; Peterson and Jolibert, 1995; Insch and Mcbride, 2004). However, even though this finding, often referred to as the Country-of-Origin effect (Josiassen, 2010) has been widely analyzed, accepted and adopted by many researchers, numerous studies have yielded different results. Therefore, many scholars still consider the COO effect to be poorly understood and deem its effects only somewhat generalizable (Verlegh and Steenkamp, 1999; Peterson and Jolibert, 1995). There are several potential reasons for this inconsistency.
First of all, though people can process COO information in a cognitive, affective or normative way, these ways of processing COO information are continuously interacting (Verlegh and Steenkamp, 1999). Therefore, the narrow focus on cognitive processes in COO research can be regarded as limiting and may decrease the generalizability of the results. Moreover, these studies found that the impact of COO on perceived product quality is stronger than it is on other types of product evaluations like product attitude (Verlegh and Steenkamp, 1999). However, when also considering and including affective and normative processes, it becomes clear that this has a greater effect on the formation of product attitudes than on perceived product quality. Thus, as product quality is just one of the factors that encompass attitudes
(Verlegh and Steenkamp, 1999) and attitudes eventually lead to purchase intentions and actual purchase behavior, the interaction of cognitive, affective and normative ways of processing a COO cue indeed has an influence on product evaluations. In fact, it has been found that, looking solely at cognitive processes inevitably leads to insignificant, inconclusive or even contradictory results (Josiassen, 2010; Phau and Prendergast, 2000; Obermiller and Spangenberg, 1989).
A second reason for this incongruity could perhaps be attributed to the fact that in a lot of previous research, COO has been treated as a single-dimensional construct (Chao, 2001; Essoussi and Merunka, 2007). In other words, COO was assumed to be a single country. However, due to the major increase in multinational production, global sourcing and various forms of competition, this single-dimensional approach has become outdated and no longer relevant nor applicable, as the majority of products, so called ‘hybrid’ products, have gone through more than one country in their production process. Thus, more recent studies have taken a multidimensional approach to examine COO and have treated it as a multifaceted construct. The most commonly used way in which this is done is by deconstructing the concept. The two most prevalent dimensions of the COO construct used are Country of Design (COD) and Country of Manufacture (COM). COD is defined as the country in which the product is planned and designed, whereas COM refers to the country in which the product is assembled (Essoussi and Merunka, 2007; Hamzaoui and Merunka, 2006; Hamzaoui-Essoussi, 2010). By deconstructing the COO concept, the informational value of the COO cue is enhanced, which subsequently affects product evaluations (Verlegh and Steenkamp, 1999). Therefore, treating the COO as a single-dimensional construct as opposed to a multi-dimensional construct yields different, less generalizable results and thus adds to the inconsistency in the existing COO literature (Peterson and Jolibert, 1995).
In sum, many studies have closely scrutinized the COO construct and its effects, but with different outcomes. However, what is known is that, in their decision-making process, consumers process the extrinsic COO information cue in different ways, which allows them to form certain favorable or unfavorable beliefs about a product. In turn, these beliefs are converted into product attitudes, which eventually lead to purchase intentions and purchase decisions.
2.4: Transparency
Having established that purchase decisions are influenced by product evaluations such as product attitudes, which in turn are formed through beliefs resulting from the processing of information, there is one more important element to consider, namely the reason why people engage in information processing in the first place. This can be explained by the fact that, in order to make an effective decision, the consumer should be able to make a distinction between comparable products. This is made possible by actively searching for product information, which in turn will then be processed, formed into beliefs and attitudes and eventually results in efficient decision-making (Davis, 1987).
The contemporary consumer is increasingly interested in various types of product information, as “today’s consumers have a need-to-know mentality” (Feitelberg, 2010 in Bhaduri and Ha-Brookshire, 2011, p.137; Tenniglo and Limbach, 2017). In particular with regard to global supply chains, consumers demand increasing amounts of information regarding the processes of how and where products are being made in various steps of the production process (Dickson, 2001 in Bhaduri and Ha-Brookshire, 2015). This can be interpreted as a demand for greater transparency on global supply chain processes of products. Transparency, which can be defined as the “visibility and accessibility of information”
(Bhaduri and Ha-Brookshire, 2011, p.136), is “premised on the notion that information matters and information can empower” (Gupta, 2008, p.3) and is, according to Bhaduri and Ha-Brookshire (2011, p.147) “becoming all the more important”.
