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A study on corporate social responsibility impact analysis and design for environment (本文)

澁谷, 健一 慶應義塾大学

2023.09.05

概要

In recent years, companies are expected to coexist with society and the environment. In
order to respond to changing social conditions and consumer needs, it is a challenge to
clarify customer perspectives toward the companies. This paper proposes and
demonstrates a causal structure model of corporate social responsibility (hereinafter
referred to as CSR), cost of ownership, quality dimensions, customer satisfaction, and
customer loyalty. In addition, the assurance case was applied to the environmentally
conscious design of automobiles, and the effectiveness of the assurance case was verified.
The results of this study aim to obtain knowledge that will help strategic decision making
in corporate efforts toward society and the environment. This paper consists of three
studies in the automotive industry. The first study compares the causal structure of
automobile serviceability, cost of ownership, CSR, customer satisfaction, and customer
loyalty across countries based on the results of a questionnaire survey of automobile users
in Japan and France. Exploratory factor analysis (hereinafter referred to as EFA) was used
to extract the above five factors, and a hypothetical model was constructed from the
extracted factors. Subsequently, confirmatory factor analysis (hereinafter referred to as
CFA) and structural equation modeling (hereinafter referred to as SEM) were conducted.
The results showed that CSR affects customer satisfaction in Japan, but not in France. In
contrast to France, Japan places more importance on CSR, indicating that it is a factor
that improves customer satisfaction. The second study examined the causal structure of
CSR, social quality, perceived quality, customer satisfaction, and customer loyalty in
Japan, where CSR influences customer satisfaction, by means of a questionnaire survey.
The results showed that CSR was associated with customer loyalty. The results showed
that CSR does not directly affect customer loyalty, but it does affect customer satisfaction
through the mediation of perceived quality. Social quality was also found to affect
customer satisfaction through the mediation of perceived quality, although it does not
directly affect customer satisfaction. The second study showed that perceived quality is a
mediator of CSR and social quality. In the third study, the assurance case was applied to
the management of Design for Environment (hereinafter referred to as DfE), which is one
of the initiatives listed as a CSR promotion item. We proposed an assurance case
description method to be applied to the process of conceptual design based on evidence
from multiple studies at the product planning stage in DfE for automobiles. As a result, it
was shown that the assurance case enables the person in charge to act autonomously by
visualizing the work process in the execution of DfE. ...

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参考文献

Factor 4. Corporate social responsibility (CSR)

This automobile company seeks to ensure long-term

success.

This automobile company will always respect the rules

and regulations set forth by law.

respect the rules and regulations always set by law.

The automobile company is committed to social

responsibility.

The automobile company

environmental impact.

strictly

manages

(Waller, 2016)

(Dočekalová, 2016)

(Rahdari et al., 2015)

its

The automobile company invests in environmental

protection activities.

Factor 5. Customer satisfaction (CS)

You are satisfied with the experience of being involved

with this automobile.

You are satisfied with my decision to purchase this

vehicle.

You are satisfied with the car.

This car is close to your ideal.

146

(Crosby et al., 1990)

(Rust et al., 1994)

(Suzuki, 2010)

(Syahrial et al. 2018)

Appendix C. Estimation of structural equation model

Equations

Multivariate normal

distribution

Likelihood function

logarithmic likelihood

function

Objective variable

Sample covariance

matrix

𝑓𝑓(𝒙𝒙|𝝁𝝁 𝜽𝜽) =

𝑛𝑛

−1

(2𝜋𝜋)− 2 |∑(𝜽𝜽)|𝑒𝑒𝑒𝑒𝑒𝑒 � (𝒙𝒙

− 𝝁𝝁)�

− 𝝁𝝁)′ ∑(𝜽𝜽)−𝟏𝟏 (𝒙𝒙

𝑓𝑓(𝑿𝑿|𝝁𝝁 𝜽𝜽) = 𝑓𝑓(𝒙𝒙𝟏𝟏 |𝝁𝝁 𝜽𝜽) × ⋯ × 𝑓𝑓 (𝒙𝒙𝒊𝒊 |𝝁𝝁 𝜽𝜽) × ⋯

× 𝑓𝑓(𝒙𝒙𝑵𝑵 |𝝁𝝁 𝜽𝜽)

𝑁𝑁

log�𝑓𝑓(𝑿𝑿|𝝁𝝁 𝜽𝜽)� = � log(𝑓𝑓(𝒙𝒙𝒊𝒊 |𝝁𝝁 𝜽𝜽))

(1)

(2)

(3)

