Index

Abstract

This study aims to examine the relationship between the hidden motives for sharing knowledge, organizational recognition and the moderating role of the need for status. The survey data was collected from 798 employees through convenient sampling from public sector organizations in Fiji. The findings revealed that the need for status significantly moderated the relationship between hidden motives to share knowledge and organizational recognition. In congruence with the costly signaling theory (CST), the study identified an underlying motive that can motivate individuals to proactively engage in sharing valued resources to gain social prestige and self-recognition. The findings also revealed that by sharing highly valued resources individuals maintained social status and at the same time earned preferential treatment in the organization. As such, this became our major contribution to the existing literature on knowledge management. Finally, this study brings a new dimension to unleashing the hidden motivation of knowledge sharing behavior through the individual need for status and the real benefit of managing individuals in an organization. Organizations can effectively create a work context that would encourage more proactive knowledge sharing behavior and also set a platform for the fulfillment of the individual need for status. Moreover, it becomes the responsibility of leaders to elicit belief in individuals that efforts made to share knowledge is highly valuable and distinguishable, and any cost incurred will not be wasted. The limitations and suggestions for further research are also discussed.

Keywords: Knowledge sharing, Organizational recognition, Need for status, Costly signaling theory, Self-prestige, Self-enhancement, Impression management, Self-recognition.

Received: 23 October 2020 / Revised: 12 November 2020 / Accepted: 2 December 2020/ Published: 17 December 2020

Contribution/ Originality

This is one of the few studies that sheds light on costly signaling theory to explain how an individual's hidden motivation to share knowledge can be unleashed through the need for status beyond self-sacrificing behavior.


1. INTRODUCTION

Knowledge is a crucial resource for organizations and sharing such a resource provides a greater competitive edge in today's volatile economy. Knowledge sharing is a process in which individuals mutually share knowledge and jointly generate new sets of knowledge (Van den Hooff & de Ridder, 2004). However, knowledge sharing often creates a dilemma for individuals for various reasons (Cabrera, Collins, & Salgado, 2006). First, sharing of knowledge can lower the value of an individual and damage their status and know-how relevant to employment and current status in the organization (Renzl, 2008), second, it poses an inherent risk indicating that reciprocation between the knowledge possessor and the receiver cannot be always guaranteed (Szulanski, 1996), and third, it triggers the problem of the "free-rider" who claims the benefit without reciprocation (Cabrera & Cabrera, 2002). As such, it becomes an interesting phenomenon to investigate the hidden motives for sharing knowledge in an organization.

The extant literature has implicitly assumed that knowledge sharing can be enhanced through extrinsic factors, such as rewards, honorable titles or social motives of one’s own accord to increase collaboration in a group (Barton & Srivastava, 2002; Cabrera et al., 2006). While this seems to work well with some external stimuli, or where individuals sacrifice their own interests for extrinsic gain, the extant literature has overlooked individual readiness to share knowledge beyond self-sacrificing behavior. This research looks at the proactive approach of knowledge sharing behavior through the need for status in an organization. Based on the self-initiated and proactive form of knowledge sharing behavior, this study explores the motivational processes urging an individual to accumulate lost resources through knowledge sharing behavior for personal growth within an organization. We also draw attention to the costly signaling theory (Zahavi, 1995) to explain hidden motivation for knowledge-sharing behavior.

From the costly signaling theory perspective (Zahavi, 1995), individuals with a high need for status are more proactively involved in knowledge sharing as this behavior enhances their social recognition and prestige. The CST denotes that individuals spend a substantial amount of energy, money and time differentiating an individual from others and publicly advertise their qualities that are costlier to obtain, such as genetic endowment, intelligence, and resource control (Gintis, Smith, & Bowles, 2001). As such, the desire to acquire one's status is considered a principal driver of individual behavior (Berger, Rosenholtz, & Zelditch, 1980), therefore, the present study introduces the novel perspective of CST and identifies the individual need for status as a catalyst to enhance knowledge sharing behavior. Similarly, Dubois, Rucker, and Galinsky (2012) observed that employees with a high need for status are proactively involved in evaluating costs associated with knowledge hiding behavior and how this can be utilized for long-term personal growth.

This study concludes by discussing the theoretical and practical implications of the findings, which show that the relationship between hidden motivation to share knowledge and organizational recognition is strengthened by the moderating role of the individual need for status. Finally, from an organizational and managerial perspective, leaders could encourage more proactive knowledge sharing behavior and set a platform for the fulfillment of the individual need for status.

