Integrating the Sustainable Development Goals into Corporate Governance: A Cross-Sectoral Analysis of Japanese Companies

Abstract

The Sustainable Development Goals (SDGs) have become a guiding framework for the public and private sectors. For companies, the SDGs offer a way to create value for investors while addressing local and global issues. Japan has embraced the SDGs to demonstrate its commitment to sustainable development but, despite its high ranking, faces challenges in improving its performance. This study aims to investigate how Japanese companies are considering the SDGs in their corporate governance. Using a database of corporate social responsibility activities in 1630 companies, the degree to which the 17 SDGs are being integrated was examined across 33 industrial sectors. Next, hierarchical clustering on principal components was applied and identified four distinct patterns in the integration of the SDGs, ranging from almost no consideration of the SDGs to the nearly full consideration of all 17 goals, with two transitionary patterns in between. Some sectors strongly tended to belong to one pattern of SDG integration, while other sectors exhibited more variability. While the direct implications of this study may be limited to the context of Japan, the methodologies and outcomes point to future research that could lead to a better understanding of how the SDGs are being approached by the private sector.

1. Introduction

1.1. Background

In the last century, the term “sustainability” was often used to discuss the relationship between environmental issues and society and, up to the 1950s, most discourse occurred at the regional scale and was concentrated mainly in Europe [1]. However, in 1968, the “Tragedy of Commons” [2] was published and became one of the most influential publications for global sustainability. This article emphasized the importance of proper regulation for preventing the over-exploitation and destruction of non-renewable common sources driven exclusively by self-interest and profit maximization. Since then, a growing awareness and understanding of the global need for sustainability and sustainable development has led to an increase in discourse and consideration in local, regional, and global decision making.

The latest global initiative for guiding international efforts towards sustainable development is the Sustainable Development Goals (SDGs) [3]. Implemented in 2016, the SDGs comprise 17 goals and 169 targets spanning the environmental, social, and economic dimensions of sustainability, and can be implemented in both the public and private sectors. The SDGs cover a wide range of interconnected issues, including poverty, hunger, health, education, gender equality, clean water and sanitation, affordable and clean energy, decent work and economic growth, industry, innovation and infrastructure, reduced inequalities, sustainable cities and communities, responsible consumption and production, climate action, life below water, life on land, peace, justice and strong institutions, and partnerships for the goals. These goals have brought renewed attention to the importance of achieving sustainable development outcomes. However, measuring progress on targets is a significant challenge due to the multi-dimensional and context-specific nature of the goals. To effectively track and measure the 17 SDGs, official national statistics and surveys remain crucial, but data partnerships with private companies can enhance SDG monitoring. A blended approach combining robust official statistics with diverse data sources can provide a more comprehensive picture of the progress towards the SDGs.

Corporate governance plays an important role in enabling companies to contribute to the achievement of the SDGs. Strong corporate governance mechanisms, such as an independent and diverse board, effective board oversight, and robust risk management practices can drive companies to prioritize and integrate SDGs into their business strategies and operations. Considering the SDGs in business strategies and operations can generate benefits for companies, but it is unclear how much progress the private sector has made in integrating the SDGs.

1.2. Research Objectives

The goal of this study is to investigate the degree to which the private sector has integrated the SDGs into their governance practices using data on the corporate social responsibility (CSR) practices of Japanese businesses. Japan has been actively engaged in implementing and promoting the SDGs in the both the public and private sectors, especially to improve its competitiveness on international markets and demonstrate the country’s commitment to the sustainable cause. Currently, Japan holds the 21st position among 166 countries in the SDG index rank (2023) [4]. Although this achievement ranks Japan highly in the world, there are still major challenges remaining.

The first objective of this study is to evaluate the rate at which the 17 individual SDGs are being integrated across the different industrial sectors in Japan. As the integration of the 17 goals may present complicated behavior, the next objective is to clarify the patterns in the integration of the SDGs using the Hierarchical Cluster on Principal Components (HCPC), which should facilitate ease of interpretation and understanding. The final goal is to examine the distribution across the clusters of the different industrial sectors in the Japanese private sector to better understand the trends in the integration of the SDGs.

The SDGs are internationally valued, and the cross-sectoral analysis that this paper aims to achieve will indicate how different industries are making efforts to improve their contribution to realizing global sustainable development. It is thus expected that the outcomes of this study will define the gaps that exist between industrial sectors and identify priorities for possible action in the case of Japan. While the detailed results may be limited to the Japanese context, the presented methodology should be applicable for any similar studies in different countries or contexts.

1.3. Research Flow

The research flow is shown in Figure 1. First, a raw database on CSR activities in the Japanese private sector was cleaned to obtain the analysis database. The degree to which the SDGs are being integrated in each industrial sector was then evaluated using the sectoral integration rate, which achieved the first objective of the study. To identify the patterns in the integration of the SDGs, multiple correspondence analysis (MCA) and hierarchical clustering on principal components (HCPC) were carried out, from which groups of companies integrating the SDGs in similar ways were identified. The integration patterns were then quantified using the cluster integration rate, which was calculated based on the number of companies in each cluster integrating each SDG. These results contribute to the achievement of the second objective. Finally, the relationship between the industrial sectors and the clusters were examined using the cluster membership rate and the sectoral representativeness ratio, which normalize and compare the integration of the SDGs in each sector. From this result, together with the results of the first and second objectives, the third objective was realized. The details of these steps, and the associated results and discussions, will be presented in the following sections.

2. Literature Review

Awareness of environmental degradation increased during the previous century as society became more knowledgeable and greater information became available to people, leading to efforts to reverse or mitigate the damage caused by humankind to the planet. The latest global initiative is the Sustainable Development Goals (SDGs), which was implemented in 2016 and lays out a broad range of targets under 17 goals (Table 1) that should be achieved by 2030. The goals are not compulsory but provide a framework for the public and private sectors to pursue sustainable development and demonstrate a commitment to sustainability.

The UN Agenda 2030 provides a framework with clear objectives for integrating SDGs into corporate strategies, emphasizing principles such as people, planet, prosperity, peace, and partnerships. The effectiveness of this framework relies on competent implementation by businesses, governments, and civil society, with criteria like interconnectedness and inclusiveness being essential for realizing the transformative potential of the SDGs [5,6,7]. Integrating Corporate Social Responsibility (CSR) categories under the SDG framework offers a strategic approach to achieving excellence, addressing current and future needs with measurable outcomes, and combining CSR and SDGs into a robust roadmap for corporate sustainability [8]. SDG reporting enhances corporate transparency and aligns activities with global sustainability goals. Early adopters of SDG reporting typically exhibit better organizational sustainability practices. Additionally, SDGs-related research related to productivity and impact have been analyzed using bibliometric tools, underscoring the need for systematic implementation and collaboration in achieving SDG targets [9,10]. Social impact theory can also aid in understanding how companies can apply the UN Agenda 2030 sustainably by focusing on the social consequences of corporate actions, assessing how business activities alter people’s lives, work, and social organization, thereby highlighting the broader social implications of corporate integration with SDGs [5,7].