𝑖𝑖=1

𝑓𝑓𝑀𝑀𝑀𝑀 = 𝑡𝑡𝑡𝑡(∑(𝜽𝜽)−1 𝑺𝑺) − log|∑(𝜽𝜽)−1 | − log|𝑺𝑺| − 𝑛𝑛

= 𝑡𝑡𝑡𝑡(∑(𝜽𝜽)−1 𝑺𝑺) − log|∑(𝜽𝜽)−1 𝑺𝑺| − 𝑛𝑛

𝑺𝑺 =

𝑥𝑥:Observed variable

𝑛𝑛:Number of observation variables

𝜇𝜇: expectation vector of (𝑛𝑛 × 1)

𝑓𝑓𝑀𝑀𝑀𝑀 : Objective variable

𝜃𝜃: parameter vector

𝑁𝑁:Number of samples

𝑋𝑋 = (𝑥𝑥1 , 𝑥𝑥2 , ⋯ , 𝑥𝑥𝑁𝑁 ): Sample vector

𝑆𝑆: Sample covariance matrix

𝑥𝑥̅ : Sample mean vector

𝒏𝒏

𝟏𝟏

�)(𝒙𝒙𝒊𝒊 − 𝒙𝒙

�)′

� (𝒙𝒙𝒊𝒊 − 𝒙𝒙

𝒏𝒏 𝒊𝒊=𝟏𝟏

147

(4)

(5)

Appendix D. List of model fitting indexes

Index

Equations

chi-square goodness of fit

Root Mean Square Error

of Approximation

(RMSEA)

Goodness of Fit Index

(GFI)

𝑑𝑑𝑑𝑑 = 𝑛𝑛(𝑛𝑛 + 1) − 𝑝𝑝

𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = �𝑀𝑀𝑀𝑀𝑀𝑀 �

𝐺𝐺𝐺𝐺𝐺𝐺 = 1 −

=1−

Adjusted GFI

(AGFI)

(7)

𝜒𝜒 2 − 𝑑𝑑𝑑𝑑

, 0�

𝑑𝑑𝑑𝑑(𝑁𝑁 − 1)

(8)

� �−1 �𝑺𝑺 − ∑�𝜽𝜽

� �� � �

𝑡𝑡𝑡𝑡 ��∑�𝜽𝜽

� �−1 𝑺𝑺� �

𝑡𝑡𝑡𝑡 ��∑�𝜽𝜽

−1

� � 𝑺𝑺 − 𝑰𝑰� �

𝑡𝑡𝑡𝑡 ��∑�𝜽𝜽

−1

(9)

� � 𝑺𝑺� �

𝑡𝑡𝑡𝑡 ��∑�𝜽𝜽

𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = 1 −

𝐶𝐶𝐶𝐶𝐶𝐶 = 1 −

Comparative Fit Index

(CFI)

(6)

𝜒𝜒 2 = (𝑁𝑁 − 1)𝑓𝑓𝑀𝑀𝑀𝑀

𝑛𝑛(𝑛𝑛 + 1)

(1 − 𝐺𝐺𝐺𝐺𝐺𝐺 )

2𝑑𝑑𝑑𝑑

𝑚𝑚𝑚𝑚𝑚𝑚�(𝑁𝑁 − 1)𝑓𝑓𝑀𝑀𝑀𝑀 − 𝑑𝑑𝑑𝑑, 0�

max�(𝑁𝑁 − 1)𝑓𝑓0 − 𝑑𝑑𝑓𝑓0 �

𝑑𝑑𝑓𝑓0 = 𝑛𝑛(𝑛𝑛 − 1)

−1

𝑓𝑓0 = 𝑡𝑡𝑡𝑡 ��𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑(𝑺𝑺)� 𝑺𝑺�

− log|(𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑(𝑺𝑺)−1 𝑺𝑺)| − 𝑛𝑛

−1

= 𝑛𝑛 − log ��𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑(𝑺𝑺)� 𝑺𝑺� − 𝑛𝑛

−1

= − log ��𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑(𝑺𝑺)� 𝑺𝑺�

𝜒𝜒 2 : chi-square, 𝑁𝑁:Number of samples, 𝑛𝑛:Number of observation variables,

𝑝𝑝:Number of parameters, 𝜃𝜃� : Maximum likelihood estimate,

𝑆𝑆: Sample covariance matrix

148

(10)

(11)

(12)

(13)

