Impact of self-construal on choice of enterprise social media for knowledge sharing.
The choice of knowledge-sharing enterprise social media should be made according to the target users' characteristics or expectations. For example, users' cultural background is an important factor (Ardichvili, Maurer, Li, Wentling, & Stuedemann, 2006). We expanded cross-cultural research on knowledge-sharing through an examination of users' self-construal, which is defined as how individuals construct the self in relation with others (Markus & Kitayama, 1991). Self-construal is a fundamental psychological factor with implications for cognition, emotion, and motivation in social interaction (Cross, Hardin, & Gercek-Swing, 2011). It influences how and why people use social media to interact with others (Kim, Kim, & Nam, 2010).
Our objective was to understand how employees' self-construal influences their choice of knowledge-sharing social media in organizations. Two types of knowledge-sharing ESM are used: wiki (user-generated knowledge repositories) and Q&A. They have both been widely adopted by organizations (Budzik & Hammond, 1999; Majchrzak, Wagner, & Yates, 2013), and have distinctive approaches for generating, sharing, and retrieving knowledge. We compared these two types of ESM when investigating how self-construal impacts on employees' knowledge-sharing motivation, self-efficacy, and openness of sharing via ESM, and discuss implications for knowledge management.
Knowledge-Sharing Media and Virtual Communities of Practice
The participatory nature and proliferation of ESM have given rise to many VCoPs, which have been accepted as a vehicle of knowledge creation and exchange in organizations, and that feature the collaborative, web-based creation of knowledge and information (Fulk & Yuan, 2013). The most successful example of collaborative content creation through VCoPs is Wikipedia (O'Sullivan, 2012). Wikipedia is an Internet-based, volunteer-contributed encyclopedia, where everyone may easily change and improve the content.
Researchers have explored the social, organizational, and technical factors that supported the evolution of wiki-based VCoPs. For example, Hara, Shachaf, and Hew (2010) analyzed Wikipedia cross-culturally in four languages, and explained the different norms of behavior with the cultural dimensions of Hofstede (1997). Bryant, Forte, and Bruckman (2005) studied Wikipedia users' perceived role transformation from novice to expert, and found that new users started by correcting mistakes in individual articles and later became motivated to build the Wikipedia community as a whole. There are also gender differences; less than, another of the popular knowledge-sharing social media, 15% of Wikipedia contributors are women (Glott & Ghosh, 2010).
Q&A, another popular type of knowledge-sharing ESM, is a searchable online forum designed for sharing knowledge and expertise between question askers and answerers. For example, Yahoo! Answers has become one of the largest Internet knowledge exchange VCoPs (Adamic, Zhang, Bakshy, & Ackerman, 2008). Shachaf (2010) proposed a framework to account for the collaborative process of Q&A, in which several influential factors, such as question type, user characteristics, participation norms, and technology contexts, were identified.
Wiki and Q&A represent two knowledge management strategies used in companies: codification strategy and personalization strategy. The codification strategy involves the codification and storage of knowledge so that it can be accessed and reused; in the personalization strategy knowledge is shared mainly through person-to-person contact (Hansen, Nohria, & Tierney, 1999). Although various researchers have discussed choosing the effective strategy according to the organizational structure and culture, and knowledge characteristics, only a few have considered users' personal characteristics (Kumar & Ganesh, 2011; Liu, Chai, & Nebus, 2013). For example, Kumar and Ganesh (2011) discussed the advantages and downsides of the two strategies considering explicit versus tacit knowledge and the changing pace in industry. Bhatt (2001) stated that the interaction between technology, techniques, and people allows an organization to manage its knowledge effectively. We believe that there is a need to better understand how organizations can choose the right strategy.
In their self-construal theory, Markus and Kitayama (1991) identify two types of self: The independent self emphasizes individual autonomy and uniqueness and is separated from the social context. In contrast, the interdependent self is connected to others and defined by relationships with others within the social context. Interdependent people have a higher motivation to get along with ingroup others because they value conformity, cooperation, and reciprocity. The ingroup-outgroup distinction is vital for interdependent people. Outgroup others are treated differently and do not experience the advantages of interdependence (Cross et al., 2011).
