Can CSR and Slow Fashion Influence Purchase Intent?

A quantitative study investigating factors that affect consumers’ behavioral intentions towards buying fashion online

MAKAKALA, CECILE NEFFLING, MINDA

School of Business, Society & Engineering

Course: Master Thesis in Business Supervisor: Cecilia Lindh Administration

Course code: FOA403 15 cr Date: 20/6/2, 20/6/9

ABSTRACT

Date: 20/06/02, 20/06/09 Level: Master Thesis in Business Administration, 15 cr Institution: School of Business, Society and Engineering, Mälardalen University Authors: Cecile Makakala Minda Neffling (94/11/20) (95/07/02) Title: Can CSR and Slow Fashion Influence Purchase Intent? A quantitative study investigating factors that affect consumers’ behavioral intention towards buying fashion online Tutor: Cecilia Lindh Keywords: CSR, Theory of Reasoned Action, Slow fashion, Online shopping, Purchase intent Research question: How can CSR affect consumers’ intent to buy fashion online? Purpose: The purpose of the study is to investigate the impact of CSR on consumers’ purchase intent towards buying fashion online. The study utilizes the Theory of Reasoned Action as the foundation for an extended model and brings together consumers’ attitudes, subjective norms and CSR. Additionally, the research combines the concept of Slow Fashion into the model in order to measure consumers’ attitudes towards sustainable purchases. Method: Quantitative Conclusion: The findings of this study showed that CSR in the branches of proactive and reactive has a low impact on the purchase intent when buying fashion online. The foundation for the purchase intent and the main influence generates from the attitudes and the subjective norms. Moreover, the results indicated that the respondents were not familiar with the concept of Slow Fashion. Nevertheless, their attitudes towards slow fashion purchases were positive, which indicated a positive relationship with purchase intent.

Acknowledgements

The authors of this research are forever grateful to everyone around the world who participated in the survey and contributed to this study. The authors are ever thankful for the amazing support

and guidance provided by Professor Cecilia Lindh, the supervisor of this research. Finally, the

authors would like to acknowledge the rest of the research team, Ellinor, Laura, Adelle and

Victoria for their wholehearted support and guidance during the whole process. This study is an outcome of a cooperation of many parties and the gratitude belongs to everyone who helped the

authors during this journey.

Table of Contents

1. INTRODUCTION ...... 6

1.1. RESEARCH GAP ...... 9

1.2. PURPOSE AND RESEARCH QUESTION ...... 10

2. THEORETICAL FRAMEWORK ...... 11

2.1. THE THEORY OF REASONED ACTION ...... 11

2.2. CONSUMER ATTITUDES ...... 13

2.3. SOCIAL GROUPS ...... 14

2.4. CSR ACTIVITIES ...... 15

2.5. SLOW FASHION AND SUSTAINABILITY ...... 18

2.6. PURCHASE INTENT ...... 20

2.7. ONLINE SHOPPING ...... 22

3. HYPOTHESIS DEVELOPMENT ...... 24

3.1. CONCEPTUAL MODEL ...... 27

4. METHODOLOGY ...... 30

4.1. PHILOSOPHICAL CHOICE ...... 30

4.2. EVOLUTION OF THE THEORY ...... 31

4.3. QUANTITATIVE APPROACH ...... 31

4.4. DATA COLLECTION ...... 32

4.5. SAMPLE ...... 34

4.6. OPERATIONALIZATION ...... 35

4.7. DATA ANALYSIS ...... 37

4.8. TIME SCALE ...... 39

4.9. RELIABILITY AND VALIDITY ...... 39

4.10. ETHICS ...... 41

4.11. LIMITATION ...... 42

5. ANALYSIS OF THE FINDINGS ...... 43

5.1. REGRESSION ...... 43

5.2. CORRELATIONS ...... 44

6. DISCUSSION ...... 46

7. CONCLUSION ...... 51

7.1. FUTURE RESEARCH ...... 53

8. MANAGERIAL IMPLICATIONS ...... 54

9. REFERENCE LIST ...... 55

10. APPENDIX ...... 75

1. Introduction

Nowadays, it has become more common that when a consumer seeks to make an online purchase, their decision is based on the role the company has in the society and their level of environmental responsibility (Grimmer & Bingham, 2013). For the past decades, companies have tried to pursue a path where the aim is to develop a sustainable long-term relationship with their stakeholders.

Therefore, corporate social responsibility (CSR) activities are essential in order to preserve the social, cultural and economic elements of the environment in which an organization operates in

(Shahzad, Qu, Rehman, Zafar, Ding, & Abbas, 2020). Implementing CSR initiatives is a strategy that has been widely used to differentiate firms and their products while influencing consumer choices (Uhlig, Mainardes, & Nossa, 2019). A study by McWilliams, Siegel and Wright (2006) suggests that CSR is an important part of firms’ differentiation strategies. It could be in a direct way through product feature development or indirectly through the reputation and the brand image of the firm (Kuokkanen & Sun, 2019).

For the past two decades, a shift has occurred in corporate strategies from mostly focusing on scattered CSR activities to identifying the role CSR has in the business ecosystem (McWilliams et al., 2006; Kuokkanen & Sun, 2019). Although, most studies have a positive attitude towards

CSR practices and initiatives, studies show that CSR by itself is not an effective component to influence purchase intent in an online setting. Purchase intent can also be influenced by factors such as brand affection, brand recognition and the attitude towards the brand (Lin, Chen, Chiu, &

Lee, 2011; Anastasiadou, Lindh, & Vasse, 2018; Deli-Gray, Haefner, & Rosenbloom, 2012).

Furthermore, purchase intent can be a result of attitudes and subjective norms which are known to be the foundation for a persons’ behavioral intent (Mi, Chang, Lin, & Chang, 2018).

Because of the drastic industrial and social changes caused by technology the internet is easier accessible, through smartphones and additional internet-dependent devices. The increasing trend of online shopping has therefore triggered a huge growth in the level of competition between firms (Akroush & Al-Debei, 2015). A study by the World Internet Usage & Population Statistics, shows that approximately half of the world’s population are regular internet users (Anastasiadou et al., 2018). Due to the increase in popularity of online shopping, online vendors are constantly exploring new ways to connect with more customers and reach those beyond their domestic borders (Kawaf & Tagg, 2012; Anastasiadou et al., 2018).

While online shopping and internet access are increasing, consumers are becoming more educated and aware and therefore aim to make purchases that are more sustainability and ethically conscious (Pookulangara & Shepard, 2013). Slow fashion is a concept that gives the consumer the alternative to make more sustainable and ethical purchases (Hazel, 2008). In contrary to fast fashion, slow fashion values good quality, sustainability, longevity, local production and resources and an environmentally friendly production process (Sener, Biskin, & Kilinc, 2019; Hall, 2017;

Hazel, 2008). The ultimate goal of slow fashion is to reduce the waste volume and to persuade consumers to buy less by creating fashion items that have longer life cycles (Hall, 2017; Hazel,

2008).

The authors have chosen to base the theoretical framework on the Theory of Reasoned

Action (TRA). TRA is a model that is often used in the context of trying to predict consumer behavior or a persons’ behavioral intent (Ajzen & Fishbein, 1980; Park & Levine, 1999; Madden, 7

Ellen, & Ajzen, 2007; Ramayah, Lee, & Mohamad, 2010; Mishra, Akman, & Mishra, 2014).

According to TRA, a persons’ behavioral intentions are determined by two factors: the attitude and subjective norms. The attitude refers to an individuals’ attitude towards the behavior which is personal in nature. Subjective norms are perceptions of social pressures and its influence on either performing or not performing a certain behavior (Ajzen & Fishbein, 1980; Madden et al., 2007;

Belleau, Summers, Xu, & Pinel, 2007). Many scholars argue that understanding the behavioral intention is essential when predicting or explaining a persons’ behavior and the reasoning behind it (Madden et al., 2007; Mishra et al., 2014; Mi et al., 2018; Alzahrani, Hall-Phillips, & Zeng,

2019). The authors believe that the TRA model will be useful in this study because it focuses on the factors related to behavioral intention which is the focus of this study. The reasoning in which why such theory has been chosen is due to previous studies showing success in applying TRA in the fields of marketing, purchase intent and CSR activities.

The remainder of the paper will have the following structure. First, a research gap, the purpose and the research question will be presented. Second, the theoretical framework where the relevant concepts and previous research will be discussed. Followingly, the third chapter introduces the development of the hypotheses. Fourth, the conceptual model created for this study will be presented followed by the methodology. The fifth section will present an analysis of the findings, followed by a discussion. Lastly, this research will conclude with a conclusion, future research and managerial implications.

1.1. Research Gap

There are many pre-existing studies that focuses on the effects CSR activities have on a firms’ performance, reputation and its impact on the market value. Moreover, studies have been concentrated on whether CSR activities have an effect on consumer behavior and their purchase intentions (Anastasiadou et al., 2018). The popularity of digitalization and the increased use of technology has resulted in growth in online shopping (Deli-Gray et al., 2012). Consumers are now choosing brands based on knowledge, trust and the attitudes towards the brand, rather than an emotional connection (Deli-Gray et al., 2012). Furthermore, there are other factors that can influence consumer behavior. Psychology suggests that an individual is highly influenced by others and their social bonds. Whether these bonds are strong or weak, they play a significant role on a persons’ actions, decisions, attitude and opinions (Mochalova & Nanopoulos, 2014). The framework of TRA is commonly used when measuring behavioral intentions and have been successfully used in various studies in numerous fields (Mi et al., 2018). Meanwhile, TRA has also been used in previous studies concerning purchase intent such as (Belleau et al., 2007; Omar &

Owusu-Frimpong, 2007; Tsai, Chin, & Chen, 2010; Dodd & Supa, 2011; McClure & Seock, 2020).

Despite these previous studies, there is a gap between the consumers’ behavioral aspects online and sustainable online shopping in the form of slow fashion. TRA will therefore be used as an approach in order to research the gap between attitudes and behavioral intention and sustainable fashion.

