Slow fashion industry : an empirical study on the effect of perceived product values on purchase intention

Slow fashion industry: An empirical study on

the effect of perceived product values on

purchase intention

Master thesis

Submitted to

Nazlihan Ugur

Submitted by

Henrik Roth

Study: Master in Entrepreneurship

Student Id: 11753323, 2628263

Date of Submission

Statement of Originality

This document is written by Student Henrik Roth, who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Abstract

Slow fashion, a counter movement to fast fashion, which stands for products made with high quality to last longer and which respects the environment and society, attracts more and more attention of both businesses and consumers. Nevertheless, founders of slow fashion brands still struggle to become profitable, as they suffer from higher production prices. Inspired by the author's personal founding experience in the slow fashion industry, this study explores which perceived product values do have the most significant effect on the purchase intention of slow fashion products to help entrepreneurs in the slow fashion industry in order to drive sales and profits simultanously. This empirical study discovered through a multivariate regression that perceived price and emotional value do have the most significant effect on purchase intention of slow fashion products. In conclusion, this thesis shows that founders of slow fashion brands need to draw more attention to the multidimensional construct of value creation during the purchase decision process of their potential customers, to be able to increase sales and profits.

1 Table of contents

6.1 SLOW FASHION PRODUCTS ... 9

6.2 PERCEIVED PRODUCT VALUE ... 11

6.3 PURCHASE INTENTION AND ITS RELATIONSHIP TO PERCEIVED PRODUCT VALUE... 13

6.4 HYPOTHESIS AND THEORETICAL FRAMEWORK ... 14

6.4.1 Emotional value ... 14

6.4.2 Social value ... 15

6.4.3 Price value ... 15

6.4.4 Quality value ... 15

6.4.5 Environmental value ... 15

6.4.6 The importance of environmental value and price value during a purchase decision process ... 16

6.4.7 Research models ... 17

7 EMPIRICAL RESEARCH & METHODOLOGY ... 18

7.1 SURVEY INSTRUMENT DEVELOPMENT ... 18

7.2 SAMPLE DESCRIPTION ... 19

7.3 STATISTICAL ANALYSIS DESCRIPTION AND ROBUSTNESS CHECK ... 19

8 EMPIRICAL RESULTS ... 21

8.1 DESCRIPTIVE ANALYSIS ... 21

8.2 FINDINGS OF TESTING HYPOTHESIS 1A,1B,1C,1D,1E AND 1F ... 22

8.3 FINDINGS OF TESTING HYPOTHESIS 2A AND 2B ... 24

9 DISCUSSION ... 25

9.1 UNI-DIMENSIONAL VERSUS MULTI-DIMENSIONAL VALUE CONSTRUCT ... 25

9.2 SUSTAINABLE BUSINESS MODEL: SLOW FASHION QUALITY VS. PRICE ... 26

9.3 EMOTIONAL VALUE VS. ENVIRONMENTAL VALUE ... 26

9.4 SLOW FASHION:PERCEPTION AND KNOWLEDGE OF SOCIETY... 26

10 CONCLUSION AND MANAGERIAL IMPLICATIONS ... 27

11 LIMITATIONS AND FURTHER RESEARCH AVENUES ... 28

12 BIBLIOGRAPHY ... 30

2 Acknowledgments

At this point, I would like to thank all those who have supported me professionally and personally during my master's thesis. My special thanks go to my supervisor Nazlihan Ugur, who has looked after and accompanied me in my work and has given me many helpful suggestions and advice. I also thank my partner, parents and dear friends who have accompanied me during this challenging time. Thank you for the corrections, suggestions for improvement, professional help, and professional support. Of course, I would also like to thank all participants who have completed my online survey.

3 List of Tables

Table 1: Reliability and descriptive statistics of the scales. ... 20 Table 2: Correlation of each factor ... 22 Table 3: Results of the multivariate regression including the control variables. ... 23 Table 4: Results of the linear regression between perceived product value and purchase intention ... 24

4 List of Figures

5 Introduction

Both consumers and retail businesses deal more and more with the concept of slow fashion, a production method which emphasizes quality and long-lasting products as a way of achieving sustainability in the fashion industry (Clark, 2008). Slower production and higher quality often result in higher product prices and retail prices, hence creating higher product value automatically for customers, so that they are motivated to keep the item longer rather than discarding it shortly after purchase (Levy, 1999). Likewise, slow fashion urges people to buy less at a high quality, which underlies a shift in consumer mindset from quantity to quality and which reduces resources waste (Koskela & Vinnari, 2009).Main business media, such as Forbes already published many articles about the slow fashion movement and claim that "the fashion industry may be slowing down, but it is definitely heading in the right direction" (Adamczyk, kein Datum).

Increasing demand for slow fashion products results in the creation of new businesses in this industry (Pears, 2006). Nevertheless, entrepreneurs face a very high chance of failure, resulting in the bankruptcy of their business (Hall & Woodward, 2010). Especially within the retail industry, the failure rate is the third highest out of 11 industries in total (Statistic Brain, 2017). Therefore, it is essential that slow fashion brands become profitable and succeed in not only the social and environmental, but also the economic aspects (Elkington, 1998). For that reason, it is crucial for entrepreneurs to get a better understanding of the industry and factors, which influence the purchase behavior of their products in order to drive sales and profits (Steiner & Solem, 1998). Based on the research findings of Levy (1999), who showed that perceived product values influence purchase intention, then entrepreneurs in the slow fashion industry need to understand which perceived product values increase customers’ purchase intention to gain a competitive advantage (Woodruff, 1997). Additionally, Chi and Kilduff (2011) point out that consumer-desired values are the reason for business success and survival.

De Pelsmacker et al. (2005) show that perceived product values of ethical and environmental concerned consumers differ significantly from the perceived values of a consumer with unethically buying behavior. As perceived product values are the starting point for the formation of attitudes towards purchase intentions, it is imperative to understand them correctly. It is primarily of

importance to be able to implement marketing strategies particularly when targeting a niche target group, such as the slow fashion consumers (Huber, Herrmann, & Morgan, 2001).

Previous research already studied the fast fashion industry and the behavior of its customers, but not much has been found out about the slow fashion industry, especially not much about its economic aspects (Sojin & Byoungho, 2016). Nevertheless, Barnes and Greenwood (2006) indeed found some unique characteristics of slow fashion products (Barnes & Lea-Greenwood, 2006), which shows the importance of understanding them correctly to be able to succeed in the slow fashion industry economic wise. For example, today’s society has increased interest in the environment and its development, as environmental issues draw their attention. This attention results in raising awareness of ecological values of products. Understanding and internalizing ecological features of particular products increases the perceived value of sustainable products (Grewal, Krishnan, Baker, & Borin, 1998; Zeithaml, 1988). Not only consumer's attention shifts to eco-friendly product characteristics but also national and international brands (e.g., Nike and Levi's) realize that environmental friendly clothing can illustrate a competitive advantage. Green, upcycled, sustainable and natural are all buzzwords in developed countries, such as Germany and UK. Nevertheless, existing knowledge about how consumers react to slow fashion products is insufficient (Diette, Finnerty, Herther, & Stanley, 2012).

