Factors affecting attitudes and intentions towards knowledge sharing in the Dubai Police Force

International Journal of Information Management 32 (2012) 372–380

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Factors affecting attitudes and intentions towards knowledge sharing in the Dubai Police Force Ibrahim Seba, Jennifer Rowley ∗ , Sian Lambert Department of Information and Communications, Manchester Metropolitan University, Manchester, M15 6LL, UK

a r t i c l e

i n f o

Article history: Available online 12 January 2012 Keywords: Knowledge sharing Knowledge exchange Public sector Police forces Middle East

a b s t r a c t This study contributes to the limited research base on knowledge sharing in public sector organisations, specifically police forces, and organisations in the Middle East through a case study investigation into the factors that affect knowledge sharing in the Dubai Police Force. A questionnaire-based survey was conducted with staff in key departments in the Dubai Police Force. Informed by the literature and by interviews conducted in a previous phase, the core of the questionnaire was a bank of Likert-style questions covering the dependent variables intention to knowledge share, and attitude towards knowledge sharing, and the independent variables, trust, organisational structure, leadership, reward, time, and information technology. Data was analysed using structured equation modelling, in order to test the measurement model using confirmatory factor analysis, and to test the structural model. The structural model suggests a strong relationship between attitude to knowledge sharing, and intention to share knowledge. Hypotheses regarding the influence of leadership, trust, organisational structure, time, and information technology on attitude to knowledge sharing were upheld. Rewards did not to influence attitude to knowledge sharing. Recommendations are offered for practice and further research. © 2012 Elsevier Ltd. All rights reserved.

1. Introduction Knowledge sharing is widely recognised to be a central component of successful knowledge management, and one of the central characteristics of a healthy knowledge culture is that knowledge sharing is embedded in the way in which the organisation works. Knowledge sharing is fundamental to generating new ideas and developing new opportunities through the socialisation and learning process of employees (Lin, 2007). However, employees will only share knowledge if they feel that it is their interest to do so. Employees’ willingness to share knowledge can be affected by a range of organisational factors that might be seen as the components of a knowledge sharing culture. Increasing their capacity to manage knowledge is one of the major challenges facing contemporary organisations (Davenport & Prusak, 1998). Accordingly, there has been considerable interest in the factors that may influence knowledge sharing in organisations, coupled with an acknowledgement that these factors may differ, or at the very least differ in their impact, in different organisations and specifically may vary between private and public sector organisations. Accordingly,

∗ Corresponding author. Tel.: +44 0 161 247 6137. E-mail addresses: [email protected] (I. Seba), [email protected] (J. Rowley), [email protected] (S. Lambert). 0268-4012/$ – see front matter © 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2011.12.003

researchers and practitioners need to examine these factors in the context of specific organisations. This article contributes to understanding of knowledge sharing in the public sector in the Middle East through a case study based investigation of the factors that affect knowledge sharing in the Dubai Police Force (DPF). Police forces are part of the public sector and the primary mission of any police force is to protect life and property, preserve law and order, and prevent and detect crime (Luen & Al-Hawamdeh, 2001). Accordingly, the management of intelligence and knowledge is a crucial aspect of the work of policing, and police forces need to be proactive in managing both explicit and implicit knowledge, and in developing their competencies in knowledge management and in promoting and facilitating knowledge sharing. There has been limited previous work on knowledge sharing in police forces, but there is a growing body of work on knowledge management and knowledge sharing in the public sector. Some argue that knowledge sharing is embedded in the public service culture of public sector organisations (Chiem, 2001), but whether or not this is the case there is growing evidence that there are potential barriers and facilitators to knowledge sharing in the public sector, which need to be managed in order to optimise the exploitation of knowledge assets (e.g. Cong, Li-Hua, & Stonehouse, 2007; Sandhu, Jain, & Ahmad, 2011). Similarly, whilst there is a body of research on knowledge sharing in Far Eastern cultures and in India (e.g. Fong, 2005; Joseph & Jacob, 2011; Kim & Lee, 2005; Lin, 2008) there has