2. THEORY AND HYPOTHESIS

2.1. Knowledge Sharing Behavior and Organizational Recognition

Knowledge sharing is considered to be the primary method to gain a competitive edge and aspiration for career success (Stewart & Clare, 1998). It is defined as an "act of making knowledge available to others within the organization" and "involves some conscious action on the part of the individual who possesses the knowledge" (Ipe, 2003). Sharing of knowledge has been positively associated with improvement in efficiency, cost reduction, empowerment growth, and performance (Hansen, 2002; Mesmer-Magnus & DeChurch, 2009; Nonaka & Takeuchi, 1995). It has been observed that employees tend to succeed when supervisors truly recognize their talent and creativity and focus more on nurturing, promoting and recognizing, as individuals are regarded as sources of novel ideas (Williamson, 2001).

Although existing literature has assumed that knowledge sharing can be enhanced through extrinsic factors (Barton & Srivastava, 2002; Cabrera et al., 2006), research has also highlighted that autonomous forms of motivation can also yield improved individual behavior (Ryan & Deci, 2017). Intrinsic motivation being autonomous of motivation enables individuals to engage in activity for enjoyment, interest and self-prestige, and because it is associated with self-prestige, individuals are more likely to spontaneously share their knowledge, even if not solicited. Similarly, when individuals perceive that knowledge sharing can also attain organizational recognition, they are likely to share more knowledge. While much literature has focused on knowledge sharing behavior, little is known about how the need for status can affect the relationship between hidden motivation for sharing knowledge and organizational recognition. Costly signaling theory postulates that by showcasing their qualities at great personal cost to serve the collective, individuals achieve prestige and gain social recognition from others in the work setting (Gintis et al., 2001; Zahavi, 1995). In other words, an individual with a high need for status fulfills their desire through the sharing of knowledge and skills within the group. This signaling process enables the knowledge sharer to earn prestige and recognition for the quality and contributions to the collective, while others may benefit from the expanded knowledge reservoir (Semmann, Krambeck, & Milinski, 2004). Hence, social recognition serves as a vital factor in the evolution and recurrence of socially desirable attitudes and behavior as "social prestige functions like a peacock's tail or the song of a songbird, attracts collaborators and deters rivals" (Zahavi, 1995). For instance, Milinski (2006) denoted that supervisors, as key evaluators, tend to share stories of how individuals share valuable resources and knowledge on a common interest thus increasing the reputation and social position of knowledge sharers in the workplace. As such, the position or status of an individual largely depends on the endorsement and recognition of the supervisor or the managers, who are vested with legitimate control and power to allocate resources, promotions and incentives (Yukl, 2012).

We applied the principle of costly signaling theory (CST) to proactive knowledge sharing behavior in workgroup settings. Similar to proactive knowledge, prior literature also highlighted that individuals engage in knowledge sharing behavior for self-enhancement motives through impression management (Bolino, 1999; Grant & Mayer, 2009; Pfeffer & Fong, 2005; Yun, Takeuchi, & Liu, 2007). As such, self-enhancement behavior is described as "an individual employee's sensitivity to other people's perception of him or her and the employee's level of motivation to adapt his or her behavior to project a good self-image to others" (Yun et al., 2007). Prior literature also highlighted that self-enhancement through impression management motives can engender responsive acquiescent behavior in fulfilling expectations (Bolino, Varela, Bande, & Turnley, 2006; Grant & Mayer, 2009; Wayen & Liden, 1995). On the contrary, CST denotes that individual need for status leads to aggressive and proactive use of valuable resources, which are sufficiently costly in sending signals. In other words, CST appears to be more appropriate compared to self-enhancement behavior in explaining proactive knowledge sharing and the generous sharing of valuable resources in a work setting (George, Dahlander, Granffin, & Sim, 2016; Gintis et al., 2001; Smith & Bliege, 2000; Zahavi, 1995). Leaders form a positive impression of individuals who tend to exhibit more voluntary behavior, such as extra-role behavior towards organizational change (Bolino et al., 2006; Rioux & Penner, 2001), and leaders recognize this valued contribution as proactive knowledge sharing behavior (Gong, Kim, Lee, & Zhu, 2013; Nonaka & Takeuchi, 1995). According to Yukl (2012), such recognition from a leader embodies high status and social prestige in the workplace. Therefore, sharing of knowledge can be considered as an intermediate means of achieving social standing and organizational recognition and this can be strengthened by an individual with a high need for status. As such, we propose the following hypothesis:
H1: Knowledge sharing behavior is positively related to organizational recognition.

