Harnessing Knowledge: The Robust Role of Knowledge Management Practices and Business Intelligence Systems in Developing Entrepreneurial Leadership and Organizational Sustainability in SMEs

Abstract

The present study examines the role of knowledge management practices in developing business intelligence systems (BISMs) and organizational sustainability (OS) in small and medium-sized enterprises (SMEs) in Saudi Arabia. With the underpinning of the knowledge-based view (KBV) in the model of the study, the study employed a deductive approach. Cross-sectional data were gathered from CEOs, senior managers, and business intelligence officers using both offline and online survey tools. Finally, the study utilized 356 usable cases to support its conclusions. The study confirmed a positive effect on knowledge management practices, i.e., knowledge acquisition (KAG) and knowledge dissemination (KDM) on BISMs and OS. On the other hand, the impact of knowledge responsiveness (KRN) on BISMs is negative but positive on OS. Furthermore, BISMs have a positive effect on OS and entrepreneurial leadership (ELP). ELP also positively affects OS. Finally, ELP mediates the relationship between BISMs and OS. The study provides guidelines for SME managers and policymakers on how to invest in knowledge management initiatives to foster a culture of continuous learning and information sharing. The study directly supports Saudi Arabia’s Vision 2030, which requires the development of the sustainability of SMEs. Finally, the study addresses the gaps in the integrated model, providing empirical evidence from a developing context.

1. Introduction

In today’s digital and knowledge-driven economy, developing business intelligence systems (BISMs) and organizational sustainability (OS) are substantial challenges for organizations. In this way, the development of BISMs and OS is massively possible through knowledge management practices, such as knowledge acquisition (KAG), knowledge dissemination (KDM), and knowledge responsiveness (KRN) [1,2]. More specifically, these practices are the substantial and influential enablers which make organizations strong and successful in achieving their goals and objectives [1,2,3]. KAG is a key construct that enhances sustainable performance, decision making, and innovation, leading to sustainable performance [4,5,6]. Likewise, KDM underlines the organization’s knowledge distribution process, where it improves learning self-efficacy and task performance [5,7]. The final construct of knowledge management practices (KRN) strengthens the organization and empowers it to adapt to market demands, technological advancements, and competitive pressures [5,8]. Apart from that, entrepreneurial leadership (ELP) also plays its direct and indirect contribution in developing OS, where it generates innovative ideas, envisions and pursues new market opportunities, and solves the problems of the organizations with a massive creativity [9,10,11].

The domain literature demonstrates the several factors such as support learning, innovation, decision making, internal and external knowledge, knowledge sharing, knowledge extraction and use, knowledge management processes, ELP, agility, technical knowledge, social networks, organizational learning and strategic agility, responsiveness, knowledge management practices (KAG, KDM, and KRN), knowledge-based view, competitive advantage, collaboration and capability building, etc., forecast BISM and OS, and performance [1,3,12,13,14,15]. In the same manner, knowledge management, ethical values, decision-making processes, dynamic environments, strategic foresight and ethical integrity, visionary and opportunity-oriented practices, trust and organizational agility, etc., also affect the ELP [16,17,18,19].

However, the earlier literature leaves significant gaps, which lack an integrated model that connects knowledge management (KAG, KDM, and KRN) with BISMs and OS, as well as the dual role (both direct and indirect) of ELP between BISMs and OS. Furthermore, with the knowledge-based view (KBV) as its foundation, the literature still lacks empirical evidence to support this type of model. Contextually, Saudi Arabian SMEs are least concentrated, despite the country’s ongoing economic diversification efforts under Vision 2030, where the government of Saudi Arabia aims to make its country a knowledge-based economy, foster entrepreneurship, drive digital transformation, and implement BISM, which bring sustainable growth [20,21]. Thus, keeping to these gaps and deficient evidence of Saudi Arabian SMEs, the researcher raised the following questions:

• RQ1. How do knowledge management practices (KAG, KDM, and KRN) affect BISMs and OS in Saudi Arabia’s SMEs?
• RQ2. How do BISMs affect OS and ELP in Saudi Arabia’s SMEs?
• RQ3. How does ELP mediate the link between BISMs and OS in Saudi Arabia’s SMEs?

The study aims to investigate the role of knowledge management practices in developing BISMs and OS, along with the mediating contribution of ELP between BISMs and OS in SMEs of Saudi Arabia. The study contributes to an inclusive understanding of knowledge management, BISMs, and ELP in enhancing OS. This study advances the theoretical knowledge by bridging concepts from knowledge management, BISMs, and leadership within the KBV model, which offers a novel perspective on the intangible and technological resources network to boost sustainability. Practically, the study provides valuable insights for SME managers and policymakers by recognizing key levers, i.e., effective knowledge practices and leadership development, which can increase the strategic use of BISMs to accomplish long-term sustainability goals. This contribution is particularly significant for emerging economies, where controlling internal capabilities is crucial for competitive advantage and growth.

The structure of the paper is based on the following: apart from this introduction section, the Section 2 offers the literature review and theoretical underpinning, the Section 3 is hypothesis development, the fourth is methods, the Section 5 is analysis, the sixth is discussion and conclusion, and the final section is managerial implications, limitations, and future research avenues.

2. Literature Review and Theoretical Underpinning

2.1. Knowledge Management Practices

Knowledge management practices are the best practices that make organizations strong and successful in achieving their goals and objectives. Core practices such as knowledge acquisition (KAG), knowledge dissemination (KDM), and knowledge responsiveness (KRN) are recognized as the massive practices that bring sustainability and performance to organizations.

KAG shows an organization’s ability to identify external knowledge to augment its development. An organization that values employees’ attitudes and opinions boosts an internal knowledge-sharing culture through KAG [5,8]. KAG is a core construct that enhances sustainable performance, decision making, and innovation. KAG is a critical antecedent to sustainable performance in sustainability-oriented manufacturing SMEs, often working through KDM and application to create environmental and operational benefits [4,22]. It also contributes significantly to green performance when strategically aligned with entrepreneurial orientation and resource orchestration [6]. From a technological standpoint, KAG systems and business intelligence tools facilitate efficient decision making and real-time knowledge integration, especially in virtual organizations and automated manufacturing environments [1,23,24]. Social media-enabled mentoring fosters tacit KAG, reinforcing learning in sustainable organizations through social interaction and organizational support [2]. Furthermore, KAG supports corporate entrepreneurship and innovation by enabling the development of knowledge-based resources in SMEs [3], while external KAG promotes innovation by bridging environmental changes with internal capabilities [25].

