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Author: Pelletier Pui Man Ho

Title of Project: Organisational and Subgroup Cultures: Implications for

Knowledge Sharing within a Project-Based Organisation

in the United Kingdom

   

 

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Table of Contents

Chapter 1. Introduction   4  1.1. Statement of the Research Question   7  

Chapter 2. Literature Review   8  2.1. Challenges of Knowledge Sharing in Project-Based Organisations (PBOs)   10  2.2 Organisational Culture as a Predictor of Knowledge Sharing Behaviours   11  2.3 Subgroup Culture as a Moderator   16  

Chapter 3. Research Methodology   19  3.1 Settings   19  3.2 Research Design   20  3.3. Data Collection   21  3.4 Data Analysis   26  

Chapter 4. Results of Analysis   29  4.1 Demographic Information   29  4.2 Reliability   30  4.3 Organisational Culture   30  4.4 Subgroup Cultures   31  4.5 Knowledge Sharing   34  4.6 Validity – Testing Hypotheses   36  4.7 Analysing Focus Groups   41  

Chapter 5. Discussion   47  5.1 Individual Effects of Organisational Culture on Knowledge Sharing   48  5.2 Combined Effects of Organisational and Subgroup Culture on Knowledge Sharing   50  

Chapter 6. Limitations and Opportunities   53  Chapter 7. Conclusion and Recommendations   55  References   59  Appendices   65  

Appendix D1: Questions of Online questionnaire (with assigned data codes)   65  Appendix D2: Questions of Focus Groups   67  Appendix D3: Reliability Statistics   68  Appendix D4: Focus Group Responses (Coded)   78  

 

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Executive Summary

Numerous researchers had confirmed the relationship between organisational culture

and its effects on knowledge sharing behaviours (Lindkvist, 2005; Ajmal & Koskinen,

2008; Suppiah & Sandhu, 2011; Wiewiora et al., 2013). As Project-Based

Organisations (PBOs) gain prominence in organisational research, the formation of

interdependent yet autonomous project units and the associated impact of subgroup

cultures on knowledge sharing, have began to emerge as a topic of interest for other

scholars such as Eskerod and Skriver (2007), Mueller (2012), and Carton and

Cummings (2013).

This study reports the findings from a cross-sectional mixed methods research

conducted in a UK-based project-based organization (PBO). Corroboration of findings

from qualitative and quantitative analyses indicated that, within the context studied,

different organisational and subgroup cultural orientations have had different effects on

knowledge sharing behaviours. Although some limitations were identified, overall, this

study indicates that diagnosis of organisational and subgroup cultures, together with an

enriched analysis of project units’ embedded knowledge sharing behaviours, can

inform organisational efforts to enhance knowledge sharing practices and

organisational effectiveness.

Moreover, due to the scarcity of empirical research found in the application of the

Competing Values Framework (CVF) for assessing presence of subgroup cultures, this

research aims to contribute to this under-developed area of research on subgroup

cultures with organisations, as well as the wider body of knowledge management

research.

 

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Chapter 1. Introduction

During the latter half of the 20th century, there was a major shift in the way businesses

operated. Many organisations began to shift from business models that originally

focused on mass production to offer customised services to meet the demanding needs

of technically advanced and competitive markets. This also necessitated a shift from

traditionally functional organisational structures, which relied on systematic

consistency, to become project-based organisations with a focus on agile work and

flexibility (Wiewiora et al., 2009).

Project-based organisations (PBOs) are inherently flexible, and are regarded as ideally

suited for coping with today’s technological advances, needs for innovation and

responsiveness to market changes (Hobday, 2000). Agile work and the application of

project management methodologies for guiding operational activities have also gained

increasing prominence in organisational approaches for improving overall adaptive

capacities (Ajmal & Koskinen, 2008).

PBOs function in highly volatile and knowledge intensive environments, whereby the

‘project’ forms its primary business function (Wiewiora et al., 2013). This requires

effective knowledge sharing, and integration of different knowledge types and

functional skills, so to achieve project goals such as time, budget and quality of output

(Bredin, 2008). Knowledge sharing on a project level requires socialisation of project

stakeholders as well as accessing relevant project documents through shared

information networks (Pemsel & Wiewiora, 2013).

From an organisational learning perspective1, lessons may be learnt via sharing of

project members’ experiences and best practices (Swan et al., 2010). Such knowledge

sharing can help reduce risks of ‘reinventing the wheel’ as well as repeating past

project mistakes (Davenport & Prusak, 1998). The successful use of organisational

                                                                                                               1 Organisational learning is defined as a process of modifying and improving organisational actions as a result of reflection, new knowledge and insight (Edmondson, 2002 cited in Swan et al., 2010).

 

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knowledge and the cultivation of a knowledge-friendly culture are also believed to be

conducive to an organisation’s competitive advantage (Ajmal & Koskinen, 2008).

However, the context of PBOs is complex. The combination of engaged knowledge

sources, the composition of professionals from varied backgrounds at different stages

of a project, together with the multiplicity of knowledge types, poses a challenging task

for PBOs to effectively manage their project knowledge (Wiewiora et al., 2013). In

addition, project units tend to work autonomously on each project stage within the

project’s life cycle; together with managerial push for time and productivity, cross-

project learning and communication is often rendered a neglected task (Hobday, 2000).

The risk of losing accumulated knowledge throughout projects poses severe

consequences for PBOs in terms of organisational effectiveness and organisational

learning. Upon investigating variables that can impact knowledge sharing behaviours

within PBO’s, various empirical studies were found to indicate significant influence of

organisational culture in shaping patterns and qualities of interactions needed to

leverage knowledge sharing among individuals (De Long & Fahey, 2000; Gray &

Densten, 2005; Wiewiora et al., 2013).

Organisational Culture is defined as “taken-for-granted values, underlying

assumptions, expectations, collective memories, and definitions present in an

organisation” (Cameron & Quinn, 2006, p.16). As such, culture establishes an

organisational context for social interaction and creates cultural norms for defining how

people communicate and share knowledge (Ajmal & Koskinen, 2008). According to

De Long and Fahey (2000), cultural attributes can influence knowledge sharing

horizontally across organisational units, and vertically throughout different levels of the

organisation hierarchy.

In a PBO context, project work typically involves multiple project units that each has

unique ways of working, and may not be in harmony with one another or with the

prevailing culture of the PBO (Ajmal & Koskinen, 2008). Cameron and Quinn (2006)

affirm that units within organisations such as functional departments, hierarchical

 

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levels or teams each have unique cultures. During such instances, cultural differences

amongst project units can be a source of creativity and learning, or a source of conflict

and miscommunication (Wiewiora et al., 2013).

Eskerod and Skriver (2007) have also suggested that reluctance found in knowledge

sharing activities between project managers may be explained by organisational

subcultures, where work organisation by projects was found to create knowledge silos

and constrain knowledge transfer. Hence, it is important that PBOs are aware of the

distinctive cultural influences for predicting respective knowledge sharing behaviours,

so that they may structure suitable knowledge sharing mechanisms around these

behaviours for enhancing project performance and organisational learning.

The purpose of this study was, therefore, to examine the individual and combined

effects of organisational culture and subgroup cultures on knowledge sharing

behaviours within a selected project-based organisation in the United Kingdom.

Hypotheses for testing empirical relationships between organisational culture and

subgroup cultures on knowledge sharing behaviours were developed subsequent to

reviewing existing bodies of relevant literature on project-based organisations,

organisational culture, subgroup cultures, and knowledge management with a specific

focus on knowledge sharing practices.

Approaches from both quantitative correlational and qualitative case study designs

were combined in this cross-sectional mixed methods research. Both statistical and

non-statistical data obtained was used to analyse how organisational and subgroup

cultural orientations may affect patterns of knowledge sharing behaviours within the

PBO. Limitations relating to selection of population, adaptation of measurement scales,

and research design as well as opportunities identified for future research was also

discussed. This paper concludes with a summary of developed recommendations for

informing senior managements’ efforts to enhance knowledge sharing and

organisational learning effectiveness. The results of this study will be presented to the

PBO’s senior management team at a later date, and are anticipated to positively

 

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influence the PBO studied where developed recommendations will be considered for

initiating subsequent cultural changes in the coming year.

1.1. Statement of the Research Question

Typically, in mixed methods research studies, researchers should incorporate at least

one qualitative and one quantitative research question. Following advice from

Onwuegbuzie & Leech (2006), both questions should be open-ended and non-

directional when seeking to “discover, explore, or describe a particular

participant(s)… context…experience, process” (p.486).

For the purposes of this study, the mixed methods research question: “What are the

Implications of Organisational Culture and Subgroup Cultures on Knowledge

Sharing Behaviours within a Project-Based Organisation?” incorporated both a

quantitative correlational research design and a qualitative case study design.

The quantitative correlation design of the research question was intended to measure

the organisation’s dominant cultural orientation, existing subgroup cultural orientations

for predicting levels of knowledge sharing between project units within the PBO. The

qualitative case study design of the research question was intended to analyse the

embedded knowledge sharing behaviours of project units, and provided insight into

perceptions of dominant organisational culture and subgroup cultures, and how such

perceptions have influenced their knowledge sharing practices within the PBO.

