Knowledge Sharing and Organizational Commitment: Psychological Capital as a Mediator and Self-Actualization as Moderator

Abstract

This study aims to investigate the effect of knowledge sharing on organizational commitment. A conceptual model shows hypothesized relationships between knowledge sharing, psychological capital, and organizational commitment. Further, the roles of self-actualization and gender as moderators have been explored. The model is tested with data from faculty members from higher educational institutions in southern India. Using a structured survey instrument, data were collected from 368 faculty members and analyzed after testing the instrument’s psychometric properties using LISREL9 software for structural equation modeling. PROCESS macros were used to test hypotheses. The results reveal that (i) knowledge sharing significantly and positively impacts psychological capital and organizational commitment, and (ii) psychological capital mediates the relationship between knowledge sharing and organizational commitment. The results strongly support self-actualization as moderating the relationship between knowledge sharing and psychological capital. Further, gender as a moderator showed that the relationship between knowledge sharing and organizational commitment was stronger for female faculty compared to male faculty members. The theoretical contribution and practical implications are discussed. Keywords: knowledge sharing, psychological capital, organizational commitment, self-actualization, gender, higher educational institutions, India.

1. Introduction

Nonaka’s [1] seminal work on the knowledge management process has produced impressive research in psychology and organizational behavior. The five dimensions of knowledge management (knowledge creation, knowledge transfer, knowledge sharing, knowledge acquisition, and knowledge storage) have been widely researched by several scholars during the last three decades [2,3,4,5,6,7,8]. While each of the dimensions of knowledge management has its role to play in influencing attitudes-behavior relationships in work organizations, some studies have focused on knowledge sharing [9,10,11], which is a critical dimension of expanding knowledge among organizational participants.

Though knowledge sharing has been exhaustively researched, relatively few studies have focused on the effect of knowledge sharing on employees’ organizational commitment. Previous research has heavily documented the importance of the three dimensions of organizational commitment (continuance, normative, and affective); organizations need to ensure that employees remain committed [12,13]. Another important variable that has been identified nearly two decades back is psychological capital (Luthans et al. [14]), which has several positive outcomes: job satisfaction, job commitment, and organizational performance [15]. Though previous studies focused on the importance of knowledge sharing, psychological capital, and organizational commitment in influencing organizational performance, the linkage between these variables has yet to be investigated. This study aims to establish the link between knowledge sharing, psychological capital, and organizational commitment. Knowledge sharing and psychological capital were influential variables that positively affect individual behavior in organizations. However, to the best of our knowledge, it is surprising that the relationship between knowledge sharing and psychological capital as antecedents to organizational commitment has been understudied. One of the objectives of the present study is to empirically examine the effect of knowledge sharing on psychological capital and organizational commitment. As knowledge sharing between faculty members plays an important role, the relationship between the variables is studied in the context of higher educational institutions. The present study also adds another critical variable, self-actualization, which has received scant attention from scholars in influencing psychological capital. While most of the studies were conducted in the context of Western and European countries, a relatively small number of studies have focused on developing countries such as India. To bridge the gap, the present study attempts to answer the following research questions:

• Q1: How does knowledge sharing impact psychological capital and organizational commitment?
• Q2: How does psychological capital mediate the relationship between knowledge sharing and organizational commitment?
• Q3: How does self-actualization moderate the relationship between knowledge sharing and psychological capital?
• Q4: How does gender moderate the relationship between knowledge sharing and organizational commitment?

This study makes five significant contributions to the theory and practice related to knowledge management and organizational behavior. First, the study highlights the importance of knowledge sharing in educational institutions in enhancing the psychological capital of faculty members entrusted with disseminating the knowledge among students. Second, this study underscores the importance of psychological capital in enhancing organizational commitment. Third, the indirect effect of knowledge sharing on organizational commitment through psychological capital has been evidenced in this study. Fourth, self-actualization, an under-researched area in organizational behavior, has been established to play a vital role in strengthening the relationship between knowledge sharing and psychological capital. Further, the gender differences in the relationship between knowledge sharing and organizational commitment have been emphasized in this study. Fifth, the conceptual model showing the two-way interactions between (i) knowledge sharing and self-actualization in influencing psychological capital and (ii) knowledge sharing and gender influencing organizational commitment is a pivotal contribution of this research to the theories related to knowledge management and organizational behavior.

1.1. Higher Educational Institutions in India: The Study Context

This study is conducted in the context of higher educational institutions (HEIs) in India. Most knowledge transfer from faculty to students occurs in HEIs, and knowledge sharing among the faculty plays a vital role in this process. The dissemination of information from these knowledge chambers is essential for the development of the skills and abilities of students [16]. The enormous growth of HEIs in India, especially after the privatization, makes the institutions highly competitive, and to sustain the competition, HEIs are required to maintain high standards and achieve efficiency in disseminating knowledge. The culture of knowledge creation and sharing is critical in this process. In HEIs, it is essential to see how knowledge sharing among faculty members affects psychological capital and organizational commitment. Some scholars contend that the learning environment has undergone phenomenal changes during the post-pandemic period, requiring knowledge sharing among faculty members to adjust to the new environment and face challenges successfully [17].

