Analyzing the Influence of Creating Shared Value (CSV) Activities and Information Characteristics on Sustainable Information Performance

Abstract

Corporations are increasingly pressured to adopt Creating Shared Value (CSV) not only as a means of profit generation but as a strategic approach to addressing societal challenges. Through value chain innovation, firms can simultaneously enhance competitiveness and contribute to social problem-solving. Although supply chain performance has been widely studied, limited research has examined the combined relationships among CSV activities, information characteristics, and information performance. This study analyzes how CSV—reflected through business and societal value—affects information sharing and information quality, and how these factors further influence sustainable information performance across management, behavioral, and technological dimensions. Using data collected from 182 firms, the findings reveal that CSV activities significantly improve both information sharing and information quality, which subsequently enhance information performance. These results highlight CSV’s essential role in establishing cooperative supply chain relationships and strengthening organizational information capability. By integrating CSV principles with information-driven processes, this research provides theoretical and managerial contributions and demonstrates that fostering high-quality information flows grounded in CSV can support long-term competitiveness and societal value creation.

1. Introduction

Over the past several years, Creating Shared Value (CSV) has emerged as a central topic of interest in both academic and managerial circles. In conjunction with Corporate Social Responsibility (CSR), CSV is viewed as a strategic concept that integrates economic, social, and cultural value creation, thereby producing mutually reinforcing outcomes [1]. The idea was originally presented in Porter and Kramer’s 2006 [2] Harvard Business Review article, “Strategy and Society,” which emphasized the connection between competitive advantage and responsible corporate behavior. Their subsequent work in 2011 further developed CSV into a management paradigm that strengthens a firm’s competitiveness by addressing societal issues while pursuing profit objectives.

As this paradigm has matured, CSV has increasingly been analyzed through multiple theoretical perspectives. Rather than restricting their strategic objectives to profit maximization, companies are encouraged to regard CSV as an investment-oriented approach that contributes to solving community problems. By innovating across the entire value chain, organizations can reinforce their competitive standing while simultaneously addressing social needs. Sustaining a competitive advantage and maintaining societal trust requires the recognition that CSV can function as a long-term driver of corporate reputation and organizational viability [2,3].

Within supply chains, enhancing visibility across the full logistics process—from upstream partners to end consumers—plays an essential role in improving collective performance. Firms participating in these networks devote substantial effort to achieving shared performance gains. In this environment, cultivating stable and mutually beneficial partnerships is critical for improving information-related outcomes. CSV activities support the development of long-term cooperative relationships, which are vital for effective supply chain management (SCM). Companies that excel in SCM generally experience improvements in market competitiveness, product quality, responsiveness, logistical efficiency, and customer satisfaction [4].

Although supply chain performance has been examined from diverse perspectives—including collaboration measurement frameworks [4], characteristics of interorganizational information systems [5], the influence of information sharing on performance [6], and balanced scorecard approaches [7]—there remains a lack of empirical research that jointly considers information performance, SCM dynamics, and CSV. The distinctive contribution of the present study lies in its empirical investigation of information performance within the context of CSV initiatives [8,9].

Accordingly, this research explores how CSV practices influence information sharing and information quality within supply chains, and how these factors ultimately affect information performance. To guide this investigation, the study addresses two key research questions:

Q1: How do Creating Shared Value (CSV) activities shape information characteristics?

Q2: How do information characteristics contribute to information performance?

The study objectives derived from these questions are as follows.

The first objective is to analyze the relationship between organizational CSV activities and the determinants of information performance. Although existing studies [5] have explored various SCM-related strategic factors—such as collaborative infrastructures and implementation strategies—research specifically emphasizing CSV remains limited. As SCM adoption provides real-time operational insight, clarifying CSV’s impact on performance outcomes remains essential.

The second objective is to examine the interconnected roles of SCM information sharing, information quality, and information performance. Prior research [6,10] has focused on the quality of SCM information systems and their effect on performance, but many of these studies have produced incomplete or mixed results. Despite the long-recognized importance of information sharing and information quality in information systems literature, relatively few studies have analyzed the combined causal pathways linking these variables to organizational information capability. This study aims to address this gap.

