Introduction

Over the past two decades, the topic of knowledge governance has garnered significant interest within the academic realm, resulting in a plethora of studies and diverse conclusions (Hu et al., 2019). The economic implications of the COVID-19 pandemic have hindered the propensity for effective information exchange among employees, thereby attenuating the momentum toward knowledge innovation and management in various firms (Pemsel et al., 2016; Hu et al., 2019). Hence, it becomes imperative to adopt a robust knowledge management strategy to invigorate knowledge innovation within the workforce. The knowledge management process serves as a structural mechanism, designed to streamline, invigorate, steer, and oversee knowledge management initiatives and other pertinent activities within an entity (Ye et al., 2021; Wang et al., 2019). The Knowledge Management Process (KMP) is a foundational framework within organizations aimed at creating, sharing, utilizing, and managing the knowledge and information possessed by the entities (Zaim et al., 2019). KMP encompasses several core activities, including but not limited to, knowledge creation (Syed et al., 2021), storage/retrieval (Al-Emran et al., 2018), transfer (Borges et al., 2019; Cao et al., 2022), and application (Farooq, 2019). This process facilitates the efficient and effective management of organizational knowledge resources, supporting the achievement of goals such as innovation (Ahmed et al., 2019; Fang et al., 2013), competitive advantage (Peng et al., 2023), and continuous improvement of practices and processes (Shahzad et al., 2020). While evidence underscores the profound influence of this process on knowledge sharing (Al-Emran et al., 2018; Hu et al., 2019), the nuances of informal knowledge governance remain somewhat underexplored, leaving interrelationships between associated variables ambiguous (Chuang et al., 2019). Acknowledging the paramount importance of information for enterprises, a growing contingent of scholars posits that knowledge stands as a pivotal asset, ushering in benefits related to customer satisfaction and competitive edge (Mothe et al., 2018; Wang et al., 2019). Moreover, the knowledge management framework offers advantages like operational continuity and agile adaptability to environmental shifts—including the economic turbulence instigated by the COVID-19 pandemic—which can engender trust amongst stakeholders and clientele (Albort-Morant et al., 2018; Hu et al., 2019). This study aspires to illuminate the merits of knowledge management processes, extending novel insights into the discourse (Chuang et al., 2019).

This study postulates that through social exchange mechanisms, employees can bolster their positive affective orientations towards their peers, consequently aligning their behaviors more closely with the tenets of the knowledge management process (Hu et al., 2019). Social exchange mechanisms refer to the interpersonal interactions and social behaviors within an organization that facilitate the sharing of knowledge, grounded in mutual trust and reciprocal benefits. These mechanisms may include but are not limited to, mentoring relationships (McFadyen and Cannella Jr, 2004), team-based collaborative projects (Janowicz-Panjaitan and Noorderhaven, 2009), and systems that reward contributions to collective knowledge pools (Gagné et al., 2019). Such practices foster a culture where trust is paramount, and knowledge is exchanged as part of reciprocal social interactions, creating an environment conducive to innovation and collaboration (Adler and Kwon, 2002). To achieve more notable results in knowledge exchange, management must nurture these social exchange mechanisms. This involves instituting policies that promote reciprocal knowledge sharing, such as establishing mentorship programs that pair less experienced employees with more seasoned colleagues (Bolino et al., 2002), deploying collaborative platforms that encourage cross-functional dialog and idea exchange (Reagans and McEvily, 2003), and adopting leadership approaches that prioritize open communication and mutual support within the team dynamic (Le and Lei, 2018). Additionally, management should work towards breaking down silos within the organization to enhance cross-functional collaboration and ensure that knowledge flows seamlessly across departments and teams (Cao and Xiang, 2012). This assumption is grounded in the theoretical framework of the social exchange relationship that exists between organizations and their constituents (Chuang et al., 2019). The established codes and relational dynamics are anticipated to catalyze the dissemination of knowledge within employee cohorts (Wang et al., 2019). Those beneficiaries of such shared expertise are theorized to reciprocate emotionally with the knowledge sharer, invoking a virtuous cycle of interaction consistent with Bearman’s (1997) conceptualization of social exchange. It is noteworthy that certain scholars have identified persisting lacunae in the literature concerning knowledge management processes (Chuang et al., 2019). Empirical findings delineating the motivations and modalities of information propagation and transference remain nebulous, notwithstanding the considerable scholarly attention directed toward the intricacies of the knowledge management process (Al-Emran et al., 2018; Hu et al., 2019).