Table 1. Summary of the 17 Sustainable Development Goals.

No.	Title	Description
1	No poverty	End poverty in all its forms everywhere
2	Zero hunger	End hunger, achieve food security and improved nutrition and promote sustainable agriculture
3	Good health and well-being	Ensure healthy lives and promote well-being for all at all ages
4	Quality education	Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
5	Gender equality	Achieve gender equality and empower all women and girls
6	Clean water and sanitation	Ensure availability and sustainable management of water and sanitation for all
7	Affordable and clean energy	Ensure access to affordable, reliable, sustainable and modern energy for all
8	Decent work and economic growth	Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
9	Industry, innovation, and infrastructure	Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
10	Reduce inequality within and among countries	Reduce inequality within and among countries
11	Sustainable cities and communities	Make cities and human settlements inclusive, safe, resilient and sustainable
12	Responsible consumption and production	Ensure sustainable consumption and production patterns
13	Climate action	Take urgent action to combat climate change and its impacts
14	Life below water	Conserve and sustainably use the oceans, seas and marine resources for sustainable development
15	Life on land	Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
16	Peace, justice, and strong institutions	Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
17	Partnerships for the goals	Strengthen the means of implementation and revitalize the global partnership for sustainable development

Source: adapted from United Nations [11].

Table 1. Summary of the 17 Sustainable Development Goals.

No.	Title	Description
1	No poverty	End poverty in all its forms everywhere
2	Zero hunger	End hunger, achieve food security and improved nutrition and promote sustainable agriculture
3	Good health and well-being	Ensure healthy lives and promote well-being for all at all ages
4	Quality education	Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
5	Gender equality	Achieve gender equality and empower all women and girls
6	Clean water and sanitation	Ensure availability and sustainable management of water and sanitation for all
7	Affordable and clean energy	Ensure access to affordable, reliable, sustainable and modern energy for all
8	Decent work and economic growth	Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
9	Industry, innovation, and infrastructure	Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
10	Reduce inequality within and among countries	Reduce inequality within and among countries
11	Sustainable cities and communities	Make cities and human settlements inclusive, safe, resilient and sustainable
12	Responsible consumption and production	Ensure sustainable consumption and production patterns
13	Climate action	Take urgent action to combat climate change and its impacts
14	Life below water	Conserve and sustainably use the oceans, seas and marine resources for sustainable development
15	Life on land	Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
16	Peace, justice, and strong institutions	Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
17	Partnerships for the goals	Strengthen the means of implementation and revitalize the global partnership for sustainable development

Source: adapted from United Nations [11].

Besides the social impacts that focus on community, the impacts on companies as a result of incorporating the SDGs can be approached in two ways, as illustrated in Figure 2: (1) from the global point of view of the SDGs as an external factor influencing the internal corporate governance of companies (i.e., “external to internal”); and (2) from the perspective that sustainable practices inside corporate governance contributing positively to the implementation of SDGs (i.e., “internal to external”).

The work of Soysa et al. [12] on the development of an SDGs-based sustainable reporting index among Sri Lankan business firms is one example of the first point of view “external to internal.” They found that some firms use a combination of the SDGs and Global Reporting Initiative (GRI) for their sustainability reports and developed an index to monitor sustainability in private businesses combining both of these.

Principal component analysis (PCA) was used to examine the reliability of the created scoring system based on the SDGs, and the results confirmed the usefulness of the reporting index method as a replicable method for measuring sustainable performance in private businesses. Toukabri and Mohamed Youssef [13] invested climate change disclosure and the SDGs as moderators of corporate governance. Their study points to the lack of research on the effective governance structures for contributing to the SDGs. The results showed that the components of corporate governance can influence things such as carbon emissions disclosure and reduction, thus contributing to improved practices for carbon neutrality in general.

On the other hand, examples of sustainable practices in corporate governance influencing the SDGs (“internal to external”) can be seen in the work of Martinez-Ferreiro and Garcia-Meca [14], who studied the role of internal corporate governance mechanisms such as CEO independence, board composition, and board attendance as mechanisms for achieving the SDGs. Their results indicated that strong internal corporate governance positively contributes to the SDGs. In Malaysia, a study on the role played by corporations in facilitating the SDGs was carried out due to a lack of information on the relationship between the private sector and the SDGs in Malaysia [15]. It was found that the most frequently reported goals were Goals 2 and 8, and the authors concluded that there is a positive relationship between governance practices and company participation in the SDGs—especially for board meeting frequency.

In Japan, the study of Masuda et al. [16] investigated how municipalities are incorporating SDGs in their agendas. The research developed an analytical framework identifying the key components for successful SDG mainstreaming, such as governance structures, stakeholder engagement, policy mechanisms, and monitoring systems. Through the case studies of designated municipalities, they revealed approaches that foster local ownership, link existing policy resources with formal procedures, establish multi-stakeholder partnerships, and create vertical communication channels with higher-level organizations. The findings suggest that these approaches are essential for effectively integrating SDGs at the local level, providing valuable insights for other regions aiming to achieve sustainable development goals. This study highlights the significant role of local governments in addressing global challenges by leveraging local contexts and resources to implement comprehensive sustainability strategies, but the results are limited to the public sector.

The relationship between the SDGs and corporate governance has been generally shown to be positive and beneficial for businesses and the environment. However, there are few studies that focus on how this relationship may vary between different industrial sectors. In this study, the “external to internal” perspective is adopted to examine in detail the external influence of the SDGs on corporate governance practices in the Japanese private sector.

3. Methodology

3.1. Data Overview

The data used for this research were obtained from a commercial database on CSR activities in Japan developed by Toyo Keizai Inc. (Tokyo, Japan), a prominent Japanese economics and business publishing company [17]. Toyo Keizai Inc., established in 1895, is well known for its comprehensive economic and business analyses. The company publishes books and reports that cover a wide range of topics including corporate social responsibility, economic trends, and business practices. Their CSR database, in particular, is highly regarded for its depth and breadth, providing detailed information on the CSR activities of numerous companies in Japan. This extensive resource enables businesses, researchers, and policymakers to conduct thorough analyses and derive valuable insights into corporate sustainability practices across different sectors and serves as an important source of data for analytical research.

The database contains more than 1000 items separated into three major categories—(1) employment and human resources utilization; (2) general CSR, social contributions, and internal controls; and (3) environment—and has been carried out once a year since 2006. This research utilizes the 2022 database, which reports the results of the CSR survey carried out in 2021 and contains responses from 1630 companies spanning 33 industries. The distribution of responding companies by industrial sector is shown in

Table 2. Distribution of companies in the 2022 database by industrial sector (SR: sampling rate).

