June 20th, 2017
University of Groningen Faculty of Economics and Business
Nettelbosje 2, Groningen The Netherlands
Missing link in the CSR field - the importance of industry
context in studying synergies among CSR dimensions
Master thesis submitted for:
MSc BA Strategic Innovation
Management
Catalina MARINESCU
S3213390
Catalina.marinescu28@gmail.com
Supervisor: dr. Jordi SURROCA
Missing link in the CSR field - the importance of industry
context in studying synergies among CSR dimensions
Catalina Marinescu
Abstract:
This study investigates how industry context (uncertainty, complexity and munificence) affects the development of corporate social responsibility (CSR) actions and whether they strengthen the synergies or trade-offs among three CSR dimensions (Environmental CSR, Employee CSR and Customer & Supplier CSR). Synergies mean that investing in one CSR dimensions will raise the value of another CSR dimensions, while trade-offs are made when managers choose to invest in one CSR dimensions in the detriment of another. It was hypothesized that in a highly uncertain business environment synergies among CSR dimensions are consolidated, while complexity hinders the likelihood of them. In a high munificent environment companies will build more easily synergies among CSR dimensions. The hypotheses were tested on a sample of 241 observations from 5 countries and 8 industries for 2014. Using a linear regression, I found out that uncertainty does not influence synergies nor trade-offs among CSR dimensions, while a low complexity context favors complementarities between two pairs of CSR dimensions, on one side Environmental and Customer & Supplier CSR and on the other side Employee and Customer & Supplier CSR. Companies operating in a high munificent business environment experience synergies between Environmental and Customer & Supplier CSR. This paper provides additional understanding on the interactions effects among CSR dimensions under specific contextual conditions.
Keywords: Environmental CSR, Employee CSR, Customer & Supplier CSR, synergies,
trade-offs, uncertainty, complexity, munificence
Table of contents
1. Introduction ... 4
2. Theoretical background and hypotheses development ... 6
2.1 Understanding CSR dimensions and their interaction ... 6
2.2 Contextual conditions affecting CSR interactions ... 9
2.3 Hypotheses development ... 11
Uncertainty ... 11
Complexity ... 12
Munificence ... 14
3. Methodology ... 15
3.1 Data Source and sample ... 15
Measurements ... 16 3.2 Analysis technique ... 20 4. Results ... 21 4.1 Descriptive statistics ... 21 4.2 Hypotheses testing ... 22 Hypothesis 1 ... 25 Hypothesis 2 ... 26 Hypothesis 3 ... 27
Summary of complementary and substitution effects among pairs of CSR ... 28
5. Discussion ... 30
Findings and theoretical implications ... 30
Practical implications ... 31
Limitations and future research ... 32
6. Conclusion ... 33
References ... 34
Appendix 1: Summary of conceptual and empirical research on CSR contextual drivers and complementarity interaction among CSR dimensions ... 39
Appendix 2: Model without any contextual factors included ... 40
Appendix 3: Model with low uncertainty level ... 43
Appendix 4: Model with high complexity level ... 44
Appendix 5: Model with low complexity level ... 45
Appendix 6: Model with high munificence level... 46
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1. Introduction
In recent years Corporate Social Responsibility (henceforth: CSR) has become a highly debated topic to both academics and professionals alike, with the number of studies increasing in the last decade according to Frynas et al., (2016). In that respect, literature on sustainability suggests the need of opening the black box of CSR where firms coping with enhanced pressure from different stakeholder groups can use complementary or substitutable CSR dimensions depending on the context under which they operate (uncertain, complex or munificent environment). However, firms responding to stakeholder pressures need to efficiently use resources and avoid overinvestment in order to maximize outcome.
The most frequently studied stakeholders of CSR are the dimensions which address matters related to customers & supplier, human capital employed and the natural environment (Waddock and Graves, 1997; Barcos et al., 2013; Cavaco and Crifo, 2014; Crifo, 2016). Extant work initiated from the assumption that aforementioned CSR dimensions are positively correlated due to similarities of resources, expertise and acumen (Tang et al., 2012) and thus trade-offs among these dimensions can be cultivated. However, in order to reduce conflict among stakeholders, CSR policies have been used to find a common ground and exploit synergies among non-primary stakeholders groups (Cavaco and Crifo, 2014).
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Responding to the future research call of Aragon-Correa and Shrama (2003), Frynes et al. (2016), Mellahi et al. (2016) and Haffer and Searcy (2017), this paper will provide insights under which contextual conditions CSR dimensions experience interaction effects such as complementary and substitution, which are transformed in synergies and trade-offs. By deploying this analysis, the paper will close the gap between the stakeholder and contingency theories in the literature. The novelty of this study consists of breaking the unitary concept that all CSR dimension are related and positively correlated and provide the circumstances that can lead to differentiated results. This translates into the following research question:
“Which contextual conditions are more likely to strengthen or weaken synergies among CSR dimensions?”
Although the CSR stream research has been populated with numerous papers, academics are still considering this field as a scattered domain where some pieces of the puzzles are missing. Therefore, I engaged in theory testing cross-sectional procedure. The procedure analyzed secondary data from Asset4, matched with Datastream and Orbis financial and operational information for 3 Western European countries, United States and one emerging country, China. Additionally 8 relevant industries (aerospace and aircraft, automotive and parts, chemical, construction and materials, electronic equipment, food producers, oil and gas and pharmaceutical industry) were analyzed. To answer the research question, I analyzed the interaction effect between pairs of CSR dimensions (environment and employees; environment and customers & suppliers; employees and customers and suppliers) under specific contextual factors such as uncertainty, complexity and munificence. The findings show that an uncertain environment does not influence a company‘s CSR strategy. Besides, a business environment characterized by low complexity is favorable to more complementarity between two pairs of CSR dimensions, namely on one hand Environmental and Customer & Supplier CSR and on the other hand Employee and Customer & Supplier CSR. Under a high munificent context companies will experience a complementarity effect for Environmental and Customer & Supplier CSR.
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2. Theoretical background and hypotheses development
Corporate social responsibility scholars stress the importance of understanding CSR drivers and outcomes (Aguines and Glavas, 2012; Muller 2010). By emphasizing this, a wider understating will emerge. This understanding can allow CSR policies developers to build synergies or responsible make trade-offs where necessary. Further, a revision of past papers describing CSR dimensions and their interactions is provided together with an explanation of CSR practices influenced by external conditions.
