Knowledge sharing motivation in the public sector: the role of public service motivation

Abstract

The literature on knowledge sharing motivation has addressed the importance of both extrinsic and intrinsic motivation to sharing knowledge. However, a theory of knowledge sharing motivation in the public sector requires particular consideration since government’s main concern is in public service, not profits. Therefore, the present study introduces the concept of public service motivation (PSM) to the study of knowledge sharing among civil servants. Based on the PSM theory, this study postulates that civil servants’ interest in policy making, commitment to the public interest, compassion, and willingness for self-sacrifice can drive them to share knowledge for a sacred reason – serving the public interest. By using the data collected from middle-level public managers in Taiwan, the authors empirically tested whether PSM predicts knowledge sharing, and our hypotheses received strong support. Thus, PSM opens a new window for researchers interested in the study of knowledge sharing in the public sector.

Points for practitioners

With the introduction of PSM, the present study connects knowledge sharing with public administration. Public service as a calling leads civil servants to share knowledge in order to create more advanced organizational knowledge and accordingly improve public service performance. Compared to situational factors (e.g. the use of information technology and rewards), PSM plays an even more pivotal role in promoting knowledge sharing, according to the results of our empirical research. Thus, altruistic motivation should be addressed and emphasized if knowledge sharing in the public sector is to be encouraged.

Keywords

knowledge sharing public service motivation

Introduction

Knowledge is indispensable to virtually all organizations, particularly public organizations. Modern governments are expected to solve complicated problems regarding human livelihoods and to serve as driving forces to enhance societal growth (Milbraith, 1989), and solving problems needs expertise. From the view of the politics–administration dichotomy, the source of civil servants’ power is not election, but professional knowledge (Meier, 2006; Rourke, 1984). According to Waldo (1980), public administration as an innovative and active driver that facilitates civilization in history relies on its continuously updated and cutting-edge knowledge.

Surprisingly, the management of knowledge has received limited attention in the field of public administration. Focusing on knowledge sharing, we find only two articles in mainstream public administration journals (Kim and Lee, 2006; Willem and Buelens, 2007). Indeed, a few publications that explore antecedents of knowledge sharing in the public sector appear in generic management journals (Cong et al., 2007; Lee and Ahn, 2007; Sandhu et al., 2011; Seba et al., 2012; Taylor and Wright, 2004; Yao et al., 2007; Yusof et al., 2012). The authors of these articles suggest that organizational structures, managerial commitment, leadership, trust in colleagues, information technology (IT), and rewards are key predictors for successful knowledge sharing in the public sector. However, a theory of knowledge sharing motivation in the public sector has not yet been established. To address the gap, the present study investigates public sector knowledge sharing with a focus on motivation by introducing the concept of public service motivation (PSM) (Perry and Wise, 1990) to examine whether public sector employees are driven to share knowledge not only by incentives or other situational factors but also by a more sacred motive – serving the public interest. The findings are expected to enhance our understanding of knowledge sharing motivation and address the motivational structure for knowledge sharing in the public sector.

Knowledge sharing

Scholars have made serious efforts to discover miscellaneous propellers of and impediments to knowledge sharing in the hope of enhancing knowledge sharing. In general, these antecedents fall into three main categories (Ipe, 2003). The first category is the properties of knowledge itself. For example, whether knowledge is valuable, necessary for task accomplishment, and easily articulated determine individual knowledge sharing (Spender, 1996). The second category is opportunities to share, also referred to as situational factors, such as culture of the work environment, language, vision and goals, formal and centralized structures, IT application, and most importantly, managerial support (Kim and Lee, 2006; Yusof et al., 2012). The third category is motivation to share, the focus of the present study. According to Ipe (2003), there are four genres of knowledge sharing motivation (and demotivation): the fear of the loss of power, expected reciprocal benefits, rewards for sharing, and expected relationships with recipients. Most evidence-based studies of knowledge sharing motivation in the past decade include one or more of the aforementioned motivational factors (e.g. Bock et al., 2005). In sum, this preliminary typology serves as a solid research basis for knowledge sharing motivation.