The insufficient knowledge about building successful companies in the slow fashion industry is the reason why this thesis aims to identify which factors of the perceived product value have the most significant impact on the purchase intention of slow fashion consumers. This thesis analyzes (1) which factors create higher perceived product value and (2) what is the effect of these factors on purchase intention with the aim to deepen our understanding of purchase intention within the slow fashion industry.

This thesis uses the multiple item scales, developed by Sweeney and Soutar (2001) to measure perceived product value, which includes emotional, social, price, and quality value. The environmental value was added, because current research about environmental values is in a nascent status (Griskevicius, Tybur, & Van den Bergh, 2010), but still a very discussed topic in nowadays society (Meijers & Stapel, 2011). The empirical findings of this thesis will give slow fashion business owners a more in-depth overview of how to increase the purchase intention, which

can result into increasing sales, so they are able to achieve sustainability, also from an economic perspective. In the following part of the thesis, the literature review will be outlined as a basis of the conceptual framework, which is then followed by the empirical research, findings, and conclusions.

6 Literature overview

Firstly, the current state of theory about slow fashion products will be summarized, followed by the concept around perceived product value and its influence on purchase intention.

6.1 Slow fashion products

Rapid production with high volumes, increasing numbers of different seasons, low material costs, cheap labor and prices are characteristics of the fast fashion business, implemented by many retailers, such as Zara and H&M (Bhardwaj & Fairhurst, 2010; Fletcher, 2010). Low costs of fast fashion products, however, stimulate consumer’s consumption behavior (Cline, 2012), under which the product quality suffers (Ghemawat & Nueno, 2003). In contrast to that, Fletcher (2007) first introduced the concept “slow fashion" from the slow food movement initiated by Carlo Petrini in the year 1989. Fletcher (2007) projects the sustainability perspective of the slow food movement to the fashion industry and provides environmentally and socially friendly alternatives to the practices of the fast fashion industry. Based of Flechters perspective, the concept of slow fashion has become a topic of increased intereset. In the fields of research, howerver, little is known about the concept of slow fashion. Therefore, previous researchers still cannot identify a consistent definition of the term "slow fashion", which would differentiate it from broader concepts such as social responsibility or sustainability. Nevertheless, Clark (2008) established three pillars of slow fashion: emphasizing a local approach, transparent production methods, producing products with a positive environmental or social impact, which lead to a slower consumption.

The first pillar describes the connection of local production, materials and labor. Slow fashion encourages diverse business models of smaller and independent designers working on topics such as recycling, vintage and second-hand fashion (Cataldi, Dickson, & Grover, 2010). A transparent and slow production represents the second pillar of slow fashion. Slow production means that retailers produce with fewer intermediates between the final customer and the manufacturer, resulting in a more transparent supply-chain (Clark, 2008). The slow production also means that

traditional and less automated production methods are used, such as handwork, knitting and other craftsmanship practices. More transparency often improves cooperation between designers, manufacturer, and customers enhancing the relationship between each of the parties involved (Cataldi, Dickson, & Grover, 2010). Cataldi et al. (2010) for example state the possibility for customers to be part of the design process of slow fashion brands, which plays along with their needs for creativity and self-identity. Additionally, Cataldi et al. (2010) argue that slower production cycles help the environment to regenerate, due to a smaller resources usage. Slow fashion products also sustain a healthier co-existing between environment and human beings, as natural resources can grow back, and waste is reduced (Fletcher, 2010; Cline, 2012). Slower production does not only tackle environmental, but also societal issues, as it improves labor conditions of many workers, resulting in regular working hours and appreciating human rights (Cataldi, Dickson, & Grover, 2010). The third pillar reflects the quality and sustainable characteristics of slow fashion products. Focusing on less volume with higher quality generates a significantly better product experience with a longer lifetime and higher perceived product value (Clark, 2008). Product design also plays an important role in slow fashion. Meaning that slow fashion products are not only long-lasting, because of their quality, but also in terms of style and trends (Cataldi, Dickson, & Grover, 2010; Johansson, 2010). LeBlanc (2012) adds that slow fashion designs often fit multiple outfits. This characteristic implies slower consumption, in which customers keep the clothing for a longer time period and fulfill their individual identity rather than following mainstream trends in the fast fashion industry (Johansson, 2010). Nevertheless, such arguments also need to be seen critical, as sustainable productions become less sustainable if the resulting products are only worn for a few times (LeBlanc, 2012).

Additionally, slow fashion products are not comparable to luxury products, as luxury products are often produced with non-eco-friendly materials, such as furs (Steinberg, 1998). Appart from that, their production standards are disputable, similar to the fast fashion industry (Steinberg, 1998; Williams, 2000). However, there are also luxury products, which stand for premium quality, honest craftsmanship, and uniqueness (Nueno & Quelch, 1998). Another difference is that they are mostly bought because of primarily symbolic motivation to gain a specific individual, and social status (Wilcox, Kim, & Sen, 2009).

To sum it up, in contrast to fast and luxury fashion, slow fashion achieves environmental and ethical sustainability. Unfortuantly, the economic sustainability of the slow fashion industry is still questionable (Jung & Jin , 2014). The reason for that is that productions of small quantities with low-speed production methods often cannot compete against fast fashion companies with mass-production methods. As Fletcher (2007) claimed that "Slow is not the opposite of fast—there is no dualism—but a different approach in which designers, buyers, retailers, and consumers are more aware of the impacts of products on workers, communities, and ecosystems", it is possible that slow fashion businesses need to think about different strategies on how to make profit.

One way how to increase economic efficiency for slow fashion business is to improve their communication strategy, through focusing on the perceived product values, which have the highest impact on purchase intention. Like that, a slow fashion business can save up marketing costs and meanwhile generate more sales. Also, as already mentioned before, slow fashion products have very different characteristics compared to fast and luxury fashion products. Therefore, a more in-depth understanding of perceived product values of slow fashion products is needed.

6.2 Perceived product value

Burden (1998) explains that "successful retailers increasingly target their offers towards two consumer categories: those with an emphasis on value and those for whom time pressure is the key". Previous literature already covered theories about perceived values. Nevertheless, there is no precise definition. Perceived product value has been explained through different perspectives of benefit, quality, social psychology and money. The overall evaluation of the product utility reflects the benefit perspective. The quality perspective reflects the difference between paid product price and quality of the product (Bishop, 1984), meaning when less money is spent on higher quality, the perceived value will increase. The social psychology perspectives instead focus on specific meanings, which certain products carry, such as social status or culture. Sheth, Bruce, Newman, and Barbara (1991) explain that the perceived value is created here through the meaning of product purchase within the buyer’s society or community. The financial perspective builds upon the consumer surplus in economics, which means that lower prices through the offer of for example coupon vouchers create value for the consumer (Bishop, 1984).

