The Role of Institutional and Geographic Proximity in Enhancing Creating Shared Value (CSV) Initiatives Within Local Industrial Clusters: A Study of Japanese SMEs

Abstract

Creating Shared Value (CSV), a contemporary management strategy aimed at generating both economic and social value, has gained increasing attention in the context of sustainable regional development. This study examines the implementation of CSV within local industrial clusters, specifically investigating the influence of institutional and geographic proximity on the sustainability of small and medium-sized enterprises (SMEs). Utilizing surveys conducted across 11 industrial clusters in Japan and employing structural equation modeling, the impact of proximity on CSV initiatives was explored. The findings reveal that firms within these clusters enhance their sustainability by fostering iterative knowledge transfer and technological collaboration, particularly with geographically and institutionally proximate organizations. Moreover, the study highlights that a clear understanding and alignment of sustainability-oriented goals within institutional proximity strengthen the synergy of management resources through alliance capabilities, ultimately leading to the simultaneous creation of social and economic value. This research underscores the critical role of proximity in shaping effective and sustainable CSV initiatives within local industrial clusters, providing valuable insights for policymakers, industry stakeholders, and researchers aiming to promote regional sustainability and resilience.

1. Introduction

Over the past few decades, corporate social responsibility (CSR) has evolved significantly, adapting to increasing societal demands and sustainability pressures from investors. What began as socially responsible investment (SRI) in the 1920s has transformed into a widely accepted concept across various industries. Early research on CSR primarily focused on corporate ethics and compliance, emphasizing explicit norms and ethical considerations. However, recent studies have shifted towards managerial perspectives, exploring the impact of CSR initiatives on business performance and long-term sustainability [1,2].

Traditionally, CSR has been perceived as a cost incurred by companies, often viewed as a separate function from core business operations and primarily centered on reputation management. Although CSR initiatives aim to contribute to society, they are sometimes criticized for lacking a direct connection to business sustainability. In response to these limitations, a more strategic approach has emerged: Creating Shared Value (CSV) [3]. CSV posits that businesses can enhance their competitiveness while contributing to sustainable development by addressing societal challenges in ways that generate both economic and social value. Porter and Kramer [4] proposed three key strategies for achieving CSV: (1) rethinking products and markets, (2) redefining productivity in the value chain, and (3) building clusters in local communities. These strategies are interrelated and reinforce each other, promoting sustainable business growth while improving community well-being [5,6].

Understanding the distinction between CSR and CSV is essential for grasping the evolution of corporate sustainability strategies. While CSR focuses on redistributing already-created value and “giving back” to society, CSV integrates social and economic objectives directly into the business model to create new value, ensuring long-term sustainability [7]. However, CSV has also faced criticism. Scholars have argued that CSV often idealizes the balance between social and economic goals, occasionally overlooking issues related to corporate compliance and governance, raising concerns about its practical implementation and long-term viability [8].

In addition to CSV, the concept of proximity—particularly organizational, geographic, and institutional proximity—plays a vital role in fostering shared value creation and sustainability [9]. Organizational proximity refers to the closeness of relationships between firms, which facilitates collaboration, knowledge exchange, and innovation—key drivers of sustainable business practices [10,11,12]. Moreover, geographic proximity, which reflects physical closeness, and institutional proximity, involving shared formal and informal rules, norms, and support systems, have long been recognized as critical factors in enabling regional economic development through agglomeration and clustering effects [13,14,15,16]. A vast body of literature in regional science and urban economics has emphasized how these proximities contribute to industrial competitiveness and innovation [17,18,19,20,21,22,23,24], yet CSV research has rarely integrated these insights. As a result, proximity dynamics remain underexplored in CSV studies, particularly concerning small and medium-sized enterprises (SMEs) embedded within regional industrial clusters.

This issue is especially relevant in Japan, where SMEs represent 99.7% of all businesses and play a pivotal role in supporting local economies [14]. Historically, the Japanese government has approached SME development through four key phases: addressing systemic unfairness in production during the post-war period, tackling the dual structure problem between large corporations and SMEs, improving business entry and exit rates in response to the 1990s economic recession, and supporting SMEs in adapting to globalization and sustainable development challenges [14]. These policy shifts have fostered industrial networks where proximity among SMEs can be leveraged to promote shared value creation.

Despite the strategic importance of CSV and proximity in fostering sustainable regional development, previous research has predominantly focused on large corporations, leaving a gap in understanding how SMEs can engage in CSV by utilizing proximity-based advantages. Moreover, this gap is closely tied to the United Nations Sustainable Development Goal (SDG) 9, which emphasizes the importance of building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation. In this context, understanding how proximity facilitates CSV among SMEs contributes directly to advancing SDG 9, while also supporting SDG 11 (Sustainable Cities and Communities) by strengthening local economies.

To address this gap, this study explores the relationship between proximity and CSV among SMEs in Japan, particularly from a sustainability perspective. Specifically, it aims to answer the following research questions:

RQ1: How does organizational proximity influence the ability of SMEs to engage in Creating Shared Value (CSV) within regional clusters in a sustainable manner?

RQ2: To what extent do geographic and institutional proximities contribute to the sustainability and success of CSV initiatives in Japanese SMEs?

The purpose of this study is to clarify the mechanisms through which various forms of proximity influence the sustainability and success of CSV initiatives among SMEs in regional clusters. Specifically, this research examines how organizational proximity, defined as the degree of similarity in knowledge bases, shared norms, and collaborative capabilities among firms, enhances SMEs’ ability to engage in sustainable CSV practices within local industrial networks. Furthermore, it seeks to analyze the extent to which geographic proximity (physical closeness and ease of interaction) and institutional proximity (similarity in rules, regulations, and support systems) contribute to reinforcing sustainable partnerships and improving the performance of CSV initiatives in the context of Japanese SMEs.

Through this investigation, the study provides empirical evidence on how different dimensions of proximity function as critical drivers for fostering sustainable value creation that benefits both businesses and local communities. Ultimately, the findings aim to offer insights for theory development and practical policy implementation in regional economic development, with direct relevance to achieving global sustainability goals.