Knowledge sharing motivation: a thorough review

Despite its contribution, Ipe’s (2003) typology of knowledge sharing motivation has an inherent flaw: this typology assumes that knowledge sharing is a result of a person’s deliberate calculation of costs and benefits (Bock et al., 2005) and employees will not share unless they perceive the benefits of sharing, such as reciprocal benefits, rewards, and stronger interpersonal ties. While accurate, this view is nonetheless incomplete. In fact, sharing is often defined as a voluntary act (Davenport and Prusak, 1997) and should be understood through the lens of intrinsic motivation. As Osterloh and Frey (2000) indicate, intrinsic motivation is as important as extrinsic motivation in determining knowledge sharing.

The intrinsic dimension of knowledge sharing motivation has been addressed in recent empirical research. However, the content of intrinsic motivation varies. For example, in some studies, intrinsic motivation refers to knowledge sharing self-efficacy, meaning that individuals feel the confidence to provide valuable knowledge to their colleagues (Hsu et al., 2007; Kankanhalli et al., 2005; Lin, 2007). In other studies, intrinsic motivation is interpreted as the sense of self-worth, reputation, or pride (Bock et al., 2005; Hsu and Lin, 2008; Kwok and Gao, 2004).¹ More commonly, intrinsic motivation is deemed to be a person’s affective-based willingness to help colleagues (Hsu and Lin, 2008; Kwok and Gao, 2004; Lin, 2007). A popular sentiment in these empirical studies is that intrinsic motivators, despite the forms, are more effective than extrinsic motivators in predicting knowledge sharing. This reflects Gagné’s (2009) perspective that being motivated to share out of interest or personal meaning results in more positive attitudes toward knowledge sharing.

The subcategories of intrinsic and extrinsic motivations reviewed in this section cover nearly all potential motivational predictors for knowledge sharing. It is fair to say that the development of knowledge sharing motivation research is approaching a mature level. However, we argue that a theory of knowledge sharing motivation in the public sector requires special consideration of its unique context. Due to the nature of public service provision, public sector organizations are more likely than businesses to attract those who are high in public service motivation (Steijn, 2008). We believe that public service motivation, as a special form of civil servants’ motivation, determines their knowledge sharing.

Public service motivation

Perry and Wise (1990: 368) first define PSM as ‘an individual’s predisposition to respond to motives grounded primarily or uniquely in public institutions and organizations’. Following this pioneer study, many public administration scholars have tried to give different definitions to PSM (Brewer et al., 2000; Bright, 2008; Houston, 2006; Rainey and Steinbauer, 1999; Vandenabeele, 2007; Wright and Pandey, 2008). Despite different descriptions, their definitions generally follow the line of altruism, as Perry et al. (2010) indicate in a review study of PSM. Basically, PSM is reflected in four dimensions, namely attraction to policy making, commitment to the public interest, compassion, and self-sacrifice (Perry, 1996). These dimensions are underpinned by three undergrounding mechanisms: rationality, norm, and affectivity (Perry and Wise, 1990).

In the present study, we anticipate that PSM as a form of altruistic motivation functions as an accelerator for organizational knowledge sharing in the public sector. However, we do not expect that the four dimensions of PSM will influence knowledge sharing through the same mechanism, and we do not expect that they will generate similar impacts on knowledge sharing as well. Below we elaborate our views.

PSM and knowledge sharing

We first hypothesize that ‘compassion’ as a core component of PSM promotes knowledge sharing. The undergirding logic of this relationship can be observed from the nature of knowledge sharing itself. Knowledge sharing as a voluntary act (Davenport and Prusak, 1997) to some extent resembles many prosocial and altruistic behaviors such as organizational citizenship behavior (Gagné, 2009). As stated earlier, empirical evidence shows that PSM is positively associated with organizational citizenship behavior (Kim, 2006; Pandey et al., 2008), as well as citizenship behavior outside of organizational settings such as volunteering, donating blood, and political participation (Houston, 2006; Perry et al., 2008; Taylor, 2008). The positive relationship between PSM and citizenship behavior is likely grounded in compassion, the most fundamental affective component of PSM. According to Goetz (2008), compassion and agreeable personality are inseparable, and agreeableness is a source of being good-natured, forgiving, helpful, and altruistic (Barrick and Mount, 1991). In fact, compassion as an affective factor in PSM is analog to the aforementioned ‘affective-based willingness to help colleagues’ in the business management literature (Kwok and Gao, 2004; Lin, 2007).

H1: Compassion is positively correlated with knowledge sharing.