The most extensive basis for perceived product value offers a study developed by Sheth et al. (1991), which explains how multiple “consumption value” dimensions have a different influence on consumer choices. They explored five dimensions (functional, emotional, conditional value, epistemic and social) and their relation to perceived utility of choice at three different decision levels. First the decision to buy level (buy or not buy), second the product level (product A or product B) and third the brand level (brand A or brand B). A functional value was considered to have the biggest influence on consumer choice, but Sheth et al. (1991) also found that the other dimensions do play an important role. On the one hand, for example, functional and social values were more influential on the choice of using filtered or unfiltered cigarettes, whereas, the emotional value had the biggest influence on the decision to smoke. That means that the different dimensions of perceived product values have different effects on the different decision levels (Sheth, Bruce, Newman, & Barbara, 1991). Other researchers define perceived product value as a “consumer’s overall assessment of the utility of a product (or service) based on perceptions of what is received and what is given” (Zeithaml, 1988). She explains further that the overall assessment is a process where the consumer compares “get“ and “give“ factors. The most used definition of perceived product value is the ratio between quality and price (Cravens, Holland, Lamb, & Moncrieff, 1988; Monroe, 1990). Zeithaml (1988) argued that the factors of perceived product value can be differentially weighted, as, for example, some consumer perceive low-priced products as valuable, others perceive higher product value when there is a certain balance between quality and price. Even though the quality and price ratio were often used, some researchers argue that this definition is too simplistic (Bolton & Drew, 1991). According to Porter (1990) other factors, such as special features or services would increase the perceived product value. Dickson (2000) defines values as ”abstract principals that reflect an individual’s self-concept”. Sheth et al. (1991) believe that value dimensions are independent of each other, because they “relate additively and contribute incrementally to choice”. Nevertheless, there are also studies, which propose that certain dimensions are interrelated (Osgood, Suci, & Tannenbaum, 1957). Product values can be perceived throughout different stages in the purchase process (Woodruff, 1997), in contrast to for example satisfaction, which is only relevant in the post-purchase and post-use stage (Oliver, 1981).

Bearing the above in mind, the perceived value construct ist very important nowadays, as retail brands can enhance the purchase intention for their products (Steenkamp & Geyskens, 2006) and also differentiate from their competitors (Kim, Sungjoo, & Yongtae, 2016).

6.3 Purchase intention and its relationship to perceived product value

Finding explanations to the question why consumers make purchases and why not, researchers often struggle to find a clear and straightforward answer. Nevertheless, knowing the explanation would help many businesses to sell their products (Ghazali, Othman, Yahya, & Ibrahim, 2008). Purchase intention is widely used for predicting actual purchase behavior and according to Grewal et al. (1998) a reliable indicator, as the stronger the intention to engage in a particular behavior, the actual behavior would be performed with a higher likelihood (Ajzen, 1991). Several conceptual models of purchase intention were used in previous studies, in which the researcher investigated the effect of a multi-dimensional variable (Roberts & Bacon, 1997; D'Souza, Taghian, Lamb, & Peretiatko, 2006) or a single-dimensional variable (Chan, 2001; Nik Abdul, 2009; Kong, Harun, Sulong, & Lily, 2014) on purchase intention. In contrast to value perceptions, purchase intentions are formed under the assumption of a coming transaction, most often in the form of purchase (Chang & Wildt, 1994). That means that purchase intention and perceived product values are two different constructs, which are positively related though (Chang & Wildt, 1994). The relationship between perceived product value and purchase intention has been extensively investigated in previous marketing research (Dodds, Monroe, & Grewal, 1991; Netemeyer, Krishnana, Pullig, Wang, & Dean, 2004). For example, Dodds et al. (1991) found out that 40% of the variance in purchase intention can be explained through perceived product value. Also, Eggert and Ulaga (2002) show that perceived product values account for around 86% of repurchase intentions. Kardes, Posavac, and Cronley (2004) argue that purchase decisions are often based on incomplete information, and that perceived product value helps in the decision through signaling and stands therefore in a positive relationship with purchase intention, as consumers are always more likely to buy a product with higher perceived value (Chang & Chen, 2008). Higher perceived product value can also increase the word-of-mouth effect and therefore increase the purchase intention (Sweeney, Soutar, & Johnson, 1999; Ashton, Scott, Solnet, & Breakey, 2010).

In line with Nik Abdul (2009) the present thesis focuses on the purchase intention of slow fashion products. Nik Abdul (2009) defined ‘green purchase intention’, as “the probability and willingness of a person to give preference to products with eco-friendly features over other conventional products in their purchase considerations” (Nik Abdul, 2009). According to Pelsmacker et al. (2005), perceived product values of ethical and sustainable-produced products have a significant

impact on their consumers purchasing behavior. Additionally, Griskevicius, Tybur and Van den Bergh (2010) could demonstrate that perceived environmental values have multilayered effects on purchase decisions and are influenced by both cognitive (functional and economic) and affective (emotional and social) factors. An essential focus in marketing literature lies on understanding perceived product values (Sánchez-Fernández, Iniesta-Bonillo, & Holbrook, 2009) as they play a vital role in gaining and sustaining competitive advantage (Chi & Kilduff, 2011), which is especially crucial for economic unsustainable slow fashion businesses.

6.4 Hypothesis and theoretical framework

Figure 1: Theoretical framework of this thesis

This thesis builds upon the multidimensional perceived product value construct of Sweeney and Soutar (2001), because this construct is developed to describe perceived product value of consumer durable goods. The dimensions are emotional value, social value, functional value due to quality and functional value due to price. The model of this survey investigates their effect on the purchase intention of slow fashion products. A multidimensional conceptualization was chosen, because purchase experiences commonly are influenced by both cognitive (functional and economic) and affective (emotional and social) factors (Sánchez-Fernández, Iniesta-Bonillo, & Holbrook, 2009; Sweeney & Soutar, 2001). Additionally, the environmental value was added as a dimension, because testing perceived environmental values together with other value dimensions might offer a more comprehensive understanding of the purchase process of slow fashion products.

6.4.1 Emotional value

Sweeney and Soutar (2001) define perceived emotional value as benefits derived from the feelings and affective states when purchasing a product. More and more consumers purchase products to satisfy their emotional needs (Kumar, Lee, & Kim, 2009). Doods, Kent, and Monroe (1991) argue that there is a positive relationship between the emotional value on purchase intention.

6.4.2 Social value

Sweeney and Soutar (2001) define social value as the utility derived from the product’s ability to enhance social self-concept. In other words, they define social value as consequences of what the product communicates to others.

6.4.3 Price value

Slow fashion products are often more expensive than fast fashion products. The reason for that is that slow fashion brands usually have higher production costs, which in turn leads to higher retail prices (Husted, Russo, Basurto Meza, & Tilleman, 2013; Pickett-Baker & Ozaki, 2008). For trading off benefits and risks of slow fashion products, consumers instead compare the price with a standard reference price than evaluating it in absolute terms (Garbarino & Slonim, 2003). Sweeney and Soutar (2001) define price value as the utility derived from the product due to the reduction of its perceived short-term and longer-term costs.

6.4.4 Quality value

Perceived quality has been widely accepted as the primary driver of purchase intention (Kumar, Lee, & Kim, 2009). Sweeney and Soutar (2001) define quality value as the utility derived from the perceived quality and the expected performance of the product. Shet et al.’s (1991) model, which was mentioned in the literature review before, argue that functional value is created by attributes such as price, durability, and reliability. In contrary, Sweeney and Soutar (2001) argue that durability and reliability attributes are often seen as aspects of quality and are in contrary to the price attribute positively related to perceived value. Therefore, quality and price are subfactors of functional value, but still should be measured separately (Sweeney & Soutar, 2001).