2.1
Understanding CSR dimensions and their interaction
In order to have a common understanding of each CSR initiative a short description of each dimension will be provided. However, only the most frequently studied groups of stakeholders will be included in this paper, namely employees, environment and the joint group of customers & supplier (Waddock and Graves, 1997; Barcos et al., 2013; Cavaco and Crifo, 2014; Crifo, 2016). Therefore, human resources CSR initiatives refer to safe working environment, non-monetary benefits covering health and trainings, including employees in group projects, as well as improving HR activities (Branco and Rodrigues, 2006, Crifo et al., 2016). Additionally, when talking about environmental CSR, Kang and Lee (2016) refer to the operational actions impacting the environment. These actions can include strategies for pollutions reduction (Hart and Ahuja, 1996; Shrivastava and Hart, 1994) and resources reduction (Mudgal et al., 2010; Dincer, 2000). Customer & Supplier CSR initiatives cover green products offer, firm engagement to provide goods in the right place and at the right moment and obtaining quality standard certificates such as ISO 9000. Other scholars have previously constructed a customer & supplier CSR measure by analyzing green labeling for goods, customers call services and meeting customers‘ expectations (Crifo et al. 2016). Other CSR actions oriented towards customers refers to company‘s collaborations with customers for philanthropic actions.
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However, other scholars mention that when dealing with multiple dimensions of CSR, managers have to prioritize each investment taking into consideration their influence and return (Mazutis, 2013; Mazutis, 2010; Akpinar et al., 2008). Thus, these later studies seem to conflict with the idea proposed by Tang et al., (2012), which emphasized the relatedness of CSR actions. Moreover, another study that sustains the prioritization idea of CSR actions was developed by Cavaco and Crifo, (2014). In their study the authors argue that different CSR practices may be conflicting due to each stakeholders interest. Moreover, each CSR dimension entails specific expenditures which need to be prioritized in order to answer the conflicting interests between stakeholders.
Mauerhofer (2007) provided a framework to prioritize sustainable actions related to environment, social and economic interest. According to his hierarchy, in order to reach sustainable development and stakeholder integration a company needs to first develop efficient environmental matters, because they have a direct influence of the environment and implicitly on the business setting. Therefore, this framework suggests a trade-off among the CSR dimensions, putting first environmental issues. Managers that must prioritize costs in order to meet each stakeholder‘s needs will engage in a decision making process, where he or she will choose to put in practice particular CSR dimensions, which will lead to trade-off or synergies among these dimensions.
Trade-off and synergies are going to be considered in this paper as interaction effects, namely and substitution and complementary effect. A substitution effect will lead to a trade-off, while complementarity effect will results in synergies. In that respect, a definition of what exactly complementary and substitution means should be provided. This paper will adopt the definition proposed by Athey and Stern (1998). According to the authors more CSR practices are complements if they provide larger benefits at an aggregated level than the individual benefits presented by each dimension. Therefore, the marginal result of mixing multiple CSR dimensions will be higher than practicing individual CSR initiatives. Thus, the substitutability effect has an opposite definition to complementarity, leading to trade-offs among the choices of CSR practices. The interactions effects of complementarity or substitution can arise as a response to context opportunities or threats combined with pressures from stakeholder (Sharma 2000, Henriques & Sadorsky, 1999). As a result companies will try to build synergies among dimensions or will prioritize to obtain higher outcome.
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in order to obtain green products that can be offered to customers as part of the customer CSR dimension. An additional conceptual paper to support the same reasoning is provided by Lehtonen (2004) who argues that environmental investments have more than one sustainable role, they can also add social benefits to employees by increasing their well-being and signaling ethical values within the company. However, in some instances a trade-off may occur where environmental practices will display conflicting interests opposing to the other CSR dimensions (Lehtonen, 2004; Upton, 2002). From the customers‘ and suppliers‘ perspective some studies concluded that investing in strategic supply management procedures leads to customer satisfaction (Yeung, 2008) and positive interaction among CSR dimensions.
Further, a manufacturing firm engaged in environment protection and waste reduction through redesigning its operational flows will require new coordination mechanism between old and new knowledge and human capital engagement to deploy such practices (Christmann, 2000; Tang 2012). Hence, according to Tang (2012) a firm that has already implemented environmental friendly waste reduction procedures will more easily engage in developing green products with improved quality in a safer environment. It can be assumed that manufacturing companies will experience synergies among their CSR dimensions, meaning the marginal value of one CSR dimension will increase as another CSR dimension will intensify.
Developed on the stakeholder theory, the paper of Cavaco and Crifo (2014) based on 15 European countries posit that CSR actions for primary stakeholders (employees, customers and suppliers) have a complementary effect. Their assumptions are based on the reasoning of similar interests among primary stakeholders and conflicting objectives between non-primary stakeholders (environment) and primary stakeholders. Moreover, they found a substitution effect between environment and business community (customers and suppliers) explained by the overinvestment hypothesis, which entails that a company will experience an overinvestment position if it chooses to invest in the same time in multiple CSR dimensions that are substitutable. However, no concluding result was found between CSR for human capital and environmental strategies.
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characteristics and therefore substitutes each other. Moreover, as initially proved by Cavaco and Crifo (2014), environmental CSR and primary stakeholders (human capital, customers & suppliers) are substitutes. It is interesting to notice the empirical setting of both studies. Both papers focused only on European countries and none of them included moderating effects of contextual circumstances. Therefore, from a research point of view it is useful to elaborate on the contingent perspective by analyzing the effects of particular circumstances of the business environment, such as the uncertainty of markets, complexity of the business environment and munificence which may lead to complementary or substitution effects among CSR dimensions.
2.2
Contextual conditions affecting CSR interactions
In this part of the paper previous CSR literature will be reviewed with a focus on exogenous factors influencing sustainable corporate strategies. As posit by scholars, environmental strategies are developed by practitioners as a response to the characteristics of the business environment either positive or negative (Osborn and Glueck, 1980; Miller and Friesen, 1983).
