Climate Change Institutional Pressure: the role of climate change risk and opportunity perception in the effects of institutional pressure on firms.
MSc thesis Supply Chain Management,
Rijksuniversiteit Groningen, Department of Operations July 13, 2020 Lars Gorter S2962152 l.j.gorter@student.rug.nl Supervisors: Dr. ir. T. Bortolotti Dr. ir. S. Boscari Secondary supervision: Prof. dr. D.P. van Donk
Summary: Climate change becomes an increasing problem for humans. As such, governments exert increasing pressure on firms to reduce their emissions. Studies suggest that the perception of climate change risks and opportunities is a determining factor in how firms translate this pressure into firm outcomes. While some see climate change as a business risk and take confirmatory strategies, others see it is an opportunity and take a more proactive stance. This study explores the effect of the perception of climate change risks and opportunities on the relationship between institutional pressures and the adoption of low-carbon supply chain management practices, as well as the effect of climate change motivated institutional pressure on the financial performance of firms. The regression analysis provided different results than the formulated hypotheses. In the end, it is argued suggested the type of policy regime a government enacts facilitates the adoption of LCSM practices.
Keywords: Low-carbon supply chain management, climate change, opportunity and risk perception, institutional pressure.
Index
INTRODUCTION ... 3
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT ... 4
LCSM AS AN EXTENSION OF GSCM ... 4
RISKS AND OPPORTUNITIES RELATED TO CLIMATE CHANGE ... 5
HYPOTHESIS DEVELOPMENT ... 6
EXTERNAL PRESSURE REDUCES EMISSIONS ... 7
EXTERNAL PRESSURES IMPROVE FINANCIAL PERFORMANCE ... 8
CLIMATE CHANGE PERCEPTION BY FIRMS ... 9
METHODOLOGY AND RESEARCH DESIGN ... 13
DATA COLLECTION AND CONSTRUCTION OF SAMPLE ... 13
OPERATIONALIZATION OF VARIABLES ... 15
RESULTS ... 18
MODEL 1:LSCM ADOPTION ... 19
MODEL 2:FINANCIAL PERFORMANCE ... 22
DISCUSSION OF RESULTS ... 26
CONCLUSION AND IMPLICATIONS ... 29
Introduction
Climate changes poses a credible threat to businesses, as the failure to mitigate its effects or respond to climate change is seen as one of the most impactful risks to companies (World Economic Forum, 2018). Firms are subjected to mounting pressures from for example governments to implement measures that reduce their environmental footprint (Linnenluecke et al., 2011). Due to this pressure, firms adopt varying organizational responses that differ from proactive to passive stances towards the mitigation of climate change (Lozano, 2015; Sharma, 2000). Green supply chain management (GSCM) measures such as the low-carbon measure of implementing emission targets, are practices that can be used to reduce this environmental footprint (Jira & Toffel, 2013). Even though the relationship between external pressures and GSCM is well studied and found to be motivating firms to adopt such practices (Daddi et al., 2016; Sarkis et al., 2011; Q. Zhu et al., 2013), the role that climate change plays in this remains understudied (Das & Jharkharia, 2018). Furthermore, evidence of the effect of this pressure on the financial performance remains inconclusive (Li & Ramanathan, 2018).
Recent research by for example Elijido-Ten (2017), Gasbarro et al. (2017), and Roman Pais Seles et al. (2018) suggest that there is a role for the perception of climate change risks and opportunities in the adoption of GSCM, since this perception can be a driver if climate change is seen as an opportunity or a barrier if seen as a risk. However, this research remains rather conceptual. This research takes this as a motivation, as well as providing an empirical account to the understudied effects of climate change and institutional pressure on firms. The objectives of this research are to study how the perception of climate change risks or opportunities impacts the relationship between the adoption of low-carbon measures and between institutional pressure and firm performance. Therefore, the following research questions are formulated: ‘How does the firm’s perception of climate change risks and opportunities impact the relationship between institutional pressure and LCSM adoption?”, and; “How does the firm’s perception of climate change risks and opportunities impacts the relationship between institutional pressure and firm performance?’’. This will be analyzed by using quantitative research methods and utilizing linear regression techniques.
assess the stringency of climate change regulation regimes as a proxy for institutional pressure. This research continues as follows. First, an overview of relevant literature on GSCM, its extension LCSCM, and climate change perception is given. Then, the insights form the literature review and theory will be used to develop hypotheses. Next, the research design is presented. This is followed by a presentation of the results. The results are then discussed and conclusions are drawn. This research concludes with a summary of this research as well as suggestions for further research.
