Country-level sustainability performance and sustainability assessment of suppliers

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Country-level sustainability performance and sustainability

assessment of suppliers

The effect of institutional pressures on sustainability assessments and sustainability performance of clothing manufacturing suppliers.

MSc. Supply Chain Management

University of Groningen, Faculty of Economics and Business

June 21, 2020

Author

J. (Jurjen) Elzinga

Student number: 3847446

E-mail: j.elzinga.5@student.rug.nl

Supervisor

Prof. dr. J.T. van der Vaart

Co-Assessor

dr. ir. P. Buijs

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Abstract

The sustainability of firms is depending on how well their suppliers perform on sustainability. This has led to the need for sustainable supply chain management practices such as monitoring and assessment while external pressures from institutions such as governments and NGOs influence how firms respond to these sustainable supply chain management practices. This study investigates how the frequency of assessments influences the sustainable performance of suppliers, and how the country-level sustainability performance affects that relationship. This study uses survey data on the sustainability performance of 732 suppliers of a large clothing manufacturer and scores on the social and environmental performance of countries. The findings show that increasing the frequency of assessments has a mild positive effect on the sustainability performance of suppliers. The relationship is however not moderated by the institutional pressures of country-level sustainability performance. Overall, this study recommends to managers that frequent assessments are beneficial but should be used next to other practices such as collaboration.

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1. Introduction

The low profit-margins in the clothing industry cause heavy competition among manufacturers. Clothing manufacturing is very labor-intensive and by outsourcing and offshoring to developing countries, manufacturers try to limit costs (Księzak, 2017). This development led to one of the most global industries in the world, where regulations, employment conditions and environmental protection vary greatly from country to country (Perry & Towers, 2013). The heavy global competition that demands lower production costs led to poor working conditions for many laborers, lower wages and risks of environmental hazards (Claudio, 2007). An infamous example is Rana Plaza, a multi-story factory where cheap clothes are made for the western markets. Over 1100 people were killed and many more injured in this disastrous event (Burke, 2017). Working conditions, fair wages and safety standards were not up to standard, even now working conditions remain fragile (“After Rana Plaza: are workings in clothing factories better of?”, 2019). The rising awareness of consumers puts pressure on firms to meet the consumers’ expectations and to increase the supply chain transparency, i.e. consumers become more aware of the impact they have on the environment and they increasingly demand greener products from firms (Lintukangas, Hallikas & Kähkönen, 2015). These demands lead to increased pressure on firms to behave, manufacture and buy more sustainable (Centobelli, Cerchione & Esposito, 2018)

Sustainability is understood as the “development that meets the needs of the present without compromising the ability of future generations to meet their own need” (World Commission on

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Research has shown that assessments have a positive effect on the sustainability of suppliers (Gimenez and Tachizawa, 2012). With an assessment of a supplier, a buyer collects information and evaluates the suppliers’ commitment to sustainable practices (Rao, 2005). Furthermore, research by Foerstl, Reuter, Hartmann and Blome (2010) showed that without structured supplier assessment effective management can only be achieved randomly, which may lead to negative effects. Self-audits should be conducted at least annually, and regular self-inspections lead to more consistent compliance with regulations (Earnhart & Leonard, 2013). However, these results are found in within-firm assessments. To the best of our knowledge, no quantitative research has been done yet to analyze the influence of assessments on supplier sustainability performance. Furthermore, despite stating that frequent assessments are necessary to maintain the standards in the SC, Zhang, Pawar & Bhardwaj (2017) did not conduct quantitative research on the frequency of assessments and propose future quantitative research on suppliers’ assessments is still necessary.

The second gap this study is trying to fill is that it is not known what effects institutional pressures have on the actions of suppliers when responding to sustainable supply chain management practices. Research by Zhu and Sarkis (2007) state that the institutional pressures of coercive, normative and mimetic pressures can influence how firms respond to the adoption of green supply chain management initiatives. However, their study only focused on one country, and only looked at the environmental aspect of sustainability. In contrast, this study looks at the institutional pressures in different countries and looks at both the social and environmental aspects of sustainability. For firms, it can be interesting to know what effect these pressures have when assessing suppliers on their sustainability. For buying firms that want their SC to become more sustainable, they need to know the effect that assessments have in different countries. Knowing in what countries assessments have a smaller or larger effect, it can help determine the level of assessment frequency for buying firms. Therefore, the following research question will be answered:

“What is the effect of assessment frequency on supplier sustainability performance, and how do institutional pressures affect this relationship?”

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This study contributes to the literature by researching the effect of assessment frequency on factory sustainability performance. Research has shown that assessments and audits have a positive effect on the sustainability adoption of suppliers. However, what is missing is how the frequency of assessments influences sustainability performance. This study contributes that not only do assessments positively influence the sustainability of suppliers, increasing the number will be more effective. Furthermore, this research adds to the literature by using the institutional theory to look at the overall environmental and social performance of countries, and how this affects the relationship between assessments and factory sustainability performance. Up till now, research made use of pressures such as legal systems and cultural aspects, this study however takes a broader look and takes environmental health (e.g. air quality, sanitation) and ecosystem vitality (e.g. biodiversity and air pollution) into consideration. As well as life expectancy, literacy and standard of living are used in this study to represent institutional pressures. Overall this study gives insight into how country-level sustainability performance affects the relationship between assessment frequency and factory sustainability performance.

