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Corporate Carbon Accounting and Footprinting in the Ecologically Dominant Logic

With an Excursion on the Detection of Outliers in a double-logarithmic Regression Model

von Bernhard Goldhammer (Autor:in)
©2019 Dissertation 480 Seiten


In order to reach sustainable supply chains, the Ecologically Dominant Logic calls for improvement in measurements. With regard to climate change, this is the task of corporate carbon accounting and footprinting. This book contributes to these topics by proposing a double-entry based bookkeeping approach for carbon accounting, that enables continuous reporting along the supply chain, supports both product and corporate carbon footprinting and is compliant with the established carbon accounting standards. Furthermore, for estimating missing carbon footprints, a regression-based estimation approach is proposed and tested, which needs only publicly available data as input and facilitates the estimation at a decent level of quality without knowledge about the internal processes of a company.


  • Cover
  • Title
  • Copyright
  • About the author
  • About the book
  • This eBook can be cited
  • Preface
  • Table of Contents
  • List of abbreviations
  • 1. Sustainability, the Ecologically Dominant Logic and business strategies for climate change
  • 2. Carbon footprinting and carbon accounting: Relationships, concept, gaps
  • 2.1 Definitions and relationship of carbon accounting and carbon footprinting
  • 2.2 Concepts
  • 2.2.1 Different levels of carbon accounting and carbon footprinting
  • 2.2.2 Carbon emission scopes
  • 2.3 Gaps in carbon accounting and carbon footprinting
  • 3. Part I: A double-entry bookkeeping approach for corporate carbon accounting
  • 3.1 Carbon accounting controversies and problems
  • 3.2 Historical analogies in accounting
  • 3.3 General principles of double-entry bookkeeping
  • 3.4 Deriving demands for the double-entry bookkeeping system by an analysis of current standards of carbon accounting
  • 3.4.1 Principles and goals for GHG accounting
  • 3.4.2 Set-up of carbon accounting system
  • 3.4.3 Quality management: Uncertainty and data quality
  • 3.4.4 Set-up of carbon accounting system, monitoring GHG emissions: The treatment of individual business cases
  • 3.4.5 Set-up of carbon accounting system, monitoring of GHG emissions: Consolidation to a corporate result
  • 3.4.6 Target setting and adaptation: Timing of recalculation
  • 3.4.7 Reporting
  • 3.4.8 Verification
  • 3.4.9 Benchmarking with the target
  • 3.4.10 Summary of demands derived from current standards of carbon accounting
  • 3.5 Double-entry bookkeeping for corporate carbon accounting – a proposal
  • 3.5.1 General idea
  • 3.5.2 Accounting records for single business transactions
  • 3.5.3 Year-end consolidation
  • 3.5.4 Reset for the following year and the historical carbon balance sheet
  • 3.6 Discussion, contributions and limitations
  • 3.6.1 Fulfilling the reporting requirements of the standards and comparison with targets
  • 3.6.2 DeBk as a solution to the controversies and problems of carbon accounting
  • 3.6.3 Allocation of GHG emissions to products
  • 3.6.4 The accrual principle and the need for revaluation
  • 3.6.5 DeBk and carbon management accounting
  • 3.6.6 Contributions and limitations
  • 3.6.7 Propositions for future research
  • 3.7 Conclusion of part I
  • 4. Part II: Estimating Corporate Carbon Footprints with externally available data
  • 4.1 The need for external CCF estimation
  • 4.2 Conceptual background
  • 4.2.1 Carbon emission assessment between accuracy and efficiency
  • 4.2.2 Carbon emission scopes in focus
  • 4.2.3 Estimating the result of internal processes with externally visible characteristics in other fields of economic science
  • 4.3 Hypotheses and measure operationalization
  • 4.3.1 Drivers of CO2-eq emissions
  • 4.3.2 Main GHG emission drivers: Impact and hypotheses
  • 4.4 Methodology
  • 4.4.1 Variables
  • 4.4.2 Resulting base model – choice of regression formula
  • 4.4.3 Database and collected data
  • 4.4.4 Construction of homogenous subsamples
  • 4.4.5 Data analysis
  • 4.5 Results
  • 4.5.1 Impact of having two different operationalizations for LVI in parallel
  • 4.5.2 Overview of the results for the main analysis
  • 4.5.3 Base model
  • 4.5.4 Model exploration and refinement
  • 4.5.5 Possible additional refinements
  • 4.5.6 Some regression analysis-related issues
  • 4.5.7 An alternative methodological approach – multi-level modeling
  • 4.6 Discussion
  • 4.6.1 Contrasting hypotheses with empirically found effects
  • 4.6.2 The effects of accounting differences on the CCF
  • 4.6.3 Determining the sector-specific data model – the results of the comparisons
  • 4.6.4 Heteroscedasticity and data mining
  • 4.6.5 Lessons learned from OLS regression-specific problems
  • 4.6.6 The failure of multilevel modeling in this research
  • 4.6.7 A roadmap for CCF estimation research in other sectors
  • 4.6.8 Detection of outliers for OLS regression in double-logarithmic form
  • 4.6.9 Improvement and final results of the estimations for the three single sectors and the all sectors jointly characteristic
  • 4.6.10 Estimation quality
  • 4.6.11 Possible contributions and limitations
  • 4.7 Conclusion of part II
  • 5. Conclusion
  • Reference list
  • Appendix A: Data for part II, their sources and remarks
  • Appendix B: Programs used for part II
  • B.1 Creation of subsamples from the database shown in Appendix A
  • B.2 Calculation of regression variables
  • B.3 Test for LVI operationalization
  • B.4 Base model regression including calculation of descriptive statistics
  • B.5 Benchmarking model
  • B.6 Compromise model
  • B.7 Sector-specific model
  • B.8 Sector-specific data model
  • B.9 Dummy model
  • B.10 Additional control variables
  • B.11 Service percentage of turnover as additional variable
  • B.12 Variance inflation factor
  • B.13 RESET test
  • B.14 Heteroscedasticity: Visual examination, Breusch-Pagan test, Koenker test
  • B.15 Heteroscedasticity: White-Wooldridge test
  • B.16 Heteroscedasticity-robust standard errors
  • B.17 Multilevel Modeling
  • B.18 Outlier detection: Regular routines, correlations
  • List of figures and tables