Literature review and hypothesis development
LCSM as an extension of GSCM
Furthermore, the role of organizational characteristics in the implementation of GSCM has been examined. Hoejmose et al. (2012) studied the role of top management. Jabbour and De Sousa Jabbour (2016) examined the relationship between GSCM and green human resource management. Johnson (2015) considered the role that managers play in GSCM implementation. The financial and environmental performance of firms that implement GSCM have been studied as well (Bose & Pal, 2012; Green et al., 2012; Laosirihongthong et al., 2013; Miroshnychenko et al., 2017). Though research on the relation to climate change is fewer in number, driver and barriers, organizational characteristics, and performance outcomes interact with LSCM in a similar way as with GSCM (Das & Jharkharia, 2018; Grose & Richardson, 2013a; Hitchcock, 2012; Ibrahim et al., 2020; Liu et al., 2020; Shen et al., 2017). This research will be taking this perspective also.
Risks and opportunities related to climate change
Climate change poses significant risks and poses threats to business over a long time (World Economic Forum, 2018). The unpredictable nature and potentially large impacts of climate change on businesses makes it challenging (Stern, 2008). As a result, companies have been impacted by climate change (Böttcher & Müller, 2016; Jarvis & Ortega, 2010; Mozell & Thach, 2014; Nawaz et al., 2019; Rutty et al., 2017). In accordance with Gasbarro et al. (2017), and Bui and De Villiers (2017), climate change risks are defined as any corporate risk associated with climate change. In line with this, climate change opportunities are defined as any corporate opportunity associated with climate change.
emission targets imposed by governments are a source of regulatory risks (Cerutti et al., 2016). The mismanagement of this risk can result in increased operational costs for the firm (Wittneben & Kiyar, 2009). All other risks can be grouped into the “other” (market) category. Even though the third category is often referred to as “other”, this category mainly consists of market risks (Dasaklis & Pappis, 2013). An example hereof is potential reputational risks a company faces as part of climate change. Companies can get their reputation damaged when investing in products that have adverse effects on the climate (Lash & Wellington, 2007). Furthermore, climate change can negatively affect the operations of a firm. As Gasbarro et al. (2016) found, rising water temperatures negatively affects the reliability of machines firms use for the production of their products, creating a risk for the firms’ continued operations.
Climate change can also result in opportunities for firms. For example, the impact of the effects of physical climate change. Rising temperatures creates the possibility for energy companies to start the extraction of oil in the Arctic (Okereke et al., 2012). Also, in an analysis of the Dutch insurance sector, Botzen et al. (2010) found that the increased occurrence of extreme weather events opens up new markets for insurance companies to venture into. Warmer winters decrease the likelihood of frozen over roads, in turn decreasing the amount of claims insurance companies have to pay out for car accidents (Botzen et al., 2010). Policy changes can result in regulatory opportunities for firms. Elijido-Ten and Clarkson (2019) observed that telecommunication companies saw opportunities to jointly set energy standards for the industry so that the standards are in the companies’ best interest. Boiral (2006) found that green companies can obtain monetary gains through the cap and trade schemes. For “other” opportunities, firms that possess climate-related knowledge and capabilities can leverage that into the development of green products, to match shifting customer preferences (Gasbarro et al., 2017; Lash & Wellington, 2007).
Hypothesis development
External pressure reduces emissions
While there are various different stakeholders that exert pressure on a firm to reduce emissions, this study focuses on institutional pressures. According to stakeholder theory, different entities are subjected to the external effects an organization produces, making them stakeholders of a company (Freeman, 1984). As stakeholders can pressure a firm into environmental action, the capability to effectively manage stakeholders’ interest is key in order to achieve corporate success and sustainability (Delmas & Toffel, 2004; Sarkis et al., 2011). Regulatory bodies are an important stakeholder that exert institutional pressure to motivate corporate environmental strategies (C. Jones, 2010; Zailani et al., 2012).
Institutional theory is occupied with the relationship between the environment and organization, as well as the environment’s impact on the structures and processes of organizations (DiMaggio & Powell, 1983; Scott, 1987). Coercive isomorphic pressures make organizations to adopt specific strategies by which they adjust to be more homogeneous (DiMaggio & Powell, 1983). Under institutional theory, institutions such as regulatory bodies serve as a source of legitimate, coercive isomorphic pressure (DiMaggio & Powell, 1983; Rivera, 2004). As firms seek to legitimize their organizational practices, firms adopt practices that are deemed legitimate by their stakeholders, such as environmental management practices (Glover et al., 2014). Governmental bodies are able to exert coercive pressures on firms by enforcing laws and regulations (Hong & Guo, 2019; Malviya & Kant, 2017). Firms are subjected to an increasing amount of laws and regulations with as goal enforcing the participation of firms in climate change mitigation (Linnenluecke et al., 2011). As governments hold the power to influence organizational decision-making through enforcing compliance with environmental rules and regulations, coercive pressures can result in the implementation of environmental management practices (Sarkis et al., 2011).
between institutional pressures and the adoption of GSCM practices, little research has been conducted in the context of climate change. Jaaffar et al. (2018) suggest that institutional pressures motivated by climate change concerns drive Malaysian firms to increase their compliance with environmental regulations. However, they found that while the firms were receptive to the climate change concern, the firms abstained from committing extensive financial resources to environmental practices (Jaaffar et al., 2018). Others found that institutional pressure positively impacts corporate carbon reduction activities in their supply chains and creates momentum for increased carbon reduction activities of firms (F. Wang et al., 2019). By combining the theorized positive relationships between institutional pressure to reduce emissions and to implement GSCM practices, and institutional pressures motivated by climate change concerns, the following hypothesis is derived:
H1: Institutional pressure positively impacts the firms’ adoption of LCSM practices.