No.	Industrial Sector	Abbreviation	Count	SR (%)
1	Air transportation	Air_Transp	3	0.2
2	Banking	Banking	47	2.9
3	Chemistry	Chemistry	126	7.7
4	Construction industry	Constr_IND	79	4.8
5	Electrical equipment	Eletricl_Equi	131	8.0
6	Electricity and gas industry	Eletrici_Gas_IND	17	1.0
7	Fiber products	Fiber_Prod	26	1.6
8	Fisheries, agriculture, and forestry	Fish_Agro_Forestry	5	0.3
9	Glass and clay products	Glass_Clay_Prod	18	1.1
10	Groceries	Groceries	63	3.9
11	Information and communication industry	Info_Commu_IND	153	9.4
12	Insurance business	Insur_Businn	14	0.9
13	Land transportation	Land_Transp	36	2.2
14	Machine	Machine	105	6.4
15	Metal products	Metal_Prod	36	2.2
16	Mining	Mining	2	0.1
17	Nonferrous metal	Non_FerreMetal	18	1.1
18	Other financial services	Other_FinancServ	18	1.1
19	Other products	Other_Prod	48	2.9
20	Petroleum and coal products	Petro_Coal_Prod	6	0.4
21	Pharmaceuticals	Pharma	35	2.1
22	Precision mechanical equipment	Precis_Mech_Equip	23	1.4
23	Pulp/paper	Pulp_Paper	11	0.7
24	Real estate business	Real_State	47	2.9
25	Retail business	Retail_Businn	129	7.9
26	Rubber product	Rubber_Prod	12	0.7
27	Securities and commodity futures trading business	Secur_Commodities	16	1.0
28	Service industry	Serv_IND	161	9.9
29	Shipping industry	Shipping_IND	5	0.3
30	Steel	Steel	19	1.2
31	Transportation equipment	Transp_Equi	59	3.6
32	Warehousing and transportation related business	Warehou_Transp	17	1.0
33	Wholesale trade	Wholesale_Trade	145	8.9
Total			1630	100

.

The sectors with the most companies were the service industry (161 companies, 9.9%), the information and communication industry (153 companies, 9.4%), and wholesale trade (145 companies, 8.9%), whereas the industries with the fewest companies were the shipping industry (5 companies, 0.3%), fisheries, agriculture, and forestry (5 companies, 0.3%), air transportation (3 companies, 0.2%), and mining (2 companies, 0.1%).

To examine the integration of the SDGs into corporate governance in Japan, this research focused on just two items from the survey. The first is the industrial classification of the company, which was present in the database as a nominal variable consisting of the 33 industries introduced in Table 2. The second item asked the companies whether they are referencing the SDGs in their governance. This question was presented for each SDG, for a total of 17 sub-items. Responses were coded as a dummy variable, with “1” indicating that the company was referencing that SDG and “0” indicated that they were not referencing that SDG. After extracting the target data, the database for analysis consisted of 1630 observations of 18 variables. The details of these variables are shown in

Table 3. Summary of variables used in the analysis.

No.	Description	Type	Response Options
1	Industrial classification	Nominal	Banking, groceries, etc. (full list in Table 2)
2	Is the company referencing SDG 1?	Binary	1: Yes, 0: No
3	Is the company referencing SDG 2?	Binary	1: Yes, 0: No
4	Is the company referencing SDG 3?	Binary	1: Yes, 0: No
5	Is the company referencing SDG 4?	Binary	1: Yes, 0: No
6	Is the company referencing SDG 5?	Binary	1: Yes, 0: No
7	Is the company referencing SDG 6?	Binary	1: Yes, 0: No
8	Is the company referencing SDG 7?	Binary	1: Yes, 0: No
9	Is the company referencing SDG 8?	Binary	1: Yes, 0: No
10	Is the company referencing SDG 9?	Binary	1: Yes, 0: No
11	Is the company referencing SDG 10?	Binary	1: Yes, 0: No
12	Is the company referencing SDG 11?	Binary	1: Yes, 0: No
13	Is the company referencing SDG 12?	Binary	1: Yes, 0: No
14	Is the company referencing SDG 13?	Binary	1: Yes, 0: No
15	Is the company referencing SDG 14?	Binary	1: Yes, 0: No
16	Is the company referencing SDG 15?	Binary	1: Yes, 0: No
17	Is the company referencing SDG 16?	Binary	1: Yes, 0: No
18	Is the company referencing SDG 17?	Binary	1: Yes, 0: No

.

3.2. Analytical Methods

3.2.1. Quantifying and Comparing the SDGs Integration between Sectors

Cross tabulation was carried out to examine the degree to which the SDGs were being integrated by the companies within each industrial sector. Results were reported as the sectoral integration rate by SDG (IR_sect,sdg), which is calculated using Equation (1).

$$I{R}_{sect,sdg}={\displaystyle \frac{n_{sect\_integ,sdg}}{n_{sect\_total}}}\times 100$$

(1)

where n_{sect_integ,sdg}: number of companies in an industrial sector integrating an SDG; and n_{sect_total}: total number of companies in that industrial sector.

3.2.2. Identifying Patterns in SDG Integration

While the preceding metric examines the integration of the SDGs individually, it was assumed that, due to the large number of SDGs and industrial sectors, trends in the integration of the SDGs may not be readily apparent or easily interpretable. Furthermore, there may be synergies and trade-offs in how the SDGs are being integrated in the corporate governance of Japanese companies. Therefore, the goal of the next analytical step was to uncover patterns in the integration of the SDGs among the companies present in the analysis database considering the underlying data structure and relationships present in the integration of 17 SDGs. As the integration of the SDGs was represented by 17 binary variables, multivariate analysis was adopted to explore the multidimensional data. Multivariate analysis was developed in the 1960s and serves as an exploratory method for examining the associations between variables in a large categorical dataset [18]. The previous examples of the application of multivariate analysis to the study of corporate governance can be found for describing the board composition of Danish companies [19,20] and for analyzing the effect of board structure and internal corporate governance mechanisms on firm value in an emerging market [21].

The patterns in the integration of the SDGs were analyzed using hierarchical clustering on principle components (HCPC). HCPC first conducts multiple correspondence analysis (MCA) to reduce noise in the dataset and focus on the variables or latent variables with the greatest contribution to the variance in the dataset. After selecting an appropriate number of dimensions, hierarchical clustering considering only the retained dimensions is carried out. Agglomerative hierarchical clustering is an unsupervised machine learning algorithm that groups observations together into clusters based on their similarity along a set of pre-defined features. Observations and groups of observations are sequentially merged until a single group containing all observations is formed. The results can be visualized using a dendrogram, from which the number of clusters may be decided by cutting the dendrogram at the appropriate height considering the structure of the dendrogram. The extracted clusters are then characterized by examining the integration of the SDGs by the companies within each cluster. An example of the application of cluster analysis to studying progress towards the SDGs can be found in Çağlar and Gürler [22], who used the cluster analysis of countries worldwide to categorize them in terms of their progress towards the SDGs, understand the challenges in implementing the SDGs, define the gaps between countries, and identify priority actions.