International business scholars have proved that external environment influences the development of CSR policies and their intensity (Katz et al., 2001; Kolk, 2005). Empirical studies have been used to describe CSR and to measure the influence of various exogenous factors affecting the development and prioritization of sustainable practices (Akpinar et al. 2008; Aragon-Correa et al. 2013; Chen et al., 2015; Henriques & Sadorsky, 1996; Rueda-Manzanares et al., 2008;, Sharma et al., 2007). The previous mentioned scholars investigated how the characteristics of business environment are shaping CSR dimensions policies acknowledging the importance of moderators such as: industry type, country development, uncertainty, complexity, munificence, etc.
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1997; Shrivastava, 1995).Moreover, the company will try to minimize their exposure to risk by deploying resources to product diversification and innovation to achieve financial and operational stability (Miller and Shamsie, 1999). However, Aragon-Correa and Sharma (2003) suggest that perceived uncertainty in a business environment will decrease the probability that a company will use organizational resources and means to develop proactive environmental CSR practices.
In addition to uncertainty, complexity and munificence can act as exogenous variables in influencing corporate sustainable strategies. Although these subjects have not been so actively discussed in the academic world their importance cannot be contested. Moreover, complexity relates to a great array and diversity of factors that managers perceiving a complex context will have to cope with (Miller and Friesen, 1983). Companies operating in industries characterized by complexity have an increase predisposition to develop sustainable strategies for the next five years (Henriques and Sadorsky, 1999). This result was based on the positively diversified pressures by customers, shareholders, governmental regulation and community, which translates into synergies among these stakeholders groups in developing the five-year environmental strategy.
Munificence characterizes a growing industry with abundant resources that provides the occasion for companies to innovate by exploring different opportunities (Decarolis and Deeds, 1999; Nohria and Gulati, 1996). A munificent context has been proved to enhance the relationship between CSR and development of new capabilities. A munificent environment can determine CSR managers in adopting innovative and proactive sustainable measures. Moreover, the rate of growth in an industry will accelerate a company to proactively develop green measures above the industry standards. Russo and Fouts (1996) have measured munificent environments by analyzing the industry growth and concluded that companies operating under these circumstances experience wider sustainable concern due to the integration of organizational capabilities for reaching higher social performance.
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All scholars emphasizing the importance of exogenous factors impacting the business environment have been contributing to the understanding of the black box of CSR. By tackling a not so common subject they provided useful explanations of the determinants of companies‘ behavior in the presence of these factors. In such context companies implicitly develop organizational capabilities to fight the uncertainty and complexity of markets or to respond to specific environmental regulations. Table 10 from the Appendix displays a summary of the conceptual and empirical research on corporate social responsibility dimensions and their interaction under specific contextual drivers.
2.3
Hypotheses development
This research model which is built upon stakeholder and contingency theory, contributes to the understanding of CSR and the synergies and trade-offs that result among the dimensions of CSR contingent to business environment characteristics. The two previous mentioned theories place CSR actions in a new perspective where voluntary behavior determining CSR is considered outdated. The new standpoint provides insights into how companies react to various exogenous stimuli from the markets. This paper tries to respond to the unclear relationship between environment, employees and business community CSR actions, in particular contexts characterized by uncertainty, complexity and munificence.
Uncertainty
Environmental state uncertainty refers to managers‘ perception of the general business environment or one of its elements as being unpredictable and instable (Dess and Beard, 1984). As demonstrated by the sustainability literature, companies will develop proactive environmental strategies to anticipate and respond to instability in uncertain settings (Chen et al., 2015; Dess and Beard, 1984; Sharma et al., 2007 and Martin-Tapia et al., 2008). Specifically, in a perceived uncertain business environment organizations will deploy stakeholder engagement, meaning they will try to learn and integrate knowledge from their stakeholders (e.g. customers and suppliers) to generate environmental strategies (Sharma et al., 2007). Moreover, generation of proactively developing responsible practices has been positively related to stakeholder integration (Rueda-Manzanares et al., 2008). In other words, the capability of a firm to develop collaborations with stakeholders to integrate their concern into companies‘ strategies for sustainable solutions will result into proactive environmental practices. By deploying stakeholder engagement and integration companies will build up positive collaborations among functions and departments which may lead to synergetic benefits among stakeholders.
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(Nelson and Winter, 1982). Some managers may perceive this accelerated volatility as an opportunity to reach environmental legitimacy (Lewis et al., 2014) and increase firm reputation among primary and non-primary stakeholders through the development of CSR actions (Brammer and Pavelin, 2006; Koh et al., 2014). As a result, companies will correlate their CSR actions to respond to the dynamic settings and reach positive collaborations among CSR dimensions. Additionally, in unpredictable context managers are interested to continue to innovate in order to generate capabilities that will help them respond to unpredictability (Sharma el al., 2007). They will experiment with resources in innovative ways and deploy environmentally friendly processes. By using continuous innovation to tackle uncertainty, they will build up capabilities from organizational synergies.
As demonstrated by Martin-Tapia et al., (2008), uncertainty moderates the positive relationship between proactive environmental practices and international trade. Hence, companies developing proactive responsible practices beneficiate from the advantages of export opportunities to captivate and grow intangible assets (e.g. knowledge, learning and reputation) and to reach stakeholder integration. By capitalizing on the advantages of CSR practices and international exposure, firms can enhance complementary benefits among CSR dimensions.
Summarizing, market fluctuations that generate uncertainty can be overcome by companies that pursue stakeholder engagement and integration and use innovation to tackle unpredictable environments through development of complementary CSR dimensions and synergies that rise among CSR dimensions. Based on the previous arguments, it can be hypothesized that:
Hypothesis 1: Perceived high uncertainty in the business environment strengthens the likelihood of
synergies among CSR dimensions, whereas perceived low uncertainty strengthens the likelihood of trade-offs among CSR dimensions.
Complexity
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identify and integrate stakeholders other obstacles may emerge. Conflict between stakeholders concern may be present due to proliferation of distinct interests and building synergies among stakeholders may be harder (Ogden and Watson, 1999; Rowley and Moldoveanu, 2003). Moreover, complexity also hinders the positive interaction between stakeholder integration and development of proactive environmental directions (Rueda-Manzanares et al., 2008).