2.2. The Moderating Role of Individual Need for Status

Knowledge is casually ambiguous, unique and difficult to substitute and it provides a sustainable and competitive advantage for individuals and organizations (Kogut & Zander, 1992; Nonaka & Takeuchi, 1995). Thus, intangible resources can be represented by knowledge, particularly accumulated as know-how or as tacit knowledge, and are considered to be key factors in achieving status within an organization (Cabrera & Cabrera, 2002). According to McIver, Lengnick-Hall, Lengnick-Hall, and Ramachandran (2013), knowledge is "talent and intuitive know-how" as this is developed through idiosyncratic experiences. As such, it becomes exclusive as this is developed through considerable time and effort (Renzl, 2008). Therefore, sharing this valuable and special knowledge is costly enough to uncover an individual's hidden superior qualities contributing to collectives (Connelly, Certo, Ireland, & Reutzel, 2011; Gintis et al., 2001; Spense, 1973). Moreover, tacit knowledge sharing behavior is considered to be costly signaling in achieving status. Zahavi (1995) denotes that "prestige may be gained by investing in wasteful characters as well as by investing in altruistic activities" (p. 2) through the individual need for status. As such, the need for status has been defined as an "individual motive to attain respect or admiration by others" (Dubois et al., 2012). Costly signaling theory posits that individuals generously and willingly share personal resources to gain recognition and enhance social prestige through advertising one's hidden qualities to convince people of their superiority (Gintis et al., 2001; Zahavi, 1995). CST also shows that individuals share valuable and costly resources with others resulting in reciprocation and kin selection (Hamilton, 1964). With the inherent risk of return, costly signaling theory denotes that a self-sacrificial attitude and behavior may emerge from the need to "stand out" through excessive exposure of resources flaunting the hidden qualities in social settings (Gintis et al., 2001; Zahavi, 1995). As such, individuals with resultant resource loss and sacrificial behavior earn the long-term benefits of being chosen as a superior mate or a competent coalition partner in an organization (Smith & Bliege, 2000). Such behavior makes an individual more capable, generous and highly attractive because of their unselfish contributions (Gintis et al., 2001; Zahavi, 1995). For example, excessive displays of generosity and altruism can be exhibited through food sharing or housewarming parties (Hawkes & Bliege, 2002).

Prior literature has shown that individuals tend to cooperate and behave altruistically when behaviors are distinct and linked with a social reputation (Hardy & Van Vugt, 2006; McAndrew, 2002), while Gintis et al. (2001) highlighted that sacrificing for others is an evolutionary strategy, signaling to promote one's long-term survival. As alluded to above, a similar finding was also noted in the context of corporate governance, entrepreneurship and the labor market (Connelly et al., 2011). The assertions of CST denote that the need for status in an organization is a powerful motive to induce socially desirable behavior, such as engagement in knowledge sharing (Berger et al., 1980; Dubois et al., 2012). While effectively contributing to the collective cause in an organization, the need for status confers an individual's desire for recognition and unleashes hidden valuable resources. Thus, with the desire to achieve prestigious social status and recognition, individuals will proactively engage in knowledge sharing behavior compared to an individual with a debilitated status. Similarly, prior literature also highlighted that individuals with a desire for organizational recognition will not hesitate to engage in activities with such enormous costs (Hardy & Van Vugt, 2006; Hawkes & Bliege, 2002; Milinski, 2006; Millet & Dewitte, 2007). Based on this, we suggest the following hypothesis:

H2: Need for status will positively moderate the relationship between knowledge sharing behavior and organizational recognition.

In summary, our proposed research model comprises knowledge sharing behavior (KS), organizational recognition (OR) and moderating roles of need for status (NS), as shown in Figure 1.

Figure 1. Proposed research model for the study.

Note: The framework in Figure 1 provides a proposed model for the research, suggests that a hidden motive to share knowledge depends on organizational recognition. The relationship can be strengthened through the moderating role of the need for status.

3. METHOD

3.1. Sample

A total of 798 public service employees from the island of Fiji participated in the research and 41.4% of the participants are male and 58.6% are female. The age categories are 20–25 years (12.9%), 26–30 years (41.2%), 31–35 years (25.9%), 36–40 years (7.4%) and 41 years and above (12.6%). In addition, the organizational experience gained was broken down into 1–5 years (12.5%), 6–10 years (38.2%), 11–15 years (13.6%), 16–20 years (7.3%), more than 20 years (10.2%) and more than 17 years (18.2%). We also included salary scales as part of the control variable, which was captured as the following: less than FJD 10,000 (11.3%), FJD 10,000–20,000 (35.1 %), FJD 20,000–30,000 (50.2%), FJD 30,000–40,000 (1.6%) and more than FJD 40,000 (1.8%). The survey was distributed to the civil servants of three large public sector organizations from Fiji (Ministry of Health, Ministry of Education and Ministry of Agriculture). Through convenient sampling, the participants voluntarily completed and returned the self-completed survey.

3.2. Measures

The participants voluntarily responded to multiple items using a five-point Likert scale (1 = strongly disagree, 5 = strongly agree).