These analyses were carried out following the guidelines for HCPC developed by Kassambara [23] using the open source statistical analysis software R [24] and the FactoMineR package. In this algorithm, Ward’s criterion is used for clustering because, like MCA, it is based on multidimensional variance.

3.2.3. Quantifying and Comparing Patterns in SDG Integration between Clusters

After extracting the clusters using HCPC and associating each company in the database with their cluster, the cluster integration rate by SDG (IR_clust,sdg) was calculated using Equation (2).

$$I{R}_{clust,sdg}={\displaystyle \frac{n_{clust\_integ,sdg}}{n_{clust\_total}}}\times 100$$

(2)

where n_{clust_integ,sdg} is the number of companies in a cluster integrating an SDG; and n_{clust_total} is the total number of companies in that cluster. The integration rate of the SDGs within a limited number of clusters may characterize the patterns in how the SDGs are being integrated into the corporate governance in Japan and may be simpler to understand and interpret than the trends of 17 individual SDGs.

As the number of companies in each cluster may not be uniform, it was necessary to evaluate the degree to which the companies within an industrial sector were present in each cluster relative to the size of the clusters. This was achieved using the sectoral membership rate by Cluster (MR_sect,clust), which was calculated for each industrial sector and for each cluster per Equation (3).

$$M{R}_{sect,clust}={\displaystyle \frac{n_{sect,clust}}{n_{clust\_total}}}\times 100$$

(3)

where n_sect,clust is the number of companies from a sector in a cluster. The cluster membership rate thus quantifies the degree to which the companies in an industrial sector were integrating the SDGs in the pattern characterized by each cluster relative to that sector’s presence in that cluster.

By comparing the cluster membership rate, which quantifies the degree to which the companies in an industrial sector were integrating the SDGs in the pattern characterized by a cluster relative to that sector’s presence in that cluster, and the sampling rate of each industrial sector within the total dataset (SR_sect; percentages shown in Table 2), it is possible to examine the degree to which each industry is over- or under-represented in each integration pattern of the SDGs. This calculation is formalized in Equation (4) as the sectoral representation ratio by Cluster (RR_sect,clust), and serves as a means of normalizing the integration patterns of the SDGs in each industrial sector by the degree to which companies belonging to each sector are present in the dataset.

$$R{R}_{sect,clust}={\displaystyle \frac{M{R}_{sect,clust}}{S{R}_{sect}}}$$

(4)

An RR_sect,clust value greater than 1.0 indicates that companies in that industrial sector are integrating the SDGs in that cluster’s pattern at a greater rate than that sector’s presence in the dataset (i.e., over-represented), whereas a value less than 1.0 indicates that companies in that sector are integrating the SDGs in that cluster’s pattern at a lesser rate relative to its presence in the dataset (i.e., under-represented). This value can be used to evaluate and compare the degree to which each industrial sector is integrating the SDGs in the patterns characterized by the clusters considering each industrial sectors’ presence in the overall dataset.

4. Results

4.1. Sectoral Integration Rate

Figure 3 and Figure 4 summarize the sectoral integration rate, calculated using Equation (1), for the 17 SDGs across the 33 industries in the form of a heat map. The average number of SDGs integrated in each sector and their standard deviations are also shown in Figure 4. Overall, SDG8, SDG12, and SDG13 were integrated by roughly half the companies in the sample, whereas SDG1 and SDG2 were integrated by fewer than 20% of the companies. On average, the 1630 companies integrated 6.5 SDGs into their governance with a standard deviation of 6.3.

Air transportation had the highest average number of integrated SDGs, at 15.7, with a sectoral integration rate of 100% for 13 out of 17 SDGs. The standard deviation was also the lowest among all sectors, indicating that the three air transportation companies were comparatively uniform in their overall integration of the SDGs. The industrial sectors with the next-highest average number of integrated SDGs were insurance business (12.1), banking (11.5), and the electricity and gas industry (10.6). For insurance business, the sectoral integration rates were fairly consistent across all SDGs, ranging between 57.1% (SDG6) and 78.6% (eight SDGs). For banking, on the other hand, the sectoral integration rates tended to vary more widely, with a low of 42.6% (SDG6) and a high of 80.9% (SDG8, SDG9), and electricity and gas industry varied even more, with a low of 17.6% (SDG2) and a high of 88.2% (three SDGs). However, the standard deviation for the electricity and gas industry was the lowest (5.3) among these three industries, suggesting less variability in the number of SDGs integrated in this industry compared to the other two.

At the other end of the spectrum, metal products, service industry, and warehouse and transportation-related business integrated the SDGs the least, with average values of 3.8, 3.5, and 3.0, respectively. The standard deviations of the number of SDGs integrated in these three sectors were also lower than the overall standard deviation. The highest sectoral integration rates for metal products could be found for SDGs 7 (36.1%), 12 (38.9%), and 13 (36.1%), but the lowest rates were for SDG1 (5.6%) and SDG2 (2.8%). The range of sectoral integration rates for the service industry was narrower, with a high of only 31.7% (SDG8) but a low of 6.8% (SDG2). However, for warehouse- and transportation-related business, there were several sectoral integration rates of zero (SDGs 1, 2, and 6), but the highest rate was 35.3% (SDG7 and SDG8).

Industries integrating around the average number of SDGs (6.5) included glass and clay products (6.9), land transportation (6.9), machine (6.2), petroleum and coal products (6.0), and precision mechanical equipment (6.9). The highest sectoral integration rates for glass and clay products were for SDGs 7, 8, 11, 12, and 13 (all 55.6%). These five SDGs also tended to be among the highest integrated SDGs in the other four sectors as well, although the rates for SDG11 and SDG12 were considerably lower in the petroleum and coal products (33.3%). Precision mechanical equipment had a lower sectoral integration rate for SDG11 as well (39.1%). On the other hand, land transportation (50.0%), petroleum and coal products (50.0%), and precision mechanical equipment (56.5%) had higher rates for SDG5 than glass and clay products (44.4%) and machine (37.1%). The highest sectoral integration rate among all five sectors, however, was for precision mechanical equipment, for which 65.2% of the companies in this sector were integrating SDG3.

4.2. Identification and Characterization of Patterns in SDGs Integration

From the examination of the sectoral integration rates for the 17 SDGs, it is apparent that the number of SDGs integrated, as well as which ones, varied widely both between and within the industrial sectors. It is therefore difficult to understand the underlying trends in the integration of the SDGs. Hierarchical clustering on principle components was thus applied to reduce the noise in the data and identify the patterns present in SDG integration among the industrial sectors in Japan.

4.2.1. Multiple Correspondence Analysis

To obtain clusters on principal components, it is first necessary to conduct MCA as described in Section 3.2.2. MCA was carried out using the statistical analysis software R (version 2024.04.1+748) and the results are shown in Figure 5 as a scree plot. Although the results show seventeen dimensions, the figure only shows results for the first ten because the contribution of the higher dimensions is negligible. More than 60% of the total variance is explained just by the first dimension (Dim1), with the remaining variance explained by the other sixteen dimensions. The difference between the first and second dimensions is 55%, followed by a decrease of only 2.1% between the second and third dimensions.