Furthermore, organizations that are operating in a complex environment will experience difficulties in identifying key strategic resources to develop future directions (Amit and Schoemaker, 1993) and obstacles in exploiting resources in a valuable way (Black and Boal, 1994). Due to these difficulties implementation of significant changes to run CSR strategies is hard. Hence, it is even harder for an organization to implement environmental strategies with synergetic benefits across CSR dimensions. Development of CSR strategies translates into significant organizational changes aiming to include stakeholder integration at all company levels and redesign of company‘s processes and technological improvements and product stewardship (Russo and Fouts, 1997; Hart, 1995). Such changes require strong coordination form managers. However, investments in CSR practices become more difficult under a complex context (Dögl and Behnam, 2014). As a result CSR managers will have to compromise and engage in trade-off activities. They will only invest in a particular number of CSR actions without addressing the whole universe of stakeholders. As previous literature already suggested, companies operating in such a complex environment will undertake only minor improvements regarding their responsibility policies (Russo and Fouts, 1997). With this kind of small improvements no complementarity among the CSR dimensions will result.
From a financial point, companies experiencing complex environments will act more vigilant in regards to CSR expenses as they will redirect their financial means to traditional operational activities to stabilize and preserve their position in the market (Campbell, 2007). Due to cost constrains companies will act less social responsible in such environments (Chen et al., 2015) and will not have the incentives to develop synergies among their CSR dimensions. Thus, trade-offs among social and responsible practices will be installed. As a summary, companies will find it challenging to develop synergies among CSR dimensions in a complex business environment due to difficult shareholder integration, problematic coordination procedures and large investments needed to respond to complex change. Cost wise, companies will direct few resources to CSR actions if they perceived the environment as complex and more trade-offs will occur among CSR dimensions as a result of limited financing. Based on the above arguments, I propose:
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Munificence
The majority of the studies investigating this exogenous factor, originated from the paper of Dess and Bear (1984), who defined munificence as the degree of resource availability within an environment that can support revenue growth. In a munificence environment the industry is growing providing opportunities for companies to develop slack resources for exploration and innovation activities (Decarolis and Deeds, 1999; Nohria and Gulati, 1996). To beneficiate from these opportunities corporations engage in new cross-functional projects integrating responses from all stakeholders‘ groups by aligning the sustainable desirable outcomes (Rueda-Manzanares; Aragon-Correa and Sharma, 2008; Surocca et al. 2010) and each synergies among CSR dimensions.
Operating in a rich munificent environment companies have the opportunity to develop dynamic capabilities and competitive advantage by integrating proactive sustainable strategies (Mcevily and Zaheer, 1999; Aragon-Correa and Sharma, 2003). To achieve new capabilities, firms improve managerial and organizational processes, integrate current endowments of technology, requirements from customer and associate products and benefits to reach synergies among stakeholder constellation (Teece and Pisano, 1994; Danneels, 2011).
A munificent context positively affects the organizational structure by transforming the companies into more decentralized structures, allowing for cross-functional projects (Yasai-Ardekani, 1989) and therefore foster innovation for proactive strategies and collaboration for stakeholder integration. Therefore, according to Aragon-Correa and Sharma (2003) decentralization leads to proactive CSR strategies, which are attainable by capitalizing on synergies among firm‘s functions and dimensions. Moreover, a munificent business environment presents a multitude of incentives from fiscal or state subsidies and premiums for greener technologies and attractive financing. Such programs raise the interest of companies for developing CSR strategies and benefit from synergies among CSR through sustainable competitive advantage (Chen et al. 2015, Lee et al., 2014; Rothenberg and Zyglidopoulos, 2007). In sum, the previously mentioned arguments explain how munificence affects the development of synergies among CSR dimensions through sustainable competitive advantage, innovation, flexible organizational structures and governmental incentives for green technologies. Accordingly, I propose the following hypothesis:
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3. Methodology
3.1
Data Source and sample
The data included in this paper has been constructed using multiple databases. I collected data about the CSR dimensions (employee, environment and customer & supplier) from Aseet4 for the year 2014. This database provides information about the responsible behavior of around 4,500 companies. Secondly, I collected data from Datastream and Orbis for the independent variables, as well as for the control variables. The information from Datastream and Orbis comprised of statistics at industry and company levels for the years 2015 and 2014. From a geographical perspective, data has been collected for 3 Western European countries (France, Germany and United Kingdom) and United States, as well as one emerging country, China. This selection has been made based on previous literature that tested similar hypotheses on these nations (Aragon-Correa et al., 2013; Boyd, 1990; Cavaco and Crifo, 2014; Chen et al., 2015; Crifo, 2016; Dess and Beard, 1984; Martin-Tapia et al., 2008; Rueda-Manzanares et al., 2008; Sharma et al., 2007) as presented in table 10 from the Appendix.
Moreover, this cross-sectional analysis has been conducted on a combination of 8 industries such as: aerospace and aircraft, automotive and parts, chemical, construction and materials, electronic equipment, food producers, oil and gas and pharmaceutical industry to reflect the tested contextual factors: uncertainty, complexity and munificence. Nonetheless, this selection is also supported by the dynamic evolution and particular growing characteristics of these industries. This mixture of industries had been prepared base on extant papers that studied such contextual factors (Aragon-Correa et al., 2013; Boyd, 1990; Cavaco and Crifo, 2014; Chen et al., 2015; Crifo, 2016; Dess and Beard, 1984; Martin-Tapia et al., 2008; Rueda-Manzanares et al., 2008; Sharma et al., 2007). By combining service and manufacturing industries, as well as more harmful sectors like oil and gas, this study is responding to research call formulated by scholars to simultaneously take into account such relevant sectors.