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been very little research on Middle Eastern cultures. In particular, in order to implement successful knowledge management and promote knowledge sharing in Arab cultures it is necessary to understand and accommodate the associated cultural values and cultural approaches to organisation (Sabri, 2005; Weir & Hutchings, 2005). The next section is a summary of previous research on knowledge sharing and the factors that affect it, with specific reference to research in, respectively, the public sector, and the Middle East. The hypotheses and model are developed in the research design section. Next, the methodology is outlined, including the development of the questionnaire, sampling, and data analysis. Data analysis using structural question modelling (SEM) generates a model, which demonstrates the effect of a number of factors on attitude towards knowledge sharing and intention to knowledge share. The findings and discussion sections report on this analysis, present the model, and compare it with findings from previous research. Finally, the paper offers conclusions and recommendations for practice and further research.

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tend to be more selective, in the light of the need to measure each variable under consideration. For example, Lin (2007) focuses on extrinsic motivation (expected organisational rewards, reciprocal benefits) and intrinsic motivation (knowledge self-efficacy, enjoyment in helping others), whilst Al-Alawi, Al-Marzooqi, and Mohammed (2007) examine the impact of interpersonal trust, communication between staff, information systems, rewards and organisational structure. On the other hand, Bock, Zmud, Kim, and Lee (2005) include the following dependent variables: anticipated extrinsic rewards, anticipated intrinsic rewards, sense of self worth, subjective norm, and organisational climate (fairness, affiliation, innovativeness), and Joseph and Jacob (2011), in their study of knowledge sharing amongst IT professionals in India include anticipated extrinsic rewards, anticipated reciprocal relationships, organisational climate, and subjective norms. Ultimately, it would seem that there is a lack of consensus on the key variables under consideration in research on knowledge sharing. 2.2. Knowledge sharing in the public sector

2. Previous research 2.1. The factors that affect knowledge sharing According to Wang and Noe (2010), knowledge sharing refers to the provision of task information and know-how to help others and to collaborate with others to solve problems, develop ideas, or implement policies or procedures. Similarly, Dyer and Nobeoka (2000) define knowledge sharing as the activities that help communities of people to work together, facilitating the exchange of their knowledge, enhancing organisational learning capacity, and increasing their ability to achieve individual and organisational goals. A number of models of the factors that affect knowledge sharing have been proposed and tested in a wide variety of organisational and national contexts. These models vary in both the dependent and the independent variables that are included, although several variables appear in many of the models. In terms of dependent variables, models typically seek to measure one or more of attitude to knowledge sharing, intention to knowledge share, or knowledge sharing behaviour, all of which operate at the individual level. For example, Lin’s (2007) model on the effects of intrinsic and extrinsic motivation on employee knowledge sharing in large private sector firms in Taiwan included the dependent variables, attitude towards knowledge sharing, and knowledge sharing intentions, whilst Kim and Lee’s (2005) study concerned the impact of organisational context and information technology on employee knowledge sharing capabilities, in ten organisations in South Korea, and Lin and Lee’s (2004) research concerned perceptions of senior managers towards knowledge sharing behaviour. Other articles are rather vague with respect to the dependent variable of interest. For example, Lin (2008) in examining the factors affecting knowledge sharing in Taiwan’s high-tech industry, simply refers to ‘knowledge sharing’. Similarly, Ardichvili (2008) in a review of the factors, barriers and enablers of knowledge sharing in virtual communities of practice, also simply refers to ‘knowledge sharing’. Lin (2007) argues on the basis of Fishbein and Ajzen’s (1975) Theory of Reasoned Action (TRA), that there should be a close coupling between attitudes and intention. Independent factors considered to impact on knowledge sharing vary considerably between models (He & Wei, 2009). For example, Ardichvili (2008) in offering a general review identifies motivation factors (personal benefits, community-related considerations, and normative considerations); barriers (interpersonal, procedural, technological, cultural), and enablers (supportive corporate culture, trust, tools). Riege (2005) proposes three dozen knowledge sharing barriers. Empirical studies, on the other hand

