Sage Journals: Discover world-class research

Abstract

This research endeavors to investigate the influence of Social Capital and Shared Leadership on both Digital Transformation and Firm Performance, as well as the impact of Digital Transformation on Firm Performance. A survey encompassing 111 Small and Medium-sized Enterprises (SMEs) situated in the Mekong Delta region of Vietnam was conducted. Utilizing Structural Equation Modeling (SEM) analysis, the study examined various facets of leadership style, including task orientation, relationship orientation, representative orientation, and participation in advancing the digital transformation endeavor. Results indicate that a task-oriented leadership approach has a detrimental effect on digital transformation. Conversely, social capital and shared leadership positively correlate with digital transformation and subsequently enhance firm performance. Noteworthy findings include the observation that while the influence of social capital on digital transformation lacks statistical significance, it plays a constructive regulatory role in mediating the relationship between digital transformation and Firm Performance, as well as in the association between shared leadership and firm performance. The study underscores the imperative for SMEs to capitalize on social capital and cultivate leadership styles conducive to fostering digital transformation, thereby augmenting Firm Performance.

Plain language summary

The impact of external social relationships and shared leadership style of enterprise managers on digital transformation and enterprise performance

1. Aims and purpose of the research: This study aims to explore the impact of social capital and shared leadership style on digital transformation and business performance; the promoting role of social capital on the relationship between shared leadership style and business performance, and between digital transformation and business performance. 2. Background of the research: Digital transformation helps businesses increase their competitive advantage, improve operational efficiency, and achieve business growth because it significantly changes the way the market operates, reducing the costs of searching, transporting, reproducing, trading, and finding new market opportunities. Especially for Vietnam, a developing country, businesses still have many limitations in terms of capital, technology, and management capacity. Taking advantage of external capital and building a suitable leadership style to promote the digital transformation process is a necessary requirement for development. 3. Methods and research design: The study tests the hypotheses and research model using the structural equation modeling (SEM) tool. To analyze the moderating role of SoC, the study conducts three steps: step 1 analyzes the relationships with the participation of SoC; step 2 analyzes under similar conditions to step one but without the participation of SoC; step 3 compares the results to evaluate the moderating role of SoC. The study was conducted with 222 respondents who were managers and IT officers of 111 enterprises in the Mekong Delta of Vietnam. 4. Results and importance: The research results show that external social capital increases the performance of SMEs. Sharing leadership style promotes the digital transformation process, increasing business efficiency. Although social capital does not affect digital transformation, positive external relationships enhance the positive impact of digital transformation on performance. With these results, SMEs in Vietnam should take advant.

Keywords

social capital shared leadership digital transformation firm performance SMEs

Introduction

Digital Transformation (DTr) is pivotal for nations seeking a competitive edge amid market competition (C. L. Chen et al., 2021). It enables businesses to bolster their advantage, enhance operational efficiency, and drive growth (C. L. Chen et al., 2021). Digital technology reshapes market dynamics, reducing costs and identifying opportunities (C. L. Chen et al., 2021). Consequently, organizations must adapt their practices and mindset to survive (Osmundsen et al., 2018). Despite its benefits, businesses encounter barriers such as technical obstacles and organizational culture (C. L. Chen et al., 2021; Hartl & Hess, 2017).

Vietnam is undergoing the Fourth Industrial Revolution, building a digital society based on a digital economy and digital governance. DTr brings forth numerous benefits, such as reducing societal costs, enhancing service quality, improving the efficiency of government machinery, and boosting business performance. Small and medium-sized enterprises (SMEs) play a particularly crucial role in Vietnam’s economy, with approximately 785,000 enterprises, accounting for over 98% of the total number of businesses. They employ 70% of the workforce and contribute about 50% to the GDP.

Similar to the reality of DTr in other developing countries, the DTr process of SMEs in Vietnam is still lagging behind expectations due to various hindrances. These obstacles include technological infrastructure, financial constraints, the leadership’s awareness, and the ingrained habit of operating within traditional mechanisms. According to a research report on the digital maturity of SMEs in the Asia-Pacific (APAC) region in 2020 by Cisco, Vietnam ranked 14th out of 14 countries. Furthermore, according to forecasts by the Ministry of Information and Communications of Vietnam, if SMEs successfully undergo digital transformation, the GDP will increase by approximately 30 billion USD, accounting for around 7.5% of the GDP in 2022 (Thuy Dieu, 2023). Promoting digitization activities and successfully implementing DTr are urgent requirements of the current landscape.

Social capital (SoC) includes both the form and nature of relationships between members of an organization (Coleman, 1990; Leana & Pil, 2006) called “internal SoC,” as well as the connection between the organization and external entities, which can be competitors or partners (Kale et al., 2000; Uzzi, 1997) known as “external SoC” (Leana & Pil, 2006).

Several scholars have examined the correlation between internal Social Capital (SoC) and organizational performance, such as Aidoo et al. (2020) and Abban et al. (2013), along with investigating the regulatory role of internal SoC as highlighted by Rodrigo-Alarcón et al. (2018). Additionally, research conducted by Lyu et al. (2022) and Ul Zia et al. (2023) illustrates the influence of internal SoC on the innovation performance and capacity of enterprises. However, internal SoC alone may not necessarily enhance operational efficiency due to potential negative compliance arising from close relationships, as noted by Portes (1998) and Uzzi (1997). Therefore, the utilization of external sources for accessing information and resources becomes imperative, as emphasized by Burt (2000). Heller and Firestone (1995) emphasize the crucial role of external SoC in facilitating resource acquisition for organizations. Collins and Clark (2003) observe that robust external connections among top managers in high-tech firms significantly predict sales growth and stock profitability.

Research by Tomlinson and Fai (2013) underscores the importance of collaborative relationships in enabling SMEs’ innovation capabilities across various production activities in the value chain. Similarly, Easmon et al. (2019) demonstrate the impact of external social capital on export performance through innovation and marketing capacities. Kale et al. (2000) provide empirical evidence suggesting that building relational capital, combined with an integrated approach to conflict management, facilitates simultaneous achievement of learning and know-how transfer goals while mitigating opportunistic behavior among alliance partners, thereby preventing the leakage of valuable know-how.

SMEs, facing constraints in capital, technology, managerial capacity, and market conditions, must leverage external opportunities for development, as emphasized by Freel and Harrison (2006). They illustrated the limited capacity of SMEs for independent innovation compared to those engaged in collaborative ventures. Similarly, Koçak and Edwards (2005) advocated for SME survival through cooperative relationships with industries, governments, and other SMEs. Khan et al. (2018) also stressed the importance of seeking external knowledge and support in less-developed economies.

Previous studies primarily focus on the direct or indirect impact of external Social Capital (SoC) on operational efficiency and innovation capacity, neglecting to evaluate its regulatory role in amplifying the effects of other factors on SME performance. Thus, this study examines how external SoC promotes digital transformation and enhances operational efficiency while moderating the relationship with other factors.

