IB&M Master thesis
To what extent do the Sustainable Supply Chain
Management practices impact the performance of
firms?
A comparative study conducted in the U.S and Northwestern-Europe
Date of Submission: 21/01/2019
University of Groningen: Faculty of Economic and Business
Jamie Lee Tjoonk S3458601 j.l.tjoonk@student.rug.nl
Abstract
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Table of contents
Abstract ... 1 Abbreviation index ... 5 Table overview ... 6 Figure overview ... 6 1. Introduction ... 7 2. Theoretical framework ... 11 2.1 SSCM practices ... 112.1.1 Environmental management practices (EMP) ... 11
2.1.2 Socially inclusive practices (SIP) ... 11
2.1.3 Operations practices (OPS) ... 12
2.1.4 Supply chain integration (SCI) ... 12
2.2 SSCM Performance ... 12
2.2.1 Environmental performance (EP) ... 13
2.2.2 Social performance (SP) ... 13
2.2.3 Operations performance (OP) ... 13
2.2.4 Competitiveness ... 13
2.3 Hypotheses ... 14
3. Methodology ... 20
3.1 Data collection and research sample ... 20
3.2 Measuring financial performance ... 21
3.3 Research methods ... 21
3.4 Control variables ... 24
3.5 Method of analysis ... 24
3.6 Cronbach‟s alpha ... 26
3.6.1 Cronbach´s alpha for the original sample ... 26
3.6.2 Cronbach‟s alpha for the U.S. and NWE sample ... 27
3.7 Normal distribution ... 27
3.7.1 Shapiro Wilk for the original sample ... 27
3.7.2 Shapiro Wilk for the U.S. and NWE sample ... 28
3.7.3 Skewness and Kurtosis for the original sample ... 28
3.7.4 Skewness and Kurtosis for the U.S. and NWE sample ... 29
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3.8 Test of Heteroscedasticity ... 29
3.9 Test of multicollinearity ... 30
4. Results ... 34
4.1 Descriptive statistics ... 34
4.1.1 Descriptive statistics of the original sample ... 34
4.1.2 Descriptive statistics of the U.S. and NWE sample ... 35
4.2 Linear regression analysis ... 37
4.2.1 Environmental management practices and environmental performance ... 38
4.2.2 Socially inclusive practices and social performance... 39
4.2.3 Sustainable supply chain management practices and financial performance ... 40
4.2.3.1 Environmental management practices and financial performance ... 41
4.2.3.2 Socially inclusive practices and financial performance ... 43
4.2.3.3 Operations practices and financial performance ... 44
4.2.3.4 Supply chain integration and financial performance ... 46
5. Discussion ... 48
5.1 Hypothesis testing and discussion ... 48
5.2 Limitations ... 54
6. Conclusion ... 54
6.1 Managerial implications ... 55
6.2 Recommendations for further research ... 56
References ... 57
Appendices ... 61
1. Cronbach‟s alpha ... 61
1.1.1 Cronbach‟s alpha original sample: environmental management practices ... 61
1.1.2 Cronbach‟s alpha original sample: socially inclusive practices ... 61
1.1.3 Cronbach‟s alpha original sample: financial performance ... 61
1.2.1 Cronbach‟s alpha U.S. sample: environmental management practices ... 62
1.2.2 Cronbach‟s alpha U.S. sample: socially inclusive practices ... 62
1.3.1 Cronbach‟s alpha NWE sample: environmental management practices ... 62
1.3.2 Cronbach‟s alpha NWE sample: socially inclusive practices ... 63
2. Histograms for normality testing ... 63
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2.1.2 U.S. sample: histogram environmental performance ... 64
2.1.3 NWE sample: histogram environmental performance ... 64
2.2.1 Original sample: histogram social performance ... 65
2.2.2 U.S. sample: histogram social performance... 65
2.2.3 NWE sample: histogram social performance... 66
2.3.1 Original sample: histogram financial performance ... 66
2.3.2 U.S. sample: histogram financial performance ... 67
2.3.3 NWE sample: histogram financial performance ... 67
3. Plots for tests of heteroscedasticity ... 68
3.1.1 Original sample: environmental performance P-P plot of Regression Standardized Residual ... 68
3.1.2 U.S. sample: environmental performance P-P plot of Regression Standardized Residual ... 68
3.1.3 NWE sample: environmental performance P-P plot of Regression Standardized Residual ... 69
3.2.1 Original sample: environmental performance Scatterplot ... 69
3.2.2 U.S. sample: environmental performance Scatterplot ... 70
3.2.3 NWE sample: environmental performance Scatterplot ... 70
3.3.1 Original sample: social performance P-P plot of Regression Standardized Residual ... 71
3.3.2 U.S. sample: social performance P-P plot of Regression Standardized Residual... 71
3.3.3 NWE sample: social performance P-P plot of Regression Standardized Residual ... 72
3.4.1 Original sample: social performance Scatterplot ... 72
3.4.2 U.S. sample: social performance Scatterplot ... 73
3.4.3 NWE sample: social performance Scatterplot ... 73
3.5.1 Original sample : financial performance P-P plot of Regression Standardized Residual ... 74
3.5.2 U.S. sample: financial performance P-P plot of Regression Standardized Residual ... 74
3.5.3 NWE sample: financial performance P-P plot of Regression Standardized Residual ... 75
3.6.1 Original sample: financial performance scatterplot ... 75
3.6.2 U.S. sample: financial performance scatterplot ... 76
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Abbreviation index
Abbreviation index
CSP Community Social Performance
CSR Corporate Social Responsibility
EMP Environmental management practices
EP Environmental Performance
ESP Employee Social Performance
NGO Non-governmental Organization
NWE Northwestern Europe
OP Operations Performance
OPS Operations practices
SCI Supply chain integration
SIP Social inclusive practices
SP Social Performance
SPC Socially Inclusive practices for Community
SPE Socially Inclusive practices for Employees
SSCM Sustainable Supply Chain Management
SSI Sustainability Society Index
U.S. United States
VIF Variance inflation factor
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Table overview
Table 1: variable overview as explained by Thomson Reuters Eikon ... 22
Table 2: Shapiro Wilk values of environmental performance, social performance and financial performance for the original sample ... 27
Table 3: Shapiro Wilk values of environmental performance, social performance and financial performance for the U.S. and NWE sample ... 28
Table 4: Skewness and kurtosis values for environmental performance, social performance and financial performance for the original sample ... 28
Table 5: Skewness and kurtosis values for environmental performance, social performance and financial performance fot the U.S. and NWE sample ... 29
Table 6: Correlations between the independent variables in the original sample ... 30
Table 7: Correlations between the independent variables in the U.S. sample ... 30
Table 8: Correlations between the independent variables in the NWE sample ... 31
Table 9: Multicollinearity tests: environmental management practices as dependent variable VIF and tolerance ... 32
Table 10: Multicollinearity tests: Socially inclusive practices as dependent variable ... 32
Table 11: Multicollinearity tests: Operations practices as dependent variable ... 32
Table 12: Multicollinearity tests: Supply chain integration as dependent variable ... 33
Table 13: Descriptive statistics of the sustainable management practices in the original sample . 34 Table 14: Descriptive statistics of the firm performances of the original sample ... 35
Table 15: Descriptive statistics of the sustainable management practices for the U.S. and NWE sample ... 36
Table 16: Descriptive statistics of the firm performances for the U.S. and NWE sample ... 37
Table 17: Most represented industries and number of industries represented in the U.S. and NWE samples ... 37
Table 18: Linear regression analysis for environmental management practices and environmental performance ... 39
Table 19: linear regression analysis for socially inclusive practices and social performance ... 40
Table 20: Linear regression analysis for environmental management practices and financial performance ... 42
Table 21: Linear regression analysis for the socially inclusive management practices and financial performance ... 43
Table 22: Linear regression analysis for the operation management practices and financial performance ... 45