Literature shows two main effects of the transparency of information. Firstly, companies can benefit from consumers’ demand for information by making this information an added value of the product (Bhaduri and Ha-Brookshire, 2011). In fact, transparency can be used by businesses to build their reputation, maintain business legitimacy and achieve a competitive advantage (Carter, 2008 in Bhaduri and Ha-Brookshire, 2011; Holmsten-Carrizo, 2013,Tenniglo and Limbach, 2017). Furthermore, transparency enables companies to increase customer engagement, customer trust and subsequently build customer loyalty (Holmsten-Carrizo, 2013; Tenniglo and Limbach, 2017; Kang and Hustvedt, 2014; Hustvedt and Kang, 2013).
Secondly, the transparency and availability of information allows for a reduction of consumers’ information search costs by providing information that, if not present, would be difficult to evaluate (Bhaduri and Ha-Brookshire, 2015). Moreover, transparency reduces information asymmetry, consumers’ perceived risk in making a particular decision, confusion and skepticism (Bhaduri and Ha-Brookshire, 2017; Tenniglo and Limbach, 2017). Taken together, the transparency of information is said to be an important part of information processing (Bhaduri and Ha-Brookshire, 2015). As a result, by influencing information processing, the transparency of information is the first step towards forming beliefs, product attitudes and subsequent purchase decisions.
The apparel industry is one in which transparent information is becoming increasingly relevant. Due to its global supply chains, a characteristic of this industry, the demand for transparent information is particularly high (Bhaduri and Ha-Brookshire, 2011). Within this
industry, hangtags or labels are found to be the desired locations where consumers want information to be present (Bhaduri and Ha-Brookshire, 2011). A reason for this might be that, compared to other forms of communication, labels are simple, legible, visible and provide product information in an easy, efficient and clear way (Koszewska, 2011). Thus, they serve as an easy and accessible platform to transmit the product-specific information demanded by consumers and thereby facilitate the use of it in their information search process (Verbeke, 2009; Davis, 1987). Although there are contradictory findings about whether consumers actually make use of and pay attention to the label to obtain product information (Ganiere et al., 2004), Koskela and Vinnari (2009) performed a study in which labels in textile and clothing were desired by 91.3% of respondents. Similarly, Davis (1987) states that consumers do use the product information on clothing labels to help them make clothing purchase decisions, and a study by Koszewska (2011) showed that 55% of respondents actually stated their purchasing of apparel products was “mainly impeded by the unavailability of relevant information” (p.25). These results, combined with the increasing demand for information by consumers regarding the global apparel supply chain, suggest that the label is an effective way of providing customers with the demanded product information, which can then go on to influence their information processing, formation of beliefs and attitudes and purchase decisions.
2.5: Involvement
Thus, the transparency of the information sought by consumers influences the way in which they process this information and the way it is then turned into beliefs and attitudes that eventually lead to purchase decisions. However, there is another factor that has been found to influence consumers’ product attitude in the decision-making process: involvement. In its simplest form, involvement can be described as “the level of interest in an object”
(Michaelidou and Dibb, 2006, p.444). Involvement is regarded as a multidimensional construct, as “no single construct can individually and satisfactorily describe, explain or predict involvement” (Rothschild, 1979 in Michaelidou and Dibb, 2006, p.445).
Different scholars have examined different types, antecedents and effects of this complex construct. This has resulted in a multitude of definitions, although the general consensus within the involvement literature is that the essence of involvement is personal relevance (Higie and Feick, 1989; Im and Ha, 2011; El Aoud and Neeley, 2008). This personal relevance or personal significance is brought about by the fact that when consumers become involved, they form and maintain particular relationships with or attachments to products (Michaelidou and Dibb, 2006; O’Cass 2000,2004; Naderi, 2011). However, different people perceive different products in different ways. Thus, these attachments that people form to products are very personal and can differ in nature, direction and intensity (O’Cass 2000, 2004; Naderi, 2011).
Moreover, Richins and Bloch (1986), who identified enduring, or long-term involvement as the type of involvement mostly related to products, stated that “involvement represents the long-term attachment of an individual with a specific product […], likely to be manifested through extensive information search” (Richins and Bloch, 1986 in Michaelidou and Dibb, 2006, p.7). Indeed, literature shows that the level of a consumer’s involvement is influenced by the perceived importance of the information or cues available to the individual, which then influence the extensiveness of information search and, subsequently, information processing (Hopkins et al., 2004). In other words, if the information is important to the consumer, it is personally relevant, making the consumer more involved. The consumer will then process this personally relevant information at a deeper level than if it was not personally relevant, which can be explained through Petty et al.’s Elaboration Likelihood Model (ELM). This model
states that when a consumer is highly involved, information is processed through the ‘central’ route. This entails that a person is able and motivated to think about and process the information, and will develop favorable or unfavorable responses towards this information. These responses then cause an enduring attitudinal change. This attitudinal change will be favorable when the responses are positive, and unfavorable when they are negative (Petty et al., 1983). Thus, by affecting the way in which consumers process information (Hopkins et al., 2004), involvement influences the relationship between informational cues and the subsequent response to this information, which is characterized by a change in attitude (Prendergast et al., 2010).