1.2. Purpose and Research Question

The purpose of this paper is to investigate how CSR can affect the purchase intent of consumers when buying fashion online. Previous studies have shown, that even if CSR have a positive impact on consumers, it might not generate to an increase in the purchase intent (Öberseder,

Schlegelmilch, & Gruber, 2011; Lin et al., 2011). To develop a better understanding of consumer behavior in this context, this paper selects the Theory of Reasoned Action (TRA) as the foundation for the conceptual model development. The objective is to exploit an existing theory and use it as base for an extended model. Thus, the study investigates how consumers react to the three components; attitudes, subjective norms and the new addition of CSR. Furthermore, the interest lies in evaluating whether the new addition to the model is applicable in explaining the purchase intent. Furthermore, the study also investigates how the concept of Slow Fashion and the attitudes towards it influence the international consumers. This aspect connects the concept of slow fashion to the attitudinal part of the theory, which is constructed to be able to study the effect of consumers’ attitudes towards Slow Fashion purchases (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al., 2007). By the guidance of the TRA and the extended model, the study will investigate the purchase intent when buying fashion online by combining consumers’ attitudes, subjective norms,

CSR and slow fashion into one entirety. Based on these elements, the objective is to answer the following research question:

“How can CSR affect consumers’ intent to buy fashion online?”

2. Theoretical Framework

2.1. The Theory of Reasoned Action

The Theory of Reasoned Action (TRA) is a model that has been widely used for the prediction of consumer behavior and their behavioral intention (Ajzen & Fishbein, 1980; Park & Levine, 1999;

Madden et al. 2007; Ramayah et al., 2010; Mishra et al., 2014). TRA, is a branch from social psychology that predicts a person’s behavioral intention and their actual behavior of doing a particular activity, according to the individuals’ attitude and subjective norms (Mi et al., 2018).

This theory is based on the principle that individuals are rational beings that use the information available to them in a systematic way (Belleau et al., 2007). TRA is relatively straightforward and can adequately predict different behaviors. This can later be useful when identifying target groups and developing strategies on how to handle the change in the consumer behavior (Sheppard,

Hartwick, & Warshaw, 1988; Belleau et al., 2007).

The TRA model has been widely accepted and successfully used in multiple studies in a variety of fields (Mi et al., 2018). Such fields include marketing, by incorporating consumer motivations (Fitmaurice, 2005), promoting recycling behavior (Ho, 2002), the intent to watch eSports (live streaming sports events online) (Xiao, 2020), the intent to engage in sustainable behaviors (Longo, Shankar, & Nuttall, 2019) and the attitude towards luxury fashion goods (Zhang

& Kim, 2013). According to TRA, person’s behavioral intentions are determined by two factors: the attitude and subjective norms (Ajzen & Fishbein, 1980; Madden et al. 2007; Belleau et al.,

2007). Behavioral beliefs are according to the theory the underlying influence of the individuals’

attitude towards performing the behavior and the evaluation of whether doing this behavior is good or bad (Ramayah, Nasurdin, Noor, & Hassan, 2003; Madden et al., 2007). Attitudes are a set of beliefs which refer to a persons’ judgment in determining if performing a certain behavior will have a positive or a negative outcome. Generally, if a person believes that performing a behavior will have or lead to a positive outcome the attitude towards that behavior will be more positive.

On the contrary, if the individual believes that it will have a negative impact on the attitude towards it will be negative or at least less favorable (Ramayah et al., 2003).

Normative beliefs are based on subjective norms. It refers to the expectation and the social pressures of what a specific group or individuals think an individual should or should not do, and the individuals’ response to such expectations (Ramayah et al., 2003; Belleau et al., 2007).

Meaning, if an individual believes that most of its peers in which the person is motivated by think he/she should perform the behavior, then the social pressure will cause them to do so. On the other hand, if these people believe that the behavior is not something the individual should perform, the social pressure will be to avoid such behavior (Ramayah et al., 2003). In conclusion, various information sources will affect and determine the intention of a persons’ later behavior either through attitudes or subjective norms (Park & Levine, 1999; Ramayah et al., 2003; Madden et al.,

2007).

Figure 1: The Theory of Reasoned Action Model presented in Ramayah et al. (2003)

2.2. Consumer Attitudes

Consumer attitudes in this paper focuses on evaluating the attitudes towards buying fashion online.

The interest of this paper is in the Theory of Reasoned Action; thus, the concept of attitude is important to cover more thoroughly here (Belleau et al., 2007). Mathew (2016) along with Ajzen and Fishbein, (2000) examine that attitudes are a foundation for consumer behavior. According to

Evans, Jamal and Foxall (2009, p. 105) attitudes refer to an entity of factors that leads us to act in a specific manner. The authors (2009, p. 105) explain that these factors are based on the knowledge we have, feelings, tendencies and values, and that these form a demanding mental position which drives individuals towards action. In the process of consumers’ decision making, attitudes along with perceptions play an important role (Bahamonde-Birke, Kunert, Link, & de Dios Ortuzar,

2017). There is a distinguished connection between the attitudes and perception (Pickens, 2005).

For instance, Sabbir-Rahman (2012) defines perception as a process where an individual chooses, organizes and interprets impressions into a picture of the world that is logical and becomes meaningful. In this study the authors chose to separate perception and attitudes. Although, they are closely linked, this study focuses on understanding the attitudinal aspect of the theory which is an individuals’ attitude towards a behavioral intent (Belleau et al., 2007). Due the demanding nature of the attitudes, it is necessary to understand how consumers’ attitudes relate to buying fashion online (Evans, et al., 2009, p. 105; Belleau et al., 2007).

Cho (2004) examines the field of online shopping. The author (2004) recognizes that positive attitudes regarding to online buying diminish the consumers’ tendency to discontinue the shopping activity, thus there is a remarkable connection with attitude and behavior intention.

Continuously Suki and Suki (2017) refer to Cho’s (2004) insight that the attitudes consumers have towards shopping online reflect their acceptance to perform it. Other studies indicate similar results and support that attitudes influence consumers’ behavior and intentions to online buying

(Huseynov & Yildirim, 2014; Lin, 2007; Hasbullah, Osman, Abdullah, Salahuddin, Ramlee, &

Soha, 2016). Hasbullah et al. (2016) conclude in their study that attitudes regard to online shopping are positively associated with online purchase intention. Furthermore, Belleau et al. (2007) study generation Y and indicate that positive attitudes respond to an increasing purchase intent. The role of the attitudes of this younger generation outperformed the role of subjective norms, i.e. pressure coming from social sources (Belleau et al., 2007).

2.3. Social Groups

This chapter introduces the second part of the TRA model; subjective norms, which are guiding the consumers’ behavioral intentions (Belleau et al., 2007). Subjective norm can be understood as the pressure coming from social sources and how individuals perceive it (Belleau et al., 2007).

This instead is important to acknowledge as marketing and consumer behavior are strongly linked with various transforming groups (Evans, et al., 2009, p. 241). More specifically, the behavior towards buying is guided by the effect of these groups (Evans, et al., 2009, p. 242). The definition highlights that groups consist of multiple people with similar aims and purposes (Evans, et al.,

2009, p. 242). In order to reach the aims, interaction among these individuals is required (Evans,

et al., 2009, p. 242). All the participants of the groups are acknowledged by everyone and strongly linked to each other (Evans, et al., 2009, p. 242). Additionally, each of these members have similar preferences and knowledge, and their interconnectedness results from common consumption customs (Mercure, 2018).

One of the interests of this paper lies on social groups called primary groups (Evans, et al.,

2009, p. 242). Primary groups consist of people who have a contiguous relationship together, such as families (Evans, et al., 2009, p. 242). Being affected by these groups refers to a sub concept called reference groups, which have an impact on the consumer behavior (Bearden & Etzel, 1982;

Evans, et al., 2009, p. 242). The size of a reference group is a matter of consideration, as more minor groups can generate normative influence (Bamossy et al., 2006 cited in Mudondo, 2014).

These minor groups are frequently interacting and therefore have a more significant effect

(Bamossy et al., 2006 cited in Mudondo, 2014). Families and friends are indeed important influence on the behavior, and individuals are affected by the choices they make (Saluja, 2016).

This may be due the fact, that individual consumer perceives these groups as associative; indicating similar and pragmatic equals with them (Evans, et al., 2009, p. 243). Evans et al. (2009, p. 243) recognize that these associative reference groups may include co-workers and neighbors in addition to the friends, for instance.

2.4. CSR Activities

Nowadays, CSR reporting is facing an increase in demand (Kucharska & Kowalczyk, 2018) and firms are required to be more transparent in their activities (Ramesh, Saha, Goswami, & Dahiya,

2018). Being a socially responsible firm has become more popular and has developed in a sense

that it is more than being “trendy” or “up-to-date”. Most companies that wish to engage in public welfare are committing themselves to business activities that motivate changes in the society

(Ramesh et al., 2018).

According to Kim and Ferguson (2019), nowadays, the general public is watching businesses more critically, with skepticism and scrutiny. In turn, companies have incorporated

CSR strategies, and initiatives in order to establish themselves as ethical and responsible, to survive in a highly competitive economic environment (Kim, 2011; Kim & Ferguson, 2019;

Shahzad et al., 2020). Another tool of survival for companies these days, is to be meaningful and possess real value in which they can share with their stakeholders, customers and employees. This makes CSR a source to birth sustainability, competitiveness and innovation (Kucharska &

Kowalczyk, 2018).

CSR has transformed and is no longer viewed as a strategic move for competitive advantage but rather as a strategic necessity (Story & Neveas, 2015; McWilliams et al., 2006;

Uhlig et al., 2019; Kuokkanen & Sun, 2019). Many studies argue that CSR is ethical strategic efforts and practices, with a responsibility that goes beyond the firms’ interest. The purpose is to create value for an organization, with the hopes of having a positive effect on their stakeholders and society (Kim & Ferguson, 2019; Staudt, Shao, Dubinsky, & Wilson, 2014; Turker, 2009;

Ramesh et al., 2018; Kim & Choi, 2012; L’Etang, 1994).