Table 23: Linear regression analysis for the supply chain integration and financial performance 46 Table 24: Hypotheses evaluation ... 53
Figure overview Figure 1: Sustainable Supply Chain Management interpreted by Carter & Rogers (2008) ... 8
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1. Introduction
Nowadays, there are numerous research articles about Sustainable Supply Chain Management (SSCM) (Carter and Easton, 2011; Elkington, 1998; Gold et al., 2013; Markman and Krause, 2016; Pagell and Wu, 2009; Zhang et al., 2018, etc.). Not only in the literature is it a hot topic, almost every corporate organization is more concerned than ever for its environmental and social footprint. Researchers have a lot of different opinions on what SSCM exactly means, but they all go into the same direction: more collaboration and cooperation to improve the performance of all companies in the supply chain. For a company to be truly sustainable, it should not only look at itself, but at its whole supply chain. For this study, the definition by Carter and Rogers (2008, p. 368) is used, since this definition includes all three aspects of the triple bottom line which are important in the theory used. SSCM has been 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”. From a sustainability and long-term profitability point of view, actions that cause permanent damages to the eco-system are dangerous. Additionally, organizations that fail to secure safety and security, as well as minimum wage, healthcare and good working conditions for their employees, and improved living conditions for the community around them, will likely face negative consequences on the performance of their firm (Das, 2018).
8 in the market in order to compete effectively. For example, pollution within the constraints of the law still affects public health (Markman & Krause, 2016).
Cochran and Wood (1984) studied the relation between CSR and financial performance, stating that previous research lacked in research methods and data quality. Other early findings of studies on CSR show that researchers operationalized the environmental and social dimensions of CSR, without taking the economic performance into consideration (Walley & Whitehead, 1994). At the core of this approach and a theory which is still used in a lot of Sustainable Supply Chain Management (SSCM) studies is Elkington‟s (1998) triple bottom line. The theory proposes an intersection of environmental, social
and economic performance. The triple bottom line supports managers to recognize which social and environmental activities do improve economic performance and which do not. As Carter and Rogers (2008) state: the triple bottom is developed to help managers understand how they can best improve the practices in the organization to ensure not only that the company survives, but it is also successful. Consequently, optimizing the triple bottom line is in fact what SSCM is all about, and
sustainability is increasingly used as synonym for the triple bottom line (Carter & Easton, 2011). In their study, Carter and Rogers (2008) identify four supporting facilitators of SSCM: strategy, risk management, an organizational culture and transparency (as shown in Figure 1: Sustainable Supply Chain Management interpreted by Carter & Rogers (2008)).
10 Until now, the newly developed theory including its measurement scale has only been tested on multiple companies operating in India (Das, 2017). This study will be valuable for the current literature for three reasons: First of all, this complete and multiple-dimension theory including the triple bottom line is newly developed. Except for an article by Das (2018) himself, this theory is not extensively tested. Second, for this research, multiple innovative industries in the U.S. and Northwestern Europe are tested. By testing multiple industries, the sample is more valid and increases the reliability of generalization. Third, the measurement scale was tested in India. India is a developing country and the third largest economy in the world. Additionally, it is also the country with the largest number of people living in absolute poverty. They have huge challenges with air pollution and resource scarcities (Eklund, 2016). The government does recognize the importance of sustainable production and stimulates this (Das, 2018). However, it is by no means close to supply chain sustainability in developed countries. Therefore, this study focuses on the United States and Northwestern Europe where many companies which are frontrunners in sustainability are located.
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2. Theoretical framework
The theory developed by Das (2017) will be used as theoretical framework for this study. The focus of this theory is on the intersection of economic, environmental and societal goals of a company and is based on the triple bottom line theory introduced by Elkington (2004). All three dimensions are treated with equal importance in his study.
2.1 SSCM practices
The SSCM practices in the theory are divided into four dimensions: environmental management practices, socially inclusive practices, operations practices, and supply chain integration.
2.1.1 Environmental management practices (EMP)
Environmental management practices focuses solely on practices which help companies to do good for the environment. Items that fall under environmental management practices are, for example, the existence of ISO 14001 certification (also for suppliers) or other comparable environmental management systems, cleaner production and more sustainable packaging, involving suppliers and customers in design development to incorporate more sustainability and reduce the product´s consumption and recycling. These practices can help organizations to become more environmental friendly, or „green‟ and ultimately improve the sustainability of their supply chain, by involving customers and especially suppliers.
2.1.2 Socially inclusive practices (SIP)
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2.1.3 Operations practices (OPS)
The operations practices are internal in the organization. It involves newly invented management techniques incorporated in the organization that are meant to improve efficiency and quality, reduce inventory and minimize waste across the entire supply chain. Examples for these management techniques are Total Quality Management, Six Sigma, Just-in-time and lean production. Six sigma is one of the main management techniques, and described as a project-driven management approach designed to improve the organization‟s products, processes and services by reducing defects in the organization on a continuous basis. It focuses on improvements of the understanding of customer requirements, business systems, productivity and the financial performance of a firm (Kwak & Anbari, 2006). For the supplier process, management techniques which could possibly improve the operation performance could be the selection of suppliers (based on quality) or a quality management system.
2.1.4 Supply chain integration (SCI)
The supply chain consists of multiple activities spread over multiple functions within the organizations but also across different organizations upstream as well as downstream. It is a complex system and it is not only about coordinating the inventory, production and transportation of the products, but the challenge is to integrate; from customer demand to the back of the chain where production starts. Multiple researchers studied supply chain integration before. Items included in this dimension are for example sharing (information on) customer demand, production plan and inventory with suppliers (Lii and Kuo, 2016), establishing frequent contact, communicating and estimating needs and improving integration activities (Kannan and Tan, 2005). The basic message is that one should not only look at the different parts of the supply chain, but integrate the parts in order to achieve optimal efficiency. Zhu, Liu and Lai (2016) proposed that by improving the supply chain, the company‟s financial performance also improves.