External pressures improve financial performance
regulations can trigger cost reduction and innovation processes. Furthermore, Qiu et al. (2018) have argued that strict environmental regimes reshape markets such that innovative firms can reap benefits. Taking this into account, the following hypothesis is proposed:
H2: Institutional pressure positively impacts a firm’s financial performance.
Climate change perception by firms
This thesis is about a firms’ perception of climate change risks and opportunities. That is, the recognition of those risks and opportunities by the firm. These risks and opportunities can affect a firms’ operations in a negative or positive way, respectively. The corporate perception of risks and opportunities is formed through the assumptions, perceptions and knowledge of managers within the firms. Previous research underlined the importance of the role of managers’ perceptions, assumptions and knowledge of environmental issues play in the operational and strategic decision-making of firms (Bremer & Linnenluecke, 2017; Buysse & Verbeke, 2003; Cheema et al., 2020; González-Benito & González-Benito, 2006; Sharma, 2000; Shepherd et al., 2017).
According to Sharma (2000), the perception of environmental issues as a risk or an opportunity influences managerial decision-making. This perception is influenced by the cognitive frames of the managers of firms and influenced by external stakeholder pressures such as regulatory pressure (Bundy et al., 2013; Vazquez Brust & Liston-Heyes, 2010). An example of this cognitive frame is when an environmental issue is seen as antithetical to the objectives of the firm, or vice versa as a business opportunity. As climate change can be perceived as having a significant impact on a firm’s operations, for example wineries that have to deal with drought and how that affects the grape harvest (Mozell & Thachn, 2014), it can elicit an organizational response form the firm (Busch, 2011). A perceived effect of climate change on a firm that is deemed as significant triggers organizational change processes in which organizational practices are altered in order to mitigate risks or profit from opportunities, within the frame of corporate beliefs (Berkhout, 2012).
to the policy regime and other passive operational strategies (Sharma, 2000). This is echoed by Elijido-Ten (2017), who found that when firm perceive climate change as a net risk (i.e. the company identified more climate change related risks than opportunities), these firms utilize confirmatory strategies, motivated by regulatory risk. Furthermore, it was found that companies who perceive climate change as a net opportunity take a more proactive approach in adopting environmental strategies, driven by these opportunities. Literature on environmental risk management serves as an additional confirmation, as proactive operational strategies from when market opportunities are recognized, and when regulatory risks are sensed, confirmatory, passive operational strategies are employed (Bui & de Villiers, 2017).
The natural resource-based view (NRBV) is a theory that integrates the natural environment into the resource-based view (Hart, 1995). The NRBV is a theory that holds that companies can gain sustainable, competitive advantages and enhanced firm performance through the exploitation of their resources, with as addition the strategic interplay between firms and their natural environment (Hart, 1995). This is in contrast to the traditional resource-based view, which theorizes that the competitive advantage of firms merely depends on their ability to amass firm-level resources, capabilities and competences that are hard to imitate, valuable, rare and non-substitutable by the competition (Barney, 1991; Olajide et al., 2019). For some companies, their resources can be leveraged in such a way that they can result in enhanced firm performance, if they are able to accurately scan the environment and recognize an opportunity. This further implies that firms adopt proactive operational strategies when climate change is framed as an opportunity.
(Baumgartner, 2014; Mitra & Datta, 2014). Also, having a green image as a result of adopting low carbon practices can be beneficial as it attracts eco-minded investors and customers, and can boost a firm’s reputation (Gupta & Kumar, 2013). To summarize, it is more attractive for a company to pursue climate change opportunities than address climate change risks.
