MASTER THESIS
Clean Fallacy
Authors: Elske Wouda and Khang Le Supervisor: Bo Lennstrand
Date: 30th May 2017
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A quantitative study about the price-sustainability
Acknowledgement
Firstly, we would like to thank our mamas Tiny and Thảo, our papas Jan and Khâm, for giving lives to us. We are grateful for our good health, wellbeing, and sanity that have been necessary in order to write this thesis. We would like to thank our mentors: Anna for her enthusiasm, Bosse for his patience and immense knowledge, Jenny for her support, and Ola for his wise advise.
We thank all our peers from the Sustainable Management class of 2017 for their witty feedbacks, being sources of inspiration, but also they have been friends experiencing life outside of the theses with us. We especially would like to express our gratitude to Lotte for being a beacon of light in the inky darkness of Statistics Netherworld.
Furthermore, we are thankful to the Migrationsverket for issuing residence permit to Khang, a foreign student from a third world country. We also would like to thank the Swedish government and the tax payers for providing free education to Els, a citizen from an EU country. We would never have crossed our paths without the help of these institutions.
We would like to thank the Almedals Library for providing a safe space for this winding journey, and we apologise to students in the library who had to witness our spicy discussions about the thesis. Finally, we thank all the employees in the shops in which we collected the data, for refolding the t-shirts correctly and for showing kindness (including the security guard in Chanel for opening the door for us).
ABSTRACT
Corporate colonial behaviour of fashion companies has left the Rana Plaza in ruins and paved the garment industry with catastrophic deaths, casualties, and hypocrisies. As a consequence, the industry is being scrutinized, especially the cheap brands. This paper is an examination of the sustainability of clothes in relation to price and an exploration of the differences between price segments. Quantitative data in the form of price and country of manufacture of 173 t-shirts from different brands were collected and analysed by using the Sustainable Society Index. The results indicate that the social sustainability level of the country of manufacture accounts for roughly 20% of the differences in t-shirt prices. Clothes made in more socially sustainable countries indeed tend to have higher prices. However, the difference in social sustainability is not significant between the high-priced and the luxury segments. Environmental and economic sustainability have little influence on clothing prices. The limitations and implications of assessing product sustainability through the lens of the country of manufacture are addressed.
TABLE OF CONTENT
1 Introduction
1
2 Theoretical Framework
3
2.1 Sustainability 3 2.2 Country of Manufacture 5 2.3 Price 82.4 Price and Country of Manufacture Relationship 10 2.5 Hypothesis Development 11
3 Research Design
13
3.1 Research Questions and Objectives 13
3.2 Research Approach 13
3.3 Data Collection Process 14
3.4 Using Secondary Data 16
3.5 Example 18
4 Analysis
19
4.1 Simple Linear Regression (Research Question 1) 19 4.2 One Way Analysis of Variance (Research Question 2) 23
5. Discussion
27
5.1 Price and Sustainability 28 5.2 Competitive Pricing leads to Overconsumption 31
LIST OF ABBREVIATIONS
ANOVA: Analysis of Variance BO: Country of Brand Origin CBL: Cripple Bottom Line COD: Country of Design COM: Country of Manufacture COO: Country of OriginCSR: Corporate Social Responsibility ILO: International Labour Organization JRC: Joint Research Center
SSF: Sustainable Society Foundation SSI: Sustainable Society Index
LIST OF FIGURES
Figure 1 Conceptual Model
Figure 2 Multilevel stratified probability sampling of t-shirts
Figure 3 Means of Human Wellbeing scores in different price segments
LIST OF TABLES
Table 3.1 Research Design Table 3.2 Extract from Data table Table 4.1 Data Description
Table 4.2 Correlations between Price and the three indicators of the SSI Table 4.3 Result of linear regression analysis for hypothesis 1
Table 4.4 Result of linear regression analysis for hypothesis 2 Table 4.5 Result of linear regression analysis for hypothesis 3 Table 4.6 Descriptive statistic for price segments
Table 4.7 Tests of Equality of Human Wellbeing means Table 4.8 Multiple comparisons of Human Wellbeing means Table 5 Accept or Reject hypotheses
1 INTRODUCTION
In most societies, clothing is more than just textile worn by human beings. It is laden with meaning and significance. Firstly, it is an instrument for individual enhancement as clothing is associated with social status. Secondly, clothing is used as a form of social control, for instance when people are required to dress accordingly to their social identity. Furthermore, clothing is one of the first consumer goods that became widely available, contributing to consumerism (Crane, 2000). It is currently believed that we are going through an ‘ethics era’ and consumers are becoming more concerned about sustainability issues as regards clothes (Crane and Matten, 2007; Barchiesi et al., 2016). The Brundtland report of 1987 provides the most popular definition of sustainability as “to meet the needs of the present generation without compromising the ability of future generations to meet their own needs” (WCED, 1987).
The media most often focus criticism on the cheaper clothing brands, such as Primark and H&M. This results in heavy scrutiny of the sustainability efforts within the garment industry and thus sustainability issues have gained importance for both low-priced and high-priced fashion companies (Arrigo, 2015). However, designer and luxury brands are often less scrutinised because they have an established reputation around high quality items and therefore face little pressure to invest in sustainability practices (Davies et al., 2012). More expensive brands are less likely to be linked with negative sustainable practices. Furthermore, consumers can wrongly perceive that ethics and business are two different aspects, which indicate that ethical products will always lead to higher costs. This misconception contributes towards creating a belief that higher priced products are automatically more ethical than cheaper products. Harris and Freeman (2008) call this phenomenon ‘Separation Fallacy’. In luxury consumption, Davies et al. (2012) call this ‘Fallacy of Clean Luxuries’ where consumers believe that luxury products have few significant negative social or environmental impacts, based on the simple assumption that they symbolise prestige and highly valuable.
production practices. The truth is that the world's natural resources are fast depleting at current level of mass production (Claudio, 2007; Akenji, 2014). Hence, products need to be produced in a more sustainable way. Additionally, the most significant negative impacts of the garment industry as regards sustainability occur during the manufacturing process of the clothing (Emery, 2012). Furthermore, companies are less likely to increase their sustainability practices more than required in law of the countries where they operate (Yang and Rivers, 2009). Product sustainability can therefore be assessed through the lens of the sustainability of the country of manufacture. The Sustainable Society Index makes it possible to compare the overall level of sustainability of different countries. This index combines various indices into three indicators which represent the aspects of sustainability (Human, Environment, and Economic Wellbeing ) on country-level. 1
Whereas the sustainability practices of low priced fashion has been scrutinised, the high priced fashion has been neglected by the media. Yet, limited research has been conducted so far about the relationship between sustainability and price within the garment industry. Similarly can be said for the price-sustainability linkage in general. Therefore, with the underlying goal to include fashion across all price segments, the research objective is to examine the relationship between product sustainability and price within the garment industry.
Thus, the main Research Question is:
Does sustainability of country of manufacture influence clothing price?
Followed by the second research question to give deeper insight on the research objective: How does sustainability vary across different price segments?