Our second hypothesis centers on the effects of ‘self-sacrifice’ and ‘commitment to the public interest’. Knowledge sharing involves risks. As Ipe (2003) indicates, knowledge sharing is a power game. If individuals perceive that sharing causes a loss of power, they will hoard knowledge for personal defense. It is not surprising that scholars continuously call for the creation of an environment of interpersonal trust and procedural justice in order to combat knowledge hoarding stemming from perceived risks (Bartol and Srivastava, 2002; Hsu et al., 2007; Mooradian et al., 2006; Renzl, 2008). While we admit the importance of external influences such as a trust culture and procedural fairness, we also believe that individuals’ spirit of self-sacrifice for the public interest and their commitment to the public interest can transcend their selfish concern for personal risks and accordingly orient them to share knowledge for better service delivery.

H2: Self-sacrifice is positively correlated with knowledge sharing.

H3: Commitment to the public interest is positively correlated with knowledge sharing.

Finally, we consider the impact of ‘attraction to public policy making’. Knowledge sharing is often a result of rational deliberation. Sharing occurs when individuals perceive the value of knowledge sharing. The existing literature hints that the value can be identified as both personal (e.g. rewards and reciprocal benefits) and organizational (e.g. achieving the visions and goals) (Kim and Lee, 2006; Taylor and Wright, 2004). In the public sector, the value may be identified as societal as the provision of public service is often the main goal of government organizations. From this point of view, civil servants who have a strong interest in policy making are more likely than others to identify the societal value of knowledge sharing, i.e. generating better public policies and providing better public services with more updated organizational knowledge. Therefore,

H4: Attraction to public policy making is positively correlated with knowledge sharing

In sum, public service as a calling (Houston and Cartwright, 2007) may lead civil servants to share knowledge in order to create more advanced organizational knowledge and accordingly improve public service delivery. We anticipate that PSM as a form of altruistic motivation is positively related to knowledge sharing in general. Although the four dimensions, according to the literature, should positively influence knowledge sharing, we do not expect that their impacts are similarly strong. The main reason leading to the difference is the disparate level of individual self-determination accompanied by the four dimensions of PSM.

Different PSM dimensions, different self-determination, different impacts

According to Perry (1996), compassion as the central motive for public servants and ‘patriotism of benevolence’ is grounded in affectivity. Commitment to the public interest is commonly considered normative. Attraction to public policy making serves as a rational motive. Regarding self-sacrifice, Perry (1996) is not very clear.² In our view, self-sacrifice is to a great extent rooted in norms because self-sacrifice can be found in religious creeds, implying that self-sacrifice is a belief learned through socialization.

According to self-determination theory (SDT) (Ryan and Deci, 2000), when people act based on affectivity, their psychological regulatory style is internal and the motivational structure can be interpreted as intrinsic. In other words, compassion in PSM refers to a type of intrinsic motivation. When people act based on either rationality or norms, their psychological regulatory style should be interpreted as extrinsic. That is, commitment to the public interest, self-sacrifice, and attraction to policy making fall into the category of extrinsic motivation. However, extrinsic motivation is not one-dimensional as the psychological regulatory styles vary depending on the nature of the regulations. Rationality, compared to norms, exhibits weaker psychological regulation. What leads individuals to participate in policy making is the identification of the value of good policies for people. However, people cannot be condemned if they choose not to participate in policy making. A motive stemming from rationality such as attraction to policy making is referred to as identified regulation (Ryan and Deci, 2000; Vallerand and Ratelle, 2004).

Norms accompany stronger psychological regulation than rationality. Violating norms may not cause direct physical punishment, but one often feels psychologically guilty. One possible reason is that norms catalyze the internalization of identified values and their integration into our value system (Etzioni, 2000). In SDT, this is called integrated regulation (Ryan and Deci, 2000; Vallerand and Ratelle, 2004). Both commitment to the public interest and self-sacrifice as norm-based PSM belong to this category.

According to SDT, internal regulation, integrated regulation, and identified regulation constitute a person’s autonomous motivation.³ We can learn at least two things by employing SDT to understand PSM. First, altruistic motivation such as PSM does not have to be always intrinsic. Sometimes wanting to help others and contributing to the society may result from extrinsic reasons. Second, the four dimensions of PSM are reflected in different levels of self-determination: compassion as a type of internal regulation is the highest; attraction to policy making as a type of identified regulation is the lowest; commitment to the public interest and self-sacrifice as a type of integrated regulation are in between. Therefore, we offer the following hypothesis:

H5: Regarding the association between different dimensions of PSM and knowledge sharing, compassion is the strongest, attraction to policy making is the weakest, and commitment to the public interest and self-sacrifice are in between.

