The role of money attitudes in Fair Trade purchase intention forming.

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MSC THESIS DUAL DEGREE MASTER: ADVANCED INTERNATIONAL BUSINESS MANAGEMENT & MARKETING.

The role of money attitudes

in Fair Trade purchase

intention forming.

A survey study towards the understanding of the

potential moderating role of money attitudes on the

effect of the components of the extended Theory of

Planned Behavior on Fair Trade purchase

intention.

Jasper Meijer Date of submission: 07/01/2019. Word count: 12560. University of Groningen Student Number: S2556529 Supervisor: Dr. Jiyoung Shin University of Newcastle

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Abstract

The rise of ethical consumerism has led to an increase in academic interest in this topic. Especially the purchase of Fair Trade products has been a topic of interest. However, prior studies focused around this topic have either taken a socio-psychological- or an economic approach. This study aims to combine both approaches, by looking at how consumer intentions are formed according to the extended Theory of Planned Behavior and how feelings of financial distress and financial security affect this relationship. Using multiple linear regression analysis, survey findings reveal that ethical considerations and motives are one of the most important predictors of Fair Trade purchase intention. In addition, financial security is found to directly influence Fair Trade purchase intention. Negative moderating effects are found for financial distress on the relationships between both perceived behavioral control and Fair Trade purchase intention and internal ethics and Fair Trade purchase

intention. However, when financial security and financial distress are put into the same model, only the moderating effect of financial distress on the perceived behavioral control – Fair Trade purchase intention relationship remains significant. Controlling for gender, findings also reveal that women rather than men are more likely to purchase Fair Trade products. Implications and directions for future research are being discussed.

Key words: Ethical consumerism – Fair Trade consumption – extended Theory of Planned

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Acknowledgements

I would like to thank Dr. Elizabeth Alexander, from Newcastle University, who has been heavily involved in this research from the very beginning and Dr. Jiyoung Shin, who stepped in as my supervisor from the University of Groningen since September 2018. They have been providing me with loads of help, advice and support through the learning process of writing this thesis.

Furthermore, I would like to thank Dr. Paulus Aditjandra from Newcastle University and the people from the ‘Methodology shop’, from the University of Groningen, who have provided me with useful insights and guidance on the methods that have been used in this study.

In addition I would like to thank all of the participants who filled in the survey in order to provide me with the information needed to conduct the analyses used in this paper. I am grateful for the time and effort that they have put in.

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1. Introduction

Ethical consumerism is nothing new on the horizon. However, it is only from recent years that it became of increasing importance within the field of business (Singh et al., 2012). One reason for this is the increasing awareness amongst consumers of the impact of ethical behavior within the business and their ability to potentially influence this behavior through their buying behavior (Gillani & Kutaula, 2018). These so-called ‘ethical consumers’ include moral and ethical features more and more in their purchasing decisions (De Ferran & Grunert, 2007). The rise of these ethical consumers has been observed across a variety of different studies (Valente, 2015).

One of the main concerns for ethical consumers is the concept of Fair Trade (De Pelsmacker et al., 2005). The aim of Fair Trade is to improve both the working- and living- conditions of small-scale growers, farmers and workers in third world countries (Andorfer & Liebe, 2015) and paying these groups fair and stable prices for their products and services (O’Connor et al., 2017). Because of this, a price premium is associated with the purchase of Fair Trade products (Arnot et al., 2006). The Fair Trade market has been growing rapidly (Krier, 2008), making Fair Trade the most successful and high profile form of ethical consumption in terms of marketing (Newholm & Shaw, 2007). However, even though the observed growth of the Fair Trade industry indicates that the amount of people who buy Fair Trade products is rapidly growing (Nicholls, 2010), there is no consensus as to how the intention to purchase Fair Trade products is exactly formed and it remains unclear ‘who’ exactly buys Fair Trade products (Doran, 2008).

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Yeow et al., 2013). However, studies aimed at tightening this gap through empirical research are currently lacking (Chatzidakis et al., 2016). The aim of this study is to improve the

understanding of determinants of decision making in the Fair Trade purchasing context. Thus, the focus is on the reported disparity between consumer attitudes and their intention, rather than the potential disparity between intention and actual behavior.

Studies which explored Fair Trade consumption from an economic approach were mainly focused on estimating the height of the premiums consumers would be willing to pay for Fair Trade products (Andorfer & Liebe, 2012). Several studies have been conducted in order to estimate the height of these price premiums. However, the reported outcomes of these studies differ, even if the products that are subject in the studies are almost identical. For instance, Loureiro & Lotade (2005) report consumers indicate they are willing to pay a premium between 2,4 and 3,3 percent for Fair Trade coffee, while De Pelsmacker et al. (2005), report that the premium consumers indicate they are willing to pay for the same product is set around 10 percent. While one might be inclined to assume that because of the higher price of Fair Trade products these differences could be explained by different levels of income, this is not necessarily the case as ethical consumerism (and therefore the

consumption of Fair Trade products) appears to exist in different income classes and is unrelated to work status (Laroche et al., 2001). Studies by De Pelsmacker et al. (2005) and by Pepper et al. (2009) even reported that income and a willingness to pay premiums for ethical products, such as Fair Trade products, are completely unrelated.

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have been found to affect consumption patterns of consumers (Andreasen, 1984). Thus, consumers differ in their attitudes towards the economic environment and their personal finances (e.g., Kamakura & Du, 2012). Given the higher price that consumers have to pay for Fair Trade products, this raises the question whether differences in money attitudes could potentially influence how Fair Trade purchase intentions are being formed.

This is where this research aims to step in. The purpose of this study is to investigate whether or not differences in money attitudes influence the effect of customer attitudes on their purchase intention of Fair Trade products. The contribution of this study will be focused on extending the existing theory on the influence of consumer attitudes on Fair Trade

purchase intention by examining the influence of financial security and financial distress within this context. In order to do so, a survey was conducted and the dataset that was generated from this survey was analyzed using multiple linear regression analysis. The outcomes provide new insights compared to previous research by suggesting that financial security is an important direct predictor of Fair Trade purchase intention, meanwhile financial distress influences the relationship between different consumer attitudes and Fair Trade purchase intention in a negative way.