KDM is a vital knowledge management practice that underlines the organization’s knowledge distribution process. It is developed through digital platforms, while written communication standardizes knowledge sharing [5,8]. Among business educators, KDM improves learning self-efficacy and task performance [7]. KDM transforms knowledge into practical outcomes, specifically in sustainability, health, and organizational performance. In the public health domain, KDM is the process that ensures that research findings are aligned with stakeholder needs and contexts, thereby promoting sustainable and equitable health interventions [26]. In SMEs, KDM appears to be a mediating factor that develops the link between KAG and application, enabling the internal transfer of critical knowledge and ultimately leading to enhanced sustainable performance [4]. Similarly, in sustainable development, KDM is facilitated through knowledge management systems and assists organizations in disseminating SDG information [27]. Furthermore, the social media platforms, Twitter and LinkedIn, are practical tools for disseminating sustainability-related knowledge. This massively enhances community learning and awareness through interactive and communicative channels [28].

Similarly, KRN is an essential factor that strengthens the organization and allows it to actively apply acquired knowledge in adapting to market demands, technological advancements, and competitive pressures [5,8]. Likewise, when supported by an enabling organizational culture, knowledge management practices nurture environmental responsiveness, underscoring KRN as a critical component of adaptive capability [29]. Strategic orientation has a moderating contribution in bridging the connection between knowledge translation into responsive actions and the dynamic nature of KRN [30]. Among knowledge-intensive services, responsiveness is associated with the skills and adaptiveness of knowledge workers [31]. Furthermore, KRN balances local agility with global integration in multinational corporations through effective cross-site knowledge sharing [32].

2.2. Business Intelligence System (BISM)

A BISM is an integrated technology-driven system that enhances decision making, operational efficiency, and business performance by gathering, analyzing, and disseminating critical business data [33,34]. BISMs significantly support knowledge management practices where they enable the creation, sharing, and utilization of organizational knowledge [35], and when delivered via SaaS models, they facilitate scalable and remote KAG in virtual organizations [24]. A BISM is a substantial construct that brings innovation, competitiveness, and development to the markets [13]. It is also valuable in making rational managerial decisions [36]. In the banking sector context, a BISM assists in overcoming risk, which ultimately brings effectiveness and success [37]. Ref. [38]’s study demonstrates the role of a knowledge-oriented framework in enhancing the quality of BISMs [39,40]. The system dynamics approach has gained significant traction as a robust methodological approach. The utility of system dynamics plays a positive role in developing dynamic organizational theories [41]. Organizational systematic reviews further reinforce the methodological value of the system dynamics approach in various domains and contexts. Ref. [42]’s study highlights the role of system dynamics in sustainable urban development by modelling socio-economic and environmental interconnections. It also works as an effective instrument, bringing healthy performance in measurement research, processes, and the assessment of long-term outcomes. System dynamics assist in developing preventive strategies and help control several issues, such as delays and cost overruns [43,44,45].

2.3. Entrepreneurial Leadership (ELP)

ELP is an essential factor connected with leaders’ capability to generate novel ideas with massive creativity. This assists organizations in resolving problems with a rational leadership approach [9,11]. According to the assessment of refs. [10,46], ELP positively predicts visionary thinking, digital transformation, and operational performance in the SMEs. The factors such as ELP and ethical behaviour positively enhance performance among employees [47]. In emerging markets, ELP is predicted by cultural and institutional dynamics [48]. In the empirical contribution of refs. [18,49], ELP positively enhances OS and a knowledge-sharing culture. Likewise, there is a substantial predictive effect of ELP on job crafting, enhancing commitment, and reducing turnover intention among millennial employees [50]. ELP is a dynamic and multidimensional capability which creates opportunity and innovation [11].

2.4. Organizational Sustainability (OS)

OS is a very significant construct that consists of social, economic, and environmental performance [51,52]. In the development of OS, knowledge management is very prominent, enhancing long-term organizational success [49,53]. Additionally, buyer-driven knowledge transfer significantly enhances sustainability by improving suppliers’ operational efficiency and promoting eco-friendly practices [54]. Integrating emerging technologies like blockchain with knowledge management can enhance transparency, trust, and operational efficiency, henceforth supporting sustainable practices [55]. Further, a BISM organizes and makes data-informed decisions, contributing to economic and environmental sustainability [56]. In the same respect, creativity is enhanced by knowledge sharing and systems thinking, which ultimately generate innovative solutions that contribute to the sustainability of organizations [53]. Finally, ethical ELP boosts organizational trust, a core component for achieving long-term sustainability and sustainable behaviour [57].

In the literature, there are several factors such as knowledge management practices (KAG, KDM, and KRN), support learning, innovation, decision making, internal and external knowledge, knowledge sharing, knowledge extraction and use, knowledge management processes, ELP, agility, responsiveness, knowledge-based view, competitive advantage, collaboration and capability building, technical knowledge, social networks, organizational learning, strategic agility, etc. which predict BISMs and OS [1,3,6,12,13,14,15,23,24,58,59,60,61]. Likewise, ELP is also predicted by several factors, i.e., visionary and opportunity-oriented practices, knowledge management, ethical values, decision-making processes, dynamic environments, trust, organizational agility, strategic foresight, and ethical integrity [16,17,18,19,57].

The domain literature highlights several gaps that remain unaddressed in the existing literature. Notably, there is a lack of an integrated model that systematically connects the dimensions of knowledge management, namely KAG, KDM, and KRN, with BISMs and OS [52,55]. Furthermore, the dual role (both direct and indirect) of ELP in influencing BISMs and OS has not been sufficiently explored [11,49,62]. Contextually, these relationships remain empirically underexamined within the SME sector of Saudi Arabia, highlighting a significant research gap. This study proposes a comprehensive model (Figure 1) that consolidates critical constructs, i.e., KAG, KDM, KRN, BISMs, ELP, and OS, within a unified model to address these gaps. The model of the study is founded on the KBV, which underpins a comprehensive research model that suggests that leadership affects the adoption of BISMs and, ultimately, OS. According to KBV, knowledge assets, specifically KAG, KDM, and KRN, are recognized as strategic resources that enhance organizational performance when properly managed [63,64]. BISMs, in this context, are the stronger enablers of knowledge utilization which empower firms to analyze data, enhance decision making, and drive performance improvements [36,38].