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Measurements
Measure for CSR dimensions
Asset4 is a database under the Datastream umbrella which collects information at a firm level from more than 700 individual data points, resulting in over 250 key performance indicators (KPIs). These KPIs are grouped into 18 main categories, under 4 main study pillars: Economic Performance, Environmental Performance, Social Performance and Corporate Governance Performance. For the purpose of this paper not all 18 categories have been used. I took into consideration only the ones relevant to study our assumptions from 2 main pillars, Environment and Social Performance. The Environmental Performance pillar consists of 3 categories: Resource Reduction, Emission Reduction and Production Innovation. For this pillar 2 categories were taking into account to form the Environment CSR, namely: Resource Reduction and Emission Reduction. Moreover, a rearrangement of these categories have been undertaken, moving the category of ―Product Innovation‖ from the Environment Performance class, under the universe of customers & supplier CSR to construct a comparable set of indices for all CSR dimensions (customer & supplier, employee and environment) as presented in the below table. The Social Performance main class has been divided to form the 2 remaining CSR dimensions, Employee dimension and Customer & Supplier dimension. Employee CSR initiatives includes the following categories Employment Quality, Health & Safety, Training & Development, Diversity and Opportunity, while the Customer & Supplier CSR dimension include 2 categories: Product Responsibility and Product Innovation. Moreover, from the Social Performance pillar one category was removed as it was not relevant for this study, namely the Community category.
17 MAIN PILLAR CATEGORY NAME CATE GORY CODE DESCRIPTION Environment Resource Reduction ENRR
Measures a company's management commitment and effectiveness towards achieving an efficient use of natural resources in the production process. It implies to reduce the use of materials,
energy or water, and to find more eco-efficient solutions. Emission
Reduction ENER
Measures a company's management commitment and effectiveness towards reducing environmental emission in the production and operational stages. It reflects a company's capacity
to reduce air emissions, waste, hazardous waste, water discharges, spills or its impacts on biodiversity.
Product
Innovation ENPI
Measures a company's management commitment and effectiveness towards supporting the development of eco-efficient products or services. It reflects a company's capacity to reduce the
environmental costs and burdens for its customers, and creating new market opportunities through new environmental technologies or eco-designed.
Social
Employment
Quality SOEQ
Measures a company's management commitment and effectiveness towards providing high-quality employment benefits and job conditions. It implies workforce loyalty and productivity by
fair employment benefits, and by focusing on long-term employment. Health &
Safety SOHS
Measures a company's management commitment and effectiveness towards providing a healthy and safe workplace. It implies a concern for the physical and mental health, well-being and stress
level of all employees. Training &
Development SOTD
Measures a company's management commitment and effectiveness towards providing training and development (education) for its workforce. It implies developing the workforce's skills,
competences, employability and careers in an entrepreneurial environment. Diversity &
Opportunity SODO
Measures a company's management commitment and effectiveness towards maintaining diversity and equal opportunities in its workforce. It implies promoting an effective life-work balance, a family friendly environment and equal opportunities regardless of gender, age, ethnicity, religion
or sexual orientation. Product
Responsibility SOPR
Measures a company's management commitment and effectiveness towards creating value-added products and services upholding the customer's security. It reflects a company's capacity to produce quality goods and services integrating the customer's health and safety, and displaying
accurate product information and labelling.
Table 1: Description of CSR categories
Final structure of CSR dimensions after rearrangement
CATEGORY NAME CATEGORY CODE NO OF KPI PER CATEGORY TYPE
Environmental CSR
Resource Reduction ENRR 94
Percent 100=100%
Emission Reduction ENER 130
Percent 100=100%
Employee CSR
Employment Quality SOEQ 75
Percent 100=100%
Health & Safety SOHS 61
Percent 100=100%
Training & Development SOTD 38
Percent 100=100%
Diversity & Opportunity SODO 48
Percent 100=100%
Customer & Supplier CSR
Product Responsibility SOPR 113
Percent 100=100%
Product Innovation ENPI 94
Percent 100=100%
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Measure for profitability
Consistent with previous literature that studied CSR dimensions and contextual factors I used Return on Assets (ROA) to measure firm profitability (Cavaco and Crifo, 2014; Chen et al, 2015). Return on Assets was calculated based on pre-tax income divided by total assets. Pre-tax income was chosen in order to eliminate the effect of corporate tax that differs by country. Moreover, to account for better results ROA was calculated for the year 2015, while all the independent and control variables were for the year 2014.
Measure for contextual drivers
Uncertainty illustrates unpredictable evolution of events within an industry. This contextual factor was
measured with the aid of a regression analysis measuring the variability of the industry sales evolution (Boyd, 1990; Chen et al., 2015; Dess and Beard, 1989; Keats and Hitt, 1988). Although some extant literature proposes a time interval of five years (Boyd, 1990; Chen et al., 2015), while others ten years (Dess and Beard, 1989), I took into consideration eight years. This number was chosen to better operationalize this variable, as the five years interval was too short for this study. And also due to Orbis data base constrain, which provided data up to 2007 for industry sales. Therefore, uncertainty for 2014 is calculated based on industry sales evolution from 2007 to 2014. To operationalize uncertainty I collected the sales for each three-digit SIC industry from Orbis and calculated uncertainty in a two-step procedure. First, I regressed the natural logarithm of total industry sales and an index variable of years, with time as the independent variable. Then, the antilog of the standard error of regression slope coefficient was used to capture the uncertainty of each industry.
Complexity was measured by using the Herfindahl-Hirschman Index (HHI-index) for industry
concentration, which translates into company‘s sales divided by the total sales in the industry within a sector (Boyd, 1990). I calculated the HHI-index for each industry taking into account the first 50 companies by sales. This number was chosen to chosen to better operationalize this variable as several industries were extremely fragmented. The other two options to calculate the HHI-index by summing up the squared the market share of first 5 or 20 companies were inappropriate for the industries within this paper. This index can have a minimum of 0 and a maximum of 1, which means that 0 translates into a perfect competition and 1 into perfect monopoly (Boyd, 1990).
Munificence illustrates the availability of resources to support the growth of an industry. This variable
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Control variables
The analysis includes control variables that have been mentioned in similar studies that tackled CSR practices and contextual drivers. Among such variables are mentioned: firm size, R&D intensity, firm age, industry and country dummies.
Firm size may influence the distribution of resources to each stakeholder group (Rueda-Manzanares et al.,
2008). In this paper firm size is approximated by the natural logarithm of total employees within the firm (Waddock and Graves, 1997). Although other studies measure firm size by total sales, this measurement was not used due to variation of prices by country (Aragon-Correa et al 2013; Crifo 2016; Rueda-Manzanares et al., 2008, Martin-Tapia et al., 2008; Sharma et al., 2007).