Recently researchers have examined the role of self-construal in social media use behavior and motivation. For example, Lee, Kim, and Kim (2012) conducted an experiment in an online community and demonstrated that the users' relational view and electronic word-of-mouth behavioral intentions became salient when their self-construal was deemed interdependent. In a survey of Facebook use, Kim et al. (2010) found that interdependent, in contrast to independent, self-construal was associated with social motivation to use, leading to satisfaction with social networking services. The importance of interdependent self-construal in investigating social media use was raised in both studies.
Knowledge-Sharing Motivation and Self-Efficacy
Knowledge-sharing motivation is necessary to stimulate people's desire to share, and energy in sharing their knowledge, and is a critical factor in determining a VCoP's success (Ardichvili, 2008). Building on the findings of previous researchers (i.e., Bock, Zmud, Kim, & Lee, 2005; Chang & Chuang, 2011; Ipe, 2003; Kankanhalli, Tan, & Wei, 2005), we concluded that eight factors motivate knowledge sharing: (a) Image: a desire to earn respect and a better image through sharing best practice and expertise (Chang & Chuang, 2011). (b) Anticipated reciprocity: mutual give-and-take of knowledge with no certainty that the other will reciprocate (Chang & Chuang, 2011). (c) Sense of community: the sense of belonging to a knowledge-sharing community and motivation to improve the community (Ipe, 2003). (d) Affiliation: the need to form relationships and associations through knowledge sharing (Ipe, 2003). (e) Altruism: deriving intrinsic enjoyment from helping others without expecting anything in return (Chang & Chuang, 2011). (f) Reward: an expectation of gaining an extrinsic monetary or nonmonetary organizational award (e.g., promotion) through knowledge contribution (Ipe, 2003). (g) Sense of self-worth: the extent to which employees see themselves as providing value to their organizations through their knowledge sharing (Bock, Zmud, Kim, & Lee, 2005). (h) Competitiveness: the perceived loss of power and unique value within the organization associated with knowledge contribution (a negative motive; Kankanhalli, Tan, & Wei, 2005). These eight factors, describing social and relational aspects of knowledge sharing, may vary in different social contexts and with different self-construals.
Self-efficacy refers to individuals' perception of what they can do with the skills they possess (Bandura, 1986). It is one of the main determinants in forming an optimistic attitude toward knowledge sharing (Hsu, Ju, Yen, & Chang, 2007). When individuals believe that they can articulate knowledge through the knowledge-sharing process, and that others value their knowledge in the organization, they gain the confidence to contribute their knowledge (Kankanhalli et al., 2005). Conversely, if individuals feel that they lack knowledge that is valuable to the organization, or they doubt their ability to provide correct knowledge, they may decline to share knowledge.
We developed several hypotheses in regard to the effects of self-construal on the knowledge-sharing ESM choice between wiki and Q&A. The users of Q&A are exposed to relational, personalized, and contextual information, and the emphasis in wiki is on codified and generalized knowledge (Kumar & Ganesh, 2011). Because the question asker is displayed in Q&A, interdependent knowledge sharers may evaluate the relationship with the asker before they decide how to answer the question. If the asker is from an outgroup, the unfamiliarity may be a barrier for interdependent people when answering questions (Chow, Deng, & Ho, 2000). Interdependent users lack the motivation of sense of community, affiliation, altruism, self-worth, and image with outgroup members. They are also uncertain about reciprocity, reward, and the risk of losing value when sharing their knowledge. As a result, interdependent users have a decreased level of motivation, self-efficacy, and intention of sharing with outgroup members using Q&A (Markus and Kitayama, 1991; Triandis, 1989). In comparison, as the knowledge recipient is not shown in wiki, users focus less on the relational context, and more on knowledge itself, and the outgroup relationship barriers become less effective. We thus proposed the following hypothesis:
Hypothesis 1: When sharing knowledge with outgroup members, interdependent employees will have higher motivation, self-efficacy, and openness of sharing when using wiki compared with when they are using Q&A.