Knowledge management and sharing in the public sector is currently attracting an increasing level of interest. Early studies of knowledge sharing in the public sector compared the public sector with the private sector and, in particular focussed on aspects of culture. For example, Liebowitz (2003) argues that knowledge sharing in the public sector is difficult because most people view knowledge as closely coupled with power, and related to their promotion prospects. In addition, Chiem (2001) points to the different approach to rewards for knowledge sharing between the private and public sectors and the negative effect that bureaucracy has on knowledge sharing in the public sector. Bureaucratic organisational cultures tend to mean that employees in the public sector often see knowledge management as a management responsibility and not necessarily something for which every employee should take some responsibility. On the other hand, there is recognition that the public sector does not completely lack advantages for knowledge sharing (Chiem, 2001). First, a public organisation is less worried than one in the private sector about disclosing trade secrets and other vital information. Second, the fact that knowledge sharing in the public sector can be viewed as a social good can act as an incentive and this does not easily exist in the private sector. Moreover, civil servants in the public sector are not strongly profitmotivated, unlike employees in the private sector. Rather, their jobs are devoted to serving their communities. Specifically in the context of the police force, research on knowledge management and sharing is very limited. According to Dean, Filsted, and Gottschalk (2006), police investigation units represent a knowledge-intensive and time-critical environment, and this and the vast quantity of knowledge that police officers need, suggest that police officers are knowledge workers. Both tacit and explicit knowledge are of critical importance in solving criminal cases. Dean et al. (2006) found that knowledge sharing has a significant influence on all primary activities of the police investigation value shop. In another study, in Norway, Glamseth & Gottschalk, 2007) reasserted the importance of knowledge sharing on the performance of police investigations, and suggested that knowledge sharing is influenced by occupational culture. Four dimensions of occupational culture were identified: team culture, planning culture, theoretical culture, and traditional culture, but only the extent of team culture was found to have a significant influence on the extent of knowledge sharing and performance in police investigations. 2.3. Knowledge management and sharing in Arab cultures Whilst there is something of a tendency to treat knowledge management as a universal practice, which is transferable from

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sharing research (e.g. Bock et al., 2005; Lin, 2007), and hence were included in this research model. Similarly, there is previous evidence of a strong relationship between attitudes towards knowledge sharing and intention to knowledge share, as shown by Bock et al. (2005) and Joseph and Jacob (2011). Others have specifically emphasised the role of attitude in the effectiveness of knowledge sharing practices (Gottschalk, 2007; Yang, 2009). The following hypothesis is proposed: H1. Attitude towards knowledge sharing will influence intention to share knowledge.

Fig. 1. The research model.

