||Relationships between Environmental Indicator Disclosure Levels of International Contractors and Data Sources
||Department of Civil Engineering
Corporate Social Responsibility
environmental indicator disclosure
Global Reporting Initiative
The construction industry is vital for countries to develop infrastructure. However, it also has negative impacts on the environment and thus, is accountable for significant greenhouse gas (GHG) emissions, energy consumption, and waste generation. Because of this, construction companies are expected to show their commitment to the environment through Corporate Social Responsibility (CSR) reporting.
This study aimed to determine the relationships between environmental indicator disclosures and data sources in the CSR reports of international contractors. This research used content analysis and case study methods to examine nine CSR reports of 2018 that are compliant with the environmental aspects, indicators, and requirements of Global Reporting Initiative (GRI) Standards 2016, published by nine international construction companies.
The results show that the average disclosure of the 30 indicators in the nine CSR reports is 26%. Environmental compliance is the most disclosed aspect (39%), followed by Supplier environmental assessment (36%), and Materials (33%). Four indicators have more than 50% disclosure namely 301-1 (Materials used by weight or volume) with 67%, 305-4 (GHG emissions intensity) with 61%, 302-1 (Energy consumption within the organization) with 56%, and 308-1 (New suppliers that were screened using environmental criteria) with 56%.
The results also show that the indicators with data located at the department (32.3%) have higher disclosure than those at the work process (25.0%). The indicators with internal data have higher disclosure (29.3%) than external data (13.7%). The indicators with quantitative data have higher disclosure (32.0%) than qualitative data (14.7%). Furthermore, there is no relationship between the number of data sources and the disclosure level for the indicators. Lastly, there is a significant moderately positive relationship between data quality index and indicator disclosure level. This means that indicators that rely on more specific and quantifiable data tend to have higher disclosure that is consistent with the prior quantitative data’s higher disclosure.
In summary, the disclosure of the 30 environmental indicators can be increased with good potential. The collection of department, internal and especially quantitative data can be prioritized to lead to higher disclosure.
TABLE OF CONTENTS iii
LIST OF TABLES v
LIST OF FIGURES vii
CHAPTER 1 INTRODUCTION 1
1.1 Research Motivation 2
1.2 Research Objectives 2
1.3 Research Method and Process 3
1.4 Research Scope and Limitation 5
CHAPTER 2 LITERATURE REVIEW 6
2.1 CSR Reporting 6
2.1.1 Relevance of CSR reporting 6
2.1.2 CSR reporting in the construction industry 7
2.2 Environmental Information Disclosure 9
2.2.1 Environmental disclosure and performance 9
2.2.2 Factors affecting environmental information disclosure 10
2.2.3 Environmental indicator disclosure 11
2.2.4 Difficulties in data collection 13
2.2.5 Environmental information data sources 13
CHAPTER 3 COMPANY SELECTION AND INDICATOR DISCLOSURES 16
3.1 Company Selection 16
3.1.1 Selection process 16
3.1.2 Selected companies 18
3.2 Indicator Disclosures 20
3.2.1 GRI Environmental disclosure requirements 20
3.2.2 Indicator disclosure determination 23
3.2.3 Comparison of indicator disclosures 32
CHAPTER 4 DATA SOURCES AND GRI INDICATORS 43
4.1 Data Sources 43
4.1.1 ISO 14031 43
4.1.2 Data source characteristics 44
4.2 Linking Indicator Data Sources in GRI Standards 46
4.2.1 Documentation sources of GRI indicators 46
4.2.2 Data sources of GRI 2016 indicators 52
CHAPTER 5 RELATIONSHIPS BETWEEN DISCLOSURE AND DATA 57
5.1 Indicator-Level Relationships 57
5.1.1 Indicator’s data source location and nature 57
5.1.2 Indicator’s data source number and index 60
5.2 Aspect-Level Relationships 65
5.2.1 Aspect’s data source location and nature 65
5.2.2 Aspect’s data source number and index 68
5.3 Variables Affecting Indicator Disclosure 71
5.3.1 Number of reporting requirements 72
5.3.2 Assumptions and methods of calculation 73
CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS 76
6.1 Conclusions 76
6.2 Research Contribution 79
6.3 Recommendations 79
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