 

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Chapter 2. Literature Review

Knowledge is the result of processing data and information through individual

experiences, interpretation and reflection (Davenport et al., 1998). Knowledge is

categorised as either tacit or explicit. According to Nonaka (1994), tacit knowledge

refers to developed cognitive models that define how individuals perceive and define

their world, while “explicit or codified knowledge refers to knowledge that is

transmittable in formal, systematic language” (p.16). Nonaka and Takeuchi (1995) add

that knowledge may be viewed at the individual, group or organisational levels. In

agreement, De Long (1997) specifies that the purpose of knowledge management is to

ensure knowledge generated at the individual and group levels are fully captured and

leveraged at an organisational level to drive business success.

Where “new knowledge always begins with the individual”, tacit knowledge is

individualistic and context specific, which makes it difficult to formalised and

communicate (Nonaka, 1991, p.164). In organisations, tacit knowledge is usually

captured and made explicit via documents, databases and processes (Ajmal &

Koskinen, 2008). For PBOs, incremental learning occurs through tacit accumulation of

project members’ experiences, which can be applied to improve team and

organisational performance quality over time (Swan et al., 2010). The knowledge

workers tacit knowledge may contain specific know-how, workmanship and skills that

contribute to the overall success of projects, and risk of losing such invaluable

knowledge could result in unnecessary errors, wasted efforts and time loss (Wiewiora

et al., 2013).

From a resource-based view, knowledge is perceived as the primary asset of all

organisations (Argote & Ingram, 2000). Davenport and Prusak (1998) explains the

value of knowledge, which increases, with its level of accessibility. The mere existence

of knowledge somewhere, inaccessible within an organisation, alludes to a “search-

transfer problem” where members are unable to find information or access relevant

knowledge sources due to weak network ties within the organisation (Hansen, 1999).

 

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Davenport and Prusak (1998) proposes two dimensions in studying knowledge transfer,

specifically how knowledge is transferred (i.e. practice) and the richness of the

knowledge transferred (i.e. quality). Nonaka (1991) suggests that ‘Knowledge-Creating

Companies’ are not only successful due to their abilities to generate new knowledge,

but in their effective management of knowledge processes. It is believed that effective

utilisation of valuable knowledge can differentiate organisations from their competitors

for sustaining competitive advantage (Davenport & Prusak, 1998).

According to Nonaka and Takeuchi (1995), new knowledge is created through the

dynamic interaction between tacit and explicit knowledge. In the context of a PBO,

effective knowledge management will ensure that any new knowledge derived from

projects is shared through socialization and externalization of project members, which

are triggered by dialogue and teamwork; and may be facilitated through the use of

technology and shared databases (Nonaka & Takeuchi, 1995). Given the strategic value

of the knowledge workers’ professional experience and technical expertise,

organisations cannot afford to ignore the respective values and behavioural norms of

these individuals, often labelled as ‘culture’, when implementing their knowledge

management strategy (De Long, 1997).

This section focuses on establishing significance of this study by critically reviewing

the relevant literature on organisational culture, subgroup cultures and knowledge

management with a specific focus on both the practices of knowledge sharing as well

as the quality of knowledge shared within the context of project-based organisations. In

particular, this section aims to outline the key challenges of knowledge sharing within

PBOs, as well as propose possible empirical relationships between organisational

culture, subgroup cultures and levels of knowledge sharing.

 

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2.1. Challenges of Knowledge Sharing in Project-Based Organisations (PBOs)

Lindkvist (2005) refers to PBOs as knowledge ‘collectivities’ where projects require an

effective assimilation of knowledge workers (p.1200). One of the key challenges within

PBOs is that project knowledge tends to reside within the minds of individual

knowledge workers during and after project cycles, rather than being shared on a

common knowledge base. In earlier works of Lindkvist & Söderlund (2002, cited in

Lindkvist, 2005 p.1202), the authors explained that project managers should learn from

trial-and-error processes so to minimize prospective errors. Eskerod and Skriver (2007)

confirm the serious problem of sharing tacit knowledge experienced by PBOs, and their

challenges in making inter-intra project-based learning more explicit or accessible

through knowledge transfer.

PBOs in its purest form are organized solely around ‘projects’ with no formal

functional structure or organisational hierarchies, allowing the organisation to respond

more readily to market demands and change (Hobday, 2000). Unlike functional

managers, project managers within a PBO act as connectors between projects and the

organisation, and are able to assign dedicated interim resources and personnel across

business functions to work on a temporary project (Wiewiora et al., 2009). Each

project operates with a high degree of autonomy during the project cycle and its

members are disbanded when the project finishes to be regrouped to work on a new

project (Pemsel & Wiewiora, 2013). Moreover, during the project cycle, each project

unit is assigned distinct functional tasks to be completed during different project stages,

and decision-making is left to individual expertise and discretion (Swan et al., 2010).

The lack of formal links within project units and across projects, in addition to the

temporary nature of project work, have resulted in weak communication and poor

knowledge sharing amongst project members (Hobday, 2000). Newell et al. (2003)

adds that even when significant project-based learning was generated, PBOs are

ineffective in capturing, retaining or converting such learning to improve their existing

processes. Coupled with pressures on productivity and delivery, there is little

motivation or time for project members to reflect on their project experiences or

 

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document transferable knowledge for future reference (Pemsel & Wiewiora, 2013).

Other reasons such as geographic dispersion of projects and the lack of knowledge

management strategies have further hampered communication and motivation to share

knowledge within PBOs (Hobday, 2000).

2.2 Organisational Culture as a Predictor of Knowledge Sharing Behaviours

The humanistic nature of knowledge creation and the social dimension for knowledge

transfer has called for an analysis into organisational culture as either an enabler or

barrier of knowledge sharing (Lilleoere & Hansen, 2011). Knowledge outside of its

context turns into information without reference (Nonaka & Konno, 2005). The

complexity and uncertainty of PBOs has provided a unique context for knowledge

management, distinct from other business organisations (Ajmal & Koskinen, 2008).

Lindkvist (2005) refers to this context as a “project culture” (p.1206).

Schein (2010) defines organisational culture as the “product of group experiences” and

is exhibited through artefacts, espoused beliefs and values, and basic underlying

assumptions. The author describes organisational culture as assimilated patterns of

basic assumptions that are developed by its existing members as they learn to cope with

problems at work, and are to be imparted to new members as the correct way to

perceive, think and act within the same context (Schein, 2005 cited in Nonaka &

Takeuchi, 1995). Martin and Siehl (1983) have also defined organisational culture as an

expression of corporate ideology or management philosophy that guides the behaviours

and practices of its employees.

According to De Long and Fahey (2000), there are four ways in which a project culture

can influence knowledge sharing behaviours within a PBO. First, it creates a unique

context, as discussed in the previous section, in which social interaction and knowledge

sharing amongst project members are manifested. Cultural contexts can determine the

acceptability of discussing sensitive topics, perceived approachability of senior

managers or appropriateness of behaviours relating to how knowledge is managed

(Abou-Zeid, 2005). Culture also defines the knowledge structures and processes by

 

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which knowledge is utilised and distributed across the PBO. “Knowledge structures

can vary from one that is highly diffused and group-based to one that is task-specific

and individual-based” (Lam, 1997 cited in Abou-Zeid, 2005, p.149) Lastly, culture

shapes project members’ assumptions when evaluating the validity and value of

knowledge or its source (De Long & Fahey, 2000).

De Long (1997) advocates the intimate relationship between organisational knowledge

and culture, and furthers that an organisation’s ability to transfer and apply knowledge

would be impossible without ensuring cultural support for such behaviours. We,

therefore, turn our attention to identifying the relevant theories and tools used to

diagnose organisational culture so that we may understand how different cultural

attributes can support or hinder knowledge sharing within organisations.

The Competing Values Framework (CVF) was identified as one of the most widely

used tools in research on organisational culture (Suppiah & Sandhu, 2011). The CVF,

developed by Cameron and Quinn (2006), provides a holistic view of organisational

culture and has been validated in numerous international contexts (Wiewiora et al.,

2013). The CVF characterized the complexity of organisational culture into two

dimensions: flexibility and discretion versus stability and control, and internal versus

external orientations. Holistically, these two dimensions represent four quadrants to

represent the distinctive and competing assumptions, each characterized by unique

cultural attributes. These four cultural types are namely Clan, Adhocracy, Hierarchy

and Market (Cameron & Quinn, 2006). [See Figure 1]

The upper left quadrant identifies values of Clan cultures with an internal focus. Clan

cultures tend to emphasize on a shared vision and commitment through teamwork and

empowerment, representing core values of participation, tradition and loyalty

(Cameron & Quinn, 2006). The lower left quadrant identifies values of Hierarchy

cultures with a focus on internal control and stability. Hierarchy culture tends to

emphasize on formal rules and procedures with centralization and control as its core

values (Wiewiora et al., 2013). Global conglomerates such as Ford Motors and

McDonalds whose business models required stable processes for mass production, as

 

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well as many governmental departments had adopted hierarchical organisational

cultures (Cameron & Quinn, 2006).