Data

Data used in the current study were collected from civil servants in Taiwan. Strictly speaking, Taiwan is still in the burgeoning state of democracy as democratization came about less than four decades ago (Berman et al., 2013a). Despite its relatively young democracy, public administration in Taiwan features administrative values (e.g. efficiency, transparency, accountability, and rule orientation) that can be found in mature democracies around the world (Jan, 2010). Although generalization from the Taiwanese data is not impossible, we must bear in mind that the national culture of Taiwan, characterized as collectivism (Hofstede et al., 2010), may influence the practice of knowledge sharing as Chow et al. (2000) suggest. This limitation will be discussed in greater detail in a later section.

In our data, all survey participants were middle managers working in the Taipei City Government. In a 14-grade hierarchy, the grades of middle managers are generally between seven and nine. Middle managers were selected because the flow of information and the exchange of knowledge occur intensively at the middle level in most bureaucracies (Nonaka and Takeuchi, 1995), making them ideal for the current research. The questionnaire was originally designed in the summer of 2009. We cooperated with a team of scholars at National Chengchi University in Taiwan to finalize the questionnaire and conducted the survey in 2010. Among all collected responses, three cases were found to be invalid and deleted as a result of the misplacement of non-middle managers on the survey list. As a result, 514 responses were successfully collected which yielded a response rate of 66.7 percent.

Variables

We measure the dependent variable, knowledge sharing, with two Likert items (1 = not important at all and 6 = extremely important) stating, ‘I voluntarily share my professional knowledge with my colleagues through text-based ways such as messages, emails, documents, or internet’ and ‘I voluntarily share my professional knowledge with my colleagues in a face-to-face manner’ (Cronbach’s alpha = .75). Grounded in the explicit/tacit typology (Nonaka and Konno, 1998; Nonaka and Takeuchi, 1995), these two items capture explicit knowledge sharing and tacit knowledge sharing respectively.

The main independent variable is PSM. Following Perry’s (1996) dimensionality of PSM, the authors selected 14 items (three within attraction to policy making; four within commitment to the public interest; three within compassion; four within self-sacrifice) with 1 = strongly disagree and 6 = strongly agree. The most fundamental criterion applied to item selection was translation – whether an item could be translated into Chinese without losing much of its meaning. Cronbach’s alpha for each dimension of PSM is .69 (attraction to policy making), .72 (commitment to the public interest), .80 (compassion), and .81 (self-sacrifice), and for the PSM index (the summation of 14 items) is .82. To test if the four constructs of PSM as well as the dependent variable are salient and distinct, we ran a factor analysis with the VARIMAX rotational method. Using the cutoff value of .4 suggested by Stevens (2009), Table 1 demonstrates that all items correspond to composite measures adequately as expected.

Table 1.

Factor analysis

	1	2	3	4	5
PSM1-1	.092	−.042	.603	.018	−.053
PSM1-2	.055	−.005	.672	.074	.083
PSM1-3	−.002	.119	.705	.060	.201
PSM2-1	.129	.187	.381	.063	.453
PSM2-2	.143	.106	.037	.152	.624
PSM2-3	.381	.372	.106	.108	.473
PSM2-4	.332	.363	.129	.075	.436
PSM3-1	.228	.732	−.011	.087	.194
PSM3-2	.206	.783	−.007	.200	.184
PSM3-3	.105	.624	.065	.158	.070
PSM4-1	.717	.107	.053	.124	.095
PSM4-2	.740	.092	.023	.091	.159
PSM4-3	.659	.339	.090	.167	.192
PSM4-4	.568	.178	.097	.154	.101
Knowledge sharing1	.191	.224	.081	.882	.182
Knowledge sharing2	.234	.189	.099	.569	.096
Eigenvalue	2.319	2.123	1.528	1.304	1.258
Variance explained (%)	14.496	13.267	9.549	8.148	7.864

Note: Factor loadings of .4 or above are shown in bold.

