The influence of collaborative technology knowledge on advice network structures

被引：14

作者：

Keith, Mark ^{[1
]}

Demirkan, Haluk ^{[2
]}

Goul, Michael ^{[2
]}

机构：

[1] W Texas A&M Univ, Coll Business, Dept Informat & Decis Management, College Stn, TX USA

[2] Arizona State Univ, WP Carey Sch Business, Dept Informat Syst, Ctr Serv Leadership, Tempe, AZ 85287 USA

来源：

DECISION SUPPORT SYSTEMS | 2010年 / 50卷 / 01期

关键词：

Decision making; Social networks; Information and knowledge sharing; Collaborative technology; Web; 2.0; Group structure; Task environment uncertainty; Entrainment theory; Assymetric adaptability;

D O I：

10.1016/j.dss.2010.07.010

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This research describes an experiment designed to understand how an individual's knowledge concerning task-critical technologies influences the structure of their advice network relationships. The results indicate that an individual's technology knowledge leads them to become more central depending on the type of technology, their formal group structure, and task uncertainty. These results contribute to the theory on advice networks by demonstrating how individual knowledge, task uncertainty, and group departmentation influence the evolution of an advice network structure. It suggests that managers should make informed decisions about the formal group structuring and technology training which can improve their employee's advice networks. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：140 / 151

页数：12

共 50 条

[31] Collaborative tagging supported knowledge discovery [J].

Zauder, Kresimir ;

Lazic, Jadranka Lasic ;

Zorica, Mihaela Banek .

PROCEEDINGS OF THE ITI 2007 29TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES, 2007, :437-+

[32] Collaborative patents and the mobility of knowledge workers [J].

Miguelez, Ernest .

TECHNOVATION, 2019, 86-87 :62-74

[33] A Team-Level Study of the Relationship between Knowledge Sharing and Trust in Kenya: Moderating Role of Collaborative Technology [J].

Kipkosgei, Felix ;

Kang, Seung-Wan ;

Choi, Suk Bong .

SUSTAINABILITY, 2020, 12 (04)

[34] Extraversion is associated with advice network size, but not network density or emotional closeness to network members [J].

Malcolm, C. ;

Saxton, T. K. ;

McCarty, K. ;

Roberts, S. G. B. ;

Pollet, T. V. .

PERSONALITY AND INDIVIDUAL DIFFERENCES, 2021, 168

[35] Collaborative public administration on the network [J].

Graells-Costa, Jordi .

PROFESIONAL DE LA INFORMACION, 2011, 20 (03) :345-347

[36] Influence of Social Media on Enterprise Knowledge Sharing Based on Social Network Analysis [J].

Deng, Yongtao .

ENTREPRENEURSHIP RESEARCH JOURNAL, 2021, 11 (02) :99-118

[37] Design and Analysis of Knowledge Transfer in the Process of University-Industry Collaborative Innovation Based on Social Network Theory [J].

Xiao, Lin ;

Xu, Shenghua ;

Zeng, Xiaxia .

JOURNAL OF INTERNET TECHNOLOGY, 2018, 19 (04) :1155-1167

[38] Passing the torch of knowledge: Star death, collaborative ties, and knowledge creation [J].

Khanna, Rajat .

RESEARCH POLICY, 2023, 52 (01)

[39] Collaborative technologies for science, technology, engineering, and mathematics (STEM): Sociology of science and knowledge, holistic systems engineering, and systems thinking [J].

Jones, Keith W. ;

Kristof, Dale ;

Jenkins, Larry C. ;

Ramsey, Jeffry ;

Patrick, Dale ;

Burnham, Samuel ;

Turner, I. Leon .

PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COLLABORATIVE TECHNOLOGIES AND SYSTEMS: CTS 2008, 2008, :460-466

[40] Collaborative Modeling and Group Decision Making Using Chatbots in Social Network [J].

Perez-Soler, Sara ;

Guerra, Esther ;

de Lara, Juan .

IEEE SOFTWARE, 2018, 35 (06) :48-54

← 1 2 3 4 5 →