Although many studies show that consumers have a positive attitude towards companies that are engaged in CSR activities, studies also show that CSR alone does not transfer or directly influence purchase intent (Öberseder et al., 2011; Lin et al., 2011). A study by Lin et al. (2011) indicates that although CSR activities are well established in a firm, CSR alone is not an 16

independent variable for improving the purchase intent. Anastasiadou et al. (2018) suggest that even though working with CSR practices in a firm has a positive impact on businesses, it is also dependent on other factors such as trust and affective identification.

There are many branches when it comes to CSR such as corporate identity which is connected to egoistic motives, economic welfare which are strategically driven motives, but also working with sustainable developments to contribute to local communities and society to improve quality of life (Wongpitch, Samart, Tipparat & Laohavichien, 2016; Pomering & Dolnicar, 2009;

Pérez & Rodriguez del Bosque, 2012). Literature also explains that CSR practices can either have intrinsic or extrinsic motives. Intrinsic motivated practices are viewed as more sincere practices.

They are proactive as companies usually engage in such activities because they care (Story &

Neveas, 2015). Intrinsic motives are often driven by non-financial intentions which perceive CSR as the benefit itself. It is separated from financial gains and benefits and motivated by ethical principles and moral philosophy (Graafland & Mazereeuw-Van der Duijin Schouten, 2012).

Proactive CSR activities have been connected to sustainability and its involvement in sustainable developments for the apparel industry. Sustainability and the emerge of the slow fashion movement have affected business strategy, work force engagement, business operations and connections to consumers and their communities (Pookulangara & Shepard, 2013). Moreover, engaging in slow fashion is engaging in proactive CSR practices since slow fashion incorporates aspects such as green fibers, using the latest technology to reduce waste and pollution, and taking into account the employees during the production process and the product throughout the entire supply chain. All which takes time, careful planning, commitment and sincerity, and are not motivated by financial gains or benefits (Pookulangara & Shepard, 2013; Graafland &

Mazereeuw-Van der Duijin Schouten, 2012). Moreover, proactive CSR is also related to doing a certain activity or something inherent for the fun, satisfaction and enjoyment of it rather than for another separate reason. These proactive tendencies will in turn positively affect the consumer behavior (Sleimi & Davut, 2015).

Extrinsic motivated CSR is viewed as performing activities for reactive reasons. CSR initiatives are done in order to get something back, avoid punishment or public backlash (Story &

Neveas, 2015). It is also related to meeting an exterior goal or to attain a separate outcome (Sleimi

& Duvaut, 2015). The most common motives for reactive CSR activities are financial benefits

(Wagner, Lutz, & Weitz, 2009). Some managers choose to engage in reactive CSR due to its influence on profits and the company’s long-term financial performance (Graafland &

Mazereeuw-Van der Duijin Schouten, 2012). Today, companies use CSR as a part of risk management or investments in social initiatives (Graafland & Mazereeuw-Van der Duijin

Schouten, 2012). However, this does not imply that these organizational practices are ineffective, bad for the community or the company (Story & Neveas, 2015).

2.5. Slow fashion and Sustainability

Slow fashion offers a new insight to connect fashion with sustainability (Jung & Jin, 2016).

Sustainability as a concept, emphasizes the environment of the earth and the state of it, but also the exploitation of the natural resources (Portney, 2015, p. 4). The core of sustainability is to reach a harmonic balance, without putting anyone living on the earth at risk (Portney, 2015, p. 4).

Sustainability among consumers is growing rapidly, thus people are aware of the hazards and critical toward fast manufacturing (Jung & Jin, 2016). The development of the concerns towards

environment and social aspects has guided slow fashion to challenge the fast fashion, which has been governing the modern industry (Sener et al., 2019; Hall, 2017). In a way, slow fashion acts as a mediator bringing together the fashion industry, social and environmental matters and the actors (Sener et al., 2019).

Sustainability and slow fashion are inseparable elements (Sener et al., 2019). In slow fashion, sustainability should be included throughout the whole production process (Sener et al., 2019).

The concept of CSR has had major contribution in the developments of the slow fashion movement. Moreover, in the sector of apparel and design, companies are frequently using sustainability as an umbrella term. This term incorporates environmental components such as proactive CSR practices which are important for future planning and consistency (Pookulangara

& Shepard, 2013). Instead of producing big scales for masses, slow fashion values good quality, sustainability, materials that are collected nearby and prolonged time in the production (Hall,

2017). Additionally, Fletcher (2010) recognizes durability, classic style for design and production ways that align with the traditional customs to be often connected to slow fashion but criticizes these definitions to be more for the media of fashion. Fletcher (2010) reminds slow fashion not to be a counter to fast fashion, they should be seen as two different insights to look at the world. The overall goals of slow fashion are to decrease the amount of waste and motivate consumers to buy less (Hall, 2017). Thus, slow fashion desires to look further from trends and focuses on the longevity (Sener et al., 2019). That makes the equilibrium the core of the slow fashion (Ertekin &

Atik, 2014).

As the main objective of slow fashion is to decrease waste, it has been studied how consumers themselves deal with the issue (Hall, 2017; Weber, Lynes, & Young, 2016). Weber et al. (2016)

distinguish some of the activities that are related to fashion waste; reusing, reselling, donations, disposals, swapping and taking backs for instance. In addition to these waste options, the role of second-hand stores has also received a stronger footstep in the market (Gopalakrishnan &

Matthews, 2018). The information technology development has influenced the “sharing economy”, which strongly connects with the second-hand markets existing online (Hamari et al.,

2016 cited in Gautami, Bharadhwaj, & Suganti, 2018). By the effect of this “sharing economy”, people have also been inspired to start renting their clothes and making business out of it

(Florsheim, 2018).

Regardless of the appearance of slow fashion (Jung & Jin, 2016), the concept itself is not necessarily familiar to all consumers (Tama, Encan, & Öndogan, 2017). Tama et al. (2017) conducted a research to university students in Turkey and found out that nearly 80% of the participants did not possess the required amount of knowledge concerning slow fashion and were not aware of the concept. This may result from fashion industry’s lack of transparency; people may not comprehend how environmental aspects are connected to it (Beard, 2008; Ertekin & Atik,

2014)

2.6. Purchase Intent

Purchase intent refers to the probability of a consumer to buy a specific product or service, in an online setting or in a physical store (Wu, Wu, Lee, & Lee, 2015). Consumers will most likely purchase from a brand if they believe that it offers the right product quality combined with the right features (Wu et al., 2015). Therefore, Wu et al. (2015) argue that purchase intent is a combination of a consumer’s interest in buying a product and the possible action of doing so. Many

scholars such as (Cases, Fournier, Dubois, & Tanner, 2010; de Canniere, de Pelsmacker, &

Geuens, 2009; Wu et al., 2015) state that there is a strong and positive relationship between attitudes and preferences towards a brand or product and the purchase intent. Meaning, when measuring the purchase intent of a consumer, the future purchase behavior is dependent on their attitudes (Wu et al., 2015). Moreover, an increase or decrease in purchase intent will often occur after careful product evaluation from the consumer (Younus, Rasheed, & Zia, 2015). The process to buy a product or a brand can be affected by several other factors such as product price, packaging, design of a product, product knowledge, celebrity endorsements, fashion trends and the opinion of family and friends (Younus et al., 2015).

Consumer trust towards a brand is also considered to be an important contributing factor towards purchase intent (Park & Kim, 2016; Tong & Su, 2018). Trust has been argued to be a crucial element for a positive outcome in marketing and branding that include brand loyalty, retention of consumers and purchase intent (Tong & Su, 2018). Today, consumers are keen not only to purchase from brands they trust and have a relationship with, but also a brand that aligns with their ethical standards. Although consumers are leaning towards making more ethical purchases, studies show that ethics are not the most important factor that control purchase decisions. A consumer’s primary focus is still the aspects that have been previously mentioned which are price, product and the brand (Deng, 2010). But also, other factors such as brand recognition, brand trust and the attitude towards the brand (Deli-Gray et al., 2012).

2.7. Online Shopping

Over the past decade, the trend of online purchases has increased in popularity, which has triggered an increase in competition between firms (Akroush & Al-Debei, 2015). In a study by ECC-Net in

2004, approximately 20.4% of people had purchased goods and services online. By 2014, the percentages had increased with more than double to roughly 50.2% (Hunter & Wilson, 2015).

Online shopping purchases are purchases that are conducted through an electronic device or system and can unlike a usual marketplace not be restricted by physical distance (Anastasiadou et al.,

2018). According to the World Internet Usage & Population Statistics, almost half of the world’s population (51.7%) claim that they are regular internet users (World Internet Usage & Population

Statistics, 2017). Being in an online shopping setting allows the consumers to decrease their decision-making efforts due to the provision of product comparison and information screening

(Park & Kim, 2003). Because the internet is capable of providing a huge amount of information, the consumers can cut the costs of information research and efforts in making purchase decisions

(Park & Kim, 2003).

In a study by Statista, apparel is the largest category in fashion in e-commerce and it is estimated that by the year 2024 to have revenue over US$640 billion (Statista, 2020b). For the past years, the internet has become the main or a complementary sales channel for many retailers

(Kawaf & Tagg, 2012). Fashion and e-commerce have shifted from a simple combination between an online and an offline store to offering an integrated, smoother and convenient shopping experience for consumers online (Statista, 2020a). A study by ANEC in 2015 shows that people in Europe tend to do less cross-border shopping and are keener to buy products or services from online retailers that originate from the country they live in. 26% buy products or services online

several times a month, 23% buy about once a month and 10% engage in online purchases weekly

(ANEC, 2015).