one country to another, there is a growing body of work that is starting to recognise the effect of national culture on knowledge sharing and transfer (e.g. Fong, 2005; Jaw, Ling, Wang, & Chang, 2007; Hong, Easterby-Smith, & Snell, 2006; Wilkesmann, Fischer, & Wilkesmann, 2009). However, many of these studies have focussed on Far Eastern cultures (e.g. Chow, Deng, & Ho, 2000; Fong, 2005; Wilkesmann et al., 2009), and there is a paucity of studies on knowledge sharing or exchange in Middle Eastern cultures. Two exceptions are the work of Weir and Hutchings (2005) which discusses the cultural embeddedness of knowledge sharing in Chinese and Arab cultures, and that of Sabri (2005) which focuses specifically on how to transform Arab bureaucracies into knowledge creating cultures by designing the right organisational structure. The key to business in the Arab world is social networks; all business activities revolve around these networks (Weir & Hutchings, 2005). Therefore, the success of a manager or a business person depends on his relationship with the community, to the extent that if a manager has a strong relationship with his community then he will be one of the most successful people in his country. Arab people are very respectful of this relationship and some business in Arab countries is done under the reign of two values (without any contract), trust and respect. The importance of relationships is grounded on Islam. The holy book for the Muslims mentions many rules that obligate them to respect relationships, and, in addition, the prophet of Islam, Mohammad, recommends his nation to take care of relationships between all people, including non-Muslims. Arab people respect what their prophet taught and strive all the time to follow his instructions. One of these instructions is about sharing with others what we have even if we need it ourselves; in Islam this is called altruism. Accordingly, in Arab countries it is expected that if a person has a good relationship with another person then those two persons will exchange the knowledge they hold without any expectation of reward. 3. Research design Taking into account previous research into the factors that affect knowledge sharing, both in the public sector and elsewhere, and complementing this with insights from an earlier qualitative investigation into knowledge sharing in the Dubai Police Force, a number of hypotheses have been formulated. These are presented in the research model, as shown in Fig. 1. The supporting case for each hypothesis is briefly outlined below. Attitude towards knowledge sharing and intention to knowledge share are often used as key dependent variables in knowledge

Leadership and management have been identified as important influencers of effective knowledge sharing, especially in research in the public sector (e.g. Rivera-Vazquez, 2009; Cong et al., 2007; Sandhu et al., 2011). More specifically, employees look to their leaders and managers to act as role models and to show commitment, explain what was expected of their team members, and offer support. Bircham-Connolley, Corner, and Bowden (2005) suggest that leadership directs and guides all processes associated with knowledge sharing. In addition, managers control most of the other factors that shape knowledge sharing cultures and environments, including time and rewards (Bircham-Connolly et al., 2005; Lee & Ahn, 2007; Sandhu et al., 2011). Leadership is one of the strongest influencers of attitudes towards and intentions to knowledge share (Kazi, 2005; Lee, Gillespie, Mann, & Wearing, 2010), notwithstanding the fact that there are several forms and styles of leadership that might impact differentially on knowledge sharing (McNabb, 2006). Further, in the earlier qualitative phase of this research in the Dubai Police Force leadership was seen as particularly important in influencing knowledge sharing (the authors, 2012). The following hypothesis is proposed: H2. Leadership influences employee attitudes towards knowledge sharing. Organisational structure is widely acknowledged to influence inter-personal and inter-departmental communication opportunities, so it is not surprising that various authors have provided theoretical and empirical evidence on the relationship between organisational structure and the employees’ knowledge sharing (Al-Alawi et al., 2007; Gorry, 2008; Grevesen & Damanpour, 2007; Jennex, 2005; Rowley, Seba, & Delbridge, 2012). Recently, there has been recognition that organisational cultures and structures should not in themselves present a barrier to knowledge sharing, but rather that the practices and application of knowledge sharing should be adapted to suit specific organisational situations (Jennex, 2005; Willem & Buelens, 2009). Developing this theme, Gorry (2008) identifies three main types of organisational structure, which will determine the specific characteristics of knowledge sharing: dynamic structure, networking structure, and objectoriented structure. In addition, Ragsdell (2009), in a study in the voluntary sector, found that two aspects of organisational structure, physical (e.g. office layout), and reporting, were seen to impact on the effectiveness of knowledge sharing. As discussed by Gorry (2008), depending on the type, organisational structure can either be a facilitator or barrier to knowledge sharing. The following hypothesis is proposed: Organisational structure influences employee attitudes H3. towards knowledge sharing. Trust has repeatedly been identified as an antecedent to knowledge sharing (e.g. Al-Alawi et al., 2007; Butler, 1999; Coakes, 2006; Lee et al., 2010; Lin, 2007). Trust can be classified into two groups: personal knowledge-based trust, and institution-based trust (Ardichvili, 2008). Inter-personal trust develops on the basis of recurrent social interactions between individuals, and its role in knowledge sharing has often been studied using the theoretical

