Creating knowledge within a team: a socio-technical interaction perspective

Hong, Jinwon; Lee, One-Ki (Daniel); Suh, Woojong

doi:10.1057/kmrp.2015.27

Cited by 17 publications

(13 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, entering all the moderating effects simultaneously in a single step can help control the Type I error (Frazier, Tix, & Barron, 2004). In this regard, this approach has been widely employed in recent studies (for example, Ali, Musawir, & Ali, 2018;Arazy, Gellatly, Brainin, & Nov, 2016;Chua & Banerjee, 2015;Hong, Lee, & Suh, 2017;Kobsa, Cho, & Knijnenburg, 2016;Venkatesh, Thong, & Xu, 2012). To evaluate the potential confounding effects induced by simultaneously considering multiple moderating effects, this study further included a three-way interaction effect among independent variables and the moderator in the model.…”

Section: Structural Modelmentioning

confidence: 99%

Knowledge withholding in online knowledge spaces: Social deviance behavior and secondary control perspective

Shen

Sun

et al. 2019

Asso for Info Science & Tech

View full text Add to dashboard Cite

Knowledge withholding, which is defined as the likelihood that an individual devotes less than full effort to knowledge contribution, can be regarded as an emerging social deviance behavior for knowledge practice in online knowledge spaces. However, prior studies placed a great emphasis on proactive knowledge behaviors, such as knowledge sharing and contribution, but failed to consider the uniqueness of knowledge withholding. To capture the social‐deviant nature of knowledge withholding and to better understand how people deal with counterproductive knowledge behaviors, this study develops a research model based on the secondary control perspective. Empirical analyses were conducted using the data collected from an online knowledge space. The results indicate that both predictive control and vicarious control exert a positive influence on knowledge withholding. This study also incorporates knowledge‐withholding acceptability as a moderating variable of secondary control strategies. In particular, knowledge‐withholding acceptability enhances the impact of predictive control, whereas it weakens the effect of vicarious control on knowledge withholding. This study concludes with a discussion of the key findings, and the implications for both research and practice.

show abstract

Section: Structural Modelmentioning

confidence: 99%

Knowledge withholding in online knowledge spaces: Social deviance behavior and secondary control perspective

Shen

Sun

et al. 2019

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

“…Such findings challenge the conventional wisdom of the field, which has been dedicated only to see KT factors from the point of view of the influence they have on KT, i.e. direct effects (Du et al, 2007;Hong et al, 2017;Chang et al, 2017). Therefore, our work brings KT back to its roots: the field of system dynamics in organizational learning (Argyris, 2017).…”

Section: Discussionmentioning

confidence: 73%

“…In the literature, there are several studies that have considered how different organizational characteristics and practices can help to foster KT between NPD project teams (e.g. Liu & Phillips, 2011;Hong et al, 2017;Chang et al, 2017). Some scholars have analyzed these factors from the technological point of view (Alavi & Leidner, 2001;Choi et al, 2008) while others have considered human and organizational aspects (Chang et al, 2017;Hong et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Liu & Phillips, 2011;Hong et al, 2017;Chang et al, 2017). Some scholars have analyzed these factors from the technological point of view (Alavi & Leidner, 2001;Choi et al, 2008) while others have considered human and organizational aspects (Chang et al, 2017;Hong et al, 2017). Frank et al (2015) research summarized several KT factors of the literature in a taxonomy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A relationship model for factors influencing knowledge transfer between NPD teams

Frank

Ayala

Corso

et al. 2018

Prod.

View full text Add to dashboard Cite

Paper aims:To define a model that describes the relationship among the main factors influencing knowledge transfer (KT) between new product development (NPD) teams. Originality:We offer a systemic vision of the relationship between the KT factors. All main KT factors are analyzed together considering the interdependence among them.Research method: KT factors from the literature were used for the model development, which was accomplished through a quantitative evaluation of scholars and practitioners. To test the model, a practical assessment was conducted in five firms using regression analysis. Main findings:The model describes the relationships of 15 main factors and it can be used for practical assessments or for future theoretical studies. Implications for theory and practice:The model can help practitioners to use knowledge of their teams for continuous innovation in NPD. It allows to perform diagnoses of the KT factors in the specific context of a given firm.

show abstract

“…Moreover, organizations building teams with people from different functional background with the purpose of developing novel product; people associated with the team can share their diversified knowledge and accordingly work towards developing new idea and concept (Chiang, Hung, 2014). Building team can be regarded as an important factor which allows individual to show their creative side, which is significant aspect of developing a novel product (Hong et al, 2017). Teamwork also helpful in solving different problem creatively through brainstorming sessions, at the same time employees overall knowledge of the product or services also improved (Prajogo, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Hr-Linked Quality Assurance System on Operational Proficiency

Kerdpitak¹,

Boonrattanakittibhumi²

2020

JSSI

View full text Add to dashboard Cite

The purpose of this study is to embrace the theoretical context of operational proficiency and accordingly examines the connection between human resource-linked with quality assurance system and development of novel product taking with the consideration to operational proficiency, learning system, knowledge assimilation, and strategic adaptability. Learning system and knowledge assimilation are correlated with strategic adaptability of an organization, and strategic adaptability is the established capability, which enables development of novel product. In order to empirically examine the connection, data was gathered from ASEAN organizations and structural equation modeling was carried out. Findings reveal that human resource connected with quality assurance system facilitate in establishing learning focused organization, unifying knowledge and assists in development of novel product. Moreover, Unification of knowledge is progressively associated with development of new product via strategic adaptability.

show abstract

Creating knowledge within a team: a socio-technical interaction perspective

Cited by 17 publications

References 52 publications

Knowledge withholding in online knowledge spaces: Social deviance behavior and secondary control perspective

Knowledge withholding in online knowledge spaces: Social deviance behavior and secondary control perspective

A relationship model for factors influencing knowledge transfer between NPD teams

Impact of Hr-Linked Quality Assurance System on Operational Proficiency

Contact Info

Product

Resources

About