However, due to the increased popularity of digitalization and internet usage a 700 million

EUR increase in cross-border online shopping is estimated to occur by the year 2020 (Wagner,

Schramm-Klein, & Schu, 2016). In a report by e-commerce Europe, it is showcased how important e-commerce is to the EU economy as it accounts for 6.4% of all retail purchases in Europe with approximately 331 million consumers shopping online (Hunter & Wilson, 2015). Overall, the literature regarding the online setting has divided online shopping into two themes. One is focusing on the relationship between online shopping and trust, and the second theme is focused on its cognitive effects and emotion. No matter the theme, this trend has online vendors actively seeking to reach customers beyond the borders of their domestic markets and to expand their target groups

(Kawaf & Tagg, 2012; Safari, Thilenius, & Hadjikhani, 2013; Anastasiadou et al., 2018).

3. Hypothesis Development

Nowadays, many firms are choosing to engage in proactive CSR activities as studies show that it produces positive consumer responses (Groza, Pronschinshe, & Walker, 2011; Becker-Olsen,

Cudmore, & Hill, 2006; Ricks, 2005). A study by Becker-Olsen et al. (2006) reveals that proactive

CSR initiatives and activities are positively viewed by consumers which in turn will lead to an increase in consumers’ purchase intent. If firms wish to engage in proactive CSR activities, they must set a side time for careful planning and consideration. This is viewed as sincere and honest from the customers which has a positive effect on purchase intent. Moreover, proactive CSR have value-driven and strategic-driven attributes and are viewed as favorable amongst consumers and will have a positive effect on purchase intent (Groza et al., 2011). While several firms choose to engage in proactive CSR, many have chosen to adopt CSR initiatives as a reactive strategy after an irresponsible behavior have been revealed or if a firm is in a crisis (Ricks, 2005). Generally, consumers have a negative attitude towards reactive CSR activities (Becker-Olsen et al., 2006;

Wagner et al., 2009), because they are viewed as insincere and forced and are usually set in motion after pressure from the stakeholders (stakeholder-driven motives) (Groza et al., 2011). It is important when introducing CSR initiatives to be aware of the timing and the state in which the company is in during such introduction (Rim & Feurgerson, 2017). Since reactive CSR usually occurs when protecting the image of a company, or when avoiding public scrutiny and backlash.

Consumers are now becoming more skeptical and tend to wonder about the underlying reasons for firms’ CSR actions. If consumers believe that ulterior motives from the firm exists, it will result in a negative evaluation process of the firms’ sincerity in their CSR activities and therefore have a

negative effect on purchase intent (Story & Neveas, 2015; Rim & Feurgerson, 2017; Groza et al.,

2011; Becker-Olsen et al., 2006; Folse, Niedrich, & Grau, 2010). With the information provided above the first two hypotheses are formulated as follows:

H1: Proactive CSR activities have a positive effect on purchase intent when buying fashion online

H2: Reactive CSR activities have a negative effect on purchase intent when buying fashion online

Previous research indicates that attitudes affect the behavior of individuals (Mathew, 2016;

Ajzen & Fishbein, 2000) and drive people to behave in designated ways (Evans, et al., 2009, p.

105). Consequently, many studies show that attitudes affect the online shopping intentions

(Huseynov & Yildirim, 2014; Lin, 2007; Hasbullah et al., 2016; Cho, 2004; Suki & Suki, 2017).

According to Belleau et al. (2007) attitudes can cultivate the consumers’ purchase intent especially when the attitudes are positive. Thus, it can be examined that online purchase intent and the attitudes toward online buying are positively interconnected (Hasbullah et al., 2016). Therefore, the third hypothesis is formulated as follows:

H3: Positive consumer attitudes towards buying fashion online will increase the purchase intent

Additionally, this study was also interested in the attitudes towards buying second-hand fashion in an online setting and reusing timeless items and how such attitudes effects the purchase intent. The core value of slow fashion is to cut down the waste, and therefore researchers have attached more attention towards consumers’ way to manage with the issue (Hall, 2017; Weber et al., 2016). Weber et al. (2016) recognize that for example reselling and reusing are some of the activities the consumers are interested in. When it comes to timeless fashion a study by Watson and Ruoh-Nan (2013) highlights that consumers who are into slow fashion value timeless clothing

in order to obtain a durable wardrobe. The authors (2013) refer activities to such buying diverse and well-fitted clothing, but also fashion that is good quality and consistent with the already owned clothes as “slow fashion purchases”.

Continuously, Gopalakrishnan and Matthews (2018) explain that secondhand stores are increasingly obtaining attention in the markets. Secondhand as a term is referring to fashion clothing that is already worn and used, and it does not consider the fashion items’ age (Cervellon,

Carey, & Harms, 2012). Cervellon et al. (2012) examined that consumers are interested in secondhand mainly due economic reasons and indirectly due environmental matters. Despite the increasing attention towards secondhand stores (Gopalakrishnan & Matthews, 2018), consumers may not be fully committed to purchase second-hand fashion (Cervellon et al., 2012). Moreover,

Xu, Chen, Burman and Zhao (2014) add the online aspect and explain that in their study of US and Chinese students, neither of the respondents were highly interested in buying second-hand fashion online. Based on these researches, there seems to be an overall interest towards second- hand stores, but not necessarily a high intention to buy it online (Gopalakrishnan & Matthews,

2018; Xu et al., 2014). Based on the previous information, the fourth hypothesis is presented as follows:

H4: The attitudes towards slow fashion purchases affect purchase intent

Earlier research indicates that social groups have an effect on a persons’ behavior when consuming fashion (Saluja, 2016). Saluja (2016) examines that consumers are keen on shopping together with their family and friends and are affected by the choices made by these actors.

Continuously, Etherington (2018) argues that fashion choices emerge from the behavior of social peers. These studies are supported by Gershman, Pouncy and Gweon’s (2017) statement that in 26

general, other individuals can affect consumers’ decisions to choose certain products. Customers can lure other consumers and shape their choices (Gershman et al., 2017). Belleau et al. (2007) add that influence can also come from sources such as media and social status. By the reflection of these elements, it can be concluded that primary and associative groups, i.e. social groups, affect consumers fashion choices, i.e. the purchase intent (Saluja, 2016; Etherington, 2018; Gershman et al., 2017; Evans, et al., 2009, pp. 242 - 243). They are both strongly connected with the behavior and choices of the consumers (Evans, et al., 2009, pp. 242 – 243; Saluja, 2016; Etherington, 2018), thus the fifth and final hypothesis is formulated as follows:

H5: Social groups affect consumers’ fashion choices

3.1. Conceptual Model

For this study, the conceptual framework presented will be inspired by the Theory of Reasoned

Action model (see Figure 1 p. 12). However, in the modified version of the TRA framework the variable of CSR will be added. Conceptualization is the process of developing a model, while doing so it is important to keep in mind two types of variables–independent and dependent. The independent variable which is the performance variable has a measurable characteristic which in turn will affect, influence or explains the dependent variable. The dependent variable is referred to the variable that needs to be understood, explained or predicted (Hair, Celsi, Money, Samouel,

& Page 2011). In this study the conceptual model will have three concepts divided into five independent variables; proactive and reactive CSR, consumers’ attitude towards buying fashion online, consumers’ attitude towards buying slow fashion items online and social groups and one dependent variable which is the purchase intent. During a consumers’ decision-making process,

the attitude towards a behavior is proven to be a direct indicator of the behavioral intention (Zhang

& Kim, 2013). Therefore, in this model attitudes are divided into two concepts; the consumers’ attitudes towards purchasing slow fashion online and the consumers’ attitudes towards buying fashion online.

Previous literature also suggests that companies engage in CSR practices for various reasons that are either intrinsic for proactive purposes or extrinsic that are based on reactive motives (Story & Neveas, 2015). This explains why in this model the authors have divided CSR into the two branches–proactive and reactive. A person’s decision on their fashion choices or other forms of behavior can be influences by various sources such as family, friends, media, social status and other customers or even strangers (Belleau et al., 2007; Saluja, 2016; Gershman et al., 2017).

Therefore, in this study, the conceptual model will measure how social groups also referred to as primary groups (Evans, et al., 2009, p. 242) effect a person’s purchase intent. Previous literature regarding TRA have suggested that behavioral beliefs (attitudes) and subjective norms (normative) together influence a consumers’ behavioral intention (Ramayah et al., 2003; Madden et al., 2007;

Belleau et al., 2007). See Figure 2 below for a detailed illustration of the conceptual model.

Figure 2: Conceptual Model

4. Methodology

4.1. Philosophical choice

Positivism was selected as the choice of the philosophy for this paper. This paper was dedicated to obtain facts that are based on measurement and numerical forms and aimed to forecast and reason causality (Saunders, Lewis, & Thornhill, 2019, p. 144). This study researched consumers and how their online shopping behavior is affected by different variables. Positivism allowed this paper to test the Theory of Reasoned Action, in order to construct laws, or generalizations which remind of laws (Bryman & Bell, 2015, pp. 27-28; Saunders, et al., 2019, p. 144). Followingly, these constructed laws were evaluated by the five hypotheses, that are presented in previous chapters (Bryman & Bell, 2015, p. 28). All these activities were performed in order to provide this research admissible knowledge (Saunders, et al., 2019, p. 144). The objective was to test the theory and see if there are generalizable elements discovered. The sample that was collected is further explained in the following chapters, but it is necessary to state, that the sample of this research was relatively high, which supported the decision of adapting positivism (Saunders, et al., 144). Finally, the researchers of this paper remained neutral when it comes to what this research is studying (Saunders, et al., 2019, p. 144). The researchers did not take part of the research in that sense and remained impartial throughout. Continuously, the researchers were objective towards what was being studied (Saunders, et al., 2019, p. 144).

