The Effect of Corporate Environmental Responsibility on Brand Perception, Consumer Interaction and Purchasing Intention in the Fashion Industry

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The Effect of Corporate Environmental Responsibility on

Brand Perception, Consumer Interaction and Purchasing

Intention in the Fashion Industry

Patrick Benjamin Möller

Hoogeweg 1-117, 9746 TN Groningen Student number: 200382568 - NUBS

S4136934 – RUG p.b.moller2@newcastle.ac.uk

p.b.moller@student.rug.nl

Supervisor: Dr. Qionglei Yu; Dr. R.W. de Vries

Master Thesis - DDM – Advanced International Business & Management and Marketing

Faculty of Economics and Business University of Groningen

Newcastle University Business School Word count: 13,548 words

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Abstract

Climate change and global warming are among the greatest societal challenges of our time. Despite the growing interest in sustainable products, the effect of corporate environmental responsibility on companies in the fashion industry so far has only been partially examined. This thesis addresses the research gap and aims to answer the following research question: What is the effect of corporate environmental responsibility on brand perception, consumer interaction and purchasing intention in the fashion industry? For this purpose, the results of an online survey with 186 participants were statistically analyzed using ordinary least square regressions. Significant results for a positive effect of corporate environmental responsibility on brand perception as well as on consumer interaction and purchasing intention were found. These results provide important insights for future research and for fashion brands themselves. They provide indications that an investment in corporate environmental responsibility activities could be compensated by increasing brand perception and purchasing intention. In this case, a future change of the production in one of the most polluting industries in the world can not only be financially profitable, but also contribute significantly to the fight against climate change.

Key words: Corporate environmental responsibility, corporate environmental

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List of Figures

Figure 1. Conceptual Model ...21

List of Tables

Table 1. Fashion brand selection preliminary survey ...23

Table 2. Sustainability attribute selection preliminary survey ...24

Table 3. Skewness and Kurtosis ...36

Table 4. Descriptive statistics ...39

Table 5. Pearson correlation ...40

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List of Acronyms

CER Corporate environmental responsibility CEP Corporate environmental performance CSR Corporate social responsibility

GRI Global Reporting Initiative

HC3 Heteroscedasticity consistent version 3

HCCM Heteroscedasticity consistent covariance matrix MRSL Manufacturing restricted substances list

PVH Phillips-Van Heusen OLS Ordinary least squares SD Standard deviation

SME Small and medium-sized enterprises VIF Variance inflation factor

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1. Introduction

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to changes in consumer demands and growing environmental problems. CER became a growing trend.

Following on from this, this thesis aims to find out, whether CER engagement has an impact on the brand perception by consumers and their willingness to interact with brands in the fashion industry. Over the last few years, more and more fashion brands, that are fully committed to sustainable clothing, have been founded. This phenomenon suggests that the changing needs of consumers have created gaps in the highly competitive fashion market. These gaps can lead to competitive advantages, if the companies decide to react early to this trend and change the product selection and production itself. This development is relevant, because it can help to solve the current social and environmental challenges. However, companies in the fashion industry also have a profit motive and a commitment to their shareholders. Therefore, it is even more important, to find out to what extent an involvement in CER can improve the brand perception of a fashion brand and the purchasing intentions of the consumer. A positive correlation between CER and brand perception as well as consumer interaction with a brand and purchasing intention, could encourage companies to change the conditions of production and thus make an important contribution to saving the environment and still maintain or even achieve a strong position in the competitive fashion industry.

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industry or other heavy polluting industries (Du et al., 2015; Andrews, 2016; Yakovleva & Vazquez-Brust, 2011). Despite the high environmental impact of the fashion industry, only a few studies dealt with this area. Most of the studies that focused on the fashion industry concentrated on key internal company indicators such as firm performance (Amores-Salvadó et al., 2014).

Although there are studies that dealt with the view from and impact on consumers, these are often characterized by sample limitations, like homogeneous age or gender groups. This study aims to fill the research gap of measuring CER effects on consumers in the fashion industry by taking a more general approach with the sample. In particular, the consumer's perception of the fashion brands as well as the interaction with the respective brands play a crucial role, due to the growing importance of social media. In addition, the effect CER activities can have on consumers' purchasing intentions will be measured.

The central research question of this thesis is therefore: What is the effect of

corporate environmental responsibility on brand perception, consumer interaction and purchasing intention in the fashion industry?

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2. Literature Review

2.1 Corporate Social Responsibility

The effects of CSR on various industries have already been examined in numerous studies in academia. Since the concept of CSR has gained significantly in importance in recent years, corresponding studies have also been devoted to the topic. Nonetheless, the dimension of the environment was often not mentioned or only subordinated in the past. The analysis of 37 different definitions of CSR showed that the environmental dimension played the least relevant role (Dahlsrud, 2008). Although some studies do provide information that could be important for the influence of CER on brand perception in the fashion industry and offer interesting starting points.

Amores-Salvadó et al. (2014) examined the influence of environmental product innovation on firm performance and came to the conclusion that the commitment to invest in environmental product innovations has a positive effect on the performance of a company. Additionally, a significant, positive impact of a green corporate image on firm performance was found. For this purpose, primary data was collected from affected companies through a survey and a principal components factor analysis on the questionnaire measurements items was carried out. By using a small sample from a homogeneous industry, the results are difficult to transfer to other industries and therefore do not provide enough sufficient evidence.