The capabilities and leadership approaches of organizational managers play a decisive role in successful digital transformation, helping identify and shape the issues that pave the way for innovation, facilitating favorable interactions among employees within the organization, and encouraging participation in innovative activities. This allows employees to have more involvement in the decision-making process of change (Curry, 1992; Gray, 2009). The shared leadership model, characterized by the participation of members in the organization’s leadership, enhances organizational and team performance (Fransen et al., 2018); Transformational leadership affects organizational performance and culture, with varying impacts depending on the context (N. P. Nguyen et al., 2023; Habeeb & Eyupoglu, 2024). However, some researchers have failed to find support for the idea that shared leadership leads to better team performance (Boies et al., 2009). It is essential to identify the relationship between Shared Leadership and performance to clarify the role of Shared Leadership in business operations; this is a suitable leadership model to promote digital transformation. Research results from Vietnamese enterprises showed that the transformational leadership style of the CEO has a significantly positive impact on the use of management accounting information systems (Abu Afifa & Nguyen, 2023). Shared leadership, characterized by member participation, enhances organizational performance, yet its role in digital transformation remains underexplored Ho Dai and Huynh Tan (2023).

Our research aims to fill this gap by investigating the interplay between social capital, shared leadership, digital transformation, and SME efficiency to propose strategies for enterprise development.

The structure of our paper is as follows:

Section 1: This section serves as an introduction, where we lay out the research background, justify the necessity of our study, and detail our research objectives and the overall layout of the paper.

Section 2: This section presents a review of pertinent literature, providing the academic backdrop against which we study is positioned.

Section 3: Here, we discuss the methodology utilized for this empirical study, explaining the research design, data collection, and analytical tools employed.

Section 4: We report the results of we study in this section, presenting key findings in an organized and interpretable manner and we delve into a discussion of the research results.

Section 5: The final section concludes we study, summarizing key insights, connecting the findings to the existing literature, acknowledging limitations, and highlighting the study’s contribution to the field.

Concept, Hypothesis, Research Model

Theory of Social Capital

Bourdieu (1986) outlines three forms of capital: cultural, economic, and social, with social capital defined as the accumulation of resources through durable networks of mutual acquaintance and recognition, providing collective backing to its members. He argues that social capital is not inherently independent but results from intentional or unintentional investment strategies aimed at establishing or maintaining social relationships.

Social capital (SoC) is vital for group and organizational performance, according to Nahapiet and Ghoshal (1998), Leana and van Buren (1999), and Leana and Pil (2006).

Various studies analyze social capital through general and scope approaches, with the former examining cognitive, relational, and structural aspects. Researchers like H. T. T. Nguyen and Ha (2020), Saha and Banerjee (2015), and Pratono and Mahmood (2014) have demonstrated its positive impact on business performance.

The scope approach considers social capital both within and outside the enterprise. Internal SoC concerns relationships within organizations, while external SoC involves connections with external stakeholders, as highlighted by Coleman (1990), Leana and Pil (2006), Kale et al. (2000), Uzzi (1997), and Luo et al. (2004).

This study explores the role of external social capital in the digital transformation and operational efficiency of SMEs, drawing on social capital theory.

Resource-Based View Theory, RBV

The Resource-Based View (RBV) theory has been extensively employed in Information Technology research to elucidate how companies may acquire competitive advantages and superior performance. The crux of this theory is that a firm’s superior operational effectiveness emanates from its unique, scarce, and difficult-to-imitate resources and competencies (J. B. Barney, 1986; Bharadwaj, 2000). The theory postulates that the skills, capabilities, and other resources owned by an organization vary among organizations, and these resources are the key determinants of the firm’s operations. Therefore, companies that can identify resource characteristics or capabilities that cannot be imitated by competitors will achieve sustainable competitive advantages (J. Barney, 1991).

Social capital (SoC) is a source of enduring competitive advantages and differentiation (Adler & Kwon, 2002). With this characteristic, SoC aligns with the RBV. This study analyzes SoC as a resource propelling DTr and firm performance.

Shared leadership (SL) is the behavior and leadership style of managers and is a unique skill of the organization. With this characteristic, SL aligns with the RBV. This study analyzes SL as a resource driving DTr and firm performance.

Digital Transformation (DTr) assists businesses in enhancing their competitive advantage, improving operational efficiency, and achieving business growth. This study analyzes DTr as a resource bolstering the firm performance.

Concepts

Shared Leadership

Shared leadership has been delineated in various ways, yet a prevailing consensus among scholars suggests that it involves team members sharing leadership responsibilities while still acknowledging vertical leadership capabilities (Fransen et al., 2018; Pearce & Conger, 2003). Burns (1978, pp. 4–20) studied transformational leadership style, a form of empowering leadership; in which transformational leaders build dynamic relationships with employees, who feel elevated by these relationships and become more dynamic, thereby creating new leadership groups and thus having a transformational impact on both. Fisher and Bibo (2004) and Ho Dai and Huynh Tan (2023) elaborated on shared leadership, proposing a tri-dimensional model that preserves two dimensions of the traditional leadership model—relationship orientation and task orientation—and adds a third dimension of representation and participation. Task Orientation (TOL) is crucial for meeting the organization’s task demands, encompassing stress alleviation, support provision, setting work standards, evaluating member performance, and making demands on members. Relationship Orientation (ROL) addresses subordinates’ needs by fostering a positive work environment without compromising task demands. Representation/Participation Orientation (PROL) involves behaviors where subordinates influence work-related decisions. Sarin and O’Connor (2009) systematically categorized four distinct leadership behaviors, including Participative Leadership, Supportive Leadership, Achievement-oriented leadership, and Directive leadership. Our study extends the analysis of shared leadership by Fisher and Bibo (2004), Ho Dai and Huynh Tan (2023), and Sarin and O’Connor (2009), incorporating a tri-dimensional framework encompassing relationship orientation leadership (Support Leadership), task orientation leadership (Achievement-oriented leadership), and Representation/Participation Orientation leadership (Participative Leadership).

Digital Transformation (DTr)

Digital transformation herald significant organizational modifications driven, constructed, or activated by digital technology, altering how business operations are conducted (Hartl & Hess, 2017). It encompasses shifts grounded on the foundation of digital technology, engendering unique alterations in business operations, processes, and value creation (Libert et al., 2016).

In this study, digital transformation in enterprises is delineated as the assimilation and utilization of digital technologies, including big data, analytics, cloud computing, mobile, and social media platforms, to innovate and create novel values. This process aims to augment business efficiency, enhance management efficacy, elevate capabilities, and refine the competitive edge of enterprises.

Firm Performance—FPe

The Firm Performance (FPe) metric is a vital gage of an enterprise’s ability to achieve its goals and assess its competitiveness, characterized by its profitability, growth trajectory, and market valuation (Nwankpa & Roumani, 2016). By utilizing the Balanced Scorecard (BSC) approach, organizations can assess their operational effectiveness by integrating key performance indicators across financial, customer satisfaction, operational processes, and staff learning and development domains (Y. Y. K. Chen et al., 2016).

Our research scrutinizes corporate performance, focusing on facets such as profitability, growth, and market valuation.

Hypothesis on the relationship between the concepts:

Social Capital and Digital Transformation

Tomlinson and Fai (2013) delineated the potency of collaborative relationships across a spectrum of manufacturing activities within the value chain as pivotal catalysts bolstering the innovative capabilities of SMEs in both product and process innovations. Rost (2011) posited that the robustness of inter-organizational relationships plays a cardinal role in fostering innovation. A digital milieu, underpinned by trust, can emanate from knowledge sharing and transactional behaviors (Ridings et al., 2002). Ul Zia et al. (2023) substantiated that social capital bears a positive correlation with the industry’s readiness for the 4.0 era.

Digital Transformation (DTr) embodies the innovation trajectory of SMEs; thus, external social capital significantly propels the DTr dynamics of these enterprises. The hypothesis postulated is:

H1. External social capital exerts a positive influence on the digital transformation of SMEs.