6.4.5 Environmental value

Unfortunately, there is only little empirical research available about perceived environmental value, which does not conform with the increasing awareness of environmental problems within the society (Whitmarsh, 2009). Only within the past years, studies focusing on perceived values relating to the environment have been evolved (Meijers & Stapel, 2011; Griskevicius, Tybur, & Van den Bergh, 2010; Koller, Floh, & Zauner, 2011). For example, Koller, Floh and Zauner (2011) introduced the ecological value as an antecedent to the core value dimensions of functional, social, emotional, and economical with the link to loyalty behavior within the automotive industry.

Therefore, the environmental value is added to this research model, in order to understand if that value is increasing the perceived product value or not.

Following all the arguments from the theoretical framework the following hypothesis were derived: Hypothesis 1a: Higher perceived quality value leads to higher purchase intention of slow

fashion products.

Hypothesis 1b: Higher perceived emotional value leads to higher purchase intention of

slow fashion products.

Hypothesis 1c: Higher perceived price value leads to higher purchase intention of slow

fashion products.

Hypothesis 1d: Higher perceived environmental value leads to higher purchase intention

of slow fashion products.

Hypothesis 1e: Higher perceived social value leads to higher purchase intention of slow

fashion products.

Hypothesis 1f: Higher perceived product values of slow fashion products lead to higher

purchase intention.

6.4.6 The importance of environmental value and price value during a purchase decision process

Sweeney and Soutar (2001)found out that emotional value is strongly influential on the purchase intention, especially for durable goods. They elaborated on an example from the 90s, where retailers experienced a downturn in turnover, because discounts and low prices resulted in the loss of customers’ confidence (Age, 1993). Swait and Sweeney (2000) explain this phenomenon through the importance of a broader value concept for customers, which would mean a focus on another value dimension could be useful in such situations. Additionally, Sheth et al. (1991) explored that the effect of different value dimensions is dependent on the decision level (buy or not

buy), but also on the product type. Pookulangara & Shephard (2013) found out that even though many consumers would like to follow the slow fashion movement and buy slow fashion products, they were unable to do so due to their higher price. Taking this into account the following hypotheses was developed:

Hypothesis 2a: Price value has the most significant effect on the purchase intention of slow fashion products.

Nevertheless, Joergens (2006) stated that in general the public domain does not know the reasons why the prices are higher, which clearly shows the necessity to first tell a story around the production, social and environmental impact before being able to justify the price. Following this argument, the environmental value should play the second biggest role during the purchase decision process. Taking this into account the following hypotheses was developed:

Hypothesis 2b: Environmental value has the second most prominent effect on purchase intention of slow fashion products.

6.4.7 Research models

Prior work of research on the effect of perceived product value on the purchase intention is already in a mature state. That is why a quantitative research design was chosen. Another reason is to be able to find results with higher external validity. To answer the research quentions mentioned in the above the following model will be used. Previous researchers tried to identify a typical socially responsible consumer regarding demographics. Anderson and Cunningham (1972) for example concluded that a younger consumer is more socially responsible than older consumers, while education level and income showed no differences. Dickson (2001)found that female consumers are mostly the buyers of slow fashion products, even though other researchers could not find any influence between gender and ethical buying behavior (Mori, 2000; Sikula & Adelmiro, 1994). Therefore, two control variables age and gender were included in the research model.

(1) Purchase Intention= α+ β1*Quality+ β2*Emotional+ β3*Price+ β4*Environmental + β5*Social + β6*Gender + β7*Age

where:

Purchase Intention Purchase intention for slow fashion products Quality: Perceived quality value scale factor Emotional: Perceived emotional value scale factor Price: Perceived price value scale factor Environmental: Perceived environmental value scale factor Social: Perceived social value scale factor Gender: Gender (Dummy variable) Age: The exact age of respondent

7 Empirical research & methodology

The following part of the thesis deals with the empirical investigation. First, the survey instruments will be described before explaining the composition of the sample and statistical analysis methods used for the present study.

7.1 Survey instrument development

The model was conceptualized as a multi-dimensional construct. Five factors summarized in Table 1 namely social value, price value, quality value, emotional value and environmental value were used to measure the effect of perceived product values of slow fashion products on purchase intention. Items for measurement of the core product value dimensions were adopted from Sweeney and Soutar (2001). Items for measurement of perceived environmental value were adopted from Lindeman and Väänänen (2000). Items to measure purchase intention were adopted from Baker and Churchill (1977). When researching purchase intention, consumers have to be confronted with realistic multi-product buying situations during the study (De Pelsmacker, Driesen, & Rayp, 2005). For that reason, different products were presented in the online survey, namely t-shirts for men and women, a wooden bow tie and wooden brooches. All items were measured with a 5-point Likert scale, where the value of one stands for “do not agree at all” and and the value of five for “fully

agree”. Besides the purchase intention, the willingness to pay for each product was tested.

All data was composed in Excel and then analyzed with a multivariate regression in SPSS. As an incentive to completing the survey, participants were offered a coupon code for one of the shown products. Two additional coupon choices for the two major fast fashion brands were added, to be

able to test the actual product preference of the participants. The following table shows the psychometric characteristics of the used scales.

Age and gender were added to the survey to function as control variables. Respondents answered their actual age and gender was transformed into a dummy variable, whereas one stands for female and zero for male.

7.2 Sample description

The study uses the probability sampling technique, with the intent to gain results, which are highly representative of the population. The data was aggregated through an online survey during May 2018, which was distributed through e-mail and social media networks. Before sending out the survey, it was checked by the supervisor and independent individuals in order to test whether all questions are clear and not misleading.

In total 156 respondents took part in the survey, of which nine answers were deleted, due to an unusual answering time and suspicion of miss-usage of the survey. Therefore, the following empirical analysis is based on a dataset of n=147 randomly selected consumers (see Appendix B).

7.3 Statistical analysis description and robustness check

The statistical analysis was carried out with the statistical software SPSS Version 25. To be sure that there is no answer which needs to be extracted from the model, Cook’s distance was checked (Stevens, 2009). A significant outlier should only be removed if the Cook's distance value (CDi) > 1. The inspection of Cook's distances showed that all distances are significantly smaller than the critical value of 1. Thus, according to the criterion CDi> 1, no outliers were found. Since no significant outliers were transferred via the Cook's distance, all cases were kept in the dataset. Secondly, Cronbach’s alpha was used to determine the reliabilities of the scales. Following previous literature, a Cronbach's α over .50 is defined as sufficient reliable, a Cronbach's α over .70 as satisfactory reliable and a Cronbach's α over .80 as highly reliable (Wittenberg, 1998). As described in table 1 all scales show a Cronbachs α of over 0.80 and are therefore highly reliable. Items were also tested whether they improve the Cronbach’s α when deleted. This was never the case. Nevertheless Field (2013) emphasizes, that Cronbach's alpha depends heavily on the number

of items and not on the unidimensionality of a constructed measure and therefore this measure should be seen with caution.

