Would You Share? Examining How Knowledge Type and Communication Channel Influence Knowledge Sharing Paul M. Di Gangi Department of Management Information Systems Florida State University Molly M. Wasko Department of Management Information Systems Florida State University

Agenda Motivation of study Theoretical lens & research question Research framework & hypotheses Methodology Research findings Contributions, limitations, & future directions

Motivation of study

Theoretical lens & research question

Research framework & hypotheses

Methodology

Research findings

Contributions, limitations, & future directions

Motivation of Study CMCs enable knowledge sharing Regardless of location (Constant et al., 1994) Personal familiarity (Constant et al, 1996; Rice et al., 2000) Research on knowledge sharing centers around two factors Knowledge type (Constant et al., 1994; Jarvenpaa & Staples, 2001) Sharing environment (Constant et al., 1996; Kankanhalli et al, 2005; Wasko & Faraj, 2005)

CMCs enable knowledge sharing

Regardless of location (Constant et al., 1994)

Personal familiarity (Constant et al, 1996; Rice et al., 2000)

Research on knowledge sharing centers around two factors

Knowledge type (Constant et al., 1994; Jarvenpaa & Staples, 2001)

Sharing environment (Constant et al., 1996; Kankanhalli et al, 2005; Wasko & Faraj, 2005)

Research Question Simultaneous examination of multiple sharing environments is needed Differences in CMC environments Risks versus rewards evaluation for different knowledge types Do individuals share differently based on the combination of sharing environment and knowledge type?

Simultaneous examination of multiple sharing environments is needed

Differences in CMC environments

Risks versus rewards evaluation for different knowledge types

Social Exchange Theory Knowledge exchange as social exchange Norms of reciprocity (Blau, 1964; Kankanhalli et al, 2005; Wasko & Faraj, 2000) Sharing environments Face-to-face (Individual-Interpersonal) E-mail (Individual-Interpersonal) Electronic Community (Community-Generalized) Knowledge Repository (No reciprocity)

Knowledge exchange as social exchange

Norms of reciprocity (Blau, 1964; Kankanhalli et al, 2005; Wasko & Faraj, 2000)

Sharing environments

Face-to-face (Individual-Interpersonal)

E-mail (Individual-Interpersonal)

Electronic Community (Community-Generalized)

Knowledge Repository (No reciprocity)

Research Framework Knowledge type Explicit versus tacit (Nonaka & Takeuchi, 1995; Polanyi, 1966) Perceptions of risk and rewards Scope of audience (Thorn & Connolly, 1987; Zand, 1972) Reputation (Wasko & Faraj, 2005) Costs to codify knowledge

Knowledge type

Explicit versus tacit (Nonaka & Takeuchi, 1995; Polanyi, 1966)

Perceptions of risk and rewards

Scope of audience (Thorn & Connolly, 1987; Zand, 1972)

Reputation (Wasko & Faraj, 2005)

Costs to codify knowledge

Expertise Sharing Expertise as tacit knowledge High costs of codification Scope of audience for perceived benefits (Thorn & Connolly, 1987; Zand, 1972) Hypothesis One An individual is more likely to share expertise via face-to-face.

Expertise as tacit knowledge

High costs of codification

Scope of audience for perceived benefits (Thorn & Connolly, 1987; Zand, 1972)

Hypothesis One

An individual is more likely to share expertise via face-to-face.

Computer Program Sharing Computer program as explicit knowledge Low costs of codification Ease of transfer in “lean” media (Daft & Lengel, 1987) Hypothesis Two An individual is more likely to share a computer program in a CMC environment.

Computer program as explicit knowledge

Low costs of codification

Ease of transfer in “lean” media (Daft & Lengel, 1987)

Hypothesis Two

An individual is more likely to share a computer program in a CMC environment.

Reciprocity-based Sharing Degree of reciprocity Interpersonal, generalized, & no reciprocity (Blau, 1967; Kankanhalli et al., 2005; Wasko & Faraj, 2000) Greater reciprocity increases the likelihood of sharing (Chiu et al., 2006) Hypothesis Three An individual is more likely to share both types of knowledge when there is a greater likelihood of direct reciprocity.

Degree of reciprocity

Interpersonal, generalized, & no reciprocity (Blau, 1967; Kankanhalli et al., 2005; Wasko & Faraj, 2000)

Greater reciprocity increases the likelihood of sharing (Chiu et al., 2006)

Hypothesis Three

An individual is more likely to share both types of knowledge when there is a greater likelihood of direct reciprocity.

Benefits-based Sharing in CMC CMC environments and scope of audience Reputation benefits as motivation of knowledge sharing (Mauss, 1950; Raymond, 1999) Hypothesis Four When communicating electronically, an individual is more likely to contribute both types of knowledge through electronic channels that offer the greatest benefits to reputation.

CMC environments and scope of audience

Reputation benefits as motivation of knowledge sharing (Mauss, 1950; Raymond, 1999)

Hypothesis Four

When communicating electronically, an individual is more likely to contribute both types of knowledge through electronic channels that offer the greatest benefits to reputation.

