Incorporation of Climate Change in Business Strategy: A Legitimacy Theory Perspective

This research paper explores the impact of climate change on business strategy and its incorporation from a legitimacy theory perspective. It analyzes previous studies and uses descriptive and inferential statistics to test hypotheses. The study focuses on the conjecture that carbon disclosure score of the company depends on a company’s act of integrating climate change as a component in its business strategy, its internal pricing score of carbon and its consideration of future risk, where size of the firm is the control variable. The paired t-test results reveal that the p-value is less than 0.05, leading to rejection of the null hypothesis.

Assigned research question: Is climate change integrated into your business
strategy.
Introduction
Climate changes have significant influences on the visions and profit maximisation strategies of
the organisation. The awareness of the climate changes is increasing day by day throughout the
world in almost every industry. Every organisation has its distinctive opportunities, challenges
and integrating climate change which plays a key role in the policy-making process. The
fundamental issue we want to address here is the incorporation of climate change in the business
strategy. Furthermore, we will relate this issue to the legitimacy theory which means an
organisation seeks to ensure that they operate within the bounds and norms according to the local
societies. To put in simple words, the business activities are perceived to be legitimate. The
bounds and norms are not static so the organisation has to be responsive and the best way is to
rely on the notion of a social contract.
Literature Review –
A plethora of research is available which deal with the issue of climate change and its
incorporation in the process of business policymaking. In this section, we will cover some
important previous studies that deal with the issue of climate change as well as with the

perspective of legitimacy theory. An important study conducted by the McKinsey & Company
which dealing with the generalised perspective on climate change risk that varies industry to
industry. This research is covering almost all major sectors like oil and gas, Chemicals,
agriculture, transport etc. The best way to compile that report is show with the help of the
following chart;
Figure 1. Impact of McKinsey & Co on carbon disclosure. Source: McKinsey & Company
(2017)
Legitimacy theory also aids to assess the Green House Gas emission and social performance of
the firm making it one of the best tool analyse and compare the firm’s performance with climate
change.
A research study had highlighted the issue of legitimacy gap and concluding that this gap arises
when there is a clash between expectations of society and actions of an organisation. There is a
strong correlation between the expectations of society and legitimacy gap. To put in other words,

it means the gap will increase when the expectations of society changes or the unknown
information become known to the society (Set
hi, 1975).
Figure 2. Legitimacy gap. Source: Sethi (1975)
Another research is suggesting the climate change action plan that can be used as a proactive
management of risk that is associated with the climate and also discussing the opportunities and
impacts. This study is based on five stages where the first stage is deal with the understanding
footprints which means mapping the emissions and improving the reporting and accuracy. The
second step is describing the implementation of suitable measures to reduce these emissions. The
next stage is dealing with the engaging externalities which mean for instance to develop methane
and shale development communication or take part in the process of global legislation and
regulations. The final stage is dealing with the building capacity which means to give proper
attention to research and development to form an action plan to incorporate the climate change in
business strategies (Mousa and Hassan, 2015).
Conceptual Model:

Integration of climate change in business
Internal price of carbon
Future consideration of risk
Carbon disclosure score
Independent Variables
Control variables: Size of the firm
Dependent Variables
The conceptual model of this study which is dealing with the issue of climate changes
incorporation in the business policymaking process can be presented with the help of the
following chart explicitly;
Figure 3. Conceptual model of the research.
In this research framework, there are three independent variables and one dependent variable
along with a control variable. It has been considered that carbon disclosure score is the
dependent variable, which is according to the CDP disclosure is dependent upon the integration
of climate change in business, internal price of carbon and future consideration of risk, making
them the independent variable for this research framework. This research framework considers
that size of the firm is one of the main factors that control the carbon disclosure score, this it will
be considered as the control variable.