2. Literature Review and Hypotheses

The interplay between various forms of proximity—geographic, informal institutional, and organizational—plays a significant role in shaping firms’ capabilities and their ability to create shared value. This study focuses specifically on Japanese small and medium-sized enterprises (SMEs) operating within regional clusters, examining how proximity influences their Creating Shared Value (CSV) initiatives in a localized context. Understanding these relationships is vital for analyzing how SMEs in Japan leverage proximity to foster collaboration and achieve strategic objectives. This section outlines the theoretical foundations supporting our hypotheses and highlights relevant literature.

This study draws on stakeholder theory, the resource-based view (RBV), and network theory to explain how organizational and geographic proximity influence shared value creation and firm competitiveness. To provide a more integrated framework, these theories are explicitly connected to CSV as a lens to understand how proximity factors contribute to business sustainability and long-term success.

Stakeholder theory posits that organizations operate within a network of relationships with various stakeholders, where the quality of these relationships directly impacts a firm’s performance and sustainability [25]. This perspective underscores the importance of proximity in fostering trust and collaboration among stakeholders, which is essential for creating shared value through effective stakeholder engagement and cooperation.

The resource-based view (RBV) emphasizes that firms can achieve competitive advantages by leveraging unique resources and capabilities developed through interactions with stakeholders [26]. When connected to CSV, RBV suggests that firms can unlock new sources of value by aligning their resource development with societal needs. Proximity enhances these interactions, enabling firms to access and share valuable resources, knowledge, and innovations, contributing to both business competitiveness and social impact.

Network theory complements these perspectives by focusing on the dynamics of inter-organizational relationships [27,28]. It posits that geographic and organizational proximity facilitates the formation of dense networks, enhancing collaboration and resource exchange among firms. Close proximity encourages frequent interactions and stronger ties, which can lead to better access to critical information, collaborative opportunities, and innovations—key components of CSV. In the context of CSV, proximity allows firms to foster local clusters that support sustainable growth and shared prosperity.

By integrating these theories within the CSV framework, we establish a stronger rationale for the relationships hypothesized in this study, linking the research objectives with established theoretical concepts (Figure 1). This integrated framework enables a deeper exploration of how proximity influences not only business competitiveness but also the social value created through CSV initiatives. It allows us to examine how firms can simultaneously enhance their competitive position and contribute to the well-being of local communities, thereby achieving long-term sustainability.

2.1. Relationship Between Geographic/Informal Institutional Proximity and Organizational Proximity

In recent years, the concept of proximity has been analyzed from various perspectives, including geographical, cognitive, organizational, social, and institutional (Boschma, 2005) [29]. This comprehensive approach has enhanced our understanding of how different types of proximity influence inter-organizational relationships and performance outcomes. The literature on geographic and institutional proximity is vast, with significant contributions from regional science and urban economics that highlight the nuanced ways in which proximity shapes collaboration and innovation [17,18,19,20,21,22,23,24]. These fields have developed sophisticated frameworks explaining how the co-location of firms, shared social norms, and institutional contexts promote knowledge diffusion, innovation, and regional development. Acknowledging this extensive body of work provides a more robust theoretical foundation for understanding the mechanisms by which proximity affects SMEs.

Geographic proximity has long been linked to economic efficiency and knowledge acquisition, dating back to Marshall’s (1920) insights on the benefits of close physical proximity for firms [30]. Research shows that geographic proximity facilitates knowledge transfer; for example, Knoben (2009) found that shorter distances enhance tacit knowledge exchange, which is vital for innovation [31]. Seo and Sonn (2019) also demonstrated that geographic proximity leads to knowledge spillovers, benefiting nearby organizations [32]. Supporting this, Barakat et al. (2023) concluded that geographic proximity fosters trust and information sharing, offering competitive advantages to firms [33]. Additionally, recent reviews in regional science emphasize that geographic proximity alone is insufficient for sustained collaboration and innovation; instead, it interacts with other forms of proximity, such as cognitive and institutional proximity, to create a conducive environment for regional growth [34].

This body of work is part of a larger discourse within regional science, which examines how geographical clusters and the concentration of firms in specific regions foster economic development and innovation [20,23]. Notably, Torre and Rallet (2005) argue that while geographic proximity facilitates interactions, organizational and institutional proximities are crucial for maintaining long-term cooperative relationships, particularly in the context of global value chains and knowledge-intensive industries [35].

For SMEs, geographically close businesses can also learn from one another more effectively due to reduced barriers, making information a valuable resource [36,37]. Such proximity is especially beneficial during the early stages of collaborative projects, as it minimizes misunderstandings through shared foundational knowledge [38]. In Japan, Fukugawa (2013) highlighted that firms with local ties are more likely to gain valuable knowledge through joint research with universities, emphasizing the significance of geographic proximity [39]. Additionally, in our previous research, it was found that these share goals and commitment could enhance CSV activities [13].

Geographic proximity often acts as a precondition for developing organizational proximity, which refers to the extent to which organizations share similar structures, cultures, and processes, which can facilitate smoother interactions and collaboration. Frequent face-to-face interactions made possible by physical proximity allow organizations to align their structures, cultures, and processes, fostering mutual understanding and shared practices [29]. Lavoratori et al. (2005) further notes that temporary geographical proximity, such as periodic meetings or joint events, can substitute for permanent co-location in facilitating organizational learning and trust building [40].

To implement the concept of “informal institutional proximity,” it is necessary to rigorously define it as the shared cultural practices and values that influence collaboration. Similarly, “alliance capability” should be defined in terms of the specific skills and resources organizations possess to effectively engage in and manage alliances. A validated approach to these constructions will enhance the clarity and rigor of the research framework and its implications for SMEs.

Therefore, we propose the following Hypothesis 1. This hypothesis suggests that reducing geographic distance between organizations will lead to greater alignment in their structures, cultures, and processes, thereby enhancing their ability to collaborate effectively.

H1: 

Geographic proximity positively affects organizational proximity.

Among proximities, institutional proximity is often studied for its potential impact on inter-organizational relationships. Institutional proximity, defined by cultural practices and common language, affects the stability and flexibility of inter-organizational innovation [29]. This indicates that the consistency of values and commonly accepted perceptions within organizations can serve as guidelines for achieving collaborative results. In particular, informal institutional proximity has been suggested as essential for building trust between organizations due to the sharing of cultural norms and values [41]. Furthermore, organizations that have established trust through informal institutional proximity are likely to have a shared culture, reducing discrepancies in perception and facilitating smoother cooperative relationships.