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2. Theoretical background

The theoretical background starts by explaining sustainability and SC sustainability. Additionally, since the setting of this study takes place in the clothing manufacturing industry, sustainability in that industry will be shortly reviewed. In section 2.2 practices of sustainable supply chain management such as mentoring & monitoring and assessment & collaboration are reviewed as well as looking at the relationship between these practices. To understand the external pressures firms experience, the institutional theory and isomorphic pressures are discussed in section 2.3. In section 2.4 the different hypotheses are discussed. Finally, in section 2.5 the conceptual model is pictured to show how the hypotheses relate to each other.

2.1 Sustainability

Sustainability is defined by the United Nations’ World Commission on the Environment and Development (1987, p.42) as: “development that meets the needs of the present without compromising the ability of future generations to meet their own need”. While sustainability used to be focused on the environment now sustainability encompasses three components: Environmental, Economic and Social sustainability (Mota, Gomes, Carvalho & Barbosa-Povoa, 2015). The triple bottom line suggests that not only can firms engage in activities that positively affect the society and the environment, but that those activities can also result in long-term economic benefits and can generate a competitive advantage (Carter & Rogers, 2008). This is in accordance with Zhan, Li and Chen (2018) who argue that firms who actively pursue sustainability are experiencing competitive advantages.

2.1.1 Supply chain sustainability

Firms on their own cannot succeed in sustainability since sustainability is affected by every partner in the supply chain (Kumar & Rahman, 2015). Therefore, to achieve sustainability across the supply chain it needs the help of every partner and needs to be managed. Sustainable supply chain management can be defined as: “the strategic, transparent integration and achievement of an organization’s social,

environmental, and economic goals in the systemic coordination of key inter-organizational business processes for improving the long-term economic performance of the individual company and its supply chains” (Carter & Rogers, 2008). Sustainable supply chain management, therefore, needs a high level

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The definition and understanding of sustainability and SC sustainability is still quite broad as it comprises of concepts such as not ‘harming the needs of the future’ and collaborating with all partners. However, to be more specific on how these concepts can be addressed, as this research takes place in the clothing industry, this paper also shortly addresses sustainability in the clothing industry.

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n literature, sustainable clothing is hard to define since there is no industry standard (Joergens, 2006). It has been described as ethical clothing, slow fashion (Harris, Roby & Dibb) as well as eco-fashion (Niinimäki, 2010). While there are different definitions and understandings of what sustainability in the clothing industry is, most literature has several concepts in common. Eco-fashion is described by Niinimäki (2010) as fashion that does cause little or no environmental impact, is produced in an ethical production system and makes use of recycled material. Joergens (2006) defines sustainability in the clothing industry as: “The principle to source garments ethically while providing good working

standards and conditions to workers, and to provide a sustainable business model in clothes.” Therefore,

sustainability can be seen as including aspects of social and environmental sustainability, causing no impact on the environment, but remain economically sustainable.

2.2 Supplier sustainability initiatives

The increased focus on sustainability and supply chain sustainability has led to the need for tools on sustainable supply chain management. Researchers have described the methods and practices of these sustainable supply chain management, where some took a broader scope and others more detailed. Hines and Johns (2001) describe a 4-stage approach of supplier environmental involvement that a firm can progress through, (1) questionnaires, (2) monitoring, (3) mentoring and (4) partnering. Meqdadi et al. (2015) addresses questionnaires as a type of monitoring and see stage 1 and 2 as the same. Hines and Johns (2001) see providing guidance for suppliers as a different step from mentoring, while Rao (2005) classifies this as an activity in mentoring. In this paper, the broader approach is chosen where only monitoring and mentoring will be addressed.

2.2.1 Monitoring and assessments

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by the buying firm and third-party auditors may be used to gather this information (Meqdadi et al., 2015). The evaluation practices are not focused on the traditional performance criteria such as price and quality but evaluate the triple bottom line of sustainability at the suppliers instead. These evaluation criteria are based on pre-determined performance standards. In literature, a wide variety of performance standards can be found in relation to the triple bottom line. Economic standards (e.g. cost, quality, service reliability) are complemented with environmental standards (emission, recycled materials, green packaging) and social standards (e.g. employment practice, health & safety and social commitment) (Khan, Kusi-Sarpon, Ahrhin & Kusi-Sarpon, 2018).

Assessments are a suitable method when a buying firm has a large and complex supply base and it reduces the information asymmetry if high levels of monitoring are applied (Meqdadi et al., 2015). Furthermore, it is a cost-effective practice since no on-site visits need to be made and is easy to produce and replicate. With this easy replication of assessments, a lot of data can be gathered on the performance of suppliers, which can help set new objectives (Hines & Johns, 2001). The use of pre-determined norms and standards can be valuable for the assessment of suppliers since requiring compliance to these standards is beneficial in risk avoidance and performance improvements (Harms, Hansen & Schaltegger, 2013). However, there are also some drawbacks to assessments. Assessments are focused on immediate results, while long-term goals may be more effective. It can also lead to a level of distrust between suppliers and buyers, high levels of monitoring can backfire if suppliers feel their autonomy is threatened, which may lead them to retaliate (Boyd, Spekman, Kamauff & Werhane, 2007). A last weakness of monitoring is the question: What to do with the information that is gathered?