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lens of social exchange theory or social cognition (e.g. Chow & Chan, 2008; Ringberg & Reihlen, 2008; Staples & Webster, 2008). Trust has particularly surfaced in studies of knowledge sharing in the public sector (Hock, Ling, & San, 2009; Pardo, Cresswell, Thompson, & Zhang, 2006). When there are cognitive codes of trust, employees are not only willing to listen to others but are also able to absorb knowledge from others (Bakker, Engelen, Gabbay, & Leenders, 2006) In the earlier qualitative phase of this research trust, not only of colleagues, but also of managers, was seen as particularly important in influencing knowledge sharing. The following hypothesis is proposed: H4. The level of trust between employees influences employee attitudes towards knowledge sharing. Rewards, incentives, and benefits accruing from knowledge sharing have been much discussed and researched. Many researchers take motivation theory as their theoretical base for knowledge sharing, and the concept of reward as a means of driving behaviour is inherent in motivation theory. Some researchers have identified insufficient rewards as a barrier to knowledge sharing (Sandhu et al., 2011; Yao, Kam, & Chan, 2007), and others (e.g. Fathi, Eze, & Goh, 2011; Liebowitz, 2003) have recommended that organisations institute a reward system. However, findings from research on the value of rewards differentiate between extrinsic rewards (such as payment or promotion) and intrinsic rewards or benefits (such as increased reputation or respect.). For example, both Bock et al. (2005) and Lin (2007) failed to show that extrinsic rewards had any positive effect on knowledge sharing, but Bock et al. (2005) showed that anticipated intrinsic rewards did impact on knowledge sharing, and Lin (2007) showed that reciprocal benefits, knowledge self-efficacy, and enjoyment in helping others were significantly associated with knowledge sharing. Certainly one of the problems with rewards systems is that knowledge sharing between employees is difficult to measure and evaluate (Holman, 2005). The issue of rewards is complex, particularly in the public sector (Bock & Kim, 2002). Ultimately, it may seem that the impact of rewards may vary with the type of reward or incentive available and the context. Interestingly, in the earlier qualitative phase of this research, rewards were not mentioned. Nevertheless, given the interest in this construct in the literature, the following hypothesis is proposed: H5. Rewards influence employee attitudes towards knowledge sharing. The availability of time to engage in knowledge sharing has not received much attention in the literature but it surfaced strongly in the earlier qualitative phase of research in the Dubai Police Force. In a relatively early review of knowledge sharing, Ipe (2003) argues for the central importance of sufficient time to engage in knowledge exchange. Only two empirical researches, both of which were conducted in the public sector mention time allocation. Sandhu et al. (2011) identified lack of time as one of the organisational barriers to knowledge sharing. Lee and Ahn (2007) suggest that time allocation may become a serious obstacle to efficient knowledge sharing, because public sector managers frequently view knowledge sharing as an additional and supplementary procedure, which is not allocated a sufficient amount of time. Complementing this, Haas and Hansen (2007) concluded that the willingness of staff to share knowledge was determined by the amount of time allocated to a task for which knowledge sharing could be potentially useful. The following hypothesis is proposed: H6. Time allocation influences employee attitudes towards knowledge sharing. Information systems are widely regarded as a beneficial tool in knowledge sharing, and technologies such as intranets, decision

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Table 1 Sources of measurement items. Variable