The rest of this paper is organized as follows; in the next section the literature on consumers’ intention to purchase Fair Trade products and differences in personal price related factors on consumer behavior will be reviewed. After this, the methodology used to conduct the analysis will be outlined, followed by the results of the analysis. The results will be

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2. Theoretical Background

2.1 The Theory of Planned Behavior

The most prevalent approach that is applied in previous research with regard to the relationship between the consumer attitudes and Fair Trade consumption is the ‘Theory of Planned Behavior’ (Andorfer & Liebe, 2012). This theory evolved from the early work of Ajzen and Fishbein (1980), and more specifically from their theory of ‘reasoned action’. The Theory of Planned Behavior was first introduced by Ajzen (1985), who added a third

predicting variable (i.e. perceived behavior control) to the theory of reasoned action.

According to the Theory of Planned Behavior, an individual’s behavior follows directly from the intention to carry this behavior out. This intention is formed directly through the

individual’s attitude, subjective norm and perceived behavioral control regarding this behavior (Ajzen, 1991).

The first component of this theory, attitude, can be defined as “the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question” (Ajzen, 1991, p. 188), which is in this case is the purchase of Fair Trade products. The second component of the Theory of Planned Behavior, subjective norm, can be defined as the

“perceived social pressure to perform or to not perform the behavior” (Ajzen, 1991, p. 188). The last component of the Theory of Planned Behavior is perceived behavioral control, which refers to the “perceived ease or difficulty of performing the behavior” (Ajzen, 1991, p. 188). The Theory of Planned Behavior has been used to successfully explain behavior in a variety of fields (Armitage & Conner, 2001). However, as Ajzen (1991) revealed in his study, the predicting power of each of these three different components of the Theory of Planned Behavior is likely to differ across different settings. For instance, depending on the behavior that is being analyzed, it might occur that only one or two of the components of the Theory of Planned Behavior are significant predictors (Ajzen, 1991).

The Theory of Planned Behavior has been applied extensively in existing consumer research (De Cannière et al., 2009) and has shown a compelling ability to successfully predict consumer behaviors (Conner & Armitage, 1998). For these reasons the Theory of Planned Behavior is arguably the best option to analyze the Fair Trade purchase intention of

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of Planned Behavior is that it does not take any social issues or ethical considerations into account (Ozcaglar-Toulouse et al., 2006). Especially in the Fair Trade consumption context, where consumer behavior is often more focused around concern for others, the inclusion of a more ethical measure within the Theory of Planned Behavior is essential (Shaw et al., 2000).

Thus, in order to increase the predictive ability of the Theory of Planned Behavior in the context of Fair Trade purchase intention, the inclusion of ethical obligation and self-identity to the original Theory of Planned Behavior has been proposed in studies of Shaw et al. (2000) and Ozcaglar-Toulouse et al. (2006). Ethical obligation can be defined as “an individual’s set of internalized ethical rules, which reflect their personal belief about right and wrong” (Shaw et al., 2000, p. 882). The second proposed additional predictor of intention, self-identity, is concerned with “ethical concerns of an individual that become central to this individuals’ identity” (Shaw et al., 2000, p. 882).

This extended version of the Theory of Planned Behavior has been applied and tested in the Fair Trade consumption context in several studies (See Andorfer & Liebe, 2012 for an overview). The first study to test this extended version was conducted by Shaw et al. (2000), which reported that attitude, perceived behavioral control, ethical obligation, and self-identity all significantly influenced the purchase intention of Fair Trade products, whilst subjective norm in this study did not. Following this study, a variety of studies applied the extended Theory of Planned Behavior (i.e., the Theory of Planned Behavior expanded with ‘ethical obligation’ and ‘self-identity’) in the Fair Trade consumption context and confirmed that this extended version of the theory has significantly higher explanatory power in this context compared to the original model (e.g., Shaw & Shiu, 2002; De Ferran & Grunert, 2007).

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In addition, within the study by Beldad and Hegner, (2018), perceived behavioral control became an insignificant predictor of Fair Trade purchase intention for male customers.

Even though the majority of prior studies on the effect of the extended Theory of Planned Behavior on Fair Trade purchase intention reported that both ethical obligation and self-identity were found to be direct predictors of Fair Trade purchase intention (e.g. Shaw et al., 2000; Ozcaglar-Toulouse et al., 2006; Beldad & Hegner, 2018), it is worth mentioning that in a more recent study problems occurred with the inclusion of these constructs. For instance, Chatzidakis et al. (2016), reported that ethical obligation and self-identity were found to be highly correlated with one another, resulting in the inclusion of a combined construct labeled ‘internal ethics’. In addition, there have also been studies which deemed it sufficient to only include ‘ethical obligation’ and not ‘self-identity’ (e.g., De Leeuw et al., 2014).

One of the first and perhaps one of the most cited studies in this context, the study by Ozcaglar-Toulouse et al. (2006), analyzed Fair Trade purchase intention through differences between ‘regular’ consumers of Fair Trade products and people who never bought these products before. As expected, the authors in this study reported that the intention to buy Fair Trade products differed substantially between these groups. Interestingly, they also reported that the intention differed considerably within the groups. Even though Ozcaglar-Toulouse et al. (2006) noted that both groups differed considerably in terms of the role and impact of the components of the Theory of Planned Behavior on the Fair Trade purchase intention, the cause of this variation in intention within both of the groups remained rather unexplained.

Based on all these different observations and outcomes, it is still not completely clear how Fair Trade purchase intentions are being formed. This leaves room for the question if there are other factors that influence the relationship between the components of the Theory of Planned Behavior and Fair Trade purchase intention. Prior studies have confirmed the influence of the components of the Theory of Planned Behavior on Fair Trade purchase intention (e.g. Ozcaglar-Toulouse et al., 2006; O’Connor et al., 2017). Yet, there is also research that suggests the role of potential moderating effects on this relationship (Chatzidakis et al., 2007).

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addition, even though there are studies that have indicated that the higher price of Fair Trade products forms an obstacle to buy these products (e.g., Arnot et al., 2006), there are also several studies which have reported that the higher price of Fair Trade products does not form a constraint to buy these products at all (e.g., Tanner et al., 2003; De Pelsmacker & Janssens, 2007). Given these findings, it is interesting to see if differences in attitudinal meanings of money could explain the differences observed in Fair Trade purchase intention between customers.

2.2 Money Attitudes: Perceived Financial Security and Consumer Financial Distress.

Besides its economic value, people also associate several attitudinal meanings with money (Yamauchi & Templer, 1982). These attitudinal meanings associated with money reflect ‘money attitudes’, which have been measured on different types of scales (e.g., Rose & Orr, 2007). According to Duh (2016), money attitudes are either affective (i.e. positive or negative feelings sparked by individual financial prosperity) or conservative (i.e. subjective assessment of financial security and ability to budget for future needs).