← 12 | 13 →

List of abbreviations

← 14 | 15 →

1.  Sustainability, the Ecologically Dominant Logic and business strategies for climate change


Previous research has suggested that reaching sustainability leads to competitive advantage. Main theories in this field are the resource-based view of the firm (Hart, 1995), the triple-bottom line of equally important environmental, social, and economic targets (Elkington, 1998), and green means competitive due to higher efficiency (Porter & van der Linde, 1995). However, recent research (Pagell & Shevchenko, 2014) suggests that companies have become rather less unsustainable than truly sustainable, using the aforementioned theories only in an instrumental fashion. Therefore, looking at the problem from a supply chain management perspective and acknowledging trade-offs between the targets, Montabon, Pagell, & Wu (2016) postulate the Ecologically Dominant Logic as a new theory of how to reach truly sustainable supply chains. In this theory, environment comes first, then social targets, and only then economic targets. They especially stress the need for improvement and new development of sustainability measurements. At the same time, business frameworks for managing climate change (Birnik, 2013; Hendrichs & Busch, 2012) call themselves for an improvement in CO2 measurement, referred to as “carbon accounting” and “carbon footprinting”. To support the ecologically dominant logic and the business frameworks, this book aims to contribute to carbon accounting and carbon footprinting with focus on the needs of sustainable supply chain management. ← 15 | 16 →

“Wird derhalben die größte Kunst/Wissenschaft/Fleiß/und Einrichtung hiesiger Lande darinnen beruhen/wie eine sothane Conservation und Anbau des Holtzes anzustellen/daß es eine continuierliche beständige und nachhaltende Nutzung gebe/weiln es eine unentbehrliche Sache ist/ohne welche das Land in seinem Esse nicht bleiben mag.“

[Therefore, the greatest art/science/diligence/and institution of this country here will be of/how to manage the conversation and cultivation of wood in such a manner/that a continuous steady and sustainable use is feasible/because it is an indispensable matter/without which the country will not remain in its state.] (Carlowitz, 1713, pp. 105–106; translation and underlining by the author).

This quotation from a groundbreaking book on forestry that paved the way towards the reforestation of Germany after the 30-years war is seen as the first notion of today’s understanding of sustainability: “Development that meets the needs of the present without compromising the ability of future generations to meet their needs.” (World Commission on Environment and Development, 1987, p. 8). This definition and the report of the Brundlandt commission around it fostered economic research on sustainability. Most important theoretical contributions on that field were the natural-resource based view of the firm (Hart, 1995), the triple-bottom line of economic, social and environmental targets (Elkington, 1997, 1998) and the identification of win-win situations in which good environmental performance is accompanied with a gain in economic performance (Porter & van der Linde, 1995).