The remainder of the thesis is organised as follows: Chapter two introduces the theoretical framework with three hypotheses. The research design is provided in chapter three. The findings of the empirical research will be presented in chapter four and discussed in chapter five. Finally, chapter six concludes the thesis.
Some terms are written with capital initiations (e.g. Price, Economic Wellbeing, etc.) for the purpose of labelling the
1
2 THEORETICAL FRAMEWORK
We turn attention to the burgeoning theoretical literature, however we made no pretence of being complete within the scope of the covered topic. The theoretical framework first introduces general theories of sustainability and the triple bottom line. Secondly, the concept of country of manufacture and the garment industry's impacts on sustainability are reviewed. Thirdly, the focus lies on pricing strategies within the garment industry and price quality relationship theories (due to a lack of sustainability-price relationship theories in literature). Fourthly, the connection between price and country of manufacture theories will be discussed. Finally, the hypotheses are constructed based on a summary of the theories.
2.1 SUSTAINABILITY
The scale of the environmental and social problems has become increasingly clear. Key drivers for sustainability are the current highly destructive patterns of wealth creation and distribution, characterised by large and increasing gaps between rich and poor (Elkington, 2004). It is accepted that the responsibility for tackling those problems falls on the present generation and should not be pushed on to future generations (Elkington, 1994). Furthermore, with the worsening sustainability issues, pressures will continuously build on corporations and governments to make a transition towards sustainability (Elkington, 2004).
Sustainability can be a 2 + 2 = 5 (or even 50) game, thus difficult to define and quantify (Elkington, 1998). Therefore, it is no surprise that the relevant literature is abundant with studies on sustainability. The Brundtland report provides the most popular definition of sustainability: “To meet the needs of the present generation without compromising the ability of future generations to meet their own needs” (WCED, 1987). Elkington, in an effort to define sustainability, coined the term triple bottom line (TBL) of people, planet, and profit corresponding to social, environmental, and economic aspects (Elkington, 2004). According to the TBL theory, economic, social, and environmental aspects need to be in balance in order to reach sustainability goals (Elkington, 1998).
the TBL is difficult to quantify and measure. Slaper and Hall (2011) suggests many indicators that can be used to measure TBL which are discussed in the following section. Triple Bottom Line
Social sustainability has drawn considerably attention from both academics and practitioners. It is defined as a society in which life is continuously enriching and enhancing (Weingaertner and Moberg, 2014). However, this broad definition of social sustainability is often vague due to the fact that it is built on concepts of community, society, and inclusiveness which themselves have no clear definitions (Davidson, 2007). Regardless, there is a fundamentally common understanding of social sustainability (Weingaertner and Moberg, 2014). Social sustainability can be measured in terms of quality of life, human dignity, social justice, social homogeneity, equitable income distribution, and employment (Sachs, 1999; Littig and Grießler, 2005; Slaper and Hall, 2011).
Environmental sustainability is defined as a state of balance, resilience, and interconnectedness that allows society to satisfy its needs without exceeding the capacity of ecosystem services (Morelli, 2011). In order to preserve the ecosystem services for the longest period of time, people must live within the boundaries of the biophysical environment (Moldan et al., 2012). Slaper and Hall (2011) suggest that environmental sustainability can be measured in terms of air and water quality, energy consumption, natural resources, solid and toxic waste, and land use/land cover.
Given the financial and economic crisis, the economic system came under close scrutiny. Therefore, it is widely accepted that maintaining a sustainable economic growth is essential (Moldan et al., 2012). From a traditional economic standpoint, environment and ecosystem services are functions of an overall financial analysis (Morelli, 2011). However, economic sustainability means that economic issues should be adequately addressed on their own merits and with no apparent connection with the environment (Moldan et al., 2012). Measurements such as of income or expenditures, taxes, business climate factors, employment, and business diversity factors are suitable to evaluate economic sustainability (Slaper and Hall, 2011).
through which products and services are priced and assessed (Akenji, 2014). However, a problem with tangible product sustainability is the difficulty in assessing social and environmental aspects (Toppinen et al., 2013). We argue that the level of sustainability of a country can reflect the level of sustainability of a company’s production within that country for two reasons: (1) sustainability issues within the garment industry mostly circle around manufacturing process (e.g., working conditions, wages, worker rights, natural resources usage, energy consumption, greenhouse gases emission, waste, etc.); (2) a company will be less likely to increase their sustainability practices when they operate in a country with few laws or where laws are not enforced (Yang and Rivers, 2009; Emery, 2012). Thus, this paper assesses the sustainability of a product via the sustainability of the country of manufacture (COM).
2.2 COUNTRY OF MANUFACTURE
2.2.1 WHAT IS COUNTRY OF MANUFACTURE?
Country of origin (COO) is a growing complex umbrella term which includes COM, country of design (COD), and country of brand origin (BO) (Hamzaoui-Essoussi et al., 2011; Lee et al., 2013). Most companies worldwide promote both the BO along with COM for their brands and products. For instance, Apple’s iPhone advertises ‘Designed by Apple in California and Assembled in China’ (Arora et al., 2016). COM is defined as a country that produces or assembles a product (Insch and McBride, 2004). In the global market, many products are no longer manufactured or made in its country of BO (Wang, 2011). COM can vary, for instance, when a company moves the manufacturing process to another country or produces a product in different locales (Hamzaoui-Essoussi et al., 2011).
To put it simply, a ‘Designed in’ label usually represents BO while a ‘Made in’ label represents COM (Aiello et al., 2009; Arora et al., 2015). Consumers are often aware of brand origins and where the manufacturing of products take place (Ahmed and d'Astous, 2008). Due to a production tradition that boasts the COO, a ‘Made in’ label increases the competitive advantages of products (Roth and Romeo, 1992). This paper focuses solely on COM as a research phenomenon.
impacts of their purchases in regard to garment products (Goworek, 2007; Arora et al., 2015).
2.2.2 IMPACTS OF MANUFACTURING PROCESS
Despite positive effects, decades of neoliberal economic globalisation has enabled global capital to flow more freely across national borders which resulted in many negative impacts as well (Yu, 2008). The most significant negative impacts within the garment industry in regards with sustainability occur during the manufacturing process of the clothing (Emery, 2012). Sustainability practices of corporations operating in developing countries with few and loosely enforced laws are often found to be low (Yang and Rivers, 2009). A variety of brands such as Nike, Benetton, Adidas, and C&A have been accused for problems with environmental pollution and inhumane working conditions in the factories where they chose to outsource the production of their clothes (Seuring and Sarkis, 2008). Ethical issues in the clothing industry relate mainly to environmental and social sustainability as well as economic which are discussed in the following paragraphs (Goworek, 2007).
Social impacts of labour-intensive industries, such as the garment industry, can be referred to working circumstances for manufacturing workers. Extensive media exposures of notorious labour practices in global factories have remade the word ‘sweatshop’ a well-known term amongst society (Yu, 2008). A common effect of the fragmented supply chain practices of corporations is unfair and exploitative working conditions in developing countries (Drebes, 2014). For instance, low price fashion company Primark has been criticised in the media for producing its clothes in factories in Bangladesh which pay less than 0.11 EUR (1 SEK) per hour and provide poor living conditions to their employees 2
(BBC, 2008a).