3.3. Knowledge Sharing Behavior (KS)

We measured knowledge sharing using a seven-item scale proposed by Srivastava, Bartol, and Locke (2006). The respondents were requested to show the frequency of knowledge sharing behavior with coworkers. The sample items included: "This employee freely provides others with hard-to-find knowledge or specialized skills" The Cronbach's α as 0.91.

3.4. Organizational Recognition (OR)

Organizational recognition was measured on a three-item scale developed by Allen and Rush (1998) that included "This employee would be extremely costly to replace”, and the Cronbach's α (alpha) was 0.87.

3.5. Need for Status (NS)

An eight-item scale proposed by Flynn, Reagans, Amanatullah, and Ames (2006) was used to measure the need for status. The sample items included "I would like to cultivate the admiration of my peers", and the Cronbach's α here was 0.89.

4. DATA ANALYSIS AND RESULTS

The reliability and validity of the three constructs were evaluated through the validation processes and procedures. First, the reliability of the three constructs was evaluated to determine the Cronbach's α coefficient (see Table 1). As such, the reliability coefficient extended from 0.89 to 0.91, which was considered to be excellent for the study (Nunnally, 1978). A confirmatory factor analysis (CFA) formed the basis for verification and determining the convergent and discriminant validity using SPSS and AMOS software. All measurement items showed excellent reliability and composite reliability extending from 0.75 to 0.88 (see Table 1). As per the procedures outlined by Fornell and Larcker (1981), we evaluated discriminant validity and found the variance extracted (AVE) was a bit higher than the squared correlation between the constructs (see Table 1). The results show that all measurement constructs were suitable for the study, as suggested by Cheung and Lau (2008). We also evaluated the fit indices to determine the proposed hypothesized model using the structural equation model (SEM). SEM can be used to verify latent multiple indicators and control measurement errors. We used goodness of fit indices to test the model fit, e.g., chi-square (χ2), CFI, IFI, TLI and RMSEA. The recommended model fit, CFI and TLI need to be greater than 0.80, while RMSEA needs to be ≤ 0.06 (Hu & Bentler, 1999). Thus, the proposed structural model was evaluated to determine GFI through χ2, ILI, RAMSEA, CFI and TLI (see Table 4). Finally, we evaluated the moderation effect through conditional process analyses  (Hayes, 2018).

4.1. Common Method Bias (CMB)

Common method bias (CMB) poses a potential threat of bias in behavioral research, especially when single-phase data is collected (Podsakoff, MacKenzie, & Podsakoff, 2012). However, this potential threat can be mitigated through statistical remedies suggested by Podsakoff et al. (2012) and was used in the current study. During the data collection the respondents maintained anonymity, special care was taken with individual items and their wording, and we separated the predictor variables from other variables. We used the confirmatory factor analysis (CFA) to eliminate CMB. As suggested by Bagozzi, Yi, and Phillips (1991), any correlation between the constructs of more than 0.90 shows the presence of CMB. Our study showed the correlation between the focal construct to be 0.68 (see Table 1). Moreover, the common latent factor (CLF) was used to check the standardized regression weights for the proposed measurement model and the difference was minuscule. Statically, the analysis showed no threat of common method bias.

4.2. Measurement Model

The analysis shows that all constructs were very reliable and well above 0.5, and Cronbach's alpha was above 0.80. The average variance extracted (AVE) together with composite reliability (CR) exceeded the threshold of 0.5 and 0.7 (Fornell & Larcker, 1981). The average variance extracted (AVE) for three variables, knowledge sharing (KS), organizational recognition (OR) and need for status (NS), were 0.75, 0.56 and 0.77, respectively, and construct validity was accepted (see Table 1). Moreover, Table 2 shows cross-loading, an acceptable level of discriminant validity of measured constructs, while Table 3 shows the standard deviation, mean, and inter-correlation between the variables, further confirming the discriminant validity of the measurement constructs (Gefen, Straub, & Boudreau, 2000).

Table 1. Descriptive statistics and the reliability coefficient.

Descriptive statistics and reliability coefficient (AVE-average variance extracted)
Item
Mean
SD
Item-total correlation
Loading
Error
Cronbach's alpha
Composite reliability
AVE
KS 1
3.83
0.84
0.610
0.810
0.035
0.91
0.84
0.71
KS 2
3.79
0.83
0.860
0.867
0.037
KS 3
3.75
0.85
0.820
0.856
0.036
KS 4
3.77
0.82
0.770
0.822
0.039
KS 5
3.69
0.82
0.700
0.765
0.042
KS 6
3.76
0.88
0.670
0.702
0.040
KS 7
3.42
0.81
0.583
0.712
0.041
NS 1
3.74
0.84
0.730
0.732
0.042
0.89
0.88
0.77
NS 2
3.82
0.85
0.860
0.857
0.044
NS 3
3.83
0.91
0.850
0.850
0.047
NS 4
3.78
0.80
0.860
0.847
0.043
NS 5
3.80
0.75
0.690
0.855
0.045
OR 1
3.22
0.80
0.692
0.881
0.115
0.87
0.75
0.56
OR 2
3.52
0.85
0.870
0.854
0.113
OR 3
3.57
0.74
0.900
0.858
0.118

Table 2. Cross-loading matrix.