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only limited validity. Furthermore, the interpretation of interviews always has subjective elements. Since the main focus of the study is on the influence on downside risk, other aspects such as the influence on brand perception and consumer interaction remain largely unexamined and require more detailed analysis considering not only one but multiple companies.

Pedersen & Gwozdz (2014) showed in their study the development of the Nordic Fashion Industry's responses to institutional pressure for CSR. They followed a stakeholder-oriented approach to measure the strategic responses of companies to institutional pressure. To do so, they first conducted a survey and evaluated the results using a linear regression. Although surveys are a common method to measure policies and strategies in this area, their suitability is limited because companies that do not invest in CSR might not answer the survey or might not answer it adequately (Pedersen & Gwozdz, 2014). Furthermore, the list of stakeholders was incomplete and the analysis was focused on CSR, a much broader term than CER. Additionally, no effect on brand perception and consumer interaction was analyzed, so that although this study provides an insight into the CSR behavior of companies in the fashion industry, it is only a limited contribution to the issue of this thesis.

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fashion industry and illustrate the importance of more research in this area, to which this thesis contributes.

2.2 Corporate Environmental Responsibility

First of all, there are different concepts and definitions of corporate environmental responsibility. These concepts differ primarily in the way in which the environmental activities of companies are measured and evaluated. The differences already begin with labeling the concepts. The two most common terms for environmental activities implemented in a company are corporate environmental responsibility (Gănescu & Dindire, 2014) and environmental corporate social responsibility (Post et al., 2011). Both terms demonstrate that these concepts originate from the concept of corporate social responsibility.

In most studies CER is defined as environmentally friendly activities that are not required by law (Lyon, 2008; Portney, 2008). These activities are carried out voluntarily by the companies and help to internalize the environmental damage caused by the polluter. This thesis adopts this definition of CER as activities of companies to preserve the environment beyond their legal obligations (Lyon, 2008). The predominantly result are higher production costs, which have to be covered by the company. Nevertheless these costs may be offset by other factors, such as better brand perception or increasing consumer interest in interacting with the brand and purchasing brand products. Studies in the past have often dealt with the concepts of CSR or CER in general or examined their impact on different parts of the company or a specific industry. Some of these studies, which provide interesting insights and starting points, are presented below.

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corporate environmental responsibility on companies. It is particularly noticeable that there is no standard concept of CER. Instead, there are many different approaches used to measure corporate environmental performance. Predominantely, these concepts do not build on each other, so that the results of the studies provide conflicting results rather than contributing to a common understanding of CER (Guenther & Orlitzky, 2012). Furthermore, there are trade-offs between what can be measured and what should be measured (Delmas & Blass, 2010). As a consequence there is no conclusive understanding of measuring CER.

Sáez-Martínez et al. (2016) examined the influence of CER on the firm performance of SMEs using data from the surveys among SMEs in 38 different countries. The results of the surveys are analyzed using an ordinary least square regression model to identify the factors that have a positive impact on environmental engagement (Sáez-Martínez et al., 2016). Additionally, they performed a second OLS regression to determine the effect of CER on sales. They concluded that CER has a positive and significant impact on sales growth in SMEs and lead to a higher performance of SMEs (Sáez-Martínez et al., 2016). The statistical methods used are suitable and comprehensive for the data set. As they did not provide specific results for companies in the fashion industry, they are a good approach and important findings that support the assumption that CER can have a positive impact, but they cannot be fully applied to the fashion industry.

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using linear regression. They draw on data from companies in the Chinese security market over a nine-year period. Due to the data from outside the industry, the results can only have a limited influence on this thesis, but nonetheless provide good indications for further analyses.

2.3 Corporate Environmental Performance

Ilinitch et al. (1998) designed one of the first concepts of corporate environmental performance to make corporate environmental responsibility measurable. They combined both empirical and theoretical approaches to define CEP. In their framework they defined the following 4 dimensions: (1) organizational systems; (2) stakeholder relations; (3) regulatory compliance; (4) environmental impacts (Ilinitch et al., 1998). Unfortunately, these dimensions and especially the corresponding indicators are not applicable for measuring companies in the fashion industry as they are in some parts way to broad and in other parts not measurable in practice.

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fashion industry, as the indicators cannot be transferred to companies in the fashion industry in a fully satisfactory way.

In his study in Dragomir (2018) analyzed 172 papers that dealt with CEP and found out that only 2 of them dealt with the textile industry. This clearly shows how big the research gap in this industry is when it comes to relevant studies on CER. It impressively demonstrates the lack of applicable concepts and frameworks and shows how much research is still necessary to get a clear insight.

One of these studies focused on the environmental performance of SMEs in the Brazilian textile industry (Lucato et al., 2017). In particular, the relationship to financial performance was examined. In their methodology, the authors used only three different indicators based on monthly average net revenue. This is not sufficient to measure a precise analysis of the CEP of a company, as too many sub-areas are not taken into account. The other study is about sharing environmental management information with supply chain partners and therefore not useful for the purpose of this thesis (Lai et al., 2015).

2.4 Sustainability in the Fashion Industry

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environmentally friendly production. A description of the information provided by the companies relevant for this thesis can be found in Appendix B.