There is varying evidence surrounding the relationship between a firm’s perception of climate change in terms of risks and opportunities and the firm’s strategy based on that. Elijido-Ten (2017) linked the perception of physical, regulatory and market climate change opportunities and risks to environmental performance. They found that firms that perceive climate change as a risk have a relatively poor environmental performance (Elijido-Ten, 2017). In a study of the Australian seafood industry, Fleming et al. (2014) found that when climate change risks were perceived outside of the production-related aspects of the supply chain, they were met with inaction due to a lack of a holistic focus on the supply chain and increased uncertainty. Nyberg and Wright (2016) found that when firms see climate change as a risk, firms focus on continuing their operations within the new reality of climate change rather than responding to climate change by engaging in carbon abatement climate change is incorporate within the existing business strategy. Jones and Levy (2007) provide a similar account. In a study of American firms, they state that that risk-aware firms engage in political action to keep emission reduction rules relatively lax, rather than engaging in actual emission reduction (C. A. Jones & Levy, 2007). Therefore, the following hypotheses are proposed:
H3a: Perceived A) regulatory, B) physical and C) other climate change risks negatively moderate the relationship between institutional pressure and the number of emissions targets a company has
environmental performance than their peers who perceive climate change as a risk. Furthermore, firms develop climate change strategies when they sense that this strategy will earn them substantial competitive advantages, such as increased financial performance (Böttcher & Müller, 2015; Wittneben et al., 2012). However when they predict to incur losses when implementing this strategy, they chose not to develop such strategies (Böttcher & Müller, 2015; Wittneben et al., 2012). In other words, if seen as an opportunity to enhance firm outcomes and gaining competitive advantages, investing in low-carbon supply chain management practices is used to achieve this. This suggests that when firms recognize climate change opportunities, they are more likely to adopt LCSM and increase their financial performance. Hence, the following hypotheses are proposed:
H4a: Perceived A) regulatory, B) physical and C) other climate change opportunities positively moderate the relationship between institutional pressure and the firm’s adoption of LSCM practices.
H4b: Perceived A) regulatory, B) physical and C) other climate change opportunities positively moderate the relationship between institutional pressure and the firm’s financial performance. By using these hypotheses, a conceptual model depicting the relationships between the
variables was created. The resulting conceptual model can be found in figure 1 below.
Figure 1: Conceptual model
Methodology and Research Design
The following section will clarify and give insight into the methodology used for this research. This thesis uses a quantitative research design. A quantitative research design employs a variety of quantitative analysis techniques, such as establishing statistical relationships between variables by using statistical modelling, with deductive reasoning as a basis (Khalid et al., 2012; Saunders et al., 2008). This method is suitable for this study, as the influence that variables on one another has is the subject of the analysis in this study. These variables are constructed through deductive reasoning, and are possibly related to each other.
Data collection and construction of sample
This research makes extensive use of data from the Carbon Disclosure Project (CDP). The data form the CDP is used in order to examine the implementation of emission targets by firms. Furthermore, the dataset was used to gather data on firms’ identification of risks and opportunities. The CDP is a useful source for climate change data of companies, as its research design makes the returns highly standardized data. Each year, the CDP surveys companies on how climate change is measured, how it affects their operations and supply chain, and the actions companies undertake to mitigate the possible negative effects of climate change (CDP, 2020). Companies participate and disclose this information on a voluntary basis. Due to its extensive use in other studies, the CDP can be seen as a important and credible source of information about the climate change strategies of firms (Blanco et al., 2016, 2020; Elijido-Ten, 2017; Gasbarro et al., 2017; Mateo-Márquez et al., 2019).
Table 1: Composition of sample
Operationalization of variables
Dependent variable for model 1: Low-carbon supply chain management adoption
The dependent variable measures low-carbon initiatives of a firm. The dependent variable used in this research is the amount of emission reduction activities a company has implemented in the reporting year. This variable consists of any initiative a firm has with as goal the reduction of firm emissions. From the CDP questionnaire, question CC3.1 was used to construct this variable. The question reads “Did you have an emissions reduction or renewable energy consumption or production target that was active (ongoing or reached completion) in the
reporting year?”. Renewable energy consumption and emission reduction targets were combined as the two are often linked (Dogan & Seker, 2016; Fais et al., 2016).
Dependent variable for model 2: Firm performance
A separate model was tested in order to study the interplay of institutional pressure, firm performance, and the perception of climate change in terms of risks and opportunities. In this model, the dependent variable for emission targets and the control variable for firm performance were switched, making the variable for firm performance the dependent variable and the variable for emission targets an independent variable. The construction of this variable is outlined in the section for control variables.
Independent variable: Institutional pressure
In order to measure institutional pressure, data from the Climate Change Performance Index (CCPI) by Germanwatch was used. Germanwatch scores and ranks the performance of climate change regimes of 58 countries on a yearly basis (Burck, 2019). The measure for institutional pressure therefore captures the pressure exerted by governments motivated by climate change. For the ease of interpretation of the output of the regression, this value is standardized.
Moderating variable: Climate change risk and opportunities
Control variables
In total, two control variables were added to the statistical model. These variables are firm performance and firm size. Adding control variables to the model allows us to make better estimates of the impact of the relationship between risk evaluation of climate change and sustainability performance. After all, there could be different predictors that explain sustainability performance (Karlsson, 2016). These variables were selected because these are often used to explain why firms engage in green supply chain management (Suryanto et al., 2018; Q. Zhu & Sarkis, 2007).