The decision of having positivism as the choice of the philosophy was based on the functionality it offers to this research; it allowed the paper to use measurements, test the theory

and exploit five hypotheses to test the generalizations, in order to gain knowledge. Moreover, the positivism enabled the paper to use a large sample, consisting of many consumers to be able to explain and prognosticate. (Saunders, et al., 2019, p. 144; Bryman & Bell, 2015, pp. 27-28).

4.2. Evolution of the Theory

Deductive method is commonly connected with positivist studies (Saunders, et al., 2019, p. 144).

Deductive insight allowed this research to use the Theory of Reasoned Action as a foundation for the whole study (Ghauri & Gronhaug, 2010, pp. 15-16). The theory was utilized to build the hypotheses of this paper, which together were the primary elements of the whole research (Ghauri

& Gronhaug, 2010, pp. 15-16). This study desired to evaluate whether the chosen theory and hypotheses are accepted with logical rationalization and this permitted the research to forecast and explain what was found (Ghauri & Gronhaug, 2010, pp. 15-16; Saunders, et al., 2019, p. 144). The motive of the paper was to explain the effect of CSR when shopping fashion online, and this was tested with the Theory of Reasoned Action and the five hypotheses. Whether the hypotheses were accepted or rejected, the study was able to reason how attitudes, normative factors and CSR impact on consumers and their purchase intent (Ghauri & Gronhaug, 2010, pp. 15-16).

4.3. Quantitative Approach

To effectively follow the previous decisions, the paper conducted a quantitative study (Saunders, et al., 2019, p. 144). Quantitative approach aligns with the previously mentioned positivism and deductive insight (Saunders, et al., 2019, p. 144). Quantitative method as an approach emphasizes testing and auditing, which suited well to the nature of the study (Ghauri

& Gronhaug, 2010, p. 105). As mentioned earlier, it was the motive of this paper to obtain facts and to be able to generalize, thus quantitative insight was found suitable as they are both characteristics to it (Ghauri & Gronhaug, 2010, p. 105). Quantitative approach is often focusing on results and controlled-based measuring, and therefore perceived efficient for this paper (Ghauri

& Gronhaug, 2010, p. 105).

Furthermore, in quantitative method, variables and respondents are commonly included

(Saunders, et al., 2019). This paper recognized all the participants as respondents and simultaneously examined complex dynamics between the variables (Saunders, et al., 2019, p. 178;

Hair, et al., 2011, p. 134). In order to do so, this research was conducted with a mono-method quantitative style which generates to standardized and numerical form of data (Saunders, et al.,

2019, p. 178). Mono-method refers to utilizing one technique for collecting the data (Saunders, et al., 2019, p. 179).

4.4. Data Collection

Primary data was collected for this paper in order to obtain accurate and necessary information specifically for this research (Ghauri & Gronhaug, 2010, p. 99). Primary data was aligned with the desired objectives of this papers and was needed to collect knowledge from the respondents themselves (Ghauri & Gronhaug, 2010, p. 99). To reach that required data, this paper conducted a joint survey together with a research team at Mälardalen University in Västerås, Sweden (Ghauri

& Gronhaug, 2010, p. 99). This research team consisted of six master’s students in the International

Marketing programme and two academic researchers from Mälardalen University and Örebro

University. The survey was constructed by the researchers as part of their own research project, in

which the authors of this study took part. Therefore, the role of the researchers was to construct the survey. The other members of the research team assured that the chosen question items were coherent and suitable with the objectives of each individual study. The survey was conducted with a questionnaire, which was completed by the respondents personally (Ghauri & Gronhaug, 2010, p. 99; Bryman & Bell, 2015, p. 239). For the convenience matter, the survey was held online, and sent to respondents via email, text -messages, social media channels, LinkedIn and other platforms.

The objective of these various channels was to gain diversity and reach people globally

(Anastasiadou et al., 2018).

In the questionnaire the assistance of closed questions was primarily used (Bryman & Bell,

2019, p. 246; Ghauri & Gronhaug, 2010, p. 122). To simplify the data analysis, the questionnaire included a Likert scale with scores from 1 – 7, and additionally “Don’t know” (Pallant, 2013, p. 9;

Bryman & Bell, 2019, pp. 246-247). In the survey, 1 represented “Totally disagree” and score 7

“Completely agree” and “Don’t know” indicated the value of 0. Alternatively, in one question, 1. was equal with “Not at all important” and 7. “Very important”, with the addition of “Don’t know” as an option with the score of 0. Moreover, the questionnaire included a question where the respondents were asked whether they know what slow fashion as a term means. This was executed with a vertical format, with following options; “Yes”, “No” or “Don’t know” (Bryman & Bell,

2019, pp. 246-247). Additionally, the questionnaire included demographic questions, to obtain information about the respondents (Anastasiadou et al., 2018). The age, gender, nationality, highest level of education and profession was asked (Bryman & Bell, 2019, p. 514; Selmer &

Lauring, 2011).

4.5. Sample

This research had an interest in understanding global consumers and their behavior. Therefore, the aim of the sample was to reach as many international people as possible in the given time (Ghauri

& Gronhaug, 2010, p. 140). In order to reach this segment (Ghauri & Gronhaug, 2010, p. 140), non-probability sampling was utilized by the all eight members of the research team (Saunders, et al., 2019, p. 318). More specifically, the tactic for collecting answers was the snowball technique, which is based on using volunteers (Saunders, et al., 2019, p. 318). The technique allowed the team to connect with global consumers who reflected the desired sample (Anastasiadou et al.,

2018). All members of the research team used this specific technique which included that everyone either personally contacted other individuals via different channels or shared the survey link on

LinkedIn or similar platforms (Anastasiadou et al., 2018). The respondents were asked to comment/like when the survey was completed and reminded later, if they had not given any signal of answering (Anastasiadou et al., 2018). Moreover, the respondents were informed that they can re-share the survey link and help the researchers to have more answers.

Altogether, the research team obtained collectively 717 answers from the survey. However, one answer was taken off making the total number of answers 716. The survey was also widely international, including people from 59 different countries. Overall, most of the people who were contacted regarding to participating the survey took part in it. A big majority of the answers came from Sweden (32%), Mexico (14%), Netherlands (13%). Also, countries such as Finland, America and Spain were well presented. When it comes to the demographics and specifically the age, the largest category was respondents born between 1980 to 1999, with the percentage of 79.9%.

Moreover, majority of the respondents, 69.5% were women. The biggest number of respondents 34

were students (31.2%) or working in a company (37.4%), and over a half acclaimed to have a university undergraduate level as their highest level of education. Additionally, the survey asked whether the respondents are familiar with the slow fashion term. According to the questionnaire, most respondents were not familiar with it. More detailed descriptions of the demographics can be found in Appendix, see Tables 4 - 9. (Bryman & Bell, 2019, pp. 242 & 514; Selmer & Lauring,

2011; Anastasiadou et al., 2018).

4.6. Operationalization

The majority of the question items used were inspired by existing literature with some alterations in order to be coherent with the study. More specifically, the question items in this survey were based on previous studies, which in turn were founded from already existing measures for those items. Reactive CSR was measured by using four different question items. The first two items measured if it was important that the company the consumers buy from online make good quality products and are transparent with how the products are produced. The other two items measured the importance of CSR; whether the firm is ethically or sustainably certified, or transparent about their CSR practices. These question items were inspired by Wongpitch et al. (2016); Pomering and

Dolnicar (2009); Pérez and Rodriguez del Bosque (2012); Ramesh et al. (2018); Kim (2011); Kim and Ferguson (2019) and Shahzad et al. (2020). Proactive CSR was measured by using three items.

These items measured the importance of CSR, whether the firm is consistent with their CSR practices, protect the environment or contribute to local community developments. These question items were inspired by Pookulangara and Shepard (2013); Graafland and Mazereeuw-Van der

Duijin Schouten (2012) and Ramesh et al. (2018). Followingly, social groups were measured by

using three items. These items measured the factors that can influence a persons’ fashion choices.

It included the opinion of family, friends and colleagues (i.e. school, work). The items regarding social groups were inspired by Evans et al. (2009, p. 242 & 243) and Saluja (2016).

The next construct about consumers’ attitudes towards buying fashion online had three items that were inspired by Anastasiadou et al. (2018), Beldad, Hegner and Hoppen (2016) and

Hausman and Siepke (2009). These items measured the attitude towards the intention of future purchases. The next construct that was measured was the consumer attitudes towards buying slow fashion items online. These question items were inspired by Cho, Gupta and Kim (2015). These items measured whether a person is interested in purchasing second-hand fashion, fashion items that are timeless, if they don’t mind wearing fashion items for many years or reuse clothing in order to make the most out of them.

The following constructs: reactive CSR, proactive CSR, social groups, consumer attitudes towards buying fashion online and consumer attitudes towards buying slow fashion items online are all independent variables. The dependent variable, which is purchase intent, was measured by using two question items. These question items were inspired by Anastasiadou et al. (2018). The two question items asked the respondent about the intention to keep buying garments from the online retailers they buy from today, or if they intent to buy from new fashion retailers in the future.

All question items were inspired and rephrased by a combination of multiple studies in order to fit the purpose of the thesis. Moreover, all question items were measured by using a scale that ranged from 1 to 7. 1 being the equivalent to “Totally disagree” and 7 equaling to “Completely agree” with an eighth and final option of “Don’t know”. For a full visualization of the operationalization table, see Table 15 in Appendix.

4.7. Data Analysis

The data for this research was analyzed with SPSS (Hasbullah et al., 2016). As this research exploited the format of closed questions, it enabled an efficient SPSS analysis (Pallant, 2013, p.

8). The data analysis was guided through following steps; firstly, the researchers looked for possible errors (Pallant, 2013, p. 28). Secondly it was necessary to review the data with descriptive statistics, in order to reflect the sample’s characteristics (Pallant, 2013, p. 55). Finally, the third step required performing various analyses with correlation and regression (Pallant, 2013, p. 28).