A study examining the relationship between institutional proximity and firm productivity in Irish multinational companies shows that organizations characterized by institutional proximity enable effective interactive learning and the sharing of knowledge and goals [42]. This highlights that a common language and cultural understanding has lower communication barriers, enhancing the learning effects through exchanges. Additionally, research exploring the proximity between universities and industry suggests that higher levels of organizational and institutional proximity increase the likelihood of successful collaboration [43]. It also demonstrated a significant relationship between institutional proximity and organizational and cognitive proximity [15]. Collectively, these findings indicate that institutional proximity is intricately related to organizational proximity.

Institutional proximity encompasses both formal and informal aspects. Formal institutional proximity refers to the legal frameworks of a given country, while informal institutional proximity pertains to the cultural practices within firms [29]. In this study, cultural tendencies are considered a key aspect of cultural practices, and informal institutional proximity is defined as the degree of cultural similarity between firms within a cluster and their potential partners in the same cluster. Formal institutional proximity is not included in this study since all firms are located in Japan. It is essential to recognize that institutional proximity is asymmetric; companies that are more willing to learn from others tend to absorb more knowledge. Therefore, a comprehensive analysis of institutional proximity should incorporate elements of the cultural tendencies of the companies involved [44].

Based on the above, we define institutional proximity as the degree of congruence between the culture and values of an organization and those within its cluster, and we propose the following hypothesis:

H2: 

Informal institutional proximity positively affects organizational proximity.

2.2. Creating Economic and Social Value Through Alliance Capability

The concept of “alliance capability” refers to the ability to effectively implement and develop alliances, with clear, common goals being essential for enhancing this capability. Several studies have suggested that organizational proximity significantly impacts the alliance capability of companies and organizations within the same local industry cluster [45,46]. This indicates that setting common goals within an organization is a key factor contributing to the success of an alliance.

Organizational proximity, which encompasses shared structures, cultures, and processes, is critical for the formation and success of alliances [47]. Chauhan et al. (2022) highlights that the alignment of goals and policies among partners significantly influences their collaborative activities [48]. When partners work towards common objectives, this alignment facilitates smoother cooperation and enhances overall outcomes. A clear and shared purpose fosters mutual trust among partners, creating a sense of community that eases the achievement of desired results. Moreover, effective collaboration in this context enables the development of innovative strategies and practices that contribute to broader goals, such as sustainable development, thereby enhancing the alliance’s overall impact.

Several studies further emphasize the importance of shared strategic goals for successful alliances. Research indicates that alliances formed around common strategic objectives are more likely to succeed [46,49]. Shared goals provide a clear direction and purpose, which helps coordinate efforts and resources among partners. For instance, research suggests that learning across various dimensions—such as environment, task, process, skills, and goals—within strategic alliances mediates the relationship between initial conditions and outcomes [49]. Successful alliance projects tend to be highly evolutionary, undergoing cycles of learning and adjustment, while failing projects often exhibit inertia and minimal learning [50]. The strategic alliance is identified as a critical cooperative strategy where firms collaborate, share resources, and aim for synergy, thereby hoping that the alliance yields greater benefits than individual efforts [51]. Conversely, if the objectives of an alliance are not clear, there is a risk that resources will not be optimized, potentially leading to alliance failure.

Additionally, Khalid and Larimo (2012) suggest that a shared vision is crucial for alliance development [52]. A common vision helps sustain and strengthen relational capital, making it easier for companies to leverage their resources effectively [53]. This relational capital, built on trust and mutual understanding, is vital for the continuous development and success of alliances. These insights suggest that establishing a clear vision not only fosters relational capital but also enhances the agility and adaptability of organizations, thereby preventing opportunism between them. In conclusion, clearly establishing a vision reinforces alliance objectives and contributes to the overall effectiveness of collaborative efforts.

The insights from these studies underscore the importance of organizational proximity in enhancing alliance capability. When organizations within a cluster share similar structures, cultures, and processes, they are better positioned to form effective alliances. This shared organizational framework facilitates more efficient communication, trust-building, and coordination, all of which are essential for developing strong alliances.

By fostering a common vision and aligning goals, organizations can enhance their ability to collaborate, share resources, and achieve mutual objectives. This alignment not only improves the immediate effectiveness of alliances but also contributes to their long-term sustainability and success.

Based on these findings, we define “alliance capability” as the activity and diversity within a cluster, reflecting the ability of organizations to form and maintain effective alliances. Given the critical role of organizational proximity in facilitating these capabilities, we propose the following hypothesis:

H3: 

Organizational proximity positively affects alliance capability.

This hypothesis posits that organizations closer in terms of their structures, cultures, and processes will exhibit a higher capability to form and sustain successful alliances. Organizational proximity creates the necessary conditions for effective collaboration, thereby enhancing the overall alliance capability of organizations within a cluster.

Alliance capability, defined as the ability to effectively implement and develop alliances, has been shown to generate both economic and social value. Numerous studies have demonstrated that active engagement among partners within alliances enhances partnerships and increases economic value [54]. Strengthening these partnerships leads to increased productivity and commitment among the partners involved. Moreover, this engagement facilitates inter-organizational knowledge sharing, which fosters sustained relational capital and strategic investment in complementary resources, ultimately enhancing performance [55].

Research focusing on small and medium-sized enterprises (SMEs) in the Vietnamese tourism industry has also shown a positive relationship between alliance capability and inter-organizational performance [56,57]. This relationship indicates that when partners are dedicated to the alliance’s goals, cooperation and outcomes improve. Furthermore, Huang (2023) proposed that firms can enhance their innovation performance by acquiring new knowledge through learning, thus improving competitiveness [58]. Continuous learning and knowledge acquisition enable firms to remain competitive and adapt to changing market conditions.

Through this process, we posit that alliance capability can lead to economic value creation by concentrating on the aggregation of knowledge and innovation within alliances. These alliances enhance competitiveness and performance by promoting learning effects among organizations. For instance, Brunner et al. (2024) demonstrated that strong learning effects in research and development of joint ventures generate economic value [59]. In other words, the establishment of joint ventures and each company’s commitment to their operations results in the acquisition of valuable organizational learning and competitive advantages that are otherwise unattainable. Jiang et al. (2022) further identified alliance capability as a critical factor enhancing learning effects, reporting a positive impact on innovation performance [60].