Control variable: Firm performance
The first control variable is firm performance. Financial performance has been seen as having an impact on sustainability performance of firms (Alshehhi et al., 2018). The firm performance is operationalized by using a firms’ return on assets (ROA) in the reporting year. This variable is constructed using data from the Standard and Poor’s CompStat database. This variable was log transformed and standardized to facilitate the interpretation process. The ROA can be used to measure the profitability of a firm (Lo et al., 2012). Firms with a higher financial performance are likely to have more financial resources that can be used to invest and implement in low-carbon measures such as emission reduction targets (Hart, 1995; Muduli et al., 2013). The use of ROA as a measure for the financial performance of a firm in relation with GSCM implementation is in line with for example Wang and Sarkis (2013), Laari et al. (2017) and Miroshnychenko et al. (2017).
Control variable: Firm size
have easier access to financial means that can be used for the implementation of low-carbon initiatives such as the implementation of emission targets (Younis et al., 2016). The use of firm size in relation with GSCM implementation is in line with for example Teixeira et al. (2016), Suryanto et al. (2018) and Darnall et al. (2010).
Table 2 outlines the descriptive statistics of the variables used in this research.
Table 2: Composition of sample
Results
This section shows the results of the quantitative analysis. The effects of three types of risks and opportunities are examined, namely: regulatory risks and opportunities, physical risks and opportunities, and “other” (market) risks and opportunities. These were tested in two models. Model 1 establishes the relation between institutional pressure and the adoption of LCSM, with as moderator the perception of climate change risks and opportunities. Model 2 establishes the relationships between institutional pressure and firm performance, with as moderator the
Variable Min Max Mean St. Def N
lag analysis was performed. The control variables were log-transformed in order to prevent skewed data to affect the results. For the moderation analysis, the variables were mean-centered. Furthermore, all variables standardized in order to facilitate the interpretation of the regression analysis.
Model 1: LSCM adoption
The baseline model (model 1.1, table 3) includes only the dependent variable and the control variables. The model shows that there is a significant relationship between the control variables and the dependent variable. This is true for the base year and when using a two-year time lag. By adding the independent variable Institutional Pressure, (Model 1.2, table 4) the R2 and with that the explanatory power of the model increases compared to the baseline model in the base year and when considering a time lag. Before testing the moderated relationships of perceived risks and opportunities, they were added to the model as independent variables. In Model 1.3 (table 5), climate change related risks and opportunities of all kinds (regulatory, physical, and other (market) were added as independent variables. In order to prevent collinearity issues, the risks and opportunities of the same type were clustered and tested in separate models. This was again met with an increase in explanatory power. In model 1.4 (table 6), the variables for the moderation analysis were added. A slight increase in explanatory power was noted. No moderating effects were found, apart from an almost significant, positively moderating effect of physical risks (Model 1.4b, ß: .085, P<.10).
Table 5: Risk/opp as IV. ***:P<.001, **: P<.01 *:P<.05 ⌘:P<.10 (coefficient, st. err)
1.3a 1.3b 1.3c
DV=EMIS Base Timelag DV=EMIS Base Timelag DV=EMIS Base Timelag
N 759 396 N 759 396 N 759 396
R2/Adjusted .138/.132 .057/.045 R2/Adjusted .096/.090 .042/.030 R2/Adjusted .146/.140 .040/.034
ROA .086* .061 ROA .082* .054 ROA .096** .099*
.006 .010 .006 .010 .006 .006
Employees .045 -.004 Employees .039 -.012 Employees .039 .139**
.005 .009 .005 .009 .005 .007
Inst. Press .153*** .067 Inst. Press .179*** .093 Inst. Press .177*** .043
.005 .010 .005 .010 .005 .008
OPPREG .147*** .218*** OPPPHY .126** .178*** OPPOTH .210*** .000
.006 .007 .006 .007 .006 .000
RISKREG .204*** -.048 RISKPHY .150*** -.019 RISKOTH .157*** -.103⌘
.006 .011 .006 .011 .006 .008
Other Risk/Opp
Regulatory Risk/Opp Physical Risk/Opp
1.2
DV=EMIS Base Time lag
N 1040 626 R2/Adjusted .041/.039 .035/.030 ROA .118*** .109** .005 .006 Employees .119*** .096* .005 .006 Inst. Press .111*** .109** .004 .006 Baseline + IP 1.1
DV=EMIS Base Time lag
Table 6: Moderator analysis. ***:P<.001, **: P<.01 *:P<.05 ⌘:P<.10 (coefficient, st. err)
Institutional Pressure
As seen in model 1.2 (table 2), institutional pressure has a positive, significant effect on emission targets of a firm. This effect is present in the base year (ß: .111, P<.001), as well as when considering a three-year time lag (ß: .109, P<.001). Therefore, hypothesis 1 is supported. When adding climate change risks and opportunities to the model, this relationship holds in the base year ((1.3a: ß: .153, P<.001), (1.3b: ß: .179, P<.001), (1.3c: ß: .177, P<.001)), though not when considering a three-year time lag. This is also the case in model 1.4 (table 6), which tests the moderating effects.