Regarding control variables, we admit that potential confounding variables were too many and we are unable to control for all of them in one model. As a result, we chose five variables that belong to three main genres in Ipe’s (2003) categorization of knowledge sharing determinants: properties of knowledge, situational factors, and motivation. We selected them bearing in mind the following two considerations: first, they have repeatedly appeared in the research on knowledge sharing in recent years, implying their key roles in enhancing/compromising knowledge sharing. Second, Ipe’s (2003) categorization, so far the most all-encompassing and based on economic rationality, embraces non-altruistic factors in different aspects. Choosing these variables allows us to compare the impact of PSM, an indicator of social altruism, with the impact of non-altruistic factors, especially rational individualism. See Table 2 for descriptive statistics and Appendix A for variable measurement.

Table 2.

Descriptive statistics

Variable	N	Mean	SD	Min	Max
Knowledge sharing 1 (tacit; face-to-face)	506	5.04	0.73	1	6
Knowledge sharing 2 (explicit; text-based)	506	4.62	0.91	1	6
Knowledge sharing index	505	4.83	0.74	1	6
PSM1: Attracting to policy making	506	3.96	0.93	1	6
PSM2: Commitment to the public interest	506	4.77	0.69	1.75	6
PSM3: Compassion	510	5.36	0.58	1	6
PSM4: Self-sacrifice	508	4.41	0.80	1.50	6
PSM index	498	4.62	0.53	1.57	6
Knowledge sharing endangering promotion	507	2.01	0.83	1	6
Knowledge sharing for task accomplishment	507	4.87	0.89	1	6
Satisfaction with current compensation	506	4.21	0.93	1	6
Trust in colleagues	506	4.29	0.77	1.50	6
Perceived procedural justice	499	3.73	0.99	1	6
Age	495	44.99	7.15	24	64
Agency tenure	500	4.70	5.35	0	39
Male	500	0.54	0.50	0	1

Findings

Results from the correlation matrix in Table 3 provide some preliminary support to our hypotheses. Correlation coefficients show that all knowledge sharing variables (explicit sharing, tacit sharing, and the index as the summation of these two) are significantly (p < .01) correlated with every subdimension of PSM as well as the PSM index, although the coefficients of compassion, self-sacrifice, and commitment to the public interest are apparently higher than that of attraction to policy making. Regarding controls, with the exception of gender and agency tenure, almost every variable is significantly correlated with knowledge sharing, a finding in line with the existing literature.

Table 3.

Correlation matrix.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)
Knowledge sharing 1: Tacit (1)	1.00
Knowledge sharing 2: Explicit (2)	0.61	1.00
Knowledge sharing index (3)	0.87	0.92	1.00
PSM1: Attracting to policy making (4)	0.16	0.14	0.16	1.00
PSM2: Commitment to the public interest (5)	0.40	0.30	0.38	0.28	1.00
PSM3: Compassion (6)	0.41	0.32	0.40	0.08	0.49	1.00
PSM4: Self-sacrifice (7)	0.40	0.35	0.41	0.15	0.50	0.42	1.00
PSM index (8)	0.48	0.40	0.48	0.57	0.81	0.63	0.77	1.00
Knowledge sharing endangering promotion (9)	−0.27	−0.15	−0.23	−0.04	−0.18	−0.18	−0.22	−0.21	1.00
Knowledge sharing for task accomplishment (10)	0.35	0.28	0.35	0.07	0.26	0.27	0.26	0.30	−0.20	1.00
Satisfaction with current compensation (11)	0.30	0.27	0.32	0.18	0.09	0.10	0.21	0.22	0.01	0.05	1.00
Trust in colleagues (12)	0.32	0.26	0.32	0.23	0.26	0.25	0.25	0.35	−0.35	0.30	0.26	1.00
Perceived procedural justice (13)	0.15	0.20	0.20	0.18	0.09	0.10	0.20	0.21	−0.12	0.08	0.40	0.47	1.00
Age (14)	0.15	0.21	0.21	0.03	0.17	0.16	0.26	0.23	−0.01	−0.08	0.23	−0.01	0.12	1.00
Agency tenure (15)	0.02	0.10	0.07	0.00	−0.03	0.02	0.03	0.00	0.05	−0.08	0.03	−0.03	0.00	0.26	1.00
Male (16)	0.03	−0.04	−0.01	0.05	0.16	0.00	0.08	0.11	0.03	−0.07	0.00	−0.03	0.15	0.20	0.04	1.00

p < .01 when coefficients < .12; p < .05 when coefficients > .09.