The lower right quadrant identifies values of Market cultures with a strong external

focus rather than an orientation towards internal affairs. Market-type organisations

value competition, productivity and achieving bottom-line targets (Cameron and

Quinn, 2006). Market cultures, therefore, place heavy emphasis on sustaining

competitive advantage and profitability. Jack Welch, former CEO of General Electric,

was a strong advocate of this highly competitive culture (Cameron and Quinn, 2006).

Similarly, the upper right quadrant identifies Adhocracy cultures with a strong external

orientation. Adhocracy cultures are also referred to as open systems, which emphasize

flexibility, adaptability and innovation (Wiewiora et al., 2013). Adhocracy cultures,

therefore, do not have centralized power and encourages individuality and risk taking

(Cameron and Quinn, 2006). [See Figure 2]

According to Davenport et al. (1998), the cultivation of a knowledge-friendly culture is

one of the most important enablers for knowledge sharing. In such cultures, the

organisation holds a positive orientation to knowledge creation and places emphasis on

knowledge sharing and organisational learning (Davenport et al., 1998). This induces

knowledge sharing behaviours where individuals will proactively seek out

knowledgeable colleagues as knowledge sources and trusted advisors (Connelly &

Kelloway, 2003). However, not all cultural attributes will positively influence

knowledge sharing (De Long & Fahey, 2000).

Knowledge sharing can also be seen as a process of knowledge exchange (Lilleoere &

Hansen, 2011). Of the numerous cultural attributes identified in past empirical research,

characteristics relating to ‘trust’ had received the most attention in relation to its

positive influence on knowledge sharing (Wang & Noe, 2010). Wiewiora et al. (2013)

proposes that knowledge sharing is contingent upon personal choice and disposition,

where individuals are reluctant to share knowledge without some degree of personal

gain in return, or if they perceived their working environment to lack trust. In

innovative cultures, where employees are encouraged to ‘think outside the box’,

sharing experiences of trial and error are perceived as opportunities for learning and

 

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improvement rather than blame (Mueller, 2014). Davenport et al. (1998) emphasizes

that it is important employees do not feel that they are at risk when sharing knowledge

with others.

However, it’s been posited that where knowledge is recognised as power, employees

are generally motivated to hoard rather than share knowledge so to maintain a

competitive advantage in their careers (Suppiah & Sandhu, 2011). Similarly,

organisational cultures that promote competition and individualism were found to

impede knowledge sharing, whereas collaborative cultures that highlight shared

responsibilities and teamwork was found to enhance knowledge sharing amongst its

team members (Wang & Noe, 2010). This was mainly due to employees’ fears of

letting their colleagues down and so would exhibit greater efforts to support each other

by sharing valuable knowledge (De Long, 1997). In addition, cultures that reward

individuals for sharing behaviours were found to create different knowledge sharing

patterns than cultures that do not promote such activities (De Long & Fahey, 2000).

Evans (2012) adds that in hierarchical cultures, formal organisational structures may

run contrary to open access and free flow of communication that is demanded by a

collaboration and knowledge sharing to occur. Other case study results also indicate

that market cultures tend to have a negative impact on inter-project knowledge sharing

(Wiewiora et al., 2013). Hence, in summary and with reference to the cultural attributes

of the four culture types offered by the CVF, it is proposed that organisational

orientation towards clan and adhocracy cultures would facilitate knowledge sharing,

whereas organisational orientation towards market and hierarchy cultures would

impede knowledge sharing within the context of a PBO.

Hypothesis 1 (H1): Dominant organisational orientation towards clan culture has a positive influence on knowledge sharing.

Hypothesis 2 (H2): Dominant organisational orientation towards adhocracy culture has a positive influence on knowledge sharing.

 

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Hypothesis 3 (H3): Dominant organisational orientation towards market culture

has a negative influence on knowledge sharing.

Hypothesis 4 (H4): Dominant organisational orientation towards hierarchy culture has a negative influence on knowledge sharing.

Figure 1: The Competing Values Framework (Cameron & Quinn, 2006)

Figure 2: Attributes of Clan, Adhocracy, Hierarchy and Market Cultures (Cameron & Quinn, 2006)

 

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2.3 Subgroup Culture as a Moderator

Organisations with strong organisational cultures provide clear and coherent values so

that all of its members are defined by the same behaviours, and are driven towards the

same goals (Boisnier & Chatman, 2002). Strong organisational cultures and high levels

of agreement, however, impose stability and consistency, which are contrary to the

agile nature of PBOs and have been found to inhibit an organisation’s ability to change,

adapt and innovate (Boisnier & Chatman, 2002). Given the technically advanced and

competitive markets within which businesses operate, it would be difficult for modern

organisations to operate with only one stable culture.

Subgroup cultures are small interdependent groups within an organisation that share a

set of norms, values, and beliefs (Carton & Cummings, 2013). Membership in

subgroups may be formed from workgroups, levels of hierarchies, geographical base,

socio-demographic similarities or friendships (Hansen et al., 2005). Through frequent

interactions, subgroup members will form shared mental models that can impact

behaviours relating to communication, learning and knowledge sharing (Wang & Noe,

2010). Due to the smaller composition of subgroups, it is believed that they are more

malleable and can better respond to the agile needs of a PBO (Boisnier & Chatman,

2002).

Subgroup cultures in PBOs are formed because of the dissimilarities in tasks, expertise

and challenges encountered by different project units (Martin & Siehl, 1983). In such

knowledge rich environments, knowledge-based subgroups are formed from project

members who share the same technical language and approach to problem solving

(Carton & Cummings, 2013). Members of the same knowledge base possess similar

mental models that allow them to process or filter knowledge in similar ways (Hansen

et al., 2005). Chen and Huang (2007) explain that apart from accessibility, the value of

knowledge is also determined by its application. Where each knowledge-based

subgroup represents a unique source of knowledge and learning, knowledge acquired

can be applied to increase decision quality, creative outputs, reduce costs of errors and

ultimately enhance organisational performance (Van Knippenberg & Schippers, 2007).

 

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However, evidence for both the positive effects as well as the negative effects of

subgroups on organisational effectiveness was found (Van Knippenberg & Schippers,

2007). In order to sustain competitive advantage, PBOs will need to harness the diverse

knowledge sources within the organisation whilst defusing any potential sources of

conflict arising from its subgroups (Carton & Cumming, 2013). One of the negative

effects of heterogeneous subgroups is the lack of shared mental models that may induce

deviations away from the common norms and values defined by the organisation’s

dominant culture (Carton & Cummings, 2013). This raises questions as to whether and

how subgroup cultures, formed from project units, may influence the existing

relationship between dominant organisational culture and knowledge sharing within the

PBO.

Martin and Siehl (1983) expressed that assumptions and values defined by an

organisation’s dominant culture are shared by the majority of its members, but not

necessarily all of its members. Martin and Siehl (1983) developed three typologies for

the possible relationships between subgroup culture and organisational culture:

enhancing, orthogonal or neutral, and countercultural. Subgroups that enhance the

dominant organisational culture are generally more enthusiastic about the

organisation’s espoused values than other members of their organisation. Subgroups

that are orthogonal will embrace the values and beliefs of the dominant organisational

culture, but also hold a distinctive set of values, beliefs and norms that are unique to

their subgroup members. As these subgroups are neutral, they will not threaten the

cohesiveness of the dominant culture (Martin and Siehl, 1983). It is, however, the

countercultural subgroups that most organisations are concerned with, as they tend to

disagree with the core values of the dominant organisational culture and hold values

that directly conflict with core organisational values (Boisnier & Chatman, 2002).

Following the parent-child metaphor, Wolfgang and Ferracuti (1970 cited in Boisnier

& Chatman, 2002) suggested that a subgroup culture, like a child, would not be entirely

different from its ‘parent’ culture. So although, some subgroup cultures may conflict

with the dominant culture of the organisation, others may not. Hence, it is anticipated

 

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that each corresponding relationship described above may affect project members’

prioritisation and motivation to share knowledge inter and intra their subgroups.

The notable competing values of each quadrant were the main cause for the name:

Competing Values Framework (Cameron & Quinn, 2006). Each continuum on the

vertical and horizontal axes of the CVF highlights opposing core values, namely

flexibility versus stability, internal versus external. These dimensions, therefore,

produce countercultural relationships between subgroup culture and organisational

culture on the diagonal, namely clan versus market, and hierarchy versus adhocracy.

However, adjacent quadrants, which share the same orientations on each axis, although

are negatively correlated, produce neutral relationships between subgroup culture and

organisational culture (Cameron & Quinn, 2006). When both subgroup and

organisational cultures belong to the same quadrant, the relationship between subgroup

and organisational culture is enhancing.

Assuming that the dominant organisational culture is conducive to knowledge-friendly

behaviours, in instances where subgroup cultures are complimentary, it is predicted that

creativity and learning would be enhanced (Wiewiora et al., 2013). However, in

instances where subgroup cultures clash with the organisation’s knowledge-friendly

culture, conflict and miscommunication are expected to flourish (Eskerod & Skriver,

2007). Similarly, it is predicted that knowledge-friendly subgroup cultures can reduce

the negative impact of non-knowledge-friendly organisational cultures on knowledge

sharing. It is therefore, hypothesized that subgroup cultures may either facilitate or

impede the relationship between dominant organisational culture on knowledge

sharing.