The third objective is to investigate information performance from a supply chain perspective. Traditional performance evaluation methods—including financial metrics, non-financial indicators, the Balanced Scorecard (BSC), and the Supply Chain Operations Reference (SCOR) model [7]—have been widely applied in SCM research. However, one of the most meaningful outcomes derived from SCM system implementation is the improvement of organizational and interorganizational information performance. Thus, this study examines how SCM systems contribute to enhanced information performance across supply chains.

2. Theoretical Background

2.1. Creating Shared Value

CSV has increasingly become a core principle guiding contemporary corporate strategy, functioning as a framework that supports long-term organizational sustainability. It can be understood not only as a novel business approach but also as a more advanced and strategic extension of traditional CSR practices [3,11]. While CSR has historically focused on enhancing corporate reputation and managing costs to maintain a positive public image, CSV emphasizes generating economic returns by directly engaging with social challenges and creating mutual value. In this respect, CSV operates as a strategic pathway through which firms can build and maintain sustainable competitive advantage [12].

The CSV framework is generally viewed as comprising two key dimensions: Business Value (BV) and Societal Value (SV) (Figure 1) [3,12]. When firms adopt CSV within supply chain contexts, efforts to address societal issues often promote shared economic benefits across partner organizations. Process enhancements driven by such initiatives tend to reduce operational costs, improve efficiency, and strengthen market performance. As a result, all stakeholders involved in the supply chain typically experience increased levels of satisfaction and mutual prosperity [2].

2.2. Information Sharing

Empirical studies indicate that firms operating within a supply chain can enhance their performance by exchanging not only information but also knowledge that includes operational expertise. Information sharing encompasses both formal and informal communication of accurate and timely data among firms. The degree to which such sharing occurs depends on a company’s readiness to offer valuable information to its partners in a collaborative manner. Moreover, when partner firms expect to receive broad and detailed information, they are better positioned to respond effectively to internal operations as well as changing market environments [10,13].

The literature commonly distinguishes knowledge into two categories—information and experiential know-how. Establishing mechanisms that support the reciprocal exchange of information yields several advantages: it improves the alignment of strategic plans and investment decisions, and it helps firms monitor environmental changes so they can react quickly to market fluctuations or new opportunities. Through these functions, such mechanisms foster sources of competitive advantage and contribute to overall performance improvement [10,14].

Creating robust channels for interfirm information exchange also enables supply chain participants to coordinate investments in fixed production assets more efficiently, thereby optimizing the use of resources and operational capacity [15]. Companies strive to achieve transparency and visibility throughout the value chain by participating in structured information-sharing processes with their partners [16]. However, if firms perceive that shared information lacks credibility or usefulness, the establishment of effective long-term cooperation within the supply chain becomes considerably more difficult.

2.3. Information Quality

When accurate and up-to-date information is integrated into decision-making and circulates efficiently across all stages of the supply chain, its value and usability increase markedly, contributing to substantial improvements in both supply chain effectiveness and operational efficiency [17]. The proper use of information helps diminish uncertainty in demand forecasts and enhances communication between manufacturers and their suppliers [18]. Achieving strong performance in interfirm information utilization requires that the information being exchanged maintain a high level of quality. As a result, information quality has become a central concern within the organizational and operational aspects of information systems research [19].

For information to be regarded as high quality, it must possess several essential characteristics, including consistent and repeatable updates, dependable modifications, suitability for its intended purpose, adaptability across various contexts, ease of access, and clarity of meaning for users [20].

Information quality is often described in terms of specific attributes and can be assessed through seven indicators:

• Relevance—the degree to which information aligns with user needs and aids in solving problems;
• Timeliness—the prompt availability of information and the validity of its content over time;
• Accuracy—the extent to which information accurately reflects actual conditions with minimal error;
• Precision—the level of detail and specificity appropriate for the problem being addressed;
• Completeness—the comprehensiveness of information based on user requirements;
• Conciseness—the removal of superfluous or redundant data;
• Format—the suitability of the presentation style and structure for the given context and user needs.