In addition to correlation coefficients, we investigate how PSM influences knowledge sharing using OLS regression with the use of the knowledge sharing index (the summation of explicit sharing and tacit sharing) as the dependent variable. The results are reported in Table 4. After controlling for all confounding variables, we find that the PSM index (Model 1) is still a statistically significant predictor for knowledge sharing (coef = 0.47, p < .00). When PSM is separated into four subdimensions (Model 2), we find that commitment to the public interest, compassion, and self-sacrifice are statistically significant, but attraction to policy making is not (coef = 0.03, p < .28). This provides evidence supporting H2, H3, and H4 but not H1.⁴

Table 4.

OLS regression: knowledge sharing Index as DV

	Model 1			Model 2
	Beta	Coef	p	Beta	Coef	p
PSM index	0.33	0.47	0.00**	–	–	–
PSM1: Attracting to policy making	–	–	–	0.04	0.03	0.28
PSM2: Commitment to the public interest	–	–	–	0.10	0.11	0.03*
PSM3: Compassion	–	–	–	0.20	0.26	0.00**
PSM4: Self-sacrifice	–	–	–	0.14	0.13	0.00**
Knowledge sharing endangering promotion	−0.10	−0.09	0.01*	−0.09	−0.08	0.02*
Knowledge sharing for task accomplishment	0.26	0.22	0.00**	0.24	0.21	0.00**
Satisfaction with current compensation	0.20	0.16	0.00**	0.20	0.16	0.00**
Trust in colleagues	0.01	0.01	0.84	0.01	0.01	0.82
Perceived procedural justice	0.02	0.01	0.66	0.03	0.02	0.53
Age	0.08	0.01	0.05*	0.07	0.01	0.11
Agency tenure	0.08	0.01	0.03*	0.08	0.01	0.03*
Male	−0.06	−0.09	0.12	−0.05	−0.08	0.18
N		463			463
Adjusted R square		0.373			0.387

p < .01; *p < .05.

In the present study, we use standardized coefficients (Beta values) to compare the substantive influence of each variable. In Model 1, PSM index (Beta = .33) is the most influential predictor for knowledge sharing. In Model 2, after we separate PSM into four dimensions, the most influential predictor is perceived necessity of knowledge sharing for task accomplishment (Beta = .24). Compassion as affective PSM (Beta = .20) is the second most influential predictor. Its influence is as strong as that of compensational satisfaction (Beta = .20). If we compare the four dimensions of PSM, we find that compassion is the most influential predictor (Beta = .20), more influential than commitment to the public interest (Beta = .10) and self-sacrifice (Beta = .14) as the norm-based PSM. The least influential one is attraction to policy making (Beta = .04) as the rational PSM. To be more precise in statistics, we conducted several post-regression tests to examine whether any two coefficients of PSM are statistically different from each other. Under the null ‘any two PSM coefficients are equal’, most test results rejected the null at the level of α = .05 or at least α = .10. Therefore, H5 is supported.

Regarding control variables, knowledge sharing endangering promotion, knowledge sharing for task accomplishment, satisfaction with the current compensation, and agency tenure are statistically significant. The influence of age is diluted when PSM is separated into four dimensions (Model 2). Trust in colleagues, perceived procedural justice, and gender fail to reach the significance level of α = .05. While we are unable to pinpoint what exactly leads to insignificant coefficients of trust in colleagues and perceived procedural justice, fairly high statistical correlations between these two variables (.47) and between trust in colleagues and satisfaction with current compensation (.40) are a possible reason.

To verify whether it is suitable to estimate explicit and tacit knowledge sharing jointly, we perform the bivariate ordered probit statistical procedure.⁵ Table 5 presents the two-equation model that is generated from the analysis. Overall, the model fits the data well (Wald χ²= 184.61, p < .00). The estimated correlation between the error variances of the two equations is .587, which is statistically significant (p < .00). We also find that, in general, the results pattern of bivariate ordered probit regression is similar to that of OLS regression: the coefficients of compassion, self-sacrifice, and commitment to the public interest are statistically significant, but the coefficient of attraction to policy making is not.⁶ However, some interesting findings deserve special attention. First, regarding PSM, compassion and commitment to the public interest are much more influential in the model of explicit knowledge than the model of tacit knowledge. Does it mean that sharing tacit knowledge implies the loss of personal value, and the fear of losing value counterbalances the impacts of PSM? Second, age, agency tenure, and gender are statistically significant only in the model of tacit knowledge. If the loss of personal value is indeed an important concern, does it mean that senior people are less afraid to share knowledge because their status is more established? Does it mean that men are more afraid to share knowledge, or does it mean that they are simply less talkative than women? These propositions go beyond the scope of the current study and the answers are not readily available, but they would be interesting topics for future research.