Historically, academic discourse has gravitated more toward the availability of information-sharing platforms than the intrinsic motivational drivers underpinning knowledge sharing (Wang et al., 2019). However, numerous empirical inquiries have corroborated that the knowledge management architecture intrinsically augments knowledge dissemination and transference (Shraah et al., 2022; Hu et al., 2019; Peng and Shao, 2021). To elucidate, both the infrastructural avenues facilitating knowledge sharing and individual’s intrinsic motivations critically influence knowledge exchange behaviors (Chuang et al., 2019). The multifaceted construct of knowledge sharing encompasses aspects of information interchange, archival, retrieval, and the codification of systematic organizational procedures (Hassan et al., 2016). As articulated by Lailin and Gang (2016), knowledge transfer transcends mere information relay and encapsulates the holistic process of selection, assimilation, integration, and application of knowledge (Zhao et al., 2021). It is therefore incumbent upon the knowledge management framework to engender conducive environments for knowledge disseminators, while concurrently proffering appropriate incentives (Harzing et al., 2016; Shraah et al., 2022). A conspicuous gap in empirical literature persists regarding the functionality, relevance, and potency of knowledge-sharing and transfer mechanisms, with a marked dearth of insights specific to the information service sector (Chuang et al., 2019). This investigation endeavors to elucidate the ramifications of the knowledge management paradigm on employee’s propensities towards knowledge sharing and transference (Hu et al., 2019).

Organizations institute knowledge management processes with the intent of enhancing the exchange and transfer of knowledge among employees (Zhao et al., 2021). However, existing literature suggests that a rigid management framework might engender feelings of exclusion among employees, possibly diminishing their propensity to disseminate information and prompting opportunistic tendencies (Hassan et al., 2016). Areed et al. (2021) posited that intra-organizational social dynamics influence the appraisal of an individual’s social capital. This, in turn, can facilitate knowledge transfer at an individualistic level, thereby augmenting organizational value. In this context, social capital is understood as the sum of actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or organization (Adler and Kwon, 2002; Bolino et al., 2002). It is broadly categorized into structural social capital, which refers to the impersonal configuration of linkages between individuals or units (Burt, 2000; Coleman, 1988), and relational social capital, which emphasizes the personal relationships developed through a history of interactions, characterized by trust, reciprocity, and mutual respect (Putnam, 1995; Nahapiet & Ghoshal, 1998). These dimensions of social capital facilitate cooperative behaviors and knowledge exchange, enhancing organizational and individual performance (Le and Lei, 2018; Reagans and McEvily, 2003). The knowledge management process shapes individuals’ perceptions regarding governance protocols and is demonstrably influenced by social capital (Al-Emran et al., 2018). Interpersonal affiliations can bolster both formal and informal communication channels among staff, thereby promoting resource and expertise exchange (Shraah et al., 2022). Recent empirical evidence from Bhatti et al. (2021) underscores the profound influence of social capital on members’ tendencies towards knowledge sharing. Furthermore, Swanson et al. (2020) asserted that social capital positively modulates information dissemination across structural, relational, and cognitive dimensions. Nevertheless, the nexus between social capital and the knowledge management process remains underexplored (Lailin and Gang, 2016). Consequently, this study contends that delving into the ramifications of social capital on the knowledge management process holds significant academic and practical implications (Harzing et al., 2016; Shraah et al., 2022).

Literature review

Social exchange theory

The social exchange theory offers an analytical framework to interpret behaviors manifesting in social transactions. The rewards derived from social exchanges, both intrinsic and extrinsic, are often nebulous and defy precise quantification (Blau, 1964). Consequently, the emphasis on social exchanges gravitates toward the cultivation of enduring relationships rather than transient transactions (Shariq et al., 2019; Bolino et al., 2002; Bourdieu, 1986). Within this paradigm, knowledge dissemination can be conceptualized as a variant of social exchange where participants engage in oblique transactions (Shariq et al., 2019; Al-Emran et al., 2018; Farooq, 2019). The individual proffering knowledge prioritizes relationship cultivation over immediate gains, with the knowledge management system serving as an intermediary bridge connecting knowledge donors and recipients (Kankanhalli et al., 2005; Foss et al., 2010; Hansen, 1999). Leveraging the social exchange theory can yield insights into the merits of the knowledge management process, thereby optimizing returns for employees and fostering a robust culture of knowledge exchange and transfer (Ganguly et al., 2019; Ghahtarani et al., 2020; Mohajan, 2019).

The knowledge management process can significantly enhance the efficacy of knowledge transfer within organizational frameworks, as articulated by Ye et al. (2021). “Knowledge transfer” is defined as the dissemination of expertise from one entity to another via experienced conduits, and it is instrumental in amplifying organizational performance (Hamdoun et al., 2018; Lombardi, 2019; Al-Emran et al., 2018). As delineated by Farooq (2019), knowledge transfer is inherently unidirectional, signified by the transmission of information from the donor to the recipient. This encompasses the donor’s act of proffering information and the recipient’s subsequent assimilation and application of said information (Hansen, 1999; Foss and Pedersen, 2019). Moreover, the process of knowledge transfer is punctuated by stages of translation and transformation, as expounded by Krylova et al. (2016). Through these stages, knowledge is rendered more comprehensible and actionable (Lombardi, 2019; Ferraris et al., 2020), underscoring the applicability of the transferred knowledge within the recipient’s domain and illustrating the continuity of information flow (Lilleoere and Holme, 2011). Within the realm of academia, knowledge governance should pivot on the methodologies employed by educators in disseminating their knowledge and the pivotal role of leadership in orchestrating knowledge governance (Fabiano et al., 2020; Foss et al., 2010).