The natural resource-based view is explained by Hart (1995):

“In the future, it appears inevitable that businesses (markets) will be constrained by and dependent upon ecosystems (nature)… In other words, it is likely that strategy and competitive advantage in the coming years will be rooted in capabilities that facilitate environmentally sustainable economic activity…” (p. 991).

To achieve this target, companies can pursue three different strategies: Pollution prevention, product stewardship (that is, incremental improvement of the product), and sustainable development (meaning radical improvement). A lot of research has been built on this theory, e.g. assessing the innovation policies of car makers in the light of the natural resourced-based view (De Stefano, Montes-Sancho, & Busch, 2016), elaborating the link between corporate financial performance and corporate environmental performance (Busch, Stinchfield, & Wood, 2010) and how intangible assets mediate this link (Surroca, Tribo, & Waddock, 2010).

The triple bottom line concept was developed by Elkington (1997, 1998). It means that each dimension of the triple of economic, social, and environmental targets is equally important:

“…The triple bottom line suggests that at the intersection of social, environmental, and economic performance, there are activities that organizations can engage in which not only positively affect the natural environment and society, but which also result in long-term economic benefits and competitive advantage for the firm.” (Carter & Rogers, 2008, pp. 364–5). ← 16 | 17 →

The triple bottom line has been especially emphasized in supply-chain management. Elkington himself mentioned the importance of partnerships to achieve sustainability: “Effective, long-term partnerships will be crucial during the sustainability transition.” (Elkington, 1998, p. 37). A whole framework of sustainable supply chain management is built upon the triple bottom line by Carter & Rogers (2008), who define it “… as the strategic, transparent integration and achievement of an organization’s social, environmental, and economic goals in the systemic coordination of key interorganizational business processes for improving the long-term economic performance of the individual company and its supply chains.” (p. 368). In order to assess the triple bottom line for a supply chain, Foran, Lenzen, Dey, & Bilek (2005) combine several economic, social, and environmental measures with input-output-tables. This procedure is also used by Wiedmann, Lenzen, & Barrett (2009) for benchmarking the sustainability of a business including its supply chain. Jasinski, Meredith, & Kirwan (2016) use the triple bottom line to create a framework for the assessment of the sustainability of the automotive industry including its supply chain. Furthermore, Pagell, Wu, & Wasserman (2010) state that a change is occurring to classic supply chain management, which requires the development of “…purchasing portfolio models that account for the newfound need for supply chains to be both profitable and responsible.” (p. 60). Their extension of the theory on supply management and purchasing portfolios to a sustainable purchasing portfolio matrix is based on the triple bottom line.

Becoming green as an competitive advantage is advocated first by Porter & van der Linde (1995). They claim that pollution means inefficient, bad resource utilization, and reveals a bad product design or production process. Hence, environmental improvement means increasing competitiveness. Building on this theory, Chakrabarty & Wang (2013) find that efforts of climate change mitigation strengthen the competitiveness of multi-national companies, specifically sales effectiveness and product leadership. As another field of application, many theoretical and business frameworks capitalize on the green and competitive theory, e.g. a model for high-level corporate environmental performance (Sharfman, Shaft, & Tihanyi, 2004), a framework for green supply chain management and performance measurement (Hervani, Helms, & Sarkis, 2005), and the identification of different carbon management strategies (Busch & Wolfensberger, 2011). The theory has been confirmed at least in specific cases, like the existence of a linkage between the level of environmental management, quality management, and corporate performance (Wiengarten & Pagell, 2012). Besides economic literature, proofs for the theory can also be found in engineering articles that do not even mention the economic theory behind it: For example, a new polishing technology is able to reduce CO2 emissions for up to 80% while increasing the quality of the polished product (Pusavec & Kenda, 2014).

Among the environmental topics in sustainability, climate change has been of increasing importance in recent years. What is meant by climate change? ← 17 | 18 →

“Anthropogenic greenhouse gas emissions have increased since the pre-industrial era, driven largely by economic and population growth, and are now higher than ever. This has led to atmospheric concentrations of carbon dioxide, methane and nitrous oxide that are unprecedented in at least the last 800,000 years. Their effects, together with those of other anthropogenic drivers, have been detected throughout the climate system and are extremely likely to have been the dominant cause of the observed warming since the mid-20th century.” (IPCC, 2014, p. 4).