Table 5.

Bivariate Ordered Probit regression (n = 463)

	Explicit knowledge sharing		Tacit knowledge sharing
	Coef	p	Coef	P
PSM1: Attracting to policy making	0.05	0.43	0.05	0.42
PSM2: Commitment to the public interest	0.27	0.01*	0.13	0.20
PSM3: Compassion	0.54	0.00**	0.35	0.00**
PSM4: Self-sacrifice	0.20	0.02*	0.20	0.01**

Knowledge sharing endangering promotion	−0.29	0.00**	−0.07	0.34
Knowledge sharing for task accomplishment	0.40	0.00**	0.32	0.00**
Satisfaction with current compensation	0.35	0.00**	0.20	0.00**
Trust in colleagues	−0.01	0.87	0.03	0.73
Perceived procedural justice	−0.05	0.44	0.11	0.07
Age	0.00	0.67	0.02	0.04*
Agency tenure	0.01	0.32	0.02	0.02*
Male	0.04	0.73	−0.25	0.02*
Wald test (χ²)	184.61**
ρ	0.59
LR test of independent equations (χ²)	112.72**

p < .01; *p < .05.

Implications

With the introduction of PSM, the present study connects knowledge sharing with public administration. When research on knowledge sharing is conducted in the public sector context, existing findings show that knowledge sharing determinants noted in the generic management literature can be readily applied to the public sector (e.g. Yusof et al., 2012), meaning that ‘sector matters little’. Focusing on motivation, however, we argue that a theory of knowledge sharing motivation in the public sector requires special consideration as civil servants’ altruistic motivation is not limited to intraorganizational affairs. Public service as a calling (Houston and Cartwright, 2007) can lead civil servants to share knowledge in order to create more advanced organizational knowledge and accordingly improve public service delivery or the quality of public programs/policies. In sum, our research advances the theory of knowledge sharing motivation by considering the special context of the public sector and giving altruistic motivation a broader definition that includes serving the public interest.

The present study contributes to the field of general public administration as well. Although Waldo (1980) reminded us that public administration relies on constantly updated knowledge to facilitate civilization, the research on knowledge-related topics is still scant, except two knowledge-sharing articles published in mainstream journals (Kim and Lee, 2006; Willem and Buelens, 2007). This article, as the third piece of research that focuses on knowledge sharing in the public sector, does not merely advance the understanding of knowledge sharing or PSM. In a broader sense, it encourages scholars to pay more attention to knowledge-related research, a topic that is critical but underdeveloped in public administration.

In addition to the aforementioned main contributions, a few additional points deserve greater discussion. The first one concerns different dimensions of PSM. Regression results show that compassion as an affective motive has the greatest impact on knowledge sharing whereas the rational motive, attraction to policy making, has the weakest impact (and more importantly, the coefficients are not statistically significant). The norm-based motives, commitment to the public interest and sacrifice, are in between. It implies that to enhance helping behaviors such as knowledge sharing, the effect of rational PSM alone is not enough. In fact, a few recent empirical studies of volunteering provide a similar view. They either argue that attraction to policy making is presumed to be a poor antecedent of volunteering activity (Coursey et al., 2011) or find that attraction to policy making is less effective than other PSM dimensions in predicting volunteering and donating decisions (Clerkin et al., 2009).

The second point concerns the relative importance of PSM compared to controls included in the present study. Except for demographics, controls in the present study pertain to properties of knowledge, situational factors, and extrinsic motivation for knowledge sharing. Existing research that simultaneously examines both altruistic motivation and other situational and motivational antecedents generally demonstrates that altruistic motivation is more influential than other factors (Hsu and Lin, 2008; Lin, 2007). Our finding is consistent with this pattern: the influence of PSM is stronger than that of most controls, especially in the aggregate model (Model 1 in Table 4). The finding perfectly reflects Gagné’s (2009) perspective that being motivated to share out of interest or personal meaning results in more positive attitudes toward knowledge sharing. Similarly, the literature on volunteering suggests that knowledge sharing as a type of voluntary act (Davenport and Prusak, 1997) is more strongly espoused by altruistic motives than by functional motives (e.g. self-protection, career help, making friends, and self-enhancement) (Mowen and Sujan, 2005), further supporting our finding.