Primarily, the researchers were obliged to go through the values that are not adequate, this means searching for codes outside the given values (Pallant, 2013, p. 45). Also, it was important to calculate the frequency distribution per variable (Ghauri & Gronhaug, 2010, p. 153; Pallant,

2013, pp. 46-47). After the previously mentioned parts were accomplished, the research evaluated the reliability (Pallant, 2013, p. 101). The reliability was measured by using the coefficient in

Cronbach’s alpha, which is concerned about the internal consistency of a scale (Pallant, 2013, p.

101). The objective was to reach the value of 0.70 or higher and to have an adequate internal consistency (Barutçu, 2007). However, Bryman and Bell (2015, p. 169) add that 0.8 is considered as an efficient value, but in some cases a smaller value can be equally approved. Taber (2017) measures Cronbach’s alpha by using various scales, such as one between 0.45 and 0.96 and another from 0.45 to 0.98. Those are considered sufficient and acceptable values for the Cronbach’s alpha

(Taber, 2017).

After the first steps, the study was able to start evaluating the relationships (Pallant, 2013, p. 28). When it comes to the relationships, the study was focused on evaluating the correlations,

with Spearman’s rho (Pallant, 2013, pp. 28 & 107). The correlation coefficient, “r”, is between +1 and -1 (Saunders, et al., 2019, p. 615), and indicates whether two variables have a linear relation with each other (Wetzels & Wagenmakers, 2012). This analysis enabled to measure the strength of two variables and if their relationship is negative or positive (Pallant, 2013, p. 28). When the correlation is perfectly positive, the value must be +1, whereas -1 equals with a perfect negative correlation and results in with a negative linear relation (Saunders, et al., 2019, p. 615; Wetzels &

Wagenmakers, 2012). A value of 0 reflects that there is no linear relation to be found (Wetzels &

Wagenmakers, 2012).

Above this, a linear regression, i.e. a simple regression was applied (McCormick, Salcedo,

& Poh, 2015, p. 256; Pallant, 2013, p. 108). Simple regression is concerned to test one independent variable to one dependent variable (McCormick et al., 2015, p. 256; Pallant, 2013, p. 108). The regression enabled to detect a t-value, which dedicates if a chosen independent variable is significant and linked to the dependent variable (Silvia, Iqbal, Swankoski, Watt, & Bullard, 2014, pp. 114 & 116). Commonly, the t-value should be 2 and preferably bigger or equal with it (Silvia, et al., 2014, p. 116). This indicates a declining of a null hypothesis and that in turn shows statistical compatibility (Silvia, et al., 2014, p. 116).

Continuously, a p - value, which reports the statistical significance was measured (Sullivan

& Feinn, 2012). The p – value emerges in a scale of 0 to 1, where a value under .05 shows evidence that opposes the null hypothesis (Rumsey, 2015, p. 42). Saunders et al. (2019) align and explain that if the value is under .05, it is almost impossible that the measured coefficient would have emerged just by itself (Saunders, et al., 2019, p. 618). Followingly, Wetzels and Wagenmakers

(2012) support the value of .05 or smaller to be effective in declining the null hypothesis. This

generates to a rejection of the null hypothesis that an existing relation is not taking place (Wetzels

& Wagenmakers, 2012; Bryman & Bell, 2015, p. 360). In contrast, if the value is more significant than .05, this means the null hypothesis is unlikely rejected, as there is frail evidence to oppose the null hypothesis (Rumsey, 2015, p. 42). Sullivan and Feinn (2012) indicate that a p - value of .05 or bigger is effective in expounding differences with the guidance of the variability of the sample.

All in all, the null hypothesis reveals that there is no connection between two variables when reflecting the population (Bryman & Bell, 2015, p. 358). In general, p - value may require a relatively remarkable sample size, which will commonly lead to a significant difference (Sullivan

& Feinn, 2012).

4.8. Time Scale

This research followed the cross-sectional time scale. The paper focused on investigating a specific topic and was conducted in a clear timeframe. (Saunders, et al., 2019, p. 212). The research was conducted during November 2019 to June 2020.

4.9. Reliability and Validity

The overall quality and competence of this paper was evaluated with reliability and validity

(Saunders, et al., 2019, p. 213). In order to examine the reliability, Cronbach’s alpha was utilized

(Ebrahimi & Banaeifard, 2018). Reliability coefficient in Cronbach’s alpha enabled the authors to study the questionnaires’ reliability (Barutçu, 2007). Table 1 will introduce each construct and their Cronbach’s alpha values;

Table 1: Cronbach’s alpha values Construct Variable Cronbach’s alpha N of items Reactive CSR Independent .777 4 variable Proactive CSR Independent .902 3 variable Social Groups Independent .841 3 variable Consumers attitudes Independent .759 3 towards buying variable fashion online Consumer attitudes Independent .512 4 towards buying slow variable fashion Purchase intent Dependent .661 2 variable

As established in Table 1 the first construct “Reactive CSR” received a value of .777, dedicating efficient internal consistency (Bryman & Bell, 2015, p. 169; Barutçu, 2007). “Proactive

CSR”, “Social Groups” and “Consumer attitudes towards buying fashion online” continued with adequate values; .902, .841 and .759 and reached the required level of internal consistency

(Barutçu, 2007; Bryman & Bell, 2015, p. 169). However, the construct of “Consumer attitudes towards buying slow fashion” the Cronbach’s alpha coefficient reached the value of .512 and for the “Purchase intent” it was .661. Both values are under the acknowledged level of internal consistency (Barutçu, 2007), however the values are sufficient and acceptable according to Taber

(2017).

The validity in this paper was reflected through construct validity and content validity (Keller

& Kros, 2011) which are concerned about the measurement validity, i.e. does the measuring measure what was originally initiated (Saunders, et al., 2019, p. 213). This is known as the internal validity (Saunders, et al., 2019, p. 517). Firstly, to assure the construct validity, the paper chose a suitable theory for developing the hypothesis (Bryman & Bell, 2015, p. 171). The Theory of 40

Reasoned Action acted the base for the hypotheses and was evaluated to fit the nature of this research and what is being studied (Bryman & Bell, 2015, p. 171). More specifically, construct validity is concerned about correlations in connection with constructs’ measures and other different measures (Westen & Rosenthal, 2003). Thus, the research indicated correlations to prove the construct validity (Westen & Rosenthal, 2003). When it comes to the content validity, the research team together discussed and analyzed the questionnaire questions in advance (Saunders, et al., 2019, p. 517). This enabled the team to investigate each question in the questionnaire, and make sure they are suitable (Saunders, et al., 2019, p. 517).

4.10. Ethics

This study was conducted with a respect of ethical aspects during the entire process. Firstly, the research followed the norms of integrity and fairness. The objective was to be fully honest, transparent and accurate while conducting the study. These included restricting any deception or wrong presentation of the gathered information; such as the data and the findings. Moreover, the research was done with a respect of all respondents or others influenced by the research and any harmful effects were precluded. (Saunders, et al., 2019, p. 257). Privacy of all respondents was fully respected, and the data was preserved perfectly confidential (Bryman & Bell, 2015, p. 155;

Saunders, et al., 2019, p. 258). Moreover, the privacy included the anonymity of all who took part to the survey (Hair, et al., 2011 p. 61). Also, in the questionnaire it was stated that the interest of the research was not for commercial purposes (Saunders, et al., 2019, p. 257). Additionally, a concise introduction to the topic of the research was included (Bryman & Bell, 2015, p. 154).

4.11. Limitation

First limitation of this research is concerned of the age divergence of the respondents. Most respondents (79.9%) were born between 1980 – 1999. This may according to Anastasiadou et al.

(2018) affect negatively to the generalizability. Moreover, most respondents were women (69.5%), indicating that less men participated to the survey. When the awareness of the term slow fashion was asked, the results showed that most respondents did not know the meaning of the concept.

This could result in their answers regarding slow fashion; some participants could be acting according to slow fashion values and purchase fashion accordingly but may not be aware of the concept behind it. Continuously, according to the feedback of few respondents, it was noticed that the term CSR was also considered difficult to understand. Authors of this research received several observations in regard to the challenging vocabulary, which may have affected the final results.

This is leading to the following limitation concerning the self-administered surveys (Coughlan,

Cronin, & Ryan, 2008). It is examined that respondents may inquire help to fill out the survey or possibly let someone else to fill it (Coughlan et al., 2008). This can possibly affect the sample’s representativeness, even if the researchers of this study are not able to detect this (Coughlan et al.,

2008).

5. Analysis of the Findings

5.1. Regression

In the regression analysis, t – values for each independent variable were calculated, see the Table

2 (Silvia, et al., 2014). This value shows if the independent variables are in connection with the one dependent variable (Silvia, et al., 2014). According to Silvia et al. (2014) an adequate t- value is 2 or more significant. Firstly, “Proactive CSR” has a t – value of -.803, which is noticeably under the acceptable level (Silvia, et al. 2014). Aligning with that, “Reactive CSR” obtains a value of -1.547, also dedicating an insufficient t – value (Silvia, et al., 2014). However, “Consumer attitudes towards buying fashion online” – variable reaches the highest t – value of them all;

19.878. Followingly, the variable “Consumer attitudes towards slow fashion purchases” exceeds the acceptable level for the t- value with 2.288 along with “Social groups” with the t - value of

2.111 (Silvia, et al., 2014).

The significance values or p – values was followingly tested, see the summary of the results in

Table 2 (Sullivan & Feinn, 2012). “Proactive CSR” receives the value of .422, which is more significant than 0.05 and therefore the declining of the null hypothesis cannot be done (Rumsey,

2015, p. 42). “Reactive CSR” obtains a value of .123, it is over 0.05 and therefore the declining of the null hypothesis cannot either be performed (Rumsey, 2015, p. 42). These two constructs show frail evidence when it comes to opposing the null hypotheses, and this leads to an unsuccessful rejection (Rumsey, 2015, p. 42). Respectively “Consumer attitudes towards buying fashion online” reaches the p – value of .000 and supports the null hypothesis’ rejection (Rumsey, 2015, p. 42;

Wetzels & Wagenmakers, 2012). “Consumer attitudes towards slow fashion purchases” has the value of .022, also under the critical point of 0.05, and shows suitable evidence in the data that can decline the null hypothesis (Rumsey, 2015, p. 42; Wetzels & Wagenmakers, 2012). Finally, the

“Social Groups” receives a p - value of .035, and therefore opposes the null hypothesis with an adequate evidence (Rumsey, 2015, p. 42).

