Influence of Environment-conscious Management on Financial Performance: Evidence from Construction Companies in Japan Mika Goto, Tokyo Institute of Technology Yoshito Fukazawa, Tokyo Institute of Technology Mieko Fujisawa, Kanazawa University
Outline • Introduction • Literature review • Purpose of the study • Data • Methodology • Empirical Results • Conclusion 2017/9/6 IAEE Europe 2017 @ Wien 2
Introduction (1/3) • Green growth and sustainable development • Green growth means fostering economic growth and development, while ensuring that natural assets continue to provide the resources and environmental services on which our well-being relies (OECD, 2011: Towards Green Growth) • Green economy • A green economy is one that results in improved human well-being and social equity, while significantly reducing environmental risks and ecological scarcities. In its simplest expression, a green economy can be thought of as one which is low carbon, resource efficient and socially inclusive (UNEP, 2011: Green Economy Report) • Corporate management for green growth and sustainability 2017/9/6 IAEE Europe 2017 @ Wien 3
Introduction (2/3) • Corporate social responsibility (CSR) has been recognized as an essential component for sustainable operation of firms in modern economy. • CSR incorporates a wide range of contents, including work style reform, workforce diversity, legal compliance, and environmental protection. • Environmental protection is one of the most important social issues in the world, particularly after the enactment of Kyoto Protocol in 2005. • Many companies have published environmental and sustainability reports in recent years. • Global Reporting Initiative (GRI) Standards are the first global standards for sustainability reporting. GRI launched the first version of the guidelines, representing the first global framework for comprehensive sustainability reporting in 2000. • Environmental accounting has been introduced by many companies, particularly listed companies. 2017/9/6 IAEE Europe 2017 @ Wien 4
Introduction (3/3) • Concern v.s. Motivation • There is a concern from corporate managers that CSR may impair firms’ profitability. • Meanwhile, an important motivation for them to introduce the environmental accounting is that it may have positive influence on consumers and investors because its introduction gives them good impression on environment-conscious management of companies and consequently increases brand and corporate values. 2017/9/6 IAEE Europe 2017 @ Wien 5
Literature review Relationship Examples Cochran and Wood (1984), McGuire et al. (1988), Russo and Fouts (1997), Waddock and Graves (1997), Griffin and Mahon (1997), Stanwick and Positive Stanwick (1998), Simpson and Kohers (2002), and Orlitzky et al. (2003). Mahapatra (1984), Jaggi and Freedman (1992), and Surroca et al. (2010). Moreover, some studies found no relationship between CSR and financial Negative performance, which include Aupperle et al. (1985), Ullman (1985), Pava and Krausz (1996), and McWilliams and Siegel (2000). • Margolis and Walsh (2003) surveyed 127 previous studies and found that 70 studies showed a positive relationship, 10 studies presented a negative one, 31 studies did not indicate both positive and negative ones. • Furthermore, they report that some combinations of these different relationships were found in 23 studies. These mixed results are also observed in studies on Japanese firms. 2017/9/6 IAEE Europe 2017 @ Wien 6
Purpose of the study • This study examines the relationship between firms’ efforts for implementing CSR and their managerial performance using data of 43 construction firms in Japan from 2011 to 2015. • Construction companies are one of the key players for the development of smart cities and communities, and environment-conscious management is an important factor for sustainable operation of firms. • This study particularly focuses on the influence from environment- related CSR to financial performance. • From the results, this study discusses how environment CSR improves financial performances of construction companies in Japan. 2017/9/6 IAEE Europe 2017 @ Wien 7