There is no fixed rule for deciding the number of dimensions to retain for clustering, and the decision is often based on either the eigenvalues of the dimensions or the total variance explained. In this study, it was decided to proceed to clustering using the first three dimensions, which cumulatively explain 73.3% of the overall variance, as it was felt that there was no drawback in increasing the number of dimensions slightly to capture more of the variability in the original dataset.

4.2.2. Hierarchical Clustering on Principal Components

After determining the appropriate number of principal components from MCA, HCPC was carried out using the software R with the retained dimensions as the input data, with the resulting dendrogram shown in Figure 6. In a dendrogram, the heights at which two observations or groups of observations join represent the similarity between the observations or groups of observations, with lower heights indicating greater similarity. After considering the shape of the dendrogram and examining the characteristics of clusters formed by cutting the dendrogram at different heights, it was determined that four clusters provided the best representation of the patterns in the integration of the SDGs. Figure 6 also provides a close-up view that better illustrates the similarities and dissimilarities within and between the four clusters. Clusters 1 and 2 are more similar to each other than Clusters 3 and 4, as Clusters 1 and 2 join together at a lower height than Clusters 3 and 4.

Another output of HCPC analysis was the factor map of the first two dimensions (Figure 7). The plot shows the similarities and dissimilarities between clusters. Clusters 1 and 2 can be clearly distinguished from Clusters 3 and 4 when examined on Dim1. Clusters 1 and 2 overlap slightly on Dim1 as well as Dim2. Conversely, Clusters 3 and 4 are highly overlapping on Dim1, so the differences between these two Clusters may be more attributed to Dim2 and Dim3 (the latter is not shown on the two-dimensional factor map).

4.2.3. Overall Cluster Distribution and Cluster Distribution by Sector

From the identified clusters, the distribution of companies by cluster can be obtained (Figure 8). Cluster 1 was the largest with 732 companies, followed by Cluster 3 with 356 clusters. Clusters 2 and 4 were relatively similar in size, with 276 and 266 companies, respectively.

Figure 9 shows the distributions of clusters within each industrial sector, and distinct tendencies could be observed for many sectors. The industries with a large percentage of companies in Cluster 1 were as follows: warehousing and transportation related business (70.6%), securities and commodity futures trading business (68.8%), service industry (68.3%), real estate business (61.7%), information and communication industry (61.4%), metal products (61.1%), and fisheries, agriculture, and forestry (60.0%). Six other industries also had more than half of their companies in Cluster 1. Clusters 2 and 3 were less strongly represented. Slightly more than half of the companies in the nonferrous metals industry (55.6%) and electricity and gas industry (52.9%) belonged to Clusters 2 and 3, respectively. Strong representation in Cluster 4 was also only found for a few industries: air transportation industry (100%) and insurance business sector (64.3%). On the other hand, there were also many industrial sectors that showed no strong tendency towards any single cluster: chemistry (16.7–32.5%), electrical equipment (17.6–35.1%), groceries (17.5–30.2%), other financial services (16.7–38.9%), pharmaceuticals (20.0–34.3%), precision mechanical equipment (17.4–34.8%), rubber products (16.7–33.3%), and transportation equipment (18.6–33.9%).

4.2.4. Patterns in the Integration of the SDGs Using the Cluster Integration Rate

The clusters are characterized by the cluster integration rate, or the percentage of companies in each cluster that are integrating each SDG, which was calculated using Equation (2). These results are visualized using both a heatmap and a radar chart (Figure 10), and it can be seen that the cluster analysis was able to identify four distinct patterns in SDG integration.

In Cluster 1, the SDGs are integrated at an extremely low rate, with a cluster integration rate equal to or less than 2% for nearly all SDGs. Only SDG 3 is integrated at a rate greater than 2%. Cluster 2 represents progress in the integration of the SDGs when compared with Cluster 1, as the cluster integration rate is higher for all SDGs. The differences between the IR between the clusters were also calculated and are shown on Figure 10. The largest differences between Clusters 1 and 2 can be observed for SDGs 3, 5, 7, 8, 9, 12, and 13, with an increase of more than 50% over Cluster 1, and more than half of the companies in Cluster 2 are integrating these SDGs into their governance. However, the cluster integration rate in Cluster 2 is still quite low for SDGs 1, 2, 6, 10, 14, and 15.

Cluster 3 represents yet further progress in the integration of the SDGs, as the cluster integration rates for all SDGs are higher in Cluster 3 than in Cluster 2, with particularly large improvements of more than +30% for SDGs 4, 5, 6, 7, 10, 11, 14, 15, 16, and 17. Furthermore, while SDGs 3, 5, 7, 8, 9, 11, 12, and 13 are integrated by more than 80% of the companies in Cluster 3, the cluster integration rates for SDGs 1 and 2 remain quite low. The final evolution of the SDGs integration is captured by Cluster 4. Again, the cluster integration rate for all SDGs is higher in Cluster 4 than in Cluster 3, with the largest increases for SDGs 1 and 2 (more than +70%), followed by SDG14 (+38.1%) and SDGs 4, 6, 10, and 15 (more than +20%). Cluster 4 contains the companies that integrate the SDGs the most, as the cluster integration rates are greater than 80% for all SDGs and greater than 90% for 12 of the 17 SDGs.

4.3. Sectoral Membership Rate and Sectoral Representation Rate by Cluster

Figure 11 shows the relationships between the sampling rate and the cluster membership rate for Clusters 1–4. The sampling rate is presented in Table 2 and cluster membership rate was calculated according to Equation (3). Due to the large number of industrial sectors, only the ten largest sectors in the dataset are labeled in these figures. The corresponding sectoral representation ratios were calculated using Equation (4) and the results by cluster for all industrial sectors are summarized in Figure 12.