In sum, the transparency of information can be considered as a first step towards the formation of attitudes, by influencing the processing of an informational cue. This subsequently also affects purchase decisions. COO is an extrinsic informational cue that consumers increasingly seek, as they demand more accessible, clear and transparent information regarding a product’s supply chain. Moreover, previous literature has shown that COO has an impact on consumers’ product attitudes, and the consumer’s level of involvement is said to influence this relationship.
Chapter 3: Theoretical Gap, Hypotheses and Conceptual Model
The current chapter seeks to formulate hypotheses and derive a conceptual model from the theoretical gap that is established based on the existing literature elaborated on in the previous chapter.
3.1: Theoretical gap
Several scholars have examined COO, product attitude, the transparency of information and involvement in their studies. Particularly, the works by Verlegh and Steenkamp (1999), Bhaduri and Ha-Brookshire (2011), Henderson and Hoque (2010) and Prendergast et al. (2010) are very insightful. However, no previous study has yet examined the transparency of COO information. Though it is known that COO has an influence on product attitudes, this thesis seeks to scrutinize whether this also holds when COO is split up according to different levels of transparency. Besides providing new insight into the already extensive COO literature, this research will also contribute to the existing knowledge on how informational cues impact product evaluations such as product attitude, and subsequently influence purchase decisions.
Moreover, knowing that the relationship between COO and product attitudes is influenced by involvement, this study seeks to confirm that this also holds true when COO is divided into different degrees of transparency, thus enriching the existing research on involvement.
3.2: Hypotheses and Conceptual Model
The increasing demand for transparent information regarding a product’s supply chain means that it is likely that the presence of COO information will be perceived favorably by consumers. Upon processing this information, it is therefore expected that consumers will
form more favorable beliefs regarding the product, which will result in a more positive product attitude. Accordingly, hypothesis 1 can be stated as follows:
H1: There is a positive relationship between the transparency of Country of Origin information and product attitude.
More specifically, this research expects to find that higher degrees of transparency for COO information made available to consumers will lead to more favorable product attitudes.
Involvement influences the relationship between informational cues and the subsequent response to this information, in the form of a change in attitude (Prendergast et al., 2010). Thus, the degree of involvement acts as a moderator between information and the forming of attitudes (Prendergast et al., 2010). Considering COO is an informational cue and consumers deem the availability and accessibility of this COO information to be highly important, it is expected that consumers will be highly motivated to process this information cue. Thus, it is likely that the transparency of COO information will generate more positive responses, eventually leading to an enduring positive attitude. Accordingly, hypothesis two is as follows:
H2: The positive relationship between the transparency of COO information and product attitude is moderated by involvement, so that the relationship is stronger for higher levels of involvement.
By combining hypotheses 1 and 2 and the relationships between the different variables, the following conceptual framework is formed:
Figure 1: Conceptual Model
This thesis will attempt to fill the theoretical gap, answer the research question and test the above hypotheses by means of an online experiment, which will be explained in detail in the following chapter.
Chapter 4: Methodology
In this section, the empirical part of the thesis will be presented. First, a description of the design of the study will be given, followed by an explanation of the characteristics of the sample that was used in this research. Finally, the variables, together with their measurements will be described.
4.1: Research Design
In order to answer the research question of this thesis and to better understand the effect of the transparency of COO information on product attitude and how this effect is moderated by involvement, a quantitative approach was taken. More specifically, an online experimental, between-subjects design was adopted. This online experiment took the form of a survey, in which respondents were randomly allocated to one of four conditions. Three of these conditions represented a degree of COO information transparency, namely high, medium or low, and the fourth condition acted as the control group. As the two main dimensions of COO information used in literature are country of design (COD) and country of manufacture (COM), the conditions included either one of these dimensions, both, or none. The allocation of a degree of transparency to a type of COO information was partly based on Bhaduri (2017)’s research. In his study, though focusing mainly on the transparency of Corporate Social Responsibility (CSR) information in the USA, he stated that “a message was considered highly transparent when information was provided on whether the brand designs […] and manufactures their products in the USA and low transparent in absence of such information” (p.298). Grounded on this statement, a pretest (N=15) was conducted in order to test whether it also holds true for the perceived transparency of COO information, and not only for the USA.