Matrix of loading and cross-loading
 
KS
NS
OR
KS 1
0.836**
0.590**
0.383**
KS 2
0.864**
0.629**
0.415**
KS 3
0.863**
0.581**
0.465**
KS 4
0.846**
0.582**
0.358**
KS 5
0.804**
0.530**
0.356**
KS 6
0.771**
0.534**
0.394**
KS 7
0.652**
0.640**
0.323**
NS 1
0.528**
0.811**
0.475**
NS 2
0.582**
0.877**
0.521**
NS 3
0.620**
0.759**
0.563**
NS 4
0.567**
0.876**
0.523**
NS 5
0.551**
0.850**
0.497**
OR 1
0.440**
0.530**
0.871**
OR 2
0.479**
0.557**
0.812**
OR 3
0.398**
0.554**
0.845**

The result of the correlation between variables was analyzed through Pearson correlation analysis (see Table 3) and the relationship was investigated through SEM.

Table 3. Mean, standard deviation, and inter-correlation among variables.

Variables
Mean
SD
1
2
3
4
5
6
7
1. Age
2.80
1.35
1
2. Gender
2.00
1.01
0.02
1
3. Occupational Experience
2.69
1.40
0.74**
0.14**
1
4. Salary Scale
2.81
0.88
0.26**
-0.03
0.31**
1
5. KS
3.81
0.78
0.01
-0.07**
0.02
0.10**
1
6. OR
3.43
0.79
-0.02
-0.17**
-0.06
0.09**
0.44**
1
7. NS
3.78
0.71
0.05
0.07
0.11**
-0.02
0.68**
0.35**
1

Note: * p < 0.05. ** p < 0.01.

Table 4. Model fit.

X2
df
RMR
RAMSEA
IFI
TLI
CFI
252.676
87
0.027
0.051
0.973
0.97
0.97

Table 5. The moderating effect of need for status (NS).

 
Step 1
Step 2
Step 3
 
b
SE
β
b
SE
β
b
SE
β
Constant
3.470
0.119
1.166
0.192
1.115
0.191
Age
0.027
0.032
0.04
0.040
0.029
0.067
0.034
0.028
0.056
Gender
-0.113
0.029
-0.140
-0.095
0.026
-0.117***
-0.087
0.026
-0.107***
Occ
-0.065
0.032
-0.111*
-0.092
0.028
-0.158***
-0.091
.028
-0.157***
Salary
0.104
0.034
0.111*
0.120
0.031
0.128***
0.118
0.030
0.126***
KS
0.412
0.052
0.341***
0.421
0.051
0.349***
NS
0.181
0.054
0.144***
0.175
0.054
0.139***
KS*NS
0.143
0.041
0.110***
R2
0.039
0.241
0.253
R2
0.034***
0.236***
0.247***

Note: Dependent Variable: Organizational Recognition (OR).
Note: **p < 0.01, ***p < 0.001: Dummy variable: Gender (0 = male, 1 = female), age, occupational experience, salary scale. KS = Knowledge Sharing: NS = Need for Status.

The goodness of fit indices for the proposed research model shows the best model fit for the study to be: x2 = 252.676; df = 87; RMR = 0.027; RAMSEA = 0.051, IFI = 0.973; TLI = 0.97 and CFI = 0.97 (see Table 4). The control variables for the study included age, organizational experience, gender and salary scale, and were statistically significant. Knowledge sharing had a positive correlation with organizational recognition (β = 0.341, p < 0.001), and hypothesis one was accepted. A significant R2 (0.236) in model 5 provides collateral evidence in support of H1. In addition, hypothesis 2 was also accepted as the need for status showed a significant positive moderating effect (β = 0.110, p < 0.001) thereby strengthening the positive effect between knowledge sharing and organizational recognition (see Table 5). Table 5 provides a summary of the interaction effect of the need for status.

Figure 2. The interaction effect of need for status (NS) between knowledge sharing and organizational recognition.

The analysis of moderating effects showing two-way integration was plotted, as suggested by Stone and Hollenbeck (1989). Figure 2 shows that individuals achieve a high need for status through engaging more in knowledge sharing behavior.