Hypothesis 5 (H5): Subgroup culture moderates the relationship between dominant organisational culture on knowledge sharing.

 

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Chapter 3. Research Methodology

This research aims to examine the individual and combined effects of organisational

culture and subgroup cultures on knowledge sharing behaviours within a project-based

organisation.

3.1 Settings

The selected PBO is a marketing agency offering direct response marketing and digital

engagement solutions to large national corporations as well as small to medium

enterprises in the United Kingdom. Due to variations in project scales, the PBO is

divided into two offices with the London office managing longer-term projects of

larger scales, and the Ipswich office managing shorter-term projects of smaller scales.

Projects’ scales range in accordance to budgets of over £2 million for large projects to

£20,000 for smaller projects, and usually last for a maximum of 1-2 years to a

minimum of 3 weeks. Allocation of projects is usually subject to decisions of the

PBO’s senior management team. Project teams may vary from 20 persons for large

projects to 3 persons for small projects. Within the project teams, functional units are

formed where each unit is responsible for individual stages of project cycles.

Following Hobday’s (2000) categorisation of organisational structures, the selected

PBO may be categorised as a ‘lightweight project management structure’ where project

managers operate within a matrix, subordinate to senior functional managers, and do

not have direct control over allocation of resources for their projects. [See Figure 3]

 

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Figure 3: Lightweight Project Management Structure of PBO adapted from Hobday (2000)

3.2 Research Design

Empirical inquiries into the combined effects of organisational culture and subgroup

cultures on knowledge sharing behaviours are extremely limited. Although there has

been some research on the effects of organisational culture on knowledge sharing

behaviours, most investigations were undertaken from a qualitative stance (Lindkvist,

2005; Ajmal & Koskinen, 2008; Wiewiora et al., 2013). There has been much debate

relating to both merits and boundaries of using either qualitative and quantitative

research methods. While qualitative methods adopt a constructivist approach and allow

an in-depth inquiry into the experiences and perceptions of participants studied,

quantitative methods adopt a deductive approach and are able to maximise objectivity,

replicability, and generalizability of findings that are useful for predicting causal effects

(Harwell, 2011). Nonetheless, quantitative methods are also critiqued for offering a

single ‘truth’, independent of human perception, and qualitative methods fall short in

developing generalizable inferences and may be subject to researcher’s personal biases

(Johnson & Onwuegbuzie, 2004).

Triangulation allows confirmation and cross-validation of findings from using both

deductive and constructivist approaches to research (Onwuegbuzie & Leech, 2006).

Harwell (2011) proposes that in a mixed-methods design, weaknesses of either

 

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qualitative or quantitative data can be offset by strengths of the other. In order to

quantify the individual and combined effects of organisational culture and subgroup

cultures on knowledge sharing behaviours, we’d require descriptive and inferential

statistics, which are obtained from quantitative methods (Dewberry, 2004).

Hofstede (1998) reminds that in order to fully comprehend the complex nature of

organisational and subgroup cultures, one would require insight into the minds of

organisational and subgroup members. The case study method was suggested as the

one of the most complementary designs to be aligned with descriptive and exploratory

research designs, as they are both non-directional in nature (Onwuegbuzie & Leech,

2006). A case study design can, therefore, elicit qualitative data regarding research

participants’ perceptual assessments of their organisation’s culture, existing subgroup

cultures and how such perceptions have influenced their knowledge sharing

behaviours.

Hence, this study combined approaches from both quantitative correlational and

qualitative case study designs in order to benefit from the methodological triangulation,

which has the potential to enhance the fidelity of the research design and significance

of research findings (Onwuegbuzie & Leech, 2006).

3.3. Data Collection

The PBO consists of 46 full time employees across both London and Ipswich offices,

in addition to 4 senior managers and their CEO. With the consent of their CEO, all 51

members were invited to participate in this research.

To ensure adequate triangulation, data was collected from multiple sources: 1) online

questionnaire, 2) focus groups and 3) review of the PBO’s corporate website and

documentation. Based on the theoretical framework provided in Chapter 2,

organisational cultural orientation, subgroup cultural orientations and levels of

knowledge sharing were operationalized through the use of an online questionnaire.

Focus group questions were designed to capture data around perceptions of the PBO’s

 

22

organisational culture, perceptions of subgroup cultures, perceived effectiveness of

knowledge sharing processes and types of knowledge shared. The focus groups were

also employed as opportunities for organisational members to propose

recommendations for senior managers’ regarding improvements that could be made to

enhance knowledge sharing within the PBO.

Before launching the questionnaire online, all items were peer reviewed by

postgraduate colleagues at Birkbeck to ensure questions were phrased in a

comprehensible manner. Comments were gathered to improve the final version of the

questionnaire. Likewise, focus group questions were piloted with the first 3 focus

groups before conducting the remaining sessions.

The online questionnaire comprised of 4 sections and all questions were close-ended.

[See Appendix D1] Response settings for all questions were designed as mandatory to

avoid missing cases. The Organisational Culture Assessment Instrument (OCAI),

which was the developed tool based on the CVF by Cameron & Quinn (2006), was

adopted in the first section of the questionnaire for diagnosing the PBO and subgroup

cultures across six key characteristics: Dominant Characteristics, Organisational

Leadership, Management of Employees, Organisational Glue, Strategic Emphasis and

Criteria of Success. Descriptions for each characteristic are provided in Figure 4.

Figure 4: Descriptions of key characteristics on OCAI (Wiewiora et al., 2013, p.1166)

 

23

The full and adapted versions of the OCAI have been used in more than 1000

organisations internationally in studies relating to organisational change, knowledge

management and organisational effectiveness (Suppiah & Sandhu, 2011). The

fundamental principle of the CVF is that as organisations evolve in response to

challenges and changes in their operating environment, they tend to develop a

dominant cultural orientation, but are seldom categorized by any single cultural type

(Cameron and Quinn, 2006). It is for this reason, the CVF and OCAI was chosen as a

preferred tool for assessing the dominant cultural orientations of the PBO studied.

Contrarily, only a single study was found to have used the OCAI for diagnosing

subgroup cultures in predicting agreement patterns within a department of defence at a

military university (Paparone, 2003). Results from Paparone’s study indicated that the

use of OCAI in diagnosing subgroup culture, when cross-validated with qualitative

data, was effective for identifying existence of subgroups. A decision was made to

undertake the same approach in this study and an abridged version of the OCAI was

adopted for diagnosing the subgroup cultures within the PBO. The results of this study

are expected to test the generalizability of Paparone’s methodology in using the OCAI

for diagnosing subgroup cultures in other contexts.

The second section of the questionnaire incorporated sociometric questions to test the

asymmetry of knowledge sharing between project units. Tsai (2002) asserts that one

unit sharing its knowledge with another unit does not mean that knowledge sharing is

reciprocal or symmetrical. Respondents were asked to select any or all units within the

PBO from which they had received new knowledge or technical expertise. To validate

whether knowledge sharing was asymmetrical, an opposite question asked respondents

to select any or all units to which they had provided new knowledge or technical

expertise (Hansen, 1999).

The third section of the questionnaire was designed to analyse levels of knowledge

sharing across 12 items [See Figure 5]. Items developed were based on investigations

of knowledge sharing practices across organisational units conducted by Gamble and

 

24

Blackwell (2001), Tsai (2002), and Mueller (2014). The last section of the

questionnaire collected demographic information from respondents.

Figure 5: Item topics and simplified version of question items with referenced authors

In addition to the online questionnaire, 13 focus groups were held to provide a richer

insight into the embedded knowledge sharing behaviours, the quality of knowledge

shared, perceptions of organisational culture and subgroup cultures. Kitzinger (1995)

adds that focus groups are useful for exploring individual knowledge and experiences

by tapping into different forms of interpersonal communication, which can highlight

subcultural values and norms.

Pre-prepared questions were used to guide discussions, when necessary, probing

questions were asked for clarification. [See Appendix D2] Questions developed were

based around findings from the online questionnaire and on relevant literature

investigating effects of project units’ perceptions of organisational culture and

subgroup culture on knowledge sharing, categorisation of knowledge, and barriers and

enablers of knowledge sharing (Sackmann, 1992; Lilleoere & Hansen, 2011; Evans,

2012; Mueller, 2012; Wiewiora et al., 2013;) [See Figure 6] Subgroup cultures

identified from the online questionnaire were used to guide groupings of focus group

participants. All focus group sessions, with permission from the PBO, were audio

recorded and transcribed.

 

25

Lastly, review of the PBO’s corporate website and marketing materials provided a

better understanding of their business nature, public value statements and

organisational structure.

Figure 6: Focus group item topics, overview of question items and expected themes with

referenced authors

 

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3.4 Data Analysis

A cross-sectional mixed-methods design was employed as the individual and combined

effects of organisational culture and subgroup cultures on knowledge sharing was only

measured once within the selected PBO (Schwab, 2011). Quantitative data2 collected

from the online questionnaire was triangulated with qualitative data obtained from

focus groups and review of the PBO’s corporate website and marketing materials.