4.2: The Pretest
In the pretest, respondents were presented with four questions, as shown in Appendix 1. In the first question, after being given a definition of transparency, participants were shown statements regarding their perception of the transparency of each of the COO dimensions that they subsequently had to rate on a 7-point Likert scale. In the second question, participants were asked to rank the different dimensions of COO information according to how transparent they thought the dimensions were. In essence, these two questions measured the same thing. However, by asking people to clearly rank the four dimensions (COD only, COM only, COD and COM, no COO information) from 1 (most transparent) to 4 (least transparent), it was possible to obtain a clearer understanding of the type of COO information respondents perceived as being more or less transparent. Responses showed that people perceive the availability of both COD and COM information on a label to be the most transparent, followed by COM only and subsequently COD only. Respondents perceived the absence of COO information to be the least transparent. These results, which are also in line with the findings by Bhaduri, formed the basis for the characterization of the four conditions.
The remaining two questions in the pretest sought to understand respondents’ perceptions of 7 different EU countries regarding their ability to efficiently manufacture a pair of jeans and to produce a high quality design of a pair of jeans. This was measured by having respondents rate these different countries on a 5-point Likert scale, ranging from very unable to very able. Jeans were the apparel product chosen for the online experiment because they are considered a highly visible and popular product (Kuik, 2004), thus making it a relatively easy and familiar product for people to form opinions about. Moreover, most consumers own a pair of jeans, and in fact, 97.8% of respondents in the sample of the actual experiment stated that they wore jeans sometimes or often.
The 7 countries used in the pretest question were countries belonging to the EU, as it is in the EU that COO labeling is not mandatory. Moreover, they were considered not to be major manufacturers or designers of apparel products, and countries often used in COO research such as Italy, France and Germany were deliberately excluded. By having respondents rate different countries’ capacities, the goal was to find a EU country of which consumers have a neutral perception relating to the manufacturing and designing of a pair of jeans. The main reason for this is that it has been found that when consumers have a specific country image or stereotype towards a country, this creates biases when using COO information, that subsequently have an effect on product evaluations (Hamzaoui and Merunka, 2006; Hamzaoui-Essoussi, 2010). Thus, in order to “avoid situations where the relevant consumer beliefs are intractable” (Obermiller and Spangenberg, 1989, p.3), and to increase consumers’ reliance on COO when forming product evaluations (Schaefer, 1997), this study has purposefully chosen a country for which consumers’ perceptions were found to be the most neutral, namely Greece. In the pretest, Greece was the country that most respondents indicated as ‘neither able nor unable’ for both the manufacturing and designing of a pair of jeans. Hence, this country was chosen as the country to be used in the experiment and was held constant throughout all conditions in order to avoid any potential bias due to country images or stereotyping (Hamzaoui and Merunka, 2006; Hamzaoui-Essoussi, 2010)
4.3: The Experiment
In the actual experiment, respondents, after being randomly assigned to one of the four conditions, were all told to imagine they were shopping for a pair of jeans. They were then shown a label that supposedly belonged to a pair of jeans they had just picked up. This label included information held constant throughout the four conditions such as general washing descriptions, a fiber composition considered standard for jeans (98% cotton, 2% elastane) and
the fictitious, non-existent brand name ‘ZAFI’. The reason for including these different types of information cues is that is has been demonstrated that single-cue studies, which were often employed in earlier COO research, lack realism and cause inflation of effect sizes (Bilkey and Nes, 1982; Verlegh and Steenkamp, 1989). Therefore, within COO research, it has essentially become the norm to use multiple cues in every study, which enables the simulation of actual market conditions (Chao, 2001).
In addition to the mentioned information cues, each condition included one of the statements ‘Designed in Greece’, ‘Manufactured in Greece’ or ‘Designed and Manufactured in Greece’. In the control group, no information regarding the country of design or manufacture was mentioned on the label. All respondents were then asked to respond to questions measuring their product attitude toward the pair of jeans, as well as their involvement with the product in general. The reason why involvement was not made part of an actual condition in the study design was that, as has been advised by Malhotra (2004), it is better to use a median to split the respondents into low and high involvement groups upon analyzing the data.
Lastly, respondents were asked questions regarding their age, gender, nationality and highest degree of education they had completed. These demographics were used as control variables. Moreover, by inverting some of the Likert scale questions, a careless response check was carried out. The relevant questions as stated in the actual questionnaire can be found in Appendix 2.
4.4: Sample
Non-probability convenience sampling was used for this research. As there was no limit with regard to the population that could be used for this study, the survey was sent out to respondents online, through Facebook and email. This resulted in a total of 262 respondents, of which 37 were discarded due to partial response. Thus, this research was carried out with a
sample of N=225. Of these respondents, the majority was female (69.82%). Moreover, respondents’ age ranged from 17 to 67 (M= 26.12, SD= 7.74), although most respondents fell in the age range between 22 and 24, indicating a plurality of student respondents. Furthermore, 54.5% of respondents had completed their bachelor’s degree and 33.78% had obtained their master’s degree. As for the respondents’ nationalities, the majority was Dutch (44.14%), although the rest of the sample included 26 other nationalities from four different continents.