Table 1: Reliability and descriptive statistics of the scales.

Scale Number of Items α Min. Max. M SD Price value 3 .90 1 5 3.19 .92 Quality value 3 .80 1.67 5 3.94 .72 Environmental value 3 .87 2 5 4.02 .85 Social value 2 .84 1 5 3.06 1.01 Emotional value 3 .89 1 5 3.61 .93

All scales together 5 .82

Note: Min.= Minimum; Max. = Maximum, M = Mean; SD = Standard Deviation.

In addition to the reliability test, a confirmative factor analysis for the five scales was conducted to be able to check the construct validity. As a rotation method, the Varimax rotation was used, which is the most commonly used method to analyze factor loadings. The rotated component matrix (see Appendix D) showed that the value scales load on five different factors separately, which confirmed the thesis’ framework. For a confirmative factor analysis, it is assumed that the items are highly correlated with each other. To test this a Bartletts test is used. The Bartletts test for sphericity tests the null hypothesis, which state that all observed variables are uncorrelated and have equal variances (Eid, Gollwitzer, & Schmitt, 2017). That means a significant Bartletts test is positive, because the variables are not uncorrelated. The Bartlett’s test showed significant results on an alpha level of 5% (see Appendix E) indicating that the correlation matrix contains not only random, but also systematic scattering. The Olkin-criteria indicates whether the entire correlation matrix is suitable for a confirmative factor analysis. The Olkin value of over .878, which is stated as very good (Hutcheson & Sofroniou, 1999), can be seen as positive therefore as well.

To be able to run a multivariate regression, a robustness check was conducted. First, concerning the sampling design, an effort was made to choose only consumers within Europe, to reduce any cultural bias. To test the robustness of each model several tests were conducted. The data was tested first on autocorrelation, linear relationship, homoscedasticity, and multicollinearity. A Durbin-Watson test resulted in a Durbin-Durbin-Watson value of 2.28, which means there is a slightly negative

autocorrelation, but still acceptable (see Appendix G). All independent variables were tested positively on a linear relationship with the dependent variable. Additionally, all individual scatterplots showed a consistent relationship between standardized residual and the standardized predicted value. Therefore, the used data is homoscedastic. Besides that, all variables showed a Variance Inflation Factor (VIF) value smaller than 3, which means there is no multicollinearity, as all VIF values are under the critical value of 10 (Hair, 2006).

To test the hypotheses one and two, a multivariate regression was performed. The results are shown in the next section of the empirical results.

8 Empirical results

In the following, the results of all five hypothesis are reported. Findings of testing the first hypothesis will be reported first. Subsequently, the statistical results of the second hypotheses are presented.

8.1 Descriptive analysis

The dataset contains information about their demographics, perceived product values, willingness to pay for demonstrated products and their purchase intention. The average age of the respondents is 26.33 years, where most (57.82%) of the respondents were between 19 and 25 years old. 68.03% of the respondents came from Germany (n=100), followed by 24.49% from other European countries (n=36) and 7.48% from Netherlands (n=11). Respondents stated as highest education in 56.46% of the answers a bachelor’s degree, for 29.93% a master’s degree and 13.61% a high-school or other degree.

With regard to the consumption related characteristics, the respondents showed different habits. More than the half of the respondents prefer to shop online (31.29%) and in small boutiques (24.49%), followed by brand stores with 19.73%. 59.18% of the sample could state at least one slow fashion brand. The brands were checked if they fall under the definition of a slow fashion brand. Besides it was interesting to see the differences in the willingness to pay for the stated products. On average respondents were willing to pay 31.69€ for the wooden bow ties, 26.08€ for the t-shirts and 13.20€ for the brooches.

Out of the five factors, the variables for the multivariate regression were created. Table 2 shows the correlations between the factor variables and the variable purchase intention. All factor variables show a significant positive correlation with the dependent variable (p<0.01).

Table 2: Correlation of each factor Price value

Quality value

Social value Emotional value

Env. value Purchase intention Price value 1 .528** .367** .386** .464** .666** Quality value .528** 1 .492** .627** .671** .487** Social value .367** .492** 1 .632** .339** .451** Emotional value .386** .627** .632** 1 .450** .601** Env. value .464** .671** .339** .450** 1 .385** Purchase intention .666** .487** .451** .601** .385** 1 **. Correlation is significant at the 0.01 level (2-tailed).

8.2 Findings of testing hypothesis 1a, 1b, 1c, 1d, 1e and 1f

To test hypothesis 1a, 1b, 1c, 1d and 1e, a multivariate regression with environmental value, price value, emotional value, social value, quality value as independent variables and purchase intention as a dependent variable was conducted. As seen in table 3, all individual perceived values do have a significant positive effect on an alpha level of 5% (p< 0.05) on purchase intention of slow fashion products. The coefficient was for environmental value 0.169, for price value 0.616, for emotional value .494, for social value 0.231 and for quality value 0.128. Price value and emotional value have the biggest impact on purchase intention. The model has an R2 _{of 0.614 (see table 3), which means} that this model explains 61.4% of the variance, which is an acceptable value.

Hypothesis 1a states that higher perceived quality value will result in higher purchase intention of slow fashion products. As quality value has a positive significant effect (.139) on purchase intention, this hypothesis fails to be rejected.

Hypothesis 1b states that higher perceived emotional value will result in higher purchase intention of slow fashion products. As quality value has a positive significant effect (.472) on purchase intention, this hypothesis fails to be rejected.

Hypothesis 1c states that higher perceived price value will result in higher purchase intention of slow fashion products. As quality value has a positive significant effect (.605) on purchase intention, this hypothesis fails to be rejected.

Hypothesis 1d states that higher perceived environmental value will result in higher purchase intention of slow fashion products. As quality value has a positive significant effect (.171) on purchase intention, this hypothesis fails to be rejected.

Hypothesis 1e states that higher perceived social value will result in higher purchase intention of slow fashion products. As quality value has a positive significant effect (.227) on purchase intention, this hypothesis fails to be rejected.

Table 3: Results of the multivariate regression including the control variables.

Variable Unstandardized coefficient B Std. Error Standardized Coefficient β Constant 2.316** .245 Env. value .171** .058 .155 Price value .605** .060 .547 Emotional value .472** .059 .427 Social value .227** .058 .205 Quality value .139* .059 .126 Age .024** .009 .151 Gender -.101 .119 -.046 R2 _.614

Dependent variable: Purchase Intention; *p < .05, **p < .01

Hypothesis 1f states that in general higher perceived product values will result in higher purchase intention of slow fashion products. All perceived product values were summarized into one factor variable and then tested through a linear regression on correlation with purchase intention. As stated in Table 4, the independent variable perceived product value has a highly positive and significant effect on purchase intention. Therefore, hypothesis 1f fails to be rejected. This means

that higher perceived product values of slow fashion products will automatically result in a higher purchase intention to buy them.