In a more recent study by Hampson et al., (2018), the authors successfully managed to observe differences in consumer behavior by evaluating these consumers based on money attitudes. More specifically, the authors in this study use ‘perceived financial security’ as a reflection of conservative money attitudes and ‘consumer financial distress’ as a reflection of the affective money attitudes. Perceived financial security can be defined as the extent to which an individual judges his/her personal financial situation as being secure (Haines et al., 2009), meanwhile consumer financial distress occurs when individuals associate negative feelings to their personal financial situation (Henry & Crawford, 2005).

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influence the relationship between consumer attitudes and the intention to purchase Fair Trade products.

Stress is one of the most apparent negative feelings associated with financial well-being (Maier & Wiken, 2014). It has been suggested before that stress affects consumption patterns of consumers (Andreasen, 1984). For instance, consumers will value potential gains less while simultaneously valuing potential losses more, causing them to make different financial decisions (Weller & Helburn, 2010). In line with this, consumers experiencing higher levels of financial distress are generally less inclined to pay more (Hampson et al., 2018). Given the higher price associated with Fair Trade products, it might be the case that experiencing financial distress will negatively influence the relationship between an

individual’s consumer attitudes and their intention to purchase Fair Trade products.

Prior research has indicated that understanding money attitudes is necessary in order to be able to understand behavior (Tang, 2014). However, to the fullest knowledge of the author in this study, the influence of perceived financial security and consumer financial distress has not been included within prior literature on Fair Trade consumption. Building upon the work by Hampson et al., (2018), this study will analyze the possible moderating effect of perceived financial security and consumer financial distress on the relationship between each of the constructs of the extended Theory of Planned Behavior and Fair Trade purchase intention.

2.3 Theoretical Framework.

Based on the literature reviewed in section 2.1 and 2.2, the theoretical model in Figure 1 is being proposed.

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Moreover, as discussed in section 2.1, it has been established in prior research that the addition of ethical obligation to the original Theory of Planned Behavior improves its

explanatory power (Conner & Armitage, 1998), especially within the Fair Trade consumption context (e.g.; Shaw et al., 2000; Ozcaglar-Toulouse et al., 2006; Andorfer & Liebe, 2015). Based on these findings, it is expected that ethical obligation will positively influence Fair Trade purchase intention in this study as well.

Furthermore, self-identity, as discussed in section 2.1, has been identified to improve the predictive ability of the Theory of Planned Behavior as well and it has been found to positively influence people’s Fair Trade purchase intentions in prior research (e.g. Ozcaglar-Toulouse et al., 2006; Beldad & Hegner, 2018). As acknowledged in section 2.1, there has been a study that reported that self-identity and ethical obligation were too similar and

therefore used a combined construct labeled ‘internal ethics’ (i.e., Chatzidakis et al., 2016). In addition, there have also been studies which did not include self-identity at all when

predicting Fair Trade purchase intention (i.e., De Leeuw et al., 2014). Based on these outcomes the role of self-identity within the Fair Trade purchasing context could be questioned. However, given the higher amount of studies that did identify self-identity as being an independent, significant, predictor of Fair Trade purchase intention, it is expected that self-identity will positively influence Fair Trade purchase intention in this study as well.

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.

Figure 1; Proposed theoretical model.

Even though the extended Theory of Planned Behavior has been tested in the context of Fair Trade purchase intention in previous studies (e.g., Ozcaglar-Toulouse 2006; Shaw et al., 1999), the influence of differences in money attitudes in terms of ‘perceived financial

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H1: ‘Perceived financial security’ positively influences the relationship between ‘attitude’ and ‘Fair Trade purchase intention’.

H2: ‘Perceived financial security’ positively influences the relationship between ‘subjective norm’ and ‘Fair Trade purchase intention’.

H3: ‘Perceived financial security’ positively influences the relationship between ‘perceived behavioral control’ and ‘Fair Trade purchase intention’.

H4: ‘Perceived financial security’ positively influences the relationship between ‘ethical obligation’ and ‘Fair Trade purchase intention’.

H5: ‘Perceived financial security’ positively influences the relationship between ‘self-identity’ and ‘Fair Trade purchase intention’.

H6: ‘Consumer financial distress’ negatively influences the relationship between ‘attitude’ and ‘Fair Trade purchase intention’.

H7: ‘Consumer financial distress’ negatively influences the relationship between ‘subjective norm’ and ‘Fair Trade purchase intention’.

H8: ‘Consumer financial distress’ negatively influences the relationship between ‘perceived behavioral control’ and ‘Fair Trade purchase intention’.

H9: ‘Consumer financial distress’ negatively influences the relationship between ‘ethical obligation’ and ‘Fair Trade purchase intention’.

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3. Methodology

3.1 Design.

In order to test the hypotheses formulated in section 2.3, a broad dataset was generated using a survey questionnaire. This questionnaire consisted of 55 questions; the complete questionnaire can be found under Appendix A. The questionnaire was conducted and distributed online through Qualtrics. Respondents could simply click a link to enter the survey. Using an online survey in order to generate data has several advantages, of which the most notable are both the speed and the quantity of the data collection process (Fleming & Bowden, 2009), the data accuracy and the possibility of respondents to remain anonymous (Hooley et al., 2012). However, this form of data collection also has disadvantages. For instance, Auger and Devinney (2007) argue that when using online surveys as the method of data collection, respondents are likely to overestimate their actual preferences and intentions, meaning that social desirability bias is likely to occur. In order to control for the social desirability bias in this study, eight items aimed to measure this were added to the questionnaire, which are being discussed in detail in section 3.7.

Furthermore, there are ethical issues associated with the use of online surveys (Hooley et al., 2012). In order to prevent these issues from arising, participants were informed that all of the information collected during this study would be kept private, and participants had to be over the age of 18. In addition, ethical approval for this study was obtained at the

University of Newcastle. Before the survey started, the following statement was shown to the participants;

“The following survey is set up in order to get data to analyze the potential moderating role of money attitudes on the effect an individuals’ personal values on their intention to buy Fair Trade products. Your information will be kept strictly private, your answers will be anonymous and that this data will not be shared with parties other than the researcher. Please be aware that there are no right or wrong answers and that you can step out of this survey anytime you like. Your participation is highly appreciated in advance!”

This way, participants were informed that right or wrong answers did not exist, as they were merely expressing opinions (Podsakoff et al., 2003).

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Likert scales, which are discussed in detail in section 3.4 below. The last questions of the survey were used to check for social desirability bias and to analyze the demographic characteristics of the participants.