Among the ten largest sectors, service industry, information and communication industry, wholesale trade, and retail business are all over-represented in Cluster 1, with representation ratios of 1.52, 1.37, 1.20, and 1.24, respectively. These results show that these four industrial sectors are proportionally more present in Cluster 1 than they are in the overall dataset. The two industrial sectors that are the most over-represented in Cluster 1, however, are warehousing- and transportation-related business (RR_sect,cluster = 1.57) and securities and commodity futures trading business (RR_sect,cluster = 1.53). Although the sampling rates of these two industries are only 1.04% and 0.98%, respectively, they represent 1.64% and 1.50% of the companies in Cluster 1, respectively. Other industrial sectors with comparatively higher sectoral representation ratios for Cluster 1 are as follows: real estate business (1.37); metal products (1.36); and fisheries, agriculture, and forestry (1.34). The industrial sectors highly over-represented in Cluster 1 also tend to be highly under-represented in the other clusters. Warehousing- and transportation-related business is fairly equally represented in Cluster 2 (RR_sect,cluster = 1.04), but under-represented in Cluster 3 (RR_sect,cluster = 0.54) and completely absent in Cluster 4. Securities and commodity futures trading business and service industry are both under-represented in Clusters 2, 3, and 4, as are information and communication industry and real estate business. Metal products, on the other hand, are also over-represented in Cluster 2 (RR_sect,cluster = 1.31), but highly under-represented in Clusters 3 and 4. Fisheries, agriculture, and forestry exhibits a different tendency, as it is over-represented in Cluster 4 (RR_sect,cluster = 1.23) in addition to Cluster 1, but slightly under-represented in Cluster 3 and completely absent from Cluster 2. There are also eight industries with representation ratios less than 0.5 in Cluster 1, which means that the degree to which companies in these industries are present in Cluster 1 is less than half their presence in the overall dataset. Air transportation and mining are entirely absent from Cluster 1 (RR_sect,cluster = 0.00), and the electricity and gas industry have the smallest non-zero representation ratio (RR_sect,cluster = 0.26).

In Cluster 2, the over-represented industrial sectors tend to be those with a comparatively small number of companies in the dataset. The largest representation ratios were found for nonferrous metals (n = 18; RR_sect,cluster = 3.28), mining (n = 2; RR_sect,cluster = 2.95), and the shipping industry (n = 5; RR_sect,cluster = 2.36), which are present in Cluster 2 at more than double their presence in the overall dataset. These values are also much larger than the largest representation ratios found for Cluster 1, which indicates that there is a greater tendency for industries to be over-represented in Cluster 2 than in Cluster 1. Cluster 2 is the only cluster for which nonferrous metals are over-represented, but both the mining and shipping industry are also over-represented in Cluster 3 (RR_sect,cluster = 2.29 and 1.83, respectively). Other industries with comparatively larger representation ratios in Cluster 2 include fiber products (RR_sect,cluster = 1.82), precision mechanical equipment (RR_sect,cluster = 1.54), and other products (RR_sect,cluster = 1.48). There are several industrial sectors completely absent from Cluster 2: air transportation; fisheries, agriculture, and forestry; insurance business; and securities and commodity futures trading business. The smallest non-negative representation ratio in Cluster 2 is for banking (RR_sect,cluster = 0.50), followed by the construction industry (RR_sect,cluster = 0.52), and pulp/paper (RR_sect,cluster = 0.54).

Over-representativeness is less pronounced in Cluster 3 compared to Cluster 2, as the largest representation ratio is just 2.42 for electricity and gas industry. This is, however, larger than the largest value observed in Cluster 1. The next most over-represented industrial sectors are mining (RR_sect,cluster = 2.29), which has just two companies in the entire dataset, and construction industry (RR_sect,cluster = 1.97), which is the eighth-largest sector with 79 companies in total. The electricity and gas industry was previously noted as being very under-represented in Cluster 1, but it is roughly equally represented in Clusters 2 and 4. The construction industry, on the other hand, is somewhat under-represented in the other three clusters. Shipping industry, land transportation, and other financial services are also quite over-represented in Cluster 3 (RR_sect,cluster = 1.83, 1.78, and 1.78, respectively). The shipping industry is also one of the most highly over-represented sectors in Cluster 2, whereas land transportation and other financial services are similar to the construction industry in that they are only over-represented in Cluster 3. The only industrial sector not present in Cluster 3 is air transport, giving Cluster 3 the broadest presence across all industrial sectors. Furthermore, fiber products is the only sector with a representation ratio below 0.5 (RR_sect,cluster = 0.35). There are very few sectors positioned close to the line of equality for Cluster 3, however, and thus most sectors are either somewhat over-represented or somewhat under-represented in this cluster.

Finally, Cluster 4 has the two highest representation ratios among the four clusters and 33 industries. Although there are only three air transport companies present in the overall dataset, all three of these companies belong to Cluster 4, leading to a representation ratio of 6.13—that is, air transport is six times more present in Cluster 4 than it is in the overall dataset. Even though there are other industrial sectors with a small number of companies in the dataset, such as mining (n = 2), fisheries, agriculture, and forestry (n = 5), shipping industry (n = 5), and petroleum and coal products (n = 6), none of these exhibit the uniformity of air transport, which is the only industrial sector for which all companies belong to just one cluster. Insurance business and banking, which both have more companies in the dataset than air transport, are also highly over-represented in Cluster 4, with representation ratios of 3.94 and 3.13, respectively. All three of the industries highly over-represented in Cluster 4 are also either under-represented or completely absent from the other three clusters, with the exception of banking, which is equally present in both the overall dataset and Cluster 3. Two of the smallest industrial sectors in the overall dataset, mining and shipping industry, are both absent in Cluster 4, as is warehousing- and transportation-related business, and very low representation ratios can be found for metal products (RR_sect,cluster = 0.34), land transportation (RR_sect,cluster = 0.34), and the service industry (RR_sect,cluster = 0.42).

Finally, correlation analysis was conducted using the results from the clusters to examine the tendencies of over- and under-representation of the industrial sectors among the four clusters. As shown in Figure 13, the representation ratio for Cluster 1 exhibits a weak to moderate negative correlation with the representation ratios of the other clusters. A similar result can be observed for Cluster 4. These results indicate that industrial sectors over- or under-represented in Clusters 1 or 4 have a slight tendency to be under- or over-represented, respectively, in the other clusters. Only a weak positive correlation was found between the representation ratios of Clusters 2 and 3.

5. Discussion

As previously reported in the literature, the SDGs are important global indicators that can be successfully adapted to a corporate context, resulting in positive outcomes for the company and the environment. This study has aimed to provide detailed information on how corporate governance in the private sector is affected by the SDGs (the “external to internal” perspective) through a cross-sectoral study of how companies in Japan are considering the SDGs in their agendas, with a focus on understanding the patterns in the integration of SDGs into corporate governance. The analysis results found that certain SDGs are more focused on than others and revealed different levels of effort to realize the SDGs among private sector companies. The gaps between industries were also clarified. From these results, it is possible to understand how the SDGs are being integrated into corporate governance in Japan and draw conclusions regarding the approach of Japanese companies to the SDGs.

5.1. Identifying Trends in the Integration of Individual SDGs

The first challenge in this study was measuring the integration of the SDGs within the industrial sectors as, considering the large number of companies and the 17 SDGs, the results may be complex and difficult to interpret. To tackle this problem, the sectoral integration rate was introduced, which is simply calculated from the number of companies in a sector referring to an SDG and the total number of companies in that sector. The overall integration rate for all companies in the sample can also be used to establish the baseline for the private sector as of the time of the survey.