Challenges like this have been solved in past research mainly by collecting data at the consumer level, usually through consumer interviews or surveys. In the following, some of these studies are presented in order to give an overview of the areas that have already been researched in the literature.

One of the most important and recent studies on sustainability in the fast fashion industry and its impact on consumer perception, trust and purchasing intention was conducted by Neumann et al. (2020). Like this thesis, it demonstrated the importance of sustainability in the world's second most polluting industry (Neumann et al., 2020). In their analysis they tested the impact of sustainability efforts on consumers. In doing so, they specifically examined the impact of social responsibility on consumer trust and the general attitude of consumers towards the company and the extent to which this has an impact on purchasing decisions. They conducted an online survey where 216 young women participated and analyzed the data using partial least squares structural equation modelling. Neumann et al. (2020) found that the perception of social responsibility is directly related to the attitude towards these fashion brands, but does not influence purchasing intentions.

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serves as a valuable starting point for this thesis, which aims to gain insights that have a higher general validity by extending the sample to all generations and genders.

A further study in this sub-area was conducted by D'Souza et al. (2015). In their study the authors investigated to what extent the purchasing decision of male consumers would make a difference in the eco-fashion industry. D'Souza et al. (2015) conducted a survey of 193 male consumers in a shopping mall and analyzed the data using partial least squares to develop a conceptual model. In their analysis they found that there are four significant exogenous variables with a negative impact: environmental concern, sustainable pricing, sustainable behavior and sustainable branding. This study also has numerous limitations. For one thing, the sample consisted of only one gender, similar to Neumann et al. (2020). Since purchasing decisions can vary between the different genders and thus differ significantly, the results have only limited significance. Similarly, the study explains only 63% of the variance in the results. In order to be more meaningful, further studies with a sample that better represents society would be necessary.

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In his study, Sarkar (2014) explored the nature of brand love in the context of the Asian market. He conducted semi-structured in-depth interviews with 600 participants in urban and sub-urban environments in North and South India. He came to the conclusion that brand love is cognitively biased and takes the form of a powerful passion at a higher level (Sarkar, 2014). The results are interesting in so far as rational factors can take on a subordinate role through the development of brand love. Besides the functional aspects, clothing in particular also fulfills social aspects. Thus they can be both a way of expression and a status symbol. Consequently, such a relationship of consumers to a certain brand can lead to a distortion of the perception of the activities of that brand. Although this has only limited relevance to the research area of this thesis, it provides insightful findings that can explain possible irrational purchasing decisions and thus clearly plays into the purchasing intention.

2.5 Hypothesis

The studies presented above illustrate that the importance of CSR for business has increased in recent years. A large amount of literature dealt with the effects of corporate social responsibility on various industries, while there are significantly fewer studies on the influence of corporate environmental responsibility. This is especially the case for the fashion industry, which has a large share of environmental issues due to its production processes. Although the effects of CER engagement in other industries or for SMEs in general are investigated, they are only of limited relevance for the fashion industry.

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positive characteristic of a company and thus increases trust in the brand (Sarkar, 2014). Due to the growing environmental crises, the importance for the consumer is increasing and an investment in ecologically sustainable production is no longer seen only as an ecological necessity but also as an ethical necessity (Parsa et al., 2015). Recent studies have shown, that there is a direct relationship between the reputation of a fashion brand and the attitude of the consumers (Neumann et al., 2020). Following Neumann et al. (2020) findings, it can be assumed that the improved attitude of consumers towards companies is accompanied by an improved perception of them. As CER engagement is seen as societal desirable and should enhance the brands reputation. Studies have shown that a reputation has a positive effect on the perception of product quality and therefore on the brand itself (Akdeniz et al., 2013). Consequently CER engagement should influence the brand perception of the consumers.

H1: CER has a positive effect on consumers brand perception.

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changed attitude is also reflected in the willingness to communicate with companies. A growing positive reputation leads to an increased willingness of consumers to interact (Akdeniz et al., 2013). It can therefore be estimated that a higher CER engagement has a positive effect on the willingness of consumers to interact with companies.

H2: CER has a positive effect on the willingness of consumers to interact with the company.

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2016). It therefore can be assumed that the CER engagement leads to an increased green image of the products and therefore has a positive effect on the consumers purchasing intentions.

H3: CER has a positive effect on consumers purchasing intentions.

2.6 Conceptual Model

This thesis takes an unusual approach by analyzing the effect of one independent variable on three dependent variables. Figure 1 shows the graphical representation of the relationship between the independent variable corporate environmental performance and the dependent variables brand perception, consumer interaction and purchasing intention. As it can be seen in this model a positive effect of corporate environmental performance on all dependent variables is expected.

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3. Methodology

3.1 Preliminary Survey

In order to measure the impact of CER on brand perception and consumer interaction a preliminary survey was conducted. This survey determined which brands are of particular importance to the consumer. It also served to determine which attributes of sustainability and environmental friendliness are particularly important to the consumer. The results of this survey were used to reduce the number of fashion brands and sustainability attributes. All fashion brands that were available for selection, as well as the attributes that were available for selection, can be seen from the results in Table 1 and Table 2.