4.5: Measures
Product attitude
The dependent variable product attitude was measured using a scale by Verlegh et al. (2005), which included three items scored on a 7-point Likert scale. These items were ‘I like these jeans’, ‘I appreciate these jeans’ and ‘I have a positive image of these jeans’. This particular scale was chosen mainly because of its high reliability (Cronbach’s α =.94)
Involvement
Involvement was measured using Zaichowsky’s (1994) ten-item scale, which was adopted from Prendergast et al. (2010), and scored on a 7-point semantic differential scale (Cronbach’s α =.94). The items of this scale included bipolar adjectives such as important vs. unimportant, boring vs. interesting, relevant vs. irrelevant, unexciting vs. exciting, means nothing vs. means a lot to me, appealing vs. unappealing, fascinating vs. mundane, worthless vs. valuable, involving vs. uninvolving and not needed vs. needed.
Chapter 5: Results
This chapter presents the findings from the analysis of data collected from the online
experimental survey and provides further insight into the two hypotheses that were tested as part of this research.
5.1: Preliminary Steps
Before starting the analysis of the data, some necessary steps were taken in order to ensure the dataset was ready to be analyzed. First, the raw data from the different respondents was transformed and recoded into a categorical variable to represent the various degrees of transparency of COO information, in line with the results of the pretest. These degrees were low transparency, where only COD information was given, medium transparency, where only COM information was presented, high transparency, where both COD and COM information was given, and no transparency, constituting the control group in which no COO information was given to respondents. Secondly, after a frequency check in order to make sure there were no errors present in the dataset and the recoding of counter indicative items, the scale means were computed. The descriptive statistics of the variables can be found in Table 1 below. Table 2 shows the descriptive statistics per condition.
Variable Mean St. Dev Min Max
Product Attitude 4.93 0.93 2.3 7 Transparency of COO information 2.44 1.14 1 4 Involvement 4.71 1.17 1 7 Age 26.12 7.74 17 67 Gender 1.71 0.47 1 3
Education level 2.23 0.65 1 5
Nationality 2.83 1.83 1 4
Table 1. Descriptive Statistics
Variable N Mean St. Dev St.
Error Lower Bound Upper Bound Min Max Low Transparency 62 5.01 0.86 0.11 4.79 5.23 3 6.3 Medium Transparency 56 4.90 0.87 0.12 4.67 5.13 3 6.3 High Transparency 52 5.33 0.74 0.10 5.12 5.53 4 7 Control 55 4.51 1.06 0.14 4.22 4.79 2.3 7 Total 225 4.93 0.83 0.06 4.81 5.06 2.3 7
Table 2. Descriptive Statistics per Condition
Subsequently, a normality check was performed to ensure the data was distributed symmetrically around the center of all scores. A histogram with a bell-shaped curve, a Q-Q plot with plots on the diagonal line and skewness and kurtosis tests all proved the normal distribution of the data. Detailed versions of these graphs can be found in Appendix 3.
5.2: Scale reliabilities
Following these initial steps, reliability checks were performed on all variable scales and interpreted by means of the Cronbach’s alpha, which should be higher than 0.7 in order to ensure reliability and validity (Cortina, 1993). As can be seen in Table 3, both the dependent variable and the moderating variable had a Cronbach’s alpha higher than 0.7, thus proving their reliability and internal validity. More specifically, product attitude and involvement had a reliability score of α= .91 and α= .93 respectively. This indicates the suitability of these variables for the further proceedings of the analysis.
Variable Cronbach’s α
Product Attitude 0.91
Involvement 0.93
Table 3. Reliability Scales
After the data preparation and reliability checks proved to be suitable for further analysis, the hypotheses were tested.
5.3: Hypothesis 1
Hypothesis 1 suggested a positive relationship between the transparency of COO information and product attitude. In other words, a higher degree of transparency of COO information should lead to higher or more favorable product attitudes. For this combination of variables, it is advisable to perform a one-way ANOVA. However, given the presence of control variables, an ANCOVA was first performed. The outcome of the ANCOVA shows a significant result of the transparency of COO information on product attitude, while controlling for gender, age, nationality and education, F(3,214) = 7,7, p< .001. None of the control variables yielded a significant result, thus suggesting that they do not influence the hypothesized relationship.