According to the All-India Survey of Higher Education (AISHE) report released by the Ministry of Education of India, there are 58,000 HEIs and 993 universities with an enrolment of 43.3 million students [18]. The Indian educational system is governed by several autonomous bodies such as the All India Council for Technical Education (AICTE), Indian Council of Agricultural Research (ICAR), National Council for Teacher Education (NCTE), and Distance Education Bureau (DEB). The primary goal of these HEIs is knowledge creation and dissemination. The economic growth and prosperity of India largely depend on how the HEIs maintain standards to satisfy the accreditation requirements.

1.2. Variables in the Present Study

This study investigates the relationship between the variables: knowledge sharing, psychological capital, organizational commitment, self-actualization, and gender.

1.2.1. Knowledge Sharing

Knowledge sharing, one of the five dimensions of knowledge management, refers to “the provision or receipt of task information, feedback, and know-how to help others and to collaborate with others to solve problems or develop new ideas, products or procedures” (p. 773) [19]. Knowledge includes ideas, facts, opinions, and judgments that may profoundly impact an individual’s and team’s behavior, and knowledge sharing is a critical component in organizations that leads to sustained competitive advantage [20]. As some recent studies have reported, an effective knowledge sharing mechanism facilitates internal employee communication that helps in decision-making processes [21]. In addition, knowledge sharing results in collaboration and enhances interpersonal relationships among organizational members [22]. Literature reviews have predominantly documented several positive outcomes of knowledge sharing, which include innovation [23], collective learning [24], agility [25], and psychological capital [26]. In HEIs, knowledge sharing helps the faculty members keep abreast of emerging pedagogical tools and curriculum developments. It is common for the HEIs to conduct faculty development programs, periodical seminars, and conferences so that they can share their ideas, experiences, and trends in research, which facilitates effective teaching.

1.2.2. Psychological Capital

The Psychological capital concept introduced by Luthans [14] and his colleagues around two decades ago has attracted researchers’ attention in organizational behavior and industrial psychology [14]. Psychological capital is a psychological resource consisting of four dimensions—self-efficacy, optimism, hope, and resilience. A formal definition of psychological capital, as advanced by Luthans et al. [14], is as follows:

“an individual’s positive psychological state of development that is characterized by: (1) having confidence (self-efficacy) to take on and put in the necessary effort to succeed at challenging tasks; (2) making a positive reference (optimism) about succeeding now and in the future; (3) persevering toward goals and, when necessary, redirecting paths to goals (hope) in order to succeed; and (4) when beset by problems and adversity, sustaining and bouncing back and even beyond (resilience) to attain success.” (p. 3) [14]

Previous studies have consistently demonstrated the positive impact of psychological capital on trust, job satisfaction, and performance [11,27]. This study, however, delves deeper into the causal relationship between knowledge sharing among faculty members and psychological capital. Furthermore, we aim to uncover the mediating role of psychological capital in the relationship between knowledge sharing and organizational commitment.

1.2.3. Organizational Commitment

According to Allen and Meyer [28], organizational commitment is “a psychological state that binds the individual to the organization” (p. 14) [28]. Organizational commitment is a multi-dimensional construct consisting of three dimensions: affective, normative, and continuance commitment [29]. Affective commitment is related to the emotional attachment of individuals to the organization, and this emotional bond motivates them to stick with the organization [28,30]. Individuals high in affective commitment tend to attend to their duties and complete given tasks regularly [13,31,32,33].

Normative commitment, another dimension of organizational commitment, is best understood as an individual’s moral obligation to stay with an organization. This sense of duty, often instilled during recruitment and induction when the importance of loyalty is emphasized (Wiener [34]), motivates employees to show normative commitment. When employees are satisfied with the organizational climate and find cultural socialization, they tend to exhibit normative commitment, further strengthening their bond with the organization.

The third dimension of organizational commitment is continuance commitment, which is related to the costs associated with leaving the organization and the benefits associated with continuing with the organization [12,35]. When employees invest their time in learning organization-specific and job-specific skills, they are more likely to exhibit continuance commitment [12]. Further, the lack of employment opportunities may also motivate the employees to continue with the organization in which they are working.

1.2.4. Self-Actualization

One of the most prominent frameworks in the field of motivation is the ‘integrated need-hierarchy’ theory from Maslow [36]. The central theme of the seminal work is that individuals attempt to reach the self-actualization stage once they feel that their lower-level needs (physiological, safety) and middle-order needs (social, esteem) are satisfied (Maslow [37]). Individuals with self-actualization needs are motivated by growth and give importance to love and humanity rather than fulfilling their basic needs. The dimensions of self-actualization are continued freshness of appreciation, acceptance, authenticity, equanimity, purpose, efficient perception of reality, humanitarianism, past experiences, moral intention, and creative spirit [38,39,40]. Extant research reports that individuals characterized by self-actualization maintain positive relations and become self-transcendent, prefer autonomy and personal growth, and are more likely to realize their purpose in life [41,42,43,44].