The main reason for this reduction is that a main survey with information and questions on eight fashion brands would be too extensive and the participants could lose focus and the results could therefore lose their validity. As there is a very large number of different brands in the fashion industry, it is particularly important for the main survey to select brands that are as familiar as possible to the consumer and which the consumer has the most experience with and information about. In the first part of the preliminary survey, the participant had the opportunity to choose their most important brands from the following eight different brands: Ralph Lauren, H&M, Zara,

Tommy Hilfiger, Nike, Adidas, Boss and Patagonia. Multiple selections were possible

for this question. The results of the first question are listed in Table 1.

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Table 1. Fashion brand selection preliminary survey

Rank Fashion Brand Votes Percentage of total

votes 1 Tommy Hilfiger 16 20.00 2 Ralph Lauren 14 17.50 3 Adidas 13 16.25 4 Nike 12 15.00 5 H&M 8 10.00 6 Boss 6 7.50 6 Zara 6 7.50 8 Patagonia 5 6.25 Total 80 100.00

survey are more important to the consumer. The results of the second part are listed in Table 2.

A total of 27 people took part in this preliminary survey. Of the 27 answers, all were usable. The survey addressed mainly family members and friends. Since the sole purpose of this survey is to reduce the size of the main survey and no significant findings are drawn from it, no statistical quality tests are necessary to verify the quality of the data. The results in Table 1 show that the most important fashion brands for the respondents are Tommy Hilfiger, Ralph Lauren, Adidas and Nike. These four brands are thus selected as the brands for the main survey. The results in Table 2 show that

"Quality of textile dyes" is the most important attribute for the respondent, followed by

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characteristics. Surprisingly, packaging seems to be more important to the consumers surveyed than the rate of recycled material or the percentage of organic cotton.

Table 2. Sustainability attribute selection preliminary survey

Rank Sustainability Attribute Score

1 Quality of textile dyes 22.4

2 Packaging of the delivery 19.0

3 Packaging of the product 18.8

4 Investment into improvement of production standards

18.0

5 Investment into improvement of technology and product characteristics

17.2

6 Rate of recycled material 14.6

7 Use of organic material 14.0

8 Transportation methods 12.4

Notes. N = 27.

The five CER attributes that will be tested in the main survey are therefore: “Packaging

of the delivery”, “Packaging of the products”, “Quality of textile dyes”, “Investment into improvement of production standards” and “Investment into improvement of technology and product characteristics”.

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this research approach, such a preliminary survey is sufficient to justify the selection of the companies and attributes for the main survey.

3.2 Main Survey 3.2.1 Data collection

All data used for this analysis is self-collected primary data, which was collected through an online survey. This online survey consisted of a total of five sections. A detailed breakdown of the survey and the exact questions asked in the survey can be seen in Appendix A. Before the first question, the respondent was shown information about the CER activities of the companies. This information was taken from the companies' annual sustainability reports. More detailed explanations of the information can be found in the research context.

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for demographic data. These included the age and gender of the respondents, as well as the highest level of education and monthly spending on clothing.

3.2.2 Sample

As mentioned above, all of the data was collected through an online survey on consumer level. A total of 186 participants completed this survey. Since all participants answered the questions not for one single company but for four different companies, it was possible to use partial answers. Although this leads to a different number of observations in the linear regression of the individual dependent variables in the later stage of this thesis, this difference is only marginal due to the size of the number of observations. The overall number of 186 participants is appropriate for the purpose of this thesis and thus represents an acceptable basis for further statistical analyses.

In past studies restrictions were often placed on the gender of the participants (D'Souza et al., 2015; Neumann et al., 2020), this thesis aims to avoid these restrictions as much as possible when selecting participants. Since the purchasing behavior between men and women can often differ, a study with only one gender also has limited validity in its results (D'Souza et al., 2015; Neumann et al., 2020). In this survey, the proportion of female participants is 50.5% and the proportion of male participants 49.5%. This means that both genders are equally represented, thus a more general statement should be possible.

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participants. 39% of the respondents stated that they were between 18 and 24 years old, 47% between 25 and 34 years. This implicates that the sample also includes a large proportion of people who have finished their educational training and started working and are therefore particularly interesting for the fashion brands.

Studies that collect primary data through online surveys frequently focus on students (Chiu & Leng, 2016), this thesis aims to include all educational qualifications in my survey. In this sample, 40% of the participants have no academic degree. 36% of the respondents have a bachelor degree and 21% have a master degree. Five of the participants and thus 3% have a doctorate. Although there is a small focus on participants with academic degrees, a significant portion of the sample consists of people without completed academic education. The results of my statistical studies should therefore be of higher general significance than comparable studies that are limited to a specific group.

3.2.3 Research Context

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Ralph Lauren

Ralph Lauren uses around 10% of sustainable materials for their products. Since 2019 they rely fully on renewable energy. They are engaging to improve the sustainability of all materials to 100% by 2025 (Ralph Lauren, 2020).

Tommy Hilfiger

Tommy Hilfiger uses around 25% of sustainable materials for their products. Currently around 25% of the energy used is renewable. By 2025 they aim to use 100% sustainable cotton and viscose (PVH Corp., 2020).

Adidas

Adidas uses 100% of sustainable cotton and 50% recycled polyester. By 2020 they aim to safe 20% of the energy used compared to 2014. By 2024 they aim to improve the rate of recycled polyester to 100% (Adidas AG, 2020).