Thereafter, findings from triangulation was compared to existing literature taking into

account both conflicting and convergent perspectives when analysing the

generalizability of this research.

To ensure that data collected from the online questionnaire was free from random

errors, the Cronbach’s alpha was used to calculate the reliability of the question items’

measurement scales (Dewberry, 2004). Schwab (2011) advises that an alpha coefficient

of 0.70 is usually taken as the minimum level accepted. However, Suppiah and Sandhu

(2011) suggest that it is possible to obtain a coefficient value of below 0.70 when

measuring diverse psychological constructs such as perceptual assessments of

organisational culture or subgroup cultures.

For the online questionnaire, the OCAI consisted of 24 questions and uses an ipsative

rating scale in which respondents were asked to divide 100 points amongst 4 questions

corresponding to each CVF quadrant for all six key characteristics (Cameron and

Quinn, 2006). The total points collected from the key characteristics were averaged

according to each quadrant for each respondent. The aggregated mean of the quadrant

results from all respondents were graphed on the CVF to visualise the cultural

orientations of the organisation.

For the purposes of this study, subgroup culture was operationally defined as

identifiable patterns observed on the CVF based on responses obtained from

questionnaire items relating to subgroup culture. Following Hofstede’s (1998)

empirical approach for identifying subcultures, a Hierarchical Cluster Analysis using                                                                                                                2 All qualitative data were computed and analyzed using the Statistical Package for Social Sciences (SPSS) version 22.

 

27

Ward's method was used to identify subgroupings based on similarities of responses

relating to subgroup culture. Demographic data was also included in the cluster

analysis to explore whether any subgroupings were formed based on membership

criterion suggested by Hansen et al. (2005). Squared Euclidean Distance was applied as

the similarity measure to determine the optimum number of subgroups within the PBO

(Dewberry, 2004). Thereafter, a Chi-square test was conducted to examine which

membership variables were statistically significant against the formed clusters. This

method differs from the discriminant analysis approach taken by Paparone (2003),

which presumes prior knowledge of membership for subgroup formation.

Responses from sociometric questions were crosstabulated to identify whether

knowledge-sharing relationships were asymmetrical. Descriptive statistics from

sociometric responses also revealed knowledge sharing patterns within the PBO.

Levels of knowledge sharing were measured using a Likert 5-point scale. Items for

‘modes of communication’ were accorded a maximum of 4 points to a minimum of 0

points depending of frequency of use. Items for positive knowledge sharing behaviours

were accorded a maximum of 4 points to a minimum of 0 points depending on levels of

agreement. The item for measuring ‘time pressure’ was regarded as a reversed question

and, hence, scoring for this item was inverted. The aggregated mean of these items was

used as a single value scale representing the levels of knowledge sharing.

Validity refers to “the truth of a research conclusion or inference” (Schwab, 2011,

p.14). The Pearson product-moment correlation coefficient was used to examine the

strength and direction of the hypothesised association between organisational culture

and levels of knowledge sharing (i.e. H1 – H4). Statistical significance for each

correlation was also checked. The hypothesised moderation of subgroup cultures on

organisational culture and knowledge sharing (i.e. H5) was tested using the standard

multiple regression technique. In standard multiple regression, a dependent variable is

related to two or more independent variables (Schwab, 2011). Cultural orientations of

subgroups, as identified using Ward’s method, were used as a categorical moderator

indicating subgroup culture. Moderation effect was produced by multiplying the

predictor variable (i.e. organisational culture) and the moderator variable (i.e. subgroup

 

28

culture). Significance was checked for any variance the moderated effect had on the

dependent variable (i.e. levels of knowledge sharing).

Systematic analysis of qualitative data collected from focus groups was conducted in

two stages: during and after focus groups. Pre-prepared questions for guiding group

discussions were adapted into a standardised theme-based template for capturing

responses during focus groups in accordance to expected themes [ref. Figure 6]. Other

responses and emergent themes, which did not fall within the pre-designed template,

were captured as ‘Additional Notes’. Content analysis from field notes and transcripts

of audio recordings were conducted after each focus group session, within the same

day. Any key themes across and within groups were recorded. Consistency was

observed for words used, frequency of comments, degree of agreement, specificity, and

intensity of feelings towards a particular topic (Krueger and Casey, 2002). Special

attention was also accorded for evaluating the impact of group dynamics between focus

group participants (Kitzinger, 1995).

 

29

Chapter 4. Results of Analysis

4.1 Demographic Information

Response rate for the online questionnaire was 75%. However, 3 cases were deleted

due to response errors, hence, a total of 36 cases were computed for data analysis.

Figure 7 exhibits the demographic characteristics of respondents. Responses from the

Ipswich office were double those of the London office, which was reflective of the

actual size variance between the two locations, with Ipswich employing more than 70%

of the PBOs full-time employees. Overall, males outnumbered females by

approximately 2:1, which again was reflective of the gender disproportions within the

PBO. Almost 90% of respondents were below 39 years of age and almost 45% had

been working for less than a year in the PBO. This reflects the high turnover rates

within the organization, which was subsequently confirmed by senior managers during

the focus groups.

Figure 7: Demography of online questionnaire respondents

 

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4.2 Reliability

The reliability of all major factors was measured. Organisational culture items of the

OCAI were grouped according to CVF quadrants but generated alpha coefficients

below minimum level acceptable: Clan Culture (α = 0.4), Adhocracy Culture (α = 0.6),

Market Culture (α = 0.6), Hierarchy Culture (α = 0.6). These findings were similar to

reliability values found by Suppiah and Sandhu (2011), who confirmed that coefficient

values of below 0.70 can be realistically expected for scales measuring diverse

psychological constructs such as perceptual assessments of organisational culture may

obtain coefficient values [i.e. acceptable indicators for Adhocracy culture (α = 0.6) and

Hierarchy culture (α = 0.6)].

On the contrary, an abridged version of the OCAI was used to measure subgroup

cultures and generated a high alpha coefficient of 0.8. Knowledge sharing items

generated an acceptable alpha coefficient of 0.7. [See Figure 8; Appendix D3]

Figure 8: Descriptive Statistics: Inter-item correlations for Organisational Culture, Subgroup Culture

and Knowledge Sharing

4.3 Organisational Culture

The mean scores of Clan, Adhocracy, Market and Hierarchy cultures were graphed on

the CVF [see Figure 9]. The PBO’s organisational cultural orientation was analysed

across the vertical and horizontal axes. Higher weightings of approximately 11% and

46% were respectively attributed to external/ differentiation and stability/control

dimensions. Analysis of quadrant values indicated higher weightings were attributed to

Market and Hierarchy dimensions as compared with Clan and Adhocracy dimensions.

 

31

Combining values on the vertical and horizontal axes with quadrant values revealed the

dominant Market orientation of the PBO’s organisational culture.

Figure 9: Organisational Culture of PBO

4.4 Subgroup Cultures

Items of subgroup culture and demography were subject to a Hierarchical Cluster

Analysis using Ward’s Method (Hofstede, 1998). The process of combination is

provided on a dendrogram [see Figure 10]. A single solution of 2 clusters was

identified with 27 cases falling under the first cluster and 9 cases under the second

cluster [see Figure 11]. Therefore, questionnaire respondents are separated into 2 main

subgroups within the PBO.

The Chi-square test was conducted to examine which membership variables were

statistically significant against the formed clusters (Dewberry, 2004). Results revealed

that difference between demographic items (i.e. age, function & tenure) were

statistically significant against the formed clusters [see Figure 12]. However, results

 

32

also revealed that differences between all subgroup culture items and 2 demographic

items (i.e. gender & location) were not statistically significant. Hence, variances of

functions, age and tenure separated the 2 subgroups within the PBO, whilst

convergence of responses on subgroup culture, gender and location were identified as

the basis for subgroup membership and development of shared mental models (Wang

& Noe, 2010). Descriptive statistics also revealed the composition of cluster 1 with a

majority of cases belonging to Clan cultures (78%) that are predominantly male (74%),

and are based in Ipswich (63%). Even though cluster 2 had fewer cases, its composition

was similar to that of cluster 1. [See Figure 13]

Figure 10: Dendrogram of Subgroup Cultures

 

33

Figure 11: Distribution of cases by clusters

Figure 12: Results of Chi-Square Test: Ward’s Method (Clusters) x membership variables

Figure 13: Descriptive Statistics: Composition of Clusters by Subgroup Culture, Gender and Location

 

34

4.5 Knowledge Sharing

Crosstabulation of sociometric responses confirmed Tsai’s (2002) assertion relating to

asymmetrical knowledge-sharing relationships across all project units [see Figure 14].

Validated responses for knowledge provided and knowledge received revealed that

majority of knowledge sharing activities were accounted by the senior management

(34%) and design & production teams (29%). [See Figure 15]

Figure 14: Crosstabulation: Knowledge sharing relationships

Figure 15: Crosstabulation: Validated responses for ‘knowledge provided’ and ‘knowledge received’

Levels of knowledge sharing were calculated by aggregating the means of 12

knowledge-sharing items into a single continuous variable. Frequency statistics of

central tendency and dispersion were calculated, and levels of knowledge sharing

ranged from a lowest score of 16 to a highest score of 37 [see Figure 16]. Percentiles

revealed low (below 33.33%), medium (between 33.33 – 66.66%) and high levels

(above 66.66%) of knowledge sharing. A positive skewed distribution revealed low to

medium levels of knowledge sharing across the PBO [see Figure 17].