2.2.2 Assessment vs mentoring

While sustainability is becoming a hot topic and SC’s are becoming more sustainable there is still a gap between the desired state and the current state. Whereas the assessment of suppliers is a useful tool for evaluating suppliers in terms of the triple bottom line, it does not necessarily mean that suppliers will also improve (Gimenez & Tachizawa, 2012). There is still debate going on if assessment alone can improve the sustainability of suppliers. Although Murray (2000) found support that assessment practices have a positive effect on the environmental and social performance of firms, Simpson et al. (2007) found that it only affects if relation-specific investments are made.

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that are required to build environmental capabilities (Meqdadi et al., 2015). There are a number of activities buying firms can undertake to mentor their suppliers: Sustainability education and training sessions, joint investments in sustainability projects, exchanging information skills and capabilities and setting common sustainability goals. Thus, by working together and having shared responsibility, firms can collaborate and improve sustainability. However, there are some weaknesses of mentoring; it requires a lot of resources and know-how to improve the sustainability of suppliers. Moreover, there is a risk of loss of investment and dependency on suppliers is higher than with monitoring, which can lead to supplier behaving opportunistic (Meqdadi et al., 2015; Vachon & Klassen, 2006). Overall, both strategies have their benefits and drawbacks and can be the most effective in different environments.

2.3 Institutional pressures

Firms are increasingly facing pressure from external stakeholders to adopt sustainable practices (Wolf, 2014). Firms are experiencing increasing pressure from governments; e.g. legislation to reduce pollution (Linton, Klassen & Jayaraman, 2007), market groups e.g. pressure from NGOs (Kumar & Rahman, 2015) and consumers; e.g. increased awareness puts pressure on firms to be more sustainable (Lintukangas et al., 2015). The institutional theory is relevant in stakeholder pressure literature since firms’ strategies and organizational decision-making are influenced by external social, political and economic pressures (Glover et al., 2014). The institutional theory states that firms make those decisions in order to look legitimate in the eyes of their stakeholders (Glover et al., 2014). Institutions are defined by Scott (2014, p.56) as “Institutions comprise regulative, normative and cultural-cognitive elements

that, together with associated activities and resources, provide stability and meaning to social life.”

Institutions consist of rules, norms and cultural-cognitive beliefs as well as associated behaviors and material resources. Thus, institutions are not a certain person or firm, but rather a social construct. The institutions define what is acceptable behavior and this will trigger how firms make decisions. In terms of adoption sustainability, according to the institutional theory, a firm will embrace sustainable development and will take sustainable-oriented decisions if a certain institution exerts power over the firm (Escobar & Vredenburg, 2011). Moreover, Zhu and Sarkis (2007) argue that a firm’s responsiveness to green supply chain management practices depends on institutional pressures.

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.3.1 Isomorphism

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Normative forces are pressures that are placed on organizations by market forces (Scott, 1995). In earlier

research, it was shown that consumers are increasingly aware of their environmental impact and are starting to prefer green products (Sarkis et al., 2011). These consumers put pressure on organizations to behave more sustainable. In addition, the moral values of a culture are influencing organizational strategies and decisions (Martinez-Ferrero & Garcia-Sanchez, 2015).

Mimetic pressures drive firms to copy actions of others especially in environments that create

uncertainty. As DiMaggio and Powell (1983) stated: “Uncertainty is a powerful mechanism that

encourages imitation.” In order to look legitimate in the eyes of their stakeholder, firms adopt generally

accepted behavior in the same industry. In a large-scale study done by Cormier, Magnan and Veldhoven (2005) mimetic institutions were found to have a positive effect on environmental performance quality through the use of industry imitation trends. Managers and firms conform to the accepted social beliefs, legitimize them and in that sense further improve socially acceptable norms.

Coercive pressures can come from both formal and informal pressures put on firms. Firms may

experience pressure from other organizations upon which they depend, leading to institutional isomorphic change. Furthermore, cultural expectations of society can be seen as well as coercive forces (DiMaggio & Powell, 1983). Coercive pressures are crucial in improving environmental performance and governments are key in promoting sustainable practices. Regulations and laws have shown to be improving awareness of sustainability and the drivers of adopting sustainable practices (Sarkis et al., 2011).

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2.4 Hypotheses

Based on existing literature a conceptual model is pictured in figure 1. The first hypothesis is about the relation of assessment frequency with factory sustainability performance. The second hypothesis looks at the relation of assessment frequency with factory sustainability performance and what the effect of country-level sustainability performance (CLSP) is on that relationship.