Information dissemination is a critical facet of knowledge-oriented endeavors and is imperative for transmuting individualized knowledge into an organizational asset. This practice augments capabilities pertaining to innovation, knowledge synthesis, and generative knowledge, whilst facilitating integration and application at the organizational level (Foss and Pedersen, 2019; Ritala and Stefan, 2021; Farooq, 2019). Hansen (1999) postulates that knowledge dissemination encompasses the mutual exchange of expertise, acumen, insights, and advisories amongst team constituents. The propensity to support peers is intrinsically linked with knowledge-sharing behavior, and both extrinsic and intrinsic inducements exert a profound influence on the predisposition toward knowledge dissemination (Foss and Pedersen, 2019; Ganguly et al., 2019; Borges et al., 2019; Yong et al., 2020; Peng, 2022). Amplified motivation heightens members’ discernment of the merits inherent in knowledge contribution, thereby catalyzing the sharing dynamic. The volition for information exchange, coupled with the presence of conducive platforms, predicates the volume and quality of expertise disseminated (Foss and Pedersen, 2019; Ganguly et al., 2019; Zhao et al., 2021; Abbas et al., 2020). Lilleoere and Hansen (2011) assert that members’ perception of available dissemination avenues critically influences intra-organizational knowledge sharing. The attendant risks and overheads associated with sharing diminish when individuals can leverage platforms underpinned by their social affiliations, thus nurturing a pro-sharing disposition (Anwar et al., 2019; Bhatti et al., 2021). A predisposition to share is fortified when individuals perceive unencumbered access to sharing conduits (Gagné et al., 2019; Saleh and Bista, 2017).

Knowledge management process

The Knowledge Management Process (KMP) serves as an instrumental framework within the ambit of the knowledge-based economy. In an era characterized by rapid shifts in consumer expectations and relentless market competition, organizations are increasingly reliant on KMP for the procurement and operationalization of innovative knowledge (Ahmed et al., 2019; Xie et al., 2019). KMP is delineated as a structured endeavor aimed at either enhancing organizational performance or offering value-added services to the community through the strategic deployment of extant expertise (Zaim et al., 2019; Farooq, 2019). It acts as a foundational nexus for the acquisition, dissemination, and efficacious utilization of knowledge assets, which in turn catalyze organizational innovation (Migdadi, 2021; Al-Emran et al., 2018). Empirical studies underscore the pivotal role of KMP’s triadic components: knowledge acquisition (KA), knowledge dissemination (KD), and knowledge application (KAP), in augmenting the processes of information sharing and transfer (Qasrawi et al., 2017; Shahzad et al., 2020; Han et al., 2019). These components serve as the foundational mechanisms through which knowledge is managed within organizations. Specifically, KA involves the identification and absorption of new knowledge (Al-Emran et al., 2018); KD refers to the distribution of knowledge within the organization (Borges et al., 2019); and KAP pertains to the effective utilization of knowledge in decision-making and organizational practices (Farooq, 2019). To clarify, the impact of KMP extends beyond the mere facilitation of these components. The successful implementation of KMP leads to tangible outcomes, including enhanced organizational innovation (Ahmed et al., 2019), improved employee performance (Abbas et al., 2020), and increased competitive advantage (Zaim et al., 2019). Therefore, when it is stated that KMP fosters knowledge sharing, it implies that the systematic and structured approach to managing knowledge—encompassing acquisition, dissemination, and application—enables a culture and practice of sharing, which in turn contributes to these broader organizational outcomes. This delineation ensures that the discussion of KMP’s role in fostering knowledge sharing is not circular but indicative of its comprehensive impact on organizational knowledge dynamics. Engaging with stakeholders through this structured paradigm enables organizations to assimilate novel information and gain nuanced insights into consumer predilections within evolving market landscapes (Shahzad et al., 2020; Borges et al., 2019).

Furthermore, the assimilated knowledge is harnessed to enhance both the final products and internal processes of the enterprise (Migdadi, 2021; Farooq, 2019). Institutions that prioritize knowledge often motivate their personnel to actively engage in organizational activities, thereby offering pragmatic solutions (Abbas et al., 2020). Environmental specialists and behavioral scientists posit that the consumption of non-sustainable products significantly contributes to environmental degradation, manifested in pollution, deteriorated air quality, and climate perturbations (Li et al., 2019; Hamdoun et al., 2018). The social exchange theory postulates that organizations fortified with robust KMP and nimble competencies are better positioned to innovate and manufacture sustainable commodities, thereby mitigating adverse impacts on both society and the environment (Foss and Pedersen, 2019; Ganguly et al., 2019).

Research has underscored the advantages of KMP in facilitating knowledge exchange (Al-Emran et al., 2018; Olaisen & Revang, 2017; Shahzad et al., 2020). Han et al. (2019) contend that there exists a lacuna in understanding the influence of structured knowledge governance on knowledge dissemination. A recent investigation by Syed et al. (2021) assessed the ramifications of both structured and unstructured KMP on knowledge dissemination, revealing a dichotomy between organizational expectations and individual employee motivations (Migdadi, 2021). While enterprises anticipate that employees will disseminate knowledge for collective advantage, individuals often retain specialized knowledge to safeguard their personal vested interests and organizational stature (Farooq, 2019). Consequently, a socio-organizational paradox emerges between firms and their staff. Cao and Xiang (2012) posit that KMP is pivotal in augmenting knowledge dissemination, serving as a catalyst for collaborative knowledge sharing among personnel (Ali et al., 2018; Qi and Chau, 2018; Xie et al., 2019). Given these considerations, this study propounds the ensuing hypothesis:

H1: Knowledge management process has a positive impact on knowledge sharing behavior.