 

35

Aggregate scores (n) of n ≤ 22.22 were regarded as low levels of knowledge sharing,

those 22.22 < n ≤ 27.11 were regarded as medium levels of knowledge sharing, and n >

27.11 were regarded as high levels of knowledge sharing. Descriptive statistics further

revealed low to medium levels of knowledge sharing in cluster 1 and medium to high

levels of knowledge sharing in cluster 2 [see figure 18].

Figure 16: Frequency Statistics for Levels of Knowledge Sharing

Figure 17: Histogram of KS Aggregate Scores X Frequency, positive skew

 

36

Figure 18: Descriptive Statistics: Composition of Clusters by Levels of Knowledge Sharing

4.6 Validity – Testing Hypotheses

Bivariate correlations analyses were conducted for each of the CVF organisational

culture types and levels of knowledge sharing [see Figure 19]. Results revealed a

significant positive correlation of medium-sized effects was found between Clan-type

organisational culture and knowledge sharing (r = 0.3, p = 0.04), and that a significant

negative correlation of medium-sized effects was also found between Hierarchy-type

organisational cultures and knowledge sharing (r = -0.3, p = 0.04). However, results

indicated that both positive and negative non-significant correlations of small-sized

effects were found between Adhocracy and Market-type organisational cultures and

knowledge sharing. These respective relationships yielded r = 0.14, p = 0.20 and r = -

0.1, p = 0.30. Therefore, hypotheses H2 and H3 were rejected.

With reference to OCAI scores in section 4.3, there was a relative insignificant

weighting of Adhocracy-type culture (102.64). Hence, its was expected that its

corresponding hypothesis (H2) was to be rejected due its inability to effectively

measure for effects of adhocracy attributes on knowledge sharing. Conversely, while

OCAI score for Clan-type organisational culture was also relatively low, its presence

was strong amongst clusters found in section 4.4, which may have accounted for its

significant effect on knowledge sharing inter-intra subgroups. This inference is to be

cross-validated with subsequent analysis of focus group findings. Also, OCAI scores

indicated significant dominance of a Market-type culture (235.28) while its

corresponding hypothesis (H3) was rejected.

 

37

According to Field (2009), rejecting an alternative hypothesis does not mean that the

null hypothesis is true (i.e. where there is no effect in the population). Therefore,

although non-significant results are generally not interpreted, the rejected hypotheses

were kept in the research model so that implications of both accepted and rejected

hypotheses may be discussed within the context of the PBO studied in Chapter 5.

Figure 19: Correlation Matrix: KS Aggregate (Levels of knowledge sharing) and

CVF Organisational Culture Types

Four moderator*predictor variables were created by multiplying four predictor

variables (i.e. CVF organisational cultures) with the moderator variable (i.e. subgroup

culture). A standard multiple regression analysis was carried out using knowledge

sharing as the dependent variable, and CVF organisational cultures and

moderator*predictors as the predictor variables [see Figure 20]. Dewberry (2004)

advises that correlation coefficients greater than 0.7 are usually indicative of high

associations. The coefficients from the analysis reveal that both negative and positive

correlations between levels of knowledge sharing and all predictor variables are weak.

However, correlations between predictor variables: market*subgroup culture (r = -0.35,

p = 0.02) and hierarchy*subgroup culture (r = -0.44, p = 0.004) to knowledge sharing

 

38

were statistically significant. This may be due to the high organisational cultural

orientations of Market and Hierarchy type organisational orientations on the CVF

against a high orientation of Clan-type subgroup culture producing counter-cultural

effects as suggested by Boisnier and Chatman (2002). However, this interpretation

again would be cross-validated with subsequent analysis of focus group findings.

The multiple correlations coefficient (R) and the square of the multiple correlations

coefficient (R2) were calculated but revealed that only 36% of the variation in levels of

knowledge sharing were explained with the predictor variables [See Figure 21]. Beta

values were calculated to indicate which predictor variables uniquely predicts levels of

knowledge sharing in the PBO. The beta values revealed that the best unique predictor

of levels of knowledge sharing is the combined effect of Clan-type subgroup culture

and Hierarchy-type organisational culture (highest beta value of 2.7), albeit not

statistically significant against other predictor variables [see Figure 22]. With reference

to literature reviewed in section 2.3, these two cultural orientations, when viewed on

the CVF, are expected to be negatively correlated. Nonetheless, with a statistically

non-significant ANOVA (i.e. Analysis of Variance) score, hypothesis H5 must be

rejected due to its inability to test for all three of the expected moderating relationships:

enhancing, orthogonal and counter-cultural [see Figure 23]. Again, the rejected

hypothesis was kept in the research model so that implications may be discussed within

the context of the PBO.

 

39

Figure 20: Correlation Matrix: KS Aggregate (Levels of knowledge sharing), CVF Organisational

Culture Types, and Product of CVF Organisational Culture Types*Subgroups

 

40

Figure 21: Model Summary: Multiple Regression Coefficient (R) and the square of the multiple

correlations coefficient (R2)

Figure 22: Coefficients, Beta values, t-test (t) and significance figures (Sig.)

Figure 23: Analysis of Variance (ANOVA)

 

41

4.7 Analysing Focus Groups

A total of 13 focus groups were held across both London and Ipswich offices, and

demographic information of participants is displayed in figure 24. Due to logistical

reasons, it was challenging to arrange group sessions based purely on the criteria of

subgroup membership as identified in section 4.4. An agreement was reached to

arrange respondents by location and function, and when possible, by gender.

Figure 24: Demography of focus group participants

Each focus group was analysed separately to identify whether participants’ responses

fell under expected themes or emergent themes. With reference to previous literature

(e.g. Sackmann, 1992; Lilleoere & Hansen, 2011; Evans, 2012; Mueller, 2012;

Wiewiora et al., 2013), all data were condensed into expected themes. A thematic table

for each question was built and all responses were coded. The coded responses were

constructed on a bar graph to indicate the frequency of comments and degree of

agreement [see Appendix D4]. As participants ratios were almost 2:1 for both location

and gender, and are expected to produce effects for sampling bias, responses were

coded only by functions. An example of the bar graph is shown in Figure 25. Some

themes were visibly more prevalent and were marked as major themes for each

question across all groups.

From part 1 of the focus group questions (i.e. perceptions of organisational culture),

responses relating to divisions by functions and locations, emphasis on efficiency,

competition and hierarchy were most frequent [see Figure 26].

 

42

Figure 25: Bar graph example of themes derived from focus group questions 2.1 & 2.2

Figure 26: Respondent remarks on Organisational Culture

 

43

Part 2 of the focus group questions examined participants’ perceptions of subgroup

culture and revealed emphasis on collaboration, support and openness. Response by

participants indicated that underlying assumption relating to both divisions by location

and functions were perceived as causes for subgroup formation [see Figure 27].

Figure 27: Respondent remarks on Subgroup Culture

Part 3 of the focus group questions attempted to categorise types of knowledge shared

within the PBO. Naturally, each group’s specialisation within the project cycle

influenced the types of knowledge shared with other team members. Generally,

dictionary knowledge relating to project timelines, client information and work

specifications was most widely shared across teams. Other knowledge types included

technical know-how’s, instructions from senior managers, recommendations for clients

and general explanations for technical queries.

Questions related to barriers of knowledge sharing generated frequent responses

regarding the organization’s culture, organisational processes and challenges in

communication. Other comments included: low morale, non user-friendly technology,

and organisational push for productivity and timely output. Explanations regarding

cultural barriers to knowledge sharing reiterated and expanded on remarks in part 1.

Repeated references were made regarding the perceived lack of trust from senior

managers, internal competition amongst the 2 office locations, lack of learning

orientation as well as the lack of receptiveness to change. Remarks relating to process

barriers included the lack of efficiency, lack of value, inconsistent practice and non-

consultative approaches to decision making [see Figure 28]. Contrasting concepts were

 

44

identified in the last section of the focus group as enablers of knowledge sharing.

Themes identified were largely related to cultural change, improved processes and

facilitated communication. Additional feedback was captured relating to exemplary

leadership, greater job satisfaction, and user-friendly technology. [See Figure 29]

Some overlaps were identified across themes and participant responses, which

illustrated the intricacy between individual perceptions of organisational culture,

subgroup culture and knowledge sharing behaviours. From observation, some group

participants (such as account managers and digital technicians) were generally more

vocal than others, and in most cases lead to a higher degree of agreement amongst

members of the same group. From a researcher’s point of view, such incidents were

beneficial for enhancing input from more inhibited participants, as well as facilitated

conversations around presumably sensitive comments such as dislike of particular

senior managers, unequal pay and for making specific recounts of unpleasant

experiences at work.