2.4.1 Hypothesis 1

Evaluation activities such as audits and assessments are used to assess the operating performance of suppliers based on pre-determined performance standards (Klassen & Vachon, 2009). Customer evaluation on sustainability has a positive effect on investment and commitment to sustainability by suppliers (Simpson et al., 2007). Likewise, Klassen & Vachon (2009) found that evaluation activities have a positive effect on the environmental-specific investments of suppliers. By implementing audits, setting formal assessment processes and offering feedback based on those assessments, suppliers are more likely to invest in sustainable practices. It makes the suppliers aware of how they are doing and what is still overlooked in terms of sustainability. Furthermore, the direct inspection of the buying firm makes managers aware of being evaluated and encourages greater environmental investment (Simpson et al., 2007). Frequent audits of suppliers ensure that corporate social responsibility standards will be upheld throughout the SC (Zhang et al., 2017). If suppliers are not structurally assessed, effective SC management cannot be achieved and that can lead to corporate reputational damage for a buying firm due to suppliers’ misconduct (Foerstl et al., 2010). Since structural assessments of suppliers make sure that suppliers’ performance will be maintained, we expect that increasing the frequency of assessments will result in higher sustainability performance for suppliers. Therefore, the following hypothesis is proposed:

H1: “There is a significant positive relationship between frequency of assessments and factory sustainability performance”

2.4.2 Hypothesis 2

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come from institutional pressures, in this study represented by country-level sustainability performance (CLSP). CLSP can be understood as to how well a country addresses social and environmental issues, such as education promotion, alleviation of poverty, improvement of living standards, resource conservation, and conservation of sources (Xiao, Vaart & Donk, 2018). For example, with mimetic isomorphism firms copy actions of competitors in the same industry then how well that industry performs can be seen as a pressure that is put on firms. If a country performs very poorly on sustainability, a firm might not feel obliged to improve its sustainability practices. Likewise, if a country performs very well on CLSP then a firm might feel a lot of pressure to improve. We expect that differences in institutional pressures as represented by CLSP influence assessments to be more or less effective in affecting the sustainability performance of suppliers. In other words, If the frequency of assessments positively influences suppliers to adopt sustainability, then the extent of institutional pressures affects this relationship. We expect this because a difference in institutional pressures changes the way how firms respond to pressures, if a firm already feels pressure from CLSP, increasing assessments might be less effective. Furthermore, Zhu and Sarkis (2007) state that institutional pressures are able to influence how an organization responds to the adoption of green supply chain management initiatives. For example, we expect that the presence of high institutional pressures will decrease the effect that the frequency of assessments has on the sustainability performance of suppliers. Therefore, the following hypothesis is proposed:

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2.5 Conceptual model

The conceptual model is shown in figure 1. Firstly, we expect to find that assessment frequency has a positive relationship with factory sustainability performance. Secondly, we expect that the effect that assessment frequency has on factory sustainability performance (FSP) will decrease as the level of country-level sustainability performance will increase. Likewise, we expect that as country-level sustainability performance decreases, the effect of assessment frequency on factory sustainability performance will increase.

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3. Methodology

3.1 Research design

The purpose of this research is to study what the effect of the frequency of assessments is on the sustainability performance of supplying factories, and how institutional pressures influence that relationship. This study uses a quantitative approach to identify the effect of assessment frequency on the sustainability performance of those supplying factories, and it studies how country-level sustainability performance influences this effect. It makes use of a mixed-method approach by the use of a survey to collect firm-level sustainability performance and with secondary data collection to gather data on institutional pressures. Firstly, a survey in the form of a questionnaire was used to assess a large number of suppliers. A survey provides a quantitative description of a population by researching a sample of that population, it can take the form of questionnaires (Creswell, 2017). A questionnaire is a suitable method since it can be used to compare large samples since it uses the same evaluation process (Meqdadi et al., 2015). A questionnaire is based on pre-determined performance standards and focuses on specific, easily verifiable measures (Klassen & Vachon, 2009). A questionnaire enables at arms-length with suppliers to collect quantitative data in a standardized way, on the suppliers’ level of commitment to the environment and their compliance to regulations (Meqdadi et al., 2015). Secondly, to gather the data on institutional pressures per country, secondary data collection was used. Secondary data collection is a suitable method since the data covers a broad set of entities and is representative of a whole population (Vartanian, 2010). A survey was suitable for this research since factories needed to be evaluated against pre-determined standards. It is also a suitable method when researching how variables are related and to what extent a relationship is present. The use of a secondary dataset in this study is also suitable since institutional pressures in the dataset are representative for the different countries (Vartanian, 2010). Therefore, a mixed method of survey data and secondary data is used.

3.2 Sample selection and data collection

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The clothing brand collected sustainability performance data of all the supplying factories over a 5-year period, from 2015 to 2019. The clothing brand used a SAFE rating sheet to assess each supplier based upon a standard set of performance measures. The SAFE rating sheet consists of 21 different standards dividing into three groups, labor performance, health & safety and environmental concerns (see appendix A). Each factory received a score based on a percentage as well as a score from A to D (see section 3.4 measurement). The sustainability performance assessment was conducted by different parties, either the clothing brand itself conducted the assessment, or the assessment was outsourced to an external auditor. The last option was used in cases where not only the clothing brand itself was a customer of the supplying factory, but another brand used the same supplier. It is however not known for which factories that is the case. While most factories were assessed more than once, there was not an even number of assessments per factory or year. On average 2.3 assessments per factory have been conducted between 2015 and 2019. Especially in the years 2015 and 2019 fewer assessments were conducted. In table 2 the number of suppliers that were assessed per year can be found. For the assessments done by the external auditor only the final score of A to D of the sustainability performance of each factory was sent and collected by the clothing brand.