Next to the practices, there are also SSCM performances. These are used to measure the impact of the practices on the overall firm performance.
2.2 SSCM Performance
13 measures the operational efficiency, and the fourth dimension, competitiveness, may be considered as an external performance since it evaluates the performance of the firm in comparison to its competitors.
2.2.1 Environmental performance (EP)
When firms invest in environmental practices, they are interested in the effects of these practices and therefore will likely evaluate their environmental performance. There are several ways to evaluate the EP of a company, for example through reduction of solid, liquid, gaseous waste and toxic materials, reduction of the number of environmental accidents in the company and the impact of the company on natural systems (e.g. air, land and water).
2.2.2 Social performance (SP)
It can cost firms a lot of time to evaluate the effect of social inclusive practices on their social performance. The manager needs to monitor to what extent the investment has actually had an effect towards improving capabilities of the employees and positively changing the environment for the surrounding community. The employee-centered social performance can be evaluated by reduction in employees‟ remuneration inequities, improvement of working, living and health conditions. Desirably, these improvements will enable employees to develop themselves within the organizations. Eventually, the organization will benefit from the development of its employees. The community-centered social performance is evaluated in terms of corporate social image, the improvement of chances for the surrounding community and the improvement of health and education. It is also a reflection of the reputation of a company.
2.2.3 Operations performance (OP)
Operations performance is intern in a firm and is measured in terms of decrease in cost and improvement of efficiency, not only in the firm itself but across the entire supply chain. Examples here are decrease in purchasing costs, energy consumption and an increase in logistics efficiency.
2.2.4 Competitiveness
14 The elements discussed previously are not mutually exclusive in nature. They are complementary and they represent practices which firms can adopt in order to improve the sustainability of the supply chain (European business review, 2009). Supply chain managers are not only focusing on practices which relate to cost reductions, but they think about the impact on their employees and the community too. This encourages them to implement more than just one of the SSCM dimensions and performances.
With this theory, hypotheses can be formed which will make it possible to answer the research question. This will be done in the next section (2.3).
2.3 Hypotheses
The research question is: to what extent do the Sustainable Supply Chain Management practices impact the environmental, social and financial performance of firms?
In order to answer the research question, multiple hypotheses are formed and studied. The relationships tested in this study are the relationships between the four management practices and the performance scores. First are the sustainable environmental management practices. These practices are based on doing good for the environment. Included are waste of products and resources and investing in green supply chains by collaboration, producing and monitoring in the supply chain. Rao et al. (2009) studied the effect of environmental management practices on the environmental performance and found that investing in environmental management practices led to an increase in environmental performance. Yang et al. (2011) concluded the same in their research. Resulting from the previous literature, expected is that when a firm invests in practices to improve the environment, the environmental performance will also improve.
H1a: Sustainable environmental management practices are positively related to environmental performance.
15 creates goodwill, which in turn creates customer and supplier loyalty and trust. This could probably lead to an increase in customers or sales and thus an increase of firm performance. Furthermore, research shows that innovative firms invest more in CSR activities and reap greater financial benefits from these investments (Shen, Tang, & Zhang, 2016). Rao et al. (2016) proved that sustainable environmental management practices leads to improved competitiveness of firms. Also, Zailani et al. (2012) showed that environmental management practiced improved the firm performance. Therefore, the following hypothesis is formed:
H1b: Sustainable environmental management practices are positively related to the financial performance.
The sustainable socially inclusive practices include targets for diversity and opportunity, OHSAS 18001 and/or policies for training and development, skills training and community involvement. “OHSAS 1800:2007 Occupational Health and Safety Management Certification is an international standard which provides a framework to identify, control and decrease the risks associated with health and safety within the workplace” (EU Certification, 2018). By implementation of this system standard, you communicate the clear message to your stakeholders that you prioritize the health and safety of your employees.
Most of the variables involved in the socially inclusive practices dimension are practices concerning employees, and one variable is for community improvement. Gold et al. (2013) showed in their research that companies which invest in socially inclusive practices results in positive social performance, for example improved healthcare and improved education and economic opportunities. Furthermore, for employees, e.g. the improvement of skills and motivation, leads to better social performance. Expected is a positive relation between sustainable socially inclusive practices and social performance, which leads to the following hypothesis:
H2a: Sustainable socially inclusive practices are positively related to social performance.
16 explicit cost of those investments is minimal and employee morale and productivity will go up (Moskowitz, 1972; Parket & Eibert, 1975). The sustainable socially inclusive practices also consist of both practices for employees and the community. Community involvement and development can have a significant influence on the financial performance of the firm (Zhu, Liu, & Lai, 2016) Moreover, Mefford (2011) showed that employee related socially inclusive practices positively influenced the firm financial performance. Therefore, the following hypothesis is formed:
H2b: Sustainable socially inclusive practices are positively related to financial performance.
The third hypothesis is based on sustainable operations practices, in this study Six sigma and other sustainability quality management systems. Companies implement these innovative managerial initiatives to stay ahead of their competition. They help to set goals and acknowledge priorities, as well as indicate potential differences between the company and their customers and activities (Rao et al., 2009). The operation systems are developed to make the operation process smoother and less costly, for example by reducing waste or reducing inventory (Kwak & Anbari, 2006). Therefore, by running a smoother and less-costly business, the company will be able to save money and perform better. Rao et al. (2009) concluded that operations practices have a positive effect on financial performance, as was also argued by Yang et al., (2011). He argued that lean manufaturing practices are positively related with financial performance. This leads to the next hypothesis:
H3: Sustainable operations practices are positively related to financial performance.
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H4: Sustainable supply chain integration is positively related to financial performance.
The RobecoSAM (2018) Country Sustainability Ranking is used as an indicator of country sustainability. These scores are based on 17 environmental, social and governmental (ESG) indicators. The U.S is places on the 15th position in the ranking. Denmark is the leader of the ranking, followed up by Sweden, Switzerland, Finland and Norway. 7th in the ranking is the Netherlands, followed-up by Ireland. When it comes to their sustainability reports, European companies include far more governance and sustainability items than the companies located in the U.S. (Kolk, 2008). Moreover, when looking at the broad perception of sustainability by the three pillars – environmental, social and economic factors, European companies are leading the world (European business review, 2009). The Sustainability Society Index (SSI), shows that Northwestern European countries as Norway, Switzerland, Sweden and Finland are on top when it comes to sustainability. In this index, U.S. ends up on the 61st place. The U.S. is consistently at the top of the economic pillar of sustainable development, but it did not invest this wealth into environmental protection or into protection of its citizens and improving their quality of life. It has one of the highest rates in income inequality and poverty rates (European business review, 2009). This significantly influences the sustainability in the country, since the poor do not have the funds in order to save the environment. This leads to hypothesis 5a and b:
H5a: Companies located in Northwestern Europe invest more in sustainable management practices than companies located in the U.S.