Social Capital and Firm Performance

Social capital positively influences a company’s operational effectiveness (Abban et al., 2013; Koka & Prescott, 2002; H. T. T. Nguyen & Ha, 2020; Pratono & Mahmood, 2014; Saha & Banerjee, 2015; Stam et al., 2014). Ince et al. (2023) study found that social capital impacts firm performance through innovation performance.

The external social capital of medium and small enterprises significantly impacts their operations (Collins & Clark, 2003; Easmon et al., 2019; Luo et al., 2004; Tomlinson & Fai, 2013). Given the constraints of SMEs, external social capital serves to enhance their operational efficiency. The hypothesis proposed is:

H2. External social capital has a positive impact on the firm performance of SMEs.

Shared Leadership and Digital Transformation

Shared leadership indirectly positively influences the operations of a company and its teams (Hmieleski et al., 2012; Ogbonna & Harris, 2000). The transformational leadership style has a significantly positive impact on the use of management accounting information systems (Abu Afifa & Nguyen, 2023).

DTr is a comprehensive innovation process, the role of leaders and employees in the enterprise is especially important. With a task-oriented leadership style, the leader communicates to members what results or goals are expected of them, sets challenging goals for members, expects them to undertake responsibility and perform at the highest level. Through the use of such behavior the leader demonstrates trust in team members that will motivate them to make efforts to achieve goals.

On that basis, we propose the following hypothesis:

H3a: Task-oriented leadership positively impacts the digital transformation process of SMEs.

With a relationship-oriented leadership style, the leader is friendly, approachable, and shows concern for the well-being of team members. It shows the leader’s respect for employees and conveys signals about the leader’s personal qualities. By treating others with respect, considerate leaders create a pleasant work environment, thereby motivating employees to achieve their goals. Based on this, we propose the following hypothesis:

H3b: Relationship-oriented leadership positively impacts the digital transformation of SMEs

With a representative and participative leadership style, the leader invites members to participate in the decision-making process. Participative leaders consult with their team members, solicit their input, and consider these suggestions when making decisions. Engagement demonstrates how a leader behaves toward others as well as his influence on team members, which will have a favorable impact on the digital transformation of SMEs.

Based on this, we propose the following hypothesis:

H3c: Representative and participation leadership positively impacts the digital transformation of SMEs

Shared Leadership and Firm Performance

Shared leadership positively correlates with the operational efficiency of teams (D’Innocenzo et al., 2014; Hoch et al., 2010; Kim & Han, 2019; Saythongkeo et al., 2022). Moreover, shared leadership impacts operational effectiveness more profoundly than traditional leadership (Fransen et al., 2018; McIntyre & Foti, 2013). Using data from 903 employees in Vietnam’s manufacturing sector, N. P. Nguyen et al. (2023) and Habeeb and Eyupoglu (2024) showed that transformational leadership has a positive impact on organizational performance.

By communicating to members about the required outcomes or goals, the leader sets targets and expects employees to take responsibility and perform at their highest level, thereby motivating them to excel in their work. Based on this, the hypothesis is proposed as follows:

H4a: Task-oriented leadership positively impacts the performance of small and medium-sized enterprises.

By treating others with respect, being friendly, approachable, and caring about the well-being of team members, the leader makes employees feel responsible to reciprocate, thereby motivating them to strive to achieve their assigned tasks. Based on this, we propose the following hypothesis:

H4b: Relationship-oriented leadership positively impacts the performance of small and medium-sized enterprises.

By trusting subordinates, listening to their opinions, and boldly delegating authority to them, the leader makes employees proud of themselves, thereby actively performing their work most effectively. Based on this, the hypothesis is proposed as follows:

H4c: Representative and participative leadership positively impacts the performance of small and medium-sized enterprises.

Traditional leadership styles combined with task-oriented, relationship-oriented, participative, and representative directives positively affect the performance of small and medium-sized enterprises.

Digital Transformation and Firm Performance

Portal functionalities and cloud computing significantly influence organizational performance (Y. Y. K. Chen et al., 2016). Ji et al. (2024) also discovered the positive impact of Digital transformation on the financial performance.

Digital transformation, entailing shifts in an organization’s structure, processes, functions, and business models, profoundly enhances its efficiency (Hess et al., 2016; Sahu et al., 2018). Digital transition exerts a favorable influence on the operational effectiveness of female-led businesses (Popović-Pantić et al., 2019). Moreover, digital transformation bolsters innovation and amplifies a company’s operational efficacy (Nwankpa & Roumani, 2016). The digital shift profoundly impacts business efficiency, reverberating through business processes (Lozić & Čiković, 2021). The hypothesis we postulate is:

H5: Digital transformation positively impacts on the firm performance of SMEs.

The Moderating Role of Social Capital

Stam and Elfring’s (2008) research identified the moderating role of social capital in the relationship between entrepreneurial orientation and organizational performance. The study of Ji et al. (2024) also discovered the moderating role of social capital in the relationship between digital transformation and financial performance. External relations facilitate managerial operations, enhancing their efficacy. Concurrently, these external connections amplify the impact of digital transformation on the performance of SMEs. Our hypotheses are posited as:

H6. External social capital moderates the relationship between shared leadership and the digital transformation of SMEs.

H7. External social capital moderates the relationship between shared leadership and the performance of SMEs.

H8. External social capital moderates the relationship between digital transformation and the performance of SMEs.

Research Model

Being based on the Resource-Based View (RBV), social capital theory, and the research models of Nwankpa and Roumani (2016), we propose the research model depicted in Figure 1.

Figure 1.

Suggested research model.

Within this framework, we anticipate that leveraging social capital, combined with a shared leadership style, will have a salutary effect on the digital transformation process and the overall operational efficiency of enterprises.

Research Methodology

Research Process

This study is conducted using a cross-sectional design. This method is suitable for identifying and evaluating behavior and expectations and is considered one of the most commonly used designs in the social sciences.

The research process comprises two main stages:

(1) Grounded in the Resource-Based View (RBV), social capital theory, and preceding studies, hypotheses are formulated, theoretical frameworks are crafted, and metrics for various constructs are devised. Qualitative research is then embarked upon to unearth, refine, and augment measurement variables for the conceptual scales; followed by preliminary quantitative research (with a sample of n = 98 selected by convenience method) to preliminarily test the reliability and discriminant validity of the scales introduced into the formal study.

(2) Quantitative research is executed to validate these scales using tools such as Cronbach’s alpha, Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA). Hypotheses and theoretical models are subsequently tested using Structural Equation Modeling (SEM). To dissect the moderating role of SoC, the investigation proceeds in three phases: the initial phase analyzes relationships involving SoC; the second phase mimics the conditions of the first but omits SoC’s involvement; the third phase compares the outcomes of the both phases to evaluate SoC’s moderating influence.