Risks
In the base year, all types of climate change related risks have a positive, significant effect on emission targets ((1.3a: B;.204, P<.001), (1.3b: ß: .150, P<.001), (1.3c: ß: .157, P<.001)). This effect is not present in when considering a time lag. Model 1.3c gives an almost significant, negative effect of “other” (market) risks on emission targets (1.3c: ß: -.103, P<.10), though again, this result is not significant. No moderating effects are found (model 1.4, table 6). This means that there is no support for hypothesis 3a. Interestingly, model 1.4b suggests an almost
1.4a 1.4b 1.4c
DV=EMIS Base Timelag DV=EMIS Base Timelag DV=EMIS Base Timelag
N 759 396 N 759 396 N 759 396
R2/Adjusted .164/.156 .062/.045 R2/Adjusted .100/.092 .047/.030 R2/Adjusted .151/.143 .041/.034
ROA .091** .059 ROA .085* .050 ROA .094** .098*
.006 .010 .006 .010 .006 .006
Employees .029 -.005 Employees .041 -.16 Employees .041 .134**
.005 .009 .005 .009 .005 .007
Inst. Press .174*** .023 Inst. Press .188*** .044 Inst. Press .167*** .016
.005 .011 .005 .011 .005 .008
OPPREG .235*** .221*** OPPPHY .136** .184*** OPPOTH .216*** .000
.006 .007 .006 .007 .006 .000
RISKREG .147*** -.036 RISKPHY .136*** .000 RISKOTH .159*** -.083
.006 .011 .005 .011 .006 .009
M1oppreg .044 .049 M2oppphy -.043 .016 M3oppoth .022 .000
.006 .007 .005 .006 .006 .000
M4riskreg .053 .060 M5riskphy .085⌘ .090 M6riskoth .055 .062
.006 .008 .007 .008 .005 .006
Physical Moderation Other Moderation
significant, positive moderating relationship of physical climate change risks on the relationship between institutional pressure and emission targets in the base year (1.3b, ß: .085, P<.10). This result is not significant. As in model 1.3, in model 1.4 (table 6) all types of climate change related risks positively impact emission targets in the base year, and not when considering a time lag.
Opportunities
In model 1.3 (table 5), it becomes apparent that that or all types of climate change related opportunities, there is a positive relationship with emission targets. This holds for the base year ((1.3a: ß: .147, P<.001), (1.3b: ß: 126, P<.01), (1.3c: ß: .210, P<.001)), though when considering a time lag, this relationship does not hold for “other” (market) opportunities (1.3c: ß: .000, P<.10). The effect of regulatory and physical opportunities becomes greater when considering a time lag. In model 1.4 (table 6), this effect is also present. There are no moderating effects of climate change related opportunities on the relationship between institutional pressure and emission targets. Since no moderating effects are found, hypothesis 4a is not supported. Control Variables
The control variables have a positive, significant effect on the independent variable in the base line model (table 3). This effect disappears when adding more independent variables (model 1.3, 1.4). Firm performance positively and significantly impacts emission targets in the base year in models 1.3, 1.4, though not when considering a time lag (with exception of 1.3c, 1.4c). Firm size is not significant, with exception of time lag models 1.3c 1.4c.
Model 2: Financial performance
separate models were tested in order to prevent collinearity issues between the types climate change of risks and opportunities. This model also utilizes a three-year time lag.
Models
First, the baseline is tested. Table 7 displays the results of this analysis. The results of this test show that the financial performance of firms increases when the firm have more emission targets. By adding institutional pressure to the model, we see that institutional pressure does not have a significant relationship with the financial performance of a firm (table 8). In the next step, the individual variables for climate change risks and opportunities (regulatory, physical, and “other” (market)) were added. They were tested in separate models in order to prevent collinearity issues. The results of this analysis can be seen in Table 9. By adding these variables, the explanatory power of the model again increases. When testing for a moderating effect of climate change risks and opportunities, no significant results of moderation were found (table 10). In addition to this, there was no increased explanatory power when adding the moderating variables, as the R2 did not increase. This model will not be considered, though presented in table 10 for reference.