We also predicted that when interdependent employees share knowledge with ingroup members, the differences between wiki and Q&A become less significant than when outgroup sharing. Ingroup advantages, which are based on the intimacy, reciprocity, and mutual commitment of ingroup relationships (Kim et al., 2010), exist regardless of the type of ESM being used. We thus proposed the following hypothesis:
Hypothesis 2: When knowledge is shared through enterprise social media, the type used will have a greater influence on interdependent employees' outgroup than ingroup knowledge sharing.
The differences between ingroup and outgroup sharing may not be meaningful for independent people, who are not as sensitive as others are to relationship differences (Lee et al., 2012; Triandis, 1989). Moreover, the differences between Q&A and wiki may also be less salient for independent users because independent self-construal has much less impact on people's relational view and social media use than interdependent self-construal (Kim et al., 2010; Lee et al., 2012). We thus proposed the following hypothesis:
Hypothesis 3: When knowledge is shared through enterprise social media, the organizational relationship and the type of ESM used will have a greater influence on interdependent employees' knowledge sharing than on that of independent employees.
Participants were 232 Chinese employees (113 women and 119 men) from different for-profit companies. They were recruited through online advertisements and emails. Their ages ranged from 21 to 56 years, with an average of 28.41 years (SD = 4.75). Of the participants, 93.5% had a bachelor's or higher degree, 76.7% worked in the information technology industry, and 66.8% were in research and development (R&D) departments. Participants' average work experience was 2.58 years (SD = 2.54). Of the experience that all participants had in browsing or searching for knowledge through wiki and Q&A websites, 29.3% had edited wikis, 58.2% had asked questions, and 48.7% had answered on Q&A websites. The potential effects of the differences in use experience were statistically assessed and no significant differences between more and less experienced participants on the dependent variables of the experiment were found.
A 2 x 2 x 2 between-subject design was used in this study. The three independent variables were self-construal (independent vs. interdependent), knowledge-sharing media (wiki vs. Q&A), and type of relationship between knowledge sender and recipient (ingroup vs. outgroup). Self-construal was manipulated after the task. The other two independent variables were manipulated before the task by randomly assigning each participant to one of the four conditions. Dependent variables included knowledge sharing, self-efficacy and motivation, and openness of sharing.
We used a scenario-based questionnaire, a method that has been applied in many knowledge-sharing studies to manipulate different social conditions (e.g., Chow et al., 2000; He, Zhao, & Hinds, 2010). Participants filled out an online questionnaire consisting of five parts: (1) self-construal scale; (2) questions about their experience of using wiki and Q&A; (3) a scenario describing a knowledge-sharing context; (4) openness of sharing, motivation, and self-efficacy scales; and (5) demographic questions. All the materials were in Chinese.
There were four scenario versions, representing the four between-subject conditions: ESM (wiki vs. Q&A) x relationship type (ingroup vs. outgroup). In the wiki and ingroup condition, for example, participants read the following scenario:
Yang, who worked for six years in industry X, has a broad and deep understanding of this industry. Recently, he left industry X and moved to industry Y to do research and development work in a large company. There are a dozen colleagues in his team, who had established a knowledge-sharing website similar to Wikipedia, called Team Wiki, for their team's work. Everyone in the team can access Team Wiki. They can also edit the content on a voluntary basis, and those who do so may receive a monetary reward. One day, Yang searches the keyword "industry X" in Team Wiki and finds that the page has not been edited. Do you think he will edit the page when he has time, and share his knowledge of industry X in Team Wiki?