The importance of climate change among environmental issues can be seen from the Environmental Performance Index (Emerson et al., 2010): Among ten different environmental policies of which the index is composed, a weight of 25% is attached to climate change, by far the highest. No wonder that an abundant amount of literature can be found about climate change. This is true for economic science, too. For example, a literature review by Stechemesser & Guenther (2012) revealed 129 articles alone on the topic of carbon accounting. The importance of the topic to economic sciences is also founded in the growing awareness that climate change most likely affects all kinds of businesses: A “carbon crisis” seems possible, with fossil fuels becoming a scarce resource and the changing of the climate affecting economic action (Shrivastava & Busch, 2013). This calls for a two-fold strategic approach of fighting climate change: “Avoiding the unmanageable – harmful climatic change due to a significant further increase in greenhouse gas emissions – and managing the unavoidable – the impacts of the already noticeable and further anticipated climatic changes…” (Weinhofer & Busch, 2013, p. 140, based on Friedman, 2008). No wonder that, especially from management literature, several business frameworks have emerged that address climate change: Birnik (2013) provides a framework for a firm-level climate change strategy with the four steps knowledge acquisition and key stakeholders conviction, quantification of climate impact, management of greenhouse gas emissions, and shaping the competitive landscape. Hendrichs & Busch (2012) focus on small and medium-sized enterprises and present a carbon management framework tailored to their needs. In order to combine a dynamic and static perspective as well as a quantitative and financial view on carbon management, Hoffmann & Busch (2008) provide a framework of four measures on corporate scale: Carbon intensity (carbon usage per size measure per year), carbon dependency (relative change in carbon intensity over time), carbon exposure (monetary implications of carbon usage per year), and carbon risk (change in carbon exposure over time). Additionally, Busch & Wolfensberger (2011) offer eight competitive carbon management strategies, based on different strategies regarding optimization (processes or products/services), competitive focus (lower costs or differentiation), and carbon focus (reduction or compensation).

Despite the optimistic theories regarding sustainability, and the frameworks for coping with climate change, recent research raises doubts whether true sustainability can be reached with these tools and theories. The degree of competitive advantages companies gain from the application of environmental strategies was ← 18 | 19 → found to differ by their characteristics (Christmann, 2000). Hence, there may be also unsustainable business models with negative competitive effects of environmental strategies, which can be seen as “…barriers to the creation of competitive advantage from environmental strategies…”. (Christmann, 2000, p. 676). The choice of environmental strategy (reactive, pollution prevention, environmental leadership) largely depends on the sector a company belongs to (Buysse & Verbeke, 2003), also a hint to inherent unsustainable business models. It is no wonder that, against this background, for decreasing the amount of emissions a change in industrial structures is promoted (Akashi, Hanaoka, Matsuoka, & Kainuma, 2011; Mi, Pan, Yu, & Wei, 2015). Opposed to the optimistic theory that sees large globalized and diversified multi-national enterprises as being ahead in becoming sustainable (Sharfman et al., 2004), large, highly innovative firms are the least likely to reach true sustainability, as the risk imposed by new technologies and new business models may threaten the survival of the firm (Shevchenko, Lévesque, & Pagell, 2016). This has been illustrated for the automobile industry, where CO2 emissions from the use of cars only trended down after the introduction of emission regulations (Voltes-Dorta, Perdiguero, & Jiménez, 2013). And even if voluntary carbon norms are set and adopted by an industry, they may be only seen as a substitute and not a real move towards sustainability (Pinkse & Busch, 2013). Furthermore, companies from dynamic sectors (like fashion, electronics) do not benefit from environmental investments in the supply chain in terms of cost, quality, delivery and flexibility and, therefore, invest less in supply chain environmental practices than companies from static sectors (Wiengarten, Pagell, & Fynes, 2012):

“Previous research that has concluded that it pays to be green has not been nuanced enough. The operational benefits of reducing a supply chain’s impact on the environment will not be equal for all organizations, and based on this research producers in dynamic industries will not reap any operational benefit from such investments.” (p. 548).

Investment policy may also hinder achieving sustainability: Especially high and unsustainable investments shape the future for a long time and can impose a high risk to the business of a company (Busch, Weinhofer, & Hoffmann, 2011). And even if companies are aware of climate change, it does not necessarily mean that they shift to sustainable business models, as an investigation of energy utility companies shows (Weinhofer & Busch, 2013):


ISBN (Hardcover)
2019 (Mai)
Sustainability Supply Chain Management Climate Change Double-entry bookkeeping Regression analysis
Berlin, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2019. 479 pp., 20 fig. col., 52 fig. b/w, 139 tables

Biographische Angaben

Bernhard Goldhammer (Autor:in)

Bernhard Goldhammer has obtained a Diploma in Commerce and Engineering from the University of Karlsruhe (TH), and a doctoral degree in economics from the EBS University for Business and Law, Oestrich-Winkel.


Titel: Corporate Carbon Accounting and Footprinting in the Ecologically Dominant Logic
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482 Seiten