2. Theoretical Framework, the Variables, and Hypotheses Development

Theoretical underpinnings for the present study come from Positive Organizational Behavior Luthans et al. [14] Organizational Learning Theory (OLT) [45,46], and Organizational Commitment Theory (OCT) [12,13].

Psychological capital, a significant part of POB, is a multidimensional construct of four components: efficacy, hope, optimism, and resilience. Based on social cognition theory [47], Efficacy refers to the belief or confidence individuals possess to complete a given task. Hope, based on hope theory [48], is related to the steps taken by individuals to reach their goals. Based on attribution theory [49], optimism is how individuals attribute positive events to internal causes and adverse events to external and non-controllable situations. The fourth dimension, resilience, relates to how individuals bounce back from failure, adversity, and conflict to achieve goals successfully. Psychological capital is a major driving force for faculty in HEIs so that they can perform their jobs efficiently.

OLT, another theory we used in this research, posits that individuals learn from various sources (e.g., information sharing), which helps them perform their jobs effectively and efficiently. Organizational learning is “a system of actions, actors, symbols, and processes that enables an organization to transform information into valued knowledge, which increases its long-run adaptive capacity” (p. 8) [50]. More often, individuals engage in knowledge sharing to cope with the changes in the environment, enabling them to increase their problem-solving skills [51]. Following OLT, we incorporated knowledge sharing as a crucial independent variable significantly influencing organizational commitment.

The third theory is the OCT, in which organizational commitment is a three-dimensional construct: affective, normative, and continuance [28]. These three components are vital in reducing absenteeism, lowering turnover intention, and increasing citizenship behavior [31,33]. In this study, we integrate these three theories and explore the relationships between the constructs.

2.1. Hypotheses Development

2.1.1. Knowledge Sharing and Organizational Commitment

Knowledge sharing in organizations enables others to develop competencies and solve complex problems [19,52], which is more likely to increase employees’ commitment. Knowledge sharing builds relationships among the organizational members, which positively affects affective commitment and may also influence continuance commitment [53]. The positive relationship between knowledge sharing and organizational commitment has been established by previous researchers [54,55,56,57,58]. A study conducted on 582 employees working in the software industry from India revealed that knowledge sharing is significantly positively associated with affective commitment through competency development [58]. In a recent study conducted on 291 employees in the hotel industry in Malaysia, the researchers found that knowledge management practices, including knowledge sharing, resulted in higher employee commitment, which, in turn, influenced performance [59]. In one study conducted on 408 employees in the healthcare industry in Jordan, Thneibat [60] found that knowledge sharing is an important variable contributing to high employee commitment. Thus, based on the above arguments, we offer the following hypothesis.

H1: 

Knowledge sharing significantly and positively impacts organizational commitment.

2.1.2. Knowledge Sharing and Psychological Capital

Knowledge sharing is one of the five dimensions of knowledge management (other dimensions are knowledge creation, knowledge storing, knowledge accessibility, and knowledge application), which plays a vital role in enhancing the skills and competencies of members [61,62]. Knowledge sharing is crucial when it comes to tacit knowledge (which is not easily shared), and, most importantly, willingness on the part of the members is essential to share such knowledge. As earlier scholars argued, knowledge sharing requires an open environment whereby individuals feel free to share their knowledge, and Kim et al. [10] thought personality characteristics play a vital role in this process [63]. Knowledge sharing helps individuals to enhance their psychological capital (self-efficacy, resilience, and hope). For example, Ghazinour et al. [26] showed a positive association between knowledge sharing and employees’ hope. Fan et al. [64] found that knowledge-sharing results in an increase in resilience. The positive effect of knowledge sharing on self-efficacy has been found by earlier scholars [65,66]. In a study on 700 employees in public sector undertakings, technology companies, and educational institutions in India, some researchers found a relationship between psychological capital and knowledge sharing [67]. Thus, based on the above arguments and prior empirical support, the following hypothesis is advanced:

H2: 

Knowledge sharing significantly and positively impacts psychological capital.

2.1.3. Psychological Capital and Organizational Commitment

The relationship between psychological capital and organizational commitment is straightforward. Psychological capital represents a positive emotional state characterized by high resiliency, efficacy, optimism, and hope. In a study conducted on managers in oil and petrochemical companies from Saudi Arabia, researchers found that psychological capital significantly increased organizational commitment [68]. In another study conducted on 800 employees in small and medium-sized enterprises in Vietnam, the researchers found a strong positive association between psychological capital and organizational commitment [69]. A study conducted on 836 medical postgraduate students from eight medical universities in China found that psychological capital enhanced their commitment to their profession [70]. Psychological capital builds confidence among the individuals that they can effectively perform tasks assigned to them and are more likely to exhibit high levels of commitment. We offer the following hypothesis based on the above arguments and available empirical support.