The production process of garment has experienced serious environmental problems linked to exhaustive usage of natural resources and chemical products resulting in negative environmental impacts (De Brito et al., 2008; Lakhal et al., 2008). Earth’s natural resources are unable to keep on supporting the present level of mass production and the volume of landfills from the disposal of garments is expanding everyday (Claudio, 2007). Cotton is the most common textile to produce organically. Despite that, organic cotton production accounts only for 0.04% of the global cotton industry. As a result, the standard cotton industry is responsible for 11% of the worldwide pesticide consumption and creates significant environmental problems (Kooistra and Termorshuizen, 2006). Nevertheless,
All currency exchanges are rounded
some fashion retailers aim to produce environmentally friendly clothes. One example is Patagonia, a company with the mission to “give maximum attention to product quality while striving to do no harm to the environment” which uses organic cotton (Chouinard and Brown, 1997).
For economic aspects, it is unclear whether the expanded export manufacturing of garments in developing countries such as Cambodia and Laos is reflected in the development of the domestic economic performance (Rasiah, 2009). Companies often concentrate the knowledge-intensive activities (e.g., product development and strategic planning) in western countries while the manufacturing process frequently finds place in the Global South. It is accepted that the garment industry is an important factor in East Asia’s export growth. However, one can question whether international trade is a basis of continuous economic growth in developing countries for the reason that low skilled and paid assembly oriented export activities do not seem to lead to genuine industrial upgrading (UNIDO, 2004).
2.2.3 DRAWBACKS OF COUNTRY OF MANUFACTURE PERSPECTIVE
2.3 PRICE
The purpose of price is to express and quantify the value of products. Thus, price itself can be defined as the value of a product (Dibb et al., 2016). To the consumer, price is the exchanged value for a product or service. According to traditional marketing literature, various factors such as, inter alia, cost, brand value, and economies of scale are influential on the price decision (Dibb et al., 2016; Kotler and Armstrong, 2016). Kotler and Armstrong (2016) define three different pricing strategies: customer-value based, cost-based, and competition based pricing. Companies use price together with other aspects to distinguish their products from those of their competitors. Price is a key aspect for companies since it directly relates to the generation of total revenue. However, a product or service can compete either on a price or on a non-price basis. Whereas, price competition is a marketing strategy that emphasised price as an issue, such as equal to or lower than the prices of competitors. Non-price competition is a strategy that emphasises other aspects of a product, for instance quality. However, an increase in price often leads to reduction of customers (Dibb et al., 2016).
Many consumers use price as an indicator to judge the quality of a product or service. But, is a higher price truly a guarantee for higher quality, even for higher sustainability? Our literature review indicates that there is a lack of theories concerning the relationship between price and sustainability. Therefore we have chosen to interpret the price and quality relationship into price and sustainability relationship.
2.3.1 FALLACIES
The correlation between price and quality depends on the information available to consumers. A positive correlation between price and quality is most expected when product information is available (Garvin, 1984). Thus, consumers should be able to obtain enough information to evaluate product quality. If this is not possible, they rely on other aspects when making the assessment, including comparative pricing (Riesz, 1979).
There are many studies of the price-quality relationship that has yielded highly consistent outcomes that the price-quality correlations are positive but often found to be weak (Riesz, 1979; Gerstner, 1985; Kirchler et al., 2010). On the other hand, a few studies have found a stronger correlation between price and quality (see Gabor and Granger, 1966). Therefore, price is not a guarantee for quality; higher prices appear to be poor signals of higher quality (Gerstner, 1985; Kirchler et al., 2010). Regardless, Olbrich and Jansen (2014) state that it is rare to find high priced products that offer poor quality.
Harris and Freeman (2008) propose ‘Separation Fallacy’ which suggests that consumers can wrongly perceive that ethics and business are two different aspects and therefore indicate that ethical products will always lead to higher costs. This contributes towards creating a belief that higher priced products are automatically more ethical when compared to cheaper products. In the sustainability context, Davies et al. (2012) propose the ‘Fallacy of Clean Luxuries’ implying that consumers usually perceive a higher price with more sustainable. However, luxury brands have also been reported for sustainability issues, such as Prada for the exploitation of illegal Chinese immigrant garment workers in Italian sweatshops (ibid.).
To sum up, the literature of price and quality suggests that higher prices do not necessarily indicate higher quality. Despite that, consumers still use prices as cues for higher quality. The misconception does not only apply for quality, but consumers also usually perceive a higher price with being more sustainable. Furthermore, consumers use COM as a cue to evaluate the quality of a product (Iyer and Kalita, 1997). Therefore, one can argue that it is possible to translate the relationship between price and quality to the relationship between price and COM. Section 2.4 will go more in depth.
2.3.2 PRICING WITHIN THE GARMENT INDUSTRY
environment as it increases simultaneously the usage of natural resources and waste (Cline, 2012).
Current market data of the garment industry indicates that retailers and brand marketers are implementing a price tier strategy (Fratto et al., 2006). Price tiers are translated into price segments in the context of this paper. Segments are used to categorise brands into different price or quality segments. A corporation can operate in different segments by having multiple brands. The number of segments within an industry is product or market specific. However, segments normally describe three markets based on ‘good, better, best’ (Dolan and Simon, 1996). Fratto et al. (2006) translated these three markets into price segments within the garment industry: economy, middle and premium (whereby premium is described as affordable luxury in this context). The luxury segment is not represented in this strategy since price is not explained rationally but rather based on the prestige of brands within this segment (Kapferer et al., 2014). The price segment strategy first determines the price of the products beforehand setting the costs of making it. Thus, price sets the position which then dictates the acceptable cost level (Dolan and Simon, 1996).
2.4 PRICE AND COUNTRY OF MANUFACTURE RELATIONSHIP
As we argued prior in section 2.1, measuring product sustainability is limited into measuring sustainability of the COM to ensure that the complexity of sustainability is manageable. Price in relation with the COM will be reviewed in this section.On the other hand, an International Labour Organization (ILO) study about the global garment industry found that labour costs indeed are important but not the most critical factor in establishing the competitiveness of a manufacturing region (ILO, 2000). This indicates that other factors have the same or a higher impact on the cost price than wages (Pollin et al., 2004). Besides, research from Datta and Christoffersen (2005) points out that the benefits of economies of scale are increasingly important within the garment industry. Economies of scale became to gain importance in the cost price of products, while labour cost decreased its importance due to the fact that technologies are getting more advanced. However, in developing countries, the awareness of environmental and human rights are often found to be low (Shen, 2014). Apparel companies take advantage of lower environmental and social awareness and looser environmental regulatory systems in those countries in the pursuit of further lowering production costs (Nagurney and Yu, 2012). The fact that the manufacturing process is being outsourced in order to reduce costs, implies that consequently the cost price of a piece of clothing decreases.