 

45

Figure 28: Respondent remarks on barriers of knowledge sharing

 

46

Figure 29: Respondent remarks on enablers of knowledge sharing

 

47

Chapter 5. Discussion

Due to the complexity of interactions between knowledge workers and across project

units, the phenomenon of knowledge sharing in PBOs is not easily understood (Ajmal

& Koskinen, 2008). The purpose of this study aims to examine the individual and

combined effects of organisational culture and subgroup cultures on knowledge sharing

behaviours within a selected PBO in the United Kingdom. Approaches from both

quantitative correlational and qualitative case study designs were combined in this

cross-sectional mixed methods research to explore and analyze how perceptions of

organisational and subgroup cultural attributes had affected knowledge sharing within

the PBO studied.

Johnson and Onwuegbuzie (2004) proposes that mixed methods research is an

inclusive and pluralistic form of research; which refrains a researcher from

methodological bias by legitimizing the use of both confirmatory and exploratory

approaches to answering a research question. Although, through statistical analysis, not

all hypotheses were accepted, a decision was made to retain both accepted and rejected

hypotheses so that ontological and epistemological implications of their respective and

interrelated effects may be discussed within the unique context of the PBO [see Figure

30]. In addition, by leveraging the benefits of triangulation, this chapter intends to

provide a holistic view of the intricate relationships upon which the research question

was found.

Figure 30: Summary of analysis of hypotheses

 

48

Overall, cross-validation of findings from qualitative and quantitative analysis

indicated that in the context of the PBO studied, different organisational cultural

orientations can have different effects on project knowledge sharing behaviours. This

finding is consistent with previous research conducted in Hong Kong, Australia and

Germany (Mueller, 2012; Wiewiora et al., 2013). This chapter intends to critically

evaluate the findings of this study with reference to the theoretical framework

developed from the literature review in Chapter 2. Limitations relating to selection of

population, adaptation of measurement scales, and research design as well as

opportunities identified for future research will also be discussed in the concluding

chapter.

5.1 Individual Effects of Organisational Culture on Knowledge Sharing

Cross-validation of statistical and non-statistical data have identified high

organisational orientations of Market-type and Hierarchy-type cultures with a

particularly high emphasis on stability and control within the PBO. Responses from

focus groups revealed that perceived competition between the two office locations and

amongst senior managers, as well as high emphasis on productivity and deadlines, had

in fact contributed to respondents’ reluctance to share any knowledge relating to project

shortcomings or “bad news”. De Long and Fahey (2000) cautions against market-type

cultures in knowledge rich organizations as it emphases power dynamics and

competition that leads to knowledge hoarding behaviours. However, the causal effects

of the PBO’s hierarchical organisational structure, underlined by rigid organisational

processes, were observed and validated3 to have an even more significant negative

impact, as compared to effects of Market-type cultures, on knowledge sharing within

the PBO.

Evans (2012) states that when people are culturally inhibited from interacting across

departments and functions, they avoid sharing data and information outside of their

silos (Evans, 2012). Respondents commented that knowledge sharing across project                                                                                                                3 In research, validity should be interpreted in terms of verisimilitude (i.e. appearance of truth), rather than absolute truth (Schwab, 2011).

 

49

units was not encouraged by senior managers. They were also reluctant to reach for

support from other units, which were managed by different functional managers, as it

would be perceived as “stepping on someone’s shoes”. This was validated by a

statistically significant negative correlation between Hierarchy-type organisational

cultures and knowledge sharing (H4).

Hobday (2000) explained that in order for PBOs to remain agile and responsive to

market changes, its internal structures must be flexible with systems that encourage

individuals to exercise autonomy and decision-making powers regarding their work.

Cameron and Quinn (2006) also explained that Adhocracy-type culture is generally

adopted by agile organisations and focuses on risk-taking, entrepreneurship and

creativity. However, in the context of the PBO studied, respondents reported that they

were generally assigned work by senior managers, and without any consultative

process in place, they were unable to exercise any decision-making powers or offer

suggestions for improvements at work.

From the OCAI scores, the PBO studied was not of an Adhocracy-type culture; hence

the original research model was unable to measure for effects of adhocracy attributes

on knowledge sharing. Remarks from focus groups reflected perceptions of the PBO’s

lack of interest to change or generate innovative work, often leading to low morale

amongst its members and induced a high turnover rate within the organization. Risk

avoidance was also recognized as a potential barrier of knowledge sharing where

employees were less inclined to speak up during meetings fearing that due to a lack of

clarity on project scope and status, their reputation or performance reviews may be at

risked. Several remarks were made with regards to the need for clearer project briefs or

documentation processes to reduce miscommunication cross units.

Lindkvist (2005) suggested that silo mentalities are manifested due to inherent project

cultures where organization of work by projects inhibits knowledge sharing amongst

project teams. However, the findings of this research supports an alternative view by

Evan’s (2012) that formal hierarchical structures, in fact, had a greater negative impact

on the effectiveness of knowledge sharing between different project units. De Long &

 

50

Fahey (2000) reminded that knowledge sharing within an organization occurs

horizontally and vertically. Findings of this study confirmed the asymmetrical

knowledge sharing relationships proposed by Tsai (2002), and found that senior

managers had accounted for the majority of knowledge sharing activities within the

PBO. Remarks from focus groups revealed that one of the underlying assumptions of

the PBO’s hierarchical culture was due to strict managerial control and top-down

communication.

Hierarchical culture within the PBO was also found to reinforce status hierarchies

across functions and locations. One respondent’s feedback revealed, “The Ipswich

office is sometimes looked down because they have smaller accounts [as compared to

the London office]”. Another respondent expressed that the account management team

was perceived to be more valued than other teams as they held key functions for

business development and income generation, “it’s totally unfair that they get to ask

for overtime pay and we don’t...besides, they already get reimbursed for food and

travel when they head out for meetings”. Clustering analysis also confirmed the

statistical differences amongst subgroups based on functions. According to De Long

(1997), perceptions that functions are valued differently or unequally reinforce silo

mentalities and undermine cross-functional knowledge sharing. In such circumstance,

individual or teams will form subgroups that seek to defend the same knowledge bases.

5.2 Combined Effects of Organisational and Subgroup Culture on Knowledge Sharing

Within the PBO studied, statistical analysis accepts that Clan-type organisational

culture is conducive to positive knowledge sharing outcomes (H1). However, OCAI

scores on organisational culture indicated a low orientation in this CVF quadrant.

Clan-type orientation, nonetheless, was found to have a high presence within subgroups

as identified by both cluster analysis and focus group data. Cameron and Quinn (2006)

confirmed that when assessing an organization’s culture, it’s important to consider the

aggregated effects of subgroups, which can provide an approximation of the dynamic

 

51

relationships within the organization. Focus groups claimed that emphasis on

collaboration and support within functional units was conducive to open

communication and positive knowledge sharing behaviours within their own units.

Response from focus groups also confirmed the criticality of trust and employee

involvement, which also noted by Wang and Noe (2010), as key enablers of knowledge

sharing within organisations.

Nevertheless, strong organisational cultures, particularly strong market-type and

hierarchical organisational cultures as identified with the PBO studied, impose internal

competition, stability and resistance to change (Boisnier and Chatman, 2002). As

observed on the CVF graph [ref.: Figure 9], the PBO is highly oriented on

stability/control dimensions on the vertical axis. Where cultural differences can be a

source of creativity and learning, or a source of conflict and miscommunication, in the

case of this PBO, cultural difference between a strong market-type and hierarchical

organisational cultures against a highly Clan-oriented subgroup culture had been

observed to produce countercultural effects (Wiewiora et al., 2013; Boisnier &

Chatman, 2002). So, although, members were effectively sharing knowledge within

their own units, they were ineffective sharing knowledge across units.

From statistical analysis, significant negative correlations between Market-type and

Hierarchy-type organizations against Clan-oriented subgroup culture correspond with

this interpretation. Focus group remarks also indicated that divisions by function and

location were main causes for the lack of cross-functional and cross-location

collaboration, socialisation and organisational learning. References to competition were

also made regarding challenges within the account management team, initiated by

senior managers with the purpose of driving higher goal achievements, but were

resisted by members who felt ‘embarrassed’ and ‘awkward’ to compete against their

team members.

Without dominant presence of Clan-type or Adhocracy-type organisational cultures

within the PBO, our original research model was unable to measure for the full

moderation effects of enhancing, orthogonal and counter-cultural organisational-

 

52

subgroup relationships on levels of knowledge sharing. Hence, based on deductions

from hypotheses 1 and 4, and in conjunction with our constructivist approach, this

research found that dominance of hierarchy-type organisational culture negatively

impacts knowledge sharing across project units, while aggregation of clan-type

subgroup culture within the PBO positively impacts knowledge sharing within the

boundaries of individual project units. Respective impacts were also justified by the

identified variations in levels of knowledge sharing from our statistical analysis.

 

53

Chapter 6. Limitations and Opportunities

The current research design neglected to consider challenges in obtaining significant

weightings in all four of CVF’s orientations from a single organization. Opportunities

for future research should consider adopting a between-cases design so varying impacts

of different cultural orientations on levels of knowledge sharing and pattern of

knowledge sharing behaviours may be measured and compared across cases. Also,

while the selected context was not ideal for investigating the hypothesized endogenous

effects of organisational culture and subgroup culture on knowledge sharing, it

produces opportunities for investigating exogenous effects such as employees’

personalities, where levels of confidence and sociability may predict varying levels of

knowledge sharing, even in absence of knowledge-friendly organisational cultures.

