Proceedings of the 12th European Conference on Knowledge ...

Claire Gubbins et al
Wang and Noe (2010) identifies a number <strong>of</strong> individual level characteristics as key influencers but
<strong>the</strong>y and Cho, Li and Su (2007) recognise a number <strong>of</strong> gaps and argue for fur<strong>the</strong>r research on
individual level variables. Additionally, Wang and Noe’s (2010) review only focused on <strong>the</strong> knowledge
sharing process <strong>of</strong> knowledge management. In this regard, this paper focuses on exploring individual
level influencers on each <strong>of</strong> <strong>the</strong> sub-processes <strong>of</strong> knowledge management. Also, many empirical
studies concerned with knowledge management fail to differentiate between tacit and explicit
knowledge and <strong>the</strong> inherent differences in <strong>the</strong> challenges presented in managing <strong>the</strong>se different forms
<strong>of</strong> knowledge. Therefore, this study aims to explore <strong>the</strong> influence <strong>of</strong> individual level factors on tacit
knowledge management processes.
2. Research Methodology
This research is part <strong>of</strong> a wider study <strong>of</strong> tacit knowledge management in seven manufacturing MNC’s
that is being undertaken as part <strong>of</strong> an academic-industry collaborative research project. The aim <strong>of</strong>
<strong>the</strong> study is to design, develop and implement a methodology to enable <strong>the</strong> description and evaluation
<strong>of</strong> tacit knowledge practices and preferences among engineers in manufacturing MNC’s in Ireland.
This paper reports <strong>the</strong> findings from interviews with a sample <strong>of</strong> engineers and managers from one
case study site. The participants are engineers whom engage in routine and non-routine tasks which
demand use <strong>of</strong> both explicit and tacit knowledge. The participants were selected by <strong>the</strong> lead
researcher to meet <strong>the</strong> following criteria: ensure a cross-section <strong>of</strong> views were obtained and ensure
participants work included routine and non-routine tasks which demand <strong>the</strong> use <strong>of</strong> both explicit and
tacit knowledge. Then, a snowball sampling approach (Noy, 2008) was utilised, whereby <strong>the</strong> initial
interviews were used to identify fur<strong>the</strong>r populations for study whom were important to <strong>the</strong> focal
individuals efforts to manage <strong>the</strong> knowledge required to do <strong>the</strong>ir work. The qualitative methodology
consisted <strong>of</strong> structured interviews (Miles & Huberman, 1994; Streb, 2009) ranging in duration from 75
to 120 minutes. A total <strong>of</strong> 33 interviews were conducted. This paper focuses predominately on <strong>the</strong>
views <strong>of</strong> <strong>the</strong> maintenance engineers with <strong>the</strong> views from <strong>the</strong> o<strong>the</strong>r interviewees used to validate,
cross-check, understand or elaborate on <strong>the</strong> views <strong>of</strong> <strong>the</strong> engineers. A qualitative exploratory and
explanatory methodology is utilised which adopts a funnelling approach (see Minichiello et al, 1992) to
semi-structured interviews. The interviews were audio recorded, transcribed verbatim and content
analysed using NVivo.
3. Findings
The results <strong>of</strong> this study reveal that, in considering <strong>the</strong> knowledge circulation sub-processes with a
focus explicitly on tacit knowledge or ‘know-how’, it is <strong>the</strong> impact <strong>of</strong> individual level factors on <strong>the</strong> subprocesses
<strong>of</strong> seeking and capture that most strongly impact <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> tacit knowledge
management process. The importance <strong>of</strong> individual level factors on intention or willingness to share
knowledge also emerges. Therefore, <strong>the</strong> findings are organised under <strong>the</strong>se headings <strong>of</strong>: seeking
tacit knowledge, capturing tacit knowledge and willingness to share. The results reveal that this
knowledge circulation is mediated by a number <strong>of</strong> individual level processes. These processes can be
categorised into two clusters; attributes <strong>of</strong> <strong>the</strong> tacit knowledge seeker as perceived by <strong>the</strong> seeker and
<strong>the</strong>ir influence on <strong>the</strong> knowledge management process steps <strong>of</strong> seeking and capture; and attributes <strong>of</strong>
<strong>the</strong> knowledge source as perceived by both <strong>the</strong> seeker during <strong>the</strong> knowledge seeking process and as
perceived by both <strong>the</strong> seeker and <strong>the</strong> source during <strong>the</strong> collaborative knowledge capture process. A
third cluster <strong>of</strong> influencers moderating <strong>the</strong> seeking and capture processes pertain to <strong>the</strong> tacit
knowledge source. The source whom is approached by a knowledge seeker engages in a decisionmaking
and analysis process, influenced by his/her personal attributes, which determines his/her
willingness to share knowledge and what or how much to share before <strong>the</strong> capture process can
commence. Figure 1 presents a tentative, descriptive model to illustrate <strong>the</strong>se observations and <strong>the</strong>
results leading to this model will be discussed in <strong>the</strong> following sections.
3.1 Individual Influencers on Efforts to Seek Tacit ‘Know-How’
The results <strong>of</strong> this case site illustrate that <strong>the</strong>re is a strong awareness among respondents <strong>of</strong> where to
seek required ‘know-how’ and whom <strong>the</strong> experts are in any given functional area or with respect to
any given machine. This awareness is facilitated informally through <strong>the</strong> social network. However
decisions on whe<strong>the</strong>r to seek knowledge, when to seek knowledge and whom to seek knowledge
from are influenced by a number <strong>of</strong> factors discussed below. Seeker Attributes; The first <strong>of</strong> <strong>the</strong> most
frequently cited seeker attribute influencers included <strong>the</strong> individual’s social confidence in seeking
knowledge from o<strong>the</strong>rs. There is a general belief that engineers must be willing to use <strong>the</strong>ir initiative
and actively go and seek and ask for <strong>the</strong> knowledge <strong>the</strong>y require. This extends to some perceptions
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