2.5 HYPOTHESIS DEVELOPMENT
Figure 1: Conceptual Model (Source: Authors)
Thus, the following hypotheses have been developed based on the theories. Figure 1 is the conceptual model for the hypotheses.
Hypotheses
H1: Social sustainability of country of manufacture positively
influences the price.
H2: Environmental sustainability of country of manufacture
positively influences the price.
H3: Economic sustainability of country of manufacture
positively influences the price.
3 RESEARCH DESIGN
Table 3.1 shows the research design outline. The outline is based on the four questions that a research design should answer according to Yin (2014).
3.1 RESEARCH QUESTIONS AND OBJECTIVES
The purpose of this paper is to explore the relationship between product sustainability and price within the garment industry. The following research questions are conducted with the aim to give insight into the research objective:
Does sustainability of country of manufacture influence clothing price? How does sustainability vary across different price segments?
Yilmaz (2013) suggests that a quantitative study should begin with hypotheses and theories. Hence, the hypotheses proposed in the previous chapter will be tested in order to answer the research questions.
3.2 RESEARCH APPROACH
This study examines the relationship between price and sustainability of COM based on the sustainable society index (SSI) score with a statistically quantitative approach. The price and SSI scores are the raw data input for the analysis. The SSI is used to quantify the data with the aim to measure and analyse the price-sustainability relationship within a logical, reductionistic, and deterministic framework (Denzin and Lincoln, 1994; Yilmaz, 2013).
Table 3.1 Research design
What is the phenomenon? 3.1 Research questions and objective
How to research? 3.2 Research Approach
Which data to collect?
Philosophically, the quantitative paradigm is based on positivism. The ontological position of the quantitative paradigm is that there is only a singular truth, an objective truth that exists separately from human perception (Yilmaz, 2013). Epistemologically, the researcher and the researched are independent entities, and it is of importance to put a distance between themselves and what is being studied (Sale et al., 2002; Yilmaz, 2013). By doing that, the authors are capable of investigating a price-sustainability relationship phenomenon without altering it or being altered by it (Sale et al., 2002).
3.3 DATA COLLECTION PROCESS
Some practical activities of daily life: a chef takes one piece of spaghetti out of the pot to know if the pasta is cooked; a consumer tries food samples in the supermarket before purchasing (Gobo, 2004). The scientific sampling procedure is the same, whether conducted within social or natural science. Defining sampling units clearly and planning the process accordingly are sine qua non to avoid sloppy and empirically shallow research (ibid.). This paper employs sampling technique to collect the quantitative data necessary to test the hypotheses.
Generation of quantitative data often requires probability sampling. This sampling technique is used since it leads to a larger number of brands selected to be representative for the garment industry (Teddlie and Yu, 2007). Researchers need to select a large range of samples to be able to generalise the findings from the samples (Yilmaz, 2013). Moreover, Teddlie and Yu (2007) suggest that the total sample size should consist of at least 50 units. T-Shirt Mystery shopping
Mystery shopping is a method to externally measure the quality of the service or compliance (Van der Wiele et al., 2005). In this case, we chose to ‘mystery shop’ the 3
cheapest t-shirts made of at least for 90% out of cotton from each brand as products to be assessed for sustainability. T-shirts were chosen for the following reasons: T-shirts are worn by both men and women and t-shirts are versatile products and therefore available in many stores. Thus, a t-shirt is a usable sample item for this study due to its comparability. The following two types of data were collected from the t-shirts: (1) the list price and (2) the COM on the label. A pilot test in Visby was conducted prior to the empirical research in order to ensure that there would be no difficulties in collecting the data. The complete data set was collected in Stockholm during two days of mystery shopping. The data was collected together, during which one author checked the price and
We did not actually buy the t-shirts
COM and the other author wrote down the information. Figure 2 illustrates the process of probability sampling of t-shirts.
Figure 2: Multilevel stratified probability sampling of t-shirts (Adapted from Teddlie and Yu, 2007) 1. Sampling physical stores in Stockholm
COM information is not available in online stores. Therefore, physical stores are most relevant to collect the data for the research as only in this way it will be possible to gather information of both the variables (price and COM). Stockholm was the selected geographic area due to the dense distribution of clothing stores. Further, clothes of different price segments are available in Stockholm, which makes this city a good starting point for the sampling. It is doubtful if random locations lead to different variations in price. Therefore, the following shopping streets and malls were selected in order to generate representativeness of different price segments: Luxury department store Nordiska Kompaniet (NK) and Åhlens which offers a wide variety of different brands, high-end shopping street Biblioteksgatan, and Drottninggatan where many cheap chain stores are located. We used the cluster sampling method, which is a popular compromise between random and stratified sampling (Teddlie and Yu, 2007). Cluster sampling is chosen due to the existing price segment strategy within the garment industry as discussed in the literature chapter.
2. Sampling brands
The brands were randomly selected based on the availability in the store. A t-shirt of one brand can have different prices depending on the locations in which it is available (prime shopping location, non central location, or online store). Nonetheless, the data is not affected because fluctuations in prices are extremely minimal.
1. Sampling physical stores in Stockholm
2. Sampling brands
3. Sampling t-shirts
The aim is to examine the cheapest available t-shirt, which is at least for 90% made out of cotton, in store of each brand. Focusing on one sub-product reduces the amount of data that needs to be collected which makes it possible to include a larger number of brands in the research. Thus, 184 t-shirts were examined, 11 of which were eliminated due to lack of COM information. 173 t-shirts were eventually used for the analysis.
3.4 USING SECONDARY DATA
It is worth repeating that the goal of this paper is to examine the relationship between price and sustainability through the lens of COM. The quantitative research requires a numerical form of the two types of data namely: price and COM of t-shirts. While the prices are already collected in a numerical form, the COM is not. Hence, it is of importance to quantify the COM. We chose the Sustainable Society Index (SSI) as a tool to quantify the sustainability of COM since the SSI satisfy the criteria in the theory of this study.
3.4.1 SSI INTRODUCTION
The Sustainable Society Foundation (SSF) in the Netherlands has been developing the SSI since 2006 with the aim to measure at a glance the sustainability of 154 countries in three indicators (Social Wellbeing, Environmental Wellbeing, and Economic Wellbeing) encompassing 21 various sub-indicators (Van de Kerk and Manuel, 2008; Seppälä et al., 2016). The sub-indicators conform with Slaper and Hall’s (2011) measurement for sustainability discussed in the theoretical framework. For instance, sub-indicators Sufficient Food, Sufficient to Drink, Safe Sanitation, and Healthy Life fit well to quality of life measurement; Energy Usage and Energy Saving fit well with energy consumption measurement; etc. The SSI, which includes data for each individual indicator, can be accessed on the world wide web . The 2016 SSI, the latest version, is used for this research. 4
Shen et al. (2014) used the SSI to evaluate sustainability performance of the countries in fashion firm H&M’s supply chain. Strähle et al. (2015) suggest that it can be beneficial to use the SSI as a tool to evaluate sustainability of the supplier selections of firms.