H3: 

Psychological capital significantly and positively impacts organizational commitment.

2.1.4. Psychological Capital as a Mediator

Several studies have documented the direct effects of knowledge sharing on organizational commitment [55,57,59,60]. However, knowledge sharing may indirectly affect organizational commitment through psychological capital. Psychological capital mediates between emotional intelligence and job performance (Gong et al. [71]) and between service leadership and organizational citizenship behavior [72]. Similarly, when knowledge sharing increases self-efficacy and resilience, they feel more confident performing tasks, motivating them to remain committed to the organization [26]. We offer the following mediation hypothesis based on the direct relationships between knowledge sharing, psychological capital, and organizational commitment.

H4: 

Psychological capital mediates the relationship between knowledge sharing and organizational commitment.

2.1.5. Gender as a Moderator

In the knowledge-sharing literature, gender is a demographic variable that has received relatively little attention despite its potential to significantly influence organizational commitment. While some scholars have noted distinct gender differences in how individuals perceive and act [73], others have found no such disparities [74,75]. In this study, our specific focus is to highlight gender differences in the relationship between knowledge sharing and organizational commitment, a key objective that has not been extensively explored.

One of the main reasons for gender differences is how women perceive social life differently from males [76]. Studies conducted in Western countries (e.g., the USA) and European countries reveal that men tend to have independent self-construal. In contrast, women are skewed towards interdependent self-construal [77], whereas in developing countries (e.g., India), women prefer dyadic relationships to men who prefer social life. In educational institutions, men interact face-to-face, whereas women prefer discrete interactions through online platforms [78,79]. The relationship between knowledge sharing and organizational commitment will be stronger for women than for men, especially in the context of educational institutions. Since earlier scholars did not study gender differences, we offer the following exploratory moderation hypothesis.

H1a: 

Gender moderates the relationship between knowledge sharing and organizational commitment such that the relationship will be stronger for women than for men.

2.1.6. Self-Actualization as a Moderator

The need-hierarchy theory, as proposed by Maslow [36], is a seminal contribution to the field. It posits that the highest order need is ‘self-actualization’. This theory has been a cornerstone for several researchers in organizational psychology. They argue that individuals characterized by self-actualization are more likely to be creative, strive for personal growth, and find purpose in life [40,41,42,43,44]. These individuals are eager to learn and grow, are curious about new things, and express themselves through innovative ideas. For instance, curiosity, a key characteristic of self-actualized individuals, is defined as the “recognition, pursuit, and intense desire to explore novel, challenging, and uncertain events” (p. 368) [80].

In this study, we argue that self-actualization strengthens the positive effect of knowledge sharing on psychological capital. When knowledge sharing is positively related to psychological capital, individuals who are high in self-actualization tend to enhance their psychological capital by their curiosity, innovativeness, and readiness to learn new things. Though social and organizational psychology researchers demonstrated that self-actualization is a strong predictor of several work-related outcomes (such as job satisfaction), the moderating effect of self-actualization has not been investigated. In this study, we explore the moderating effect by offering the following hypothesis to fill the research gap.

H2a: 

Self-actualization moderates the relationship between knowledge sharing and psychological capital such that, at higher (lower) levels of self-actualization, knowledge sharing results in higher (lower) levels of psychological capital.

The conceptual model is presented in Figure 1.

3. Method

3.1. Sample

To test the hypothesized relationships, we focused on faculty members working in higher education institutions (HEIs) in southern India. We prepared a carefully crafted survey instrument and distributed it among faculty members. The survey was sent electronically using Google Forms. Since it is challenging to approach respondents because of social distancing problems and risks involved in face-to-face interactions, most researchers prefer using online data collection platforms. Several researchers followed the risk-free electronic method of collecting data (6–9). We sent 500 emails to the respondents and received 368 responses (73.6% response rate). Since Google Forms does not allow incomplete data, all the responses received were complete. We checked the non-response bias by comparing the first seventy-five respondents with the last seventy-five responses and found no statistical differences between these two data groups.

3.2. Demographic Profile

The sample consists of 161 male faculty (43.8%) and 207 female faculty (56.2%). The demographic profile is mentioned in

Table 1. Demographic profile of the respondents.

Category	Profile	Total Number	Percentage
Gender	Male	161	43.8
	Female	207	56.2
Age	25 years or less	28	7.6
	25–35	130	35.3
	25–45	163	44.3
	45–55	42	11.4
	Over 55	5	1.4
Experience	Less than 5 years	115	31.3
	5–10 years	112	30.4
	10–15 years	90	24.5
	15–20 years	33	9.0
	Over 20 years	18	4.9
Educational Qualification	Post-graduate Masters	45	12.2
	M. Phil	89	24.2
	Ph. D	234	63.6
Family type	Joint family	133	36.1
	Nuclear family	235	63.9
Marital status	Married	329	89.4
	Unmarried	39	10.6
Annual income	Up to INR 300,000 [USD 3500]	208	56.5
	INR 300,000–INR 600,000 [USD 3500–USD 7000]	119	32.3
	INR 600,000–INR 900,000 [USD 7000–USD 10,500]	2	0.5
	INR 900,000–INR 1,200,000 [USD 10,500–USD 14,000]	26	7.1
	above INR 1200,000	13	3.5

.

