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Sustainability Balanced Scorecard Architecture and Environmental Investment Decision-Making Cover

Sustainability Balanced Scorecard Architecture and Environmental Investment Decision-Making

Foundations of Management
Volume 12 (2020): Issue 1 (January 2020)
By: ,   and    
Open Access
|Dec 2020
Figures & tables

Figures & Tables

Table 1

Evolution of BSC to SBSC-4 and SBSC-5

(Source: Authors’ own research)

PhaseSummary of PhaseSource
1BSC: Was introduced as a performance measurement system through a longitudinal research on 12 companies, at the leading edge of performance measurement. The study designed a dashboard (i.e., the BSC) that gives top management a fast and comprehensive view of their business. The BSC includes financial measures that tell the results of actions already taken by complementing financial measures with operational measures on customer satisfaction, internal processes and people within the organization.Kaplan and Norton (2001)
2SBSC-4: Four components (i.e., environment, safety and health performance, employment practices, and community investment) were embedded into the four BSC perspectives. This scorecard was designed for companies to comply with national and local regulations on the environment, employee health and safety, hiring and employment practices to avoid shutdowns or litigations, and so on.Kaplan and Norton (2001)
3SBSC-5: Stephan Schaltegger along with two of his Ph. D students published a seminal paper that introduces the SBSC framework where the sustainability parameters are proposed as a separate 5th perspective. Their initial intent was to introduce non-market perspectives such as “child labor.” In several follow-up papers, Schaltegger and his team introduced other components of sustainability related to the physical environment from environmental management accounting.
The introduction of the 5th perspective, thus gave birth to two separate schools of thought on SBSC; one where sustainability parameters are embedded into BSC perspectives (SBSC-4) and the 5th perspective type configuration with sustainability as a separate perspective (SBSC-5), see Fig. 1.		Figge, et al. (2002)
Figure 1

Architecture of SBSC-4 and SBSC-5 (Source: Authors’ own research)

Figure 2

Research Model (Source: Authors’ own research)

Table 2

Four groups and manipulated conditions (Source: Authors’ own research)

ConditionsConfigurationIncluding riskNumber of SBSC perspectivesExperimental group No.
1SBSC-4 without riskNo4Group 1
2SBSC-4 with riskYes4Group 2
3SBSC-5 without riskNo5Group 3
4SBSC-5 with riskYes5Group 4

[i] Note:Appendix A presents the details of the research instrument with four conditions

Table 3

Descriptive statistics of environmental investment decision-making

(Source: Authors’ own research)

SBSC ArchitectureRiskInvestment AInvestment B
MeanSDMeanSD
SBSC-4Without risk8.409 (42%)2.92211.591 (58%)2.922
With risk5.521 (27.6%)1.64714.478 (72.4%)1.647
SBSC-5Without risk12.833 (64.2%)1.7867.167 (35.8%)1.786
With risk7.56 (37.8%)2.12312.44 (62.2%)2.123

[i] Mean-scores and SD are in millions of dollars allocated by the participants

Table 4

Results of ANOVA for environmental investment decision-making (between subject effect)

(Source: Authors’ own research)

SourcedfMSF-Valuep-Valueη2
SBSC architecture1244.80752.39<0.0010.368
Risk1390.36983.541<0.0010.481
SBSC architecture risk133.377.1410.0090.074

[i] Dependent variable: environmental investment decision making, significant at p < 0.05

Table 5

Pairwise Comparison between SBSC-4 and SBSC-5 (with risk and without risk)

(Source: Authors’ own research)

Risk levelSBSC architectureMean difference (MD)SEp-value95% CI for differenceη2
LBUB
Without riskSBSC-4SBSC-54.424*0.638<0.0013.1575.6920.384
With riskSBSC-4SBSC-52.038*0.6250.0020.7973.2790.106

* The mean difference (MD) is significant at p < 0.05

Table 6

Path coefficient for the mediation effect of SBSC knowledge between SBSC architecture and environmental investment decision-making (Source: Authors’ own research)

PathBSET/Zp-valueLLCIULCI
IV to Mediators (path a)

  • SBSC architecture–SBSC knowledge

−0.6970.334−2.085<0.051.371−0.023
Mediator to DV (path b)

  • SBSC knowledge–env. investment decision-making

1.6060.2107.641<0.0011.1822.030
Direct effect (path c)

  • SBSC architecture–env. investment decision-making

−3.3050.488−6.766<0.001−4.290−2.320
Indirect effect (path ab)

  • SBSC architecture–env. investment decision-making

−1.1190.561−1.996<0.05−2.046−0.165

[i] Significant at p-value < 0.05. The negative signs of the values of B are a result of the manner in which the dichotomous variables are coded. If the coding were reversed, then the values would appear positive. Hence the negative values do not warrant any remarks