3. Hypothesis Development

3.1. Knowledge Acquisition (KAG), Business Intelligence Systems (BISMs), and Organizational Sustainability (OS)

The connection between KAG and BISMs is positive and significant in the literature, where both support learning, decision making, and innovation [24,58]. In virtual and distributed settings, Saas-based BISMs improve the access to internal and external knowledge, enabling continuous learning and knowledge sharing [24]. The empirical studies of refs. [1,23] suggest that a BISM improves strategic decisions and managerial practices by empowering better knowledge extraction and use. BISMs contribute to capturing both tacit and explicit knowledge, which positively facilitates knowledge management processes [12,58]. In advanced environments, i.e., Industry 4.0, BISMs, especially those integrated with predictive analytics and simulation, aid in acquiring forward-looking knowledge, further boosting agility and responsiveness [14,59]. Conceptually, KAG is a fundamental element of intelligent systems and is essential for adequate decision support [65,66]. Additionally, on the grounds of the resource-based view (RBV) and knowledge-based view (KBV), KAG, when supported by a BISM, positively contributes to competitive advantage and organizational performance [3,67].

Similarly, KAG positively drives OS, innovation, and long-term performance [22,52]. Ref. [6]’s study claims that entrepreneurial orientation and resource orchestration optimize green knowledge acquisition, positively and significantly enhancing sustainable performance. Additionally, external knowledge sources, i.e., buyer-driven knowledge transfer [54] and technical knowledge from partnerships [60], massively assist firms in aligning with sustainability goals by enhancing their environmental and operational practices. The social dimension is also emphasized in the studies by refs. [2,68], highlighting that social networks and mentoring, enabled by digital platforms, facilitate KAG. In technologically advanced contexts, innovations, i.e., green and blockchain technologies and green KAG strategies, substantially nurture corporate sustainability performance [55,69]. Likewise, leadership reinforces this connection, as entrepreneurial and knowledge-oriented leadership styles mediate the link between KAG and sustainable outcomes [18]. Furthermore, integrating knowledge management with environmental awareness and innovation boosts green practices, especially in SMEs [70].

Consequently, KAG is an essential component of knowledge management practices. However, its effect on both BISMs and OS still needs further confirmation, especially in the presence of ELP. Thus, the researcher developed the following hypotheses:

H1a. 

KAG positively enhances BISMs in SMEs.

H1b. 

KAG positively enhances OS in SMEs.

3.2. Knowledge Dissemination (KDM), Business Intelligence Systems (BISMs), and Organizational Sustainability (OS)

KDM is a critical element of knowledge management that empowers the transformation of insights into organizational actions and BISMs [35,58]. The factors such as BISMs and knowledge management processes positively enhance organizational responsiveness and performance [71]. Scholars like [72,73] demonstrate the contribution of KDM in developing financial knowledge systems and BISMs. According to [13], the role of BISMs is supporting dynamic dissemination models that adapt to organizational needs, while [61] validate that BIS-facilitated knowledge flows from drive brand innovation. Furthermore, ref. [74] propose integrative frameworks where a BISM stores and analyzes data and systematizes disseminating evidence-based insights, making decision making more collaborative and data-driven.

KDM is also a vital factor which promotes OS. KDM enables the transfer of sustainability-related knowledge among employees, departments, and external stakeholders, enabling informed decision making and cohesive action [26,75]. According to [4], KDM, KAG, and application directly contribute to manufacturing SMEs’ sustainable performance. Similarly, [15]’s study provides a framework in which sustainability is rooted in strategic planning through robust knowledge management systems that accentuate dissemination for enabling green innovation. KDM also supports operationalizing sustainable development goals (SDGS), demonstrated by [27], through structured knowledge management systems that spread awareness and drive collective action. Likewise, domain scholars like [76,77] suggest the mediating role of knowledge management, especially dissemination in translating organizational learning into sustainable performance, particularly in sustainability-oriented projects. In the digital age, platforms like LinkedIn and Twitter have also emerged as tools for sustainability-related KDM and to enhance public and organizational awareness [28]. Henceforth:

H2a. 

KDM positively enhances BISMs in SMEs

H2b. 

KDM positively enhances OS in SMEs.

3.3. Knowledge Responsiveness (KRN), Business Intelligence Systems (BISMs), and Organizational Sustainability (OS)

KRN’s organizational ability to rapidly sense, interpret, and respond to internal and external knowledge signals has made a massive contribution to enhancing the effectiveness of BISMs [78]. The investigation of [79] demonstrates a positive connection between KRN and BISMs, which eventually enhances firm performance. The service responsiveness improves business intelligence and market integration [80]. In the notion of [72], knowledge sharing and BISMs are connected positively and enhance organizational innovation. A BISM supports operational excellence by equipping organizations with KRN and fulfilling the marketing demands [81].

Similarly, KRN significantly brings sustainability to organizations [29]. Factors such as systems thinking and knowledge sharing make a massive and significant contribution to developing creativity and firms’ sustainability [53]. Stakeholder pressure and visibility push firms and environmental responsiveness which are positively and significantly connected to each other [82]. In the perception of [83], knowledge management (KRN) and supply chains boost innovation, resilience, and sustainability in firms.

Consequently, BISMs and OS are predicted by KRN. Nonetheless, in relation to ELP with dual roles (predictor and mediator), the contribution of KRN warrants further empirical validation, particularly within the SME context in Saudi Arabia. Henceforth:

H3a. 

KRN positively enhances BISMs in SMEs.

H3b. 

KRN positively enhances OS in SMEs.

3.4. Business Intelligence Systems (BISMs), Entrepreneurial Leadership (ELP), and Organizational Sustainability (OS)

ELP and BISMs have massive prominence and reputation in developing innovation and OS [84,85]. A BISM boosts and nurtures leaders by providing opportunities and capabilities, which make them substantially competitive against their rivals in the market [86]. According to [10], entrepreneurial leaders are significant agents of society who play their roles in digital transformation and the implementation of BISMs in strategic and operational frameworks. The linkages between BISMs and performance are mediated by proactive business responses [46]. The empirical investigations of [48,87] suggest the meaningful role of ELP in developing BISM adoption, organizational agility, and innovation.