Table 7, 8: Baseline, Baseline + IP. ***:P<.001, **: P<.01 *:P<.05 ⌘:P<.10 (coefficient, st. err)
2.1
DV=ROA Base Time lag
N 1014 626 R2/Adjusted .018/.016 .012/.009 Emis .121*** .099* .211 .041 Employees -.072* -.067⌘ .031 .041 Baseline 2.2
DV=ROA Base Time lag
Table 9: Risk/opp as IV ***:P<.001, **: P<.01 *:P<.05 ⌘:P<.10 (coefficient, st. err)
Table 10: Moderator analysis ***:P<.001, **: P<.01 *:P<.05 ⌘:P<.10 (coefficient, st. err)
2.3a 2.3b 2.3b
DV=ROA Base Time lag DV=ROA Base Time lag DV=ROA Base Time lag
N 759 388 N 759 388 N 759 388
R2/Adjusted .021/.014 .070/.058 R2/Adjusted .020/.013 .068/.056 R2/Adjusted .019/.026 .030/.023
Emis .098* .035 Emis .089* .002 Emis .109** .019
.227 .040 .222 .039 .228 .044
Employees -.144** .071 Employees -.144** .065 Employees -.110** .070
.031 .045 .-31 .045 .031 .051
Inst. Press .011 -.233*** Inst. Press .009 -.225*** Inst. Press .004 -.177**
.030 .053 .030 .053 .030 .059
OPPREG -.003 -.066 OPPPHY -.012 .047 OPPOTH -.092* .000
.037 .038 -.034 .035 .037 .000
RISKREG -.033 -.340*** RISKPHY .004 -.354*** RISKOTH .022 -.245***
.-37 .058 .034 .057 .036 .064
Physical Risk/Opp Other Risk/Opp
Regulatory Risk/Opp
2.4a 2.4b 2.4c
DV=ROA Base Time lag DV=ROA Base Time lag DV=ROA Base Time lag
N 759 388 N 759 388 N 759 388
R2/Adjusted .023/.014 .071/.054 R2/Adjusted .023/.014 .069/.052 R2/Adjusted .031/.022 .030/.022
Emis .101* .037 Emis .095* .002 Emis .108** .019
.228 .041 .223 .039 .228 .044
Employees -.112** .071 Employees -.116** .066 Employees -.108** .071
.031 .045 .031 .045 .031 .051
Inst. Press .009 -.218** Inst. Press -.004 -.219** Inst. Press .006 -.169**
.030 .060 .031 .060 .030 .064
OPPOTH -.009 -.072 OPPOTH -.012 .052 OPPOTH -.092* .000
.037 .039 .035 .036 .037 .000
RISKOTH -.030 -.340*** RISKOTH .014 -.357*** RISKOTH .020 -.251***
.037 .-37 .035 .058 .036 .067
M1oppreg -.036 -.037 M2oppphy .064 .024 M3oppoth -.082⌘ .000
.038 .037 .032 .029 .035 .000
M4riskreg -.011 -.009 M5riskphy -.062 -.019 M6riskoth .080⌘ -.018
.035 .043 .040 .043 .034 -.047
effect is only present on the longer term ((2.3a: ß: -.233, P<.001), (2.3b: ß: -.225, P<.001), (2.3c: ß: -.177, P<.01)). This is in contrast to the model without the variables for risk and opportunities, where there is no relation between institutional pressure and financial performance. This, in combination of the result of model 2.2 (table 8) has as a result that there is no support for hypothesis 2.
Risks
The effect of climate change related risks becomes evident on the longer term. Here, climate change related risks of all kinds have a significant, negative relationship with the financial performance of a firm ((2.3a: ß: -.340, P<.001), (2.3b: ß: -.354, P<.001), (2.3c: ß: -.245, P<.001)). Because the model that tests for moderation of climate change risks (model 2.4, table 10) has no explanatory power over model 2.3 (table 9), no moderating effect of climate change risks could be established. As such, there was no support for hypothesis 3b.
Opportunities
Overall, there seems to be no relationship between climate related opportunities of all type and the financial performance of firms. An interesting exception is “other” (market) opportunities in the base year, where it has a significantly negative relationship with the financial performance of firms (ß: -.092, P<.05). Compared to other relationships, this relationship is relatively weak. Because the model that tests for moderation of climate change opportunities (model 2.4, table 10) has no explanatory power over model 2.3 (table 9), no moderating effect of climate change risks could be established. Therefore, there was no support for hypothesis 4b found.
Control Variables
significant, negative relationship with financial performance, though this effect is not present when considering a time lag. Though the analysis suggests a weak, positive relationship, it is insignificant (table 9).