It is not recommended to combine the economic, social and environmental components into an overall sustainability index since there is a negative correlations between indicators. The Environmental Wellbeing strongly and negatively correlates with the
SSI website: http://www.ssfindex.com/
Economic Wellbeing and Human Wellbeing. Human and Economic Wellbeing appear to go hand-in-hand for most of the countries, but at the cost of Environmental Wellbeing (Saisana and Philippas, 2012). Therefore, all the three wellbeing indicators will be tested separately.
3.4.2 SSI IN PRACTICE
The decision to use the SSI instead of other indices is based on the following reasons: I. There are many intentions on measuring sustainability but only few of them have an
approach that includes the TBL (Van de Kerk and Manuel, 2008; Singh et al., 2012). The SSI is based on the TBL definition and includes all three dimensions of sustainability: human, environmental, and economic.
II. 154 countries are included in the index which accounts for 99% of the world population. Thus, the SSI is much broader in scope than others indices that only represent a specific geographical area, such as Europe.
III. The indicators are data compiled from various world institutional indices such as World Bank, Food and Agriculture Organization, ILO, etc. (Saisana and Philippas, 2012) (for complete indicators and sources see Appendix 1). Therefore, the index comprehensively measures many aspects of sustainability.
IV. The index has been audited in 2012 by the Joint Research Center (JRC) of the European Commission. The JRC considers the SSI as a basic and quantitative method for observing and measuring human and environmental systems worldwide. Besides, the JCR implies that the SSI is a conceptually and statistically solid tool, not driven by methodological assumptions, which is broadly applicable for a continuous assessment of human and environmental systems. Hence, the SSI is a benchmark for future developments and reports on the current state of society (ibid.).
To sum up, the conceptual framework of the SSI is understandable, meets the requirements of the European Commission’s JCR and is relevant for assessing the development of nations in a economic, human, and environmental wellbeing sense (Rodríguez-Rosa et al., 2017). Besides the advantages, are also limitations to be found for using the SSI as an analytical tool in the scope of this research:
focus on a one certain industry or sector. In this case, it means that not all the 21 indicators used to analyse the COM can be related to the manufacturing process within the garment industry. For that reason is the SSI not a tool to completely profile fashion firms (Strähle et al., 2015). Regardless, we have collected enough samples in order to generalise the use of the SSI as well as the result.
II. The SSI still has drawbacks such as subjectivity, due to the assumptions in estimating the measurement error in data (see Singh et al., 2012).
III. Despite the fact that the SSI consists of a variety of different indicators is an error in data possible due to subjectivity on including or excluding indicators within the index (Pissourios, 2013).
3.5 EXAMPLE
A (brand) t-shirt with the list price at 1699.00 SEK and made in China. The price is measured in Swedish Krona (SEK), (1 EUR ≈ 9.64 SEK). The COM of the t-shirt is China which can be quantified by using three indicators from SSI. The indicators are measured at a 0 to 10.0 scale with one decimal. Table 3.2 illustrates the example which is extracted from the complete dataset (see Appendix 2 for the complete dataset).
Quantitative data in a raw form, which means, before the data is processed and analysed, convey in general little meaning to the public. Raw data, therefore, needs to be processed to make them useful and understandable (Saunders et al., 2009). The next chapter demonstrates the analysis of the data.
Table 3.2 Extract from data table
Price (SEK) COM WELLBEINGHUMAN ENVIRONMENTAL WELLBEING ECONOMICS WELLBEING
4 ANALYSIS
This chapter provides a statistical analysis in order to answer the two conducted research questions:
Does sustainability of country of manufacture influence clothing price? How does sustainability vary across different price segments?
The analysis is twofold. Regarding the first research question and the testings of three hypotheses, a simple linear regression analysis was used to determine the relationship between price and the three indicators of the SSI. For the second research question, a one way analysis of variance (ANOVA) was conducted to explore the difference between price segments. SPSS Version 24.0 was used to analyse the data. The predetermined level of significance is 0.05. Thus, for a hypothesis to be accepted, p-value (sig.) needs to be less than or equal to 0.05. It is important that the significance is lower or equal to 0.05 to ensure that the findings are not by chance (Field, 2009).
4.1 SIMPLE LINEAR REGRESSION (RESEARCH QUESTION 1)
4.1.1 DESCRIPTIVE STATISTIC
The number of t-shirts used for the analysis is N = 173 (see Table 4.1). The dependent variable Price ranged from 24.75 to 6890.00, with a mean of 649.02 and a standard deviation of 835.46. Concerning the independent variables, Human Wellbeing scores of COM ranged from 5.5 to 8.5, with a mean of 7.12 and a standard deviation of 0.72. The second independent variable, Environmental Wellbeing scores ranged from 2.6 to 6.4, with a mean of 4.70 and a standard deviation of 0.73. For the last independent variable, Economic Wellbeing scores ranged from 2.5 to 6.9, with a mean of 5.01 and a standard deviation of 1.03.
Table 4.1 Data Description
N Range Min Max Mean Std. Deviation
Price 173 6865.25 24.75 6890.00 649.02 835.4585
Human Wellbeing 173 3.0 5.5 8.5 7.125 0.7239
Environmental Wellbeing 173 3.8 2.6 6.4 4.702 0.7320
4.1.2 NORMALITY
In statistics, assumptions for data need to be examined for the sake of making either parametric or nonparametric analyses. The assumption of normal distribution of data needs to be met in order to conduct a parametric linear regression. To check whether the distribution of scores is normal, one can examine the values of skewness and kurtosis. Skewness measures asymmetry and kurtosis measures tailedness of the probability distribution of a variable. The further skewness and kurtosis values are from 0, the less likely it is that the data is normally distributed. The Kolmogorov-Smirnov test determines whether the data is normally distributed (Field, 2009). Appendix 3 shows the skewness, kurtosis, and Kolmogorov-Smirnov tests of all the variables, as well as histograms and Q-Q plots to assess the normality visually.
The dependent variable Price was non-normally distributed, with a substantial positive skewness of 4.196 and a leptokurtosis of 22.854. The values were therefore clustered to the left and peaked in the centre with heavy-tailed distribution, as shown in the histogram (Appendix 3.1). Therefore a logarithmic transformation was used to compute the data. ‘Price_log’ is the transformed data which showed an improved skewness of 0.236 and kurtosis of 0.913. The Kolmogorov-Smirnov test was still significant, meaning that the data was still non-normal. Despite that, George and Mallery (2010) suggest that values for skewness and kurtosis between -2 and +2 are considered to be acceptable to prove normal distribution. Therefore, this abnormality is unlikely to drastically affect the result.