Similarly, a BISM substantially advances OS, enabling data-driven environmental, social, and governance decision making. It provides the tools to collect, integrate, and analyze socio-environmental data, therefore, enabling organizations to monitor sustainability performance effectively [88,89]. These systems empower organizations to operationalize sustainability by providing real-time dashboards, predictive analytics, and sustainability indicators which guide corporate actions toward long-term ecological and social outcomes [90,91]. Furthermore, BISMs contribute to managing sustainability strategies during digital transformation and the Fourth Industrial Revolution (IR 4.0) and empowers more adaptive, innovative, and resilient organizational behaviour [56,92]. BISMs have been confirmed to support sustainability in various sectors, including commercial banking [37] and higher education [93]. In applied contexts, i.e., in the Iraqi cement industry, BISMs have shown measurable impacts on advancing environmental sustainability goals [94]. Moreover, eco-business intelligence instruments effectively integrate environmental accountability into core business processes [95,96].

According to the above literature, it is clear that a BISM is a positive and significant enabler of ELP and OS. Nevertheless, based on the need of confirmation of these connections in SMEs, the researcher proposed the following:

H4a. 

BISMs positively enhance ELP in SMEs.

H4b. 

BISMs positively enhance OS in SMEs.

3.5. Entrepreneurial Leadership (ELP) and Organizational Sustainability (OS)

ELP significantly contributes to OS by nurturing innovation, strategic agility, and long-term value creation through visionary and opportunity-oriented practices. This leadership style drives sustainability by implanting knowledge management and ethical values into decision-making processes, which are critical for achieving enduring performance in dynamic environments [18,57]. Entrepreneurial leaders act as catalysts for integrating sustainability into business models. This encourages risk-taking, empowers employees, and aligns organizational goals with social and environmental priorities [17,19]. Several scholars like [49,97,98] demonstrate that ELP enhances trust and organizational agility, which are found to be key enablers of sustainable operations in sectors, i.e., education, social enterprises, and SMEs. Additionally, ethical ELP contributes to improved organizational performance, where it establishes a culture of responsibility and stakeholder inclusivity [47,99]. In this way, the domain literature suggests that ELP, when combined with sustainability-oriented traits, i.e., strategic foresight, empowerment, and ethical integrity, enhances high-performing, adaptive, and socially responsible organizations [16].

Consequently, ELP is a predictor of OS; however, its dual contribution as both a predictor of OS and an outcome of BISM requires further confirmation. Thus:

H5. 

ELP positively enhances OS in SMEs.

3.6. Entrepreneurial Leadership (ELP) as a Mediator

ELP is a substantial construct that plays dual roles (direct and mediating) in developing the connection between BISMs and OS. BISMs support data-driven decision making and strategic foresight, but their effectiveness in promoting long-term sustainability depends heavily on leaders transforming this intelligence into innovative and sustainable practices [18,100]. ELP, characterized by proactiveness, innovation, and adaptability, is instrumental in translating the analytical capabilities of BISMs into strategic creativity that supports sustainability goals [11,101]. There is moderating and mediating potential of ELP in improving employee outcomes, which contributes indirectly to sustainability [50]. ELP transforms BISM-driven insights into sustainable action by connecting internal capabilities with external demands, eventually reinforcing the sustainability performance of organizations [11,18,50,100,101,102,103].

As a result, the domain literature consistently demonstrates a direct association between ELP, BISMs, and OS, and its mediating role in developing the connection between BISMs and OS. Hence, based on these consistent associations and lack of evidence from SMEs of Saudi Arabia, the following hypothesis is proposed:

H6. 

ELP mediates the relationship between BISMs and OS in SMEs.

4. Research Methods

4.1. Design and Sample

To keep the research consistently confidential and appropriate while preserving the respondents’ anonymity, the researcher used a quantitative approach, which has recognition in management, social, and business research [104]. These methods continue to support accumulating attitudes and behavioural responses while serving to help researchers and provide resources [105]. In the literature concerned with the domains of sustainability, knowledge management, and BISMs and ELP, several scholars like [3,9,12,13,14,51,58,60] applied the same strategy to explore the problems.

The study’s context is Saudi Arabia’s SMEs. There are several reasons behind the selection of these SMEs, keeping in view the ongoing economic diversification efforts under Vision 2030 and emphasizing knowledge-based economies, entrepreneurship, digital transformation, and BISMs to support sustainable growth and strategic leadership in SMEs [20,21].

With regard to the respondents of the study, the researcher selected CEOs, senior managers, and knowledge or business intelligence officers as justifiable and suitable due to their massive responsibility in driving strategic initiatives by aligning with Vision 2030. SMEs massively adopt knowledge-based practices and digital tools to compete and sustain themselves in the market [106,107]. In this way, these top-level executives and managers are the best individuals who can offer a real picture of the organization [108].

4.2. Method Bias Test

The study applied multi-phase surveys by conducting consecutive partitioning of the measurement items under each construct of a circumstance, i.e., constructs (e.g., KAG, KDM, KRN, BISMs, ELP towards OS) may create the chances of common method bias on the collected data [109]. In this regard, the researcher applied the common latent factor to reduce the common method bias, following the recommendations of [110,111]. This method captures the communal variance in all the indicators in the confirmatory factor analysis common latent factor (CLF) stage. In this way, the researcher examined the differences in loadings with and without CLF. As a result, the values of loadings appear to be below 0.18. Hence, these results ensured that common method bias does not exist in this data set.

4.3. Data Collection Procedure

The researcher applied a survey questionnaire (administered in English) to obtain the respondents’ responses. The researcher ensured the authenticity of the survey tool by conducting a pilot test, where 30 cases were gathered, as this sample size for piloting was adequate to validate the survey instrument [112]. Due to extensive criticisms of Cronbach’s Alpha as regards its sensitivity to the number of items and assumptions of tau-equivalence (unrealistic loadings) [113,114], the researcher applied the composite reliability (CR) and average variance extracted (AVE) along with model fit indices, such as CFI, GFI, AGFI, and RMSEA, to support the reliability of and validity of the instrument. The CR, AVE, and model fit indices (e.g., CFI, GFI, AGFI, and RMSEA) were within the satisfactory ranges (see

Table 1. Results of pilot test [n = 30].