Nike

Nike uses around 40% of sustainable materials for their apparel. Currently around 25% of the energy used is renewable. By 2020 they aim to use 100% sustainable cotton (Nike Inc., 2020).

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the willingness to invest in sustainability without making a direct evaluation and significantly distorting the participants' perception.

3.2.4 Variables

3.2.4.1 Dependent variables

Since this thesis examines the effect of CER on brand perception, consumer interaction and purchasing intention, there are three dependent variables. The first of these dependent variables is brand perception. Brand perception, like the other dependent variables, is measured by the results of the online survey on consumer level. The answers of the individual questions are converted into scores and the total score for the brand perception is calculated. All individual scores receive the same weighting. In the past, brand perception on consumer level has been analyzed by many studies and determined through surveys (Hudson et al., 2016; Neumann et al., 2020; Thuy & Thao, 2017). These surveys were often very extensive and detailed, as they only dealt with brand perception as a dependent variable. By the fact that this thesis analyses three dependent variables a just as detailed questioning is not possible to the individual variables, since otherwise both the length and the scope of the survey would not be any longer proportionate.

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The third dependent variable purchasing intention is determined in the same way as the two previous dependent variables. The individual scores from the questions are also combined in equal weight to form an overall score. In addition, the selection of the questions was based on previous surveys (Awuni & Du, 2016; Neumann et al., 2020).

3.2.4.2 Independent variable

The independent variable for this analysis is corporate environmental performance. Corporate environmental performance is used to measure the sustainability of companies, especially with regard to environmental factors. For this analysis, the consumer's impression alone is of decisive importance. In general, there are many ways to measure corporate environmental performance. There are numerous frameworks that are designed to enable a generally accepted measurement of corporate environmental performance at company level (Escrig-Olmedo et al., 2017; Ilinitch et al., 1998). For this thesis, it is not corporate environmental performance at the company level, but from consumer´s perception that will determine the CER of the fashion brands. Therefore, corporate environmental performance must also be measured at consumer level. As with the dependent variables, the independent variable is also measured through the survey. Here, the respondents of the survey first receive additional information about the fashion brands, as already explained in the research context.

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on the evaluation from the survey. All these individual scores are then combined with equal weighting to form an overall score for corporate environmental performance.

3.2.4.3 Control variables

In addition to the independent variable, there are other factors that might have an impact on brand perception, consumer interaction and purchasing intention. A total of four control variables are used in this analysis, which are determined by the answers to demographic questions in the survey.

The first control variable is the age of the respondents. Studies have shown that younger people in particular are paying more attention to sustainability and make their purchasing decisions dependent on the sustainability of the product itself and the company (Parsa et al., 2015, Yadav & Pathak, 2016). They are willing to spend more for sustainable products and prefer them over non-sustainable alternatives (Parsa et al., 2015). As the purchasing intention can differ significantly between generations, age can also have a decisive influence on the respective dependent variable. For this reason, age is used as the first control variable in this analysis.

The second control variable is the educational level of the respondents. Previous studies have found evidence that with higher levels of education the importance for sustainability increases (Felgendreher & Löfgren, 2018). It is therefore possible that the educational level of the participants has an influence on the respective perception of the brands and on how they interact with the brands. Therefore, the second control variable included in this analysis is the level of education.

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such as social status or expression of one's own personality, the decision on how much money is invested in clothing each month can have an influence on perception. Therefore, monthly spending on clothing was included as a control variable in the survey.

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4. Results

The following section presents the results of the analysis. First, the preliminary analysis to determine the quality of the data and their results are presented. Thereafter, the results of the descriptive statistics and the correlation analysis are shown and interpreted. Finally, the results of the linear regressions are explained, which test the previously presented hypotheses.

4.1 Preliminary Analysis

In order to investigate the effect of CEP on the dependent variables, it must first be determined whether the collected data are suitable for further statistical analysis. There are several ways to test the collected data for their quality. In the following section first the reliability of the data is tested by calculating Cronbach´s alpha. Afterwards the skewness and kurtosis of the single variables are calculated to get a picture of the distribution of the data. Afterwards, the data is tested on heteroscedasticity. Finally, the qualitative testing of the data is completed with the test for multicollinearity. These measurements are also used to test the robustness of the results and data.

4.1.1 Cronbach´s Alpha

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there is a possibility that the items are redundant, thus the same question could be tested in a different formulation (Tavakol & Dennik, 2011). In this analysis, independent variables corporate environmental performance as well as the dependent variables brand perception, consumer interaction and purchasing intention were determined by multiple questions in the survey. Therefore these variables are to be tested with Cronbach's alpha. The value for Cronbach's alpha for the independent variable corporate environmental performance is approximately 0.77 and is thus above the required value of 0.7.

The calculation of Cronbach's alpha for the dependent variable brand perception resulted in a value of 0.87. For the dependent variable consumer interaction a value of approximately 0.80 could be determined. The testing of Cronbach's alpha for the dependent variable purchasing intention resulted in a value of 0.89. It can therefore be concluded that for all tested variables the values of Cronbach's alpha are above the required limit value of 0.7. They are also below the upper limit of 0.9, thus poor interrelatedness can be excluded. Thus, a good reliability can be assumed for the collected data.

4.1.2 Skewness and Kurtosis

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could be due to the choice of possible answers to this question in the survey, where no concrete numbers can be inserted, but number ranges are used as answer possibilities. This is a possible explanation for the fact that both the skewness value with 1.77 and the value for kurtosis with 6.21 are clearly above the limits.