Items

References

Leadership Organisational structure

5 items 5 items

Attitude Trust

5 items 5 items

Intention Reward Time

4 items 5 items 5 items

Information technology

5 items

Lu, Leung and Koch (2006) Van den Hooff and Huysman (2009) Bock et al. (2005) Chow and Chan (2008) Developed items from interviews Bock et al. (2005) Barreto (2003) Developed items from interviews Van den Hooff and Huysman (2009)

support systems, knowledge repositories, and social networking all provide opportunities for communication and knowledge sharing. Accordingly, information systems, specifically their quality and functionality, might be regarded as one of the factors that influence knowledge sharing. Information systems have surfaced repeatedly in research on knowledge sharing in the public sector (Choi, Lee, & Yoo, 2010; Cong et al., 2007; Sandhu et al., 2011). Robinson, Carrillo, Anumba, and Patel (2010) suggest that information technology performs a functional role in knowledge sharing, and also that technology skills and competences may either contribute, or hamper knowledge sharing. Accordingly, although information technology was not mentioned by respondents in the earlier qualitative phase of this study, it nevertheless seems appropriate to propose the following hypothesis: H7. Information systems influence employee attitudes towards knowledge sharing. 4. Methodology This article develops a model of the factors that affect knowledge sharing in the Dubai Police Force, using a questionnaire-based survey of the DPF’s employees. 4.1. Questionnaire design Questionnaires were used because they are an efficient means of data collection when the researcher knows what data is required to answer their research questions, and how to measure the research variables (Easterby-Smith, Golden-Biddle, & Locke, 2008). Respondents’ attitudes towards the role of the factors identified in the previous section were measured using 5-point Likert scale questions (5 = “disagree strongly”; 1 = “agree strongly”). This study measured eight constructs: intention to share knowledge, attitude towards knowledge sharing, leadership, organisational structure, reward, trust, time, and information technology. All constructs were measured using multiple items. Item statements for these variables were informed by previous research as summarised in Table 1. All of the items that were retained after analysis are shown in Table 3. Negative items were included alongside positive items as a basis for checking consistency of response. Categorical questions were used for demographic variables, such as department, gender, age, and educational level, and work experience. The questionnaire was piloted with professional researchers, and then with individuals from the research population, in both English and Arabic. This eliminated any inconsistencies and confirmed the suitability of the content, structure and design of the questions and the questionnaire.

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Table 2 Profile of respondents. Demographic characteristics Department Department A Department B Department C Gender Male Female Age 18–25 26–30 31–40 41–50 Over 50 Education level High school Diploma Bachelor Masters or more Work experience 0–5 years 5–10 10–15 15–20 20–25 Over 25 Position Manager Chief officer or officer Type of work Field work Managerial work

5. Findings Number of responses

Percentage

109 93 109

35.0 29.9 35.0

283 28

91.0 9.0

51 82 127 40 11

16.4 26.4 40.8 12.9 3.5

228 31 48 4

73.3 10.0 15.4 1.3

63 76 70 47 28 27

20.3 24.4 22.5 15.1 9.0 8.7

94 217

30.2 69.8

142 169

45.7 54.3

4.2. Questionnaire distribution and respondents The questionnaire was distributed by the managers of three large operational departments in the Dubai Police Force. The total population for these three departments is about 4000 officers. 600 hundred questionnaires were sent out, and 519 (86.5%) completed questionnaires were received. After incomplete questionnaires and those with evidence that the respondent had not read the questionnaire were eliminated, there were 319 usable questionnaires, which were used as the basis for the data analysis. The respondent profile is given in Table 2. Responses were fairly evenly distributed amongst the three departments. In keeping with the demographic profile of these departments, the respondents were predominantly male (91%). In terms of age, and length of work experience, respondents were well-distributed across the different categories. For 73.3% of respondents the highest educational level attained was high school; most others had either a diploma or a bachelors degree. 30.2% of respondents were managers and 69.8 were police officers or chief police officers.

4.3. Data analysis The research model shown in Fig. 1 was analysed using SEM supported by AMOS. SEM is second-generation multivariate technique for analyzing causal models. SEM was used to generate both the measurement model and the structural model. The measurement model is estimated using confirmatory factor analysis (CFA) to test whether the constructs possess sufficient validation and reliability. The structural model is used to investigate the strength and direction of the relationship between the theoretical constructs.