Product category Nr of factories Accessories 229

Apparel 437 Footwear 124 Unknown 22 Subtotal 812

Table 1. Number of factories per product category

Year Nr of suppliers assessed 2015 192

2016 438 2017 445 2018 481 2019 122

Table 2. Number of suppliers assessed in the years 2015-2019

3.3 Measurement

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or a different report from an external auditor. The SAFE rating sheet as sent out by the clothing brand addresses 21 different performance standards, each with a different maximum score and can be divided into three categories, labor performance, health & safety and environmental concerns. The 21 different performance standards can be found in appendix A. Questions such as “Does the factory maintain training records for all factory employees?” and “Do migrant workers enjoy the same benefits and protection according to applicable laws as local workers?” are answered for every factory resulting in a score for all of the 21 different performance standards. The performance of a factory is measured by the percentage of total points that can be awarded as well as a grade connected to the percentage. Only this final score was provided by the clothing brand. Detailed scores on each of the 21 performance standards were not given. Since factories received a different number of assessments, the average score was used as the factory sustainability performance. In table 3 the percentages and grades are shown.

In cases where an external auditor conducted the assessments of the factories, only a grade was provided to the clothing brand. The external auditor represents 400 of the 1878 assessments that were conducted. Since factory sustainability performance in this study is measured as a percentage of the total points, the 400 assessments of the external auditor were changed using valid mean substitution and list-wise deletion. This will further be elaborated in chapter 3.6 ‘data analysis’.

Grade Score A >95% B+ 90%-95% B- 85%-90% C 75%-85% D <75%

Table 3. Assessment grades and scores of factory sustainability performance.

The second construct is the assessment frequency as being conducted at the supplying factory, measured in the number of assessments or audits conducted at a factory. Based on the data as provided by the clothing brand we looked at the frequency of assessments. For every factory, it is known how often they have been assessed in the years 2015 to 2019. Therefore, the frequency of assessments is the number of assessments conducted by either the clothing brand or the external auditor at a supplying factory.

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Nations Development Program was created to assert that the development of a country should be revolved around the people and their capabilities, and not just economic growth. A country’s performance is measured based on three dimensions, life expectancy, adult literacy and purchasing power (McGillivray, 1991). According to Sagar and Najam (1998), the HDI may be flawed in a way that it ignores the environmental aspect of development. Therefore, this study also makes the use of the EPI, where environmental results of countries are evaluated against pre-determined policy targets. The index assesses social and economic forces, pressures on the environment, states of changes in the environment and impact on the human health & ecosystem (Hsu, Lloyd & Emerson, 2013). Thus, the EPI represents the environmental sustainability performance of a country (Xiao et al., 2018). Sustainability coves both social as well as environmental dimensions in sustainability, therefore both the HDI and the EPI are included in this study.

The EPI scale ranges from 0-100 where 0 represents a very low performance, and 100 a very high performance. The HDI scale ranges from 0-1. First, the EPI index was rescaled from 0-1 in order to match the HDI scale. A correlation analysis between the variables of EPI and HDI was conducted in order to see if both variables of EPI and HDI may be added to form a new variable of country-level sustainability performance. EPI and HDI correlate significantly (r = .91, p = .009). Then the reliability was assessed to see if indeed both variables could be added to make a new CLSP variable. Cronbach’s Alpha is a test to measure internal consistency (Karlsson, 2016). In table 4 the results can be found. Cronbach’s Alpha is α = 0.908. According to Karlsson, 2016) with α => 0.8 the measure is very reliable. Therefore, we added both scores of the EPI and HDI Index to compute a new variable that shows the CLSP, this is in accordance with Xiao, et al. (2013) who also used a combined score of both indexes. In appendix B the CLSP scores per country can be found.

N Mean St. Dev 1 2 1 HDI 779 .74 .08 1 2 EPI 779 .50 .10 .091** 1

Table 4. Descriptive statistics and correlations HDI and EPI Note: * p < .10, ** p < .05, *** p < .01

3.4 Control variables

We used two control variables in the analyses that may affect the factory’s sustainability performance. Organizational distance and status of the assessment were used to control for the variation in this performance score.

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and its suppliers (Awaysheh & Klassen, 2010). According to Awaysheh and Klassen (2010), the organizational distance of a supplier in the supply chain impacts the adoption of supplier socially responsible practices. The lack of control over lower-tier suppliers (thus suppliers of suppliers) means it is more difficult for buying firms to manage the sustainability in the supply chain (Wilhelm, Blome, Wieck & Xiao, 2016). Literature states that with lower-tier supplier’s complexity tends to increase since and control over a supplier that is not directly linked to the focal firm is more difficult to manage. Likewise, it is easier to manage the relationship with a supplier that a focal firm has a direct relationship with. An increase in suppliers in the supply chain results in higher uncertainty and complexity in the supply chain and a higher difficulty in managing these relationships (Awaysheh & Klassen, 2010). In this study, there were tier-level 1 and tier-level 2 suppliers. To control for this difference in the distance of suppliers, a dummy variable was coded with tier-level 1 as 0 and tier-level 2 as 1. It was then added as a control variable in the analysis.