5. DISCUSSION

The individual behaviors in the organization are guided through intricate motivation orientations, which are interwoven by different motives, the most common being the extrinsic incentives and selfish motives that drive individual motivational orientation. Prior literature has assumed that hidden motives of knowledge sharing behavior can be unleashed through extrinsic incentives (Bartol & Srivastava, 2002; Cabrera et al., 2006), while self-sacrificial behavior needs to "stand out" through excessive exposure of resources flaunting the hidden qualities in social settings and has been overlooked (Gintis et al., 2001; Zahavi, 1995). Therefore, we address this dilemma through the costly signaling theory (Zahavi, 1995).

Based on costly signaling theory, this study identified an underlying motive that can motivate individuals to proactively engage in sharing valuable resources to gain social prestige and recognition. As such, we specifically focused on the individual need for status by sharing tacit knowledge in promoting one's social prestige through organizational recognition. The finding of the study was in congruence with costly signaling theory (CST), which states that by indulging in costly signaling behavior individuals spend a substantial amount of money, time and energy differentiating them from others, and publicly advertise qualities that are costlier to obtain, such as genetic endowment, intelligence and resource control to gain social prestige. CST further postulates that by sharing highly valued resources individuals maintain social standing and at the same time earn preferential treatment in an organization (Zahavi, 1995).

The current study applied the costly signaling theory to the motivational dilemma of knowledge sharing behavior. Strategically, while it is true that individuals tend to recover lost resources through incentives (Wang & Noe, 2019; Wasko & Faraj, 2005), we reevaluate the understudied proactive knowledge sharing behavior through internal dispositional behaviors, such as the individual need for status to gain organizational recognition. The findings of the study indicate a positive relationship between knowledge sharing and organizational recognition. For instance, the costly signaling theory could encourage individuals to strive for power through spontaneously displaying valuable resources to gain recognition from leaders or management (Cabrera et al., 2006; Ipe, 2003). This motive of self-enhancement could also lead to a need for status and by exhibiting positive behavior and achieving prestigious status within an organization an individual may engage more in knowledge sharing behavior. However, sharing high-quality knowledge could also be viewed as "showing off". As such, the costly signaling theory labels such behavior as very costly yet reliable. Therefore, the present study shows that knowledge sharing behavior and its influence on organizational recognition is more contingent on the individual desire for prestigious status in an organization.

6. PRACTICAL IMPLICATION AND CONTRIBUTION

This study introduces a new dimension in uncovering hidden motivation for knowledge sharing behaving through the individual need for status and provides real benefit to managing individuals in an organization. The empirical and theoretical analysis resonates with several practical implications on improvement in job design factors with more autonomy in the decision-making process (Grant, 2007; Humphrey, Nahrgang, & Morgeson, 2007). In addition to extrinsic incentives, an organization can effectively create a work context that could encourage more proactive knowledge sharing behavior and set a platform for the fulfillment of individual desires for the need for status. As such, the supervisors need to elicit belief in employees that sharing of knowledge is utmost important in the organization, and any cost incurred in acquiring will not be wasted. This contemporary behavior can be driven by the activation of CST in the organization.

7. LIMITATION AND DIRECTION FOR FUTURE STUDY

While the present study makes a significant contribution to the extant literature, some limitations require further consideration. Though the present study positively links hidden motivation for knowledge sharing to organizational recognition through the need for status, future research could elaborate on another channeling mechanism that could trigger the hidden motives for knowledge sharing behavior through perceived team support, perceived coworkers support and supervisory support. Second, the measurement of knowledge sharing behavior specifically looked at constructs on an individual level and future research could replicate the model at an organizational level. Finally, the current study used a quantitative method to collect data for the evaluation process and future research could also include case studies to collect data on the organization.

Funding: This study received no specific financial support.  

Competing Interests: The authors declare that they have no competing interests.

Acknowledgement: All authors contributed equally to the conception and design of the study.

REFERENCES

Allen, T. D., & Rush, M. C. (1998). The effects of organizational citizenship behavior on performance judgments: A field study and a laboratory experiment. Journal of Applied Psychology, 83(2), 247–260.Available at: https://doi.org/10.1037/0021-9010.83.2.247.

Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in. Administrative Science Quarterly, 36(3), 421-458.Available at: http://dx.doi.org/10.2307/2393203 .

Bartol, K. M., & Srivastava, A. (2002). Encouraging knowledge sharing: The role of organizational reward systems. Journal of Leadership & Organizational Studies, 9(1), 64-76.

Barton, K., & Srivastava, A. (2002). Encouraging knowledge sharing: The roles of organizational reward system. Journal of Leadership and Organizational Studies, 9(1), 64-77.Available at: https://doi.org/10.1177/107179190200900105.