4.1.3 CORRELATION
Table 4.2 shows the test of the correlation between price and the three indicators of the SSI using Pearson’s r at 2-tailed in order to test the statistical significance in both directions. Cohen (1992) suggests that a relationship can be defined as weak when r ≥ 0.1, medium when r ≥ 0.3, and strong when r ≥ 0.5. Price_log and Human Wellbeing are positively and moderately correlated, r = 0.445, p < 0.01. Thus, when social sustainability of the COM increases, price is likely to increase as well. The correlation between Price_log and Environmental Wellbeing is positive, very weak, and not significant, r = 0.033, p = 0.670 > 0.05. This result indicates that there is almost no correlation between price and environmental sustainability. Price_log negatively and weakly correlates to Economic Wellbeing, although non-significant, r = -0.139, p = 0.069 > 0.05. In other words, if a t-shirt is made in more economic sustainable country, it is likely to have lower price. This finding is however not significant.
Regarding the independent variables, Human Wellbeing is positively and weakly correlated with Environmental Wellbeing, r = 0.252, p < 0.01. Meaning that when Human Wellbeing increases so does Environmental Wellbeing. On the other hand, Economic Wellbeing is negatively and moderately correlated to Human Wellbeing (r = -0.334, p < 0.01) and negatively and strongly to Environmental Wellbeing (r = -0.720, p < 0.01). In other words, when Economic Wellbeing increases, Human Wellbeing decreases and Environmentally decreases. Although some independent variables are strongly correlated, multicollinearity is not a problem for simple linear regression (Field, 2009).
4.1.4 REGRESSION
A simple linear regression was conducted to explore the relationship between price and the SSI indicators. Price is the dependent variable, whereas the three SSI indicators are the independent variables. The R Square measures the portion of total variance in the price that is explained by the three separate SSI indicators. The p-value or sig. indicates if there is a statistically strong significance by using the model, as well as reject or accept the
Table 4.2 Correlations between price and the three indicators of the SSI
Mean Std. Deviation Price_log Human Wellbeing Environmental Wellbeing Economic Wellbeing Price_log 2.6285 0.38051 1 0.445** 0.033 -0.139 Human Wellbeing 7.125 0.7239 1 0.252** -0.334** Environmental Wellbeing 4.702 0.7320 1 -0.720** Economic Wellbeing 5.008 1.0267 1
hypothesis. The unstandardised regression coefficients B shows the impact and direction of a SSI indicator on price.
Hypothesis 1: Social Sustainability
H1: Social sustainability of country of manufacture positively influences the price.
In the case of H1, concerning the relationship between price and social sustainability, it can be reported that 19.8% (R2 = 0.198) of the total variance in price can be explained by the
Human Wellbeing score of the COM (Table 4.3). In another word, Human Wellbeing of COM can account for 19.8% for the differences in prices of t-shirts, while 80.2% of the differences in prices cannot be explained by Human Wellbeing.
By having a closer look, the regression coefficient showed an impact in a positive direction (B = 0.234; p < 0.01) as hypothesised. Which means that the price of a t-shirt is higher when it is made in country with a higher SSI score on Human Wellbeing. Further, there is a statistical significance by using the model, F(1,171) = 42.223, p < 0.01. Thus it can be assumed that the Human Wellbeing of COM has an explanatory power on the price of t-shirts. The first hypothesis (H1) is supported.
Hypothesis 2: Environmental Sustainability
H2: Environmental sustainability of country of manufacture positively influences the
price.
For the next hypothesis, which states that environmental sustainability has a positive influence on the price. Environmental Wellbeing indicator, 0.1% (R2 = 0.001) of the total
variance in price can be explained by this variable (Table 4.4). That is to say, the environmental Wellbeing score of COM on the SSI can account for 0.1% for prices of t-shirts. 99.9% of the variation in prices cannot be explained by Environmental Wellbeing. Furthermore, regression coefficient was positive (B = 0.017, p = 0.670) as expected from the hypothesis. So, the price of a t-shirt is higher when it is made in country with high SSI score on Environmental Wellbeing. However, the regression coefficient is extremely low
Table 4.3 Results of linear regression analysis for hypothesis 1
Model R Square F B Sig.
1 0.198 42.223 0.234 0.000a
that it might be mere chance. Nonetheless, the model of Environmental Wellbeing indicates no statistical significance (p = 0.670 > 0.05). This implies that the Environmental Wellbeing score of the COM does not have explanatory power on the price of t-shirts. Thus, the second hypothesis (H2) is unsupported.
Hypothesis 3: Economic Sustainability
H3: Economic sustainability of country of manufacture positively influences the price.
For the last hypothesis, 1.9% (R2 = 0.019) of the total variance in price can be explained by
the Economic Wellbeing score of the COM (Table 4.5). Specifically, Economic Wellbeing of COM can account for 1.9% for differences in prices of t-shirts, and 98.1% of the variation in prices cannot be explained by this variable.
The coefficient regression was negative (B = -0.051, p = 0.69) instead of positive as proposed in the hypothesis. Hence, the price of a t-shirt is higher when it is made in country with a lower SSI score on Economic Wellbeing. The model of Economic Wellbeing however indicates no statistical significance (p = 0.069 > 0.05). This implies that the Economic Wellbeing indicator neither has an explanatory power on the price of t-shirts. The third hypothesis (H3) remains unsupported.
4.2 ONE WAY ANALYSIS OF VARIANCE (RESEARCH QUESTION 2)
Since only Human Wellbeing has explanatory power on the price of a t-shirt while Environmental Wellbeing and Economic Wellbeing do not, one way analysis of variance (ANOVA) was used test in order to explore the differences in Human Wellbeing between price segments. The dataset is the same as the previous analysis but only Human Wellbeing and Price variables were used in this analysis. Continuous variable Price wereTable 4.4 Results of linear regression analysis for hypothesis 2
Model R Square F B Sig.
2 0.001 0.183 0.017 0.670a
a. Predictors: (Constant), Environmental Wellbeing
Table 4.5 Results of linear regression analysis for hypothesis 3
Model R Square F B Sig.
3 0.019 3.345 -0.051 0.069a
therefore categorised based Price Segment in the theory as following: Low-priced ≤ 250 SEK, Medium-priced ≤ 500 SEK, High-priced ≤ 1000 SEK, Luxury > 1000 SEK. A luxury segment was constructed for the reason that there were many t-shirts with prices ranged from 1000 SEK to 7000 SEK, which did not fit well with high-priced segment. In this way differences between segments could be explored.
4.2.1 DESCRIPTIVE STATISTIC
The numbers of t-shirts in each price segment are: 72 Medium-priced t-shirts (41.6%) represented the largest segment in the sample, followed by Low-priced with 42 t-shirts (24.3%), and High-priced with 36 t-shirts (20.8%); while 23 Luxury t-shirts (13.3%) was the least represented.
4.2.2 DIFFERENCES IN PRICE SEGMENTS
Two assumptions for Human Wellbeing need to be met in order to use ANOVA. For the first assumption of normality, the Kolmogorov-Smirnov tests showed significant (see Appendix 3.2), meaning that the data was different from normal. Nevertheless, the skewness of 0.408 and kurtosis of -1.251 were within acceptable range proposed by George and Mallery (2010). The second assumption is homogeneity of variances, which the Levene’s test showed significant, p < 0.01 (Table 4.7). Thus, the second assumption of homogeneity of variance is violated.