Moreover, rather than solely focusing on the immediate success of the alliance, it is crucial to seek long-term and stable partnership opportunities. Managing alliances with a balance between short-term and long-term interests is suggested to lead to better economic performance. Studies indicate that adjusting an alliance’s portfolio to access diverse resources positively impacts performance by increasing revenues and reducing costs [61]. This strategic adjustment allows participating companies to share resources, compensating for any deficiencies and optimizing outcomes.

Furthermore, it was proposed that companies in alliances may gain new market share, particularly those that are active participants in these collaborative efforts [62]. These companies often experience significant benefits, especially in small firms operating within unstable market environments.

Collectively, these findings illustrate that alliances facilitate high learning effects and knowledge transfer, which become critical sources of competitiveness and improved business performance. By enabling organizations to share knowledge, resources, and best practices, alliances contribute significantly to economic value creation.

Based on the reviewed literature, it is essential to rigorously define constructs such as “alliance capability” and explore the validation processes surrounding them, ensuring a robust theoretical foundation for their application in future research.

H4: 

Alliance capability positively affects creating economic value.

This hypothesis posits that organizations with strong alliance capabilities will experience enhanced corporate performance, leading to increased economic value. This relationship underscores the importance of fostering alliance capabilities to achieve sustainable competitive advantage and improved business outcomes.

The concept of generating social value through corporate alliances is gaining increasing attention, highlighting the dual goals of achieving both economic and social value. Companies can simultaneously enhance economic and social conditions in the communities where they operate by leveraging their relationships with various organizations [4]. This dual value creation is significantly influenced by the diversity and activism among companies, which drives social innovation and produces social value [41]. In this regard, the combination of resources among companies participating in the alliance is thought to lead to a more efficient creation of social value alongside economic value.

Studies on shared value creation in Base of the Pyramid (BoP) businesses have demonstrated that strengthening alliances and networks enhances social capital, which in turn promotes social value creation [63]. Social capital facilitates the sharing of knowledge and new technologies—strategic resources that are crucial for societal benefits [64].

Moreover, effective coordination and the establishment of robust communication channels within the alliance are foundational for innovation that leads to social value creation. de Koning and van der Bijl-Brouwer (2024) emphasized the importance of deepening dialogue with stakeholders, as it lays the groundwork for social innovation [65]. These communication channels enable the sharing of goals and processes, fostering the creation of social value.

It is also crucial to recognize that discussions around social value are often less clearly defined than those around economic value. Therefore, establishing unique indicators that incorporate the company’s own values and objectives is vital. Previous research has demonstrated that collaboration and coordination within alliances—based on shared goals and proactive alliance management—lead to the creation of both economic and social value [13].

Moreover, alliances have proven particularly effective in environmental governance, where they help improve social performance by reducing environmental impacts, such as in wastewater and waste management [66]. Establishing collaborative environmental governance within the alliance and encouraging mutual compliance with these standards can lead to a positive cycle of environmental measures.

Furthermore, it highlighted the importance of collaborative partnerships between buyers and suppliers in enhancing sustainable value along the value chain [49]. These partnerships are essential for improving the social impact of corporate activities, as they promote sustainable practices and enhance overall social conditions within the supply chain. Thus, organizations involved in alliances and partnerships must demonstrate sufficient commitment to one another to maximize these benefits.

Based on the reviewed literature, it is evident that alliance capability is crucial for creating social values. Alliances enable organizations to collaborate effectively, share resources, and innovate, all of which contribute to a positive social impact. By fostering strong relationships and communication channels, companies can leverage their alliances to enhance social conditions and drive social innovation. Therefore, we propose the following hypothesis:

H5: 

Alliance capability positively affects creating social value.

This hypothesis posits that organizations with strong alliance capabilities will experience enhanced social impact, leading to increased social value. This relationship underscores the importance of fostering alliance capabilities to achieve sustainable social outcomes and improve the overall well-being of the communities in which they operate.

3. Materials and Methods

3.1. Survey

This study has conducted a thorough literature review, then developed hypotheses, surveyed and validated them using questionnaires, and verified the hypotheses based on the data obtained. Initially, this study conducts a theoretical literature review on proximity and its relationships, which have been investigated by various researchers, and then constructs a hypothesis after setting indicators on their potential to lead to alliance activities and to create value.

The research employed the cluster sampling method [67] and collected data from firms belonging to 11 industrial clusters across Japan. The selection of these 11 clusters was strategically designed to ensure a representative sample of Japan’s industrial landscape by incorporating both regional diversity and sectoral significance. The selection of these 11 clusters was based on the need to capture the economic and industrial diversity of Japan’s SME landscape, ensuring the sample reflects the variety of industries and regions present in the country.

Clusters were chosen from different regions (prefectures) to reflect geographical diversity, from northern areas like Hokkaido to southern regions like Wakayama and Kobe. This geographic diversity was intended to avoid regional bias and to include a broad spectrum of local economies, which are critical to understanding the variation in CSV activities across Japan’s different regions. This range captures the unique economic activities and industrial strengths of various parts of Japan, ensuring that the sample does not skew towards any region or industry.

In terms of sectoral diversity, the selected clusters represent key industries critical to Japan’s economy. For instance, the Hokkaido Information System Industry Association (Hokkaido) reflects the information technology sector, while the Tohoku Genki Monozukuri cluster covers six prefectures (Aomori, Iwate, Miyagi, Akita, Yamagata, Fukushima) and spans diverse manufacturing industries. The sectoral mix was intentionally selected to represent a variety of traditional and emerging sectors in Japan, including manufacturing, food, aerospace, information technology, and medical devices. Clusters such as the Minami Iwate Food Industrial Cluster (Iwate) and Yamagata Food Industry Cluster (Yamagata) represent the food industry, while the Ibaraki Information Service Industry Association (Ibaraki) and Niigata Sky Component Association (Niigata) contribute to the information service and aerospace sectors, respectively. Furthermore, specialized clusters like the Shizuoka Parts Medical Cluster (Shizuoka) and the Kobe Biomedical Innovation Cluster (Kobe) emphasize medical device manufacturing and biomedical advancements.