Table 4: Results of the linear regression between perceived product value and purchase intention

Variable Unstandardized coefficient B Std. Error Standardized Coefficient β Constant 2.918** .068 Perceived product values .743** .068 .155 R2 _.452

Dependent variable: Purchase Intention; *p < .05, **p < .01

8.3 Findings of testing hypothesis 2a and 2b

Hypothesis 2a states that price value has the most significant effect on purchase intention of slow fashion products. To test hypothesis 2a, the results of the multivariate regression were analyzed. As seen in table 3, price value does have the most prominent effect on purchase intention compared to the other values. This means that hypothesis 2a fails to be rejected.

Hypothesis 2b states that environmental value has the second most prominent effect on purchase intention of slow fashion products. To test hypothesis 2a, the results of the multivariate regression were analyzed. As seen in table 3 environmental value does not have the second most significant effect on purchase intention compared to the other values. With an unstandardized coefficient of 0.169 environmental value does have only the fourth most prominent effect on purchase intention. Emotional value does have the second most prominent effect on purchase intention (0.494). This means that hypothesis 2b can be rejected. As mentioned earlier two control variables age and gender were added to the regression.

As seen in table 3 the positive correlation between age and purchase intention of slow fashion products is significant on a 5%-alpha level (p< 0.05). Age does have a positive effect (0.024) on the purchase intention. In contrary, the correlation between gender and purchase intention is not significant on a 5%-alpha level (p> 0.05).

9 Discussion

9.1 Uni-dimensional versus multi-dimensional value construct

Research around perceived product values has been extensively done before, which has led the conceptualization to become very heterogeneous. Perceived product values have not only been used as an exploratory variable in many different settings, but it also seems that scholars can not agree to any consistent definition nor explanation. This thesis does not only contribute to a better understanding of the application of the product value construct in the slow fashion industry, but also clearly supports the multi-dimensional approach of perceived value theory.

In earlier days practitioners believed that utilitarian values affected consumer preferences (Chiu, Hsieh, Li, & Lee, 2005). This belief is drawn from the neoclassical economic theory, which defines consumers as human beings, who decide rationally with the goal to maximize utility, but are still constraint by on the one hand the price and on the other hand their budget (Sweeney, Soutar, Whiteley, & Johnson, 1996). A more recent and popular conceptualization of perceived product values has been considered as a cognitive trade-off between benefits and sacrifices, where benefits stand for the performance in terms of quality and sacrifices reflect the price. Most of the studies have focused on such economic-based consumer. Therefore, it can be said that this uni-dimensional approach to study the construct of perceived product values dominates. An uni-dimensional approach has the advantage to be simple. Nevertheless, it does not reflect the complexity of perceived product values. Sweeney et al. (1996) described the approach as “summarized” and others as “narrow” (Mathwick, Malhotra, & Rigdon, 2001). This approach fails to explain several intrinsic, emotional and intangible factors, which do still play an essential role in the value creation process (Holbrook & Hirschman, 1982). Therefore, many scholars concluded that perceived product values instead need to be seen with a multi-dimensional approach (Mathwick, Malhotra, & Rigdon, 2001; Sweeney & Soutar, 2001). This thesis research was based on the multi-dimensional construct of Sweeney and Soutar and as the results show the emotional value has the second most significant impact on the purchase intention, clearly shows that product values cannot be described only by quality and price. Additionally, the results showed that all value scales were significant and therefore essential to keep in the model.

9.2 Sustainable business model: slow fashion quality vs. price

Pookulangara and Shephard (2013) found out that consumers believe that it requires much budget to buy slow fashion products, which are additionally not as "trendy" compared to fast fashion items. Additionally, Carrigan and Attalla (2001) show that green product attributes, even if considered as important, do not make up for the higher perceived costs. This empirical research suggests similar findings. As the price value has the most significant effect on purchase intention for slow fashion products, it can be assumed that price is more important than the environmental features of the products. As an example, Carrigan and Attalla (2001) explain that shoppers do make ethical and environmental purchases, in case they do not need to pay more or lose quality. Similar findings were also discovered in the organic food segment by (Lee & Yun, 2015). Therefore, it is recommended that entrepreneurs in the slow fashion industry find strategies, which will minimize the adverse price effect.

9.3 Emotional value vs. environmental value

Hypothesis 2b stated that perceived environmental value has the second most significant effect on purchase intention of slow-fashion products after the perceived price value. Contrary, the empirical results show that not environmental value, but the emotional value has the second most significant effect after the price value on consumers’ purchase intention. Even though this study was about eco-friendly products, perceived environmental value seems only to have a small effect on the purchase intention. Why is that the case? Padel and Foster (2005) investigated consumers of organic food and found out that they feel happy and gratified when buying organic food, as they believe that they contributed to a better environment and animals' well-being. This finding showed that perceived environmental value and perceived emotional value are two constructs, which relate very much to each other (see table 2). Especially slow fashion shoppers feel an emotional connection to the items they bought, as they care about the production, materials, and impact on the environment (Watson & Yan, 2013). These arguments support the findings of this study, that emotional value has a higher effect on purchase intention than environmental value.

9.4 Slow Fashion: Perception and knowledge of society

Slow fashion is an emerging trend, which caught the attention of many retailers and consumers in the past years. Wood (2009) reports that consumers think twice what they buy and begin to buy products, which last longer. Nevertheless, consumers currently still do not seem to have sufficient

knowledge on slow fashion to make fully informed decisions (Pookulangara & Shephard, 2013). This fact was also confirmed by the answers of this thesis’ survey. 42% of the respondents did not know any slow fashion brand. Additionally, a few respondents believed that some of the biggest fast fashion retailers are slow fashion brands. Especially in case of slow fashion, it is vital and critical to understand the today's environmental problems fully. Otherwise, consumers do not see the importance to engage in buying more sustainable products (Moisander, Markkula, & Eräranta, 2010). To be able to inform today's consumers' retailers do not only need to focus on transparency of their supply chain and production method but also on the easy access to this information so that consumers can make more informed purchase decisions (Gargi & Ha-Brookshire, 2011). The decision on consumer level will at the end determine the success of slow fashion retailers, as they need to connect and identify with the products they buy and story the retailer tells (Tran, 2008). Why are transparency and the education of consumers about slow fashion so crucial in the context of the product value creation? Devinney, Auger, Eckhardt & Birtchnell (2006) explain that increasing transparency concerning production methods and environmental impact will increase the value perception of consumers. As a result, perceived product values of slow fashion products would increase, and slow fashion retailers can justify higher prices.

10 Conclusion and managerial implications

This thesis contributes to the literature in three ways. First, based on an in-depth literature review, building on the multidimensional value scale of Sweeney and Soutar (2001), this study examines the multi-dimensional perceived value model (social value, price value, quality value and emotional value) in the context of slow fashion products. The scale of each value construct was proven reliable and valid. Second, a new value construct ‘environmental value’ was added to the framework, which showed a small positive significant correlation with purchase intention. All five value constructs accounted for most of the variance of the perceived value effect on purchase intention (59.1%). Third, the empirical research shows that the perceived value construct cannot be seen as a unidimensional construct, but needs to be seen as a multidimensional construct, where not only quality value and price value play an important role, but also emotional and social values. Even though the measures and scales were tested with slow fashion products, it is very likely that the research can also be applied to other product categories or industries. Additionally, this thesis adds implications and recommendations for entrepreneurs and founders in the slow fashion retail industry. Value-creation belongs to an essential business strategy for creating long-term success.