3.3. Measures

All the constructs were measured with indicators on a Likert-type 5-point scale (1 = strongly disagree; 5 = strongly agree) on which the respondents were asked to express their opinions. The measures were drawn from the literature. Knowledge sharing was measured with five items (α = 0.72) adapted from Lin [81]. Psychological capital was measured with four dimensions adapted from Luthans et al. [82]: efficacy (three items; α = 0.79), hope (three items; α = 0.76), resilience (three items: α = 0.85), and optimism (three items: α = 0.87). The reliability coefficient of psychological capital as a second-order construct was 0.82. Organizational commitment was measured with three dimensions adapted from Meyer and Allen [32]: affective commitment (three items; α = 0.82), normative commitment (three items; α = 0.84), and continuance commitment (three items; α = 0.85). The reliability coefficient Cronbach’s alpha for the second-order latent construct ‘organizational commitment’ was 0.78. Self-actualization was measured with ten dimensions adapted from Kaufman [40]: continued freshness of appreciation (three items: α = 0.78), acceptance (three items: α = 0.79), authenticity (three items: α = 0.81), equanimity (three items; α = 0.72), purpose (three items: α = 0.73), efficient perception of reality (three items: α = 0.78), humanitarianism (three items: α = 0.83), experience (three items: α = 0.76), good moral intuition (three items: α = 0.79), and creative spirit (three items: α = 0.77). Cronbach’s alpha for second-order latent construct self-actualization was 0.82. [All the indicators for the constructs are mentioned in Appendix A].

4. Analysis and Results

As Anderson and Gerbing [83] suggested, the measurement model was checked before testing the structural model. We used structural equation modeling to check the measurement model. The results of measurement models are presented in

Table 2. Confirmatory factor analysis.

Variable	Alpha	Standardized Loadings (λyi)	Reliability (λ2 yi)	Variance (Var (εi))	Variance-Extracted Estimate Σ (λ2 yi)/[(λ2 yi) + (Var (εi))]
Knowledge sharing	0.72				0.67
KS1		0.83	0.69	0.31
KS2		0.85	0.72	0.28
KS3		0.78	0.60	0.40
KS4		0.84	0.70	0.30
KS5		0.80	0.65	0.36
Self-actualization
Continued freshness of appreciation	0.78				0.66
FA1		0.79	0.62	0.38
FA2		0.83	0.70	0.30
FA3		0.82	0.67	0.33
Acceptance	0.79				0.71
A1		0.88	0.77	0.23
A2		0.80	0.65	0.35
A3		0.85	0.72	0.28
Authenticity	0.81				0.73
AT1		0.84	0.70	0.30
AT2		0.86	0.75	0.25
AT3		0.86	0.74	0.26
Equanimity	0.72				0.78
E1		0.89	0.80	0.20
E2		0.90	0.82	0.18
E3		0.85	0.72	0.29
Purpose	0.73				0.76
P1		0.89	0.78	0.22
P2		0.82	0.67	0.33
P3		0.90	0.82	0.18
Efficient perception of reality	0.78				0.70
PR1		0.81	0.66	0.34
PR2		0.84	0.71	0.29
PR3		0.85	0.73	0.27
Humanitarianism	0.83				0.69
H1		0.85	0.72	0.28
H2		0.82	0.68	0.32
H3		0.82	0.68	0.32
Past experiences	0.76				0.70
PE1		0.79	0.63	0.37
PE2		0.87	0.76	0.24
PE3		0.84	0.71	0.29
Moral intention	0.79				0.65
MI1		0.79	0.63	0.37
MI2		0.80	0.65	0.35
MI3		0.81	0.66	0.34
Creative spirit	0.77				0.74
CS1		0.83	0.69	0.31
CS2		0.84	0.70	0.30
CS3		0.90	0.82	0.18
Organizational commitment
Affective commitment	0.82				0.74
AC1		0.87	0.76	0.24
AC2		0.86	0.75	0.25
AC3		0.84	0.71	0.29
Continuance commitment	0.85				0.64
CC1		0.81	0.66	0.35
CC2		0.74	0.55	0.45
CC3		0.84	0.71	0.29
Normative commitment	0.84				0.79
NC1		0.87	0.76	0.24
NC2		0.91	0.83	0.17
NC3		0.89	0.79	0.21
Psychological capital
Efficacy	0.79				0.70
PCE1		0.83	0.70	0.31
PCE2		0.86	0.75	0.25
PCE3		0.80	0.65	0.35
Hope	0.76				0.69
PCH1		0.86	0.74	0.26
PCH2		0.82	0.67	0.33
PCH3		0.81	0.66	0.34
Resilience	0.85				0.72
PCR1		0.82	0.68	0.32
PCR2		0.85	0.73	0.28
PCR3		0.87	0.76	0.25
Optimism	0.87				0.67
PCO1		0.87	0.75	0.25
PCO2		0.81	0.66	0.34
PCO3		0.78	0.60	0.40
Second-order constructs
Self-actualization	0.82				0.63
Continued freshness of appreciation		0.72	0.52	0.48
Acceptance		0.89	0.79	0.22
Authenticity		0.80	0.64	0.36
Equanimity		0.82	0.67	0.33
Purpose		0.85	0.73	0.27
Efficient perception of reality		0.76	0.58	0.43
Humanitarianism		0.82	0.68	0.32
Past experiences		0.81	0.66	0.35
Moral intention		0.72	0.53	0.48
Creative spirit		0.71	0.51	0.49
Organizational commitment	0.78				0.70
Affective commitment		0.79	0.62	0.38
Continuance commitment		0.88	0.78	0.22
Normative commitment		0.84	0.70	0.30
Psychological capital	0.82				0.76
Efficacy		0.91	0.82	0.18
Hope		0.89	0.79	0.21
Resilience		0.85	0.72	0.29
Optimism		0.84	0.70	0.30