Following these two points, we provide practical suggestions to front-line public managers. While most research on knowledge sharing encourages managers to provide a sense of security and procedural justice for employees, facilitate interpersonal trust, use IT, and offer benefits for sharing, the method of enhancing altruistic motivation is not commonly addressed. We do not deny the importance of situational factors and extrinsic motives, but apparently altruistic motivation, particularly PSM in the public sector, plays an even more pivotal role in promoting knowledge sharing. To ensure a high level of civil servants’ PSM, public managers may wish to consider the following issues: are there adequate tools that help in the hiring of individuals high in PSM and winnowing out those low in PSM? Are there mentoring programs that help enhance employees’ PSM (Bozeman and Feeney, 2009)? Does the organization provide appropriate training that helps employees counteract the ‘reality shock’ brought on by citizens’ cynical attitudes and lack of appreciation (Blau, 1960; Buurman et al., 2009)? Does the organization provide excessive external incentives such as contingent rewards based on performance that eventually crowd out PSM (Frey and Jegen, 2001; Jacobsen, 2011)? In sum, to enhance knowledge sharing, public managers may benefit not only from the generic management literature about knowledge sharing but also from the PSM literature.

Limitations and suggestions for future research

Despite the contribution of linking PSM to knowledge sharing, limitations exist in the present study and we call for future research to improve them. First, we tested our hypotheses using data collected in Taiwan which is culturally dominated by Confucian collectivism. People in this culture tend to create a group norm, follow it, and hesitate to be too prominent (Berman et al., 2013b). They also face less competition than people in an individualist culture, where people often have an obsessive desire to get ahead of others and keep material and knowledge to themselves to avoid harm (Kirby and Ross, 2007). Is PSM more likely to help people transcend the concern for self-protection in a collectivist culture than in an individualist culture? We need more evidence. Due to this generalizability concern, we call for similar studies in an individualist culture.

Second, we rely on only two items to capture different facets of knowledge sharing. This is not enough. Contemporary studies of knowledge sharing often make knowledge sharing behaviors, attitudes, and intentions distinctive and isolated from each other (Bock and Kim, 2002; Gagné, 2009; Hsu and Lin, 2008). It would provide a substantial contribution if researchers could compare the impact of PSM on the three different knowledge sharing components. Finally, the measurement of PSM can be improved as well. We collected the data in early 2010 and happened to miss newly developed PSM measurement tools by Kim and his colleagues (Kim, 2009; Kim et al., 2013). The new tools contain elements more tailored to the Asian context and include commitment to public value as a new dimension. They may more faithfully and completely reflect multiple dimensions of PSM.

To study knowledge sharing motivation in the public sector, we aim to go beyond the framework of knowledge sharing motivation grounded in the generic management literature by introducing PSM, a core theory in the field of public administration. In fact, if scholars intend to more faithfully depict knowledge sharing or other knowledge management dynamics in the public sector, improving the understanding of theories in public administration is necessary. In addition to PSM, the theory of red tape (Bozeman, 1993; Bozeman and Feeney, 2011), for example, could be useful to the research of knowledge sharing because red tape as a type of external intervention may crowd out (Frey and Jegen, 2001) an individual’s intrinsic motivation to share knowledge. In sum, the present study merely scratches the surface of public sector employees’ knowledge sharing motivation. More research effort is called for in the future.

Financing

The authors thank the Taiwan National Science Council for project funding (grant number NSC-96-2414-H-004-037-SS2); the Chiang Ching-kuo Foundation for International Scholarly Exchange (grant number RG003-D-06); and the Nanyang Technological University (start-up grant number 4080392). The authors also thank Dr Don-Yun Chen at National Chengchi University for making the data available.

Footnotes

Notes

Chung-An Chen is assistant professor in the Public Policy and Global Affairs Programme, Nanyang Technological University, Singapore. His research interests include public management, organizational behavior, and human resource management, with a particular focus on human motivation.

Chih-Wei Hsieh is assistant professor in the Department of Public Policy, City University of Hong Kong. His research interests focus on public service delivery, human resource management, and organizational behavior. He has published articles on emotional labor, public service motivation, and workplace diversity in various journals.

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