Therefore, founders of slow fashion brands need to emphasize the different dimensions of perceived product value and think about the implications of every process from product creation to product marketing.

Summarizing the findings of this research, price value has the most significant effect on purchase intention of slow fashion products, followed by the emotional value, social value, environmental value and quality value. These results show the importance for retailers to find ways how to justify the higher prices and convey enough emotions throughout the storytelling and promotional campaigns. The order of the importance of each value in a purchase decision process contradicts with findings from other studies, where quality and price value were the primary drivers for higher purchase intention and define social and emotional value only as complementary (Chi & Kilduff, 2011; Kwon, Trail, & James, 2007). Therefore, entrepreneurs need to be careful as this fact clearly shows that theory around perceived value cannot be generalized, as results can be misleading and not correct for other services or products.

To come to an end, entrepreneurs in the fashion industry need to keep in mind that fashion is a dynamic process, which is very dependent on the current trends and individual lifestyles of consumers. Therefore, especially perceived social and environmental value of consumers can change, which poses a significant challenge to entrepreneurs in the fashion industry, as they need to stay up-to-date and explore a variety of theories (Cholachatpinyo, Padgett, & Croker, 2002).

11 Limitations and further research avenues

This thesis adds empirical evidence to the literature and gives implications for future research, but also for practitioners. Nevertheless, there are also still some limitations, which need to be mentioned and taken into consideration for future studies. This study shows the impact of different perceived values on the purchase intention of slow fashion products at a particular point in time. As perceived product values should be seen as a continuous process, in which the relationship between retailers and consumers will always change - especially with the young slow fashion industry, it is essential also to conduct longitudinal studies, to be able to understand the consumer, but also industry development fully. Additionally, future studies should have a more in-depth look into the impact of demographic variables on the formation of product values, as this study did not have a closer look in potential demographic differences other than age and gender. As the data was

retrieved through an online survey, consumer segments that do not have access to the internet were left out. Therefore, future studies should use a hybrid model and also use offline data collection methods. In general, it would also be interesting to increase the sample size to be able to generalize the results better.

12 Bibliography

Adamczyk, A. (n.d.). Forbes. Retrieved April 2018, from

http://www.forbes.com/sites/aliciaadamczyk/2014/11/20/why-brands-and-retailers-are-running-withthe-slow-fashion-movement/#1b1266906505

Age. (1993). Call for Retailers to Win Back Consumers’ Loyalty. Melbourne. (November 25), 24. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision

Processes, 2(50), pp. 179-211.

Anderson, T., & Cunningham, W. (1972, July). The Socially Conscious Consumer. Journal of

Marketing, (36), pp. 23–31.

Ashton, A., Scott, N., Solnet, D., & Breakey, N. (2010). Hotel restaurant dining: the relationship between perceived value and intention to purchase. Tourism and Hospitality Research,

3(10), pp. 206-18.

Baker, M., & Churchill, G. (1977). The Impact of Physically Attractive Models on Advertising Evaluations. Journal of Marketing Research(14), pp. 538-555.

Barnes, L., & Lea-Greenwood, G. (2006). Fast fashioning the supply chain: shaping the research agenda. Journal of Fashion Marketing and Management, 10 (3), pp. 259-271.

Bhardwaj, V., & Fairhurst, A. (2010). Fast fashion: response to changes in the fashion industry.

The International Review of Retail, Distribution and Consumer Research, 20 (1), pp.

165–173.

Bishop, W. (1984). Competitive Intelligence. Progressive Grocer(19), pp. 3

Bolton, R., & Drew, J. (1991, March 17). A Multistage Model of Customers’ Assessments of Service Quality and Value. Journal of Consumer Research, 17 (March) pp. 375–384. Burden, S. (1998, November 1). Current Trends and Issues in the Retail Sector. European

Venture Capital Journal, pp. 1-5.

Carrigan, M., & Attalla, A. (2001). The myth of the ethical consumer – do ethics matter in purchase behaviour? Journal of Consumer Marketing, 18, pp. 560–578.

Cataldi, C., Dickson, M., & Grover, C. (2010). Slow fashion: tailoring a strategic approach towards sustainability. Master’s thesis, Blekinge Institute of Technology, Sweden. Chan, R. (2001). Determinants of Chinese consumers green purchase behavior. Psychology and

Chang, H., & Chen, S. (2008). The impact of online store environment cues on purchase intention: trust and perceived risk as a mediator. Online Information Review, 6(32), pp. 818-41.

Chang, T.-Z., & Wildt, A. (1994). Price, Product Information, and Purchase Intention: An Empirical Study. Journal of the Academy of Marketing Science, 1(22), pp. 16-27.

Chi, T., & Kilduff, P. (2011). Understanding consumer perceived value of casual sportswear: An empirical study. Journal of Retailing and Consumer Services, (18), pp. 422–429.

Chiu, H.-C., Hsieh, Y.-C., Li, Y.-C., & Lee, M. (2005). Relationship Marketing and Consumer Switching Behavior. Journal of Business Research, 58(12), pp. 1681–9.

Cholachatpinyo, A., Padgett, I., & Croker, M. (2002). A conceptual model of the fashion process – part 1: the fashion transformation process model. Journal of Fashion Marketing and

Management, 6(1), pp. 11-23.

Clark, H. (2008). Slow Fashion: An Oxymoron or a Promise for the Future . . . ? Fashion Theory:

The Journal of Dress, Body & Culture, 12 (4), pp. 427-446.

Cline, E. (2012). Overdressed: The Shockingly High Cost of Cheap Fashion. Portfolio/Penguin. Cravens, D., Holland, W., Lamb, C., & Moncrieff, W. (1988, November 17). Marketing’s Role in

Product and Service Quality. Industrial Marketing Management, pp. 285–304.

De Pelsmacker, P., Driesen, L., & Rayp, G. (2005). Do consumer care about ethics? Willingness to pay for fair-trade coffee. Journal of Consumer Affairs, pp. 363–385.

De Pelsmacker, P., Driesen, L., & Rayp, G. (2005). Do Consumers Care about Ethics?

Willingness to Pay for Fair-Trade Coffee. The Journal of Consumer Affairs, 2(39), pp. 363-385.

Devinney, T., Auger, P., Eckhardt, G., & Birtchnell, T. (2006). The other CSR: consumer social responsibility. Stanford Social Innovation Review, 3(4), pp. 30-7.

Dickson, M. (2000). Personal Values, Beliefs, Knowledge, and Attitudes Relating to Intentions to Purchase Apparel from Socially Responsible Businesses. Clothing and Textiles Research

Journal, 1(18), pp. 19–30.

Dickson, M. (2001). Utility of No Sweat Labels for Apparel Consumers: Profiling Label Users and Predicting Their Purchases. The Journal of Consumer Affairs, 1(35), pp. 96–119. Diette, C., Finnerty, K., Herther, K., & Stanley, B. (2012). Styling sustainability, what’s en vogue

when it comes to eco-fashion? Retrieved from Onegreenscore: http://

Dodds, W., Monroe, K., & Grewal, D. (1991). Effects of price, brand and store information on buyers’ product evaluations. Journal of Marketing Research(28), pp. 307-319.