This strategic selection ensures a comprehensive representation of both regional and industrial diversity in Japan, allowing the study to explore the factors influencing CSV activities in SMEs across varied sectors and regions. By including both well-established sectors and emerging industries, the study captures a broad perspective on the different challenges and opportunities related to CSV activities across Japan’s diverse SME ecosystem.

The variables measured were evaluated after being adjusted according to a Likert scale [68] so that a score could be assigned on a scale of 1 to 5 for each question. The questionnaire consisted of 6 latent variables and 17 measured variables in this study (Appendix A). The study conducted a questionnaire survey of the target companies between 27 July and 14 October 2022, using an enquiry form and an email. This information was derived from the website information of each of the companies surveyed. Through this process, 889 questionnaires were sent out and 86 pieces of data were obtained, both in terms of the number of responses and valid responses (9.67% valid response rate). In addition, a description of each latent variable and item is provided below.

3.1.1. Informal Institutional Proximity

This construction is based on the frameworks of Ishida (2020) and Boschma (2005) [29,69], focusing on the degree of similarity in corporate practices and culture within the cluster. To quantify informal institutional proximity, the following items were developed:

Degree of agreement on stability and upward orientation. Measured on a scale of 1 to 5, where 1 indicates strong disagreement and 5 indicates strong agreement among organizations regarding stability and upward growth goals.

Degree of agreement on individual and group orientation. Participants rated their alignment on a scale from 1 to 5 regarding the emphasis on individual versus group efforts within their organizations.

Degree of agreement on result/process orientation. This item assesses the consensus among cluster members about the importance placed on results versus processes, again measured on a scale from 1 to 5.

3.1.2. Geographic Proximity

Geographic proximity is measured following Boschma’s (2005) description [29], with specific quantifiable items:

Distance between organizations. This variable is quantified in kilometers (km) to assess physical proximity.

Degree of accessibility. Respondents rated the ease of access between organizations on a scale from 1 to 5, where 1 indicates very difficult access and 5 indicates very easy access.

3.1.3. Organizational Proximity

This construction is grounded in the indicators proposed by Shirasawa and Seo (2023) [13]. Three items were created to quantify organizational proximity in the context of Creating Shared Value (CSV):

Degree of similarity of vision. Measured on a scale from 1 to 5, participants rated how closely their organization’s vision aligns with that of other cluster members.

Degree of shared goals for economic value. Respondents rated the extent of alignment on economic objectives related to CSV on a scale from 1 to 5.

Degree of shared goals for social value. Similar to the previous item, participants assessed their alignment on social objectives associated with CSV on a scale from 1 to 5.

3.1.4. Alliance Capability

To assess alliance capability, items focusing on alliance implementation and diversity were developed based on several studies [45,54]:

Degree of presence in the cluster. This variable quantifies how actively a company participates in the cluster, rated on a scale from 1 to 5.

Resource utilization capability. Participants rated their organization’s ability to leverage its resources for technological advancement on a scale from 1 to 5.

Utilization of resources from different industries. This measures the extent to which organizations collaborate across different sectors, rated on a scale from 1 to 5.

3.1.5. Economic Value

Economic value is assessed based on frameworks by Muthusamy and White (2006) and Toylan et al. (2020) [54,55]. The items reflect economic outcomes from two perspectives: market and labor.

Productivity improvement per operation. Respondents rated their perceived improvement in productivity due to CSV initiatives on a scale from 1 to 5.

Growth in market share. Participants estimated their market share growth within their region as a result of CSV, rated from 1 (no growth) to 5 (significant growth).

Creation of new products, technologies, or markets. This item measures the perceived innovation output resulting from CSV efforts, rated on a scale from 1 to 5.

3.1.6. Social Value

Social value is measured by extending the indicators proposed by Ishida (2020) [69]:

Consideration of the value chain. Participants rated the degree to which their organizations consider the entire value chain in their corporate activities on a scale from 1 to 5.

Environmental friendliness of products and services. Respondents assessed their products and services for environmental sustainability, rated from 1 (not environmentally friendly) to 5 (very environmentally friendly).

Health and safety considerations for stakeholders. This item measures how much organizations prioritize health and safety in their activities, rated on a scale from 1 to 5.

3.2. Structural Equation Modeling (SEM)

This research utilized Structural Equation Modeling (SEM) to examine the research hypotheses. SEM is a powerful multivariate analysis technique that allows for the simultaneous estimation of multiple relationships between latent and observed variables within a single model. This method is particularly useful for testing complex hypotheses and evaluating how different variables interact with one another. SEM enables the creation of diverse models that can accurately represent the research hypotheses using a single dataset, making it an ideal tool for this study.

The primary goal of this study is to propose a model to investigate the relationships between organizational proximity, geographic proximity, institutional proximity, and the success of Creating Shared Value (CSV) initiatives. SEM is suitable for this purpose because it provides a flexible framework for testing multiple hypotheses while accounting for measurement errors and relationships among variables.

The SEM process in this study involved two main components: the measurement model and the structural model. The measurement model specifies how the latent variables are measured by observed variables, allowing us to understand how constructs such as organizational proximity, geographic proximity, and institutional proximity can be operationalized through observable indicators. The structural model, on the other hand, outlines the relationships between latent variables, showing how these proximities influence the success of CSV initiatives within SMEs.

In this study, the covariance structure was estimated by using the measurement equation to describe the relationship between observed and latent variables and the structural equation to depict the relationships between latent variables. The parameters were then estimated using maximum likelihood estimation to determine the strength and significance of the relationships in the model.

To evaluate the goodness of fit of the model, we used several indices: the Goodness of Fit Index (GFI), Adjusted GFI (AGFI), and Root Mean Square Error of Approximation (RMSEA). These indices are widely used to assess how well the model fits the observed data and whether the hypothesized relationships are supported by the data. A good fit between the model and the observed data indicates that the model accurately represents the real-world phenomena being studied.

The actual SEM analysis was conducted using IBM SPSS Amos 27, a widely used software package for structural equation modeling. Amos provides a user-friendly interface for specifying and estimating SEM models, as well as tools for evaluating model fit and conducting hypothesis testing. By using this software, we were able to conduct a robust analysis of the relationships between proximity factors and CSV success in SMEs, while also ensuring the validity and reliability of the results.