Other limitations were identified relating to the low reliability coefficients of the OCAI

instrument. Limitations with this measurement’s scale were also reported during focus

group discussions where several respondents provided feedback regarding difficulties

experienced in completing the OCAI component of the online questionnaire. The

OCAI uses an ipsative rating scale, which requires respondents to divide 100 points

amongst 4 questions corresponding to the CVF quadrants (Cameron and Quinn, 2006).

3 cases were subsequently excluded for data analysis due to miscalculations of points

for some questions. However, an abridge version of the OCAI made used of a nominal

scale for measuring subgroup cultures, and generated a high Cronbach’s alpha of 0.8.

Hence, future researchers may consider adopting a similar scale or redesigning the

point allocation system to facilitate ease of calculations for respondents using the

OCAI.

Other feedbacks regarding the OCAI included comments on wording ambiguities,

which made some items difficult to understand, and possibly led to unintended

variances in the reliability analysis. Schwab (2011) advises that it’s often dangerous to

assume respondents will share the researcher’s frame of reference, such as

understanding intentions of the underlying competing values of the OCAI instrument.

Schein (2010) also cautions against the use of survey instruments, such as OCAI, as

 

54

such measurement methods tend to reduce the complexities of the cultural

phenomenon.

Although the use of a mixed-methods approach provided insightful findings through

corroboration of different data types, mixed-methods inquiries require more time,

resources, and effort to effectively organize and implement (Johnson & Onwuegbuzie,

2004). The qualitative analysis of this study was limited to perceptions of project unit

members, rather than senior managers, because of their practical responsibilities within

the project cycle where knowledge sharing inter-intra project units would be most

affected. Contrasting responses collected from between senior managers and team

members during focus groups were valuable for providing a holistic view of the PBO’s

cultural manifestations, knowledge sharing behaviours and rationale for its

organisational structure. Nonetheless, a limitation regarding the use of mixed-methods

relates to the huge amount of data collected, which although are interesting and useful

for providing enriched understandings, full discussions all data would far exceed the

scope of this dissertation report.

 

55

Chapter 7. Conclusion and Recommendations

The complexity of project-based organisations has provided a unique context for

knowledge sharing. This research has examined the individual and combined effects of

organisational culture and subgroup cultures on knowledge sharing behaviours within a

selected project-based organization in the United Kingdom. This research conforms to

the theoretical framework of Cameron and Quinn (2006) whereby organizations are

seldom categorized by any single cultural type. By using the Competing Values

Framework, this study has found that, within the project–based context studied,

different organisational and subgroup cultural orientations have had different effects on

knowledge sharing behaviours. Specifically, through the Organisational Culture

Assessment Instrument, dominance of hierarchy-type organisational culture was found

to impede knowledge sharing across project units, while clan-type subgroup culture

had facilitated knowledge sharing within individual project units.

This research validates the methodological approach of Paparone (2003) whereby the

Organisational Culture Assessment Instrument may be applied for diagnosing cultural

orientation across organisational levels as well as subgroup levels, and within different

contexts. Numerous researchers such as Lindkvist (2005), Mueller (2012) and

Wiewiora et al. (2013) have studied and established the respective effects of

organisational culture and subgroup culture on knowledge sharing behaviours.

However, this research provides a new paradigm and empirical model for studying

knowledge sharing behaviour by integrating the effects of both organisational culture

and subgroup cultures in order to provide a deeper understanding into the dynamic and

multi-level effects of culture within organisations. The discussions in the previous

chapter also points to the criticality of contextualisation to ensure that inferences made

about the population studied are correct and that any exogenous factors arising from

contexts studied should be controlled within the research design.

The benefits of effective knowledge sharing and organisational learning such as

productivity, problem solving capabilities and employee satisfaction were already

discussed in the early sections of this report. Although some limitations have been

 

56

identified for our research model, overall the results of this study indicates that

diagnosis of organisational and subgroup cultures, together with an enriched analysis of

project units’ embedded knowledge sharing behaviours, can inform organisational

efforts for enabling knowledge sharing and enhancing organisational effectiveness.

The challenge with knowledge sharing within project-based organisations, however,

lies in their ability to harness the wealth of tacit knowledge from their knowledge

workers and making such knowledge explicit and accessible by others within the

organisation. As reviewed in Chapter 2, Davenport and Prusak (1998) proposed two

dimensions for ensuring effective knowledge sharing, specifically the process via

which knowledge is shared and the quality of knowledge shared. Nonaka (1991) also

expressed that successful Knowledge-Creating Companies are not only effective in

their abilities to generate new knowledge, but in their effective management of

knowledge processes to ensure that valuable knowledge captured from individual or

sub-levels are leveraged at the organisational level.

As observed from the findings of this research, culture defines the structures and

processes by which knowledge is utilised and shared across the PBO. Culture also

shapes project members’ perceptions relating to value of knowledge and

approachability of knowledge sources (De Long & Fahey, 2000). Therefore, upon

recognising the critical role of culture for predicting knowledge sharing behaviours, we

may now negotiate culture shifts and for putting in place the relevant structures to

facilitate knowledge sharing and organisational learning.

3 key recommendations are offered for senior managers at the PBO:

First, efforts for cultural shift within the PBO should be dispensed towards cultivating

an organic environment within which each knowledge worker within the organization

are able to served as trusted advisors and be acknowledged as sources for

organisational learning. Socialisation of knowledge workers will require a supportive

culture that emphases trust, open communication, and commitment towards

organisational goals through teamwork and empowerment. Such cultural shifts are

 

57

necessary for redefining the existing negative perceptual assessments of existing

members towards the organization, so that positive basic underlying assumptions

regarding constructive knowledge sharing practices and orientation for continuous

improvement may be imparted to new members of the PBO (Schein, 1992). Exemplary

leadership should also emphases on the creation of a shared vision to increase

organisational members’ understanding of organisational objectives and ties to one

another so that they may break away from existing mental models of alienation and

divisions by location or function.

Although the captured responses from the PBO’s members provide conceptual

directions for initiating culture change, as De Long (1997) rightly posits, initiatives for

cultural change are likely to be incremental. Hence, cultivation of a knowledge-

friendly culture will require on-going efforts and commitment of senior managers and

all of its members as key change agents.

Second, captured responses from focus groups relating to procedural barriers for

knowledge sharing should be reviewed. Senior managements’ recognition and reaction

to feedback offered by organisational members demonstrates management’s visible

commitment in breaking away from existing ways of working towards developing a

more collaborative and consultative process. From a social exchange perspective,

individuals are generally reluctant to alter their behaviours without some degree of

personal gain in return. De Long (1997) points out that by rewarding the right

knowledge sharing behaviours, organizations can improve the motivation for

employees to exhibit those behaviours. As observed from the findings of this research,

the lack of recognition and reward for project members’ contributions towards project

successes was one of the most cited barriers to effective knowledge sharing. Where

perceptions of unequal rewards reinforced status hierarchies and silo mentalities,

procedural review should ensure that reward systems are transparent and consistent

across all functions and locations.

In addition, integration and collaboration activities should be facilitated by collective

decision-making and accessibility through open systems of communication and

 

58

effective use of technology. Resource constraints such as money and time are often

perceived to be challenges related to implementation of change initiatives. However, by

undergoing a procedural review, it is expected that some existing inefficiencies may be

eliminated and that through a collaborative process, organisational members are able to

agree on collective objectives and performance targets for the PBO so that returns may

be reinvested in system enhancements and facilitative tools to support their work.

Lastly, organizations can only successfully promote a knowledge-sharing culture by

directly incorporating knowledge management in its business strategy (Evans, 2012).

Following Nonaka’s (1991) notion of Knowledge-Creating Companies, knowledge

management strategies should not only ensure acquisition of internal knowledge but

also external knowledge from sources such as clients and competitors. This reinforces

the recognition that both knowledge itself and the source of knowledge as critical assets

of organizations. Aligning knowledge management with business strategy will require

conscious efforts of all members within the organization to effectively convert and

apply knowledge acquired towards achievement of organisational goals such as

differentiation from competitors and preservation of competitive advantage.

It is often difficult for organisations to question its existing norms and ideologies

during processes of change. Organisational learning, however, requires habitual

practices of ‘un-learning’ and ‘re-learning’ to order to ensure that organizations remain

adaptive within an ever evolving and demanding operating environment. While this

cross-sectional research study was able to present existing knowledge sharing

challenges relating to individual and combined effects of organisational and subgroup

cultures, it is suggested that a follow-up organization-wide research be conducted as a

means to evaluating the practicalities of these recommendations after they have been

implemented within the PBO.

 

59

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Appendices Appendix D1: Questions of Online questionnaire (with assigned data codes)

 

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Appendix D2: Questions of Focus Groups  

                                                 

 

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Appendix D3: Reliability Statistics  

                   

 

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Appendix D4: Focus Group Responses (Coded)  

                             

 

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