D'Souza, C., Taghian, M., Lamb, P., & Peretiatko, R. (2006). Green products and corporate strategy: An empirical investigation. Society and Business Review, 2(1), pp. 144-157. Eggert, A., & Ulaga, W. (2002). Customer perceived value: A substitute for satisfaction in

business markets? The Journal of Business & Industrial Marketing(17), pp. 107-118. Eid, M., Gollwitzer, M., & Schmitt, M. (2017). Statistik und Forschungsmethoden. Beltz. Elkington, J. (1998). Cannibals with Forks: The Triple Bottom Line of 21st Century Business.

BC, Canada: New Society: Gabriola Island.

Field, A. (2013). Discovering statistics using IBM SPSS Statistics. London.: Sage. Fletcher. (2007). Slow fashion. Ecologist, p. 61.

Fletcher. (2010). Slow fashion: an invitation for systems change. Fashion Practice(2), pp. 259– 266.

Forester, M. (1999, April). Deja vu Discussion Delivers Message Emphasizing Value. Chain

Store Age, p. 12.

Garbarino, E., & Slonim, R. (2003). Interrelationships and Distinct Effects of Internal Reference Prices on Perceived Expensiveness and Demand. Psychology & Marketing, 3(20), pp. 227–248.

Gargi, B., & Ha-Brookshire, J. (2011). Do transparent business practices pay? Exploration of transparency and consumer purchase intention. Clothing and Textiles Research Journal,

29(2), pp. 135–149.

Ghazali, M., Othman, M., Yahya, A., & Ibrahim, M. (2008). Products and country of origin effects: The Malaysian consumers' Perception. International Review of Business Research

Papers, 2(4), pp. 91-102.

Ghemawat, P., & Nueno, J. (2003). ZARA: Fast Fashion. . Harvard Business School, Boston, MA.

Grewal, D., Krishnan, R., Baker, J., & Robin, N. (1998). The effect of store name, brand name, and price discounts on consumers’ evaluations and purchase intentions. Journal of

Retailing, (74), pp. 331-352.

Griskevicius, V., Tybur, J., & Van den Bergh, B. (2010). Going green to be seen: Status, reputation, and conspicuous conservation. Journal of Personality and Social

Hair, J. (2006). Multivariate data analysis. New York: Pearson Prentice Hall. Hall, R., & Woodward, S. (2010, June). The Burden of the Nondiversifiable Risk of

Entrepreneurship. The American Economic Review, pp. 1163-1194.

Holbrook, M., & Hirschman, E. (1982, September). The Experiential Aspects of Consumption: Consumption Fantasies, Feelings and Fun. Journal of Consumer Research(9), pp. 132– 140.

Huber, F., Herrmann, A., & Morgan, R. E. (2001). Gaining competitive advantage through customer value oriented management. Journal of Consumer Marketing, pp. 41–53. Husted, B., Russo, C., Basurto Meza, M., & Tilleman, S. (2013). An Exploratory Study of

Environmental Attitudes and the Willingness to Pay for Environmental Certification in Mexico. Journal of Business Research. In press.

Hutcheson, G., & Sofroniou, N. (1999). The multivariate social scientist: Introductory statistics

using generalized linear models. CA: Sage Publications.

Joergens, C. (2006). Ethical fashion: myth or future trend? Journal of Fashion Marketing &

Management, 10(3), pp. 360–371.

Johansson, E. (2010). Slow fashion: the answer for a sustainable fashion industry? Master thesis, The Swedish School of Textiles., Sweden.

Jung, S., & Jin , B. (2014). A theoretical investigation of slow fashion: sustainable future of the apparel industry. International Journal of Consumer Studies(38), pp. 510–519.

Kardes, F., Posavac, S., & Cronley, M. (2004). Consumer inference: a review of processes, bases, and judgment contexts. Journal of Consumer Psychology, 14(3), pp. 230-56.

Kim, J., Sungjoo, L., & Yongtae, P. (2016). A visual context-based market analysis of mobile application services. Management Decision, 9(54), pp. 2106-2132.

Koller, M., Floh, A., & Zauner, A. (2011). Further insights into perceived value and consumer loyalty: A “green” perspective. Psychology & Marketing(28), pp. 1154–1176.

Kong, W., Harun, A., Sulong, R. S., & Lily, J. (2014). THE INFLUENCE OF CONSUMERS’ PERCEPTION OF GREEN PRODUCTS ON GREEN PURCHASE INTENTION.

International Journal of Asian Social Science,, 8(4), pp. 924-939.

Koskela, M., & Vinnari, M. (2009). Future of the consumer society. Future of the Consumer

Society. Tampere, Finland.

Kumar, A., Lee, H., & Kim, Y. (2009). Indian consumers' purchase intention toward a United States versus local brand. Journal of Business Research, 5(62), pp. 521- 527.

Kwon, H., Trail, G., & James, J. (2007). The mediating role of perceived value: Team identification and purchase intention of team-licensed apparel. Journal of Sport

Management, 21, pp. 540–554.

LeBlanc, S. (2012). Sustainable fashion design: oxymoron no more? BSR America.

Lee, H.-J., & Yun, Z.-S. (2015). Consumers’ perceptions of organic food attributes and cognitive and affective attitudes as determinants of their purchase intentions toward organic food.

Food Quality and Preference, 39, pp. 259–267.

Levy, M. (1999, September 15). Revolutionizing the Retail Pricing Game. Discount Store News. Lindeman , M., & Väänänen, M. (2000). Measurement of ethical food choice motives.

Appetite(34), pp. 55-59.

Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential Value: Conceptualization,

Measurement and Application in the Catalog and Internet Shopping Environment. Journal

of Retailing, 77(1), pp. 39–56.

Meijers, M., & Stapel, D. (2011). Me tomorrow, the others later: How perspective fit increases sustainable behavior. Journal of Environmental Psychology(31), pp. 14-20.

Moisander, J., Markkula, J., & Eräranta, K. (2010). Construction of consumer choice in the market: challenges for environmental policy. International Journal of Consumer Studies,

1(34), pp. 73–79. Retrieved from International Journal of Consumer Studies.

Monroe, K. (1990). Pricing: making profitable decisions. New York: McGraw-Hill Book Company.

Mori. (2000). European Attitudes towards Corporate Social Responsibility. London: Mori. Netemeyer, R., Krishnana, B., Pullig, C., Wang, G., & Dean, D. (2004). Developing and

validating measures of facets of customer-based brand equity. Journal of Business

Research, (57), pp. 209-224.

Nik Abdul, R. (2009). Awareness of eco-label in Malaysia‟s green marketing initiative.

International Journal of Business and Management, 4(8), pp. 132-141.

Nueno, J., & Quelch, J. (1998). The mass marketing of luxury. Business Horizons, 6(41), pp. 61– 8.

Oliver, R. (1981). Measurement and Evaluation of Satisfaction Processes in Retail Settings.

Journal of Retailing, (57), pp. 25–48.

Osgood, C., Suci, G., & Tannenbaum, P. (1957). The Measurement of Meaning. Urbana, Illinois: University of Illinois Press.