2.4. Information Performance

Prior research assessing supply chain management (SCM) performance generally falls into four major categories [8]. The first category evaluates performance through financial indicators such as return on investment (ROI), growth rates, profit margins, sales volumes, inventory turnover, return on assets (ROA), and return on equity (ROE). The second category focuses on non-financial perspectives, emphasizing elements such as employee satisfaction, customer service quality, customer retention, and customer satisfaction levels. A third approach is the Balanced Scorecard (BSC), which evaluates performance across four dimensions: customer orientation, learning and growth, internal processes, and financial outcomes. The fourth category comprises the Supply Chain Operations Reference (SCOR) model, which assesses supply chain activities across five key areas—production, delivery, returns, planning, and sourcing [9].

Although these frameworks contribute meaningfully to evaluating information system performance, one of the most significant outcomes expected from SCM system adoption is the enhancement of organizational information performance. Achieving improvements in this domain requires seamless information flows supported by both high-quality information and effective mechanisms for sharing it [21].

In this study, information performance is conceptualized through three dimensions (Figure 2) [22].

Management Performance (MP): the organization’s capability to manage information efficiently using its information systems;

Behavior Performance (BP): the degree to which the organization cultivates behaviors and values among its members that promote effective information utilization for achieving organizational goals;

Technology Performance (TP): the organization’s ability to construct and leverage technological systems that support informed decision-making and facilitate smooth communication [23].

Importantly, information performance is not limited to individual firms or their internal information systems departments. Instead, it extends across all entities connected within the supply chain network. Thus, evaluating information system effectiveness solely through outcome-based measures is insufficient. A more appropriate approach is to assess the information capabilities that emerge from data integration and process connectivity made possible through SCM system adoption [24]. Moreover, meaningful improvements in information performance can only be achieved when high-quality information and effective sharing mechanisms are firmly established [25].

3. Research Model and Hypotheses

The research model developed in this study examines how the two dimensions of CSV—Business Value and Societal Value—shape information sharing and information quality. Additionally, the model outlines the interdependent relationships among these constructs and analyzes how such interactions ultimately influence information performance (Figure 3).

Development of Hypotheses

The concept of CSV can be broadly interpreted as an approach that integrates both economic value generation and contributions to societal well-being [12]. Implementing CSV places strong emphasis on strengthening cooperative relationships by addressing social problems within the supply chain [11]. Such initiatives promote mutual development among partner firms, thereby contributing to enhanced information sharing and improved information quality.

The economic dimension of CSV extends beyond financial gains such as increased sales; it also encompasses non-financial benefits, including ethics and environmental responsibility, which elevate the value of all firms involved [2]. By recognizing societal needs and innovating accordingly—an essential aspect of economic value creation—CSV is expected to foster higher levels of both information sharing and information quality across partner firms. This reasoning leads to the formulation of the following hypotheses:

H1. 

CSV will have a significant effect on information sharing.

H2. 

CSV will have a significant effect on information quality.

Effective collaboration within the supply chain requires seamless and meaningful information exchange between participating firms. The adequacy, reliability, and usefulness of shared information influence not only financial outcomes but also non-financial benefits such as enhanced mutual value [20]. Strong information-sharing practices are therefore likely to improve the quality of shared information [13], which is vital for both operational and strategic decisions. Based on this understanding, the following hypothesis is proposed:

H3. 

Information sharing will have a significant effect on Information Quality.

Information-sharing activities among partner firms also support the formation of strategic alliances [21]. Smooth information flows minimize delays and disruptions in supply chain processes [23]. By promoting interfirm information exchange and strengthening knowledge management, information sharing contributes directly to enhanced information performance. This leads to the next hypothesis:

H4. 

Information sharing will have a significant effect on information performance.

High-quality information strengthens the capabilities of users involved in SCM activities and thereby improves information performance [22]. Firms that rely on high-quality information typically demonstrate greater maturity in their information systems and are better positioned to adopt and apply new technologies effectively [19]. Thus, information quality serves as a key determinant of organizational information capability. Based on this rationale, the following hypothesis is proposed:

H5. 