Constructs	No. of Items	CR	AVE	CFI	GFI	AGFI	RMSEA
1.Organizational sustainability [OS]	20	0.718	0.529	0.912	0.899	0.903	0.0309
2.Business intelligence system [BISM]	10	0.760	0.590
3.Entrepreneurial leadership [ELP]	8	0.899	0.612
4.Knowledge acquisition [KAG]	6	0.787	0.658
5.Knowledge dissemination [KDM]	5	0.803	0.692
6.Knowledge responsiveness [KRN]	5	0.772	0.571

Source: authors’ own calculation. Note(s): CR, composite reliability; AVE, average variance extracted; CFI, comparative fit index; GFI, goodness-of-fit index; AGFI, adjusted goodness-of-fit index; RMSEA, root mean square error of approximation.

). The researcher also ensured the validity. For this purpose, the researcher sent a few survey forms to academic and industry experts. This assumption ensured the validity of the survey tools by verifying the content, language, and layout design of the survey items.

The researcher applied online and offline survey techniques to gather the data using convenience sampling due to difficulty retrieving the framework and figuring out the total number of CEOs and managers of Saudi Arabia’s SMEs with the specific characteristics of the targeted population. In this way, the researcher visited SMEs across Saudi Arabia and emailed the survey forms as online survey links via WhatsApp, X platform, and SMEs’ LinkedIn pages. The researcher also cared about the ethical protocols of the respondents, where they were completely assured of their anonymity and confidentiality, and a cover letter outlining the study’s objectives was provided. In total, 600 surveys were distributed and sent, where in return, the researcher received 360 in a raw shape with a response rate of 60%. After data cleaning and screening, the researcher discarded four cases, and finally, 356 cases were utilized for the final analysis.

The researcher used G*Power 3.1, which is the best software and ensures the adequacy of the required sample size [115]. In this way, the researcher applied five main predictors to decide the effect size, where the test proposed the requirement of 138 samples. Thus, this 356-sample size is appropriate for the results.

4.4. Measurement Scales

The researcher adopted all the surveys from the field literature (KAG measured on six items; KDM measured on five items; and KRN measured on five items), and adopted from [8]. The BISM being assessed on ten items was adopted from [33]. Similarly, ELP was measured on eight items adopted from the study of [9]. Finally, the researcher measured OS based on 20 items with three dimensions, social (6 items), environmental (8 items), and economic (6 items), as adopted by [51] and assessed all the items of the scale on a five-point Likert scale, ranging from one (strongly disagree) to five (strongly agree) (

Table 2. Details of survey measurements.

Construct	Definition	Items Details	Scale [Five-Point Likert Scale]	Source
Knowledge acquisition [KAG]	--- gathering and integrating valuable information from employees, market changes, financial systems, technology expertise, international partnerships, and market surveys.	kag1: Organizational values, employees’ attitudes, and opinion.	strongly disagree = 1; strongly agree = 5	[8]
		kag2: The organization has well-developed financial reporting systems.	=
		kag3: The organization is sensitive to information about changes in the market place.	=
		kag4: Science and technology human capital profile.	=
		kag5: The organization works in partnership with international customers.	=
		kag6: The organization obtains information from market surveys.	=
Knowledge dissemination [KDM]	--- effective information sharing within an organization through different sources, i.e., technology and written communication.	kdm1: Market information is freely disseminated.	strongly disagree = 1; strongly agree = 5	[8]
		kdm2: Knowledge is disseminated on-the-job.	=
		kdm3: Use of specific techniques to disseminate knowledge.	=
		kdm4: The organization uses technology to disseminate knowledge.	=
		kdm5: The organization prefers written communication.	=
Knowledge responsiveness [KRN]	--- the organization’s ability to adapt and act on customer needs, market trends, technological changes, competitor actions, and emerging opportunities.	krn1: We respond to customers.	strongly disagree = 1; strongly agree = 5	[8]
		krn2: We have well-developed marketing functions.	=
		krn3: We respond to technology.	=
		krn4: We respond to competitors.	=
		krn5: Our organization is flexible and opportunistic.	=
Business intelligence system [BISM]	--- enhances coordination, reduces costs, improves responsiveness, streamlines processes, boosts productivity, and supports efficient decision making, ultimately optimizing operations and market performance.	bism1: BISM improved the coordination with business partners/suppliers.	strongly disagree = 1; strongly agree = 5	[33]
		bism2: BISM reduced the cost of transactions with business partners/suppliers.	=
		bism3: BISM improved the responsiveness to/from suppliers.	=
		bism4: BISM intelligence improved the efficiency of internal processes.	=
		bism5: BISM increased staff productivity.	=
		bism6: BISM reduced the cost of effective decision making.	=
		bism7: BISM reduced operational costs.	=
		bism8: BISM reduced customer return handling costs.	=
		bism9: BISM reduced marketing costs.	=
		bism10: BISM reduced time-to-market products/services.	=
Entrepreneurial leadership [ELP]	--- a leadership style characterized by visionary thinking, innovation, risk taking, and a strong passion for driving change, where leaders inspire and challenge others to pursue creative solutions, develop new products, and rethink traditional business practices.	The leader of this company… elp1: often comes up with radically improved ideas for the products that we are selling	strongly disagree = 1; strongly agree = 5	[9]
		elp2: often comes up with ideas of completely new products that we could sell.	=
		elp3: takes risks.	=
		elp4: has creative solutions to problems.	=
		elp5: demonstrates passion for his/her work.	=
		elp6: has a vision for the future of our business	=
		elp7: challenges and pushes us to act in a more innovative way.	=
		elp8: wants us to challenge the current ways that we do business	=
Organizational sustainability [OS]	--- the ability of an organization to operate in a manner that ensures long-term viability by balancing and integrating economic efficiency, environmental responsibility, and social equity in its strategies, operations, and stakeholder relationships.	osso1: The sustainability management system (SMS) is clearly documented and understood.	strongly disagree = 1; strongly agree = 5	[51]
		osso2: Staff are informed and trained about the natural and cultural heritage of the local area.	=
		osso3: The organization participates in partnerships between local communities, NGOs, and other local bodies where these exist.	=
		osso4: The organization has identified groups at risk of discrimination, including women and local minorities.	=
		osso5: The organization seeks to bring innovative green products and services to the market.	=
		osso6: The organization often uses eco-labels on packaging and shows them on their corporate websites.	=
		en1: Records of these programmes are listed and managed.	=
		en2: There is an environmental awareness-raising plan.	=
		en3: Native and endemic plants obtained from sustainable sources have been used in landscaping and decoration, avoiding exotic and invasive species.	=
		en4: The organization uses green procurement criteria.	=
		en5: The organization holds environmental protection awareness programmes for the community.	=
		en6: The total direct and indirect greenhouse gas emissions are monitored and managed.	=
		en7: Chemicals, especially those in bulk amounts, are stored and handled in accordance with appropriate standards.	=
		en8: The organization is aware of, and complies with, relevant laws and regulations concerning animal welfare.	=
		ec1: SMS includes a process for monitoring continuous improvement in sustainability performance	=
		ec2: Energy used per tourist/night for each type of energy is monitored and managed.	=
		ec3: Water saving equipment is regularly maintained and is efficient.	=
		ec4: Equipment and facilities for air quality are monitored and maintained.	=
		ec5: A solid waste management plan is in place.	=
		ec6: The organization uses and promotes the usage of recyclable water or grey water in other operations (e.g., watering trees).	=