The efficacy of a knowledge management approach, as delineated by Syed et al. (2021), holds promise not merely for bolstering information dissemination but also for enhancing the cognitive capacities of employees, paving the way for sustained knowledge transmission (Migdadi, 2021). An integral knowledge management framework is quintessential for cultivating a sharing ethos, institutionalizing methodologies, and judicious resource allocation within enterprises (Shahzad et al., 2020). Cultivating a sharing ethos stimulates employees to disseminate their acquired insights with colleagues (Al-Emran et al., 2018). Standardizing methodologies, encompassing operational protocols, documentation architectures, and reward-sanction mechanisms, lays the groundwork for facilitating knowledge exchange among staff (Fabiano et al., 2020; Olaisen & Revang, 2017). In scenarios of constrained resources, prudent resource stewardship becomes pivotal to amplifying knowledge transmission efficiency (Xie et al., 2019). Concurrently, elements such as trust, socio-professional networks, and personal identification exert significant influence on knowledge propagation (Han et al., 2019; Zhao et al., 2021; Qi and Chau, 2018). Interpersonal network affiliations and trust modulate the extent of tacit knowledge dissemination, while personal identification gauges the intrinsic worth of knowledge (Ali et al., 2018). Given the intricacies inherent in knowledge transmission, the salience of knowledge governance in elevating the efficacy of knowledge asset dissemination is accentuated (Zaim et al., 2019). In light of these insights, this study advances the subsequent hypothesis:

H2: Knowledge management process has a positive impact on knowledge transfer behavior.

Social capital

While earlier research acknowledged the role of knowledge management in integrating various organizational processes, it often overlooked the critical influence of social connections (Syed et al., 2021). Recently, however, there has been a noticeable shift towards examining the social aspects of knowledge management, particularly the role of social capital among organizational members, as highlighted in the studies by Ghahtarani et al. (2020) and Pemsel et al. (2016). The exploration of social capital has evolved significantly, tracing back to the pioneering works of Coleman (1988) and Putnam (1995), while also acknowledging the contributions of Pierre Bourdieu (Han et al., 2019). Coleman (1988) introduced social capital within a broader sociological framework, emphasizing its role in enabling specific actions through leveraging norms, networks, and social trust within social structures. Putnam (1995) further elaborated on social capital, elucidating its capacity to strengthen communities and organizations through networks of civic engagement, trust, and reciprocity, thus underlining the vital contribution of social capital to societal betterment and organizational innovation (Akram et al., 2017; Peng, 2022).

Simultaneously, Bourdieu’s examination offers a comprehensive perspective on social capital as the accumulation of real or potential resources stemming from one’s network, characterized by various degrees of institutionalized relationships, mutual familiarity, and recognition. His insights underscore the importance of networking and its benefits within a sociological context (Zhao et al., 2021). Social capital, as articulated by these scholars, comprises both hidden and overt resources that are accessible through networks of affiliation. According to Ganguly et al. (2019), Edinger & Edinger (2018), and as reinforced by Qi and Chau (2018), social capital within a team or organization facilitates the achievement of collective goals through enhanced cooperation and trust. Teams or collectives that effectively leverage their social capital, described by Al-Emran et al. (2018) as possessing a more readily mobilizable form, demonstrate greater efficiency in accessing, sharing knowledge, and mutual support, thus significantly elevating organizational performance.

Therefore, assessing a team’s social capital necessitates a comprehensive understanding of its broader organizational context, focusing on how social structures, networks, and the nature of interpersonal relationships contribute to achieving organizational goals (Coleman, 1988; Putnam, 1995; Alghababsheh & Gallear, 2020). Research efforts, as noted by Ganguly et al. (2019), Lucas et al. (2018), and Pinho & Prange (2016), commonly employ both relational and structural measures to quantify social capital. The relational dimension of social capital refers to the quality of personal relationships that exist within networks, characterized by trust, mutual respect, and an obligation to reciprocate, which facilitate cooperative behaviors and information sharing among individuals (Akram et al., 2017; Chen et al., 2020; Zhou et al., 2021). This dimension emphasizes the importance of strong, trust-based relationships in enabling effective communication and collaboration (Zhou et al., 2022). Conversely, the structural dimension of social capital pertains to the overall configuration of connections within a network, including the density and connectivity of social ties that enable individuals to access resources and information (Akram et al., 2017; Chen et al., 2020; Zhou et al., 2021). This dimension focuses on how the structure of networks, rather than the quality of individual relationships, facilitates or impedes the flow of information and resources across an organization. This study posits that an encompassing assessment that incorporates both relational and structural dimensions is crucial to fully appreciate the extensive benefits that social capital brings to information and knowledge management (Shahzad et al., 2020). Recent studies further underscore this point, showing that the interplay between relational and structural dimensions of social capital significantly impacts organizational innovation and performance (Reagans and McEvily, 2003; Hu and Randel, 2014). Solely focusing on one dimension might obscure the depth of insights and information employees derive from their social networks (Olaisen & Revang, 2017). This integrated perspective combines the foundational theories of social capital with current research, highlighting its pivotal role in enhancing knowledge management within organizations.