Information quality will have a significant effect on information performance.

4. Methods

The measurement items for the variables employed in this study are summarized in

Table 1. Research Construct Item.

Construct	Items
Business Value [2,5]	Firms engaged in CSV activities strive to improve their economic performance.
	Firms engaged in CSV activities contribute to economic development through profit generation.
	Firms engaged in CSV activities strive to create employment opportunities.
Societal Value [11,12]	Firms engaged in CSV activities contribute to solving fundamental social problems.
	Firms engaged in CSV activities contribute to social contribution activities.
	Firms engaged in CSV activities contribute to social welfare.
Information Sharing [13,14]	Our company and its partner firms share information that can potentially influence each other’s business operations.
	Our company and its partner firms share information that is necessary for the effective operation of each other’s businesses.
	Our company and its partner firms share information that contributes to improving each other’s business performance.
Information Quality [19,20]	The information shared between our company and its partner firms is sufficient.
	The information shared between our company and its partner firms is accurate.
	The information shared between our company and its partner firms is useful.
Management Performance [21,22]	Since the adoption of SCM, necessary information has been collected through structured and systematic procedures.
	Since the adoption of SCM, it has become possible to systematically analyze the information required for business decision-making.
	The adoption of SCM has enabled continuous maintenance and management of up-to-date information.
Behavior Performance [23,26]	The adoption of SCM has encouraged an environment that promotes open disclosure and suggestion of information.
	Since the adoption of SCM, information has been provided transparently to both internal and external members of the organization.
	Since the adoption of SCM, users have entered accurate data into the system to maintain information integrity.
Technology Performance [27,28]	Since the adoption of SCM, work processes have become more consistent and efficient.
	Since the adoption of SCM, improved information utilization has enabled more innovative work performance.
	Since the adoption of SCM has made decision-making related to work activities easier and more effective.

.

Data were collected over a four-month period, from August to November 2024. Approximately 300 survey questionnaires were distributed using three different methods: telephone contact, email dissemination, and direct on-site administration. A total of 188 questionnaires were returned. After removing six responses deemed incomplete or insincere, 182 valid cases were retained for hypothesis testing and model assessment. Statistical analyses were performed using SPSS 25 and SMART-PLS 4.0, and the characteristics of the final sample are summarized in

Table 2. Profiles of companies and respondents.

	Number	Percent (%)
Industry
Manufacturing/engineering	76	42%
Retailing and wholesale	42	23%
Information and Communication	24	13%
Services and utilities	22	12%
Transportation and logistics	18	10%
Number of employees
Less than 1000	52	29%
More than 1000	130	71%
Title of respondent
Assistant manager	86	47%
Manager	62	34%
General manager	27	15%
Executive director	7	4%

.

To examine validity, factor analysis was employed. Factors were extracted using the criterion of eigenvalues greater than 1, followed by Varimax rotation. The minimum acceptable factor loading depends on sample size; for datasets exceeding 100 observations, loadings between 0.50 and 0.55 are generally regarded as adequate [29]. With a sample size of 182, a threshold of 0.50 was adopted. As indicated in

Table 3. Results of factor analysis. (5-point Likert-type scale).