The level of R&D intensity may influence the selection and development of CSR practices. McWilliams and Siegel (2000) state that the expenditure spend on R&D is correlated with the CSR dimension through the innovation product or process. Companies can engage in innovative product exploration or product differentiation to respond to environmental pressures and customers demand (Cavaco and Crifo, 2014; Crifo 2016). Consistent with previous studies (McWilliams and Siegel, 2000; Crifo 2016) R&D intensity was calculated based on R&D expenditure divided by sales.
The firm age can also influence how a company tackles CSR matters, as an older firm may already have installed organizational procedures for CSR and knows how to deal with responsible issues (Chen et al, 2015; Meng et al., 2013).
Industries dummies were elaborated as it has been shown that business sectors can influence the
development of CSR actions (McWilliams and Siegel, 2000). Some industries have specific characteristics that can help a firm develop synergies among its CSR dimensions to reach new competitive advantages (McWilliams and Siegel, 2000). Based on three-digit SIC code a dummy has been created for each of the 8 aforementioned industries.
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3.2
Analysis technique
The analysis was based on the paper of Athey and Stern (1998) and Crifo (2016). To test the formulated hypotheses a linier regression has been used where the complementary or substitution effect among dimensions was investigated. In order to examine these effects seven interactions have been created as suggested by Crifo (2016), namely:
1. Interaction1_0=1 if the firm had deployed only environmental CSR activities; and=0 if the firm had not invested in any CSR dimensions;
2. Interaction2_0=1 if the firm had deployed only employee CSR activities; and=0 if the firm had not invested in any CSR dimensions;
3. Interaction3_0=1 if the firm had deployed only customer and supplier CSR activities; and=0 if the firm had not invested in any CSR dimensions;
4. Interaction4_0=1 if the firm had deployed both environmental and employee CSR activities; and=0 if the firm had not invested in any CSR dimensions;
5. Interaction5_0=1 if the firm had deployed both environmental and customer & supplier CSR activities; and=0 if the firm had not invested in any CSR dimensions;
6. Interaction6_0=1 if the firm had deployed both employee and customer & supplier CSR activities; and=0 if the firm had not invested in any CSR dimensions;
7. Interaction7_0=1 if the firm had deployed CSR activities in all three dimensions; and=0 if the firm did had not invested in any CSR dimensions.
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4. Results
4.1
Descriptive statistics
An overview of the sample data can be provided by illustrating the descriptive statistics. To test for the normal distribution of the sample all the variables were analysed based on their Skewness and Kurtosis. All sample felt within the requirements of a Skewness below 3 and Kurtosis below 5. More specifically, all variables had a Skewness and Kurtosis below 1.
In general the profitability ratio measured by ROA indicated that in average the companies within the sample had a profit five times greater than their total assets, with an average number of employees of 15,600 (antilog of 9,665). R&D expenditure represented around 9% of companies‘ sales and in average firms had an age of 57 years. In terms of industry concentration, complexity showed that the industries within this study are rather competitive with and average HHI of 0.247.
. Variable Obs Mean Std. Dev. Min Max Skewness Kurtosis 1 ROA 241 5.004 9.165 (45.920) 43.180 0.000 0.000 2 Size (employees) 241 9.655 1.619 5.545 13.189 0.100 0.007 3 R&D Intensity 241 0.093 0.533 0.000 8.129 0.000 0.000 4 Firm Age 241 57.456 54.735 2.000 349.000 0.000 0.000 5 Uncertainty 241 1.102 0.027 1.073 1.157 0.000 0.397 6 Complexity 241 0.247 0.180 0.030 0.995 0.000 0.000 7 Munificence 241 1.037 0.077 0.854 1.114 0.000 0.002 Table 3: Descriptive statistics
22 Variables 1 2 3 4 5 6 7 1 ROA 1 2 Size (employees) 0.2157*** 1 3 R&D Intensity -0.2043*** -0.2312*** 1 4 Firm Age 0.0547 0.2132*** -0.0785 1 5 Uncertainty -0.1327** -0.3581*** 0.2309*** -0.1702*** 1 6 Complexity 0.1087 0.1949*** -0.0659 0.1784*** 0.0249 1 7 Munificence 0.4671*** 0.2231*** 0.1026 0.1234 -0.1995*** 0.0313 1 *** p<0.01, * *p<0.05, * p<0.1
Table 4: Matrix correlation
4.2
Hypotheses testing
Each of the hypothesis was tested using linear regression with ROA as the dependent variable and each interaction from 1 to 7 as the independent variables. For all hypotheses all control variables have been included in each of the seven regressions tested. Moreover, each hypothesis was tested by running two models for a business environment characterized by high uncertainty and low uncertainty; high complexity and low complexity; high munificence and low munificence. The delimitation between high and low was made by spilling the sample into two sub-sample based on the median of each of the three contextual drivers. Therefore, a total of six models have been analyzed and for each of these six models seven regressions were investigated independently, plus a model without the influence of any contextual factor. The following section will only present the results of the complementary and substitution effects, namely the coefficients related to each interaction and not the overall results of the regressions, as this is not the purpose of this study. However, the results for Hypothesis 1, model under high uncertainty levels is presented as an illustration of each of the seven regressions. All the remaining five models‘ results plus a model without the effect of any contextual factors can be consulted in the Appendix.