Table 7

Results of the mediation test of SBSC Knowledge between SBSC Architecture and Environmental Investment Decision-Making (with risk) (Source: Authors’ own research)

PathBSET/Zp-valueLLCIULCI
IV to Mediators (path a)

  • SBSC architecture–SBSC knowledge

−1.5570.252−6.180<0.001−2.064−1.049
Mediator to DV (path b)

  • SBSC knowledge–env. investment decision-making

1.6330.2187.493<0.0011.1942.071
Direct effect (path c)

  • SBSC architecture–env. investment decision-making

−0.5030.504−0.9990.323−0.5111.518
Indirect effect (path ab)

  • SBSC architecture–env. investment decision-making

−2.5420.536−4.743<0.001−3.640−1.695

[i] Significant at p-value < 0.05. The negative signs of the values of B are a result of the manner in which the dichotomous variables are coded. If the coding were reversed, then the values would appear positive. Hence the negative values do not warrant any remarks.

Table 8

Pairwise comparison between both risk levels (with risk and without risk) (Source: Authors’ own research)

SBSC architectureRiskMean Difference (MD)SEp-value95% CI for differenceη2
LBUB
SBSC-4Without riskWith risk−2.887*0.645<0.001−4.168−1.6070.182
SBSC-5Without riskWith risk−5.273*0.618<0.001−6.501−4.0460.447

* The mean difference is significant at p-value < 0.05. The negative signs of the values of MD are a result of the manner in which the dichotomous variables are coded. If the coding were reversed, then the values would appear positive. Hence the negative values do not warrant any remarks.

Table 9

Conditional direct and indirect effects of SBSC architecture on environmental investment decision-making (with and without risk) (Source: Authors’ own research)

EffectRiskEffectSELLCIULCI
DirectWithout risk−3.2980.511−4.313−2.282
With risk*0.4770.490−0.4971.452
IndirectWithout risk−1.1260.503−2.276−0.215
With risk−2.5160.490−3.570−1.671

* Effects are all non-standardized values. The negative signs of the values of B are a result of the manner in which the dichotomous variables are coded. If the coding were reversed, then the values would appear positive. Hence the negative values do not warrant any remarks.

Table 10

Index of moderated mediation (Source: Authors’ own research)

MediatorIndexSE (Boot)Boot LLCIBoot ULCI
SBSC knowledge−1.3890.717−2.992−0.216
Panel G1

An example of the information that the participants could see at one time (SBSC-4)

Financial perspectiveGoalsInvestment AInvestment B
Return on investment17%12–14%16–22%
Annual cash flow increase$325,000$100,000–$300,000$300,000–$400,000
Sales growth24%22–27%18–23%
Payback period3 years5 years3 years
Energy cost savings325,000300,000–400,000100,000–300,000
Panel G2

An example of the information that the participants could see at one time (SBSC-4 with risk)

Financial perspectiveGoalsInvestment ARiskInvestment BRisk
Return on investment17%12–14%>1516–22%<15
Annual cash flow increase$325,000$100,000–$300,000$300,000–$400,000
Sales growth24%22–27%18–23%
Payback period3 years5 years3 years
Energy cost savings325,000300,000–400,000100,000–300,000
Panel G3

An example of the information that the participants could see at one time (SBSC-5)

Environmental perspectiveGoalsInvestment AInvestment B
Energy cost savings325,000300,000–400,000100,000–300,000
Number of community complaints about company pollutant emissions31–37–9
Annual tons of nitrogen dioxide emissions3020–3040–55
Number of hours of training per factory employee for environmental emergency responses275180–250240–300
Panel G4

An example of the information that the participants could see at one time (SBSC-5 with risk)

Environmental perspectiveGoalsInvestment ARiskInvestment BRisk
Energy cost savings325,000300,000–400,000<15100,000–300,000>15
Number of community complaints about company pollutant emissions31–37–9
Annual tons of nitrogen dioxide emissions3020–3040–55
Number of hours of training per factory employee for environmental emergency responses275180–250240–300
DOI: https://doi.org/10.2478/fman-2020-0015 | Journal eISSN: 2300-5661 | Journal ISSN: 2080-7279
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Language: English
Page range: 193 - 210
Published on: Dec 31, 2020
Published by: Warsaw University of Technology
In partnership with: Paradigm Publishing Services
Keywords:
sustainability balanced scorecard,
SBSC architecture,
environmental investment decision,
SBSC knowledge,
strategic risk information
JEL:
M41,
D81
Related subjects:
Computer sciences,
Business computing,
Business and economics,
Business management,
Management accounting, financial controlling, cost calculation, investment

© 2020 Suaad Jassem, Zarina Zakaria, Anna Che Azmi, published by Warsaw University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 12 (2020): Issue 1 (January 2020)
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