Hypotheses:
H0: There is no relationship between the independent variables and dependent variables.
H1: Integration of climate change in business, internal price of carbon and future consideration of
risk positively affects the Carbon disclosure score.
Proxy Measures for Theoretical Constructs
Table 1. Proxy measures for theoretical constructs.
Theoretical Constructs Proxy Measures Type of Variable Sources
Integration of climate
change in the business
strategy
Nominal answer of
Yes/No to Question
from the CDP data.
Independent Variable CDP survey
Internal price of Carbon Measureable in
currency($)
Independent Variable
Future considerations of
risk
Measurable using
previous data
comparisons
Independent Variable
Voluntary Carbon
Disclosure score
Percentage carbon
disclosure score. The
measurement is
related to the firms on
carbon disclosure
sources mentioned in
CDP spreadsheet.
Dependent Variable CDP Survey

Company profile Companies: Mining,
Chemicals
(high profile)
Control Variable ASX company sector
categorisation.
Corporation Size (Low Profile)
Market
Capitalization
Control Variable ASX of top 200
corporations
Research Methodology
A sample number of 180 corporations including various sectors of industries is taken into
consideration in the study. The major section of sectors used in CDP are high profile industries
and includes low profile industries as well. All these industry types are classified under Global
Industry Classification Standard. voluntary disclosure have been found out, in this study the size
is measured as control variable (cv) measured in terms of the firm’s market capitalization of
particulars industrial sector, regresssion analysis is delivered by using secondary data.
Data Collection
The sample data was taken from the CDP survey 2015. The database had 1048 firms from
different countries with various sectors.
Sample selection for this research project was restricted by the number of companies with
appropriate data. Many companies did not answer the CDP questions which were the focus of the
research so the sample size was more limited than initially expected. The final sample consisted

of 56 companies from different countries and various sectors. These companies did have a
response to the identified research question. (Note that the class lecturer approved the use of 56
companies given the research question and CDP data). Adopting random sampling, data was
collected from 28 Companies responding YES and 28 Companies responding NO.
Data Analysis - Descriptive
Descriptive data analysis is being used in the research paper to analyse the data and comparison.
Descriptive data analysis is the best form to analyse and tabulate the collective data from the
samples and graphical representation as well. Mean, Median, Mode are used to measure the
central tendency results to analyse their differences from the data collection. Range, kurtosis,
skewness is used to box plot the central tendency results.
On the basis parameters, the research proceeds to explain about the analysing of data by means
of tabular representation using descriptive analysis. The two key research questions for
descriptive data analysis were the following:
1. Is climate change is integrated in the business strategy, and if so, how does it affect the
carbon disclosure score?
2. Is climate change not integrated into the business strategy and if so, how does it affect the
carbon disclosure score?
Table 1. Companies where climate change is integrated in the business strategy
Companies responding YES compared with disclosure scores
Mean 90.53571
Median 94

Mode 100
Standard Deviation 13.2957
Sample Variance 176.7765
Kurtosis 4.314874
Skewness -2.17536
Range 50
Minimum 50
Maximum 100
Sum of 2535
Count 28
Table 2: Climate change is not integrated in the business strategy
Companies Responding NO compared with disclosure scores
Mean 55.3571
Median 63.5
Mode 0
Standard Deviation 34.3664
Sample variance 1181.0529
Kurtosis -1.1030
Skewness -0.5509
Range 99
Minimum 0
Maximum 99
Sum of 1550
Count 28
Statistic Std. Error
yes Mean 90.54 2.513
95% Confidence Interval for
Mean
Lower Bound 85.38
Upper Bound 95.69

5% Trimmed Mean 92.21
Median 94.00
Variance 176.776
Std. Deviation 13.296
Minimum 50
Maximum 100
Range 50
Interquartile Range 11
Skewness -2.175 .441
Kurtosis 4.315 .858
No Mean 55.36 6.495
95% Confidence Interval for
Mean
Lower Bound 42.03
Upper Bound 68.68
5% Trimmed Mean 56.07
Median 63.50
Variance 1181.053
Std. Deviation 34.366
Minimum 0
Maximum 99
Range 99
Interquartile Range 57
Skewness -.551 .441
Kurtosis -1.103 .858
The above represented descriptive tabular data represented analyses on two parameters of
integrating climate change in the business and other parameter representing opposite of not
integrating climate change in the business.
 Analysed Mean from table 3 responding yes with disclosure scores and mean of 90.53
depicts a vast difference from the companies responding No in integrating climate change
to business.