Table 3. Skewness and Kurtosis

Variables Skewness Kurtosis

CEP - 0.2719 2.7531 Brand perception - 0.5908 2.7764 Consumer interaction 0.5643 2.5157 Purchasing intention - 0.3974 2.1988 Age 0.8729 3.9339 Educational level - 0.2265 1.9143 Monthly Spending 1.7731 6.2185 Gender - 0.0834 1.0069 Note. N = 576.

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recommended values (Field, 2018). Since during a transformation not only the non-normal data but all data have to be transformed, and since the variables that scored significantly above the recommended limits are control variables, there is a high risk that the quality of the data will decrease due to the transformation. For these reasons, this thesis refrains from transforming the data and considers the non-normality of the two control variables in the interpretation of the regression results.

4.1.3 Heteroscedasticity

Another requirement that the data must meet to successfully perform a linear regression is the absence of heteroscedasticity. To exclude heteroscedasticity a Breusch-Pagan test was performed for each of the regression models (Breusch & Pagan, 1979). The results show that heteroscedasticity cannot be rejected in the third regression model, which measures the influence of corporate environmental performance on purchasing intention. In this case, the null hypothesis that a constant variance exists cannot be rejected ( p > Chi2_{= .38). The results show that in this cases}

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4.1.4 Multicollinearity

Finally, the variables are tested for multicollinearity, to exclude that there is a perfect linear relationship between the predictors. For this purpose a Shapiro-Wilk test is conducted (González-Estrada & Cosmes, 2019). The exact results of the Shapiro-Wilk test can be found in Appendix C. The accepted threshold for the VIF is ten and the tolerance should be above 0.2 (Field, 2018). From the results it can be seen that none of the VIF values is greater than ten. In addition, all tolerance values are well above the recommended threshold of 0.2. Furthermore, the average VIF should not be substantially greater than one (Field, 2018). The VIFaverage for each of the three models

is 1.05 and thus not substantially greater than 1, suggesting that the results will not be biased. Therefore it can be excluded that collinearity is present.

4.2 Descriptives

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newsletters as well as mutual communication via social media. The average score of 4.25 (SD=1.14) for the purchasing intention is slightly positive, as is the brand perception. Thus, the willingness to purchase products of the presented brands seems to be rather positive overall. Interesting in the results is that the willingness to purchase products is possibly greater than the willingness to interact with the brands. The average age of the participants is 2.76 (SD=0.81) and thus between 25 and 34 years.

Table 4. Descriptive statistics

Median Mean Std. Dev. Min. Max. Corporate environmental performance 4 3.93 0.78 2 6

Brand perception 4.75 4.52 0.98 2 6 Consumer interaction 3.25 3.39 1.05 2 6 Purchasing intention 4.25 4.22 1.14 2 6 Age 3 2.76 0.81 1 5 Educational level 4 3.57 1.19 1 6 Monthly spending 1 1.79 1.09 1 6 Gender 2 1.52 0.50 1 2

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Table 5 shows the results of the Pearson correlation. From these results first insights can be gained whether the variables correlate and thus have an influence on each other. The results show that some significant positive and negative correlations exist. Many of the results show however only a small correlation. The Pearson correlation analysis shows significant positive correlations between the independent variable CEP and all dependent variables. These results are r (.39) = .00, p ≤ .001 for brand perception, r (.33) = .00, p ≤ .001 for consumer interaction and r (.36) = .00, p ≤ .001 for purchasing intention. This is a good indicator for an effect between the variables and supports the analysis by OLS regression. It is also remarkable that the dependent variables show a significant correlation among each other, which partly exceeds the threshold values of 0.7 recommended the literature and points to multicollinearity (Kennedy, 1992). However, this can be excluded by a multicollinearity

Table 5. Pearson correlation

Variable 1 2 3 4 5 6 7 8 1. CEP 1.00 2. Brand perception .39*** 1.00 3. Consumer interaction .33*** .66*** 1.00 4. Purchasing intention .36*** .81*** .65*** 1.00 5. Age - .11** - .12** - .11** - .10* 1.00 6. Educational level - .04 - .02 - .10* - .03 .23*** 1.00 7. Monthly spending - .01 .06 0.08* .07† .18*** .15*** 1.00 8. Gender - .06 - .14*** - .17*** - .19*** .00 .03 - .05 1.00 Notes. N = 576. †p ≤ .10; *p ≤ .05; **p ≤ .01; ***p ≤ .001.

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and the dependent variables can be determined. There is also a significant correlation between the control variable gender and the dependent variables. The values are r (-.14) = .00, p ≤ .001 for brand perception, r (-.17) = .00, p ≤ .001 for consumer interaction and r (-.19) = .00, p ≤ .001 for purchasing intention. Furthermore, there is a positive correlation between the control variables age and educational level

(r (.23) = .00, p ≤ .001). This can be explained by the fact that academic degrees can only be achieved after a certain amount of time due to the duration of the academic training.