	Behavior Performance	Societal Value	Management Performance	Technology Performance	Information Quality	Information Sharing	Business Value
BV1	0.082	−0.082	0.075	0.043	0.132	0.228	0.789
BV2	−0.127	0.249	−0.409	0.174	−0.058	0.149	0.608
BV3	0.086	0.230	0.136	0.009	0.159	0.096	0.793
SV1	−0.001	0.807	−0.060	0.139	−0.224	0.116	0.181
SV2	0.012	0.872	−0.100	0.025	0.081	0.132	0.070
SV3	−0.096	0.759	−0.307	0.112	−0.034	0.096	0.008
IS1	−0.005	0.057	−0.002	0.128	0.110	0.825	0.231
IS2	−0.018	0.272	0.065	0.049	0.157	0.849	0.122
IS3	0.038	0.077	0.281	0.246	0.168	0.675	0.102
IQ1	0.063	0.102	0.046	0.179	0.803	0.151	0.090
IQ2	0.255	−0.093	0.232	−0.017	0.743	0.207	0.110
IQ3	0.116	−0.175	0.242	0.084	0.829	0.087	0.096
MP1	0.098	−0.196	0.760	0.118	0.144	0.090	0.240
MP2	0.081	−0.087	0.699	0.089	0.197	0.292	−0.080
MP3	0.052	−0.125	0.848	−0.058	0.131	−0.011	−0.038
BP1	0.843	−0.131	0.077	0.118	0.275	0.018	0.036
BP2	0.886	−0.002	0.057	0.233	0.025	0.042	0.011
BP3	0.881	0.049	0.095	0.159	0.095	−0.046	0.056
TP1	0.242	0.020	0.039	0.811	0.139	0.144	0.042
TP2	0.143	0.020	−0.083	0.865	−0.019	0.172	0.088
TP3	0.168	0.317	0.174	0.765	0.167	0.048	0.022

BV: Business Value; SV: societal value; IS: information sharing; IQ: information quality; MP: Management Performance; BP: Behavior Performance, TP: Technology Performance. The shaded numbers ≥ 0.5 (factor loadings).

, all items met this threshold, and seven distinct factors were identified.

Model fit was then evaluated to determine the degree to which the covariance structure aligned with the theoretical assumptions of the study. Convergent validity was tested by examining the correlations among indicators belonging to the same construct. Construct reliability (CR) was computed using factor loadings and error variances, with values above 0.70 indicating satisfactory convergent validity. Cronbach’s alpha values exceeded 0.768, confirming strong internal reliability (

Table 4. Results of CR, AVE, and Cronbach’s α.

Measures	AVE	CR	Cronbach’s α
Business Value	0.534	0.812	0.799
Societal Value	0.526	0.831	0.815
Information Sharing	0.573	0.829	0.841
Information Quality	0.549	0.809	0.838
Management Performance	0.601	0.835	0.847
Behavior Performance	0.587	0.827	0.856
Technology Performance	0.562	0.822	0.797

) [29].

Discriminant validity assesses whether each construct is sufficiently distinct from others in the model. This was evaluated by comparing the square root of each construct’s Average Variance Extracted (AVE) with the correlations among constructs. Discriminant validity is supported when the square root of the AVE exceeds inter-construct correlation coefficients. As shown in

Table 5. Results of discriminant validity analysis.

	Business Value	Societal Value	Information Sharing	Information Quality	Management Performance	Behavior Performance	Technology Performance
Business Value	0.731
Societal Value	0.301 *	0.725
Information Sharing	0.400 *	0.258 *	0.757
Information Quality	0.211 *	0.233 *	0.370 *	0.741
Management Performance	0.189 *	0.299 *	0.272 *	0.432 *	0.775
Behavior Performance	0.192 *	0.176 *	0.182 *	0.349 *	0.227 *	0.766
Technology Performance	0.210 *	0.226 *	0.345 *	0.247 *	0.172 *	0.393 *	0.750

The shaded numbers in the diagonal row are the square roots of the AVE. * Significant at α = 0.01.

, all constructs met this requirement, confirming adequate discriminant validity [29].

Additionally, correlation coefficients were all below the recommended threshold of 0.85, suggesting that multicollinearity was not an issue. Further tests using variance inflation factor (VIF) and tolerance (TOL) values—presented in

Table 6. VIF and tolerance.

	Tolerance	VIF		Tolerance	VIF
Creating Shared Value	0.754	1.289	Information Sharing	0.659	1.318
Information Quality	0.786	1.271	Dependent Variable: Information Performance

—also indicated the absence of multicollinearity. VIF values of 10 or lower and TOL values of 0.3 or higher are considered acceptable, and all variables fell within these ranges.

Table 7. Fit statistics for validating the measurement model.

