Analysing knowledge sharing behaviour in business centres: a mixed multinomial logit model

被引:7
|
作者
Weijs-Perree, Minou [1 ]
Appel-Meulenbroek, Rianne [1 ]
Arentze, Theo [1 ]
机构
[1] Eindhoven Univ Technol, Dept Built Environm, Urban Syst & Real Estate, Vertigo 8-35, Eindhoven, Netherlands
关键词
Business centre; face-to-face interaction; knowledge sharing; experience sampling method (ESM); mixed multinomial logit model (MMNL); EXPERIENCE SAMPLING METHODOLOGY; PERSPECTIVE; PERFORMANCE; OFFICE; LAYOUT;
D O I
10.1080/14778238.2019.1664269
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Previous studies have analysed face-to-face interaction patterns and knowledge sharing between employees within large organisations. However, knowledge about whether and which type of knowledge is shared in business centres where organisations share spaces, facilities and services, is still limited. This paper addresses this research gap by looking at knowledge sharing in business centres. Data was collected among 100 users of seven business centres in the Netherlands, by means of a questionnaire and an Experience Sampling Method (ESM). A mixed multinomial logit model (MMNL) was used to analyse the data. The results showed that tacit knowledge is shared more frequently during discussions/debates, formal meetings and when receiving or giving advice. In addition, the people more often share explicit knowledge during pre-planned interactions than during unplanned interactions. Results of this study provide more insights in business centre users' knowledge sharing behaviour, which could help organisations to increase their innovation processes.
引用
收藏
页码:323 / 335
页数:13
相关论文
共 50 条
  • [1] Semiparametric multinomial logit models for analysing consumer choice behaviour
    Kneib, Thomas
    Baumgartner, Bernhard
    Steiner, Winfried J.
    [J]. ASTA-ADVANCES IN STATISTICAL ANALYSIS, 2007, 91 (03) : 225 - 244
  • [2] Semiparametric multinomial logit models for analysing consumer choice behaviour
    Thomas Kneib
    Bernhard Baumgartner
    Winfried J. Steiner
    [J]. AStA Advances in Statistical Analysis, 2007, 91 : 225 - 244
  • [3] A spatial multinomial logit model for analysing urban expansion
    Krisztin, Tamas
    Piribauer, Philipp
    Woegerer, Michael
    [J]. SPATIAL ECONOMIC ANALYSIS, 2022, 17 (02) : 223 - 244
  • [4] Formulating the Rasch model as a mixed coefficients multinomial logit
    Adams, RJ
    Wilson, M
    [J]. OBJECTIVE MEASUREMENT: THEORY INTO PRACTICE, VOL 3, 1996, : 143 - 166
  • [5] A multinomial mixed logit model of housing tenure.
    Garcia, Javier A. Barrios
    Hernandez, Jose E. Rodriguez
    [J]. REVISTA DE ECONOMIA APLICADA, 2005, 13 (38): : 5 - 27
  • [6] Sensitivity Analyses for the Mixed Coefficients Multinomial Logit Model
    Kasper, Daniel
    Uenlue, Ali
    Gschrey, Bernhard
    [J]. DATA ANALYSIS, MACHINE LEARNING AND KNOWLEDGE DISCOVERY, 2014, : 389 - 396
  • [7] A Bayesian mixed logit-probit model for multinomial choice
    Burda, Martin
    Harding, Matthew
    Hausman, Jerry
    [J]. JOURNAL OF ECONOMETRICS, 2008, 147 (02) : 232 - 246
  • [8] Vacation length choice: A dynamic mixed multinomial logit model
    Grigolon, Anna B.
    Borgers, Aloys W. J.
    Kemperman, Astrid D. A. M.
    Timmermans, Harry J. P.
    [J]. TOURISM MANAGEMENT, 2014, 41 : 158 - 167
  • [9] Learning Mixed Multinomial Logit Model from Ordinal Data
    Oh, Sewoong
    Shah, Devavrat
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 27 (NIPS 2014), 2014, 27
  • [10] Asymptotic Inferences in a Multinomial Logit Mixed Model for Spatial Categorical Data
    Brajendra C. Sutradhar
    R. Prabhakar Rao
    [J]. Sankhya A, 2023, 85 : 885 - 930