Although the statistically significant result between the independent and the dependent variable shows that there is a difference between some conditions in the experiment, there is a need for post-hoc comparisons in order to provide further insight. As the independent variable, transparency of COO information, is a categorical variable and includes 4 different conditions of which one is a control group, Dunnett’s test would be the most suitable post-hoc test for analyzing the hypothesized relationship (Field, 2013). With this test, it is possible to compare the control group means against all other group means to see whether they differ from each other.
However, Dunnett’s test could not be performed with SPSS, the statistical software used for this study, in combination with the ANCOVA. Instead, only a limited amount of post-hoc tests were available, such as Tukey’s LSD test, which is not recommended, and the Bonferroni or Sidak tests, which are less appropriate (Field, 2013). Moreover, these tests all execute pairwise comparisons, which are not applicable to this research.
It is, however, possible to implement Dunnett’s test with a one-way ANOVA. Since control variables were found not to influence the hypothesized relationship, a one-way ANOVA could be performed, and with it Dunnett’s test.
Accordingly, a one-way ANOVA was conducted in order to compare the effect of the transparency of COO information on product attitudes in four conditions: low, medium, high and no transparency of COO information. Before running the ANOVA, variables were analyzed to ensure they met all the assumptions required for this type of analysis. The six assumptions that should be met include having a continuous dependent variable, a categorical independent variable, independence of observations, no significant outliers, a normal distribution and homogeneity of variance. The variables used in this research met all six criteria. Product attitude, the dependent variable, is continuous, and transparency of COO information, the independent variable, is categorical. Moreover, there were different participants in each condition thus ensuring independence of observations. There were no significant outliers and the normal distribution of the dependent variable was already proven by means of a histogram, by a Q-Q plot and by the skewness and kurtosis tests in the preliminary steps. Lastly, homogeneity of variance, or homoscedasticity, was tested for by means of Levene’s test, which yielded a statistically insignificant result (p= .052, p<.05). From this insignificance, it can be deducted that the data meets the assumption for
homoscedasticity. Thus, as all 6 assumptions are met, the one-way between subjects ANOVA can be performed.
This analysis, summarized in Table 4, showed a significant effect of the various degrees of transparency of COO information on product attitudes, F(3,221)=7,765, p< .001. The effect size, calculated by η2, was 0.095, representing a medium effect (Cohen, 1988). From the ANOVA result, it can be concluded that there is a statistically significant effect between some of the conditions in the experiment.
Sum of Squares df Mean Square F Sig Between Groups 18.39 3 6.13 7.77 .000 Within Groups 174.50 221 .79 Total 192.89 224 Table 4. ANOVA
In order to determine between which groups the statistically significant effect is present, Dunnett’s post-hoc test was conducted. As H1 of this research suggested a positive relation between the transparency of COO information and product attitude, it was expected that all group means would be higher than the control group mean. For this reason, a one-tailed Dunnett’s test was performed, the results of which can be found in Table 5. The analysis showed significant results for all groups. Specifically, the high transparency level group was found to have the highest significance (p= .000, p<.05), followed by the low transparency level group (p= .004, p<.05) and the medium transparency level group (p= .029, p<.05). Thus, these statistically significant results indicate a positive relationship between the transparency of COO information and product attitude.
Condition I Condition J Mean Diff (I-J)
St. Error Sig Lower
Bound Low Transparency Control 0.50 0.16 0.004 0.16 Medium Transparency Control 0.39 0.17 0.029 0.04 High Transparency Control 0.82 0.17 0.000 0.46
Table 5. Dunnett’s Test (one-sided)
However, looking at both the p-values and the mean plot, which can be found in Appendix 4, it can be observed that there is, in fact, no linear relationship between the variables, as the mean difference of the medium transparency level group is lower and the p-value is higher than those of the low transparency level group. Therefore, there is a motive to investigate and explain the cause of these differing scores. In order to detect the reason for this anomaly, a two-tailed Dunnett’s test was performed, the results of which can be found in Table 6. Even though this test does not directly measure the hypothesized relationship as stated in H1, a two-tailed test “accounts for all possible outcomes, providing more valuable, unbiased insights which can be reported on with confidence” (Valee, 2015, p.1).
The two-tailed Dunnett’s test revealed a significant result of the high transparency level group (p= .000, p<.05) and of the low transparency level group (p= .007, p<.05) but no significance was found for the medium transparency level group (p= .057, p<.05).
