Climate Change in the Business Strategy-Free-Samples for Students

Question: Is climate change integrated into your business strategy. Answer: 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 firms 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 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: 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 firms 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: Is climate change is integrated in the business strategy, and if so, how does it affect the carbon disclosure score? 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 35.179 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 its higher disclosure is legitimate or makes sense. Theyre 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 companys 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 (ODonovan, 2002). The analysis reveals that a companys 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 indep endent 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 (ODonovan, 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-Muoz, 2013). The decre ase 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-Muoz, S.C., 2013. Firm-value effects of carbon emissions and carbon disclosures.The Accounting Review,89(2), pp.695-724. ODonovan, 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.