The second control variable that was included in the analyses is ‘status of assessment’. The status of the assessment shows if the assessment at the supplier is the first assessment or an ongoing assessment. The analysis conducted in this study is based on assessments done in the year 2015 to 2019. A first assessment means that a supplier was assessed for the first time in the years 2015-2019. An ongoing assessment means that a supplier has been assessed before the year 2015 and again between 2015 and 2019. Assessments have a positive influence on sustainability performance (Simpson et al., 2007), and we know that structural assessments of suppliers ensure that suppliers will not misbehave and that they will maintain the social responsibility standards (Zhang et al., 2017). If a supplier has not been assessed before it might perform less, while a supplier that has been assessed before and now is assessed again may have a better sustainability performance. In this study, a dummy variable was coded with ‘first assessment’ as 0 and ‘ongoing-assessment’ as 1. It was then added as a control variable in the analyses.

3.5 Data reliability & validity

The first step was to detect outliers in the assessment scores by using a rule of thumb to label outliers. An outlier is defined as such if it does not fall in between the following interval (Hoaglin & Iglewicz, 1987):

FL – 2.2(FU - FL) and FU + 2.2(FU – FL)

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that nearly 25% of observations could potentially be labeled as outliers, while in fact, they are not. Therefore, in this study a multiplier of 2.2 used. Table 5 shows the descriptive statistics and correlations between the variables.

N Mean St. Dev 1 2 3

1 FSP 731 89.46 5.36 1

2 Assessment freq. 807 2.31 1.31 .139*** 1 3 CLSP 779 1.24 .018 -.093** -.016n.s. ₁

Table 5. Descriptive statistics and correlations among variables Note: * p < .10, ** p < .05, *** p < .01

3.6 Data analysis

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30% of the cases would be erased resulting in loss of statistical power (Myers, 2011). For missing values at factories that only received 1 assessment, the value was addressed as missing in SPSS. This was the case for 75 factories, and they were excluded from further regression analyses.

To calculate the factory sustainability performance, the average assessment score was calculated for every supplier. This was done because not all factories received the same number of assessments and this way a linear regression analysis could be conducted with 1 dependent variable. The average assessment score was calculated by adding all individual scores of a supplier and dividing them by the number of assessments. In cases where a score was not known (i.e. The external auditor did not provide a % of the score) it was addressed as a missing value.

According to Wilhelm et al. (2016), sustainability management efforts changes depending on the distance of the suppliers. We performed an independent sample-T test to test whether the frequency of assessments is different for suppliers in tier-level 1 and tier-level 2. The independent sample-T test was not significant with a p = .490. Therefore, the number of assessments does not differ for suppliers in tier-level 1 and tier-level 2.

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Country Nr or cases per country Country Nr or cases per country Albania 2 Madagascar 2 Argentina 15 Malaysia 2 Australia 6 Mauritius 3 Bangladesh 28 Mexico 22 Brazil 14 Myanmar 2 Cambodia 25 Pakistan 16 China 247 Paraguay 1 Croatia 1 Philippines 3 Ecuador 1 Poland 2 Egypt 8 Portugal 7 El Salvador 3 Romania 8 Ethiopia 1 Slovakia 1

Georgia 3 South Africa 7

Germany 2 Sri Lanka 4

Guatemala 5 Swaziland 1 Honduras 1 Taiwan 26 Hungary 1 Thailand 5 India 49 Tunisia 1 Indonesia 41 Turkey 32 Italy 8 Ukraine 3 Japan 15 United Kingdom 5

Jordan 2 United States 1

Korea, Republic of (South

Korea) 28 Vietnam 146

Lesotho 1

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4. Results

This section contains the results from the analyses performed in SPSS. It starts with a simple linear regression analysis between the control variables ‘Organizational distance’ and ‘Assessment status’ with FSP in model 1, followed by a regression analysis including the predictor variable of assessment frequency in model 2. The third and fourth models include a moderating variable in order to test the moderating effect of CLSP on the relationship between assessment frequency with FSP. All the results of the different regression analyses are presented in Table 7.

4.1 Hypothesis 1

Model 1

Model 1 includes the control variables only. In order to test the correlation between the control variables of ‘Organizational distance and ‘Assessment status’ with factory sustainability performance. The relationship between the control variables and FSP was tested using simple linear regression analysis. The regression showed a significant result with an R-squared of .030, F(2, 697) = 10,854 and p < .000. Organizational distance is not significant correlated with FSP with B = -.0630, t = -1.185 and p = .237. Assessment status is significant positively correlated with FSP with B = 1.695, t = 4.148 and p < .000.

This means that the sustainability performance of suppliers scores 1.695 lower if the assessment was performed for the first time. Likewise, the sustainability performance increases with 1.695 if they have been assessed before 2015 and were assessed again when the collection of data was conducted between 2015 and 2019. The adjusted R-squared is .027 which means that 2.7% of the variance in FSP can be explained by the difference in organizational distance supplier and status of the assessment.

Model 2

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The adjusted R-squared was .039 which means that 3.9% of the variance in FSP can be explained by the variance in assessment frequency. A positive correlation was found between assessment frequency and FSP, therefore hypothesis 1 is supported.