Table 2: Hypothesis Testing Results

Hypothesis t-value Significance Result H1: Proactive CSR -.803 .422 Not supported activities have a positive effect on purchase intent when buying fashion online H2: Reactive CSR -1.547 .123 Not supported activities have a negative effect on purchase intent when buying fashion online H3: Positive consumer 19.878 .000 Supported attitudes towards buying fashion online will increase the purchase intent H4: The attitudes towards 2.288 .022 Supported slow fashion purchases effect purchase intent H5: Social groups affect 2.111 .035 Supported consumers’ fashion choices

5.2. Correlations

In order to check the correlations between the constructs the Spearman’s rho test was used (see the

Table 3). We found out that the correlation between consumer attitudes towards buying fashion online and purchase intent are significant at the 0.01 level with a coefficient of .599**. This implies

that these two variables have a linear relationship with each other (Wetzels & Wagenmakers,

2012). Meanwhile, social groups and consumer attitudes towards slow fashion purchases are significant at the 0.05 level, with coefficients of .084* and .088* which also implies that there is a positive relationship between those constructs and purchase intent. When it comes to proactive

CSR and the relationship it has with the purchase intent, the coefficient is -.044 which shows a negative relationship. The fifth correlation measured was between reactive CSR and purchase intent which has a coefficient of -.073 which also implies that there is a negative relationship between the two constructs (Saunders, et al., 2019, p. 615; Wetzels & Wagenmakers, 2012). The correlations for the items within each construct were also measured, and those results can be found in Tables 10-14 in Appendix.

Table 3: Correlation Matrix of Constructs

Independent Variable Dependent Variable Correlation Proactive CSR Purchase Intent -.044 Reactive CSR Purchase Intent -.073 Consumer attitudes Purchase Intent .599** towards buying fashion online Consumer attitudes Purchase Intent .088* towards slow fashion purchases Social Groups Purchase Intent .084* *. Correlation is significant at the 0.05 level (2-tailed)

**. Correlation is significant at the 0.01 level (2-tailed)

6. Discussion

The objective of this study was to investigate the effect CSR, social groups and attitudes have on consumers’ intentions to purchase fashion online. More importantly, how can CSR affect consumers’ intentions to purchase fashion in an online setting. Previous literature emphasizes that intrinsic motivated CSR practices are proactive, and firms engage in such activities because they care and are motivated by non-financial benefits (Story & Neveas, 2015). Previous research also indicates that proactive CSR activities generate positive consumer responses which in turn will increase purchase intent (Groza et al., 2011; Becker-Olsen et al., 2006; Ricks, 2005). The Theory of Reasoned Action was used as a basis in order to develop the conceptual model. TRA was found to be accurate to this study due to previous research demonstrating its usefulness in explaining the persons’ behavioral intention to purchase an item (Belleau et al., 2007; Omar & Owusu-Frimpong,

2007; Tsai, Chin, & Chen, 2010; Dodd & Supa, 2011; McClure & Seock, 2020).

The attitude perspective of the Theory of Reasoned Action was measured with H3. The independent variable “Consumer attitudes towards buying fashion online” was constructed in order to evaluate consumers attitudes when it comes to online shopping. The significance and t - value emphasize that this variable is supported, based on a high t-value (19.878) and an adequate p – value (.000). Thus, the opposing of the null hypothesis is successful (Rumsey, 2015, p. 42; Wetzels

& Wagenmakers, 2012; Silvia, et al., 2014). This verifies a relationship between positive consumer attitudes and an increase in purchase intent (Wetzels & Wagenmakers, 2012; Bryman

& Bell, 2015, pp. 358 & 360). Respectively, this relationship aligns with the Theory of Reasoned

Action, which suggests that attitudes towards a certain behavior are indeed a foundation for the

individuals’ behavioral intent (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al., 2007).

The role of positive attitudes is confirmed to be affectual towards the purchase intent and online fashion purchasing by the respondents of the survey. Moreover, this relationship follows the findings of the previous research; for example, Belleau et al. (2007) recognize positive attitudes to be a source to an increasing purchase intent (Belleau et al., 2007). Followingly, many other studies identify the impact of attitudes in online buying intentions and comply with this finding (Huseynov

& Yildirim, 2014; Lin, 2007; Hasbullah et al., 2016; Cho, 2004; Suki & Suki, 2017). (Belleau et al., 2007).

The following hypothesis H4 was structured in order to study the variable “Consumer attitudes towards buying slow fashion items online”. This variable was followingly studying the attitudinal perspective of the Theory of Reasoned Action and more specifically the attitudes towards slow fashion purchases (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al., 2007). As seen in the previous chapter, both the p – value (.022) and the t – value (2.288) was adequate and therefore the null hypothesis was opposed (Rumsey, 2015, p. 42; Wetzels & Wagenmakers, 2012; Silvia, et al., 2014, p. 116). These values show that here is a positive relationship between attitudes towards slow fashion purchases and the purchase intent (Wetzels & Wagenmakers, 2012; Bryman & Bell,

2015, pp. 358 & 360). Again, this relationship aligns with the Theory of Reasoned Action, and supports that attitudes affect the consumers intention towards a behavior, in this case the purchase intent (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al., 2007). Previous research shows that people are affected by their attitudes and this aligns what was also found in this study (Mathew,

2016; Ajzen & Fishbein, 2000). It can be established that the consumers’ attitudes towards slow fashion purchases, i.e. second-hand purchasing online, shopping timeless items and reusing have

an effect on the purchase intention (Weber et al., 2016, Watson & Ruoh-Nan, 2013;

Gopalakrishnan & Matthews, 2018; Xu et al., 2014). Thus, when consumers are considering buying for example timeless clothes or second-hand through online, their own attitudes towards doing so are an important attribute for the behavioral intent (Zhang & Kim, 2013). Slow fashion purchases and the purchase intent towards them are a result of a decision-forming process of the consumer and guided by their attitudes (Zhang & Kim, 2013).

The study examined the fifth hypothesis with the variable “Social Groups”. The Theory of

Reasoned Action examines that subjective norms are a foundation for individuals’ behavioral intent and indicates the individuals’ own perceptions towards social influence (Ajzen & Fishbein,

1980; Madden et al., 2007; Belleau et al., 2007). Therefore, the variable “Social Groups” was chosen, as the interest was in understanding the effect of social influence to consumers’ purchase intent. Much like the previous hypotheses, the fifth hypothesis is supported with the p – value

(.035) and t -value (2.111). The results indicated a relationship between social groups and the purchase intent (Rumsey, 2015, p. 42; Wetzels & Wagenmakers, 2012; Silvia, et al., 2014, p. 116;

Bryman & Bell, 2015, pp. 358 & 360). In the Theory of Reasoned Action, the role of the subjective norm is distinguished to be effective in guiding the behavioral intent, and this finding effectively follows the concept of the theory (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al.,

2007). Consequently, the way consumers perceive the social influence and the pressure strongly effects the purchase intent (Ajzen & Fishbein, 1980; Madden et al., 2007; Belleau et al., 2007), thus the sample of this research confirms being influenced by their social groups in relation to their purchase intent. Moreover, previous studies indicate similar results. For example, Saluja (2016) examines consumers to be inclined to shop with their closest friends and family and are influenced

by them. Followingly, Etherington (2018) supports and claims consumers’ fashion choices are indeed resulting from social peers and their behavior. Therefore, it can be established that consumers tend to be affected by their social groups which in turn effects their fashion purchasing online.

Previous research suggests that firms applying proactive CSR practices should generate a positive consumer response, our findings indicate differently. With a less significant p–value

(.422) and a negative t-value (-.803). The findings show that the first hypothesis “Proactive CSR activities have a positive effect on purchase intent when buying fashion online” is not supported.

It cannot be stated that proactive CSR necessarily has a negative effect on purchase intent but according to this study’s sample, proactive CSR does not have a positive effect on purchase intent in an online setting.

Despite the fact that companies usually engage in proactive CSR activities, many firms are choosing to use CSR as a reactive strategy (Ricks, 2005). Previous research such as (Becker-Olsen et al., 2006; Wagner et al., 2009; Groza et al., 2011) suggests that consumers usually have a negative attitude towards reactive CSR since it is viewed as insincere or forced and is mostly set in motion due to stakeholder pressure. Research also points out that firms receive a negative consumer response from their reactive CSR activities because they are preformed to avoid public backlash, to gain something and to protect the image of a company which negatively affect a consumers’ purchase intent (Story & Neveas, 2015; Rim & Feurgerson, 2017; Groza et al., 2011;

Becker-Olsen et al., 2006; Folse et al., 2010). The findings of this study regarding reactive CSR do not align with previous research which states that reactive CSR has a negative effect on the purchase intent. With a less remarkable significance (.123) and a negative t – value (-1.547), H2

is not supported. According to the sample of this study, reactive CSR does not have a negative effect on purchase intent. However, this does not imply that reactive CSR necessarily has a positive effect on purchase intent.

Our findings regarding proactive and reactive CSR have shown to contradict what previous studies says about their effect on purchase intent. Studies show that there are many branches to

CSR (Wongpitch et al., 2016; Pomering & Dolnicar, 2009; Pérez & Rodriguez del Bosque, 2012), however, there are also other studies that show that engaging in CSR activities is not an independent variable that alone influences purchase intent (Öberseder et al., 2011; Lin et al., 2011;

Anastasiadou et al., 2018). However, no research to our knowledge has investigated the difference between the various CSR branches and whether one branch is superior in its influence on purchase intent. As proactive CSR and slow fashion are somewhat related and share similar values, the results of this study show that although the knowledge about slow fashion is low, the attitudes towards more sustainable purchases are positive.