In outgroup scenarios, the website was named with a prefix of "corp-," and was described as "being used for the mutual sharing of knowledge among different companies within the enterprise group and among unfamiliar employees." In Q&A scenarios, another employee called Peng, either Yang's teammate (ingroup) or an unfamiliar colleague (outgroup), posted a question on the website: "Who is familiar with industry X? Can you share some knowledge about it? All kinds of information are welcome!"
There were two questions to check the manipulation of the independent variables. One question, which was whether or not Yang was familiar to most users of the knowledge-sharing website, was designed to check the manipulation of ingroup versus outgroup relationship. The other question presented three website layouts, that is, Wikipedia, Baidu Q&A (a well-known Chinese Q&A website), and Shuimu bulletin board. Participants were asked which one of these appeared to be closest to the website in the scenario. Only the participants who answered both questions correctly were included in the sample.
Self-construal was measured using the Self-Construal Scale (SCS; Singelis; 1994) comprising independent and interdependent dimensions. Each dimension has 12 items with 7-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). We used the Chinese translation of the scale by Wang, Yuan, and Xu (2008). Cronbach's alpha was .83 (interdependent) and .71 (independent).
Openness of sharing was measured by six questions directly after the scenario. Participants were asked to indicate how likely they thought it was that Yang would post his knowledge on the website if he could supply the information being sought in the scenario. They rated their responses on a scale from 1 (very unlikely) to 7 (very likely). A question about the likely action of the employee in the scenario, instead of the participant, can control potential social desirability bias (for similar methods see Chow et al., 2000; He et al., 2010; for a discussion of the method see Nederhof, 1985). The questions were used to ask about six types of knowledge regarding industry X, that is, definition, history, classification, characteristics, future prospects, and the current employment situation. Factor and reliability analyses were conducted to ensure the validity of the measure. One factor accounting for 67.12% of the variance was identified. Cronbach's alpha was .90.
Knowledge-sharing motivation was measured by 16 items adapted from existing scales representing the eight motivation factors (see Table 1). The items were translated into Chinese and back-translated to ensure accuracy. Participants were asked to imagine that they were in the same situation as Yang, and to rate the importance of each item for their knowledge sharing from 1 (very unimportant) to 7 (very important). The items were selected by using definitions in the original literature, so they had face validity. Factor analysis extracted a single factor accounting for 63.55% of the variance. Cronbach's alpha was .84.
The knowledge-sharing self-efficacy measure included four items adapted from existing scales (see Table 1). Participants were asked to imagine that they were in the same situation as Yang, and to rate how much they agreed with the statements from 1 (strongly disagree) to 7 (strongly agree). Factor analysis extracted one factor accounting for 63.32% of the variance. Cronbach's alpha was .81.
We compared independent and interdependent self-construals, and examined the effects of knowledge-sharing ESM and type of relationship on motivation, self-efficacy, and openness of sharing. Self-construal was manipulated by dividing the participants into independent and interdependent groups according to their self-construal scores. Participants with a higher independent score were included in the independent group and those with a higher interdependent score were included in the interdependent group. The remaining participants, with equal scores, were excluded from further analysis (see Nakashima, Isobe, & Ura, 2008 for a similar grouping method). The interdependent group comprised 122 participants, and the independent group comprised 94 participants. The means of interdependent and independent self-construal within each group were compared. There were significant differences in the result (see Table 2), indicating that the grouping was valid.
Interdependent Self-Construal Participants
Multivariate analysis of variance (MANOVA) was used to determine the influence of knowledge-sharing ESM and type of organizational relationship on motivation, self-efficacy, and openness of sharing. Bartlett's test of sphericity (90.47, df = 5, p < .001) indicated that MANOVA was appropriate.