Recommended Value		Measurement Model
Fit statistic	X2/DF (≤3.000)	2.571
	GFI (≥0.900)	0.906
	RMSR (≤0.050)	0.046
	RMSEA (≤0.080)	0.047
	AGFI (≥0.800)	0.818
	CFI (≥0.900)	0.871
	TLI (≥0.900)	0.913
	PGFI (≥0.600)	0.608

reports the model fit indices used in this study. With the exception of the Comparative Fit Index (CFI), all statistical measures reflected satisfactory model fit, supporting the appropriateness of proceeding with additional analyses under the established model conditions [30].

5. Model Structure

As illustrated in Figure 4, Creating Shared Value (CSV) was measured using two underlying components: Business Value and Societal Value. Likewise, information performance was evaluated through three dimensions—management, behavioral, and technological performance—allowing for a more structured and comprehensive assessment of the construct.

For Hypothesis 1, which proposed a positive influence of CSV on information sharing, the analysis revealed a statistically significant path coefficient (γ = 0.38, t = 5.52). Verification of the first-order submodel similarly showed a positive and significant effect. These results correspond with earlier research [12], supporting the idea that CSV strengthens the value proposition of participating firms and promotes smoother information exchange within the supply chain.

Hypothesis 2 suggested that CSV would positively affect information quality, and the results confirmed this relationship (γ = 0.19, t = 2.42). The first-order construct evaluation also demonstrated a significant positive association. These outcomes are aligned with previous studies [2], indicating that CSV—by incorporating both financial and non-financial considerations—contributes to maintaining high levels of information quality among partner firms.

The analysis of Hypothesis 3 showed that information sharing had a statistically significant impact on information quality (β = 0.34, t = 5.34). First-order construct verification mirrored this pattern, indicating a consistent relationship. These findings reinforce earlier research [13,20], suggesting that efficient information sharing enhances information quality through improved communication and smoother business interactions among supply chain partners.

In this study, information performance was conceptualized using three subcomponents—Management Performance, Behavior Performance, and Technology Performance—which collectively represented the higher-order construct of information capability (Figure 4).

Hypothesis 4 examined the effect of information sharing on information performance, and the results again showed statistical significance (β = 0.27, t = 4.50). The submodel analysis confirmed the same pattern. These findings concur with previous literature [21,23], indicating that sharing information promotes interorganizational knowledge exchange, enhances information flow, and strengthens overall knowledge management, ultimately improving information performance.

For Hypothesis 5, information quality exhibited a significant positive influence on information performance (β = 0.40, t = 7.49). Consistent results were observed in the first-order model verification. These outcomes align with earlier research [19,22], suggesting that high-quality information improves user capability within SCM environments, thereby raising the level of overall information performance.

Additional findings—including both direct and indirect effects—are summarized in

Table 8. Coefficients of direct, indirect, and total effects.

		Information Sharing	Information Quality	Information Performance
CSV	Direct Effect	0.38 *	0.19 *
	Indirect Effect	-	-
	Total Effect	0.38 *	0.19 *
Information Sharing	Direct Effect		0.34 *	0.27 *
	Indirect Effect		-	0.11 *
	Total Effect		0.34 *	0.38 *
Information Quality	Direct Effect			0.40 *
	Indirect Effect			-
	Total Effect			0.40 *

Note: * significant at α = 0.05.

.

6. Conclusions

This study aimed to examine the effects of CSV, measured in terms of Business Value and societal value, on information sharing and information quality. In addition, it sought to investigate how the interrelationships among these factors influence information performance.

Accordingly, the major implication of this research is that it provides an empirical analysis of the effects of CSV and information-related factors on information performance. We also conducted a comparative analysis that incorporated prior research to validate and contextualize our findings.

An examination of the factors that enhance information sharing, information quality, and information performance through CSV creation with partner firms provided the following results.

First, CSV activities, encompassing both business and societal value, were found to have a positive effect on information sharing and information quality. In the first-order construct verification for the submodel, CSV activities also had a significant effect on information quality and information performance (Management Performance, Behavior Performance, and Technology Performance). These findings are in concordance with insights widely acknowledged in the existing body of research [12].