. The baseline second-order four-factor model fitted the data well (χ²/df = 3.5; RMSEA = 0.065; RMR = 0.046; standardized RMR = 0.057; CFI = 0.93; TLI = 0.91; GFI = 0.90). These goodness-of-fit statistics for the four-factor model render evidence of construct distinctiveness for knowledge sharing, psychological capital, self-actualization, and organizational commitment. Table 2 reveals that the factor loadings of all the constructs were well above acceptable levels of 0.70, and the average variance extracted (AVE) estimates were above 0.50, indicating the construct’s reliability and validity [84]. Discriminant validity is established by ensuring that the AVE exceeds the squared correlations between the variables. For example, the AVEs of knowledge sharing and self-actualization were 0.67 and 0.63, respectively, which exceeded the squared correlations between knowledge sharing and self-actualization (r = 0.26; and r² = 0.067) (see

Table 3. Means, standard deviations, and zero-order correlations.

	Mean	S. D	1	2	3	4	5
1. Knowledge sharing	4.03	0.65	1
2. Psychological capital	4.16	0.69	0.14 ***	1
3. Self-actualization	4.02	0.55	0.26 ***	0.36 ***	1
4. Organizational commitment	3.92	0.48	0.21 ***	0.31 ***	0.53 ***	1
5. Gender	1.56	0.50	0.05	0.13 **	0.09	0.09	1

*** p < 0.01; ** p < 0.05; Gender [1 = male; 2 = female].

for correlations between the variables). The goodness-of-fit statistics and CFA results support this study’s discriminant validity of these four second-order latent constructs.

4.1. Common Method Bias (CMB)

Since survey-based research has inherent CMB, it is necessary to statistically check the extent of the CMB. We conducted three tests: (a) We followed Harman’s single-factor method and found that a single factor accounted for 21.63 percent of the variance; (b) we verified the variance inflation factor (VIF) and found that the VIF values were less than 5.0; and (c) we conducted latent variable approach by subjecting all the constructs on a single factor and rotated with all constructs and found that the inner VIF values were less than 3.3 [85]. These statistics reveal that CMB did not affect the data.

4.2. Testing H1–H3

We performed Hayes [86] PROCESS macros for testing the hypothesized relationships. The results of the direct hypotheses are presented in

Table 4. Results of hypotheses testing.

Hypotheses	Relationship	Coeff	se	t	p	Boot LLCI	Boot ULCI	Result
H1	Knowledge sharing → Organizational commitment	0.1547	0.0378	4.0975	0.0001	0.0805	0.2289	Supported
H2	Knowledge sharing → PsyCap	0.2581	0.0383	6.7349	0.0000	0.1829	0.3334	Supported
H3	PsyCap → Organizational commitment	0.1039	0.0376	2.7626	0.0059	0.0300	0.1778	Supported

.

The regression coefficient of knowledge sharing on organizational commitment, as predicted in Hypothesis 1, is significant and positive (β = 0.15; t = 4.09; p < 0.001). The beta coefficient of knowledge sharing on PsyCap was significant and positive (β = 0.26; t = 6.73; p < 0.001), thus supporting H2. The direct effect of PsyCap on organizational commitment was positive and significant (β = 0.10; t = 2.76; p < 0.01), thus supporting H3.

Hypothesis 4 predicts that PsyCap mediates the relationship between knowledge sharing and organizational commitment. To test the mediation hypothesis, we verified whether the indirect effect is significant or not. The results reveal (see

Table 5. Indirect effect.