23 Model with high uncertainty levels
Dependent variable ROA
Variables Interaction 1 Interaction 2 Interaction 3 Interaction 4 Interaction 5 Interaction 6 Interaction 7
Size (number of employees) 1.45*
(0.81) 1.83** (0.78) 0.74 (0.79) 1.56** (0.78) 0.79 (0.80) 1.01 (0.79) 1.10 (0.79) R&D intensity -4.05*** (1.30) -4.02*** (1.28) -4.20*** (1.30) -4.03*** (1.30) -4.20*** (1.31) -4.12*** (1.31) -4.10*** (1.31) Firm Age -0.00 (0.02) -0.00 (0.02) -0.01 (0.02) 0.00 (0.02) -0.01 (0.02) -0.00 (0.02) -0.00 (0.02) Interaction 1 (Environmental CSR only) -2.21 (2.79) Interaction 2 (Employee CSR only) -5.10* (2.57) Interaction 3
(Customer & supplier CSR only)
3.28 (2.91) Interaction 4
(Environmental and Employee CSR)
-3.29 (2.54) Interaction 5
(Environmental and Customer & Supplier CSR)
2.92 (3.07) Interaction 6
(Employee and Customer & Supplier CSR)
1.11 (2.88) Interaction 7
(Environmental, Employee and Customer & Supplier CSR)
0.43 (2.98)
Aerospace and aircraft industry 1.96
(3.51) -2.34 (3.45) 9.48*** (3.62) -1.80 (3.49) 9.69*** (3.61) -1.89 (3.52) -1.90 (3.56) Automotive and spare parts industry
Chemical industry
Construction and materials industry Electric equipment industry
Food producers industry Omitted Omitted 11.71***
(3.12) Omitted
11.98***
24 Model with high uncertainty levels
Dependent variable ROA
Variables Interaction 1 Interaction 2 Interaction 3 Interaction 4 Interaction 5 Interaction 6 Interaction 7
Oil & gas industry -12.50***
(3.08) -11.96*** (3.03) Omitted -12.24*** (3.06) Omitted -12.20*** (3.11) -12.31*** (3.10) Pharmaceutical industry 4.29 (3.02) 3.87 (2.95) 17.10*** (2.65) 4.42 (2.96) 17.13*** (2.66) 4.86 (3.01) 4.72 (2.99)
China Omitted Omitted Omitted Omitted Omitted Omitted Omitted
France -2.78 (7.47) -1.04 (7.36) -7.16 (7.94) -2.30 (7.41) -6.74 (7.99) -4.94 (7.98) -4.21 (7.99) Germany -4.69 (8.73) -2.84 (8.63) -7.43 (9.01) -4.76 (8.68) -6.37 (8.87) -5.69 (9.05) -5.02 (8.90) UK 0.90 (6.98) 2.85 (6.87) -3.40 (7.30) 1.28 (6.88) -2.91 (7.30) -1.33 (7.28) -0.70 (7.23) US -0.72 (6.61) 0.31 (6.50) -3.88 (6.90) -0.75 (6.54) -3.38 6.87 -2.12 (6.84) -1.65 (6.82) Constant -5.01 (11.53) -7.99 (11.30) -9.79 (11.11) -5.88 (11.38) -10.46 (11.20) -1.24 (11.96) -2.22 (12.00) Observations 100 100 100 100 100 100 100 R-squared 0.41 0.43 0.41 0.42 0.41 0.41 0.41 F test 5.69*** 6.20*** 5.79*** 5.85*** 5.73*** 5.61*** 5.59***
Table 5: Result of investing in CSR dimensions in high uncertainty context
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Hypothesis 1
The results of the model without any contextual factors and the first two models under an uncertain context are illustrated in Table 6. The results from the model without the contextual are mostly not insignificant except, investing in Environmental CSR and Customer & Suppliers CSR which has a positive coef. 2.6 (p<0.1). In this case the pair of CSR actions is complementary as define by Athey and Stern (1998), because their aggregated coefficient is 2.61, which is greater than the sum of the individual coefficient of each dimensions of 1.51, composed of the coefficient of Environmental CSR of 1.15 and the coefficient of Customer & Supplier CSR of 0.36.
The results are inconclusive to indicate whether a low perceived uncertainty in the business environment weakens the probability of synergies among CSR dimensions, or high perceived uncertainty strengthens the likelihood of synergies. Most of the results are not significant, except investing in Employee CSR only under a high perceived uncertain environment, which negatively affect the financial performance (coef. -5.10, p<0.05). Therefore, Hypothesis 1 is not supported.
Model without contextual factors
Model with high uncertainty
Model with low uncertainty
Type of interaction Sign Coefficient Sign Coefficient Sign Coefficient
One CSR dimension
Environmental CSR only + 1.15 - 2.22 + 3.42 Employee CSR only - 0.24 - 5.10** + 2.87 Customer & supplier CSR
only + 0.36 + 3.29 - 1.40
Two CSR dimensions
Environmental CSR and
Employee CSR + 0.26 - 3.29 + 2.63 Environmental CSR and
Customer & Supplier CSR + 2.61* + 2.93 + 2.46 Employee CSR and
Customer & Supplier CSR + 1.86 + 1.12 + 2.31
Three CSR dimensions
Environmental, Employee and Customer & Supplier CSR
+ 1.46 + 0.44 + 2.07 *** p<0.01, * *p<0.05, * p<0.1
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Hypothesis 2
The results of the models testing complementary and substitution effect under high and low complexity are depicted in Table 7.Most of the results are inconclusive to indicate whether a low perceived complexity in the business environment strengthens the likelihood of synergies among CSR dimensions, or a high perceived complexity strengthens the likelihood of trade-offs.
Although the majority of the results are not significant, it can be agreeable to some extent that a business context characterized by low complexity is favorable to more complementarity between CSR dimensions. This affirmation is supported by the results among two pairs of interactions, namely Environmental CSR and Customer & Supplier CSR (coef.=3.95, p<0.05) pair and Employee and Customer & Supplier pair (coef.=3.70, p<0.1). More specifically, both pairs of interactions predict complementarity effect between the tested CSR dimensions, with the coefficient of each pair being stronger that than the sum of their individual effects. They are complementary, as define by Athey and Stern, (1998), because the coefficient associated with the pair, Environmental CSR and Customer & Supplier CSR is 3.95, which is stronger than the sum of their individual effects, which is 1.79 (the coefficient for Environmental CSR only is 0.74 and the coefficient for Customer & Supplier CSR only is 1.05). Employee CSR and Customer & Supplier are complementary because their aggregated coefficient is 3.70, which is greater than the sum of the individual coefficient of each dimensions of 0.71, composed of the coefficient of Employee CSR of -0.34 and the coefficient of Customer & Supplier CSR of 1.05. Therefore, Hypothesis 2 on complementarity under low complexity is partially supported.