Field (2009) suggests using Brown-Forsythe and Welch tests in case of violating homogeneity of variances instead of normal ANOVA. Both Brown-Forsythe and Welch tests are statistically significant, p < 0.01. Therefore, there is a statistically significant difference in the means of Human Wellbeing amongst the different price segments. Post hoc tests were needed to check which price segments differ from others.
Table 4.6: Descriptive statistic for price segments
Post Hoc Tests
Since the data does not meet the homogeneity of variances assumption, Games-Howell post hoc test (Table 4.8) is recommended (Field, 2009). The test revealed that:
I. Low-priced is significantly different from medium-priced (p = 0.048 < 0,05), high-priced (p < 0.01), and luxury (p < 0.01). This implies that Human Wellbeing of COM of low-priced t-shirts is different from those of medium-priced, high-priced, and luxury. II. Medium-priced is significantly different from high-priced (p = 0.003 < 0.01), and luxury
(p < 0.01). Which means that Human Wellbeing of COM of medium-priced t-shirts is different from those of high-priced and luxury.
III. High-price and luxury are not significantly different from each other (p = 0.999 > 0.05). In other words, there is no substantial difference of Human Wellbeing of COM of high-priced and luxury t-shirts.
Figure 3 illustrates the difference in means of Human Wellbeing of price segments: low-priced at lowest, follows by medium price, then high-price, at last with luxury at highest. This also reconfirms the positive relationship between price and Human Wellbeing of COM, which is that the price of a t-shirt is likely to be higher when it is made in country with a high SSI score on Human Wellbeing.
Table 4.7 Tests of Equality of Human Wellbeing means
Sig.
Levene Statistic 0.000
ANOVA 0.000
Welch 0.000
Brown-Forsythe 0.000
Table 4.8 Multiple Comparisons of Human Wellbeing means Games-Howell test
(I) Price Segment (J) Price Segment Mean Difference (I-J) Sig.
Low-priced Medium-priced -0.2792* 0.048 High-priced -0.8472* 0.000 Luxury -0.8703* 0.000 Medium-priced High-priced -0.5681* 0.003 Luxury -0.5911* 0.000 High-priced Luxury -0.0231 0.999
5. DISCUSSION
This chapter discusses the findings of the empirical research. The findings will be reviewed in the context of the theoretical framework presented in chapter two. It is worth repeating that the purpose of this paper is to answer the following two research questions:
Does sustainability of country of manufacture influence clothing price? How does sustainability vary across different price segments?
At first the hypotheses will be either accepted or rejected. The relationship between price and social sustainability from a COM perspective will be discussed in the next section. The results indicate that only social sustainability of COM has an influence on price. Therefore, the discussion continues to focus on difference in social sustainability amongst the price segments. Afterwards, environmental and economic sustainability in relation to price are examined. Subsequently, the influences of competitive pricing and overconsumption within the garment industry are addressed. At last, the meaning of the lack of transparency about the COM will be reviewed.
Table 5. Accept or Reject hypotheses
Hypothesis Coefficient
(B) R2
Accept/reject significant
H1: Social sustainability of country of
manufacture influences the price of a t-shirt. 0.234 0.198
Accepted*
H2: Environmental sustainability of country ofmanufacture influences the price of a t-shirt. 0.017 0.001
Rejected
H3: Economic sustainability of country ofmanufacture influences the price of a t-shirt. -0.051 0.019
Rejected
Note: For a hypothesis to be accepted, the model must have p-value ≤ 0.055.1 PRICE AND SUSTAINABILITY
5.1.1 SOCIAL SUSTAINABILITY
The result of the empirical research confirms that price of clothing can be predicted by social sustainability. The explanatory power of social sustainability on price is roughly 20%, which means that social sustainability can account for 20% of differences in clothing price. Hence, the hypothesis for the social aspect of sustainability is supported. This indicates that the price of a t-shirt is likely to be higher when it is made in country with a higher SSI score on Human Wellbeing. Human Wellbeing represents the social aspect of the TBL in the SSI. Nine indicators are included in the SSI in order to measure social sustainability . Various of these nine indicators are relevant to social sustainability issues 5
related to the manufacturing process within the garment industry. The most prevalent ones, based on the theoretical framework, are: sufficient to drink, safe sanitation, good governance, and income distribution.
Various brands have been accused for social scandals related to poor working circumstances, for instance the lack of clean drinking water and low hygienic standards in factories (BBC, 2008a; Yu, 2008). The SSI indicators Sufficient to Drink and Safe Sanitation address those issues. As stated before, developing countries tend to have weaker human rights protection (Shen, 2014), which implies poor governance. Brands can make abuse of these weak human rights protection by for example demanding long working hours from garment workers. Besides, weak protection of human rights indicates that it is harder for employees to raise their voices against corporations. The weaker the community voice is, the less likely companies will adapt to sustainability practices (Yang and Rivers, 2009). Thus, countries with weak human rights protection are also countries that are less expected to force companies into a more socially sustainable direction.
Furthermore, literature suggests that companies started to outsource their production to countries with low wages in order to reduce production costs (Arora et al., 2015). Low wages are part of the income distribution indicator in the SSI. To illustrate how low the wages are: the monthly minimum wage (345 SEK or 36 EUR) of production workers in Bangladesh is lower than the list price of the most expensive t-shirt sampled (500 SEK or 52 EUR) from this very same country. In other words, even though living standards are different in Bangladesh comparing to Sweden, a Bangladeshi garment worker might not be able to buy one of the shirts he or she produced for the income that is earned in one month. However, study of the ILO (2000) points out that low wages are not the most
(1) Sufficient Food, (2) Sufficient to Drink, (3) Safe Sanitation, (4) Education, (5) Healthy Life, (6) Gender Equality, (7)
5
important factor for choosing a location to outsource manufacture practices. Besides, economies of scale have gained importance versus low wages in the cost price of clothing. This implies that corporations do not only seek to produce in developing countries to take advantage of low wages, but production outputs are also of importance to those corporations (Datta and Christoffersen, 2005). Other aspects of social sustainability are equally or even more important when it comes to choosing a country to outsource the production. Poor governance is likely to be the most influential indicator, for the reason that poor governance within a country makes it easier for companies to force employees into long working days in order to reach a higher manufacture output.
Most of the media attention as regards sustainability within in the garment industry focusses on social issues. The empirical study supports that indeed social sustainability has the highest influence on price of all three aspects. However, especially cheap brands such as H&M and Primark have been heavenly scrutinised for their manufacture practices related to social sustainability. Therefore, the difference in social sustainability of the COM amongst different price segments is further explored.
As illustrated in Figure 3, the low-priced segment has a lower social sustainability score when compared to the medium- and the high-priced segments. Further, the medium priced segment also has a lower social sustainability score than the high-priced segment. However, the high-priced segment and luxury clothes are not significantly different from each other. This indicates that there is no difference in social sustainability between high price and luxury clothing. This result is in line with the literature where Davies et al. (2012) state that consumers misbelieve that luxury products have few significant negative social or environmental impacts which they call the phenomenon the ‘Fallacy of Clean Luxuries’. It is indeed a fallacy since there is no significant difference between the high-priced and luxury segment.