H5b: Companies located in Northwestern Europe score higher on environmental, social and financial performance.
18 more incentives for environmental sustainable behavior (Schoenherr & Talluri, 2013). Wallace (1995) investigated the different (legal) environmental policies in Europe and the U.S, concluding there were significant differences leading to a different degree of adoption of sustainability initiatives. Schoenherr and Talluri (2013) concluded that the emphasis on adopting sustainability initiatives is higher in European plants than in U.S. plants. To test whether the location has a moderating effect on the aforementioned relations (H1a, H1b, H2a, H2b, H3 and H4), hypothesis 5c is as follows:
H5c: Companies located in Northwestern Europe experience a stronger relation between their sustainable management practices and their environmental, social and financial performance than companies located in the United States.
By studying these hypotheses, it will be clear what the effect of the sustainable management practices is on the performance of the firm. This study does intentionally not test every management practice against every performance measures since this will be illogical and it will not ensure a better or more complete result. Instead, only the relevant relations are tested, in order to test the theory provided by Das (2017), as well as study the benefits for companies of investing in sustainable practices. Additionally, this research is set out to reveal potential differences between companies located in the U.S. and Northwestern Europe.
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3. Methodology
3.1 Data collection and research sample
The data used for this research will be obtained from two databases: Orbis and Thomson Reuters Eikon, but most of the data is obtained from Thomson Reuters Eikon. This data source does have incomplete variables, and the data from Orbis will complement this data. In this section, the data and their sources will be explained. The companies in the sample are constructed from indices: S&P 500 for the U.S.-based companies and the STOXX Europe 600 for the Northwestern Europe-based. The companies were retrieved from Orbis on September 26, 2018. Companies which are in these indices but are not based in the concerned countries (so in the U.S. for the U.S based companies and in Northwestern Europe for the Northwestern Europe-based companies) will be removed to get a more reliable sample. Similarly, companies with not enough relevant information available will also be excluded from this research. In total, this research will use the data of 218 U.S.-based companies and 222 Northwestern Europe-based companies, together forming the database of 440 companies.
The sample of Northwestern Europe-based companies focuses on Northwestern Europe and consists mostly of companies in Great Britain (23%), France (22%), Germany (16.1%) and the Netherlands (9.4%). There are also multiple companies located in Sweden, Norway, Denmark and Finland as well as some companies in other countries. These countries are, to some extent, similar regarding sustainability practices based on their Country Sustainability Ranking (RobecoSAM, 2018).
21 most of these companies belong to the list of biggest and most innovative companies in the world.
3.2 Measuring financial performance
Financial performance consists of much different financial data and in order to create a complete image, only one variable measuring the financial performance would be insufficient. Griffin and Mahon (1997) made a literature overview and studied the different measures for financial performance. In the 51 studies they reviewed, 80 different measurements were used to measure financial performance of the firm, indicating that there is no standard measurement which is relevant for every study. For this study, many variables were tested1, and from these variables, gross profit, total revenue and net income after taxes were selected. First of all, the variables were categorized in order to compare and merge the variables. After the categorization, the Cronbach‟s alpha was measured (see section 3.6) in order to decide which variables have the highest reliability and can be best grouped together. Not only did these three have a reliable alpha, they also complemented each other and are therefore a good representation of financial firm performance.
3.3 Research methods
Since the data is not collected manually, it is important to study the exact meaning and interpretation of all the variables which will be used in this research. There will be eight variables which measure environmental management practices, nine variables which will measure the socially inclusive practices, one which will measure the operations practices and one which will measure the supply chain integration. These variables do include the most important aspects of their accompanying concepts. For example, the operations practices variable measures all relevant systems instead of all the systems measured separately. Additionally, the concepts are not mutually exclusive and most likely experience some overlap. Following is a table (Table 1) Table 1: variable overview as explained by Thomson Reuters Eikonincluding the practices, performances, and their accompanying explanations (as explained by Thomson Reuters Eikon).
1
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Variable overview (data source: Thomson Reuters EIKON)
Variables Explanation
Dimension 1: Environmental management practices
Resource Reduction Policy
Does the company have a policy for reducing the use of natural resources or to lessen the environmental impact of its supply chain?
ISO 14000 or EMS Does the company claim to have an ISO 14000 or EMS certification? Waste reduction
initiatives
Does the company report on initiatives to recycle, reduce, reuse, substitute, treat or phase out total waste?
Environmental investments initiatives
Does the company report on making proactive environmental investments or expenditures to reduce future risks or increase future opportunities?
Environmental partnerships
Does the company report on partnerships or initiatives with specialized NGOs, industry organizations, governmental or supra-governmental organizations, which are focused on improving environmental issues? Environmental
products
Does the company report on at least one product line or service that is designed to have positive effects on the environment or which is environmentally labeled and marketed?
Environmental supply chain management
Does the company use environmental criteria (ISO 14000, energy consumption, etc.) in the selection process of its suppliers or sourcing partners?
Employees health and safety OHSAS 18001
Does the company have health and safety management systems in place like the OHSAS 18001?
Dimension 2: Socially inclusive practices
Health and safety training
Does the company train its executives or key employees on health and safety?
Training and development policy
Does the company have a policy to support the skills training or career development of its employees?
Policy community involvement
23 Policy employee
health and safety
Does the company have a policy to improve employee health and safety?
Health and safety policy
Does the company have a policy to improve employee health and safety within the company and its supply chain?
CSR sustainability committee
Does the company have a CSR committee or team?
Management training
Does the company claim to provide regular staff and business management training for its managers?
Policy career development
Does the company have a policy to improve the career development paths of its employees?
Policy skills training Does the company have a policy to improve the skills training of its employees?
Dimension 3: Operations practices
Six Sigma and Quality Mgt systems
Does the company claim to apply the six sigma, Lean manufacturing, TQM or any other similar quality principles?
Dimension 4: Supply chain integration
Supplier ESG training
Does the company provide training in environmental, social or governance factors for its suppliers?
Performance scores
The Environmental Pillar score
The environmental pillar measures a company‟s impact on living and non-living natural systems, including air, land and water, as well as complete ecosystems. It reflects how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities in order to generate long term shareholder value
The Social Pillar Score
The social pillar measures a company‟s capacity to generate trust and loyalty with its workforce, customers and society, through its use of best management practices. It is a reflection of the company‟s reputation and the health of its license to operate, which are key factors in determining its ability to generate long term shareholder value.