The construct of social capital encapsulates the inherent attributes of mutualistic network relationships, exerting influence not solely on knowledge dissemination but also bolstering the aptitude of employees to assimilate and deploy novel insights (Syed et al., 2021). Fundamental social dynamics, epitomized by intra-organizational cohesion and trust, stand as linchpins in sculpting a vibrant social network (Han et al., 2019). Such a network serves as a conduit for the seamless transition of organizational assets, acumen, and proficiencies (Danilov and Mihailova, 2021; Ahmed et al., 2019). The intricacies of social processes are instrumental in the genesis and operationalization of knowledge, underscoring the indispensable nature of social capital (Ghahtarani et al., 2020; Pemsel et al., 2016). In light of these considerations, this study delineates the ensuing hypotheses:

H3a: Relational social capital has a positive impact on knowledge management process.

H3b: Structural social capital has a positive impact on knowledge management process.

Prior empirical investigations, as highlighted by Swanson et al. (2020) and Rezaei et al. (2020), have meticulously probed the nexus between structural social capital and knowledge management. Their collective inference suggests that knowledge management acts as a catalyst for enhancing structural social capital (Liu & Meyer, 2020). Structural social capital inherently mirrors the intensity and regularity of affiliations among colleagues (Sheng & Hartmann, 2019). An amplified frequency of engagements, underpinned by social capital, bestows upon employees augmented avenues to disseminate explicit data and assimilate tacit wisdom (Foss and Pedersen, 2019). Such dynamics inevitably bolster the propensity to disseminate information, magnifying its periodicity, depth, and breadth within the confines of social exchanges (Khan and Khan, 2019). Bolino et al. (2002) accentuated that reciprocal trust stands as the cornerstone in the edifice of social capital connections. The magnitude of mutual trust and collaboration epitomizes the essence of social capital affiliations (Ganguly et al., 2019; Le and Lei, 2018). An elevated echelon of trust within the workforce invariably catalyzes a heightened inclination to unveil tacit insights and privileged intelligence (Ferraris et al., 2020). Intimate synergies among employees expedite the conveyance of tacit understanding, whereas the prevailing norms, trust, and collaboration within the social capital framework magnify the prospects for personnel to reciprocate and promulgate explicit knowledge (Gubbins and Dooley, 2021). Given these precepts, the subsequent hypothesis is posited:

H4a: Relational social capital has a positive impact on knowledge sharing behavior.

H4b: Structural social capital has a positive impact on knowledge sharing behavior.

H5a: Relational social capital has a positive impact on knowledge transfer behavior.

H5b: Structural social capital has a positive impact on knowledge transfer behavior.

According to the above hypotheses, the research framework is shown in Fig. 1:

Fig. 1
figure 1

Research framework.

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Methodology

Sampling

This study aims to explore knowledge management practices within the research and development (R&D) sector of the information service industry, with a keen focus on companies operating within the People’s Republic of China. Recognizing the importance of ethical research practices, particularly in safeguarding the confidentiality of participants’ identities during the survey process, this study employs a purposive sampling method. This approach facilitates a targeted examination of specific characteristics within a select population group, ensuring that the identity of respondents is meticulously protected from any potential threats or breaches of confidentiality. The research was conducted among companies characterized by a unique amalgamation of state-driven and market-driven economic practices, a hallmark of the Chinese business environment. This environment, distinct from traditional capitalist market economies due to significant state intervention, impacts various management processes and practices. The companies surveyed span multiple sectors—manufacturing, technology, and services—and are situated in major economic hubs such as Shanghai, Shenzhen, and Guangzhou. Engaging with companies that, despite being rooted in a Chinese context, often participate in global markets, provides a relevant and rich field for examining knowledge management practices. In conducting this study, special emphasis was placed on research ethics to protect the identities of participants and prevent any inadvertent threats. The unique blend of influences in the Chinese context—ranging from state policies and cultural nuances to the historical evolution of the Chinese economic system—contributes significantly to the shaping of management processes. This backdrop allows for an intriguing exploration of knowledge management practices in an environment that diverges from the purely capitalist model, underpinned by a strong commitment to maintaining the highest standards of confidentiality and ethical rigor in the research process.

The study population was comprised of R&D workers from high-tech companies, excluding administrative personnel, to ensure a representative sample. Before commencing the sampling process, all research procedures, including the methods of data collection and analysis, were reviewed and approved. This was to ensure that the study adhered to the highest ethical standards and that the rights and privacy of participants were protected. All participants were informed about the purpose of the study, and their informed consent was obtained. They were also assured of the confidentiality of their responses and were informed that they could withdraw from the study at any time without any repercussions. The study utilized an electronic questionnaire to gather data from the participants. Out of 490 individuals approached, we received 483 valid responses after removing 7 invalid ones, yielding a response rate of approximately 98.6%. Such a high response rate is in line with Saleh and Bista’s (2017) emphasis on the importance of response rates in determining the reliability and validity of survey findings. The results showed that the majority of the participants were male (63.1%), highly educated with a master’s degree or above (61.4%), and between the ages of 30 and 40 years old (72.1%). The average work experience of the participants was 5.2 years. These demographic characteristics provide a clear picture of the study participants and offer important insights into the impact of identity threats on information-sharing behaviors among R&D workers in the information service industry.