It was found that SDG8 (decent work and economic growth, 52.7%), SDG12 (responsible consumption and production, 50.5%), and SDG13 (climate action, 49.9%) were the most integrated SDGs across all companies. The high integration rate for SDG8 indicates that socio-economic factors still play an important role in sustainable corporate governance. In the case of Japan, the particular focus on SDG8 may relate to the decreasing and aging population, which spurs concerns about future economic growth considering the limitations of a shrinking and aging labor force [25,26]. These have been prevalent topics across many different spheres of Japanese society since the turn of the century, thus incentivizing the promotion of this goal. The other two goals, SDGs 12 and 13, were similarly recognized as a priority even before the establishment of the SDGs in 2016, but their comparatively higher integration may be reflective of Japanese policies towards recycling and the recent commitment of the Japanese government to achieve carbon neutrality by 2025 [27,28].

The SDGs with very low overall integration rates also provide insights into the priorities of the Japanese private sector. SDG1 (no poverty) and SDG2 (zero hunger) are the least-integrated goals at 18.9% and 19.1%, respectively. Conversely, low integration rates for SDG1 (no poverty) and SDG2 (zero hunger) reflect the developed status of Japan, where the rates of poverty and hunger are low [29]. Consequently, these are less pressing issues for Japan, so it is expected that corporations would show less interest in integrating these SDGs into their corporate governance agenda. However, these SDGs are not entirely neglected, and are present in some of the integration patterns found in the cluster analysis.

Although some general trends in the priorities of the Japanese private sectors can be observed, the priorities of actions are complex and must be considered in the context of socio-economic trends, regional environment, resource availability, and the commercial product or service of the industry. These factors vary widely between industrial sectors and may have a large influence on how the SDGs are integrated within a specific sector. Although it is clear that Japan is contributing to international efforts to achieve the SDGs and realize a sustainable planet, it will be necessary in the future to investigate in more detail the role of these and other internal factors on the integration of individual SDGs.

5.2. Examining Patterns in the Integration of the SDGs

The large number of SDGs made it difficult to interpret the trends in the integration of the SDGs for any one sector. Therefore, a better quantification and visualization of the complex information on how the SDGs are being integrated was pursued by applying HCPC to identify integration patterns. The cluster integration rates obtained after the cluster analysis could provide easier information to interpret on the integration of SDGs in Japan, and the cluster membership rates and sectoral representation ratios were effective in describing and comparing the tendencies of the industrial sectors.

Four distinct clusters with unique characteristics were identified from the results of HCPC. Clusters 1 and 4 demonstrated the opposite tendencies, with companies belonging to Cluster 1 generally showing almost no integration of the SDGs in their agendas and companies in Cluster 4 generally integrating a large number of the SDGs. The integration rate of all SDGs increased progressively from Cluster 1 through Clusters 2, 3, and 4. This indicates that the Japanese companies, in general, tend to progressively integrate more and more SDGs and that, on the aggregate, there is no regression in the consideration of an SDG.

The largest differences between Cluster 1 and Cluster 2 were for SDGs 8, 12, and 13, which all increased by more than 70%. This demonstrates that these three SDGs are generally the baseline that Japanese private sector companies begin with when beginning to include the SDGs in their agendas. These were also noted as the three SDGs with the highest overall integration rates among the sampled companies. The next largest changes between these two clusters are for SDGs 3 (good health and well-being), 5 (gender equality), 7 (affordable and clean energy), and 9 (industry, innovation, and infrastructure), which all increase by more than 50%. The attention to SDG7 (Affordable and Clean Energy) and SDG9 (Industry, Innovation and Infrastructure) may reflect the Japanese concern with maintaining development progress and modernization of the country. Japan is renowned for its technological advancements and industrial prowess, which aligns with the objectives of SDG9. The country’s focus on clean energy sources and sustainable infrastructure development, as outlined in SDG7, is crucial for its continued economic growth and environmental sustainability [30].

On the other hand, SDG3 (good health and well-being) and SDG5 (gender equality) may reflect current pressing social challenges in Japan, such as the aging population and persistent gender equality issues. With one of the highest life expectancies globally, Japan faces the challenge of providing quality healthcare and support services for its rapidly aging population, which is addressed by SDG3 [28]. Additionally, despite being an economically advanced nation, Japan still grapples with gender disparities in various areas, including the workforce and leadership positions, making SDG5 a priority.

From Cluster 2 to Cluster 3, the largest increases were found for SDGs 10 (reduce inequality within and among countries), 15 (life on land), and 17 (partnerships for the goals), which increased by more than 40%. The progress of these SDGs between these two clusters, rather than between Clusters 1 and 2, show that these SDGs are of lower priority for corporate governance in Japan compared to the previously mentioned SDGs with the largest rates of change between Clusters 1 and 2.

The largest changes from Cluster 3 to Cluster 4 were found for SDGs 1 and 2, which increased by more than 70%. These two SDGs were integrated the least in the overall dataset, and their integration rate was consistently low across Clusters 1, 2, and 3. However, Cluster 4 consists of the companies integrating the SDGs at the highest rate. As discussed previously, the issues related to SDGs 1 and 2 (no poverty and zero hunger, respectively) may not be considered very critical for Japanese society, and thus these may not be considered a priority for most Japanese companies. However, the effort to integrate all SDGs—even those less critical in the Japanese context—could be considered a distinguishing factor for the companies belonging to Cluster 4.

5.3. Examining Cross-Sectoral Differences and Similarities

Another complexity of this study involved how to evaluate, visualize, compare, and interpret the differences and similarities in the integration of the SDGs between industrial sectors in Japan. This was made easier by the identification of the four patterns in the SDGs integration, which were then normalized to account for the presence of each industrial sector in the database using the sectoral representation ratio.

Some industries were found to have a particularly strong tendency to belong to one cluster, the most prominent example being air transport, the only industry for which all companies belonged to just one cluster (Cluster 4). While the number of companies is small, the uniformity in this industrial sector suggests that air transport companies are adopting a similar approach to the integration of the SDGs, regardless of differences between companies, possibly due to industry-specific regulations and international standards that drive higher sustainability practices [28]. It may be that this level of achievement—as Cluster 4 represented the highest level of SDGs integration—is a characteristic of this industry. While not nearly as uniform as air transport, insurance business was also found to be highly over-represented in Cluster 4. This result also suggests that most insurance business companies are adopting a similar, proactive approach to the integration of the SDGs into their corporate governance in Japan, reflecting an industry-wide trend towards risk management and sustainability [31].

At the opposite end of the integration spectrum, there were several industries with high over-representation in Cluster 1, such as warehousing- and transportation-related business, securities and commodity futures trading business, and service industry. A majority of companies in all three industrial sectors belonged to the cluster representing the lowest integration rate of the SDGs, suggesting that are these are the Japanese industries lagging the furthest behind in considering global sustainable development in their corporate governance, and that companies in these industries tend to follow this trend regardless of the individual company characteristics. These sectors may face unique challenges, such as market constraints or less pressure from international standards, leading to the slower adoption of sustainable practices [32]. The challenges for these sectors may be complex and depend on their services or products, as well as whether their market and operations are more domestic or international.