7. Conclusion

The main focus for this study was to investigate how CSR can affect the purchase intent when buying fashion online. Hence, the proposed research question for this study; “How can CSR affect consumers’ intent to buy fashion online?” After conducting this study, results showed that CSR has a relatively low effect on purchase intent when buying fashion online. The sample of the study indicated that neither proactive nor reactive CSR have a remarkable impact on online fashion purchase intent. The findings emphasize that both CSR branches had the opposite effect on online purchase intent compared to what previous research indicates. Generally, reactive CSR has a negative effect on consumers’ purchase intent. However, the sample of this study indicated that reactive CSR in contrary to previous research may not have a negative effect on the purchase intent. When referring back to the Theory of Reasoned Action, the findings of this study align with the foundation of the theory. The theory suggests that, the base of an individuals’ behavioral intention lies in the attitudes towards the action and the perception of the subjective norms.

Therefore, other factors may not be triggering elements towards influencing a behavioral intent such as the purchase intent. This could explain why CSR in this case is not as effective as attitudes and subjective norms i.e. social groups.

TRA as a theory showed great applicability by indicating that consumers worldwide were mostly influenced by their attitudes and subjective norms, which not only followed the findings of the previous research but also emphasized the strength of the theory. When evaluating consumers’ behavioral intent, or as in this case the purchase intent, the reflection should start with the two components of the model which are efficient in explaining the consumers’ purchase intent when

they are buying fashion online. The theory enabled the research to build a model which combined various elements, and showed that besides the attitudes and subjective influence, consumers may not be strongly influenced. Especially when referring to the concepts of CSR and Slow Fashion.

Adding new elements to the model was not proven to be workable, and this only showed that the theory itself is somewhat explicit. Consumers were not influenced by the branches of CSR, despite what earlier studies may have emphasized. Thus, the model was only strengthening the components that already existed in the theory, not the new additions. CSR with both reactive and proactive branches needs to be studied by applying them directly either to the attitudes or subjective norms, which could lead to the most optimal exploitation of the Theory of Reasoned

Action.

Slow fashion was another aspect of this research. Interestingly most respondents did not have much previous knowledge about the term nor the concept. However, previous research show that people are more environmentally and sustainably conscious. Nevertheless, it may not affect their fashion choices when shopping online. This study contributes to existing research by challenging the role CSR has to consumers. Although, the sample of the study showed low interest towards proactive CSR, it does not take away its importance. The interconnectedness between slow fashion and proactive CSR is existing according to previous literature. However, proactive

CSR and slow fashion are not seen as two aspects that are part of the same concept. Perhaps proactive CSR activities can have a stronger influence on purchase intent if consumer learn to combine the two concepts together.

7.1. Future Research

For further research it is highly recommended to examine the differences and impact of the branches of CSR. CSR is commonly divided into reactive or proactive approaches, and it depends on the company how they decide to manage it. As seen in this research the respondents showed relatively low interest towards CSR activities. The findings were opposing the previous research and indicated that CSR activities may have various responses within the consumers. Therefore, it is important to continue studying how reactive and proactive CSR are actually perceived by the consumers. Researching further how consumers react to CSR and whether it effects the purchase intent is important, as many consumers may not respond similarly to what earlier studies suggests.

CSR itself is an important concept and increasingly adapted in businesses, thus the key element is to comprehend how consumers react to it and whether it has an influence on their behavioral intent.

Secondly, the concept of slow fashion was unfamiliar to most respondents which most likely explains the unawareness of the term. However, many people may still act based on the values of slow fashion, but without acknowledging it. Thus, could be ideal to continue investigating what kind of slow fashion values consumers have already adapted and study the behavior based on them.

Moreover, there were small number of respondents who answered being aware of the concept of slow fashion, so studying those consumers can bring more information and awareness to the concept. Understanding different consumer perspectives towards slow fashion can bring value to related studies and enable remarkable benefit for businesses, consumers and the planet.

Furthermore, this can enable the consumers to start connecting slow fashion with proactive CSR.

8. Managerial Implications

For managerial implications, this study recommends companies to focus on understanding the consumers. They are the foundation for any successful business and managers should emphasize customers in their decision - making. CSR in both reactive and proactive forms can bring benefit for companies, and it is the managers’ task to investigate what is the best branch for them. Thus, market research and getting information about the consumers’ perceptions of CSR is crucial and highly recommended. All in all, CSR is not anymore seen as a foundation for competitive advantage; it is strategically inevitable (Story & Neveas, 2015; McWilliams et al., 2006; Uhlig et al., 2019; Kuokkanen & Sun, 2019). In addition, as consumers are getting increasingly conscious and critical, adapting the correct CSR for the business is important and something that companies and managers cannot avoid to do.

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10. Appendix

Table 4: Nationality Percentage Swedish 32% Other 16% Mexican 14% Dutch 13% Finish 7%

American 5%

German 4%

Spanish 4%

No Answer 3%

English 2%

Scottish 1%

Table 5: Age Percentage 1980 – 1999 79,9 % 1960 – 1979 13.3 % 1959 < 3.1 % 2000 > 3.2 % Don’t Want to Say 0.4 %

Table 6: Gender Percentage Female 69,5 % Male 29,5 % Don’t Want to Say 1%

Table 7: Educational Level Percentage Undergraduate 54.3 % Postgraduate 27.2 % Secondary School 14.7 % PhD 2.6 % Don’t Know 1.2 %

Table 8: Occupation Percentage Company Employment 37.4 % Student 31.2 % Self-Employed 10.1 % Working Within Education 6.8 % Government Employee 5.9 % Work in Retail 3.2 % Unemployed 1.4 % Blogger/Influencer 0.4 % Don’t Want to Say 3.5 %

Table 9: Slow Fashion Awareness Percentage Yes 28.1 % No 57.3 % Don’t know 14.6 %

Table 10: Correlation Matrix of Reactive CSR Question 1 2 3 4 Item 1 2 .350** 3 .250** .493** 4 .237** .543** .835** 1.000 **. Correlation is significant at the 0.01 level (2-tailed)

Table 11: Correlation Matrix of Proactive CSR

Question Item 1. 2. 3. 1. 2. .747** 3. .721** .757** 1.000 **. Correlation is significant at the 0.01 level (2-tailed) **. Correlation is significant at the 76

Table 12: Correlation Matrix of Social Groups Question Item 1. 2. 3. 1. 2. .651** 3. .537** .743** 1.000 **. Correlation is significant at the 0.01 level (2-tailed) 0.01 lev el (2-tailed) Table 13: Correlation Matrix of Consumer Attitudes towards Shopping Online Question Item 1. 2. 3. 1. 2. .565** 3. .524** .409** 1.000 **. Correlation is significant at the 0.01 level (2-tailed)

Table 14: Correlation Matrix of Consumer Attitudes towards Slow Fashion Purchases

Question 1. 2. 3. 4. Item 1. 2. .174** 3. .016 .233** 4. .126** .209** .493** 1.000 **. Correlation is significant at the 0.01 level (2-tailed)

Table 15: Operationalization

Variables Type of scale and Items Referring to construction Reactive CSR 4 items and 6 items, 2.2 make good Insipired by Ramesh (extrinsic) Likert – Scale 1-7., 1 quality products et al. (2018), Kim equal to “Totally 2.4 that are (2011), Kim and disagree” and 7 transparent about Ferguson (2019) and “Completely agree” how the products are Shahzad et al. (2020) and additionally produced “Don’t know” 5.1 are ethically or sustainably certified

5.2 are transparent about their CSR practices Proactive CSR 6 items, Likert – 5.3 are consistent in Ramesh et al. (intrinsic) Scale 1-7., 1 equal to their CSR (2018), “Totally disagree” 5.5 that protect the Pookulangara and and 7 “Completely environment Shepard (2013) and agree” and 5.6 that contribute Graafland and additionally “Don’t to local community Mazereeuw-Van der know” development Duijin Schouten projects (2012) Social Groups 7 items, Likert – 6.2 My family’s Evans et al. (2009), Scale 1-7., 1 equal to opinion of my p. 242 & 243 and “Totally disagree” fashion choices is Saluja (2016) and 7 “Completely important to me agree” and 6.3 My friends’ additionally “Don’t opinions of my know” fashion choices are important to me 6.4 My colleagues’ opinions (i.e. school, work etc.) of my fashion choices are important to me Consumers’ 5 items, Likert – 9.1 I intend to buy Anastasiadou et al. attitude towards Scale 1-7., 1 equal to more fashion (2018), Beldad et al. buying fashion “Totally disagree” products soon. (2016) and online and 7 “Completely 9.2 I intend to keep Hausmann and agree” and buying fashion Siepke (2009) additionally “Don’t products on the know” Internet 9.3 I believe I will buy more fashion products in the future than I do now Consumer 8 items, Likert – 10.2 I purchase Cho et al. (2015) attitudes towards Scale 1-7., 1 equal to second-hand fashion buying slow “Totally disagree” items online (i.e. fashion items and 7 “Completely exchange or social online agree” and media websites) additionally “Don’t 10.3 I only buy know” fashion items that are timeless (i.e. not based on seasonal trends) 10.4 I don’t mind wearing the same clothes or shoes for many years, as long 78

as they look and feel fresh. 10.5 I reuse clothing in order to make the most out of them Purchase intent 5 items, Likert – 9.4 I intend to keep Inspired by Scale 1-7., 1 equal to buying fashion Anastasiadou et al. “Totally disagree” garments from the (2018) and 7 “Completely online retailers I buy agree” and from today additionally “Don’t 9.5 I intend to buy know” fashion garments from new online retailers in the future (Mostaghel, 2020)