Data (1/2) • This study uses panel data comprising 43 construction companies in Japan over the period 2011 – 2015. • CSR data are obtained from Comprehensive CSR Data from Toyo Keizai. • Financial performance data are from Capital IQ of Standard & Poor’s. • This study uses four performance measures: • ROA (return on assets) • ROE (return on equity) • TEV (total enterprise value) • EBITDA (earnings before interest, tax, depreciation, and amortization). • ROA and ROE are indexes, and TEV and EBITDA are given in million Japanese yen. 2017/9/6 IAEE Europe 2017 @ Wien 8
Data (2/2) • We collected 17 items of environment-related CSR as independent variables, and four financial performance indexes as dependent variables. • The 17 CSR items are classified into four groups: • (1) Organization and governance for environment protection (Division, Director, and Percentage), • (2) Environmental accounting (Accounting, Understanding, Cost, Energy, Greenhouse, and Waste), • (3) Environmental management (Management, CO2, GreenPur, Material, WaterPol), and • (4) Countermeasures against climate change problem (Climate, Renewable, and CarbonOff). 2017/9/6 IAEE Europe 2017 @ Wien 9
Method (1/5) • This study applies a “two - step analysis” using a panel data estimation combined with PCA. 1. This study conducts PCA for CSR data, because 17 items are too many to obtain reasonable results when they are all used in an estimation equation. Thus, we apply PCA and summarize CSR information to essential factors or principal components. 2. This study conducts panel data estimation using the principal components as independent variables to explain financial measures as dependent variables. 2017/9/6 IAEE Europe 2017 @ Wien 10
Method (2/5): PCA • We obtained seven principal components that have eigenvalues more or equal to 1. • The cumulative proportion of these seven components is approximately 77%. • The next table describes seven components and eigenvalues that correspond to original 17 items as well as classified four groups. • The results of PCA presents unique characteristics of each component as follows. • Comp1: Quantitative assessment for environment-conscious corporate management; • Comp2: Broader effort for environmental accounting and environmental management; • Comp3: Environmental effort from corporate organization and governance perspectives; • Comp4: Organization, governance, and cost assessment; • Comp5: Environmental management and effort for climate change problems; • Comp6: Organization, governance, and environmental management; • Comp7: Focused effort for environmental accounting and environmental management. 2017/9/6 IAEE Europe 2017 @ Wien 11
Method (3/5) Results of principal component analysis Major CSR Items Comp1 Comp2 Comp3 Comp4 Comp5 Comp6 Comp7 Characteristics Division -0.0745 0.1295 0.0411 -0.2196 -0.2523 0.5488 -0.5096 Organization and Director -0.1166 0.2314 0.4966 0.3343 0.0113 0.1029 -0.0203 governance Percentage -0.0500 0.2822 0.5045 0.3439 0.0991 -0.0199 -0.0426 Accounting 0.0222 0.2903 -0.0412 -0.0083 -0.3896 -0.2851 0.4004 Understanding 0.0737 0.3293 -0.2070 -0.2340 -0.3721 0.1136 0.1187 Cost Environmental 0.3399 -0.1873 -0.0777 0.3838 -0.1598 -0.2051 -0.0301 accounting Energy 0.4896 -0.1233 0.1210 0.0534 0.1244 0.0232 0.0472 Greenhouse 0.4904 -0.1023 0.1100 0.0220 -0.0002 0.1883 -0.1137 Waste 0.3278 0.1434 0.2635 -0.3667 0.2332 0.1210 0.1149 Management 0.1165 0.1079 -0.3319 0.2459 0.2767 0.4527 0.3049 CO 2 0.1517 0.3159 -0.2900 0.1863 0.2121 -0.0161 0.0757 Environmental GreenPur 0.1520 0.2535 0.1793 0.0512 -0.4023 0.2052 0.2861 management Material 0.1086 0.3514 -0.0527 -0.0566 -0.0445 -0.4026 -0.3741 WaterPol 0.0453 0.3300 -0.2168 0.1873 0.1498 -0.1317 -0.3781 Climate Countermeasures -0.3083 0.1362 0.1377 -0.2530 0.3822 -0.0595 0.2651 Renewable against global -0.3136 -0.0596 -0.1621 0.4248 -0.1288 0.2498 0.0151 CarbonOff warming 0.0483 0.3819 -0.1703 -0.0359 0.2651 0.0907 -0.0231 2017/9/6 IAEE Europe 2017 @ Wien 12
Method (4/5) • In the second step, this study applies panel data estimation. • The advantage of using a panel data set is that it enables us to examine the influence from independent variables to a dependent variable based on rich information in general compared with a case of cross-sectional data or time series data. • Further, it captures unobserved unique characteristics of each firm in a constant term. A fixed effects (FE) model and a random effects (RE) model are described in Equations (1) and (2), respectively. The model selection is conducted by using Hausman test. 2017/9/6 IAEE Europe 2017 @ Wien 13
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