Measures

The study employed a bespoke questionnaire to evaluate various factors within the realm of industrial practice. A five-point Likert scale was used to gauge the magnitude of each factor, where 1 signifies “strongly disagree” and 5 represents “strongly agree.” The instrument for assessing social capital was informed by the model proposed by Tsai et al. (2014) and underwent modifications building on scales developed by Lin and Huang (2010), Yilmaz and Hunt (2001), and Croteau and Raymond (2004). This questionnaire encompasses seven items probing both relational and structural dimensions of social capital, with the verbiage tailored to the industrial milieu.

The knowledge management process is gauged using a questionnaire grounded in the scales formulated by Shahzad et al. (2020) and refined by Migdadi (2021) to suit the information service industrial setting. The tripartite components of the knowledge management process—knowledge acquisition, knowledge dissemination, and knowledge application—are delineated into 6, 5, and 5 items correspondingly. The metric for assessing knowledge-sharing is derived from Al-Emran et al. (2018), encompassing 11 items that scrutinize three facets of knowledge-sharing practices: motivation, opportunities, and behavior.

The knowledge transfer scale is adapted from Reagans and McEvily (2003), and the five questions in the questionnaire evaluate employees’ knowledge transfer situations. The terminology is altered to fit the context, and the questions aim to assess the ease of transferring knowledge and information. The scale of constructs is shown in Table 1.

Table 1 Scale of variables.
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Analysis strategy

In this study, we employed Structural Equation Modeling (SEM) as our primary analytical tool. SEM was chosen due to its capability to assess complex relationships between observed and latent variables, allowing for a comprehensive understanding of the underlying constructs in our research model. SEM is particularly beneficial for research like ours, where multiple relationships are hypothesized simultaneously, and it provides a more nuanced understanding of the direct and indirect effects between variables (Dash and Paul, 2021; Savalei, 2020). Moreover, SEM’s flexibility in handling both measurement and structural models makes it an apt choice for our study, ensuring robustness in our findings (Hallgren et al., 2019).

Results

Measurement

In line with the recommendations of Hair et al. (2017), our first step was to evaluate the measurement model. This involved assessing the reliability and validity of the constructs used in the study. The validity of the postulated factor structure was appraised using confirmatory factor analysis (CFA). Adhering to the two-step CFA approach recommended by Anderson and Gerbing (1988), the construct validity of the model was ascertained. Initially, individual item reliability was evaluated by analyzing the direct loadings or correlations between the measures (or indicators) and their pertinent constructs. It was deemed imperative to verify that the factor loadings of these indicators surpassed 0.7, denoting a robust linkage (Hair et al., 2014). Subsequently, the model’s reliability was affirmed by scrutinizing Cronbach’s alpha and composite reliability (CR) metrics, both of which exceeded the benchmark value of 0.7 as posited by Hair et al. (2017). In the third step, the average variance extracted (AVE) metrics were observed to exceed the threshold of 0.50 (Hair et al., 2017), indicating satisfactory convergent validity, as shown in Table 2.

Table 2 Reliability and validity of all variables.
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Discriminant validity is a crucial aspect of construct validity, ensuring that a construct is distinctly different from other constructs within the model (Hair et al., 2016). In essence, it assesses the extent to which a construct is truly unique and not just a reflection of other constructs in the model. For our study, discriminant validity was tested to ensure that the measures of our constructs were not highly correlated with measures of other constructs, thereby confirming that each construct captures a unique phenomenon. In Table 3, the results for discriminant validity are presented. The diagonal values represent the square root of the average variance extracted (AVE) for each construct, while the off-diagonal values are the correlations between constructs. For adequate discriminant validity, the diagonal values (square root of AVE) should be greater than the off-diagonal values in the corresponding rows and columns (Fornell & Larcker, 1981). As can be observed in Table 3, our model meets this criterion, indicating satisfactory discriminant validity. It’s worth noting that discriminant validity is not just a statistical requirement but also a theoretical one. Ensuring distinct constructs allows for clearer interpretations of the relationships among constructs and enhances the robustness of the theoretical framework (Henseler et al., 2015).

Table 3 Discriminant validity.
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Hypothesis testing

In this study, the structural model was assessed utilizing SmartPLS 3.0, with the linkages and foundational assumptions of the conceptual framework validated via PLS-SEM. Subsequent to the evaluation of the measurement model, we advanced to the structural model examination, adhering to the guidelines proposed by Hair et al. (2017). This phase entailed scrutinizing the interrelations among the constructs and appraising the posited hypotheses. When deploying PLS-SEM, it is imperative to assess both the model’s quality and the variances of the dependent variables, with pertinent metrics encompassing SRMR, NFI, Q2, and R2. Prior to delving into hypothesis testing, collinearity’s potential influence must be ascertained within the structural model. This entails examining whether variance inflation factors (VIFs) exceed the conventional threshold of 3. The results elucidate that collinearity is not a concern in this study, given that all VIF metrics fall below 3. Additionally, a bootstrapping method with 5000 subsamples was employed for the structural models in this investigation.