The financial performance
24 Furthermore, it is important to look at the performances of companies. In the Thomson Reuters Eikon database, there are two relevant performance indicators: the environmental pillar score and the social pillar score. The scores by Thomson Reuters Eikon include multiple aspects. The environmental pillar consists of resource use, emissions and innovation, and the social pillar consists of workforce, human rights, community and product responsibility (Reuters, Thomson, 2018). The environmental pillar stands for the environmental performance and the social pillar for the social performance. The variables are carefully chosen in order to create a full image of all the possible practices which could be involved in the dimensions.
3.4 Control variables
In order to measure relations, one has to look at the bigger picture and identify other independent variables which could possible influence the relation between the dependent and independent variable. Control variables in this study identify relevant characteristics of the companies which might influence the performances of the companies too. For example, argued is that smaller firms are less likely to invest in CSR initiatives due to resource access constraints and lower visibility. Bigger firms have a bigger social impact, when measuring impact by scale of activities (Cowen, Ferreri, & Parker, 1987). By setting these variables as control variables, this influence can be measured. The control variables in this research will be (1) size (measured by the number of employees), (2) age of the company and (3) industry, as they are argued to influence the investment in SSCM practices (Hooghiemstra, 2000). This data is derived from the Thomson Reuters Eikon database; missing values for the company age were added from the data derived from Orbis.
3.5 Method of analysis
To analyze the data, IBM SPSS 23 will be used.
25 Testing the data on normality is crucial in order to execute statistical tests with relevant and significant outcomes. The best way to study the normal distribution of a sample is by testing a combination of checking figures, like the histogram, the assessment of the skewness and kurtosis and formal normality tests (Kim, 2013). The sample consists of 440 companies. For this sample size, which is smaller than 2000 respondents, the Shapiro-Wilk test is most appropriate to measure the normality of the sample. The Shapiro-Wilk test is based on the correlations and is frequently recommended as the best choice for testing the normality of data (Ghasemi & Zahediasl, 2012). In order to test the normality, a null hypothesis and alternative hypothesis have to be stated.
H0 = the data in the sample is normally distributed
HA = the data in the sample is not normally distributed
If the p-value is lower than the alpha level, which is .05, the null hypothesis will be rejected. This means that there is evidence found that the tested data is not from a normally distributed population. When the p-value is higher than the alpha level, the contrary is true.
The Shapiro Wilk test is a tool for testing the normality of data, and it looks for the well-known symmetric bell-shape curve. However, not every distribution of data is symmetric and this is called skewness. Data can be skewed to the right, also known as positively skewed with a tail on the right side, and skewed to the left, also called negatively skewed with a tail to the left side (Kim, 2013). A z-test is a measurement tool in order to assess the normal distribution of data by using the skewness and kurtosis. However, when the sample size increases, the standard errors get smaller and thus for sample sizes over 300, z-values are not relevant: skew values larges than 2 and kurtosis values larger than 7 are an indication of non-normality (Kim, 2013). According to George and Mallery (2010), the values for skewness between -2 and +2 are considered as acceptable when proving the normal distribution of data.
26 are homo- or heterogeneous, since a problem of heteroscedasticity invalidates the tests of hypotheses, e.g. the t-test and f-test.
Last test in order to ensure the quality of data is het multicollinearity test. Multicollinearity means that there are very high inter-associations among the independent variables (Statistic Solutions, 2018) (in this study: environmental management practices, socially inclusive practices, operations practices and supply chain integration). This can be tested through the Variance inflation factor (VIF), which should not exceed 10 (Hair, Anderson, Tatham, & Black, 1995) Other statistic experts claim that a VIF of 5 is already problematic (Ringle, Wende, & Becker, 2015). Another tool to test multicollinearity is the tolerance, which is the percentage of variance in one of the independent variables, that is not accounted for by the other independent variable in this sample. This level should be larger than .20 (Statistic Solutions, 2018). Both tools will be used in this study.
To measure the strength of the relations, the linear regression analysis is used. This tool will measure the relation between the environmental management practices and the environmental performance as well as the relation between socially inclusive practices and the social performance. The linear regression analysis takes into account the influence of the control variables (company age, industry and size). The coefficients are important, as well as the significance, which determines the likelihood that the relationship between the variables is not caused by chance. After that, the linear regression analysis will also measure the effect of environmental management practices, socially inclusive practices, operations practices and supply chain integration on the financial performance of firms, while controlling for company age, industry, and size. In all the linear regression analyses, the effect of location (U.S. or Northwestern Europe) will be measured through moderation. This means the effect that location has on the tested relation. When you test moderation in a linear regression analysis, it is important to standardize the variables first.
3.6 Cronbach’s alpha
3.6.1 Cronbach´s alpha for the original sample
27 Cronbach‟s alpha (α=0.73) is considered good, whereas the socially inclusive practices‟ Cronbach‟s alpha (α=0.82) is even better.
The financial performance consists of multiple aspects, as mentioned in section 3.2, and thus the reliability check is also important here. The three variables together resulted in a Cronbach‟s alpha of 0.69. Since this variable only consists of three aspects, it can be deemed acceptable. When removing one of the three variables, the resulting Cronbach‟s alpha score would be 0.74. However, since the other Cronbach‟s alpha value is deemed acceptable and this includes more relevant variables, it is thus a better representation of financial performance and is more suitable to use in this study.
3.6.2 Cronbach’s alpha for the U.S. and NWE sample
The environmental management practices Cronbach‟s alpha was considered good (α=0.73) in the U.S.-database, and acceptable in the Northwestern Europe database (α=0.68). The socially inclusive practices consists of nine variables, and that resulted in a good Cronbach‟s Alpha score for the variables in the U.S. database (α=0.83), and in the Northwestern Europe database (α=0.74). These scores are good to work with.
3.7 Normal distribution
3.7.1 Shapiro Wilk for the original sample
The three dependent variables in this study are the environmental performance, the social performance and the financial performance. The table below (Table 2) shows the Shapiro Wilk values. All Shapiro Wilk values are significant and have a p-value smaller than .001, which means that the data is statistically different from a normal distribution in accordance to the Shapiro Wilk test.
Table 2: Shapiro Wilk values of environmental performance, social performance and financial performance for the original sample
Degree of freedom Shapiro Wilk p-value
Environmental performance 440 .93 p < .001
Social performance 440 .95 p < .001
Financial performance 440 .92 p < .001
28
3.7.2 Shapiro Wilk for the U.S. and NWE sample
For the divided samples, the Shapiro-Wilk is also used to test the normality. The table below shows the Shapiro Wilk values. All Shapiro Wilk values are significant and have a p-value smaller than .001, which means that the data is statistically different from a normal distribution in accordance to the Shapiro Wilk test. Results are shown in Table 3.