5.1.2 THE ‘OTHER’ SUSTAINABILITY
The level of environmental and economic sustainability of the COM have particularly little influences on price. Thus dubbed the term ‘other’ sustainability for both environmental and economic sustainability as insignificant and unimportant sustainability in the frame of sustainability-price relationship.
Hypothesis 2 was conducted to test whether the environmental sustainability score of the COM influences the price of clothing. The findings do not support this, therefore the hypothesis is rejected (see Table 5). Environmental Wellbeing and its sub-indicators that 6
are related to the manufacturing process of garment appear to be not of importance in clothing prices. Simply put, environmental sustainability has extremely little influence on price, as low as 0.1%. Thus, only 0.1% of the difference in prices of clothes can be explained by the environmental sustainability of the COM. Plus, the SSI indicates that developed countries do not necessarily score higher on the SSI’s Environmental Wellbeing indicator (see Appendix 2), which contributes to this result.
Hypothesis 3 was rejected as well (see Table 5), which indicates that the economic sustainability level of the COM has little significant influence on prices. 1.9% of the price different of clothes can be explained by the economic sustainability of the COM. Economic aspects affect the manufacturing process of t-shirts, yet those aspects do not affect the 7
prices. It is accepted that the garment industry is an important factor in export growth for some developing countries (UNIDO, 2004). However, it remains unclear whether the expanded export of manufacture of garments in developing countries promotes the domestic economic performance (Rasiah, 2009). Nevertheless, Isaksson et al. (2015) propose an adjusted TBL to the Crippled Bottom Line (CBL) which focuses solely on people (social) and planet (environmental) since they are the main stakeholders on the planet. This does not mean that profit is unimportant, but implies that profit is not the end itself but a means to an end. Therefore, economic sustainability can be a mean to achieve social and environmental sustainability.
One can argue that environmental and economic sustainability do influence the price of clothing, but the SSI model that was used in this research was not applicable. However, social sustainability of the model can significantly explain the price of clothing. Thus, there is absence of environmental and economic sustainability within prices. Additionally, regardless of how high the prices of clothes are, environmental and economic aspects of
(11) Renewable Water Resources, (13) Energy Use, (15) Greenhouse Gases
6
(17) Organic farming, (20) Employment
the COM play diminutive roles, even nonexistent, in prices. Furthermore, literature suggests that other factors such as brand reputations and economies of scale are more influential on the prices of clothes.
According to literature, garment manufacturing often takes place in countries with low environmental awareness. Yet, worker right issues in those countries are constantly in the spotlight, enabling social sustainability to overshadows the ‘other’ sustainability. However, as the CBL suggests, environmental sustainability is not less important than social sustainability, as the planet is not less important than the people living on it. Therefore, environmental sustainability should receive equal attention from the industry, the media, the government, and the consumers.
Additionally, sustainability practices of companies operating in developing countries, where there are few laws or where laws are not well enforced, are often found to be low. Unawareness and loose regulations of environmental issues allow the garment industry to exclude the environmental repercussions in their manufacture costs as well as in the prices of their products. This can contribute to why environmental sustainability has such little to no influence on price. For the luxury segment, prices are kept high in order to maintain the prestigious brand reputations (Kapferer et al., 2014). As stated before, ‘Fallacy of Clean Luxuries’ proposes the misconception of consumers that they believe luxury products have few significant negative impacts, based on the simple assumption that they are luxurious and prestigious. This is especially a fallacy regarding environmental and economic sustainability.
5.2 COMPETITIVE PRICING LEADS TO OVERCONSUMPTION
The competitive pricing strategy within the garment industry leads to environmental and social issues. The collected data for the empirical research supports the statement that the garment industry is highly competitive, as there are many t-shirts that have exactly the same price but are from different brands. For instance, eight different brand offer their cheapest t-shirt for a price of 199 SEK (21 EUR) and 21 brands for 299 SEK (31 EUR). Although, the same price does not necessarily means that the t-shirts are produced in the same country. A variety of COM is to be found amongst t-shirts with exactly the same price (see Appendix 2). However, it is unlikely for those brands to raise the prices of their t-shirts since many competitors sell a similar product for the same price.
(21 EUR) before it is manufactured. It is clear that this strategy focuses extremely on pricing and thus seems to pay little attention to the environmental and social issues that emerge with low cost manufacturing practices. Therefore, it seems unlikely that companies which are following this strategy will invest more money than necessary; for instance, sourcing clothes from organic cotton or providing fair working circumstances and living wages for garment workers. The question arises whether it is possible to produce clothes as cheap as it is done nowadays while still taking responsibility for people and planet during the manufacture process. Moreover, a significant negative consequence of the competitive pricing strategy is that the cheaper brands will remain selling their products for low prices. As mentioned earlier, low prices do encourage people to overconsume (Cline, 2012). Overconsuming poses per definition a negative effect on the environment since it simultaneously increases the usage of resources and the generation of waste.
5.3 ‘
UNCOM’ T-SHIRTS
6. CONCLUSION
In a society where growth and economy have become an end to themselves, the wellbeing of the people and planet has been put aside (Akenji, 2014). Therefore, it is imperative to pay attention to sustainability issues, such as the clothes we wear everyday, where those are made, under which circumstances, from which materials, and how we dispose them. The most significant negative impacts of the garment industry as regards sustainability occur during the manufacturing process of the clothing (Emery, 2012). These impacts should be an incorporated criterion through which products are priced and assessed. The reductionist view made it possible to minimise the complexity of sustainability. Therefore, the sustainability of a product is assessed via the sustainability of COM which is quantified by using the SSI. Despite some drawbacks of the SSI, the results of the research proves that the SSI is a useful model to measure sustainability. Furthermore, measuring sustainability should integrate indicators for wellbeing, and that is precisely what the SSI does. Thus, the SSI is a usable tool to asses the product sustainability of different industries. Be that as it may, the SSI is developed from a western perspective and therefore the chosen indicators are influenced by a western bias.
The empirical research reveals that social sustainability accounts for roughly 20% of differences in the list price of clothing. Thus, the chances that a piece of clothing is produced under fairer circumstances (e.g., better worker rights and higher wages) slightly increases when the price is higher. However, the social sustainability differences between the high-priced and the luxury segment are not substantial. For instance, a 999 SEK (103 EUR) piece of clothing is likely to have the same level of social sustainability as one of 6890 SEK (715 EUR). By contrast, there is lack of evidence to support that environmental and economic sustainability have influences on prices of clothes. This implies that higher priced clothes can be made under equally environmentally unsustainable circumstances as lower priced ones (e.g., more energy input, more greenhouse gases emission, and unsustainable natural resources usage). Altogether, the result of this paper supports the ‘Fallacy of Clean Luxuries’ proposed by Davies et al. (2012).