Research Samples

Hair et al. (2010) asserted that for adequate sampling, the minimum sample size should be five times the number of observed variables. Given the 27 observed variables in this study, the requisite sample size would be 135. Unlike simulation-based research, this investigation was conducted within authentic enterprise settings. The study employed a stratified random sampling strategy, categorized by the geographical location of businesses headquartered in the Mekong Delta region (The Mekong Delta, located in the southwest of Vietnam, covers an area of 39,700 km², accounting for 12.2% of Vietnam’s area. It has a population of approximately 18 million people, making up 19% of the country’s population). However, due to health concerns stemming from a disease outbreak, conducting face-to-face interviews as initially planned was impractical. Consequently, a convenient non-random sampling method was adopted, gathering data from willing businesses until the target sample size was attained. Recognizing the potential compromise in reliability with this approach, the sample size was augmented to 222 to bolster the study’s credibility. Participants were directly surveyed through questionnaire administration, utilizing a five-point Likert scale. The study comprised 222 participants from 111 businesses, inclusive of senior managers and IT department heads. Respondents were given a preview of the interview questionnaire, agreed to be interviewed, and signed the document before answering. Among the participants, 51.4% were male, and 48.6% were female. Regarding enterprises’ revenues, 42.3% generated revenues below 50 billion VND annually, while 32.4% fell within the 50 to 100 billion VND range, 16.2% ranged from 100 to 200 billion VND, and 9.1% exceeded 200 billion VND. Business domains encompassed 68.5% in general merchandise, 14.4% in fuel distribution, 6.3% in electronics, and 10.8% in other product categories.

Scale

The scales for various concepts are inherited from prior studies: The external social capital scale adopts the measure from Easmon et al. (2019), Luo et al. (2004), comprising five observational variables; the shared leadership scale encompasses three secondary scales (Task-oriented leadership with four observational variables; relationship-oriented leadership with four observational variables; representative and participatory leadership with five observational variables) based on the measure by Fisher and Bibo (2004), Sarin and O’Connor (2009), and Ho Dai and Huynh Tan (2023); the digital transformation scale with five observational variables and the firm performance scale with four observational variables, drawing from the measure by Nwankpa and Roumani (2016).

Outcomes of Qualitative Research and Preliminary Quantitative Research

Engaging in bilateral discussions with a group of 10 senior managers and focused group discussions with 10 IT department managers from various companies aimed to construct scales and models, all respondents concurred on the relationships within the model and the scales of the concepts with 27 observational variables.

The preliminary quantitative research results are in Table 1. Cronbach’s alpha and EFA values both meet the requirements, the scales can be used for official research.

Table 1.

Preliminary Analysis Results.

Observable variables	Loading factors > 0.5						Corrected item-total correlation > 0.3
Observable variables	1	2	3	4	5	6	Corrected item-total correlation > 0.3
DT1. Our firm is driving new business processes built on technologies such as big data, analytics, cloud, mobile and social media platform.			0.834				0.775
DT2. Our firm is integrating digital technologies such as social media, big data, analytics, cloud and mobile technologies to drive change.			0.820				0.794
DT3. Our firm operations are shifting toward making use of digital technologies such as big data, analytics, cloud, mobile and social media platform.			0.887				0.838
DT4. Our firm is driving customer service through the application of digital technologies such as social media, big data, analytics, cloud and mobile technologies.			0.772				0.763
DT5. Our firm operations are embracing technologies such as big data, analytics, cloud, mobile, and social media platforms			0.635				0.665
RO1. He does little things to make it pleasant to be a member of the group						0.590	0.562
RO2. He is friendly and approachable						0.539	0.615
RO3. He looks out for the personal welfare of group members						0.711	0.740
RO4. He is understanding of individuals’ personal problems						0.703	0.664
PRO1. He backs up group members in their actions		0.825					0.791
PRO2. He seldom acts without consulting the group		0.815					0.831
PRO3. He puts suggestions made by the group into operation		0.734					0.838
PRO4. He gets group approval on important matters before going ahead		0.820					0.799
PRO5. He encourages suggestions from group members		0.935					0.862
SC1. Our relationship with our overseas partners	0.816						0.789
SC2. Our relationship with governmental agencies	0.828						0.837
SC3. Our relationship with trade and business associations	0.844						0.819
SC4. Our relationship with other private companies	0.791						0.821
SC5. Our relationship with state officials	0.721						0.716
TO1. He lets group members know what is expected of them				0.778			0.679
TO2. He sees to it that group members are working to capacity				0.928			0.797
TO3. He maintains definite standards of performance				0.712			0.657
TO4. He asks the members to do their job well				0.519			0.699
FP1. our firm profits increased in the past 3 years					0.614		0.563
FP2. Customers are always loyal to our firm; the size of customers has increased in the past 3 years					0.775		0.620
FP3. our firm ROI increased over the past 3 years					0.802		0.655
FP4. our firm sales increased over the past 3 years					0.721		0.628
Number of observable variables	5	5	5	4	4	4	∑ = 27
Cronbach’s α > .7	0.921	0.934	0.906	0.826	0.798	0.821
Eigenvalue > 1	9.307	3.716	2.527	2.099	1.861	1.272
Cumulative % > 50%	33.385	43.982	52.081	58.802	64.627	68.003
KMO > 0.7	0.824
n	98

Results and Analysis

Exploratory Factor Analysis and Reliability Assessment

The Cronbach’s alpha results as shown in Table 2, indicate alpha coefficients for the scales exceeding .7, and the total variable correlation for all scales ranging between .532 and .873, ensuring reliability. Table 2 also reveals an Eigenvalue of 1.039, extracting six factors congruent with the model. Factor loadings ranged from 0.585 to 0.879, surpassing the 0.5 thresholds, and a cumulative variance of 69.874%, indicating the scales ensure convergent and discriminant values for the 27 observational variables used in subsequent analyses.

Table 2.

Reliability and Exploratory Factor Analysis.

Observable variables	Loading factors > 0.5						Corrected item-total correlation > 0.3
Observable variables	1	2	3	4	5	6	Corrected item-total correlation > 0.3
DT1. Our firm is driving new business processes built on technologies such as big data, analytics, cloud, mobile and social media platform.	0.599						0.653
DT2. Our firm is integrating digital technologies such as social media, big data, analytics, cloud and mobile technologies to drive change.	0.637						0.641
DT3. Our firm operations are shifting toward making use of digital technologies such as big data, analytics, cloud, mobile and social media platform.	0.689						0.643
DT4. Our firm is driving customer service through the application of digital technologies such as social media, big data, analytics, cloud and mobile technologies.	0.774						0.667
DT5. Our firm operations are embracing technologies such as big data, analytics, cloud, mobile, and social media platforms	0.656						0.605
RO1. He does little things to make it pleasant to be a member of the group					0.745		0.571
RO2. He is friendly and approachable					0.707		0.565
RO3. He looks out for the personal welfare of group members					0.860		0.765
RO4. He is understanding of individuals’ personal problems					0.820		0.715
PRO1. He backs up group members in their actions		0.734					0.717
PRO2. He seldom acts without consulting the group		0.864					0.823
PRO3. He puts suggestions made by the group into operation		0.839					0.823
PRO4. He gets group approval on important matters before going ahead		0.798					0.755
PRO5. He encourages suggestions from group members		0.833					0.757
SC1. Our relationship with our overseas partners			0.862				0.769
SC2. Our relationship with governmental agencies			0.682				0.532
SC3. Our relationship with trade and business associations			0.801				0.699
SC4. Our relationship with other private companies			0.766				0.636
SC5. Our relationship with state officials			0.761				0.636
TO1. He lets group members know what is expected of them				0.879			0.813
TO2. He sees to it that group members are working to capacity				0.767			0.631
TO3. He maintains definite standards of performance				0.835			0.749
TO4. He asks the members to do their job well				0.805			0.726
FP1. our firm profits increased in the past 3 years						0.644	0.771
FP2. Customers are always loyal to our firm; the size of customers has increased in the past 3 years						0.585	0.640
FP3. our firm ROI increased over the past 3 years						0.689	0.873
FP4. our firm sales increased over the past 3 years						0.658	0.809
Number of observable variables	5	5	5	4	4	4	∑ = 27
Cronbach’s α > .7	0.839	0.911	0.846	0.873	0.826	0.897
Eigenvalue > 1	7.762	3.386	3.177	2.841	1.360	1.039
Cumulative % > 50%	27.719	39.812	51.160	61.307	66.164	69.874
KMO > 0.7	0.835
n	222

Confirmatory Factor Analysis (CFA)

Model fit evaluation results in Figure 2 show a χ²/df ratio of 2.083, TLI and CFI indices respectively at 0.900 and 0.912, and an RMSEA of 0.070, all meeting the required standards.