Hypotheses 1 and 2 were tested by the interaction effects of relationship x ESM, Wilks' [lambda] = .93, F(3, 116) = 3.05, p = .032. Significant univariate interaction effects were found for motivation, F(1, 118) = 3.01, p = .085 (marginally significant), self-efficacy, F(1, 118) = 8.12, p = .005), and openness of sharing, F(1, 118) = 4.90, p = .029). We further analyzed the simple effects of media in each relationship type (see Table 3). When sharing with outgroup members, interdependent people had significantly higher motivation, self-efficacy, and openness of sharing when using wiki than when using Q&A. Thus, Hypothesis 1 was supported. The type of ESM being used had a significant effect on outgroup but not ingroup sharing. Thus, Hypothesis 2 was supported.
Independent Self-Construal Participants
The means and standard deviations for dependent variables are presented in Table 4. Bartlett's test of sphericity (73.05, df = 5, p < .001) confirmed that MANOVA was appropriate.
The multivariate main effects of relationship, Wilks' [lambda] = .95, F(3, 88) = .15, p = .228 and media, Wilks' [lambda] = .98, F(3, 88) = .53, p = .665 were insignificant, and their interaction effect (Wilks' [lambda] = .97, F(3, 88) = .95, p = .422) was also insignificant. Thus, the univariate effects were not analyzed further. In comparison with the interdependent participants' results, a very limited influence of organizational relationship and ESM type on independent participants' knowledge sharing was found. Thus, Hypothesis 3 was supported.
We have provided evidence that self-construal and organizational relationship (ingroup vs. outgroup) jointly influence the choice of which of the two ESM was better for knowledge sharing. When interdependent employees shared with outgroup members, wiki was a better choice than Q&A for promoting users' motivation, self-efficacy, and openness of sharing. There was no difference between wiki and Q&A when interdependent employees shared with ingroup members. Conversely, independent employees' knowledge sharing was not influenced by either ingroup versus outgroup relationship or wiki versus Q&A. These findings have both theoretical and practical implications.
From a theoretical point of view, we expanded the knowledge-sharing research field through an examination of users' self-construal. To the best of our knowledge, this study is one of the first in which an empirical comparison of the wiki and Q&A knowledge management strategies was conducted according to users' self-construal. Because the codification strategy does not emphasize relational and social aspects, wiki can be a good way to focus on knowledge itself. In contrast, as the primary concern in the personalization strategy is knowledge transfer among people, relational ties are important for the success of this strategy. The strategy differences are more salient for interdependent than for independent people because of the former group's strong relational concerns in social activities (Cross et al., 2011; Kim et al., 2010; Lee et al., 2012). Our results indicate that interaction among people, organizations, and technology allows for successful knowledge management (Bhatt, 2001).
In practical terms, an organization's knowledge management strategy and choice of which of the ESM will be used should be carefully selected according to employees' self-construal. If most employees have interdependent tendencies, the managers should tailor the strategies to the organizational relationships. In the context of intensive ingroup relationships, both codification and personalization strategies can work well to enhance ingroup sharing. In contrast, when knowledge is shared in a wider extent between outgroup employees, the codification strategy, wiki can be a better choice. For independent employees, the ingroup versus outgroup relationship is less important in choice between ESM. Therefore, we suggest that knowledge managers look into their employees' self-construal and decide the scope of the sharing activity (e.g., within a team or the whole company) before choosing and developing their knowledge management media strategies.
There are two limitations in this study. First, the sample involved both experienced and less experienced users of wiki and Q&A. Although significant differences were not revealed, previous researchers have found that motivations and behaviors of novices differ from those of expert users (Bryant et al., 2005).
Future researchers should consider the use experience factor. Second, a high proportion of the participants worked in R&D departments in the information technology industry. A proxy agent was described in a scenario as an R&D worker. The generalizability of the findings to other organization types and work contexts can be verified in future studies.
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JUN LIU AND PEI-LUEN PATRICK RAU
Jun Liu and Pei-Luen Patrick Rau, Department of Industrial Engineering, Tsinghua University. This research was supported by the National Science Foundation China (grant numbers 71031005 and 71188001).