4.3 Regression Analysis

This section presents the results of the main statistical analysis to provide answers to the developed hypotheses. Table 6 shows the results of the OLS regressions for all three models performed. Model 1 tests the first hypothesis with brand perception as the dependent variable. The second model tests the second hypothesis, where consumer interaction is the dependent variable. In the third and last model the third hypothesis is tested. For this purpose purchasing intention is used as dependent variable. In all three models corporate environmental performance is the independent variable. In addition, the variables age, educational level, monthly spending and gender serve as control variables in all models.

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that a positive perception of brands decreases with increasing age. There is also a negative, significant relationship between the control variable gender and brand

Table 6. Regression analysis

Model 1 Model 2 Model 3

CEP .47*** (.05) .42*** (.05) .49*** (.05) Age -.11* (0.5) -.10† (.05) -.10† (.05) Educational level .00 (.03) -.07* (.03) -.01 (.04) Monthly spending .07† (.04) .10* (.04) .08* (.04) Gender -.22** (.08) -.32*** (.08) -.39*** (.08) Constant 3.19*** (.29) 2.61*** (.32) 3.06*** (.35) R2 _.181 _.159 _.168 Adjusted R2 _.173 _.151 _.160 F-value 22.74*** 21.14*** 26.07***

Notes. NModel 1 = 569; NModel 2 = 557; NModel 3 = 570. Dependent variable: Model 1 = brand

perception; Model 2 = consumer interaction; Model 3 = purchasing intention. Robust

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perception (b = -.22, p ≤ .01). This result suggests that the brand perception of female respondents was lower than the perception of male respondents. The model performed explains 17.3% of the variation in brand perception. The F-Value shows that the model performed is highly significant (p ≤ .001). Overall, the results of model 1 of the OLS regression confirm hypothesis 1, thus corporate environmental performance has a positive effect on brand perception.

The second Hypothesis claims that there is a positive effect of corporate environmental performance on consumer interaction, which implies that an increasing CEP also leads to a higher interaction of the consumer with the fashion brand. The results show a highly significant, positive relationship between CEP and consumer interaction (b = .42, p ≤ .001). This value indicates that an increasing corporate environmental performance has a positive effect on consumer interaction.

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since a positive effect of corporate environmental performance on consumer interaction was found.

Hypothesis 3 claims that there is a positive effect of corporate environmental performance on purchasing intention, which implies that an increasing CEP leads to a higher willingness of the consumer to purchase the products of the fashion brand. The results show a highly significant, positive relationship between CEP and purchasing intention (b = .49, p ≤ .001). This result indicates that an increasing corporate environmental performance has a positive effect on the purchasing intention of the consumer. In addition, a significant, slightly positive effect between the control variable monthly spending and purchasing intention was found (b = .08, p ≤ .05). This result indicates that consumers who spend more money on clothing are more likely to purchase fashion brand products. However this result must be taken cautiously as the normality of the distribution of this data could not be fully proven. As in the first and second model of OLS regression, a significant negative relationship between gender and the dependent variable, in this case purchasing intention, was observed (b = -.39, p ≤ .001). This result indicates that female consumers have a lower purchasing intention than male consumers. With this model 16.0% of the variation of purchasing intention can be explained. The F-Value shows that this model is also highly significant (p ≤ .001). Overall, the third hypothesis can be confirmed, which states that corporate environmental performance has a positive effect on purchasing intention.

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5. Discussion

This thesis aims to examine if there is an effect of corporate environmental responsibility on brand perception, consumer interaction and purchasing intention in the fashion industry. The previous chapters have developed three hypotheses on this research question with the help of already published literature. These hypotheses were then empirically tested using the data collected. The following chapter now discusses the findings to be drawn from the results and relates them to the existing literature.

5.1 Theoretical implications

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effect of CER on brand perception can be determined. However, this only explains 17.3% of the variation in brand perception. This result was expected and might have several reasons. The brand perception itself consists of more factors than the corporate environmental performance. Studies have found that consumers are very price-sensitive, so it can be assumed that the brand perception is dependent on the price of the products as well (Erdem et al., 2002; Wakefield & Inman, 2003). Furthermore, the market in the fashion industry is highly competitive. In particular, the reputation of the brand plays a significant role in brand perception. In addition, personal taste also plays a role in the perception of the fashion industry. Brands that match personal taste with their products are rated better than brands that do not (Sarkar, 2014). Another reason could be brand love, where perception is not shaped by rational factors but is cognitively biased (Sarkar, 2014).

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communication channels such as newsletters, mutual communication channels have been created in social media. Social media are mainly used by the younger generations (Perrin, 2015). Therefore, it is surprising that no significant, negative effect of age on consumer interaction could be measured. However, this could also be due to the fact that a large proportion of the participants in the online survey are among these younger generations. Overall, it can be confirmed that there is a positive effect of CER on consumer interaction. However, the model explains only 15.1% of the variation in consumer interaction. This can have several reasons. Firstly, personal habits and preferences play a strong role in communication, especially via social media. In addition, the aspect of data protection on the internet plays an increasingly important role (Ziegler, 2019). It is therefore to be expected that many different factors will influence consumer interaction.