Even though the means of the three conditions are greater than the control group mean, only the high and low transparency level groups yielded significant results. Whereas the results of these two groups would indicate a positive relationship between the transparency of COO information and product attitude, the medium transparency level group showed no significantly higher product attitude than the control group. Therefore, hypothesis 1 can only
Condition I Condition J Mean Diff (I-J)
St. Error Sig Lower
Bound Upper Bound Low Transparency Control 0.50 0.16 0.007 0.11 0.89 Medium Transparency Control 0.39 0.17 0.057 -0.01 0.79 High Transparency Control 0.82 0.17 0.000 0.41 1.22
Table 6. Dunnett’s Test (two-sided)
5.4: Hypothesis 2
After having tested the relationship between the various degrees of transparency of COO information and product attitude and having only partially accepted Hypothesis 1, the moderation of involvement on the above-mentioned relationship was tested. This was done by using Hayes’ PROCESS program on SPSS, which measures the moderation effect of a variable M on the relationship between X and Y. Applied to this research, the objective of the moderation analysis was to find out whether involvement moderates the relationship between the transparency of COO information and product attitude and, if so, how. The variable involvement, which was initially a continuous variable, was transformed into a categorical variable containing two categories: high and low involvement. The allocation of participants into either one of the categories depended on whether their mean involvement score was situated below or above the median score, which was 4.7. Accordingly, each participant was assigned to one of the two categories. From all participants, 55.6% was considered highly involved and 44.4% lowly involved. The full breakdown of these results can be found in Appendix 3.
Subsequently, the moderation analysis was performed. The results, as illustrated in Table 7, show a statistically insignificant interaction (p= .773, p <.05). Thus, it can be concluded that
involvement does not moderate the relationship between the transparency of COO information and product attitude. Hypothesis 2 was therefore rejected.
Coeff Se (HC0) t p Lower Bound Upper Bound Constant 4.93 0.06 81.14 0.00 4.81 5.05 Transparency -0.11 0.06 -1.98 0.06 -0.22 -0.00 Involvement 0.19 0.12 1.57 0.12 -0.05 0.44 Interaction 0.03 0.12 0.29 0.77 -0.19 0.26
Table 7. PROCESS Moderation Analysis
To summarize, this research found that respondents in both the low transparency of COO information group and the high transparency of COO information group showed significantly higher product attitudes than the control group. In other words, showing both the COD and COM of the product generates the highest product attitudes, followed by showing merely the COD of the product. Surprisingly, no statistically significant results were found for the medium transparency level group, who were only shown the COM. Taking this into account, Hypothesis 1 could only be partially accepted. Furthermore, a moderation effect of involvement on the relation between transparency of COO information and product attitude was tested, but produced no statistically significant results. Therefore, hypothesis 2 was rejected.
Chapter 6: Discussion, Limitations and Future Research
In this chapter, the main results obtained in the previous chapter will be elaborated on in more detail. Moreover, the shortcomings of this research will be exemplified and recommendations for future research will be given. This chapter will close with a general conclusion of the research.
6.1: Discussion
Several points of discussion arise from the findings of this research. Firstly, the current experiment found that the most transparent degree of COO information, namely both COD and COM, resulted in the highest product attitudes across conditions. Similarly, the control group was found to have the lowest level of product attitudes. This suggests that increased transparency of COO information leads to the formation of more favorable product attitudes. This finding is in line with previous literature in the field setting forth that the transparency of information is both becoming more requested by and more important to consumers and is therefore influencing their information processing and formation of favorable beliefs, which subsequently lead to the development of product attitudes (Bhaduri and Ha-Brookshire, 2015). Contributing to this literature, the present research examined whether this process also holds for the transparency of COO information. When merely looking at the differences between the high level of transparency group and the control group, it can indeed be seen that more transparent COO information leads to more favorable product attitudes.
Whereas this result was consistent with the existing literature on COO, transparency and product attitudes and thus somewhat expected, there were also some less anticipated results, such as the fact that the respondents of the medium transparency level group, in which only
the COM was shown, had a lower product attitude than the low transparency level group, who were only shown the COD.
This outcome is interesting for several reasons. First of all, the allocation of degrees of transparency to the type of COO information presented was decided based on the pretest conducted before the experiment. The pretest showed that consumers perceived the portrayal of the COD information only to be less transparent than the display of the COM information. This is not surprising, as manufacturing processes are mostly relocated to less developed countries in order to financially benefit from the cheap labor and production costs (Prendergast et al., 2010). Consumers often have a more negative image of these countries, so when a brand mentions a negative piece of information on the label of their products, this could be interpreted as the brand being more transparent. However, in the experiment, people’s attitude towards the product when only shown the COD was significantly higher than when participants were shown only the COM. This could perhaps be attributed to the fact that the pretest was performed only on a limited sample that was not generalizable to the whole population, who may perceive the statement of COD to be more transparent than merely being shown the COM. Or it could be that, because consumers are more used to seeing just the COM on the label, which is usually communicated by ‘made in’ and is compulsory in some countries outside the EU, they perceive this as less transparent than when seeing the COD, which they less expect.