The difference between model 1 and model 2 shows that the adjusted R-squared is higher than for model 1. An adjusted R-squared compensates for the addition of extra independent variables, in this case, the adding of the assessment frequency variable. Thus, adding the variable of assessment frequency enhanced to model in terms of determining the correlation.

4.2 Hypothesis 2

Model 3 & 4

Model 3 and 4 include the moderated variable of CLSP. To test the second hypothesis that CLSP moderates the relationship between assessment frequency and FSP multiple linear regression analysis was conducted. First, the variables of assessment frequency and FSP were standardized. Second, the interaction term was calculated by multiplying assessment frequency and FSP.

Model 3 contains the standardized variables plus the control variable. The results show a significant result with R-squared of .048, F(4, 668) = 8.329 and p <.000. Assessment frequency is positively correlated with B = .516, t = 2.468 and p = .014. CLSP is negatively correlated with B = .539, t = -2.589 and p = .010. The control variable of ‘organizational distance’ is not significant with B = -.602, t = -1.054 and p = .292. The control variable of ‘assessment status’ is significant with B = 1.430, t = 3.310 and p = .001.

Model 4 includes all variables plus the interaction term between assessment frequency and FSP. The results show a significant result with R-squared of .051, F(5, 667) = 7.325 and p < .000. Assessment frequency is positively correlated with B = .545, t = 2.602 and p = .009. CLSP is negatively correlated with B = -.631, t = -2.935 and p = .003. The control variable of ‘organizational distance’ is not significant with B = -.610, t = -1.069 and p = .286. The control variable of ‘assessment status’ is significant with B = 1.411, t = 3.270 and p = .001. The interaction term between assessment frequency and FSP is not significant with B = -.412, t = -1.665 and p = .096.

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Model 1 Model 2 Model 3 Model 4 Step 1 Control variables

Organizational distance -.630 -.635 -.602 -.610 Assessment status 1.695*** 1.369** 1.430** 1.411** Step 2 adding predictor variable

Assessment frequency .468** .516** .545**

Step 3 adding moderated variable

Interaction effect -.412* Model R .174 .207 .218 .227 Model R-squared .030 .043 .048 .051 Adjusted R-squared .027 .039 .042 .044 Change in R2 Model F 10.854*** 10.349*** 8.329*** 7.235***

Table 7. Results of regression analyses predicting factory sustainability performance. Note: * p < .10, ** p <

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5. Discussion

The main question of this study was what the effect of assessment frequency on supplier’ sustainability performance is and how institutional pressures affect this relationship. In table 8 an overview of the hypotheses and results are shown.

Hypothesis Results

H1. Assessment frequency positively influences supplier sustainable performance

Supported H2. Country-level sustainability performance affects the

positive relationship between assessment frequency and supplier sustainable performance.

Not supported

Table 8. Results of Hypotheses testing.

5.1 Theoretical implications

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acting as a sustainable organization (Walker & Wan, 2012). Therefore, monitoring can be helpful but needs to be used next to other sustainable supply chain management practices. Furthermore, it was known that structural assessments make sure that suppliers won’t misbehave (Foerstl et al., 2010), but how the frequency of assessments influences the sustainable performance of suppliers was still overlooked (Krause, Scanell and Calantone, 2000). This study contributes to the literature in a way that it presents a quantifiable result that shows increasing the assessments, results in an increase in sustainable performance.

The second contribution is in the field of institutional pressures. In this study we used institutional pressures to research what pressures firms experience, and how this affects their response to the sustainability assessments of buyers. We used country-level sustainability performance (CLSP) as a way to measure the institutional pressures firms experience. Based on the theory of institutional pressures by DiMaggio and Powell (1983) and Zhu and Sarkis (2007), we expected that this performance influences how firms act and how they respond to other pressures such as assessments by buyers. In this study, however, we found no support that CLSP influences the relationship between assessment frequency and sustainability performance of suppliers. While we did not find sufficient evidence for this, it does not mean the effect does not exist. It can mean that the data we collected was not the right representation of the population or the relationship between variables works in different ways. For example, in model 3 the standardized CLSP shows a significant negative coefficient. Country-level sustainability performance might therefore not work as a moderating effect but rather have a direct influence on sustainability performance. Future research is proposed on how and why this effect occurs since literature states that institutional pressures should have a positive relationship with sustainability (Kauppi, 2013). Why we did not find support for the moderating effect we look at the research of Zhu and Sarkis (2007). Zhu and Sarkis (2007) only looked at the independent moderating effects of institutional pressures, such as market, regulatory and competitive pressures, and how these influence the relationship between green supply chain management practices and environmental performance, but they found only a slightly positive interaction result. This difference in how we classified institutional pressures by only looking at how well a country performs might be a reason for the rejection of our hypothesis. Furthermore, the direct effect of CLSP on sustainability performance may be another reason why we did not find support that CLSP moderates the relationship between assessment and sustainability performance.