Source: adopted from the domain literature.

).

5. Analysis

5.1. Respondents’ Profile

The demographic profile of the respondents indicates a majority of males (n = 287 or 80.62%) compared to females (n = 69 or 19.38%). The age factor indicates that a majority of the respondents were under fifty-five years old (n = 143 or 40.2%), while the minority were fifty-five years old and above (n = 24 or 6.7%). Regarding education level, most of the respondents had a bachelor’s degree (n = 200 or 56.2%), while only 6.7% (n = 24) had a doctorate degree. The firm size indicator demonstrates that most of the respondents (n = 164 or 46.1%) were small firms, while only 18.0% (n = 64) were micro firms. Concerning the firms’ age, most firms (n = 150 or 42.1%) were 5–10 years old, while only 25% (n = 89) were less than five years old. A most significant portion of the respondents (n = 99 or 27.8%) had contributed from services, while only 10.1% (n = 36) were from other sectors such as logistics and construction, etc. Finally, the level of digitalization/BI use indicator suggests that a majority of the firms had basic adoption of digitalization (n = 157 or 44.1%), while only 11.0% (n = 39) had no adoption (see the further details in

Table 3. Respondents’ profile (356).

Indicator	Category	Frequency (%)
Gender	Male	287(80.62)
	Female	69(19.38)
Age (years)	25–34 years	114 (32.0)
	35–44 years	143 (40.2)
	45–54 years	75 (21.1)
	55+ years	24 (6.7)
Educational level	Diploma	25 (7.0)
	Bachelor’s degree	200 (56.2)
	Master’s degree	107 (30.1)
	Doctorate	24 (6.7)
Firm size	Micro (1–9 employees)	64 (18.0)
	Small (10–49 employees)	164 (46.1)
	Medium (50–249 employees)	128 (36.0)
Firm age	Less than 5 years	89 (25.0)
	5–10 years	150 (42.1)
	More than 10 years	117 (32.9)
Industry type	Manufacturing	78 (21.9)
	Services	99 (27.8)
	Information technology	68 (19.1)
	Retail and trade	75 (21.1)
	Others (e.g., logistics, construction)	36 (10.1)
Level of digitalization/BI use	No adoption	39 (11.0)
	Basic (limited use)	157 (44.1)
	Moderate (partial integration)	111 (31.2)
	Advanced (fully integrated)	49 (13.8)

Source: researchers’ own data collection.

).

5.2. Measurement Model

Firstly, the researcher ensured the measurement of the model, where the essential components of the convergent validity were noticed, i.e., loading values, CR, and AVE. The researcher maintained threshold values for loadings and CR at >0.70 and AVE at >0.50 [116,117]. As provided in

Table 4. Measurement model [loading, CR, AVE and Cronbach’s α for the full model].

Construct	Item Code	Factor Loadings [>0.7]	CR [>0.7]	AVE [0.5]	Alpha Reliability (α) [>0.7]
Knowledge acquisition [KAG]	kag1	0.872	0.960	0.716	0.801
	kag2	0.858
	kag3	0.846
	kag4	0.833
	kag6	0.821
Knowledge dissemination [KDM]	kdm1	0.845	0.909	0.667	0.809
	kdm2	0.831
	kdm3	0.829
	kdm4	0.798
	kdm5	0.780
Knowledge responsiveness [KRN]	krn1	0.872	0.919	0.695	0.837
	krn2	0.858
	krn3	0.837
	krn4	0.818
	krn5	0.780
Business intelligence system [BISM]	bism1	0.867	0.934	0.668	0.799
	bism2	0.848
	bism3	0.839
	bism4	0.810
	bism6	0.792
	bism7	0.783
	bism9	0.776
	bism10	0.751
Entrepreneurial leadership [ELP]	elp1	0.862	0.935	0.674	0.829
	elp2	0.843
	elp4	0.833
	elp5	0.820
	elp6	0.805
	elp7	0.798
	elp8	0.781
Organizational sustainability [OS]	osso1	0.893	0.914	0.662	0.887
	osso2	0.882
	osso3	0.873
	osso4	0.861
	osso6	0.855
	osen1	0.850
	osen2	0.836
	osen3	0.821
	osen5	0.819
	osen7	0.803
	osen8	0.793
	osec1	0.789
	osec2	0.773
	osec3	0.760
	osec4	0.756
	osec6	0.731

Notes: CR = composite reliability; AVE = average variance extracted; AVE for the second-order model =averaging the squared multiple correlations for the first-order indicators; all the factor loadings of the individual items are statistically significant (p < 0.01); excluded items = kag5, bism5, bism8, elp3, osso5, osen4, osen6, osec5.