	Effect	se	Boot LLCI	Boot ULCI
Knowledge sharing → PsyCap → Organizational commitment	0.0286	0.0145	0.0036	0.0610

NB: Total Effect: Knowledge sharing. Organizational commitment = Direct effect (0.1261) + Indirect effect (0.0286) = 0.1547. Indirect effect = regression coefficient of knowledge sharing on PsyCap (0.1440) x regression coefficient of PsyCap on organizational commitment (0.1983) = 0.0286. Notes: N = 368; Boot LLCI refers to the lower bound of bootstrapping confidence intervals. Boot ULCL refers to the upper bound of bootstrapping confidence intervals. The number of bootstrapping samples for these bias-corrected bootstrapping confidence intervals is 20,000. The level of confidence for all confidence intervals in the output is 0.95. We report four decimal digits for bootstrap results because some values may be very close to zero.

) that the indirect effect (0.028) was significant (Boot LLCI = 0.0036; Boot ULCI = 0.0610). Since ‘zero’ was not in the confidence intervals, the indirect effect was significant, thus supporting H4. (See Table 5).

4.3. Testing H1a and H2a

To test the moderation hypotheses, we used model number 1 of Hayes’ [86] PROCESS macros. The results were presented in

Table 6. Results of moderation hypotheses.

Hypotheses	Relationship	Coeff	se	t	p	Boot LLCI	Boot ULCI	Result
H1a	Knowledge sharing x gender → Organizational commitment	0.1869	0.0749	2.4969	0.0130	0.0397	0.3341	Supported
H2a	Knowledge sharing x self-actualization → PsyCap	0.1261	0.0365	3.4558	0.0006	0.0544	0.1979	Supported

.

The regression coefficient of the interaction term between knowledge sharing and gender on organizational commitment was significant (β knowledge sharing × gender = 0.187, p < 0.05), thus supporting that gender moderated the relationship between knowledge sharing and organizational commitment. The interaction effect can be seen in Figure 2.

We predicted that the relationship between knowledge sharing and organizational commitment would be stronger for women when compared to men. As can be seen in the figure, the effect of knowledge sharing on organizational commitment was higher for women compared to men. However, when knowledge sharing increased from ‘low’ to ‘high’, the rate of growth in organizational commitment was higher for men, though women showed higher levels of commitment comparatively. At the other end of the continuum, when knowledge sharing was high, the gender differences disappeared. The difference in the slopes of the curves renders support for the moderation hypothesis (H1a).

We predicted that self-actualization moderates the relationship between knowledge sharing and PsyCap. The results reveal that the regression coefficient of interaction term knowledge sharing and PsyCap was significant (β knowledge sharing x self-actualization = 0.126, p < 0.05). The visualization of the interaction effect is presented in Figure 3.

As can be seen in Figure 3, at higher levels of self-actualization, knowledge sharing results in a higher level of organizational commitment than at lower levels of self-actualization. Further, when knowledge sharing increases from ‘low’ to ‘high’, the relationship becomes much stronger as the slopes of the curves representing higher levels of self-actualization are increasing at a faster rate than at lower levels of self-actualization. The slopes of the curves are different at different levels of self-actualization, thus supporting the moderation hypothesis H2a.

5. Discussion

This research aims to unravel the effect of knowledge sharing on psychological capital and organizational commitment. The data collected from 368 faculty members from HEIs were analyzed using PROCESS MACROS, and the findings supported all hypothesized relationships mentioned in the conceptual model (Figure 1).

First, the findings indicate that knowledge sharing has a significant and positive effect on organizational commitment (Hypothesis 1), corroborating the results from other studies in the literature [54,55,56,57]. When faculty members feel comfortable sharing their knowledge (such as new techniques and software), they are more likely to increase their performance and be motivated to stay with the institutions they are working in. Second, the results supported the positive effect of knowledge sharing on psychological capital (Hypothesis 2), confirming the findings from previous researchers [26,63,67,87]. Knowledge sharing enables the faculty members to enhance their psychological capital (hope, efficacy, optimism, and resilience). Third, the positive relationship between psychological capital and organizational commitment (Hypothesis 3) has been well supported in this study, consistent with previous scholars’ results [68,69,88]. Faculty members high in hope, optimism, efficacy, and resilience will likely show higher affective, normative, and continuous commitment toward the organization.

The fourth key finding from this study is the mediation effect of psychological capital in the relationship between knowledge sharing and organizational commitment (Hypothesis 4). Some studies have demonstrated the role of psychological capital in influencing the relationship between various independent and dependent variables [6,57,59,71]. Fifth, this research supported the moderating effect of gender in the relationship between knowledge sharing and organizational commitment (Hypothesis 1a). Though previous researchers did not investigate gender differences, some empirical evidence supporting the importance of gender in influencing relationships between organizational variables is available [74,75]. Sixth, the findings from this study supported self-actualization as a moderator in strengthening the relationship between knowledge sharing and psychological capital (Hypothesis 2a). This is consistent with the positive outcomes of self-actualization on organizational variables [40,41,42,43,44]. In sum, the conceptual model presented and tested in this study aligns with the theoretical underpinnings of POB, OLT, and OCT.