Figure 2.

The results of CFA.

Table 3 show that the CFA results with standardized factor loadings for all observational variables range between 0.541 and 0.989, all exceeding 0.5. All P_c values (0.832–0.911) and P_vc values (0.505–0.71) affirm the unidirectionality, convergence, discriminant value, and reliability of the scales.

Table 3.

A Table of CFA Results System.

Conceptual groups	Concepts	Observatory variables	Reliability		Residual variance P_vc	Factor loading
Conceptual groups	Concepts	Observatory variables	Cronbach alpha	P_c	Residual variance P_vc	Factor loading
SoC		5	.846	0.848	0.533	0.566 ÷ 0.884
SL	TOL	4	.873	0.871	0.636	0.601 ÷ 0.948
	ROL	4	.826	0.832	0.563	0.579 ÷ 0.915
	PROL	5	.911	0.912	0.676	0.743 ÷ 0.880
DTr		5	.839	0.835	0.505	0.656 ÷ 0.789
FPe		4	.897	0.903	0.710	0.541 ÷ 0.989

Table 4 show that the Maximum Shared Variance (MSV) is less than the Average Variance Extracted (AVE), and the square root values of the AVE for the variables (in the Fornell and Larcker table) which are numbers in bold in Table 4, are greater than the correlations between that variable and other variables in the model, ensuring discriminant validity.

Table 4.

Model Validity Measures.

Variable Name	CR	AVE	MSV	MaxR(H)	ROL	SoC	PROL	DTr	TOL	FPe
TOL	0.871	0.636	0.156	0.933	0.798
PROL	0.912	0.676	0.383	0.921	−0.153*	0.822
SoC	0.848	0.533	0.035	0.883	−0.079	−0.049	0.731
DTr	0.835	0.505	0.383	0.843	−0.395***	0.619	−0.083	0.711
ROL	0.832	0.563	0.103	0.899	−0.177*	0.214**	−0.187*	0.320***	0.751
FPe	0.903	0.710	0.321	0.999	0.053	0.515***	0.114	0.566***	0.293***	0.843

p < 0.050; **p < 0.010; ***p < 0.001.

Structural Equation Modeling (SEM) Analysis

Figure 3 shows that SEM model evaluation results mirror the model fit with a χ²/df ratio of 2.083, TLI and CFI indices at 0.900 and 0.912, and an RMSEA of 0.070. With an R²_DTr value of 0.50, indicates 50% of the DTr variance is explained by independent variables, and an R²_FPe value of 0.51 indicates 51% of the FPe variance is accounted for by the DTr factor, validating the model’s suitability for hypothesis.

Figure 3.

The results of testing the research model.

Hypothesis Testing Results

External social capital’s impact on digital transformation is statistically insignificant (p = .401), rejecting hypothesis H₁. External social capital positively influences SME’s performance (β = .230; p = .000), accepting hypothesis H₂. Task-oriented leadership negatively impacts digital transformation (β = −.292; p = .000), accepting hypothesis H_3a but inverting the initial hypothesis direction. Relationship-oriented leadership (β = .143; p = .028) and representative and participation leadership (β = .541; p = .000) both positively influence digital transformation, accepting hypotheses H_3b and H_3c respectively. Task-oriented leadership (β = .347; p = .000), relationship-oriented leadership (β = .182; p = .002), and representative and participatory leadership (β = .209; p = .006) all positively impact on firm performance, accepting hypotheses H_4a, H_4b, and H_4c respectively.

The results in table 5 show that Digital transformation has a strong positive impact on firm performance (with β = .536; p = .000), accepting hypothesis H₅. Testing the reliability of the estimates in the model using the Bootstrap test with a repeated sample of N = 1,000 shows that the absolute values of Bias/SE-Bias are all less than or equal to 2. It can be concluded that the estimates in the model are reliable.

Table 5.

Summary of Hypothesis Testing Results.

Hypotheses	Correlation	β	Bias/ SE-Bias	p	Conclusion
H₁	DTr ← SoC	−.053	2	.401	Unacceptable
H₂	FPe ← SoC	.230	−1	.000	Acceptance
H_3a	DTr ← TOL	−.292	2	.000	Acceptance
H_3b	DTr ← ROL	.143	0	.028	Acceptance
H_3c	DTr ← PROL	.541	2	.000	Acceptance
H_4a	FPe ← TOL	.347	−1.5	.000	Acceptance
H_4b	FPe ← ROL	.182	1	.002	Acceptance
H_4c	FPe ← PROL	.209	−2/3	.006	Acceptance
H₅	FPe ← DTr	.536	1/3	.000	Acceptance

Results of Multicollinearity Test

Multicollinearity is a phenomenon where independent variables are strongly correlated with each other. When this occurs in a regression model, it can cause many indices to be skewed, leading to analysis results that are not very meaningful. A limitation of the SEM model using covariance CB-SEM is that it does not test for multicollinearity. Therefore, to check for multicollinearity, the study uses SPSS software to calculate the Variance Inflation Factor (VIF).

The results shown in Table 6 indicate that all VIF indices are less than 2, suggesting that there is no multicollinearity. The regression results are therefore reliable.

Table 6.

Multicollinearity Test.

Dependent variable: DTr.

Analysis of Social Capital’s Moderating Role

The initial results are evident in the SEM analysis of the research model.

In the second step, an SEM analysis was conducted for the model excluding SoC. The results indicate a χ²/df ratio of 2.359, with TLI and CFI indices at 0.905 and 0.919 respectively, both exceeding 0.9, and an RMSEA of 0.078, all meeting the required standards (Figure 4).

Figure 4.

The results of testing the research model without SoC.

In the third step, comparing the two models reveals: Social capital moderates the relationship between shared leadership and digital transformation, altering the impacts of TOL, ROL, and PROL on DTr, though insignificantly with Δβ values of −.007, −.009, and .010 respectively, leading to the rejection of hypothesis H₆. Social capital also moderates the relationship between shared leadership and firm performance, amplifying the impacts of TOL on FPe with a Δβ of .032 and ROL on FPe with a Δβ of .046. Although SoC diminishes the impact of PROL on FPe, the degree is negligible with a Δβ of −.003. Given these results, SoC plays a positive moderating role in the relationship between SL and FPe, validating hypothesis H₇. Furthermore, social capital moderates the relationship between digital transformation and firm performance, enhancing the impact of DTr on FPe with a Δβ of .019. This underscores SoC’s positive moderating role in the relationship between DTr and FPe, leading to the acceptance of hypothesis H₈ (Table 7).

Table 7.

Comparison of Results of Two Models with SoC and Without SoC.