, the researcher found the values of loadings (from osec6 0.731 to osso1 0.893), where almost all items appeared above loadings of >0.70, except for the items such as kag5, bism5, bism8, elp3, osso5, osen4, osen6, and osec5 that do not appear with qualifying scores or loading values of >0.70. Therefore, the researcher decided to exclude these items to avoid any misleading results. Additionally, the value of AVE for all the constructs (from OS 0.662 to KAG 0.716) appeared to be above the required value (>0.50). Similarly, the values of CR for all the constructs (from OS 0.914 to KAG 0.960) also appeared to be above 0.70. Finally, the researcher ensured that the values of Cronbach’s alpha (from BISM 0.799 to OS 0.887) were within fair values (>0.70) [117]. Thus, all these parameters ensured good convergent validity.

Secondly, the researcher calculated the discriminant validity, confirming the extent to which a degree was not a reflection of some other variable. In this way, the researcher applied the square root of the AVE and found an adequate correlation of the dependent variable with all the other constructs (from 0.761 to 0.818) [118], which indicates satisfactory discriminant validity (

Table 5. Discriminant validity by Fornell–Larcker criterion for the full model.

S. No	Factors	1 BISM	2 ELP	3 OS	4 KAG	5 KDM	6 KRN
1	BISM	0.803
2	ELP	0.382	0.775
3	OS	0.401	0.431	0.790
4	KAG	0.387	0.426	0.333	0.818
5	KDM	0.318	0.379	0.404	0.416	0.789
6	KRN	−0.219	0.232	0.300	0.383	0.318	0.761

KAG = knowledge acquisition; KDM = knowledge dissemination; KRN = knowledge responsiveness; BISM = business intelligence system; ELP = entrepreneurial leadership; OS = organizational sustainability.

).

5.3. Structural Model

Model fit indices: The researcher assessed the model fit indices to evaluate how well the hypothesized model represented the observed data, ensuring that the model demonstrated an acceptable level of fit before proceeding with further analysis [119]. The model fit well with the data, as indicated by the non-significant chi-square statistic (χ²/df = 2.929), below the recommended threshold of 3 and associated with a p-value greater than 0.05 [120]. Moreover, multiple fit indices confirmed the adequacy of the model, including GFI = 0.930; AGFI = 0.933, NFI = 0.948, CFI = 0.950, and RMSEA = 0.043, all of which meet or exceed commonly accepted benchmarks for good model fit [121,122] (see the details in

Table 6. Goodness of fit indices.

Model Fitness →	CMIN/df	GFI	AGFI	NFI	CFI	RMSEA
Model fit indices →	2.929	0.930	0.933	0.948	0.950	0.043
Required values →	<3 or p > 0.005	>0.90				<0.05

Notes: CMIN = χ²/chi-square/df; df = degrees of freedom; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; NFI = normed fit index; CFI = comparative fit index; RMSEA = root mean square error of approximation.

and Figure 2.

Maintaining the findings’ generalizability and model robustness is important [123]; thus, we added age, firm size, and industry type as control variables. Specifically, in AMOS, control variables ensure that the structural paths reflect true theoretical associations rather than spurious ones [124] (see Figure 2).

Hypothesis assessment: We applied structural equation modelling (SEM) to assess the projected hypotheses. The analysis confirmed a positive effect of KAG on BISMs and OS [(H1a = KAG→BISM = β = 0.072; p < 0.01) (H1b = KAG→OS= β = 0.440; p < 0.01)]. Hence, H1a-H1b are accepted. The KDM factor positively affects BISM and OS, which accepted the H2a-H2b [(H2a = KDM→BISM= β = 0.305; p < 0.01) (H2b = KDM→OS = β = 0.509; p < 0.01)]. Furthermore, the effect of KRN is found to be positive on OS but negative on a BISM [(H3a = KRN→BISM = β = −0.038; p < 0.01) (H3b = KRN→OS = β = 0.476; p < 0.01)]. Thus, H3a is rejected, and H3b is accepted. Furthermore, the analysis supported H4a-H4b by demonstrating the positive effect of a BISM on ELP and OS [(H4a = BISM →ELP = β = 0.258; p < 0.01) (H4b = BISM→OS = β = 0.287; p < 0.01)]. The data also support the final direct hypothesis by confirming the positive effect of ELP on OS (H5 = ELP→OS= β = 0.362; p < 0.01) (

Table 7. SEM analysis [direct paths].

H.No.	Relationships	Estimate β (Path Co-Efficient)	SE	CR (t-Value)	p-Value	Decision
H1a	KAG→ BISM	0.072	0.023	3.165	0.002	[√]
H1b	KAG→ OS	0.440	0.047	9.407	0.000	[√]
H2a	KDM→ BISM	0.305	0.042	7.235	0.000	[√]
H2b	KDM→ OS	0.509	0.075	6.900	0.000	[√]
H3a	KRN→ BISM	−0.038	0.067	0.570	0.569	[×]
H3b	KRN→ OS	0.476	0.125	3.872	0.000	[√]
H4a	BISM→ELP	0.258	0.063	4.042	0.000	[√]
H4b	BISM→ OS	0.287	0.032	9.013	0.000	[√]
H5	ELP→OS	0.362	0.097	3.705	0.000	[√]

Notes: SE = standard error; CR = critical ratio; significance level p < 0.01; KAG = knowledge acquisition; KDM = knowledge dissemination; KRN = knowledge responsiveness; BISM = business intelligence system; ELP = entrepreneurial leadership; OS = organizational sustainability; [√] = accepted; [×] = rejected.

and Figure 2).

With regard to mediating effects, the analysis confirmed a mediating contribution of ELP in developing the connection between BISMs and OS (H6 = BISM →ELP→OS= β = 0.101; p < 0.01) (

Table 8. SEM analysis [indirect paths].

H.No.	Relationships	Estimate β (Path Co-Efficient)	SE	CR (t-Value)	p-Value	Decision
H6	BISM→ELP→OS	0.101	0.031	3.225	0.001	[√]

Notes: SE = standard error; CR = critical ratio; significance level p < 0.01; BISM = business intelligence system; ELP = entrepreneurial leadership; OS = organizational sustainability; [√] = accepted; [×] = rejected.

and Figure 2).