Correspondence concerning this article should be addressed to: Pei-Luen Patrick Rau, Department of Industrial Engineering, Tsinghua University, Beijing 100084, People's Republic of China. Email: email@example.com
Table 1. Knowledge-Sharing Motivation and Self-Efficacy Survey Items Measure Items Source Motivation Image 1. Gain more recognition and Bock et al. (2005); respect (within the team). Hsu et al. (2007); (b) Kankanhalli et al. 6. Improve my image (within (2005) the team). (b) Anticipated 2. I can expect somebody to reciprocity respond when I am in need. 4. Get better cooperation and benefits in return. Sense of 3. Help Y (a) achieve its community goals or visions. 14. Help the enterprise/my team accumulate or enrich its knowledge base. (b) Affiliation 5. Strengthen the tie between me and other employees. 12. Make friends with other employees/team members. (b) Altruism 7. I enjoy sharing my knowledge with others/other team members. (b) 10. It feels good to help someone (in my team) by sharing my knowledge. (b) Self-worth 8. Increase productivity in the enterprise group/team. (b) 11. Help improve work processes in the enterprise/team. (b) Reward 9. Get monetary rewards in return. 13. Receive additional points for promotion. Competitiveness 15. Lose my unique value in the enterprise/team. (b,c) 16. Worry about losing the knowledge that makes me stand out with respect to others/other team members. (b,c) Self-efficacy 1. I have confidence in my Compeau & Higgins ability to provide (1995); Kankanhalli knowledge that others et al. (2005) (in my team) will consider valuable. (b) 2. I am confident in providing my ideas and perspectives to others through Y (a). 3. I am confident in articulating myself in written, verbal or symbolic forms. 4. I am confident in authoring an article or posting a message to Y (a). Note. (a) Y represents the name of the website in the scenario. (b) Items with different wording between ingroup and outgroup conditions. (c) Reverse-scored item. Table 2. t-Test Results of Self-Construal Scores Group Self-construal n M SD t p measure Independent Independent 94 5.29 0.57 89.31 <.001 group Interdependent 94 4.73 0.60 Interdependent Independent 122 4.80 0.56 -76.82 <.001 group Interdependent 122 5.33 0.54 Table 3. Interdependent Group: Simple Effects of Enterprise Social Media in Each Relationship Type Dependent Relationship ESM n M SD variable Motivation Ingroup wiki 32 5.24 0.58 Q&A 23 5.21 0.69 Outgroup wiki 35 5.05 0.59 Q&A 32 4.63 0.59 Self- Ingroup wiki 32 5.00 0.71 efficacy Q&A 23 5.25 0.74 Outgroup wiki 35 5.54 0.88 Q&A 32 4.97 0.76 Openness of sharing Ingroup wiki 32 5.08 0.97 Q&A 23 5.23 1.00 Outgroup wiki 35 5.31 0.76 Q&A 32 4.70 1.07 Dependent Relationship F(1, 53) (a) p variable (1, 65) (b) Motivation Ingroup 0.04 .846 Outgroup 8.49 .005 Self- Ingroup 1.61 .211 efficacy Outgroup 7.85 .007 Openness of sharing Ingroup 0.33 .570 Outgroup 7.51 .008 Note. (a) Degree of freedom for ingroup. (b) Degree of freedom for outgroup. Table 4. Independent Group: Means and Standard Deviations for Dependent Variables Knowledge-sharing dependent variables Motivation Self-efficacy Openness of sharing Relationship ESM n M SD M SD M SD Ingroup wiki 30 5.13 0.85 5.43 0.87 4.96 1.21 Q&A 24 5.14 0.71 5.31 0.63 4.96 1.70 Outgroup wiki 17 5.05 0.71 5.37 0.79 5.01 1.14 Q&A 23 4.65 0.65 5.39 0.88 4.95 1.04 Total 94 5.00 0.76 5.38 .79 4.97 1.29
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|Author:||Liu, Jun; Rau, Pei-Luen Patrick|
|Publication:||Social Behavior and Personality: An International Journal|
|Date:||Aug 1, 2014|
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