Model without contextual factors
Model with high complexity
Model with low complexity
Type of interaction Sign Coefficient Sign Coefficient Sign Coefficient
One CSR dimension
Environmental CSR only + 1.15 + 1.13 + 0.74 Employee CSR only - 0.24 + 0.13 - 0.34 Customer & supplier CSR
only + 0.36 + 0.22 + 1.05
Two CSR dimensions
Environmental CSR and
Employee CSR + 0.26 + 0.60 + 0.27 Environmental CSR and
Customer & Supplier CSR + 2.61* + 1.71 + 3.95** Employee CSR and Customer
& Supplier CSR + 1.86 + 0.14 + 3.70*
Three CSR dimensions
Environmental, Employee and
Customer & Supplier CSR + 1.46 + 0.70 + 2.96 *** p<0.01, * *p<0.05, * p<0.1
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Hypothesis 3
Most of the results are not significant, except pursuing Environmental CSR and Customer & Supplier CSR (coef.=3.63, p<0.05) under a high munificent uncertain environment. The elements of this pair of CSR are complementary as define by Athey and Stern (1998), because their aggregated coefficient is 3.63, which is greater than the sum of the individual coefficient of each dimensions of 2.45, composed of the coefficient of Environmental CSR of 2.30 and the coefficient of Customer & Supplier CSR of 0.15. Therefore, Hypothesis 3 on complementarity under perceived high munificence is partially confirmed.
Model without contextual factors
Model with high munificence
Model with low munificence
Type of interaction Sign Coefficient Sign Coefficient Sign Coefficient
One CSR dimension
Environmental CSR only + 1.15 + 2.30 - 0.37 Employee CSR only - 0.24 + 1.52 - 1.93 Customer & supplier CSR
only + 0.36 + 0.15 + 0.76
Two CSR dimensions
Environmental CSR and
Employee CSR + 0.26 + 1.82 - 1.38 Environmental CSR and
Customer & Supplier CSR + 2.61* + 3.63** + 1.62 Employee CSR and
Customer & Supplier CSR + 1.86 + 2.38 + 1.70
Three CSR dimensions
Environmental, Employee and Customer & Supplier CSR
+ 1.46 + 2.84 + 0.30 *** p<0.01, * *p<0.05, * p<0.1
28
Summary of complementary and substitution effects among pairs of CSR
29 Type of interaction - Two CSR dimensions Model without contextual factors Model with high uncertainty
Model with low uncertainty
Model with high complexity
Model with low complexity
Model with high munificence
Model with low munificence
Environmental CSR
and Employee CSR substitution complementarity substitution substitution substitution complementarity complementarity
Environmental CSR and Customer & Supplier CSR
complementarity* complementarity complementarity complementarity complementarity ** complementarity * complementarity
Employee CSR and Customer & Supplier CSR
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5. Discussion
Findings and theoretical implications
The theoretical implications that this study brings in the management literature are two-sided. Firstly, it was suggested that the belief that CSR is a unitary concept is obsolete, as a company can follow different CSR directions, mainly addressing green, employee and customer & supplier practices to respond to its stakeholder groups (Waddock and Graves, 1997; Barcos et al., 2013; Cavaco and Crifo, 2014; Crifo, 2016). Therefore, due to each stakeholder‘s distinct needs, these CSR dimensions can be complementary or substitutable. Secondly, it was hypothesized that these interaction effects of complementary or substitution can be strengthened or weakened depending on three industry contexts. To this date this research is among the first few studies to investigate empirically the complementarities or substitution of CSR dimensions and the influence of uncertainty, complexity and munificence on corporate environmental responsibility, simultaneously.
Based on a cross-sectional dataset from 5 countries and 8 diverse industries for the year 2014, I found that the role of uncertainty in explaining a strengthening or a weakening influence on synergies at high and low levels of instability was not supported. Complementarity effect exists between Environmental CSR and Customers & Supplier CSR in a normal environment, but also when competition is high and resources are available. Moreover, in a low complexity environment, companies appear to build complementarities between their employee responsible practices and Customer & Supplier CSR.
I could not support with significant results Hypothesis 1, regarding the effect of uncertainty on the increase or decrease of synergies among CSR dimensions. These results merits future empirically tests as previous scholars also found conflicting results between uncertainty and CSR practices. Chen et al. (2015) proved that in an unstable environment companies are more likely to become more responsible by investing in CSR actions, while Rueda-Manzanares el al., (2008) could not find any significant effect of this contextual factor between stakeholder integration and CSR actions. Rueda-Manzanares el al., (2008) argue that one reason for the inconclusive results is the fact that uncertainty can have inverted U-shape or concave relation with the analyzed variables.
31
environment where companies experience low levels of complexity, translating in increase competition and great diversity among firms. Therefore, companies will make efforts and capitalized on their synergies among Environmental and Customer & Supplier CSR practices and Employee and Customer & Supplier CSR practices in order to respond to the increased market competition and maintain their financial and operational performance. Moreover, synergies between these Employee CSR and Customers & Supplier CSR are easily to build as they do not show conflicting objectives among their stakeholders (Cavaco and Crifo, 2014).
A munificent environment where access to resources is available makes a firm to become more responsible conscious by building synergies among Environmental CSR and Customer & Supplier CSR. Although Cavaco and Crifo (2014) show a substitution effect between this pair of CSR based on the motivation that they have different stakeholder objectives, a firm will find it more easy to build complementarities in an environment where resources permits between two CSR dimensions that in a normal environment are substitutes.
Practical implications
32
Limitations and future research
As it can be expected this study presents some limitations, which in the same time can provide interested scholars in the CSR field with possibility for a future research. Firstly, this study has been empirically tested using cross-sectional data for the year 2014. This type of analysis constrains the researcher to a specific small period of time and the findings resulted from this method can limit the generalization of the results over time. Trying to tackle this issue I introduced in the paper on year lag between the dependent variable and all the other variables. However, some of the results were inconclusive. Consequently, an extended study using cross-section time-series data can provide better insights.
Secondly, this paper was based only on public traded firms due to the databases used for data collection. Therefore, in order to improve the results and to expand the findings to private companies, a more comprehensive study including all types of organizations can be conducted. Although, harmonized information regarding CSR activities is hard to collect on private firms. Another limitation of the data used, consists on the timeframe for computing the three industry contexts. An increased timeframe of over 10 years could offer more accurate findings that include industry changes over time.
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6. Conclusion
34
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