In contrast to Clusters 1 and 4, which represent the two most extreme patterns of the integration of SDGs, there were a few examples of industrial sectors with a strong tendency towards one of the intermediate clusters. A majority of nonferrous metal companies belonged to Cluster 2, and a majority of electricity and gas industry companies belonged to Cluster 3. Mining was split evenly between Clusters 2 and 3, although there were only two mining companies in the dataset. This transitional nature highlights the ongoing efforts within these sectors to balance the operational changes with sustainability goals [33]. These industries may be in a general state of transition in the consideration of the SDGs in their corporate governance, as there were relatively few companies at the lowest integration rate (Cluster 1), but also relatively few companies exhibiting the highest integration rate (Cluster 4).

Ultimately, it was found that many industrial sectors did not show an overly strong orientation towards any single cluster or integration level of the SDGs. Chemistry, electrical equipment, groceries, other financial services, pharmaceuticals, precision mechanical equipment, rubber product, and transportation equipment are the examples of sectors that exhibited neither very high nor very low percentages for all four clusters. In contrast to those sectors with a strong tendency towards one of the four patterns, the lack of variability within these industrial sectors suggests that the integration of the SDGs in these sectors is highly influenced by the individual companies, rather than the characteristics of the industrial sectors themselves. As this study was focused on the overall trends and patterns in the integration of the SDGs, as well as the similarities and differences between industrial sectors, other factors such as company size, financial performance, governance state, and so forth were not considered in this analysis. This variability points to the significant role of company-specific factors in determining SDG adoption [34]. However, it is evident that these factors may play a significant role for some industrial sectors.

6. Limitations and Future Work

This study has adopted a rational, quantitative, data-driven approach to the study of the integration of the SDGs into the corporate governance of Japanese companies. However, the presented results should be interpreted in the context of several limitations, which are recommended to be considered in future work.

First, it is noted that this analysis was carried out using cross-sectional data only representing the situation in 2021, and therefore the obtained results, including the integration patterns of the SDGs, are only valid for this point in time. It is reasonable to assume that, with the passage of time, the integration rates of the SDGs will increase as more companies shift their corporate governance to a more sustainable model. Indeed, the four integration patterns suggest such a trend. However, it will be necessary to carry out HCPC using data from prior and successive years to clarify whether these patterns are consistent or only present in 2021.

Another limitation is with regard to the survey question used for this analysis. As explained previously, the question asked companies whether they are referencing or considering the SDGs in their governance, but no details are provided as to the ways in which the SDGs are being referenced or considered. As a result of this yes/no question format, the responses were simply encoded using a dummy variable to indicate whether companies responded positively or negatively regarding the integration of each SDG. Therefore, as the details of how the SDGs are being referenced or considered are unclear, only general conclusions about the integration of SDGs can be drawn from this analysis. Although the study presented here has clarified which SDGs are being integrated by the private sector in Japan, future studies should consider a more detailed survey instrument to better understand how SDGs are affecting corporate governance.

Finally, the analysis and results in this study only examined the similarities and differences in the integration of the SDGs between industrial sectors, and the effects of covariates such as company size, revenue, and other such characteristics were not considered. This was justified by the need to first understand the state of the integration of SDGs in Japanese companies. However, past research has shown that approaches to corporate governance may be affected by a variety of company characteristics [35,36], and it is reasonable to hypothesize that the integration of SDGs may be similarly affected. For example, companies operating internationally may face greater pressure to reflect the SDGs in their corporate governance; similarly, companies demonstrating greater environmental awareness by adopting policies and measures to reduce their environmental impacts may also be more proactive in considering the SDGs. Therefore, the effects of factors such as company characteristics and the state of corporate governance on the integration of the SDGs should be explored in greater detail in future work.

7. Conclusions

The degree to which the SDGs are considered or referred to in the governance of the private sector may serve as a reflection of the importance of addressing social environmental challenges and advancing the sustainable development agenda as perceived by society. There is a need to investigate how companies are including the SDGs in their actions and policies due to the scarcity of literature. Using data from a survey on CSR practices in the Japanese private sector, this study proposed various metrics and conducted various analyses to facilitate an understanding of the current approach to the SDGs in corporate governance in Japan.

The sectoral integration rate, while simple to calculate, provided fundamental information on the achievement level of the 33 industrial sectors for all 17 SDGs, and highlighted gaps and priority areas for the Japanese private sector. Applying HCPC, however, created a clear picture of four different levels at which the SDGs were being integrated, from almost no integration at all to the nearly full integration of all 17 SDGs, with two transitionary levels in between, and comparing the cluster integration rate between the four clusters showed which SDGs distinguished each pattern of integration.

Overall, the largest number of companies belonged to the cluster with the lowest level of integration, which suggests that much of the private sector has yet to consider the SDGs as an important aspect of their corporate governance. By examining the company distribution by cluster within each industrial sector, as well as calculating the sectoral representation rate to account for differences in sector and cluster sizes, it was shown that some industrial sectors exhibit clear tendencies in their integration of the SDGs, whether it be the lowest level of integration, the highest level, or somewhere in between. It was posited that there may be a relationship between the characteristics of an industrial sector and the integration of the SDGs for sectors with a strong tendency to belong to a single cluster, as less variability was observed between companies. However, a fair number of industrial sectors did not exhibit a strong tendency to belong to any one cluster, with their companies distributed across all four integration patterns. For these sectors, the influence of individual company characteristics may play a stronger role than the characteristics of the industrial sector itself. These outcomes suggest the future paths of research that could lead to a better understanding of how the SDGs are being adopted by the private sector.

The interpretation of these results is ultimately limited to the context of Japanese companies included in the database used by this study. Although Japan has a comparatively high level of achievement for SDGs, this has not translated into action in the private sector, even six years after the SDGs came into effect, signaling difficulty in the diffusion of this international initiative for domestic industry. As the goals established by the SDGs may only be realized through commitment and action by both the public and private sectors, more work is necessary to identify the barriers to the SDGs in the private sector and how to overcome them.

Ultimately, integrating the Sustainable Development Goals (SDGs) into business strategies presents numerous advantages for private sector companies in Japan. Firstly, it enhances corporate reputation and brand value by showcasing a commitment to global sustainability and social responsibility, attracting consumers and investors who prioritize ethical practices. Additionally, operational efficiency and cost savings can be achieved through sustainable practices like energy efficiency and waste reduction, leading to improved business performance. Aligning with SDGs also aids in regulatory compliance and risk management, helping companies stay ahead of policy changes. Furthermore, it fosters innovation by encouraging the development of new products and services that address global challenges, opening new market opportunities. This alignment can also boost employee engagement and attract talent, as individuals increasingly seek employers with positive societal impacts. Engaging in SDG initiatives builds stakeholder trust and facilitates collaboration, enhancing community relations and business outcomes. Ultimately, focusing on SDGs ensures long-term business sustainability and growth, aligning practices with global efforts to create a more equitable and sustainable world [37,38].