3.3. Semi-Structured Interview

Based on these considerations, semi-structured interviews were conducted four times from October and December 2022. The interviews were carried out online with four companies that had participated in the survey and had provided their email addresses. To facilitate in-depth discussions, the interviews were organized with groups of companies belonging to the same cluster.

The interview questions focused on the background and motivation for joining the cluster, the purpose of participation in the cluster, the types of activities conducted within the cluster, and challenges faced and success stories arising from these activities.

4. Results

4.1. Types of Companies in Local Industrial Clusters

Among the companies in this study, 79.1% had a business size of less than 300 employees and 84.9% had been in business for more than 10 years (Figure 2). Regarding the percentage of the industry, 61.6% of the companies were in the manufacturing industry, and the other major industries were wholesale trade, information and communication, and academic research/technical services. There are 2 companies that have been in operation for less than a year, 5 companies that have been established for 1 to 4 years, 7 companies operating for 5 to 9 years, 4 companies with a business history of 10 to 19 years, and notably, 69 companies that have been in business for over 20 years.

4.2. Verification of Model Reliability and Validity

In this study, Cronbach’s alpha(α) and composite reliability were measured to examine the reliability of the questionnaire items. Also, we examine common method bias using Harman’s single factor test. In addition, we evaluate the convergent validity criterion, AVE (average variance extracted), and the discriminant validity criteria, ASV (average shared square variance) and MSV (maximum shared square variance), which are discriminative validity criteria.

Table 1. Latent and observed variables and reliability indices in this study.

Latent Variables	Observed Variables	M	SD	α	CR	AVE	MSV	ASV
Informal institutional proximity	Degree of agreement with organizations in the cluster on stability and upward orientation	3.37	0.78	0.78	0.82	0.63	0.61	0.35
	Degree of agreement with organizations in the cluster in terms of individual and group orientation	3.26	0.80
	Degree of agreement with organizations in the cluster in terms of result/process orientation	3.10	0.70
Geographic proximity	Degree of proximity to organizations in the cluster	3.42	1.15	0.78	0.87	0.68	0.32	0.21
	Degree of accessibility to organizations in the alliance	3.67	0.93
Organizational proximity	Degree of similarity of vision with organizations in the cluster	3.28	1.06	0.71	0.88	0.69	0.61	0.44
	Degree of shared goals regarding the economic value aspects of CSV	3.08	1.14
	Degree of shared goals for the social value aspect of CSV	3.16	1.21
Alliance capability	Degree of presence of the company’s business in the cluster	2.14	1.19	0.64	0.72	0.54	0.36	0.36
	Degree to which the organization is capable of utilizing its own resources in terms of technology	2.53	1.32
	Degree to which there is an organization in a different industry that can utilize the company’s resources in terms of technology	2.27	1.40
Economic value	Degree of productivity improvement per operation through CSV	3.19	0.93	0.78	0.88	0.69	0.37	0.27
	Degree of growth in market share within your region	3.01	0.90
	Degree to which there are new products, technologies, or markets created by CSV	2.93	0.99
Social value	Degree of consideration of the value chain in corporate activities	3.67	1.08	0.66	0.60	0.46	0.29	0.29
	Degree of environmental friendliness of products and services	4.00	1.08
	Degree of consideration of health and safety of stakeholders in corporate activities	4.48	0.71

summarizes the latent variables and observed variables extracted in this study and their internal consistency. In order to examine the internal consistency of the questions in this study, Cronbach’s α and CR are derived for each latent variable, and the α/CR for informal institutional proximity was 0.78/0.82, the α/CR for geographic proximity was 0.78/0.87, organizational proximity was 0.71/0.88, alliance capability was 0.64/0.72, economic value was 0.78/0.88, and social value was 0.66/0.60.

The results of Herman’s single factor test on the CSV acceleration model considering proximity in local industrial clusters show that the variance of all the observed variables explained by the six extracted factors is 75.6%. The percentage of variance of all observed variables explained by the first factor is 29.1%. These results show that the possibility of common method bias in this paper is low [70,71,72,73].

4.3. Proximity-Driven CSV Acceleration Model in Local Industrial Clusters

The CSV acceleration model considering proximity in local industrial clusters was constructed by using structural equation modelling (Figure 3). The results show that informal institutional proximity within a cluster has an impact on organizational proximity (p < 0.001), and geographic proximity within a cluster also has a significant impact on organizational proximity (p < 0.05). In addition, it is confirmed that organizational proximity has a significant effect on alliance capability (p < 0.001). Furthermore, it is confirmed that alliance capability has a significant impact on economic value (p < 0.01) and a significant impact on social value (p < 0.01).

The goodness of fit of the model is GFI = 0.935, AGFI = 0.881, CFI = 1.000, TLI = 1.075 and RMSEA = 0.000. All of the above results support all hypotheses.

4.4. Case Study

Company A is involved in the certification and evaluation of electronic medical equipment, telecommunications, and information equipment, alongside licensing procedures for radio communication stations. Recently, the company has focused on researching the effects of electromagnetic radiation from medical and telecommunications equipment, establishing a close relationship with the Ministry of Internal Affairs and Communications. The company’s initial goal in joining the industrial cluster was to expand its wireless communication business for medical equipment. However, challenges have emerged, such as the excessive intermingling of different industries, insufficient exchanges between companies, and a lack of leadership, all of which hinder the creation of synergies within the cluster. Compared to other clusters, the lack of cultural and organizational alignment within the cluster seems to be a significant barrier. Company A believes it must specialize in manufacturing and seek government guidance rather than relying solely on research initiatives. These challenges highlight the difficulty in achieving effective collaboration when institutional and organizational proximity is insufficient, reflecting how differing industrial focuses can prevent the formation of valuable alliances.

Company B, as an independent division of a larger group, specializes in air- and heat-related plant equipment, including air conditioning and heat source solutions. The company is heavily involved in CO₂ reduction and sustainability efforts throughout its product lifecycle. Its participation in the Medical Industry Cluster is aimed at breaking into the medical sector and fostering new business opportunities, particularly by providing environmental support to firms in regenerative medicine. However, despite the cluster’s focus on long-term research and development, Company B faces issues such as a low sense of belonging among cluster members and frequent turnover of secretariat staff. These concerns have led the company to establish an independent organization to collaborate with the central cluster organization, while expanding its reach beyond the local area. This case demonstrates the importance of organizational proximity in facilitating sustained collaboration. Company B’s experience reveals how the lack of cohesive leadership and institutional direction in the cluster limits the potential for shared value creation. This indicates that for CSV to thrive, a clear, cohesive organizational structure with shared leadership is necessary, especially in regions with fragmented organizational support.