Hypotheses	Correlation	With SoC		Without SoC		Moderation of SoC (Δβ)	Conclusion
Hypotheses	Correlation	β	p	β	p	Moderation of SoC (Δβ)	Conclusion
H₆	FPe ← TOL	.347	.000	.315	.000	.032	Acceptance
	FPe ← ROL	.182	.002	.136	.023	.046
	FPe ← PROL	.209	.006	.212	.006	−.003
H₇	DTr ← TOL	−.292	.000	−.285	.000	−.007	Unacceptable
	DTr ← ROL	.143	.028	.152	.018	−.009
	DTr ← PROL	.541	.000	.531	.000	.010
H₈	FPe ← DTr	.536	.000	.517	.000	.019	Acceptance

Discussion

SEM Analysis Results and Hypothesis Validation

The SEM analysis underscores the affirmative influence of external social capital on firm performance, enhancing the operational efficiency of SMEs. This is consistent with the changing economic context in Vietnam, where small and medium-sized enterprises, often constrained by limited capital, management experience, and volatile markets, greatly benefit from external support, corroborating the findings of Stam et al. (2014), H. T. T. Nguyen and Ha (2020), Saha and Banerjee (2015), Pratono and Mahmood (2014), Easmon et al. (2019), Tomlinson and Fai (2013), and Ince et al. (2023). While the impact of social capital on digital transformation is not statistically significant in this sample, its positive external relationships amplify the beneficial effects of digital transformation on company performance. This result is consistent with the study by Ji et al. (2024).

Leadership with a relationship orientation propels the digital transformation process, resonating with prior studies. Such leadership styles prioritize employee welfare, empathize with their challenges, actively listen, address their concerns, and foster a congenial environment. This nurtures employee motivation and loyalty, especially during transformative phases that often accompany organizational restructuring. Participation and representative leadership positively influences digital transformation, reflecting real-world business operations. Valuing employee feedback, involving them in decision-making, and elevating their roles ensures they align with the company’s objectives, willingly embracing innovations for growth. Conversely, task-oriented leadership has an inverse effect on digital transformation, diverging from the initial hypothesis. This mirrors the reality of SMEs in transition economies, where survival often necessitates high operational standards, stringent regulations, and managerial oversight, potentially stifling creativity and impeding innovative processes. These findings are consistent with the research of Ho Dai and Huynh Tan (2023), and Abu Afifa and Nguyen (2023).

Shared leadership characterized by its unique attributes, fosters cohesion among employees and between staff and management, leveraging collective strength. This is pivotal for enhancing the operational efficiency of SMEs, these results consistent with studies by D’Innocenzo et al. (2014), Kim and Han (2019), Hoch et al. (2010), Saythongkeo et al. (2022), and N. P. Nguyen et al. (2023), Habeeb and Eyupoglu (2024), once again affirmed the role of shared leadership in business development. Especially when bolstered by positive external relationships, the role of shared leadership in operational efficiency becomes even more pronounced, aligning with the findings of Collins and Clark (2003).

Digital transformation positively impacts business performance, indicating that enterprises benefit from integrating digital elements into their operations. This transformation bolsters various business sectors, enhancing customer trust in the enterprise and its products, and elevating business efficiency as evidenced by previous research conducted by Popović-Pantić et al. (2019), Nwankpa and Roumani (2016), Y. Y. K. Chen et al. (2016), and Ho Dai and Huynh Tan (2023). This effect is further magnified when businesses capitalize on external relationships, this finding are consistent with the research of Ji et al. (2024).

Conclusions and Managerial Implications

Applying the Resource-Based View (RBV) theory and social capital theory, this study developed and validated hypotheses and research models using the Covariance-Based Structural Equation Modeling (CB-SEM) tool. The findings indicate that the theoretical model fits the empirical market data. Digital transformation significantly enhances business performance. Social capital positively impacts the performance of small and medium-sized enterprises (SMEs).

Relationship-oriented, representative, and participative leadership styles positively influence digital transformation, while task-oriented leadership has the opposite effect. Shared leadership positively impacts company performance.

A key finding of this study is the positive moderating role of social capital in the relationship between shared leadership and performance, and between digital transformation and company performance.

For small and medium-sized enterprises (SMEs) in the Mekong Delta region to thrive in the context of innovation, they must actively pursue digital transformation based on investing in technology infrastructure, equipment, and training a team of digital specialists to meet current digital development needs. They should apply digital techniques to business operations and management while fostering a shared leadership style to adapt and navigate the changing competitive and digital landscape. To accelerate this process successfully, SMEs should leverage relationships with external partners, such as business partners, relevant organizations, and government agencies, to gain management, technology, and capital expertise. This not only supports the transformation journey but also enhances operational efficiency and promotes business growth.

The Mekong Delta, an economically and educationally underdeveloped region of Vietnam, is currently receiving significant investment from the government to develop infrastructure in all aspects, aiming to attract foreign investment and elevate the Mekong Delta to be on par with the rest of the country. This presents a great opportunity for SMEs in the Mekong Delta to leverage resources from both the state and foreign investors, to accelerate digital transformation, build a shared leadership style, enhance management and business skills, and improve operational efficiency for sustainable business development.

It should be noted that building a shared leadership style and external relationships (SoC) is closely linked to the culture of the organization, so it is necessary to be careful and meticulous to avoid being superficial and formal, which can easily lead to results are not as expected.

The data collection for this study was confined to the Mekong Delta region. However, due to the convenience sampling method and small sample size (non-probability sampling), the study’s representativeness is limited, restricting its generalizability. It’s essential to expand the research scope. This study focuses only on small and medium-sized enterprises, with the business sector not being specified. Therefore, the findings of the study need to be validated in other business contexts to confirm their universality, especially in areas such as the circular economy and the sharing economy, which have higher applicability. These limitations pave the way for future research efforts.

Footnotes

Acknowledgements

First of all, I would like to thank the authors of the papers related to my research who provided an important theoretical basis for my research. I sincere thanks to all senior managers and IT managers of SMEs in the Mekong Delta in Viet Nam, who agreed to participate in this research and were willing to share their work-life and career related experiences. I am also thankful to my acquaintances, friends and my family, who helped me to establish contacts with various SMEs in the Mekong Delta. Finally, I would like to thank School of Economics and Law, Tra Vinh University for encouraging and creating favorable conditions for me to complete this study.

ORCID iD

Dai Duc Ho

Ethics Considerations

The College of Economics and Law Ethics Review Committee at Tra Vinh University approved my interviews (approval: CEL/17) on September 15th, 2023. Respondents gave written consent for review and signature before starting interviews.

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Tra Vinh University is the sponsor of this research.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The documents I cited in the article were found through Google, ResearchGate, journal websites, the library of Tra Vinh University, and Authors of articles provided via Researchgate.

Noted: References were searched on google scholar, ResearchGate, journal websites, scopus database and the library of Tra Vinh University

References

Abban

Omta (Onno)

S. W. F.

Aheto

J. B. K.

Scholten

V. E.

(2013). Connecting the dots: A multiple case study of the network relationships of small and medium-sized enterprises (SMEs) in the non-traditional agricultural export (NTAE) sector of Ghana. African Journal of Economic and Management Studies, 4(1), 74–94. https://doi.org/10.1108/20400701311303168

Abu Afifa

Nguyen

N. M

. (2023). Impact of risk-taking tendency and transformational leadership style on the use of management accounting system information: A direct-mediation model. Baltic Journal of Management, 18(3), 366–385. https://doi.org/10.1108/BJM-01-2022-0003

Adler

P. S.

Kwon

S. W.

(2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17–40.