Berger, J., Rosenholtz, S. J., & Zelditch, M. (1980). Status organizing processes. Annual Review of Sociology, 6, 479–508.Available at: 10.1146/annurev.so.06.080180.002403.

Bolino, M. C. (1999). Citizenship and impression management: Good soldiers or good actors? Academy of Management Review, 24, 82–98.Available at: 10.5465/AMR.1999.1580442.

Bolino., M. C., Varela, J. A., Bande, B., & Turnley, W. H. (2006). The impact of impression-management tactics on supervisor ratings of organizational citizenship behavior. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 27(3), 281-297.Available at: https://doi.org/10.1002/job.379.

Cabrera, A., Collins, W. C., & Salgado, J. F. (2006). Determinants of individual engagement in knowledge sharing. The International Journal of Human Resource Management, 17, 245–264.Available at: 10.1080/09585190500404614.

Cabrera., A., & Cabrera, E. F. (2002). Knowledge-sharing dilemmas. Organization Studies, 23(5), 687-710.Available at: https://doi.org/10.1177/0170840602235001.

Cheung, G. W., & Lau, R. S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296-325.Available at: https://doi.org/10.1177/1094428107300343.

Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling theory. A review and assessment. Journal of Management, 37, 39–67.Available at: 10.1177/0149206310388419.

Dubois, D., Rucker, D. D., & Galinsky, A. D. (2012). Super size me: Product size as a signal of status. Journal of Consumer Research, 38, 1047–1062.Available at: 10.1086/661890.

Flynn, F. J., Reagans, R. E., Amanatullah, E. T., & Ames, D. R. (2006). Helping one’s way to the top: Self-monitors achieve status by helping others and knowing who helps whom. Journal of Personality and Social Psychology, 91, 1123–1137.Available at: 10.1037/0022-3514.91.6.1123.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Market Research, 18, 382–388.Available at: https://doi.org/10.2307/3151335.

Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1-77.

George, G., Dahlander, L., Granffin, S. D., & Sim, S. (2016). Reputation and status: Expanding the role of social evaluations in management research. Academy of Management Journal, 59, 1–13.Available at: 10.5465/amj.2016.4001.

Gintis, H., Smith, E. A., & Bowles, S. (2001). Costly signaling and cooperation. Journal of Theoretical Biology, 213(1), 103-119.

Gong, Y., Kim, T.-Y., Lee, D.-R., & Zhu, J. (2013). A multilevel model of team goal orientation, information exchange, and creativity. Academy of Management Journal, 56(3), 827-851.Available at: https://doi.org/10.5465/amj.2011.0177.

Grant, A., & Mayer, D. (2009). Good soldiers and good actors: Prosocial and impression management motives as interactive predictors of affiliative citizenship behaviors. The Journal of Applied Psychology, 94(4), 900-912.Available at: https://doi.org/10.1037/a0013770.

Grant., A. M. (2007). Relational job design and the motivation to make a prosocial difference. Academy of Management Review, 32, 393–417.Available at: 10.5465/AMR.2007.24351328.

Hamilton, W. D. (1964). The genetical evolution of social behavior. Journal of Theoretical Biology, 7, 17–52.Available at: 10.1016/0022-5193(64)90039-6.

Hansen, M. T. (2002). Knowledge networks: Explaining effective knowledge sharing in multiunit companies. Organization Science, 13(2), 232–248.Available at: https://doi.org/10.1287/orsc.13.3.232.2771.

Hardy, C. L., & Van Vugt, M. (2006). Nice guys finish first: The competitive altruism hypothesis. Personality and Social Psychology Bulletin, 32(10), 1402-1413.Available at: https://doi.org/10.1177/0146167206291006.

Hawkes, K., & Bliege, B. R. (2002). Showing off, handicap signaling, and the evolution of men's work. Evolutionary Anthropology: Issues, News, and Reviews: Issues, News, and Reviews, 11(2), 58-67.Available at: https://doi.org/10.1002/evan.20005.

Hayes, A. F. (2018). Introduction to mediation, moderation and conditional process analysis, a regression based approach. New York: Guilford Press.

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.Available at: https://doi.org/10.1080/10705519909540118.

Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92(5), 1332-1356.Available at: https://doi.org/10.1037/0021-9010.92.5.1332.

Ipe, M. (2003). Knowledge sharing in organizations: A conceptual framework. Human Resource Development Review, 2, 337–359.Available at: 10.1177/1534484303257985.

Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383-397.Available at: https://doi.org/10.1287/orsc.3.3.383.

McAndrew, F. T. (2002). New evolutionary perspectives on altruism: Multilevel-selection and costly-signaling theories. Current Directions in Psychological Science, 11(2), 79-82.Available at: https://doi.org/10.1111/1467-8721.00173.