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SC (Choi and Hong, 2002), increases the complexity of managing suppliers. However, in this study, we found no evidence that suppliers in lower tiers are performing worse on sustainability, than the suppliers closer to the buying firm. This may be because according to Wilhelm et al. (2016), the distance of the supply base changes the sustainability management efforts of suppliers. Since in our study the frequency of assessments is the same for suppliers in tier-level 1 and tier-level 2, this could explain the fact that we did not find evidence that showed a difference in performance between tier-level 1 and tier-level 2.

5.2 Managerial implications

This study has some practical implications for buyers in a SC. First of all, it shows that while assessments may be beneficial in increasing the suppliers’ sustainable performance, this influence was not very big but other factors may beneficial as well. For example, collaboration between buyers and suppliers have shown promising results (Meqdadi et al., 2015). Buying firms therefore may use assessments as an addition to other sustainable management practices. If buyers want to make their SC more sustainable as a whole it could use several methods such as information sharing, mentoring, make relation-specific investments (Meqdadi et al., 2015; Rao, 2005; Simpson et al., 2007). These methods have been proven to work in order to make suppliers more sustainable. However, assessments are still a valuable practice to actively monitor a large global supply base and ensure that suppliers are acting in compliance with buying firms’ standards (Awaysheh & Klassen, 2010).

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6. Limitations and future research

When interpreting the findings a few limitations should be considered. While the sustainability assessment performance of the supplying factories was provided, it is not known how factories perform on each of the different performance standards. The overall performance scores of different factories can be the same, one factory may be performing very well on environmental performance but is lacking in health & safety while another factory addresses human rights not at all but scores highly on other factors. Therefore, the generalizability of these findings is limited, since only the overall score was known it made it hard to compare different countries to each other. Future research should, therefore, use more detailed performance assessments and see how the institutional pressures influence the sustainability performance separately. We suggest looking at the environmental, social and economic sustainability of suppliers and relate this to the institutional pressures that focus on these items separately. Knowing that for example, one firm performs very bad on human rights, it can more easily be compared to external pressures such as regulation and seeing how laws in that country address these human rights.

Secondly, although the factories in the sample come from 46 different countries, the countries are not equally represented. China, Vietnam, Indonesia and India represent the largest part of the dataset. In contrast with countries in Europe, which sometimes only present a few factories in the dataset. Generalizability for the countries with only a few cases is therefore limited, since individual differences may explain the sustainability performance of the factories in these countries. Future research should make sure countries are better represented to truly compare the different institutional pressures of different countries, and how this affects sustainability performance. Thirdly, the data gathered by the clothing brand and provided for this study has quite some limitations. The information on the factories is very limited, only a company name, country and supplier number have been provided. No information on the size of supplier, revenue, ownership was known. These traits can be an influencing factor for firms to adopt sustainability (Darnall, Henriques & Sadorsky, 2010; Gallo & Christensen, 2011). These limitations made it difficult to adjust the influence of assessments on sustainability performance. Furthermore, for the assessments as conducted by the external auditor, no percentage score was provided. The use of mean-substitution and list-wise deletion were used to account for these missing values; however, these practices can lead to loss of statistical power (Raaijmakers, 1999). This loss of statistical power can be seen in the low R2_{and adjusted R}2_{results of the analyses.}

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7. Conclusion

This research aimed to gain insight into what the effect of assessment frequency is on supplier’ sustainability performance and how country-level sustainability performance influences that relationship. Previous research had not sufficiently addressed these relationships; how much assessments influence sustainability performance was unknown and literature on institutional pressures had not adequately addressed how these pressures influence firms when responding to sustainable supply chain management practices.

Results show that increasing the number of assessments conducted at suppliers’ factories, lead to higher sustainability performance. This study shows how much suppliers will improve when increasing assessments. Structurally assessing suppliers on their performance will make sure they will not misbehave, and the sustainability performance of the SC will be upheld. The effect of country-level sustainability performance, which addresses how well a country performs on social and environmental sustainability, was found not to have an effect on the positive relationship between assessment frequency and supplier sustainability performance. While firms might feel pressure from the different institutional pressures to behave more sustainable, the country-level sustainability performance did not have a significant effect on the firms’ responsiveness to assessment frequency. Managers who focus much on monitoring and assessments can use this study to review their own sustainable supply chain management practices. While increasing assessments does show a positive effect, this effect is quite small. Managers therefore should not only focus on assessments if they want to increase their suppliers’ sustainability. However, assessments are a valuable first step in monitoring and assessing a large global supply base.

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9. Appendices

Appendix A. SAFE rating sheet sustainability.

Labor performance Maximum points

Overall Social performance and Management

Commitment (Management Systems) 9

Recruitment and Contracts Management 17

Compensation & Benefits 23

Forced Labor 17

Discrimination 10

Harassment & Abuse 6

Termination & Retrenchment 8

Homework, Vulnerable & Special Labor 9

Hours of Work 16

Labor Relations 24

Best Practices 0

Total 139

Health & Safety

General Health & Safety (Management System) 44

Fire Safety 18

Electrical and Mechanical Safety 20

Chemical Safety 14

Ergonomics 7

Dormitory and Welfare Amenities 0

Kitchen and Canteen 0

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Appendix B. EPI, HDI and CLSP.

Country EPI HDI CLSP

Country-level sustainability performance and sustainability assessment of suppliers