3.2 Data correction

In total 228 complete responses were recorded, of which initially seven were

eliminated due to submitting either incorrect or incomplete answers to some of the questions. After this, multivariate outliers were identified by calculating the Mahalanobis distance for each respondent. Next, the cumulative distribution function of Chi-square of the Mahalanobis distance and 43 levels of freedom (since initially 43 different statements were used to measure the eight different variables in the theoretical framework) were used to determine which of the respondents could actually be labeled as being an outlier. The data of respondents which ended up with a p-value <.001 were identified as an outlier and therefore removed from the dataset (n=12) (Tabachnick & Fidell, 2007). Lastly, twenty-nine responses were removed from the dataset because they had missing data on at least one of the constructed factor items. This meant that the final dataset consisted of data generated from 180 completed surveys. Based on G*Power (F2=.15, α=.05, confidence level of 95%, 7 predicting variables) and a total of 12 predictors (5 IVs, 2 Moderators, 5 CVs) a minimum sample size of 154

respondents would be needed, meaning that the dataset used in this study can be deemed sufficient (Faul et al., 2009).

3.3 Participants

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Table 3.1: Sample characteristics. Number: Percentage: Gender: Male 94 52.2% Female 86 47.8% Employment status: Unemployed 4 2.2% Student 102 57% Employed 72 16.5% Retired 1 0.6% Monthly Income: <€500,- 36 20.5% Between €500 - €1000 56 31.8% Between €1000 - €2000 41 23.3% Between €2000 - €3000 29 16.5% >€3000,- 14 8%

Financially dependent children:

No 143 79.9% Yes, 1 16 8.9% Yes, 2 12 6.7% Yes, 3 or more 8 4.5% Level of education: <High school 1 0.6%

High School degree 41 22.8%

College, no degree 3 1.7%

College degree 69 38.3%

Bachelor’s degree 36 20%

Master’s degree 30 16.7%

3.4 Initial Measures

The Theory of Planned Behavior measures developed by Ajzen and Fishbein (1980) were adjusted and used to measure each of the original components of this theory, along with several adaptations from other studies. For each of these components, recommendations of Ajzen (2002) have been followed. All of the items used in the questionnaire can be found under Appendix A.

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products would be;” followed by contrasting concepts such as “harmful/beneficial”, “good/bad” and “unfavorable/favorable”. The first five items were adapted from Ajzen (2002), meanwhile items six and seven were adapted from Chatzidakis et al., (2016). In addition, two items adapted from Beldad and Hegner (2018) were included and measured on a 7-point Likert scale; 8) “By purchasing Fair Trade products I can make a difference in the

lives of farmers, workers and growers in developing countries” and 9) “Purchasing a Fair Trade product enables me to help workers, farmers and/or growers in developing countries”.

Subjective norm, operationalized as the individual’s perception regarding whether important others think they should or should not purchase Fair Trade products, was measured using six items adapted from the studies of Ozcaglar-Toulouse et al., (2006) and Chatzidakis et al., (2016), and following the recommendations of Ajzen (2002). All of the items were measured on a 7-point Likert scale, e.g.,; “Most people who are important to me buy Fair

Trade products” and “Most people who influence my behavior expect me to buy Fair Trade products”.

Perceived behavioral control, operationalized as the extent to which the individual perceives to have complete control to purchase Fair Trade products, was measured using five items, all measured on a 7-point Likert scale. The first two items were adapted from Ajzen (2002) and the study by Chatzidakis et al., (2016), measuring the perceived ease of

respondents regarding the purchase of Fair Trade products; e.g., “It is relatively easy for me to

buy Fair Trade products in the near future”. The remaining three items were newly

formulated statements, based on control beliefs used by Shaw et al., (1999) and Ozcaglar-Toulouse et al., (2006).

Ethical obligation, operationalized as the extent to which an individual perceives to be ethically obliged to buy Fair Trade products, was measured using four items, all measured on a 7-point Likert scale. The statements were based on the recommendations by Ajzen (2002) and adapted from the studies of Chatzidakis et al., (2016) and Beldad and Hegner (2018), e.g.; “I personally feel that I should buy Fair Trade products” and “I see it as my duty to buy the

Fair Trade variant of a product whenever it is available”.

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different statements, all measured on 7-point Likert scales. These items were adapted from the studies of Shaw et al., (1999), Ozcaglar-Toulouse et al., (2006), Chatzidakis et al., (2016) and Beldad and Hegner (2018), e.g.; “Buying Fair Trade products is an important part of who I

am” and “I care about the situation of growers, workers and farmers in third-world countries”.

The dependent variable, intention, operationalized as the respondent’s intention to purchase Fair Trade products in the near future, was measured along six different statements adapted from prior literature (Ajzen, 2002; Ozcaglar-Toulouse et al., 2006; Chatzidakis et al., 2016). All of the statements were asked towards the likelihood of the respondent to purchase Fair Trade products in the near future, e.g.; “It is likely that I will buy at least one Fair Trade

products in the near future”.

Three items measuring perceived financial security were directly adapted from Hampson et al., (2018). These items all started with “Indicate how secure you are about the

following;” followed by three different items (See also, Logan et al., 2013); 1) “Paying monthly rent”, 2) “Paying for utilities (electricity, insurance, telephone subscription etc” and

3) “Paying an unexpected medical bill of €1000,-.” All of these statements were measured on a 9-point scale ranging from “extremely insecure” to “extremely secure”.

Another three items adapted directly from the study by Hampson et al., (2018), measure Consumer Financial Distress. All of these items started with “My current financial

situation makes me”, followed by three different items; 1) “upset”, 2) “feel stressed” and 3)

“struggle to relax”.

3.5 Measurement validity.

In order to assess the measurement validity of each of the variables, factor analysis (principal components analysis) was used and the Chronbach’s alpha and Kaiser-Meyer-Olkin (KMO) scores were analyzed (See table 3.2 for an overview of all the factor loadings,

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1.6 – See Appendix A for the detailed items) and seven separate components were constructed.

The first component, attitude, consisted of 5 items (KMO=.760, α= .799). The

remaining 4 items that were intended to measure attitude were dropped because these loaded onto separate components. The second component, subjective norm, consisted of 5 items (KMO= .811, α=.878); one item was dropped based on its low factor loading (.455). Three items designed to measure the third component, ‘perceived behavioral control’, loaded onto one component (KMO=.708, α=.705). However, the remaining two items (‘perceived

behavioral control 1.4 and 1.5, see Appendix A for the detailed items) were dropped based on their low α of .452.