The findings of this investigation are shown in Fig. 2 and Table 4. Regarding H1 and H2, the findings show that the knowledge management process has a favorable and substantial impact on workers’ knowledge-sharing and transfer behaviors (β = 0.634, p = 0.000) and (β = 0.587, p = 0.000). H1 and H2 are thus supported. Additionally, the findings indicate that structural social capital (β = 0.525, p = 0.000) and relational social capital (β = 0.464, p = 0.000) both have a favorable and substantial impact on the knowledge management process, supporting H3a and H3b. H4a and H4b are verified because relational social capital (β = 0.532, p = 0.000) and structural social capital (β = 0.214, p = 0.000) have a favorable effect on workers’ knowledge-sharing behavior. Additionally, H5a and H5b are supported by our results, which show that relational social capital (β = 0.324, p = 0.000) and structural social capital (β = 0.413, p = 0.000) positively influence workers’ knowledge transfer behavior.

Fig. 2
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Structural model.

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Table 4 Results of hypotheses testing.
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Conclusions

Discussion

The findings from this investigation underscore that KMP, defined as the systematic approach to acquiring, disseminating, and effectively using knowledge within organizations, exerts a positive influence on the dissemination and sharing of knowledge among staff members (Foss and Pedersen, 2019; McFadyen and Cannella Jr, 2004). This observation is consonant with perspectives delineated by Abbas et al. (2020), Olaisen and Revang (2017), and Areed et al. (2021). Furthermore, it is posited that an exhaustive knowledge management regimen—encompassing the key components of knowledge acquisition, dissemination, and application—significantly enhances the flow of information by fostering an environment that encourages employees to engage in knowledge transfer activities. This is largely due to the synergistic effect these components have when effectively integrated within an organization’s practices (Zaim et al., 2019; Al-Emran et al., 2018). Specifically, by establishing a methodical and formalized framework for KMP, organizations can significantly optimize the efficacy of knowledge exchange and transmission across individuals and entities (Ferraris et al., 2020; Han et al., 2019). This approach not only streamlines the process of sharing critical information but also ensures that knowledge is accurately and efficiently circulated among employees, thereby facilitating improved decision-making and innovation (Farooq, 2019; Borges et al., 2019). The organizational socialization paradigm, as expounded by Ali et al. (2018), Qi and Chau (2018), and Han et al. (2019), modulates the employees’ inclination toward fortifying knowledge dissemination and sharing. A strong organizational affiliation and a cohesive group identity serve to enhance interpersonal communication and collaboration among staff, creating a fertile ground for the effective implementation of KMP (Ahmed et al., 2019; Bhatti et al., 2021). Consequently, the leadership’s strategic approach to knowledge management plays a crucial role in shaping the dynamics of knowledge-sharing and transfer among employees, highlighting KMP’s significant contribution to promoting a culture of open information exchange and continuous improvement (Anwar et al., 2019; Hamdoun et al., 2018; Adler and Kwon, 2002; Bolino et al., 2002).

This study ascertains that, when enriched with substantial structural and relational social capital, employees exhibit an increased propensity to engage in knowledge-sharing and transfer endeavors. In this context, social capital is defined by the structural dimension, which refers to the objective and quantifiable connections among individuals or groups, such as network ties and configurations, and the relational dimension, which pertains to the subjective and qualitative aspects of relationships, such as trust, norms, and obligations (Putnam, 1995; Chen et al., 2020; Zhou et al., 2021; Adler and Kwon, 2002; Borges et al., 2019). The findings underscore that both structural and relational dimensions of social capital bolster the knowledge management procedure, consequently amplifying knowledge transfer and sharing proclivities (Ganguly et al., 2019; Ferraris et al., 2020). Accordingly, the structural dimension of social capital contributes to knowledge exchange by providing a framework of connections through which information can flow, while the relational dimension enhances the quality and effectiveness of these exchanges through interpersonal rapport and mutual understanding (Adler and Kwon, 2002; Borges et al., 2019; Chen et al., 2020; Zhou et al., 2021). An elevated reservoir of social capital, as articulated by Han et al. (2019), Zhao et al. (2021), and Bhatti et al. (2021), galvanizes employee participation in knowledge management undertakings and augments knowledge-centric collaborations. Moreover, components of social capital such as trust and shared language, which facilitate mutual understanding, are identified as critical factors that yield better results in information exchange (Coleman, 1988; McFadyen and Cannella Jr, 2004; Peng et al., 2021). Intimate social affiliations, coupled with a multifaceted social network matrix, incentivize employees to assimilate more nuanced and invaluable insights (Borges et al., 2019; Hu and Randel, 2014). These insights lead to deeper comprehension and utilization of knowledge within the organization, as individuals feel more confident and committed to sharing information in a trustworthy environment (McFadyen and Cannella Jr, 2004; Hau et al., 2013). Consequently, this equips them with an enhanced eagerness to acquire, disseminate, and implement knowledge, thereby refining their capabilities in knowledge innovation (Foss and Pedersen, 2019; Gubbins and Dooley, 2021).