6. Discussion and Conclusions

The study explored the effect of knowledge management practices on BISMs and OS, and ELP was also explored with a mediating effect in Saudi Arabia’s SMEs. The study’s findings confirmed a positive impact of knowledge management practices such as KAG and KDM on BISMs and OS. However, KRN has a positive effect on OS but an adverse impact on BISMs. These results are in line with several studies like [2,3,6,15,18,24,58,60,61,68,76,125]. However, they contradict those of [40,78,80], and [81]. These results demonstrate that in Saudi Arabia’s SMEs, knowledge management practices align or misalign with the structured, data-centric nature of a BISM versus the broader, adaptive demands of OS. KAG and KDM feed BISMs with rich, timely, and well-shared information, market surveys, employee insights, financial data, and technology-enabled sharing. On the contrary, KRN has a substantial and enormous contribution in the development of OS, but neither brings competition among customers nor creates opportunities in the business sphere. Still, it can undercut BISMs because rapid, ad hoc decision making inclines to bypass the slower, structured data analysis routines on which a BISM depends. Thus, while all three practices strengthen sustainability, only those that supply and circulate systematic knowledge reinforce BISMs, although highly opportunistic responsiveness can inadvertently weaken it.

Additionally, a BISM positively affects both ELP and OS, which is consistent with various previous studies [46,84,85,86,88,92,94]. These results demonstrate that a BISM enables better coordination with suppliers and partners, which boosts a stronger value chain connection and supports proactive leadership behaviours. It reduces transaction, marketing, operational, and decision-making costs, where a BISM empowers entrepreneurial leaders in re-allocating resources, pursuing innovation, and responding promptly to market opportunities. Concurrently, a BISM contributes to OS by refining the internal efficiency. It boosts staff productivity along with reducing the time to market for products and services. Furthermore, the system supports data-driven leadership decisions that balance short-term responsiveness with long-term development and align well with sustainability goals. In this way, it can be concluded that BISM is a substantial and influential factor that nurtures ELP and brings massive OS to SMEs.

ELP positively enhances OS. These results are in accord with several studies, like [17,18,19,49,57,97,98], who confirmed the positive connection between ELP and OS. The findings demonstrate that leaders of SMEs in Saudi Arabia generate radically new ideas and take calculated risks, leading to the enhancement of innovative green products and sustainability initiatives. Creativity assists in problem solving and overcomes complex sustainability challenges, i.e., waste management or reduction in greenhouse gas emissions. Additionally, entrepreneurial leaders encourage continuous improvement and push their organization toward adopting advanced sustainability management systems. Their efforts positively drive innovation and lead change, boosting community engagement, inclusivity, and environmental stewardship through the structured monitoring of energy and air quality. In this way, ELP is proven to be a substance for implementing sustainability in the organizational fabric, transforming sustainability from an acquiescence obligation into a premeditated and cultural priority, which confirms long-term viability and competitive advantage.

Finally, ELP mediates the link between BISMs and OS, which is also in line with the domain literature [11,18,100,101]. These results suggest that a BISM provides the data, tools, and efficiency needed to support sustainability efforts; the entrepreneurial leader interprets this intelligence, takes the initiative, and drives strategic action toward sustainable outcomes. A BISM enhances internal capabilities by improving coordination, reducing costs, increasing productivity, and accelerating decision making. However, these benefits alone do not guarantee sustainable practices unless they are channelled through visionary, innovative, and proactive leadership.

To sum up, the study’s overall results demonstrate a positive effect of knowledge management practices, such as KAG and KDM, on BISMs and OS. The impact of KRN on BISMs is negative but positive on OS. Furthermore, a BISM positively affects OS and ELP, and ELP also predicts OS. Finally, ELP mediates the link between BISMs and OS in Saudi Arabian SMEs.

7. Implications of the Research

7.1. Practical Implications

The study offers actionable visions for managers, policymakers, and academics. For SME managers, the study emphasizes the importance of formalizing knowledge acquisition and dissemination processes through structured training, cross-functional teams, and digital collaboration platforms to enhance BISMs. This study provides guidelines for managers of firms (specifically SMEs) to initiate leadership development programmes that promote entrepreneurial and critical thinking, which improve the success and progress of the firms. The study helps decision makers launch support programmes, such as subsidies or training grants, to enhance SMEs’ capacity to adopt and effectively utilize BISM tools. The study directly supports Saudi Arabia’s Vision 2030, providing guidelines and evidence on how SMEs drive sustainability, innovation, and economic diversification through the support of knowledge management practices, BISMs, and ELP.

7.2. Theoretical Implications

The study’s findings validate the KBV specifically in the Saudi Arabian SME context. Additionally, the study extends the KBV and empirically confirms that BISMs and ELP, both intangible resources, contribute to sustainable performance. The mediating contribution of ELP between BISMs and OS offers new theoretical insight into the KBV literature. Consequently, the research integrates and extends KBV theory, highlighting the connection between knowledge practices, intelligent systems, and leadership in shaping sustainability in the SME context. The study offers a valuable and constructive model integrating knowledge management practices, BISMs, ELP, and OS into one model. It provides a foundation for further research on how different dimensions of knowledge management interact with digital systems and leadership in SME contexts. The study also endorses the direct and indirect contribution of ELP, specifically in the context of SMEs in developing countries. Finally, the study’s findings enrich the depth of the literature by offering empirical evidence from a developing context.

8. Limitations and Future Research

The study is limited to a theory, applying only the KBV theory to underpin the theoretical framework. The modes of the study are quantitative, using only a single source of data collection (questionnaire). The study is restricted to a few constructs, such as KAG, KDM, KRN, BISMs, ELP, and OS, with the direct and indirect effect of ELP investigated. The study is restricted to SMEs in Saudi Arabia. Finally, the findings of the study are based on only 356 respondents.

Future studies should use other theories, such as the technology–organization–environment (TOE) framework, resource-based view (RBV), and the dynamic capabilities theory (DCT), with several constructs, i.e., personality traits, entrepreneurial intention, employee behaviours, performance, and human resources management (HRM). The mixed-method approach (qualitative and quantitative) must be used in future studies. The context of the study may be extended to other sectors, such as education and health. In the future, forthcoming researchers should develop a more explicit, multi-level framework to test these interactions systematically. Finally, the sample size must be increased to validate the results further.