This incongruity might also stem from other factors, less related to the perceptions of this research’s population. For instance, when considering the product chosen for this experiment, namely jeans, the COM information is not as important to consumers as it would be for other products. A study by Rahman (2011) indicates that for jeans, the most important cue that people process is not the extrinsic COO cue but the intrinsic cue of fit, which Rahman defines
as “the conformance of a garment to an individual’s body type or size”. As fit has more to do with fashion trends, taste and comfort (Rahman, 2011, p.3), this implies a greater contribution to the product from the designers rather than from the manufacturers. Therefore, including the COD on a jeans’ label could favorably influence consumers’ perception of fit, which would then lead to the formation of more favorable product attitudes. Thus, it is possible that it was not the transparency of COO information that caused the low level of transparency group to have higher product attitudes than the medium level, but that respondents’ derivation of the cue of fit from the statement of COD caused the increase in product attitudes.
The second major finding of this study which led to the rejection of Hypothesis 2, namely that involvement does not moderate the effect of transparency of COO information on product attitudes, also stands in contrast with prior literature. In fact, the literature on involvement, COO and product attitude indicates that involvement influences the relationship between COO and product attitudes (Prendergast et al., 2010). When a piece of information is personally relevant to a consumer, this information cue will be processed more deeply according to Petty et al.’s (1983) ELM model, by making use of the central processing route. By taking this central route, the consumer is considered to be able and motivated to think about the information cue, which eventually leads to a positive attitude change (Petty et al., 1983). However, whereas involvement does influence the relationship between COO and product attitude, this was not found to hold true when COO is split up according to the degree of transparency of the COO information. This can perhaps be explained by the fact that respondents did not find the product very personally relevant, or they did not use the central route of processing. Instead, they could have used the peripheral route, which denotes that they were either not able or motivated to process the informational cue, or they just used the COO information as a simple acceptance cue (Petty and Cacioppo, 1984). Moreover, it is
possible that more respondents considered jeans to be a utilitarian product rather than a hedonic one. As it is more likely for people attaching value to the utilitarian character of the jeans to follow the peripheral route (Petty et al., 1983), this could be an explanation for the non-significant effect of involvement on the relationship between the transparency of COO information and product attitude.
All in all, this research found that various degrees of transparency of COO information have an effect on product attitudes. However, this relationship is not linear, as lower product attitudes were found for the medium transparency level group than for the lower transparency level group. This could be due to the limited generalizability of the pretest results on which the allocation of transparency degrees was based, or due to other factors such as the importance of fit for jeans. Furthermore, involvement was found not to have a significant effect on the relationship between the transparency of COO information and product attitudes, which could mean that respondents did not perceive jeans as being very personally relevant, or they considered jeans to be a utilitarian product, implying they took the peripheral route of processing the COO cue.
6.2: Implications
The findings of this research are interesting for both academics and marketing managers. First of all, this thesis adds to the already extensive literature on COO by examining the concept through the lens of transparency, a topic that is currently very relevant and is expected to become more important in the future. Moreover, by attempting to explain the concept of the transparency of COO information through the consumer decision-making model and integrating the Theory of Reasoned Action into it, an original way of looking at COO research
was developed. This could be of interest to scholars seeking to dive deeper into this topic and possibly find other linkages or fitting theories that tie these concepts together.
Secondly, the results of this thesis could be interesting to marketing managers and businesses. The finding that some types of COO information that are perceived as more transparent result in higher product attitudes, which according to the theory subsequently result in purchase decision and actual purchases, means that managers can use this information when considering what COO information to put on their products’ labels. This is especially relevant for companies that export their products within the EU, due to the lack of EU regulations concerning COO information on labels. Thus, as it was found that stating either just the COD or both the COD and COM of the product leads to significantly higher product attitudes, choosing to disclose either of these options on a label could be beneficial to the company. Moreover, not including any COO information on a label was found to be the least beneficial option. Therefore, the findings of this thesis are valuable for businesses insofar as they empower them to have increased control over consumers’ attitudes. Hence, this indirectly also hands them more control over consumers’ purchase decisions and actual purchases.
6.3: Limitations and Future Research
A first limitation to this research resides in the sample. In fact, a non-probability convenience sample was used to collect the necessary data. This can decrease generalizability and increases the risk for lower external validity. Therefore, a similar experiment with a more specific sample could yield more accurate, generalizable results.
Secondly, the majority of the respondents were students. Even though this could also potentially reduce the generalizability of the results, it has been reported that “the use of student samples for studying COO effects is encouraged […] because of their homogeneous composition” (Baugh and Yaprak, 1993 in Brijs et al., 2006, p.142). Moreover, other studies