The findings of this study corroborate the theoretical perspectives delineated by Alghababsheh and Gallear (2020), Edinger and Edinger (2018), and Ganguly et al. (2019). These theories underscore that an employee’s social capital acts as a pivotal conduit for external knowledge acquisition and as a barometer for interpersonal dynamics (Bolino et al., 2002; Bourdieu, 1986). The concept of ‘bridging’ and ‘bonding’ social capital further refines this understanding by distinguishing between the types of network connections that facilitate the flow of new information (bridging) and those that strengthen existing relationships (bonding), respectively (Putnam, 1995; Adler and Kwon, 2002). Enhanced social capital can fortify the nexus between employees and their organization, thereby smoothing the channels for information dissemination (Ahmed et al., 2019; Han et al., 2019). This fortification of relationships within the organization creates a conducive environment for the free flow of innovative ideas and critical information, integral to the adaptive and competitive capabilities of firms (Peng et al., 2021; Zhou et al., 2021). As evidenced by Crompton et al. (2020) and supported by Zhao et al. (2021), social interactions wield a positive influence on the magnitude of information exchanged. Through the creation of virtual social collectives—platforms where insights, expertise, and experiences are pooled—employees can foster mutual connections, thereby facilitating knowledge assimilation and dissemination amongst themselves (Gubbins and Dooley, 2021; Reagans and McEvily, 2003).

Implications

The findings of this study illuminate that employees’ perception of the institutionalization of knowledge management augments information-sharing behaviors, especially in the context of the economic repercussions stemming from the COVID-19 pandemic (Abbas et al., 2020; Olaisen & Revang, 2017). There is a discernible positive association between the employment of a social capital-centric knowledge management strategy and the knowledge transfer and sharing behaviors of employees (Han et al., 2019; Zhao et al., 2021). Primarily, the knowledge management strategy notably bolsters employees’ proclivities towards knowledge dissemination and transfer (Alghababsheh & Gallear, 2020; Edinger & Edinger, 2018; Ganguly et al., 2019). For organizations aspiring to stimulate knowledge-sharing behaviors among their workforce and elevate the efficacy of intra-organizational knowledge circulation, championing a comprehensive and structured knowledge management initiative is paramount (Ali et al., 2018; Qi and Chau, 2018). By harnessing interactive knowledge management infrastructures, organizations can stimulate knowledge creation endeavors, steward knowledge transfer and sharing both intrinsically and extrinsically, and solidify synergies between macro and micro organizational tiers (Crompton et al., 2020). This not only augments employees’ knowledge-sharing and transfer behaviors but also nurtures a culture imbued with sharing ethos. Moreover, it anchors a robust knowledge management framework, judiciously allocates resources and precipitates favorable organizational outcomes.

The augmentation of employees’ human capital is intrinsically linked to their knowledge acquisition. Furthermore, it is their inherent social capital that catalyzes knowledge dissemination and sharing behaviors (Foss and Pedersen, 2019). Effective management of social capital within the workforce empowers organizations to foster their human capital, which subsequently reciprocates by amplifying their social capital (Sheng & Hartmann, 2019). Consequently, employees endowed with elevated social capital are more predisposed to engage in regular interpersonal exchanges, cultivating a more conducive work environment (Ghahtarani et al., 2020). This dynamic facilitates rapid access to and sharing of both explicit and tacit knowledge, streamlining organizational information flow and optimizing the efficacy of knowledge transfer processes (Mohajan, 2019).

Limitations

Despite its insights, this study is not without limitations. Firstly, this study primarily investigates the knowledge management process through the lens of social interaction (Ganguly et al., 2019; Le and Lei, 2018). While this perspective offers valuable insights, theoretical models encompassing a broader spectrum, such as embeddedness theory (Crompton et al., 2020) and absorptive capacity (Abbas et al., 2020), exist and can enrich our understanding when aligned with diverse theoretical orientations. To further enrich the conceptual depth of knowledge management theories, it is posited that scholars develop management frameworks that more effectively promote employees’ knowledge dissemination and transfer practices (Olaisen & Revang, 2017).

Historically, social capital has been identified as a pivotal precursor in discussions centered on its influence on knowledge transfer and sharing behaviors (Foss and Pedersen, 2019; Sheng & Hartmann, 2019). However, contemporary research positions social capital as a salient mediating variable, asserting that robust social capital can amplify the effectiveness of knowledge management strategies (Han et al., 2019; Zhao et al., 2021). Consequently, future inquiries should delve into the intermediary role of social capital to furnish a more nuanced understanding (Ghahtarani et al., 2020).

Lastly, this study did not undertake a comparative analysis of high-tech employees across different countries (Ali et al., 2018; Qi and Chau, 2018). Given the intricate tapestry of societal and cultural nuances, discernible disparities might exist in employees’ information-sharing tendencies across national boundaries (Borges et al., 2019). Therefore, it is prudent for subsequent research to evaluate the mediating effects of regional characteristics on employees’ knowledge-sharing proclivities (Valk and Planojevic, 2021).