Most notably, the measure of self-identity was problematic in this study. Two of these items loaded onto the same construct as ethical obligation, meanwhile the other four items did not load onto a separate construct. In addition, the items designed to capture this construct came from a variety of studies. Furthermore, given the fact that two of the designed items to capture this construct loaded onto another construct, including self-identity as a separate measure would increase the chance of multicollinearity in the dataset (Tabachnick & Fidell, 2007). Therefore, it was decided to drop this construct from the model.

Thus, the fourth constructed component consisted of six items (KMO=.838, α=.897). Even though all of the four items used to capture ethical obligation loaded onto this construct, the other two items were initially designed to capture self-identity. Given the one factor solution based on the principal components analysis this component was constructed as a combination of both ethical obligation and self-identity. Based on similar outcomes in a study by Chatzidakis et al., (2016), it was decided to adopt the approach taken in this study and label the fourth construct as ‘internal ethics’, in order to avoid confusion with prior research on ethical obligation.

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Lastly, the seventh measure consisted of all of the six items designed to capture ‘intention’ (KMO=.923, α=.978).

Table 3.2: Constructed components, factor loadings and reliability scores.

Construct Items Factor

Loadings

Chronbach’s

α KMO _score Attitude “Buying Fair Trade products for me would be: .799 .706

1. Harmful/Beneficial .628 2. Unpleasant/Pleasant .726 3. Bad/Good .815 4. Worthless/Valuable .757 5. Unenjoyable/Enjoyable .755 Subjective Norm

1. “Most people who are important to me buy Fair Trade products”.

.810 .878 .811

2. “Most people who are important to me think that I should buy Fair Trade products”.

.852

3. “Most people whose opinion I value buy Fair Trade products

themselves”.

.821

4. “It is expected of me to buy Fair Trade products in the near future”.

.791

5. “Most people who influence my behavior expect me to buy Fair Trade products”.

.799

Perceived Behavioral Control

1. “It is relatively easy for me to buy Fair Trade products in the near future”.

.791 .705 .708

2. “It is mostly up to me whether or not I buy Fair Trade products in the near future”.

.637

3. “Fair Trade products are available at the places where I shop”.

.780

Internal Ethics 1. “I personally feel that I should buy Fair Trade products”.

.797 .897 .838

2. “I feel that I have an obligation to buy Fair Trade products”.

.846

3. “Buying Fair Trade products would be the right thing for me to do”.

.770

4. “I see it as my duty to buy the Fair Trade variant of a product if this is available”.

.870

5. “Buying Fair Trade products is an important part of who I am”.

.810

6. “I am the type of person oriented to buy Fair Trade products”.

.781

Perceived Financial Security

“Indicate how secure you are about the following:**

.810 .742

1. Paying monthly rent. .936

2. Paying for utilities (electricity, insurance, telephone subscription etc.)

.927

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€1000,-

Consumer Financial Distress

“My current financial situation makes me: .915 .742

1. Upset .900

2. Feel stressed .933

3. Struggle to relax .900

Intention 1. “I intend to buy at least 1 Fair Trade product in the near future”.

.947 .978 .923

2. “It is likely that I will buy at least 1 Fair Trade product in the near future”.

.911

3. “I will try to buy at least 1 Fair Trade product in the near future”.

.964

4. “I plan to buy at least 1 Fair Trade product in the near future”.

.967

5. “I expect to buy at least 1 Fair Trade product in the near future”.

.949

6. “I want to buy at least 1 Fair Trade product in the near future”.

.957

**= Measured on a 9-point scale adapted from Hampson et al., (2018).

3.6 Control variables

In order to account for the influence of differences in sociodemographic characteristics of respondents on Fair Trade purchase intention, two control variables were entered in the regression models. The first control variable used in this study is gender. Gender has been included in prior studies in the Fair Trade purchasing context which reported that there is no significant difference between men and women (e.g. De Pelsmacker et al., 2005; Doran, 2008). However, there are more recent studies that have been reporting that Fair Trade purchase intention is significantly higher amongst women compared to men (e.g. Sunderer & Rössell, 2012). Nonetheless, a study by Beldad and Hegner, (2018) reported that Fair Trade purchase intention was higher for men compared to women. In addition, it has been suggested that the influence of gender regarding Fair Trade purchase intention even differs for separate constructs of the extended Theory of Planned Behavior (De Leeuw et al., 2014). Given these outcomes it was decided to control for the effect of gender on Fair Trade purchase intention in the regression models. Furthermore, one critique that research on Fair Trade purchase

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3.7 Social Desirability Bias

Self-report surveys are a widely used method when studying Fair Trade purchase intention. However, one major problem that is identified regarding these studies is the

possible presence of a social desirability bias (Andorfer & Liebe, 2012). This bias entails that participants have a tendency to deny behaviors that they deem as ‘socially undesirable’ and to report behaviors that they deem to be ‘socially desirable’ (Zerbe & Paulhus, 1987). Social desirable responding consists of two separate factors; self-deceptive enhancement and

impression management (Paulhus, 1984). Self-deceptive enhancement reflects the tendency to give honest but positively biased answers (Paulhus, 1984), whereas impression management can be defined as the tendency to consciously report exaggerated self-descriptions in order to create a socially desirable image in front of an audience (Hart et al., 2015). Impression management was prevented to occur in this study by notifying the participants that their answers would be anonymous. However, conversely, self-deceptive enhancement was likely to occur. In order to control for self-deceptive enhancement in this study, eight items

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4. Results

4.1 Descriptive statistics

Table 4.1 summarizes the means and standard deviations of each of the constructs used in the regression analysis, as well as the correlations between the constructs.

Respondents showed relatively high attitude towards buying Fair Trade products (M=4.92) whilst their subjective norm was relatively low (M=3.081). Furthermore, respondents showed relatively high perceived behavioral control (M=5.383), while the observed measure of internal ethics was moderate (M=3.708). In addition, relatively high perceived financial security (M=6.319) and relatively low consumer financial distress (M=2.878) were observed. The overall Fair Trade purchase intention of the respondents was relatively moderate

(M=4.724).

Table 4.1: Descriptive statistics and correlation amongst factors.