Aidoo

S. O.

Agyapong

Mensah

H. K.

(2020). Social capital and performance of SMEs: The role of entrepreneurial orientation and managerial capability. Africa Journal of Management, 6, 377–430.

Barney

(1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

Barney

J. B.

(1986). Strategic factor markets: Expectations, luck, and business strategy. Management Science, 32(10), 1231–1241. https://doi.org/10.1287/mnsc.32.10.1231

Bharadwaj

A. S.

(2000). Research article a resource based perspective on information technology capability and firm performance. MIS Quarterly, 24(1), 169–196.

Boies

Lvina

Martens

M. L.

(2009). Shared leadership and team performance in a business strategy simulation. Journal of Personnel Psychology, 9(4), 195–202. https://doi.org/10.1027/1866-5888/a000021

Bourdieu

(1986). The form of capital. In Richardson

(Ed.), Handbook of theory and research for the sociology of education. Greenwood. (pp 281).

10.

Burns

J. M.

(1978). Leadership. Harper & Row.

11.

Burt

R. S.

(2000). The network structure of social capital. Research in Organizational Behavior, 22, 345–423.

12.

Chen

C. L.

Lin

Y. C.

Chen

W. H.

Chao

C. F.

Pandia

(2021). Role of government to enhance digital transformation in the small service business. Sustainability, 13(3), 1–26. https://doi.org/10.3390/su13031028

13.

Chen

Y. Y. K.

Jaw

Y. L.

B. L.

(2016). Effect of digital transformation on organisational performance of SMEs: Evidence from the Taiwanese textile industry’s web portal. Internet Research, 26(1), 186–212. https://doi.org/10.1108/IntR-12-2013-0265

14.

Coleman

J. S.

(1990). Foundations_of_Social_Theory (pp. 300–321). The Belknap Press of Harvard University Press.

15.

Collins

C. J.

Clark

K. D.

(2003). Strategic human resource practices, top management team social networks, and firm performance: The role of human resource practices in creating organizational competitive advantage. Academy of Management Journal, 46(6), 740–751.

16.

Curry

B. K.

(1992). Instituting enduring innovations: Achieving continuity of change in higher education (ASHE-ERIC Higher Education Report No. 7). http://eric.ed.gov/PDFS/ED358809.pdf

17.

D’Innocenzo

Mathieu

J. E.

Kukenberger

M. R.

(2014). A meta-analysis of different forms of shared leadership–team performance relations. Journal of Management, 42(7), 1964–1991.

18.

Easmon

R. B.

Kastner

A. N. A.

Blankson

Mahmoud

M. A.

(2019). Social capital and export performance of SMEs in Ghana: The role of firm capabilities. African Journal of Economic and Management Studies, 10, 262–285.

19.

Fisher

Bibo

M. B.

(2004). No leadership without representation (A research note). International Journal of Organisational Behaviour, 6(2), 307–319.

20.

Fransen

Delvaux

Mesquita

Van Puyenbroeck

(2018). The emergence of shared leadership in newly formed teams with an initial structure of vertical leadership: A longitudinal analysis. Journal of Applied Behavioral Science, 54, 140–231.

21.

Freel

M. S.

Harrison

R. T.

(2006). Innovation and cooperation in the small firm sector: Evidence from ‘Northern Britain’. Regional Studies, 40(4), 289–305. https://doi.org/10.1080/00343400600725095

22.

Gray

P. J.

(2009). Viewing assessment as an innovation: Leadership and the change process. New Directions for Higher Education. 100), 5–15. https://doi.org/10.1002/he.10001.o1997 .

23.

Habeeb

Y. O.

Eyupoglu

S. Z.

(2024). Strategic planning, transformational leadership and organization performance: Driving forces for sustainability in higher education in Nigeria. Sustainability, 16(11), 4348. https://doi.org/10.3390/su16114348

24.

Hair

J. F.

Black

W. C.

Babin

B. J.

Anderson

R. E.

(2010). Multivariate data analysis. Vectors. 816. Seventh Edition. https://doi.org/10.1016/j.ijpharm.2011.02.019

25.

Hartl

Hess

(2017). The role of cultural values for digital transformation: Insights from a Delphi study [Conference session]. AMCIS 2017 - America’s Conference on Information Systems: A Tradition of Innovation.

26.

Heller

M. F.

Firestone

W. A.

(1995). Who’s in charge here? Sources of leadership for change in eight schools. Elementary School Journal, 96(1), 65–86. https://doi.org/10.1086/461815

27.

Hess

Benlian

Matt

Wiesböck

(2016). How German media companies defined their digital transformation strategies. MIS Quarterly Executive, 15(2), 103–119.

28.

Hmieleski

K. M.

Cole

M. S.

Baron

R. A.

(2012). Shared authentic leadership and new venture performance. Journal of Management, 38(5), 1476–1499.

29.

Hoch

J. E.

Pearce

C. L.

Welzel

(2010). Is the most effective team leadership shared? The impact of shared leadership, age diversity, and coordination on team performance. Journal of Personnel Psychology, 9(3), 105–116.

30.

Ho Dai

Huynh Tan

. (2023). The influence of organizational culture and shared leadership on digital transformation and firm performance. Journal of Governance and Regulation, 12(3 Special Issue), 214–222. https://doi.org/10.22495/jgrv12i3siart3

31.

Ince

Imamoglu

S. Z.

Karakose

M. A.

(2023). Entrepreneurial orientation, social capital, and firm performance: The mediating role of innovation performance. International Journal of Entrepreneurship and Innovation, 24(1), 32–43. https://doi.org/10.1177/14657503211055297

32.

Miao

Wan

Lin

(2024). Digital transformation and financial performance: The moderating role of entrepreneurs’ social capital. Technology Analysis and Strategic Management, 36(8), 1978–1995. https://doi.org/10.1080/09537325.2022.2118110

33.

Kale

Singh

Perlmutter

(2000). Learning and protection of proprietary assets in strategic alliances: Building relational capital. Strategic Management Journal, 21, 217–237. https://doi.org/10.1016/B978-012370877-9.00092-X

34.

Khan

Lew

Y. K.

Marinova

(2018). Exploitative and exploratory innovations in emerging economies: The role of realized absorptive capacity and learning intent. International Business Review Journal, 28, 499–512. https://doi.org/10.1016/j.ibusrev.2018.11.007

35.

Kim

Han

S. J.

(2019). Effects of three dimensions of shared leadership on team members’ perceptions on trust and team performance [Conference session]. Adult Education Research Conference.

36.

Koçak

Edwards

(2005). Independence and cooperation among small businesses: The case of the Turkish shotgun industry in a period of recession. International Journal of Entrepreneurial Behaviour & Research, 11(3), 186–200. https://doi.org/10.1108/13552550510598790

37.

Koka

B. R.

Prescott

J. E.

(2002). Strategic alliances as social capital: A multidimensional view. Strategic Management Journal, 23(9), 795–816. https://doi.org/10.1002/smj.252

38.

Leana

C. R.

Pil

F. K.

(2006). Social capital and organizational performance: Evidence from Urban Public Schools. Organization Science, 17(3), 353–366.

39.

Leana

C. R.

van Buren

H. J.

(1999). Organizational social capital and employment practices. Academy of Management Review, 24(3), 538–555.