Table 3: Shapiro Wilk values of environmental performance, social performance and financial performance for the U.S. and NWE sample
Degree of freedom Shapiro Wilk p-value U.S. sample Environmental performance 218 .93 p < .001 Social performance 218 .95 p < .001 Financial performance 218 .91 p < .001 NWE sample Environmental performance 222 .94 p < .001 Social performance 222 .95 p < .001 Financial performance 222 .91 p < .001
3.7.3 Skewness and Kurtosis for the original sample
The second test of normality is the skewness and kurtosis. The skewness of data can range from -2 to -2, whereas the skewness can go as high as 7 in order to be assumed normally distributed. In the table below (Table 4), the skewness and kurtosis, and their accompanying standard error, of the environmental performance, social performance and financial performance are shown.
Table 4: Skewness and kurtosis values for environmental performance, social performance and financial performance for the original sample
Skewness Skewness Standard error Kurtosis Standard error
Environmental performance -1.02 (.12) 1.02 (.23)
Social performance -.89 (.12) .89 (.23)
Financial performance .81 (.12) -.21 (.23)
29
3.7.4 Skewness and Kurtosis for the U.S. and NWE sample
In Table 5, the skewness and kurtosis, and standard error, of the environmental performance, social performance and financial performance are shown.
Table 5: Skewness and kurtosis values for environmental performance, social performance and financial performance for the U.S. and NWE sample
Skewness N Skewness Standard error Kurtosis Standard error
U.S. sample 218 Environmental performance -1.01 (.17) .87 (.33) Social performance -.80 (.17) .47 (.33) Financial performance .84 (.17) -.14 (.33) NWE sample 222 Environmental performance -.95 (.16) .71 (.33) Social performance -.97 (.16) 1.44 (.33) Financial performance .82 (.16) -.25 (.33)
All skewness and kurtosis values are within the range, thus all three dependent variable can be assumed normally distributed. For both samples, the skewness of the environmental performance and the social performance are both negative, whereas the skewness of the financial performance is positive. For the kurtosis score, it is the other way around.
3.7.5 Histograms
Lastly, the histograms of the three dependent variables are shown in appendix 2. The visual representation of these histograms can secure normality. These histograms show the bell-shaped curve for all three dependent variables (environmental performance, social performance and financial performance). Where the environmental performance and social performance are skewed to the right, the financial performance is skewed to the left.
Concluding, when combining the results from the Shapiro Wilk, skewness and kurtosis and the visual representation of the histogram, we can assume a normal distribution in the dataset and can thus continue to use tests where the normal distribution is assumed.
3.8 Test of Heteroscedasticity
30 already studied and explained in the normal distribution section (3.7). The P-P plot and scatterplot will be used to check for scedasticity. In appendix 3, the plots are shown.
The plots indicate no reason to assume a deviation from homoscedasticity for all three variables.
3.9 Test of multicollinearity
As mentioned in section 3.5, the multicollinearity is measured through the variance inflation factor and this should not range between 0.2 and 5 in order to ensure the reliability of data. In Table 6, Table 7 and Table 8, correlations of the independent variables are shown.
Table 6: Correlations between the independent variables in the original sample
Table 7: Correlations between the independent variables in the U.S. sample Correlations (N=440) Environmental management practices Socially inclusive practices
Operations practices Supply chain integration Environmental management practices .52** .27** .36** Socially inclusive practices .52** .12** .21** Operations practices .27** .12** .14**
Supply chain integration .36** .21** .14**
Correlations in the U.S. sample (N=218)
Environmental management practices
Socially inclusive practices
Operations practices Supply chain integration Environmental management practices .54** .37** .41** Socially inclusive practices .54** .22** .27** Operations practices .37** .22** .21**
31 Table 8: Correlations between the independent variables in the NWE sample
The tables show that there are no unusual or disturbing correlations. In the original sample, all correlations are highly significant. In the U.S. sample, the same is true. However, in the NWE sample, only the correlations with environmental management practices are (highly) significant, the others are very small and not-significant.
Next, the VIF and tolerance scores are measured. Results are shown in Table 9, Table 10, Table 11 and Table 12. All VIF scores are between 1.03 and 1.36. All tolerance scores are higher than 0.2. The test to see if the data met the assumption of collinearity indicated that multicollinearity was not a concern in this study.
Correlations in the NWE sample (N=222)
Environmental management practices
Socially inclusive practices
Operations practices Supply chain integration Environmental management practices .33** .15* .28** Socially inclusive practices .33** -.05 .07 Operations practices .15* -.05 .07
32 Table 9: Multicollinearity tests: environmental management practices as dependent variable VIF and tolerance
Variable VIF Tolerance
Original sample (N=440)
Socially inclusive practices 1.05 .95
Operations practices 1.03 .97
Supply chain integration 1.06 .95
U.S. sample (N=218)
Socially inclusive practices 1.11 .9
Operations practices 1.08 .93
Supply chain integration 1.11 .91
NWE sample (N=222)
Socially inclusive practices 1.01 .99
Operations practices 1.01 .99
Supply chain integration 1.01 .99
Dependent variable: Environmental management practices
Table 10: Multicollinearity tests: Socially inclusive practices as dependent variable
Variable VIF Tolerance
Original sample (N=440)
Environmental management practices 1.21 .82
Operations practices 1.08 .93
Supply chain integration 1.15 .87
U.S. sample (N=218)
Environmental management practices 1.34 .74
Operations practices 1.16 .86
Supply chain integration 1.21 .83
NWE sample (N=222)
Environmental management practices 1.1 .91
Operations practices 1.03 .98
Supply chain integration 1.08 .92
Dependent variable: socially inclusive practices
Table 11: Multicollinearity tests: Operations practices as dependent variable
Variable VIF Tolerance
Original sample (N=440)
Environmental management practices 1.5 .67
Socially inclusive practices 1.36 .73
Supply chain integration 1.15 .87
U.S. sample (N=218)
Environmental management practices 1.56 .63
Socially inclusive practices 1.41 .71
Supply chain integration 1.21 .83
NWE sample (N=222)
Environmental management practices 1.21 .83
Socially inclusive practices 1.12 .89
Supply chain integration 1.08 .92
33 Table 12: Multicollinearity tests: Supply chain integration as dependent variable
Variable VIF Tolerance
Original sample (N=440)
Environmental management practices 1.44 .69
Socially inclusive practices 1.36 .73
Operations practices 1.08 .92
U.S. sample (N=218)
Environmental management practices 1.56 .64
Socially inclusive practices 1.41 .71
Operations practices 1.16 .87
NWE sample (N=222)
Environmental management practices 1.16 .86
Socially inclusive practices 1.13 .88
Operations practices 1.04 .96
34
4. Results
4.1 Descriptive statistics
4.1.1 Descriptive statistics of the original sample
In order to do research, it is important to first study the descriptive statistics to check if there are any inconsistencies. The sample consists of 440 companies, where 218 companies are U.S.-based (49.5%) and 222 companies are based in Northwestern Europe (50.5%).