As the concept of Creating Shared Value suggests, fostering a shared understanding centered on addressing societal issues contributes to the creation of a favorable image among partners within the supply chain. The importance of sustained influence through supply chain participation can be understood as the belief that the value of solving societal problems, combined with the creation of economic value, serves as a bridge for generating mutual benefits among partners.

In the first-order construct verification for the submodel, information sharing was also found to have a significant effect on information quality and information performance (Management Performance, Behavior Performance, and Technology Performance). These findings are aligned with patterns that have been well-established in the broader information systems literature [20]. Ultimately, efforts to share information among partner firms are deemed to enhance interfirm information flows, promote knowledge sharing, and improve knowledge management levels, contributing to improvements in information quality and information performance.

Third, information quality was found to have a significant effect on information performance (Management Performance, Behavior Performance, and Technology Performance), demonstrating a significant positive effect on information capability (Management Performance, Behavior Performance, and Technology Performance) in the first-order construct verification for the submodel. These results correspond closely with the prevailing perspectives recognized in contemporary studies on information capability [23].

Therefore, it can be inferred that high-quality information positively influences information performance by facilitating effective business interactions with partner firms.

Until recently, research on CSV activities has primarily focused on studies related to image enhancement. This study aims to broaden the scope of future research by examining the relationships involving information performance. Furthermore, for CSV to be fully generalized as a theoretical framework, the scope of research must be expanded to encompass a wider range of contexts.

The academic and practical implications of this study are as follows.

Firstly, this study examined the relationship between CSV and supply chain-related information performance, an area that previous CSV research has rarely addressed. By analyzing CSV activities in conjunction with their impact on supply chain integration, this study provides a conceptual framework for further investigation. The core concept of CSV aligns with the inherent profit-oriented nature of firms while also being grounded in the principle of addressing societal challenges.

Firms should pursue supply chain advancement through CSV initiatives aimed at creating both business and societal value. The proposed approach suggests implementing a CSV chain model, in which the realization of CSV’s philosophy—solving societal problems—is naturally linked to the generation of corporate profits, thereby forming a sustainable growth model for the firm.

Second, as indicated by the finding that strengthening information sharing and information quality ultimately leads to improved information performance, enhancing supply chain quality based on information sharing is expected to contribute to superior information performance in business operations. In an increasingly competitive environment, achieving performance improvements within the supply chain requires strategic initiatives that promote smooth information sharing and improved information quality among all supply chain members.

Third, unlike previous methodologies for measuring SCM performance, this study assessed inter-organizational information system performance. While SCM performance is currently evaluated through financial analyses, non-financial analyses, the Balanced Scorecard (BSC) methodology, and the Supply Chain Operations Reference (SCOR) model, one of the most important outcomes expected to occur as a result of the introduction of information systems such as SCM systems is the improvement of organizational information performance. Therefore, this study sought to examine the enhanced information performance of firms and supply chains, which has often been overlooked in prior research as a result of system implementation. Furthermore, information capability was systematically analyzed in a way that considered Management Performance, Behavior Performance, and Technology Performance as components of information performance. This approach is expected to provide more useful managerial guidelines even for firms that have adopted SCM but are not yet effectively managing information within and across organizational boundaries.

This study has several limitations that should be acknowledged. Because the analysis was conducted using cross-sectional data collected at a single point in time, the dynamic changes that occur following the adoption of supply chain management (SCM) systems could not be fully captured. Future studies should therefore adopt longitudinal research designs to observe how the relationships among Creating Shared Value (CSV), information sharing, information quality, and information performance evolve over time. In addition, the sample size was not sufficiently large to explore variations by firm size, industry sector, or duration of SCM implementation. Expanding the sample scope and incorporating comparative analyses across different industrial contexts would enhance the generalizability of the findings. Moreover, future research could extend this framework by examining moderating factors—such as organizational culture, digital transformation maturity, or stakeholder engagement—that may strengthen or weaken the relationships identified in this study. Conducting cross-national or longitudinal studies would also provide deeper insights into how CSV-driven information performance contributes to sustainable competitiveness in diverse economic environments.