Research Methodology Case-based vignettes Prior empirical research (Constant et al, 1994) Direct manipulation of contextual variables (Knowledge type and communication channel) Controls for external influence Control variables Age, work experience, ownership, perceived extent to support, and propensity to share (Adapted from Jarvenpaa et al., 1998)

Case-based vignettes

Prior empirical research (Constant et al, 1994)

Direct manipulation of contextual variables (Knowledge type and communication channel)

Controls for external influence

Control variables

Age, work experience, ownership, perceived extent to support, and propensity to share (Adapted from Jarvenpaa et al., 1998)

Research Methodology 61 MBA students Business professionals (Kruglanski, 1975) Prior empirical research (Constant et al., 1994) Age (24.78 years); Work experience (3.8 years) Repeated measures ANOVA Individual unit of analysis Pairwise comparisons

61 MBA students

Business professionals (Kruglanski, 1975)

Prior empirical research (Constant et al., 1994)

Age (24.78 years); Work experience (3.8 years)

Repeated measures ANOVA

Individual unit of analysis

Pairwise comparisons

Research Findings Hypothesis 2 EKR more likely than F2F, e-mail, and EC F2F more likely than EC Hypothesis 1 F2F more likely than e-mail & EC Partial Support for H1 & H2

Hypothesis 2

EKR more likely than F2F, e-mail, and EC

F2F more likely than EC

Hypothesis 1

F2F more likely than e-mail & EC

Research Findings Hypothesis 4 EKR more likely than e-mail & EC No difference between EKR & e-mail (Expertise) No difference between e-mail & EC (Computer Program) Hypothesis 3 F2F & EKR more likely than e-mail & EC (Computer Program) E-mail more likely than EC Partial Support for H3 & H4

Hypothesis 4

EKR more likely than e-mail & EC

No difference between EKR & e-mail (Expertise)

No difference between e-mail & EC (Computer Program)

Hypothesis 3

F2F & EKR more likely than e-mail & EC (Computer Program)

E-mail more likely than EC

Contributions & Limitations Contributions Examines likelihood of sharing within different sharing environments simultaneously Extends literature on knowledge sharing Limitations Hypothetical situations (Constant et al., 1994) Subject role as computer programmer (Constant et al., 1994) Knowledge type (Polanyi, 1966)

Contributions

Examines likelihood of sharing within different sharing environments simultaneously

Extends literature on knowledge sharing

Limitations

Hypothetical situations (Constant et al., 1994)

Subject role as computer programmer (Constant et al., 1994)

Knowledge type (Polanyi, 1966)

Future Directions of Research Assess perceptions of costs and benefits for exchanging different knowledge types in different environments in real-world setting Examine alternative knowledge types and exchange environments (e.g., Wikis) Increase number of subject roles beyond computer programmer

Assess perceptions of costs and benefits for exchanging different knowledge types in different environments in real-world setting

Examine alternative knowledge types and exchange environments (e.g., Wikis)

Increase number of subject roles beyond computer programmer

Descriptive Statistics Variable N Mean Std. Dev. Variance Info Share EKR 60 5.467 1.282 1.643 Info Share F2F 60 4.050 1.751 3.065 Info Share Email 60 3.767 1.789 3.199 Info Share EC 60 3.433 1.817 3.301 Exp Share EKR 58 5.017 1.584 2.508 Exp Share F2F 60 5.250 1.694 2.869 Exp Share Email 60 4.800 1.675 2.807 Exp Share EC 60 4.200 1.725 2.976

Bivariate Correlations Mean Std. Dev. Age Work P2S1 P2S2 P2S3 Info Share F2F Info Share E-mail Info Share EC Info Share EKR Info Share Extent Support Exp Share F2F Exp Share E-mail Exp Share EC Exp Share EKR Age 24.787 4.499 Work 3.817 4.256 0.798*** P2S1 4.733 1.483 -0.028 -0.160 P2S2 4.267 1.483 -0.105 -0.024 0.280* P2S3 5.400 1.182 -0.111 -0.139 0.333** 0.180 Info Share F2F 4.050 1.751 0.053 0.063 0.025 0.230 0.056 Info Share E-mail 3.767 1.789 0.197 0.229 0.078 -0.123 -0.027 0.448*** Info Share EC 3.433 1.817 0.280* 0.088 0.207 -0.062 0.107 0.281* 0.564*** Info Share EKR 5.467 1.282 0.238 0.160 0.076 0.014 -0.069 0.095 0.167 0.363** Info Share Extent Support 2.733 1.793 0.187 0.221 0.005 -0.005 -0.045 -0.055 0.123 0.161 -0.129 Exp Share F2F 5.250 1.694 0.073 0.043 -0.169 0.088 -0.169 0.219 0.154 0.157 0.148 -0.061 Exp Share E-mail 4.800 1.675 0.075 0.070 -0.233 -0.026 -0.216 0.136 0.312* 0.207 0.076 0.146 0.723*** Exp Share EC 4.200 1.725 0.127 0.066 -0.118 0.052 0.002 0.350** 0.400** 0.368** 0.133 0.083 0.528*** 0.618*** Exp Share EKR 5.017 1.584 0.205 0.134 0.070 -0.002 -0.050 0.164 0.376** 0.381** 0.592*** -0.047 0.330* 0.435*** 0.397** Exp Share Extent Support 3.103 1.917 0.068 0.133 0.065 0.034 0.181 -0.086 0.149 0.051 0.037 0.592*** -0.107 0.027 0.007 -0.066 * - p < 0.05 ** - p < 0.01 *** - p < 0.001