As shown in Table 13, the environmental management practices range from 1 to 2.13, with a mean score of 1.76 (σ=0.24). The socially inclusive practices range from 1 to 2, with a mean score of 1.90 (σ=0.19). Considering the range of both practices, one could say that the mean of both practices is quite high, especially the mean score of the socially inclusive practices. The operations practices range from 1 to 2, with a mean score of 1.27 (σ=0.44). The supply chain integration also range from 1 to 2, with a mean score of 1.43 (σ=0.5).
Table 13: Descriptive statistics of the sustainable management practices in the original sample
N Score range Mean score Standard deviation
Environmental management practices
440 1 – 2.13 1.76 (.24)
Socially inclusive practices 440 1 – 2 1.90 (.19)
Operations practices 440 1 – 2 1.27 (.44)
Supply chain integration 440 1 – 2 1.43 (.5)
35 performance ranges from 1.33 to 7, with a mean of 3.07 (σ =1.17). This is summarized in Table 14 below.
Table 14: Descriptive statistics of the firm performances of the original sample
N Score range Mean score Standard deviation
Environmental performance 440 8.34 – 99.24 75.78 (16.16) Social performance 440 6.61 – 98.52 73.57 (15.74) Financial performance 440 1.33 - 7 3.07 (1.17)
The most represented industries in the sample are machinery, tools, heavy vehicles, trains & ships (5.2%), insurance (5%), banking (4.8%) and food & drug retailing (4.3%).
4.1.2 Descriptive statistics of the U.S. and NWE sample
In the U.S. sample, the environmental management practices mean score is 1.69 (σ=0.26) with a minimum score of 1 and a maximum score of 2.13, whereas the socially inclusive practices mean score is 1.85 (σ=0.24), with a minimum score of 1 and a maximum score of 2. Considering the scale, these scores can be considered above average, especially the social score. The mean of the operations practices and supply chain integration are significant lower, 1.26 (σ=0.44) with a minimum score of 1 and a maximum score of 2 and for the operations practices and 1.39 (σ=0.49) with a minimum score of 1 and a maximum score of 2 for the supply chain integration. The standard deviation is larger for these two variables, meaning that there is more variance in the variables, with σ=0.44 and σ=0.49 being both reasonably large standard deviations.
36 Table 15: Descriptive statistics of the sustainable management practices for the U.S. and NWE sample
N Score range Mean score Standard deviation
U.S. sample 218
Environmental management practices
1 – 2.13 1.69 (.26)
Socially inclusive practices 1 – 2 1.85 (.24)
Operations practices 1 – 2 1.26 (.44)
Supply chain integration 1 – 2 1.39 (.49)
NWE sample 222
Environmental management practices
1 – 2 1.83 (.20)
Socially inclusive practices 1 – 2 1.96 (.11)
Operations practices 1 – 2 1.27 (.45)
Supply chain integration 1 – 2 1.47 (.50)
The by Thomson Reuters Eikon calculated environmental and social pillars give a representation of the performance of the firm. Findings are summarized in Table 16. In the U.S. sample, the mean for the environmental pillar is 73.48 (σ=17.29) with a range of 8.3 to 99.01. The mean for the social pillar is 75.59 (σ=16.17), with a range from 17.86 to 97.13. The financial performance ranges from 1.33 to 7, since it is categorized into 7 categories in order to merge different aspects together. It has a mean score of 3.18 (σ=1.16).
37 Table 16: Descriptive statistics of the firm performances for the U.S. and NWE sample
N Score range Mean score Standard deviation
U.S. sample 218 Environmental performance 8.3 - 99.01 73.48 (17.29) Social performance 17.86 - 97.13 75.59 (16.17) Financial performance 1.33 - 7 3.18 (1.16) NWE sample 222 Environmental performance 25.89 – 99.24 78.04 (14.66) Social performance 6.61 – 98.52 74.53 (15.27) Financial performance 1.33 – 6.33 2.96 (1.17)
The most represented industries in the U.S. sample are electric utilities & IPPs, software and IT services, and oil & gas. In the Northwestern Europe sample, the three industries with the most companies in the sample are: machinery, tools, heavy vehicles, trains and ships, chemicals and banking services. Table 17 shows the most represented industries.
Table 17: Most represented industries and number of industries represented in the U.S. and NWE samples In the U.S. sample In the NWE sample
Most represented industries
1 Electric utilities & IPPs (6.4%) Machinery, tools, heavy vehicles, trains and ships (6.7%)
2 Software and IT services (6%) Chemicals (5.8%) 3 Oil & gas (5.5%) Banking services (5.4%)
Total number of represented industries in the sample
40 43
4.2 Linear regression analysis
38 Northwestern Europe are categorized as 1, and companies located in the U.S. are categorized in 2. This moderation variable will be used in all linear regression analyses.
4.2.1 Environmental management practices and environmental performance
First, the strength of the relation between the environmental management practices and environmental performance will be measured. The R square in the linear regression analysis shows the percentage of the environmental performance that can be accounted for by the environmental management practices. As shown in Table 18, the R Square of model 1 is .05, which means only 5% of the environmental performance can be accounted for by the control variables. In Model 2, which includes the environmental management practices, the R square is .36, which means that 36% of the environmental performance can be accounted for by environmental management practices and control variables, which is quite a large percentage. The R square in model 3 is equal to the R square in model 2. The change in R square in model 1 and 2, .31 or 31%, is the percentage of the environmental performance that can be accounted for solely by the environmental management practices.
ANOVA shows if the coefficient is statistically significant. In this case, it is (F (3, 436) = 7.29, p < .001, R = .22) for model 1, (F (5, 434) = 47.73, p < .001, R = .6) for model 2 and (F (6, 433) = 40.26, p < .001, R = .6) for model 3. Since the p-value is lower than .001, these are all highly significant.
The strength of the relationship between the environmental management practices and the environmental performance is .58, with p<.001. This means the relation is highly significant. In table 18, the unstandardized coefficients and their accompanying standard errors are shown. The unstandardized coefficients show how much the dependent variable would increase if the independent variable would go up with 1. If the environmental management practices would go up by one, this means that the company would invest in 1 more environmentally sustainable practices, the environmental performance would grow with 9.31 (SE=.66).