 Sample Variance has a huge difference in means to comparison of the samples.
 Standard deviation is explained how data distribution is moving with the mean values.
The standard deviation has a vast difference in the above tables. The normal distributed
data lies usually between -1 to +1 but the research results are way too far off the mean in
normal distributed results.
 The skewness of both the parameters have negative scores which results in lack of
uniformity and skewed negatively in the distributed data.
 Kurtosis on the tabular data representing a different result for both parameters shows a
negative trend.
 Range is a factor used to analyse small data sets of the collected data depicting a vast
difference between two parameters set.
 Minimum and maximum depicts the lowest observation and largest observation of the
collected samples in the research.
Paired Samples Test
Paired Differences
t df
Sig. (2-
tailed)Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
yes -
no
35.17
9
36.923 6.978 20.861 49.496 5.041 27 .000

Figure 1: Pie chart depicting the YES or NO response for research question (not related to
disclosure score).
The above figure evaluates that most of the companies selected for this research have integrated
climate change into their business with major proportion of the companies disclosing their score
and responding positively on their carbon disclosures.
Discussion of descriptive statistics
- Large variation b/wn yes and high score and no with low score
- Ideally, re-introduce your management theory (legitimacy) – an easy relationship is that
if the company is being legitimate, then it will integrate GHG into its business strategy so

that it’s higher disclosure is legitimate or makes sense. They’re not faking their GHG
initiative so could be perceived as more legit. Refs…. 1-2 paras
Research on descriptive data analysis resulted in large variation of results of the companies
responding Positive on the research question with higher values of YES disclosure scores about
the companies responding very less and negatively NO in number of disclosure scores in CDP
survey. Descriptive statistics of the research using SPSS method resulted that most of the
companies had a positive response in relation to integration climate change into business
strategy.
Reintroducing my research theory Legitimacy theory into the research. Legitimacy theory has
been more about research papers these days as there is an assumption that some proposals and
tasks of the entity are on spot to some uplifted number of norms adopted socially. The research
summarizes that companies having large variation of responding positively on research question,
which reasonably entitled to legit information on disclosure of their scores.
Data Analysis- Inferential statistics
The study is focused around the conjecture which states that, carbon disclosure score of the
company depends on a company’s act of integrating climate change as a component in its
business strategy, its internal pricing score of carbon and its consideration of future risk, where
size of the firm is the control variable (Guenther et al., 2016). The assumption on which the
study stands is that the companies belong to the same population of companies. The available
carbon disclosure score is depends on the treatment of the variable representing the integration
status of climate change to the business model, which leads to two groups of companies. The

groups are one, which has not yet integrated climate change to its business approach and the two,
which has integrated climate change to its business approach. A paired t-test is then employed on
the data to determine whether there is a difference between the group attributed by the answer
“YES” to the question asking whether climate change is a factor which is considered during its
strategy making and the group attributed by the answer “NO” when asked the same question
(Zikmund et al., 2013). The rationale is that, the scores being higher for the group saying “Yes”,
then integration asserts is role as a positive influencer.
Hypothesis testing
The hypotheses under scrutiny in this study are as follows:
H0: There is no relationship between the independent variables and dependent variables.
H1: Integration of climate change in business, internal price of carbon and future
consideration of risk positively affects the Carbon disclosure score.
The table 4 shows the results of the paired t-test used to test the hypothesis mentioned in
the previous section. It reveals that the p-value is less than 0.05, which leads to rejection of the
null hypothesis, H0. This implies that there is indeed a significant difference observed between
the two groups of organizations, grouped as per their answer to the question asking whether they
have integrated climate change as a deciding factor in their strategy making (Zikmund et al.,
2013). Therefore, the inference follows that the group, which has integrated notions of climate
change as a relevant insight to determine company strategy, has enjoyed higher scores of carbon
disclosure.

Discussion
The emergence of awareness among the masses with regard to climate change and the
risks it poses has worked to bring the issue to the forefront of the concerns plaguing the world. It
has brought about a sense of responsibility and accountability with regard to how companies
carry out their business as a result. Generally, its customers and the tentative market regard a
company that cares about the effects of climate change, in a more positive light. The carbon
disclosure score is an indicator of the environmental awareness of the company, along with the
level of sustainability governance it practices and its leadership status with respect to climate
change among its peers (Guenther et al., 2016).
A high carbon disclosure score reflects upon a number of things. Firstly, the outlook of
the climate change policy to shareholders, clients and the public audience. This could work in its
favour as a marketing avenue. Secondly, insight about how it can cope with threats that might
arise due to climate change. Thirdly, insight about any business opportunities that might be
available to the company. Fourthly, insight about how to increase production and efficiency in
production while reducing costs (Luo and Tang, 2014). The legitimacy theory that is of interest
in this report stresses on a key benefit that assessing and trying to improve the carbon disclosure
index of a company may present. Owing to the argument, that since the world is increasingly
shifting focus to cleaner ways of conducting activities, a company would benefit from catering to
those shifting ideals as per the rationale of legitimacy theory (O’Donovan, 2002).
The analysis reveals that a company’s reputation has an association with the inclusion of
climate change as an important point of consideration in its business model. The bottom line of
the conceptual framework of the legitimacy theory in the light of a practical scenario is that, it is