Discussion of results
In this section, the results presented in the previous section are discussed. While only one hypothesis was found to be supported (hypotheses 1), other results are of interest too. These other results are discussed in this section too. As stated in the literature review, this research considers LCSM practices a subset of GSCM practices that can be seen as interaction in similar ways, in line with other research (Das & Jharkharia, 2018; Grose & Richardson, 2013b; Hitchcock, 2012; Ibrahim et al., 2020; Liu et al., 2020; Shen et al., 2017). The terms can therefore be seen as more or less interchangeable in the context of this discussion of the results. The results of the regression analysis of model 1 suggest that when firms are subject to institutional pressure, the implementation of low-carbon environmental practices becomes more likely. This is in support of institutional theory. Coercive pressures, such as regulations on climate change, evokes isomorphism as it forces companies to adopt practices in order to comply with those regulations (DiMaggio & Powell, 1983). In addition to institutional theory, this positive relationship between institutional pressure and LCSCM implementation is also in line with previous research. For example, Jaaffar et al. (2018) Vanalle et al. (2017), Zeng et al. (2017) and Zhu and Sarkis (2007) echo this result.
through the exploitation of their resources (Hart, 1995). According to Shi et al. (2012), this competitive advantage can be GSCM. It is therefore imaginable that companies adopt GSCM practices if they see opportunities that can be exploited for the benefit of the firm. The positive effect is also present in the time lag analysis. According to the natural resource-based view, organizational capabilities are developed in order to sustain the competitive advantage over time, suggesting the importance of climate change related opportunities (Yunus & Michalisin, 2016). An exception is the time lagged effect of ‘other’ climate change related opportunities, of which no significant relationship was found long-term. Furthermore, this result is in line with Böttcher and Müller (2015). They found that when firms see an opportunity to enhance their performance, the firm develops climate change strategies based on this. This suggests that climate change related opportunities have a positive relationship on environmental practices utilized a firm. Additionally, the direct effect of opportunities of all kind is in line with Elijido-Ten (2017).
The analysis in model 2 suggests that on the longer term, institutional pressure has a negative effect on the financial performance of a firm. This is in contrast to theory. The Porter hypothesis holds that environmental regulations can provide an incentive for firms to become more competitive and therefore enhance their firm performance (Porter & Van Der Linde, 1995a, 1995b). Ramanathan et al. (2017) additionally theorize that a regime with flexible, market type regulations allow firms that improve environmental performance to gain enhanced firm performance while penalizing the firms that lag behind. This in opposition to command-and-control regulations, which can result in high regulation and compliance cost (Y. Wang et al., 2011). As studies suggest that climate change regulations are often such command-and-control type regulations (Li & Ramanathan, 2018; Xie et al., 2017), the results of this research could have captured this effect. However, it is outside of the scope of this research to examine the structure of climate change regulation regimes.
disappears overtime, which implies a negative effect on the short-term financial performance, in order to ensure the long-term survival of the firm (Blackman et al., 2010; Zucker, 1987). Given the still relative short period of the time lag used in this research (three years), the observed negative relationship can be the result of the short-term increase in cost due to conformance.
Conclusion and implications
Motivated by calls for more research on the perception of climate change by firms and motivated by providing a climate change perspective on GSCM, this research sought to establish a moderating role of the perception of climate change on the relationships between institutional pressure and financial performance, and the relation between institutional pressure and the adoption of low-carbon supply chain management. Specifically, six hypotheses were tested. With data from the Carbon Disclosure Project, Germanwatch and CompuStat, regression analysis was performed in order to find relations between the variables.
This research found support for the hypotheses that institutional pressure positively impacts the adoption of low-carbon supply chain management practices in the form of emission reduction targets. Furthermore, rather than finding a moderating effect, this research established direct effects of climate change opportunities on the adoption of LCSM. And, a negative relation of climate change risks on the financial performance of firms was also found. Similarly, a negative effect of institutional pressure was found on the financial performance of firms. The results underline the importance of the type of climate change regulation a government enacts, as flexible, market-based style policy gives firms more freedom to peruse climate change opportunities than command-and-control style regulations, which are associated with climate change risks.
This research contributes to existing literature on institutional pressure and its relation to organizational characteristics in several ways. First, this research adds the perspective of climate change to literature on institutional pressure and GSCM, a perspective that is understudied (Das & Jharkharia, 2018). Second, this research contributes by studying the perception of climate change related risks and opportunities of firms. This has been suggested as increasingly important while studying corporate behavior (Elijido-Ten & Clarkson, 2019; Furlan Matos Alves et al., 2017). Third, this research contributed to the literature by providing empirical evidence through the use of regression analysis and by linking data from multiple sources.
government enacts. While current policy regimes largely consist of command-and-control style regulations (Li & Ramanathan, 2018; Xie et al., 2017), more flexible regulations could allow firms to exploit opportunities instead of uniformly punishing firms and evoking conformity actions. This also links to the observation that the recognition of climate change opportunities positively influences the adoption of LCSM in the form of carbon reduction. Motivating firms through for example incentives facilitates a more proactive stance towards the adoption of LSCM. Second, there are implications for firms. Firms should be open to collaboration within their supply chain. This is because the mitigation of climate change requires the realignment of valuable resources that not every company has.
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