Appendix E: Reliability coefficient

Equations

Cronbach 𝛼𝛼

coeficient

𝑝𝑝

∑𝑗𝑗=1 𝑠𝑠𝑗𝑗𝑗𝑗

𝑝𝑝

𝛼𝛼 =

�1 −

𝑝𝑝 − 1

𝑠𝑠𝑇𝑇2

∑𝑝𝑝𝑖𝑖1,𝑖𝑖≠𝑗𝑗 ∑𝑝𝑝𝑗𝑗=1 𝑠𝑠𝑖𝑖𝑖𝑖

𝑝𝑝

𝑝𝑝 − 1

𝑠𝑠𝑇𝑇2

𝑝𝑝: Number of parameters

𝑠𝑠𝑗𝑗𝑗𝑗 : Sample covariance of item i, j

𝑠𝑠𝑇𝑇2 : Variance of the overall scores for the items of the target concept

Index

Criteria

Citation

Cronbach 𝛼𝛼

>0.7

(Nummally, 1978)

149

(14)

Appendix F. List of construct validity indexes

Equations

(∑ 𝜆𝜆𝑖𝑖 )2

𝐶𝐶𝐶𝐶 =

(∑ 𝜆𝜆𝑖𝑖 )2 + (∑ 𝜀𝜀𝑖𝑖 )

Construct reliability

Average variance

extracted

(15)

𝜀𝜀𝑖𝑖 = 1 − 𝜆𝜆𝑖𝑖 2

𝐴𝐴𝐴𝐴𝐴𝐴 =

𝜆𝜆: standardized factor loading for item 𝑖𝑖

𝜀𝜀: respective error variance for item 𝑗𝑗

∑ 𝜆𝜆𝑖𝑖 2

�∑ 𝜆𝜆𝑖𝑖 � + ∑�1 − 𝜆𝜆𝑖𝑖 2 �

150

(16)

Appendix G: List of evaluation index and criteria

Index

Criteria

Citation

Chi-square/df

<5.0

(Hu et al., 1997)

CFI

>0.9

(Hu et al., 1997)

AGFI

>0.8

(Hu et al., 1997)

GFI

>0.8

(Hu et al., 1997)

RMSEA

<0.08

(Hu et al., 1997)

Composite Reliability

(CR)

>0.70

(Fornel et al., 1981)

Average Variance Extracted

(AVE)

>0.50

(Fornel et al., 1981)

Factor loading

>0.50

(Hair et al., 2016)

151

List of achievements

Articles in publications (peer reviewed)

1.

Shibuya, K, Hu, E, Kobayashi, N., Suzuki, H. (2023). Visualizing the Project of

Design for Environment to Improve the Feasibility for Corporate Social

Responsibility. Review of Integrative Business and Economics Research, Vol. 12(1),

56-70.

2.

Shibuya, K., Jean-Baptiste Blet, Suzuki, H. (2024). Evaluation on the Impact of

Quality Dimensions for Social Perception. Review of Integrative Business and

Economics Research, Vol. 13(1), 1-19.

*RIBER Best Paper Prize

Articles in review stage (journal peer review)

1.

Shibuya, K., Jean-Baptiste Blet, Suzuki, H. (2023). Customer perceptions of social

quality in Garvin’s quality dimensions

Presentation at international conference (peer reviewed)

1.

Shibuya K.*., Kobayashi N., Shirasaka S. (2021). Proposal of Assurance Case

Description Method in Design for Environment (DfE) Process, Proceedings of the

4th International Conference on Complex Systems Design and Management Asia

and of the 12th Conference on Complex Systems Design and Management, CSD &

M 2021, pp. 357-369.

Presentation at Japanese conference

1.

Shibuya, K.*, Jean-Baptiste Blet, Suzuki, H. (2022). Comparison of the relationship

between CSR and customer loyalty between Japan and France using the case of

automobiles, The Japanese society for quality control, 52nd annual conference.

152

2.

Shibuya, K.*, Jean-Baptiste Blet, Suzuki, H. (2023). Impact of Garvin's Quality

Dimensions and Social Quality on Customer Satisfaction, The Japanese society for

quality control, 131st research and presentation conference.

Others

• Presentation at international conference (peer reviewed)

1. Shibuya, K.*, Suzuki, H. (2022). Citizen Perceptions of Intention to Live in a Smart

Cities Based on its Characteristics. IIAI Letters on Business and Decision Science,

Vol. 001, LBDS002 DOI: https://doi.org/10.52731/lbds.001.002.

• Articles in review stage (journal peer review)

2. Shibuya, K., Suzuki, H. (2022). A study on intention to live in a smart cities based on

perceived usefulness of citizen

153

...

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