an opportunity for the company in question. The opportunity to connect market expectation to
operational efficiency (Luo and Tang, 2014). Through effective communication within the
organization and between the changing world scenario and the company outlook, which in this
particular case is climate change, this could be possible. The aim of this paper is to highlight how
that could be done using carbon disclosure score index as a metric to represent the performance
of the company in trying to fill the legitimacy gap. The research conducted for this paper has
revealed that majority of the companies under consideration have already integrated climate
change to its business as shown in figure 1. The independent variables are the explanatory
factors, which is controllable by the company to achieve a better position with respect to its
success in dealing with the legitimacy gap (O’Donovan, 2002). Integration of climate change
into company model has thus, been found to be a good choice in that regard and it has been
supported by our analysis as well. Therefore, the move could be good for generating a more
positive market image. Following this, whether and how the remaining independent factors
identified, affect the performance of the company in light of the legitimacy gap must be
determined. The internal price of carbon is a “shadow” expense that the company expects will
add to its operational cost and due to its future investments owing to its current policy on
generating carbon emissions. High internal carbon price acts as a warning and a check during the
companies’ policy making relating to decisions, which could cause carbon emissions
(Matsumura, Prakash and Vera-Muñoz, 2013). The decrease in internal price of carbon could
thus improve the score of carbon disclosure index. Again, the predicted possible risks of carbon
generation arising out of the policies of the company, quantified from historical data could also
affect the carbon disclosure index (Luo and Tang, 2014). Considering all three explanatory
variables it could then be investigated using survey data, how the performance of the company as

per the carbon disclosure index is affected and how the increase or decrease of the metrics could
affect the ultimate performance scores, which are the carbon disclosure indices of the companies.
Limitations
Firstly, note that the data used to calculate the carbon disclosure score are from the companies
registered by the Carbon disclosure project. Thus, the self-reporting nature of data collection
may raise questions regarding the validity of the data and whatever results may follow the
analysis. Secondly, the analysis in this paper focuses on the relationship between only the
integration of climate change to the business model with the performance outcome metric. It
does not explore the relationship with the other independent variables. Thirdly, it approaches the
situation largely from an exploratory viewpoint and does not address the exact nature of the
relationship between the variables under consideration.
Further Research
Firstly, the analysis leaves scope for investigating the causal relationship between the
performance score of the company and the explanatory variables of the response. An in depth
investigation about the nature of the relationship between integration status of climate change in
the company model, predicted future risk due to climate change and the internal carbon price of
the company using more advanced statistical tools. Secondly, developing a model to predict the
performance score from the explanatory variables. Thirdly, it could be investigated what other
factors whether latent or explicit could directly or indirectly affect the carbon disclosure score
and hence how those could affect the model upon consideration.

References:
Guenther, E., Guenther, T., Schiemann, F. and Weber, G., 2016. Stakeholder relevance for
reporting: explanatory factors of carbon disclosure. Business & Society, 55(3), pp.361-397.
Luo, L. and Tang, Q., 2014. Does voluntary carbon disclosure reflect underlying carbon
performance?. Journal of Contemporary Accounting & Economics, 10(3), pp.191-205.
Matsumura, E.M., Prakash, R. and Vera-Muñoz, S.C., 2013. Firm-value effects of carbon
emissions and carbon disclosures. The Accounting Review, 89(2), pp.695-724.
O’Donovan, G., 2002. Environmental disclosures in the annual report: Extending the
applicability and predictive power of legitimacy theory. Accounting, Auditing & Accountability
Journal, 15(3), pp.344-371.
Zikmund, W.G., Babin, B.J., Carr, J.C. and Griffin, M., 2013. Business research methods.
Cengage Learning.