5.1. Theoretical Contributions

The results from this research have several implications for broadening the theoretical bases of POB, OLT, and OCT. First, this study provides detailed insights into the positive effect of knowledge sharing, especially in the context of faculty members in HEIs. The faculty is entrusted with disseminating knowledge among the students; HEIs must have a positive knowledge-sharing climate. Second, this study underscores the importance of knowledge sharing in ensuring high organizational commitment among faculty members. A climate of knowledge sharing will help increase the skills and abilities of individuals in practical problem-solving and motivate them to exhibit higher levels of affective, continuance, and normative commitment. Third, this study documented that knowledge sharing is a precursor to psychological capital influencing commitment.

Fourth, following gender studies, this research makes a significant contribution by providing empirical evidence in support of gender differences in the effect of knowledge sharing on organizational commitment. More specifically, this study evidenced that women faculty members are more likely to engage in knowledge sharing that contributes to organizational commitment than their male counterparts.

The fifth pivotal contribution of this study is the effect of self-actualization, an understudied variable in the organizational behavior literature, on influencing psychological capital. More specially, this research leverages one of the critical constructs of Maslow’s need-hierarchy theory (i.e., self-actualization), which plays a vital role in increasing the positive effect of knowledge sharing on psychological capital. Therefore, from a theoretical standpoint, this study contributes to the advancement of existing theories related to psychological capital (POB), organizational commitment (OCT), and knowledge sharing (OLT).

5.2. Practical Implications

This research has several implications for administrators and faculty in HEIs. Since knowledge creation and dissemination occur at the HEIs, the administrators must provide a congenial climate of knowledge sharing so that the students benefit from the enhanced faculty knowledge. This research explains how a nuanced understanding of knowledge sharing can enhance psychological capital and organizational commitment. Understanding the importance of knowledge sharing in HEIs will be helpful to administrators in motivating the heads of the institutions to encourage conducting workshops and conferences at regular intervals. Most institutions worldwide conduct faculty development programs and national and international seminars whereby faculty members congregate and share their ideas and knowledge, which enhances their psychological capital, motivating them to remain committed to the institutions.

As the educational sector has become highly competitive with the presence of several private colleges and universities, particularly in the context of India, it is essential for the HEIs to retain talented faculty who are ready to share their knowledge and who are high on psychological capital, and who show higher levels of commitment. HEIs that ignore the importance of knowledge sharing and psychological capital are less likely to sustain a competitive advantage.

5.3. Limitations and Suggestions for Future Research

This study has some limitations. First, as with any survey-based cross-sectional research, the problems of CMB and social desirability bias are common in this study as well. However, to counter the CMB, we have taken adequate care by following the suggestions of scholars in terms of methodology [89]. To minimize the social desirability bias, we anonymized the responses and assured the respondents about the data privacy they provided. Second, the sample is from a developing nation, India, and hence, the results may be generalizable across various developing nations where the infrastructure of HEIs is similar. Third, a relatively small sample may be a limitation, though we considered the sample representative. Further, the response rate of 73.6 percent may limit the generalizability of findings, though it is acceptable in social sciences research [90]. Fourth, the study focused on a limited number of variables. Fifth, the study tested the conceptual model in light of HEIs, and the results should be interpreted when applied to other sectors (e.g., information technology, pharmaceuticals, manufacturing).

This research provides several avenues for future studies. First, scholars may increase the sample size to make the findings more reliable and generalizable. Further, future studies may see that the response rate is higher than 80 percent to increase the generalizability. Second, longitudinal studies may help see the effect of knowledge sharing on psychology, which, in turn, influences organizational commitment. Third, future researchers can compare the HEIs in developed countries with those of developing countries to see if cultural differences influence the relationships. Fourth, researchers may include other variables such as emotional intelligence, stress and burnout, emotional exhaustion, and interpersonal trust in influencing the relationships between knowledge sharing and organizational commitment. Fifth, future studies may delve into changing nature of knowledge sharing in the present-day Industry 4.0/5.0, as suggested by some latest scholars [91]. Finally, the role of knowledge sharing in connection with human-centric operations management framework can be explored by future research [92].

5.4. Conclusions

A conceptual model based on three theories (POB, OLT, and OCT) was developed and tested in this research. We integrated these theories to tie the relationship between knowledge sharing, psychological capital, and organizational commitment. We attempted answers to the overarching research questions of how knowledge sharing is a precursor to psychological capital and organizational commitment. In addition, the roles of self-actualization and gender in influencing these relationships are highlighted. More specifically, deciphering the dynamic interaction between knowledge sharing and self-actualization in enhancing psychological capital adds to the burgeoning research. The findings from this study provide valuable guidelines for administrators in HEIs to create a positive organizational climate for knowledge sharing and incentivize faculty to increase their commitment to maintain a sustained competitive advantage. As HEIs are knowledge hubs, this study provides valuable guidelines for future research on knowledge sharing and its effects on organizational commitment.