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4.2 Assumptions

In order to examine the potential moderating role of both perceived financial security and consumer financial distress on the effect of attitude, subjective norm, perceived

behavioral control and internal ethics on the Fair Trade purchase intention of consumers, multiple linear regression analysis was conducted. Before doing this, all of the assumptions for multiple linear regression analysis were tested (See Appendix B). First, in order to observe if there is a linear relationship between all of the IVs and the DV, several scatterplots were created as well as a scatterplot in which the standardized residuals were plotted against the standardized predictors (Berry & Fieldman, 1985). Based on these plots it was assumed that there is indeed a linear relationship between the independent variables and the dependent variable, the distribution of the dependent variable Fair Trade purchase intention was

sufficient and that heteroscedasticity was not an issue. In order to check for multicollinearity amongst the predictor variables, VIFs were calculated and analyzed. Since all of the observed VIF values were lower than 5, it was assumed that multicollinearity is not an issue (Menard, 1995). The normal distribution of the dependent variable ‘Fair Trade purchase intention’ was checked by creating a p-plot. Given that the majority of residuals clustered around the line in this plot, it was assumed that the assumption for normal distribution of the DV was met. Finally, in order to check for no autocorrelation amongst residuals, the standardized residuals and Cook’s distance were used, which value indicated this assumption was met (<1).

4.3 Test of the regression models.

Multiple linear regression analysis was conducted to predict consumers’ intention to purchase Fair Trade products based on their attitude, subjective norm, perceived behavioral control, internal ethics with potential moderating effects of perceived financial security and consumer financial distress. Three different sets of models were analyzed.

First, the potential moderating role of perceived financial security on the relationship between the Theory of Planned Behavior constructs (attitude, subjective norm, perceived behavioral control and internal ethics) and Fair Trade Purchase intention was analyzed. Subsequently, the potential moderating effect of consumer financial distress on the

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In the first model (model 1), only the control variables (i.e. ‘gender’ and ‘student’) and the dependent variable, Fair Trade purchase intention, were included. After this the constructs of the extended Theory of Planned Behavior (i.e. attitude, subjective norm, perceived

behavioral control and internal ethics) were added as independent variables (model 2). In order to examine the potential moderating effect of perceived financial security on Fair Trade purchase intention, perceived financial security was first added as a direct

predictor (model 3). Next, the interaction effects of each of the Theory of Planned Behavior constructs and perceived financial security were added in the subsequent model (model 4).

Consumer financial distress was analyzed in a similar way, meaning that first a model consisting of the control variables (i.e. ‘gender’ and ‘student’), the constructs of the extended Theory of Planned Behavior (i.e. attitude, subjective norm, perceived behavioral control and internal ethics) and consumer financial distress were included as predicting variables (model 5). Subsequently, the interaction effects between consumer financial distress and each of the constructs of the Theory of Planned Behavior were included in the model (model 6).

In addition, the effects of both perceived financial security and consumer financial distress were analyzed when included simultaneously in a model further consisting of the control variables and the constructs of the extended Theory of Planned Behavior (model 7). Finally, all interaction effects (i.e. the interaction effects of both perceived financial security and consumer financial distress and each of the constructs of the extended Theory of Planned Behavior) were added (model 8).

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financial security Internal ethics x perceived financial security .147* .098 Attitude x consumer financial distress .052 .065 Subjective norm x consumer financial distress .163* .096 Perceived behavioral control x consumer financial distress -.152* -.161* Internal ethics x consumer financial distress -.162* -.123 R2 .112 .484 .506 .521 .490 .524 .507 .544 Adjusted R2 .102 .466 .486 .489 .470 .493 .484 .499 F 11.111 27.032 25.202 16.589 23.650 16.829 21.987 12.159 Sig. .000 .000 .000 .000 .000 .000 .000 .000 Change in R2 .112 .372 .022 .014 .007 .034 .023 .037 Sig. .000 .000 .006 .290 .138 .021 .020 .113 * = p<.05 ** = p<.01 *** = p<.001

The first model (model 1), consisting of just the control variables (gender, student) as predictors of Fair Trade purchase intention, had an R2 of .112 (F (2, 177) = 11.111, p<.001. In this model, being female had a significant positive effect on Fair Trade purchase intention (β= 1.047, p<.001). Next, in model 2, the extended Theory of Planned Behavior constructs

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Fair Trade purchase intention within this model were internal ethics (β=.572, p<.001), perceived behavioral control (β=.275, p<.01) and being female (β=.618, p<.01).

Next, when perceived financial security was added as an additional predictor (model 3), R2 significantly increased to .506 (F (7, 172) = 25.202, p<.001). In this model internal ethics (β= .576, p<.001), perceived behavioral control (β=.238, p<.05) and being female (β= .568, p<.01) remained significant predictors of Fair Trade purchase intention, meanwhile also perceived financial security was found to significantly influence Fair Trade purchase intention (β=.154, p<.01). In model 4 it is proposed that perceived financial security moderates the relationship between each of the four constructs of the extended Theory of Planned Behavior and Fair Trade purchase intention. Therefore, the mean centered interaction effects between perceived financial security and each of the four constructs of the extended Theory of Planned Behavior were added as predictors. This model showed the value of R2 increase to .521 (F (11, 168) = 16.589, p<.001). However, this R2 increase was not significant (p= .290). In model 4, internal ethics (β=.578, p<.001), perceived behavioral control (β=.265, p<.01), being female (β=.605, p<.01) and perceived financial security (β=.133, p<.05) were significant direct predictors of Fair Trade purchase intention, meanwhile only the interaction effect between internal ethics and perceived financial security was significant (β=.147, p<.05). Given the fact that internal ethics is a combined construct of ethical obligation¸ these findings provide support for H4 and H5.

After the influence of perceived financial security was analyzed individually, the same was done for consumer financial distress. Therefore, it is useful to note that model 5 was basically an extension to model 2, rather than an extension to model 4. For model 5,

consisting of the control variables, the extended Theory of Planned Behavior constructs and consumer financial distress, R2 = .490 (F (7, 172) = 23.650, p<.001). Even though this is an increase in R2 compared to model 2, this increase was not significant (p= .138). Within model 5, internal ethics (β=.579, p<.001), perceived behavioral control (β= .260, p<.01) and being female (β=.628, p<.01) were the only significant predictors of Fair Trade purchase intention. Next, the potential moderating role of consumer financial distress on the relationship between each of the extended Theory of Planned Behavior constructs and Fair Trade purchase

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(β=.297, p<.01), subjective norm (β=.198, p<.05) and being female (β=.595, p<.01) were significant direct predictors of Fair Trade purchase intention. In addition, the interaction effect between consumer financial distress and subjective norm (β=.163, p<.05), the interaction effect between consumer financial distress and perceived behavior control (β=-.152, p<.05) and the interaction effect between consumer financial distress and internal ethics (β=-.167, p<.05) were found to be significant in this model. These findings provide support for H8. Meanwhile, given the fact that internal ethics is a combined construct of ‘ethical obligation’ and ‘self-identity’, this also provides support for H9 and H10. Even though a significant interaction effect was found for consumer financial distress and subjective norm, this interaction term was still positive meanwhile the other significant interaction terms were negative. Therefore, H7 was not supported.