For the control variables, the unstandardized coefficients for age and size are extremely low (in both model 1, 2 and 3), but significant. Moreover, the coefficient of the industry is .15 in models 1 and 2, .14 in model 3 and (highly) significant.
39 significant evidence that location (U.S. or Europe) will strengthen the relation between environmental management practices and environmental performance.
Table 18: Linear regression analysis for environmental management practices and environmental performance
Model 1 Model 2 Model 3
Step and variables B SE B SE B SE
Intercept 68.84** (1.89) 70.95 (1.58) 71.43 (1.61)
Control
Age .04** (.01) .02 (.01) .01 (.01)
Size 1.65E-5** (.00) 1.05E-5* (.00) 1E-5* (.00)
Industry .15* (.06) .15** (.05) .14** (.05) Main effects Environmental practices 9.31** (.66) 9.07** (.68) Location (U.S. or Northwestern Europe) .75 (.67) .67 (.67)
Two way interaction
Environmental practices x location 1.01 (.68)
R Square .05 .36 .36
Δ R Square .31** .003
* p < .05 ** p < .01
4.2.2 Socially inclusive practices and social performance
40 The strength of the relation between the socially inclusive practices and the social performance is .43, with p<.001. This means the coefficient is highly significant. In table 19, the unstandardized coefficients shows that investment of 1 socially inclusive practices by a firm will results in an increase of 6.74 (SE=.71) in social performance. In model 1, as well as model 2 and 3, although the unstandardized coefficients of the control variables; age and size are (highly) significant, they are rather small. The coefficient of industry is (highly) significant and not so small.
There is a not-significant interaction between socially inclusive practices and location (U.S. or Northwestern Europe) on social performance, B=1.28, p=.15. This means that there is no significant evidence that location (U.S. or Northwestern Europe) will strengthen the relation between socially inclusive practices and social performance.
Table 19: linear regression analysis for socially inclusive practices and social performance
Model 1 Model 2 Model 3
Step and variables B SE B SE B SE
Intercept 66.96** (1.84) 67.52** (1.7) 68.08 (1.74)
Control
Age .04** (.01) .03* (.01) .03* (.01)
Size 1.7E-5** (.00) 1.4E-5** (.00) 1.3E-5** (.00)
Industry .13* (.06) .15** (.06) .15* (.06)
Main effects
Socially inclusive practices 6.74** (.71) 5.96** (.89)
Location (U.S. or Northwestern Europe)
1.4 (.72) 1.17 (.74)
Two way interaction
Socially inclusive practices x location 1.28 (.88)
R Square .05 .22 .22
Δ R Square .17** .004
* p < .05 ** p < .01
4.2.3 Sustainable supply chain management practices and financial performance
41 financial performance of a firm is tested, again by using the linear regression analysis. The
financial performance consists of the categorized values of gross profit, net income after taxes and total revenue. The moderation variable is location (U.S. or Northwestern Europe).
4.2.3.1 Environmental management practices and financial performance
The first linear regression analysis will measure the relation between environmental management practices and financial performance with location (U.S. or Northwestern Europe) as moderation. In Table 20, the R square of model 1 is .17, which means 17% of the financial performance is accounted for by the control variables. The R square of model 2 and 3 is .21, which means 21% of the financial performance is accounted for by the control variables and environmental
42
Model 1 Model 2 Model 3
Step and variables B SE B SE B SE
Intercept 2.46** (.13) 2.44** (.13) 2.43** (.13)
Control
Age .00 (.00) .00* (.00) .00* (.00)
Size 3.2E-6** (.00) 3E-6** (.00) 3.1E-6** (.00)
Industry .01* (.00) .01** (.00) .01** (.00)
Main effects
Environmental practices .22** (.05) .22** (.06)
Location (U.S. or Northwestern Europe)
.2** (.05) .2** (.05)
Two way interaction
Environmental practices x location -.01 (.05)
R Square .17 .21 .21
Δ R Square .04** .0
* p < .05 ** p < .01
The strength of the relationship between the environmental management practices and the financial performance is .19, with p<.001. An investment of 1 in environmental management practices by a firm will increase the financial performance with .22 (SE=.05), on a scale from 1 to 7. The relation between financial performance and location (U.S. or Northwestern Europe) is significant. The interaction between age, size and industry with the financial performance is in fact (highly) significant, but really small.
However, there was a not-significant negative interaction between environmental management practices and location (U.S. or Northwestern Europe) on financial performance (model 3), B= -.01, p=.8. This means that an increase in environmental management practices will lead to an increase in financial performance, but this relation will be not be more pronounced depending on location of the company.
43
4.2.3.2 Socially inclusive practices and financial performance
The second relation analysed will be the relation between socially inclusive practices and financial performance, with as moderation variable location (U.S. or Northwestern Europe). Table 21 shows the outcomes of the linear regression analysis.
Table 21: Linear regression analysis for the socially inclusive practices and financial performance
Model 1 Model 2 Model 3
Step and variables B SE B SE B SE
Intercept 2.46** (.13) 2.41** (.13) 2.44** (.13)
Control
Age .00 (.00) .00* (.00) .00* (.00)
Size 3.2E-6** (.00) 3.2E-6** (.00) 3.2E-6** (.00)
Industry .01* (.00) .01** (.00) .01** (.00)
Main effects
Socially inclusive practices .05 (.05) .01 (.07)
Location (U.S. or Northwestern Europe)
.16** (.06) .14* (.06)
Two way interaction
Environmental practices x location .06 (.07)
R Square .17 .18 .18
Δ R Square .01* .001
* p < .05 ** p < .01
The R square of model 1 is .17, which means 17% of the financial performance is accounted for by the control variables. The R square of model 2 and 3 is .18, which means 18% of the financial performance is accounted for by the control variables and socially inclusive practices. This means that the R square change is only .1, which is small.
44 (5, 434) = 19.19, p < .001, R = .43) for model 2 and (F (6, 433) = 16.11, p < .001, R = .43) for model 3. All three models are highly significant.
The strength of the relationship between the socially inclusive practices and the financial performance is .04, with p=.41. An investment of 1 in socially inclusive practices by a firm will increase the financial performance with .05 (SE=.05), on a scale from 1 to 7. This effect is small and not significant. The relation between location (U.S. or Northwestern Europe) and financial performance is significant. The interaction between age, size and industry with the financial performance is in fact very small, but significant.
There was a not-significant interaction between environmental management practices and location (U.S. or Northwestern Europe) on financial performance (model 3), B= .06, p=.38. This means that an increase in socially inclusive practices will lead to an increase in financial performance, but this relation will be not be more pronounced depending on the location of the company.
4.2.3.3 Operations practices and financial performance