Company C specializes in temporary staffing and placement, particularly for roles in research and development, quality control, and analysis in chemistry and biotechnology. Although Company C supports the development of cluster companies by facilitating research activities, it lacks a clear purpose in its cluster participation. The company primarily responds to customer requests and does not actively engage in the cluster’s interactive events. As a result, Company C views cluster companies more as customers rather than potential collaborators, which limits its involvement and ability to contribute to the cluster’s collective growth. This case further highlights the challenges of institutional proximity, particularly the role of shared organizational goals and vision in fostering collaboration. Company C’s lack of active engagement and its transactional view of cluster relationships illustrate how the absence of strong institutional ties can lead to underdeveloped collaborative networks.

Company D, an integrated manufacturer of plastic products, has expanded its network within the industrial cluster through active participation in seminars and events. This engagement has led to collaborative efforts with universities and other businesses, enabling joint development opportunities. However, Company D acknowledges that most exchanges remain one-to-one and have not yet evolved into robust networks or value chains. The company stresses that larger entities such as major corporations, governments, and universities must take the lead to create sustainable networks. Company D’s experience emphasizes the need for geographic proximity and highlights the role of larger institutions in catalyzing smaller organizations’ participation in collaborative efforts. Moreover, Company D’s emphasis on long-term relationships and the inclusion of stakeholders who are not solely focused on immediate profits speaks to the broader importance of institutional and organizational proximity in building sustainable CSV initiatives. By expanding geographic proximity, especially through larger partners and regional collaboration, the company believes that more robust and lasting partnerships can emerge.

5. Discussion

5.1. The Role of Proximity in Creating Shared Value (CSV): Insights from Japanese SMEs

The results from the SEM analysis, complemented by insights from semi-structured interviews with Companies A, B, C, and D, provide a nuanced understanding of how different forms of proximity—informal institutional, geographic, and organizational—specifically influence alliance formation and value creation within Japanese industrial clusters. This comprehensive approach underscores the complex dynamics of proximity in fostering collaborative efforts among small and medium-sized enterprises (SMEs) in local industrial settings, ultimately contributing to sustainable economic and social development.

From the SEM analysis, informal institutional proximity emerged as a key determinant in shaping organizational alliances and Creating Shared Value (CSV) initiatives. This form of proximity reflects the extent to which organizations share cultural practices and values. It plays a pivotal role in facilitating knowledge transfer, goal alignment, and trust building among firms. Interviews with Company A revealed the challenges associated with cultural misalignment within the cluster, particularly in industries with diverse goals and practices. The absence of a common cultural framework within the cluster hindered effective collaboration. Company A’s desire to specialize in manufacturing rather than focusing solely on research underscores the importance of shared cultural values for building a cohesive organizational culture that encourages collaboration. This finding aligns with Boschma’s (2005) assertion that cultural and social similarities reduce misunderstandings and enhance collaboration, ultimately promoting sustainability in industrial clusters. The lack of shared institutional values can create friction, which diminishes the potential for achieving long-term sustainable development goals (SDGs) through CSV initiatives. The study emphasizes the need for institutional frameworks that align organizations’ cultural norms to foster a supportive environment for sustainable growth and value creation [29].

Geographic proximity was also found to significantly affect alliance formation and CSV outcomes. Both the SEM results and interview data highlight how physical proximity enables more frequent and informal interactions, thereby lowering communication barriers and enhancing knowledge sharing. Company B’s active participation in local events and seminars exemplifies the benefits of physical closeness in fostering repeated interactions, facilitating knowledge spillovers, and strengthening sustainable collaboration. These findings are consistent with existing literature, which argues that geographic proximity strengthens the relational dynamics necessary for innovation and alliance formation [74,75]. Proximity enables firms to quickly access partners, observe their processes, and exchange information in real time. This facilitates a deeper understanding of shared challenges and opportunities, enhancing the resilience and sustainability of the cluster. From a practical standpoint, clusters should prioritize geographic proximity through local networking events, which can be integral to sustainable economic development by enabling firms to adapt rapidly to market needs and foster collective innovation for CSV initiatives [76].

Organizational proximity, characterized by shared goals, visions, and organizational practices, was identified as pivotal for successful alliances. In this study, Company C’s approach of viewing other firms primarily as customers, rather than potential collaborators, illustrates how lack of alignment can undermine collaborative efforts. This perspective led to missed opportunities for joint development, restricting the potential for sustainable innovation. Conversely, Company D’s proactive engagement in cluster events highlights how the alignment of organizational goals and active participation can lead to successful joint initiatives, contributing to both economic and environmental sustainability. This suggests that for CSV initiatives to be successful, it is essential not only to align organizational objectives but also to foster a culture of active participation in collective efforts. The findings emphasize the importance of organizational proximity in developing sustainable collaborative environments that support both business success and broader social objectives.

The interviews also underscored the necessity of a shared understanding of value creation for effective alliances. Company B’s commitment to sustainability and its alignment with the Medical Industry Cluster’s goals exemplify how shared values can guide long-term collaborative efforts. However, the study also revealed that challenges, such as low sense of belonging and unclear leadership, could hinder collective action within clusters. These barriers emphasize the need for clear leadership and the articulation of shared objectives to sustain collaboration and ensure long-term sustainability. Addressing these challenges is key to reinforcing sustainable value creation through CSV initiatives within regional clusters.

The study’s findings have broader implications for both theory and practice in the field of CSV and the sustainability of SMEs. As Japan’s unique industrial context reflects specific cultural factors influencing collaboration, the core principles derived from this study—such as the significance of proximity in fostering effective knowledge sharing, innovation, and alliance formation—are applicable to other regions and sectors. The concepts of institutional, geographic, and organizational proximity can be adapted by firms in various industries, such as healthcare, technology, and renewable energy, to enhance their CSV initiatives. These industries, which rely heavily on innovation and collaboration, can benefit from fostering proximity to accelerate sustainable development goals (SDGs). By fostering proximity within clusters, firms can enhance their collective capacity to address local challenges, share knowledge, and co-create value that contributes to sustainable economic growth. This study, therefore, provides both theoretical insights into how proximity influences the success of CSV initiatives and practical guidance for SMEs seeking to improve their collaborative efforts towards sustainability.