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5. Discussion

5.1 The extended Theory of Planned Behavior within the Fair Trade purchasing context.

Regarding the influence of the components of the extended Theory of Planned Behavior on Fair Trade purchase intention, some interesting findings were revealed in this study. First of all, as discussed in section 2.1, there have been studies which reported different outcomes regarding the importance of each of the different constructs of the extended Theory of Planned Behavior in the Fair Trade consumption context. For instance, De Leeuw et al., (2014), included only ethical obligation in the form of ‘moral norms’ as an additional construct to the original Theory of Planned Behavior. Within this study by De Leeuw et al., (2014), attitude, subjective norm, perceived behavioral control and moral norms remained significant predictors of Fair Trade purchase intention. Even though a similar extended version of the Theory of Planned Behavior was applied in this study, the outcomes are very different.

For instance, attitude was not found to be a significant predictor of Fair Trade purchase intention in any of the eight models within this study. However, this is not the first study to report this outcome. Prior studies have reported that ‘attitude’ was no longer a

significant predictor of Fair Trade purchase intention when ethical obligation and self-identity were added to the Theory of Planned Behavior as additional predictors (Shaw et al., 2000; Shaw & Shiu, 2002). The findings of the current study provide support for the claim that within the Fair Trade purchasing context, ethical considerations and motives are more

important to predict Fair Trade purchase intentions than a more general attitude towards these products (Beldad & Hegner, 2018).

Furthermore, subjective norm was only found to be a significant predictor of Fair Trade purchase intention in model 6. This is in line with findings from prior studies which reported that subjective norm is a weak predictor of Fair Trade purchase intention (e.g. Shaw et al., 2000; O’Connor et al., 2017) and even in general (Armitage & Conner, 2001). One possible reason for this might be that consumers who intend to buy Fair Trade products are often segregated in this concern (Shaw & Clarke, 1999). This could be an indication that Fair Trade purchasing is still perceived to be more of a niche, even though Fair Trade purchasing is increasing, as mentioned in section 1.

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making it the second most important predictor in terms of the extended Theory of Planned Behavior. This is in line with the outcomes of prior studies (e.g., O’Connor et al., 2017), suggesting that besides internal ethical reasons, high perceived behavioral control also leads to a higher intention of customers to purchase Fair Trade products. Additionally, whereas the measurement of this construct has been difficult in a variety of prior studies (Conner & Armitage, 1998), these difficulties were not present in the current study. One reason for this might be the inclusion of an additional statement compared to previous research. In prior studies perceived behavioral control was merely measured based on statements focused on personal control regarding the purchase of Fair Trade products. In the current study an additional measure of availability was added based on the outcomes of the principal components analysis. This could be seen as an indication that the availability of Fair Trade products is an important constraint for customers to purchase these products, and including this in the measurement of perceived behavioral control improves the ability to capture this.

Above all, one of the most interesting findings in this study is the combination of both ‘ethical obligation’ and ‘self-identity’ into one combined construct of ‘internal ethics’,

adopted from the approach by Chatzidakis et al., (2016). As discussed in section 2.1, the majority of prior studies used both ethical obligation and self-identity as separate additional predictors of the Theory of Planned Behavior (e.g., Shaw et al., 2000; Ozcaglar-Toulouse et al., 2006). However, in the current study these measures did not load onto a unique

component. The results in the current study provide support for these outcomes in the study by Chatzidakis et al., (2016), suggesting that within the Fair Trade purchasing context, ‘ethical obligation’ and ‘self-identity’ are associated with measuring similar values. One possible explanation for this is that customers who identify themselves as being concerned with the situation of growers, workers and farmers in developing countries most likely feel an ethical obligation to purchase Fair Trade already (Sparks & Shepherd, 2002). However, it is worth mentioning that the lack of distinction between ethical obligation and self-identity in this study could also be caused by the items used to measure these constructs, which were adapted from a variety of different studies (e.g., Shaw et al., 2000, Chatzidakis et al., 2016). In addition, internal ethics was the most significant predictor of Fair Trade purchase intention. This further supports the claim that Fair Trade consumers make their decisions based on ethical considerations rather than motives of self-interest (Shaw et al., 2000).

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(2018), which reported that male consumers have a higher intention to buy Fair Trade products. However, the outcomes of the current study are in line with prior studies that reported that women are more likely to purchase Fair Trade products (e.g., Morell &

Jayarwadhena, 2010). One possible reason for this could be that women are more associated than men with having an ‘ethic of care’ (Bampton & Maclagan, 2009), which results in women sympathizing more with the situation of workers, growers and farmers in third world countries compared to men. However, this could also be due to the sample used.

5.2 The role of perceived financial security within the Fair Trade consumption context.

As outlined in section 2.2, the role of money attitudes, and more specifically perceived financial security and consumer financial distress, within the context of Fair Trade purchase intention gained little academic interest. Therefore the outcomes of this study provide some interesting insights. Firstly, based on the literature reviewed in section 2 it was expected that perceived financial security would moderate the relationship between each of the constructs of the extended Theory of Planned Behavior and Fair Trade purchase intention. Only one significant interaction effect was found, however; the interaction effect between perceived financial security and internal ethics, in model 4. This does provide support for H4 and H5, however through the combined construct of internal ethics. This might indicate that

consumers with strong ethical motives and considerations to purchase Fair Trade products are more likely to purchase Fair Trade products when they perceive to be financially secure at the same time. However, in the final model, none of the interaction effects involving perceived financial security were found to be significant. This could be due to the high amount of interaction effects in the final model.