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This result indicates that female consumers have lower purchasing intentions than male consumers. This could also be due to the reasons already mentioned above for a more critical approach to sustainability aspects of brands (Price & Bohon, 2019; Xiao & McCright, 2012). These results are particularly relevant because they indicate that an investment in sustainability could be compensated by an increased willingness of consumers to buy the sustainable products. A more detailed description of the effects can be found under managerial implications. The model can explain 16.0% of the variation of the purchasing intention. This can have several reasons. First, as mentioned above, consumers are very price sensitive. Past studies have shown that price is the decisive factor when buying products (Erdem et al., 2002; Wakefield & Inman, 2003). In addition, the purchase of a product is always based on personal taste and preferences. Furthermore, the reputation of the brand also plays a major role in the purchase decision (Bianchi et al., 2019; Jung & Seock, 2016). It is therefore to be expected that the influence of corporate environmental responsibility only explains a small part of the purchasing intention. Overall, a significant positive effect of corporate environmental responsibility on purchasing intention can clearly be identified.

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Neumann et al., 2020). As this thesis shows, however, gender can have a significant influence on the perception of fashion brands, the interaction with them and also the purchasing intention. Therefore, this thesis makes a valuable contribution to existing research by providing insights into the effects of CER, an area that has so far received little attention in the CSR analysis. In addition, a more general approach, both to the research question itself, to the collection of data and the structure of the sample, will provide more holistic insights. Specifically, the sample collected for this analysis is not limited to one age group or gender, even though a large proportion of the participants belong to the younger generations. Likewise, no restrictions were made with regard to the level of education. Furthermore, this sample is not limited to students as participants as prior studies (Chiu & Leng, 2016).

5.2 Managerial implications

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brands receives a significantly lower score than the perception of the brands or the purchase intention. Further, improvements are needed to further simplify communication and interaction with consumers and make them more attractive.

The significant positive effect of CER on purchasing intention indicates that investments into sustainable production and environmental protection can be financially profitable for the brands. This is an important finding, as it not only helps to achieve the motivation of the shareholders to generate profit, but also to actively fights climate change, one of the biggest challenges of our time. The fight against climate change is a societal challenge whose responsibility also affects brands in the fashion industry. In addition, with an intensified commitment and own development initiatives that lead to improved sustainability, future legal restrictions may be prevented. This is particularly true as the target group of many fashion brands is increasingly focused on younger generations. Past studies have shown that the younger generations in particular attach value sustainable, green products as highly important (Parsa et al., 2015, Yadav & Pathak, 2016).

5.3 Limitations and future research

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further research is necessary in different geographical areas. Another limitation is the non-normality of some variables. The control variable monthly spending is affected by skewness and kurtosis. Although the statistical analysis does only show a minimal effect, the results of this variable are nevertheless of limited validity. In addition, the collection of primary data can lead to mistakes in the design and structure of the survey, the questions themselves and also in the processing of the data. Even if the preliminary analyses carried out indicate that the data for this thesis is of sufficient quality, it cannot be ruled out that errors in data collection or data processing may occur. The following limitation is one of the reasons why this can happen.

There is no uniform framework in the literature for measuring corporate environmental performance at consumer level. There are general approaches that attempt to make it possible to measure corporate environmental performance at company level (Escrig-Olmedo et al., 2017; Ilinitch et al., 1998). However, many of these approaches do not build on each other, but differ in fundamental points. This makes it difficult to collect primary data, as it is difficult to use existing frameworks and to choose the right questions and structures for your own survey. Future research should focus on the development of a framework that not only facilitates the collection of data but also the comparability of results.

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difference between purchasing intention and the actual purchasing behavior of consumers. Even though this has already been researched in the past (Johnstone & Tan, 2014), more precise analyses would be desirable, especially for the fashion industry.

Moreover, there is a possibility that the causality of the relationship between the perception of the brands and the evaluation of corporate environmental performance is biased. This suggests the possibility of reversed causality, which leads to brands being rated well in their corporate environmental performance because the general perception of the brands is highly positive. Considering the results of the CEP scores for the brands, however, it can be seen that these tend to be in a neutral range and the brands are therefore not perceived as particularly positive in their CER engagement. These results contradict the assumption of reversed causality. However, reversed causality cannot be completely excluded with this analysis. To exclude reversed causality future research including detailed qualitative interviews to examine the driving factors behind the evaluation of CER activities could be necessary.

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6. Conclusion

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Appendices

Appendix A. Listing of main survey questions

Construct Question

Corporate Environmental Performance

CEP1: Environmentally friendly packaging of the delivery box

CEP2: Environmentally friendly packaging of the product itself CEP3: Quality of textile dyes

CEP4: Investment into improvement of production standards CEP5: Investment into improvement of technology and product characteristics

Brand Perception

BP1: The brand sells products that matches my taste BP2: I can identify with the brand´s products

BP3: I can identify with the values of the brand

BP4: The brand meets my expectations of fashion products Consumer

Interaction

CI1: I subscribed / I would subscribe to a newsletter of the brand

CI2: I follow / I would follow the brand on social media (Instagram, Twitter, Facebook)

CI3: I would like and share social media post of the brand CI4: I would recommend the brands to my friends and family Purchasing

Intention

PI1: I would buy products of the brand in the future

PI2: I would prefer the brand to other brands when buying a product

PI3: I would pay more for a product of this brand than of other brands

PI4: I would search for the brand if I wanted to buy a new product

Demographics D1: What is your age?

D2: What is your highest level of education?

D3: How much do you spent on fashion per month? (Clothes, shoes and accessories)

The Effect of Corporate Environmental Responsibility on Brand Perception, Consumer Interaction and Purchasing Intention in the Fashion Industry