40.

Libert

Beck

Wind

(2016, July). 7 Questions to ask before your next digital transformation. Harvard Business Review.

41.

Lozić

Čiković

K. F.

(2021). The impact of digital transformation on the business efficiency of the New York Times. UTMS Journal of Economics, 12(2), 225–239. https://www.bib.irb.hr/1159776/download/1159776.THE_IMPACT_OF_DIGITAL_TRANSFORMATION_ON_THE_BUSINESS_EFFICIENCY_OF_THE_NEW_YORK_TIMES.pdf

42.

Luo

Griffith

D. A.

Liu

S. S.

Shi

Y. Z.

(2004). The effects of customer relationships and social capital on firm performance: A Chinese business illustration. Journal of International Marketing, 12(4), 25–45. https://doi.org/10.1509/jimk.12.4.25.53216

43.

Lyu

Peng

Yang

(2022). Social capital and innovation performance of digital firms: Serial mediation effect of cross-border knowledge search and absorptive capacity. Journal of Innovation & Knowledge, 7, 1–15.

44.

McIntyre

H. H.

Foti

R. J.

(2013). The impact of shared leadership on teamwork mental models and performance in self-directed teams group. Group Processes & Intergroup Relations, 16(1), 46–57.

45.

Nahapiet

Ghoshal

(1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266.

46.

Nguyen

H. T. T.

T. M.

(2020). Social capital and firm performance: A study on manufacturing and services firms in Vietnam. Management Science Letters, 10(11), 2571–2582. https://doi.org/10.5267/j.msl.2020.3.038

47.

Nguyen

N. P.

Hang

N. T. T.

Hiep

Flynn

(2023). Does transformational leadership influence organisational culture and organisational performance: Empirical evidence from an emerging country. IIMB Management Review, 35(4), 382–392. https://doi.org/10.1016/j.iimb.2023.10.001

48.

Nwankpa

J. K.

Roumani

(2016). IT capability and digital transformation: A firm performance perspective [Conference session]. 2016 International Conference on Information Systems, ICIS.

49.

Ogbonna

Harris

L. C.

(2000). Leadership_Style_Organizational_Culture_and_Performance: empirical evidence from UK companies. International Journal of Human Resource Management, 11(4), 766–788.

50.

Osmundsen

Iden

Bygstad

(2018). Digital transformation: Drivers, success factors, and implications [Conference session]. Mediterranean Conference on Information Systems Proceedings. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1004&context=mcis2018

51.

Pearce

C. L.

Conger

J. A.

(Eds.) (2003). Shared leadership: Reframing the hows and whys of leadership. Sage.

52.

Popović-Pantić

Semenčenko

Vasilić

(2019). The influence of digital transformation on business performance: Evidence of the women-owned companies. Ekonomika Preduzeca, 67(7–8), 397–414. https://doi.org/10.5937/ekopre1908397p

53.

Portes

(1998). Social capital: Its origins and applications in modern sociology. Annual Review of Sociology, 24(1), 1–24.

54.

Pratono

A. H.

Mahmood

(2014). Social capital and firm performance: Moderating effect of environmental turbulence. Asian Social Science, 10(19), 59–68. https://doi.org/10.5539/ass.v10n19p59

55.

Ridings

C. M.

Gefen

Arinze

(2002). Some antecedents and effects of trust in virtual communities. Journal of Strategic Information Systems, 11(3–4), 271–295. https://doi.org/10.1016/S0963-8687(02)00021-5

56.

Rodrigo-Alarcón

García-Villaverde

P. M.

Ruiz-Ortega

M. J.

Parra-Requena

(2018). From social capital to entrepreneurial orientation: The mediating role of dynamic capabilities. European Management Journal, 36(2), 195–209. https://doi.org/10.1016/j.emj.2017.02.006

57.

Rost

(2011). LIT search theory learning the strength of strong ties in the creation of innovation. Research Policy, 40(4), 588–604. https://doi.org/10.1016/j.respol.2010.12.001

58.

Saha

Banerjee

(2015). Impact of social capital on small firm performance in West Bengal. Journal of Entrepreneurship, 24(2), 91–114. https://doi.org/10.1177/0971355715586893

59.

Sahu

Deng

Mollah

(2018, May 18). Investigating the critical success factors of digital transformation for improving customer experience [Conference session]. CONFIRM 2018 Proceedings. https://core.ac.uk/download/pdf/211018454.pdf

60.

Sarin

O’Connor

G. C.

(2009). First among equals: The effect of team leader characteristics on the internal dynamics of cross-functional product development teams. Journal of Product Innovation Management, 26(2), 188–205. https://doi.org/10.1111/j.1540-5885.2009.00345.x

61.

Saythongkeo

V. D.

Tran

L. T. T.

(2022). Leadership styles and innovation performance: The role of coopetition capability and in-learning in financial service firms. Sage Open, 12(2). 1–13. https://doi.org/10.1177/21582440221079901

62.

Stam

Arzlanian

Elfring

(2014). Social capital of entrepreneurs and small firm performance: A meta-analysis of contextual and methodological moderators. Journal of Business Venturing, 29, 152–173.

63.

Stam

Elfring

(2008). Entrepreneurial orientation and new venture performance: The moderating role of Intra- and extraindustry social capital. Academy of Management Journal, 51(1), 97–111.

64.

Thuy Dieu. (2023). GDP will increase by 30 billion USD if digital transformation for SMEs. Vneconomy. Retrieved June 5, 2023, from https://vneconomy.vn/gdp-se-tang-them-30-ty-usd-neu-chuyen-doi-so-cho-doanh-nghiep-sme.htm

65.

Tomlinson

P. R.

Fai

F. M.

(2013). The nature of SME co-operation and innovation: A multi-scalar and multi-dimensional analysis. International Journal of Production Economics, 141(1), 316–326. https://doi.org/10.1016/j.ijpe.2012.08.012

66.

Ul Zia

Burita

Yang

. (2023). Inter-organizational social capital of firms in developing economies and industry 4.0 readiness: The role of innovative capability and absorptive capacity. Review of Managerial Science, 17(2), 661–682. https://doi.org/10.1007/s11846-022-00539-3

67.

Uzzi

(1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42(1), 35–67.

The Role of Social Capital and Shared Leadership in the Digital Transformation and Firm Performance

Abstract

Plain language summary

Keywords

Introduction

Concept, Hypothesis, Research Model

Theory of Social Capital

Resource-Based View Theory, RBV

Concepts

Shared Leadership

Digital Transformation (DTr)

Firm Performance—FPe

Social Capital and Digital Transformation

Social Capital and Firm Performance

Shared Leadership and Digital Transformation

Shared Leadership and Firm Performance

Digital Transformation and Firm Performance

The Moderating Role of Social Capital

Research Model

Research Methodology

Research Process

Research Samples

Scale

Outcomes of Qualitative Research and Preliminary Quantitative Research

Results and Analysis

Exploratory Factor Analysis and Reliability Assessment

Confirmatory Factor Analysis (CFA)

Structural Equation Modeling (SEM) Analysis

Hypothesis Testing Results

Results of Multicollinearity Test

Analysis of Social Capital’s Moderating Role

Discussion

SEM Analysis Results and Hypothesis Validation

Conclusions and Managerial Implications

Footnotes

Acknowledgements

ORCID iD

Ethics Considerations

Funding

Declaration of Conflicting Interests

Data Availability Statement

References