Moreover, perceived financial security was found to be a significant direct predictor of Fair Trade purchase intention in all of the four different models it was included in. Adding perceived financial security to the constructs of the extended Theory of Planned behavior, without any interaction effects (model 3), resulted in a significant change in R2 of .022 (p<.01). This provides an interesting insight regarding the role of perceived financial security within the Fair Trade purchasing context. As Ajzen (1991) stated; “The Theory of Planned Behavior is open to the inclusion of additional predictors if it can be shown that they capture a significant proportion of the variance in intention or behavior after the theory’s current

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this context. This indicates that customers with a more positive perception of their financial security are more likely to purchase Fair Trade products. A possible explanation for this could be that a more positive perception of their own financial security makes customers more inclined to pay the price premium that customers associate with Fair Trade products. Thus, adding perceived financial security as an additional predictor to the Theory of Planned might be a way to decrease the broader observed gap between consumer attitudes and their intention, mentioned in section 1.

5.3 The role of consumer financial distress within the Fair Trade purchasing context.

As mentioned in section 4.3, three significant moderating effects were found in model 6. In model 6 R2 significantly increased to .520 (p<.05). The first observed significant effect was for the influence of consumer financial distress on the relationship between subjective norm and Fair Trade purchase intention. However, since this interaction term remained positive while the other significant interaction terms were negative, the influence of consumer financial distress on this relationship is different. One possible explanation for this could be that when a consumer is experiencing feelings of financial distress, this leads them to comply to the norm of meaningful others (Louis et al., 2009).

Secondly, as mentioned in section 4.3, consumer financial distress was found to moderate the relationship between perceived behavioral control and Fair Trade purchase intention. Prior research has suggested that the influence of perceived behavioral control on Fair Trade

purchase intention was influenced by the higher price of Fair Trade products (Uusitalo & Oksanen, 2004). However, based on the outcomes of the current study it could be that this is due to different levels of consumer financial distress between respondents, rather than the absolute value of price. Given that stress has been found to reduce the ability of people to overcome difficulties (Mann & Ward, 2004), it could be possible that when people are financially distressed, they are less likely to overcome difficulties regarding the purchase of Fair Trade products which seemed liable at first.

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6. Conclusion

6.1 Conclusion and contributions

Overall, this study examined the influence of both perceived financial security and consumer financial distress on the relationship between the constructs of the Theory of Planned Behavior (extended with ‘internal ethics’) and Fair Trade purchase intention. As presented and discussed in section 4 and 5, perceived behavioral control and internal ethics were found to be the most important significant direct predictors of Fair Trade purchase intention, meanwhile women were found to have a significant higher purchase intention of Fair Trade products. In addition, several contributions to the existing literature have been made.

First, this study explored the role of both perceived financial security and consumer financial distress within the Fair Trade purchasing context and to the best of the researcher’s knowledge, this has not been done before. As discussed in section 5.2, perceived financial security was found to be a significant direct predictor of Fair Trade purchase intention in all of the models it was included in. Therefore, the outcomes of the current study indicate that perceived financial security could be a useful additional direct predictor to the extended Theory of Planned Behavior when predicting Fair Trade purchase intention.

Furthermore, as discussed in section 5.3, negative moderating effects were observed for consumer financial distress on the relationship between perceived behavioral control and Fair Trade purchase intention and on the relationship between internal ethics and Fair Trade purchase intentions. However, it must be noted that only the negative moderating effect on the relationship between perceived behavioral control on Fair Trade purchase intention remained significant in the final model (model 8). This could be due to a lack of power as a result of to the high amount of interaction effects added in the final model, or even due to the sample used in this study. Further research will be needed to further explore the role of consumer financial distress as a potential moderator in the Fair Trade purchasing context (see section 6.3).

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Trade purchase intention and perhaps on the relationship between internal ethics and Fair Trade purchase intention. Both adding perceived financial security as a direct predictor and consumer financial distress as a moderator on the suggested relationships could potentially be a way to decrease the observed gap between attitudes and intention (Vermeir & Verbeke, 2006; Carrington et al., 2010; Yeow et al., 2013), as mentioned in section 1.

6.2 Limitations

Even though this study was built on prior research and noted some interesting

extensions to prior established theory, there were several limitations within this study. First of all, the final model consisted of a lot of interaction effects (n=8). Because of this high amount of interaction effects compared to the sample size of 180, it could be the case that the

significance of some interaction effects did not hold in the final model due to the lack of power. In addition to this, the majority of the respondents within this study were Dutch. Even though this study was not intended to be cross-cultural, this still might mean that these results would only hold for Dutch consumers, meaning that the generalizability of these results is still relatively low. Lastly, using a questionnaire in order to measure purchase intention still

remains a self-reporting method of behavior. Even though social desirability bias was aimed to be prevented by using the self-deceptive enhancement questions of the short BIDR-16 as developed by Hart et al., (2015), this does not guarantee that all the provided answers, including answer to the demographic questions, are completely honest (Wright, 2010).

6.3 Implications

One important implication based on the results discussed in section 5 is that ethical motives and considerations are of more importance when predicting Fair Trade purchase intention compared to general attitudes or subjective norm. This indicates that for people buying Fair Trade products, ethical considerations and motives are the strongest reasons to purchase these products. Therefore, when marketing Fair Trade products it might be better for one to rely on addressing ethical aspects of Fair Trade.

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reasons why the gap between consumer attitudes and intentions, as mentioned in section 1, is observed.

Lastly, the outcomes of this study suggest a positive direct significant effect for female respondents on Fair Trade purchase intention. Whereas there are prior studies that report that women are more likely to buy Fair Trade products (e.g., Arnot et al., 2006), the opposite has been suggested as well (e.g., Beldad & Hegner, 2018). Moreover, in prior studies that are specifically aimed at examining the role of gender in the Fair Trade purchasing context, gender was found to have a moderating role (e.g., De Leeuw et al., 2014). The outcomes of the current study, however, strongly suggest a significant direct effect on Fair Trade purchase intention for women. An implication of this is that when marketing Fair Trade products, it potentially could be beneficial to specifically target the marketing strategies to women rather than men.

6.4 Directions for future research

One first important direction for future research would be to replicate the current study in a different setting and/or with a different sample. The outcomes of this study did provide some different insights compared to prior studies, which could also be due to the used sample. Therefore, in order to make the results more generalizable, future research is needed to

confirm the observed effects of both perceived financial security and consumer financial distress. In addition, given the findings of the current study, it would be interesting to see if perceived financial security and consumer financial distress play a similar role in a different ‘ethical’ context, such as buying organic foods or non-sweatshop produced clothing for example.

A second direction for future research would be to see if the effects of both perceived financial security and consumer financial distress in this context differ for male and female consumers. In this study there was merely controlled for gender. However, a higher

significant Fair Trade purchase intention for women was found. Therefore, it could also be that the way these intentions are influenced differently as well.

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The role of money attitudes in Fair Trade purchase intention forming.