5.2. Theoretical and Managerial Implications

The theoretical implications of this study contribute significantly to two important areas of research: the impact of forming and operating alliances on performance and the role of proximity in shaping inter-company relationships within a sustainability framework. This study proposes a conceptual model to describe how Creating Shared Value (CSV) influences alliance performance, offering new insights into the mechanisms at play. Specifically, it clarifies how proximity affects alliance performance and illustrates the multifaceted benefits of alliances through the CSV framework, which integrates both economic and social sustainability dimensions.

Existing research has explored the impact of forming and operating alliances on performance [44,54] and the role of proximity in shaping inter-company relationships [74,77]. However, the mechanisms through which proximity influences performance via alliances have remained ambiguous. This study contributes theoretically by providing a clearer understanding of these mechanisms, constructing a model that demonstrates how geographical, cognitive, and organizational proximity can enhance the efficiency and effectiveness of alliances while promoting long-term sustainability.

Furthermore, this study enriches the theoretical landscape by integrating the concept of CSV into the analysis of alliances. Traditional perspectives on alliances primarily focus on economic outcomes, often overlooking the social and environmental dimensions of these collaborations [78]. By applying the CSV framework, this study illustrates how alliances can generate both economic and social value, making industrial clusters more resilient and sustainable.

To enhance their CSV initiatives, SMEs can strategically leverage proximity in several ways. Geographical proximity allows SMEs to actively participate in local networks and events, fostering frequent, informal interactions with partners. Physical closeness to key stakeholders facilitates real-time knowledge sharing and quick access to resources, driving innovation and adaptability in dynamic markets [37]. Additionally, leveraging local resources can help SMEs develop more sustainable and community-oriented CSV initiatives.

Organizational proximity is equally crucial. SMEs should align their strategic objectives with those of their partners through clear communication and sustained collaboration on joint projects. Establishing shared goals and maintaining continuous engagement can help SMEs navigate challenges and achieve mutual benefits [13]. Furthermore, adopting flexible business models will enable SMEs to better respond to evolving partnerships, ensuring the long-term sustainability of their alliances.

By focusing on these types of proximity, SMEs would improve the effectiveness of their alliances, ensuring that their CSV initiatives are not only economically viable but also socially and environmentally impactful.

5.3. Limitations and Future Research

This study presents both theoretical and empirical limitations that offer opportunities for further exploration in future research.

Firstly, the sample limitation must be acknowledged. The research focuses specifically on companies from 11 distinct industry clusters within Japan. While this approach provides valuable insights into SMEs operating in local industrial clusters, it may not fully capture the diversity of SMEs across different cultural and economic contexts. Given the potential cultural bias inherent in analyzing only Japanese SMEs, future research should consider comparative studies with SMEs from other countries or regions to enhance the generalizability of the findings. Furthermore, exploring how varying cultural contexts shape proximity-based collaborations can provide valuable insights into the adaptability of the Creating Shared Value (CSV) framework across different environments.

Secondly, while the study’s assessment of proximity was conducted using a questionnaire, it could be further refined. A more comprehensive evaluation could include objective indicators such as actual geographic distance, transportation accessibility, and digital connectivity between organizations. Future research should consider additional dimensions of proximity, such as cognitive and social proximity, to gain a more nuanced understanding of how these factors influence alliance performance and CSV initiatives.

Moreover, this study did not differentiate between types of alliances. The dynamics of alliances vary, with some collaborations being project-based and short-term, while others develop into long-term strategic partnerships. Future research should categorize alliances based on their duration, purpose, and governance structures to develop more tailored models for understanding the sustainability and effectiveness of these collaborations. A deeper understanding of the factors that contribute to the longevity and success of different types of alliances could improve the implementation of CSV initiatives.

Lastly, while this study focused on SMEs within the manufacturing and healthcare sectors, future research could extend the proposed conceptual model to other industrial contexts, such as technology-driven industries or service-oriented sectors. These industries may experience different challenges and opportunities in relation to proximity and alliance formation, and their unique characteristics could offer additional insights into the factors that promote sustainability and innovation. Additionally, emerging trends such as digital transformation, remote collaboration, and the use of advanced technologies like artificial intelligence, big data, and IoT could have significant implications on the role of proximity in fostering CSV-oriented partnerships. Investigating these aspects could provide a more contemporary view of how technological advances shape collaboration and contribute to the sustainability of SME alliances in an increasingly digital world.

6. Conclusions

This study explored the influence of institutional and geographic proximity on the realization of Creating Shared Value (CSV) among SMEs within local industrial clusters. Our findings address the two main research questions (RQ1 and RQ2) and provide insights into the role of proximity in fostering sustainable business practices through CSV initiatives.

Firstly, regarding RQ1, the study highlights that organizational proximity—characterized by the alignment of shared values, structures, and practices between firms—plays a pivotal role in enabling SMEs to engage in CSV in a sustainable manner. SMEs that successfully leveraged organizational proximity were able to engage in deeper collaboration, leading not only to enhanced competitiveness but also to meaningful social and environmental contributions within their communities, thus fostering sustainable industrial development.

Secondly, concerning RQ2, our findings indicate that both geographic and institutional proximities significantly contribute to the sustainability and success of CSV initiatives in Japanese SMEs. Geographic proximity facilitates frequent and informal interactions, promoting knowledge exchange and strengthening relational dynamics, while institutional proximity—through shared norms, values, and regulatory frameworks—supports collaboration by reducing misunderstandings and aligning organizational goals. These proximities enable SMEs to form more resilient and innovative alliances, furthering the sustainability of the local industrial clusters.

In sum, the study underscores the critical role of proximity in supporting sustainable CSV initiatives within SMEs. By fostering collaboration and aligning organizational values, proximity enhances the capacity of SMEs to contribute to both economic growth and community well-being, ultimately ensuring the long-term sustainability of local industrial ecosystems.