McIver, D., Lengnick-Hall, C. A., Lengnick-Hall, M. L., & Ramachandran, I. (2013). Understanding work and knowledge management from a knowledge-in-practice perspective. Academy of Management Review, 38(4), 597-620.Available at: https://doi.org/10.5465/amr.2011.0266.

Mesmer-Magnus, J. R., & DeChurch, L. A. (2009). Information sharing and team performance: A meta-analysis. Journal of Applied Psychology, 94(2), 535-546.Available at: https://doi.org/10.1037/a0013773.

Milinski, M. (2006). Reputation, personal identity, and cooperation in a social dilemma. In P. M. Kappeler & C. P. Van Schaik (Eds.), Cooperation in primates and humans (pp. 265–278). Berlin, Germany: Springer.

Millet, K., & Dewitte, S. (2007). Altruistic behavior as a costly signal of general intelligence. Journal of Research in Personality, 41(2), 316-326.Available at: https://doi.org/10.1016/j.jrp.2006.04.002.

Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press.

Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

Pfeffer, J., & Fong, C. T. (2005). Building organization theory from first principles: The self-enhancement motive and understanding power and influence. Organization Science, 16(4), 372-388.Available at: https://doi.org/10.1287/orsc.1050.0132.

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539-569.Available at: https://doi.org/10.1146/annurev-psych-120710-100452.

Renzl, B. (2008). Trust in management and knowledge sharing: The mediating effects of fear and knowledge documentation. Omega, 36(2), 206-220.Available at: https://doi.org/10.1016/j.omega.2006.06.005.

Rioux, S. M., & Penner, L. A. (2001). The causes of organizational citizenship behavior: A motivational analysis. Journal of Applied Psychology, 86(6), 1306-1314.Available at: https://doi.org/10.1037/0021-9010.86.6.1306.

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness (pp. 123-158). New York: Guilford Press.

Semmann, D., Krambeck, H.-J., & Milinski, M. (2004). Strategic investment in reputation. Behavioral Ecology and Sociobiology, 56(3), 248-252.Available at: https://doi.org/10.1007/s00265-004-0782-9.

Smith, E. A., & Bliege, B. R. (2000). Turtle hunting and tombstone opening: Public generosity as costly signaling. Evolution and Human Behavior, 21, 245–261.Available at: 10.1016/S1090-5138(00)00031-3.

Spense, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355-374.Available at: https://doi.org/10.2307/1882010.

Srivastava, A., Bartol, K. M., & Locke, E. A. (2006). Empowering leadership in management teams: Effects on knowledge sharing, efficacy, and performance. Academy of Management Journal, 49(6), 1239-1251.Available at: https://doi.org/10.5465/amj.2006.23478718.

Stewart, T., & Clare, R. (1998). Intellectual capital. The new wealth of organizations. Performance Improvement, 37(7), 56–59.

Stone, E. F., & Hollenbeck, J. R. (1989). Clarifying some controversial issues surrounding statistical procedures for detecting moderator variables: Empirical evidence and related matters. Journal of Applied Psychology, 74(1), 3-10.

Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17, 27–43.Available at: 10.1002/smj.4250171105.

Van den Hooff, B., & de Ridder, J. A. (2004). Knowledge sharing in context: The influence of organizational commitment, communication climate and CMC use on knowledge sharing. Journal of Knowledge Management, 8(6), 117–130.Available at: https://doi.org/10.1108/13673270410567675.

Wang, S., & Noe, R. (2019). Knowledge sharing: A review and directions for future research. Human Resource Management Review, 20(2), 115-131.Available at: https://doi.org/10.1108/hrmid-08-2019-0214.

Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35-57.Available at: https://doi.org/10.2307/25148667.

Wayen, S., & Liden, R. (1995). Effects of impression management on performance araisal Study. Academy of Management Journal, 38(1), 232-260.Available at: https://doi.org/10.2307/256734.

Williamson, B. (2001). Creativity, the corporate curriculum and the future: A case study. Futures, 33(6), 541-555.Available at: https://doi.org/10.1016/s0016-3287(00)00097-5.

Yukl, G. A. (2012). Leadership in organizations (8th ed.). Upper Saddle River, NJ: Prentice Hall International.

Yun, S., Takeuchi, R., & Liu, W. (2007). Employee self-enhancement motives and job performance behaviors: Investigating the moderating effects of employee role ambiguity and managerial perceptions of employee commitment. Journal of Applied Psychology, 92(3), 745-756.Available at: https://doi.org/10.1037/0021-9010.92.3.745.

Zahavi, A. (1995). Altruism as a handicap: The limitations of kin selection and reciprocity. Journal of Avian Biology, 26(1), 1-3.Available at: https://doi.org/10.2307/3677205.

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