SEM first used to generate the measurement model; this led to the elimination of eight items. Next SEM was used to test the structural model. This stage confirmed that five out of six factors have a strong effect on knowledge sharing in the Dubai Police. These factors are leadership, organisation structure, trust, time and IT. Reward does not have a significant effect. The details of this analysis are presented next. 5.1. The measurement model The measurement model was tested using CFA. According to Segars and Grover (1998), the measurement model should be evaluated first and then re-specified as necessary to generate the ‘best fit’ model. The first assessment of the model indicated that eight items should be removed, leaving 31 items remaining, as shown in Table 3. Item reliability ranged from 0.55 to 0.97, thus exceeding the acceptable value of 0.50 recommended by Hair, Anderson, Tatham, and Black (1992). The composite reliability ranged from 0.76 to 0.92, which is above the 0.60 benchmark recommended by Bagozzi and Yi (1988). Finally, the average variance extracted for all items exceeded the threshold value of 0.5 recommended by Fornell and Larcker (1981). Since the values of reliability were above the recommended thresholds, the scales for evaluating the items were deemed to exhibit convergence reliability. Table 4 shows that the variances extracted by items were greater than any squared correlation amongst items; this implied that the items were empirically distinct. In the end, the measurement model test was satisfactory. The fitness measures for the measurement models are shown in Table 5. 2 (the ratio between 2 and the degree of freedom = 2 /d.f.), GFI (goodness-of-fit index), AGFI (adjusted goodness-of-fit index), NFI (normalised fit index), CFI (an incremental fit index of improved NFI) and RMSEA (root-mean-square error of approximation) were used to test the goodness of fit of the proposed model. The literature suggests that 2 /d.f. should not exceed 3 (Bentler & Bonett, 1980), that NFI and CFI should be greater than the recommended value of 0.9 or higher (Bentler & Bonett, 1980) and that RMSEA should be less than 0.08 (Hair et al., 1992). Further, GFI and AGFI should be greater than the recommended value of 0.8 (Scott, 1994; Seyal, Rahman, & Rahim, 2002). All the fitness measures in the study fell into acceptable ranges and, consequently, the proposed model provided a suitable fit. 5.2. Testing the structural model The structural equation model was examined by testing the hypothesised relationships between the research variables (see Fig. 2). The results of structural model show that attitude has a significant effect on intention to share knowledge (H1, path coefficient of 0.84, p < 0.001). Also, the results showed that leadership (H2, path coefficient of 0.19, p < 0.001), organisational structure (H3, path coefficient of −0.16, p < 0.001), trust (H4, path coefficient of 0.26, p < 0.001), time (H6, path coefficient of 0.22, p < 0.001) and IT (H7, path coefficient of 0.25, p < 0.001) have a significant effect on attitude. However, reward (H5 had no direct influence on attitude towards knowledge sharing. Therefore, Hypothesis 5 is not supported. These results are summarised in Table 6. 6. Discussion This research has proposed a model of the factors that affect knowledge sharing, and in the context of this study, the Dubai

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377

Table 3 Results of CFA for measurement model. Item

Measure

Item reliability

Composite reliability

Average variance extracted

LE1

My manager always sets a good example in sharing his knowledge with others My manager supports me in sharing knowledge with colleagues in other departments My manager allows me to share my knowledge with my colleagues even though it may influence the present job process My manager instructs us on how to share our personal knowledge within the department My manager does not care about my knowledge and does not encourage me to share my knowledge with other colleagues The structure of this department promotes collective rather than individualistic behaviour The department designs processes to facilitate knowledge exchange across departmental boundaries The department encourages people to go wherever they need to for knowledge regardless of structure My practice is relation to knowledge sharing is appropriate and effective My knowledge sharing with other department members is an enjoyable experience My knowledge sharing with other department members is valuable to me My knowledge sharing with other department members is a wise move I know my department members will always try and help me out if I need to know something I can always trust my department members to lend me a hand if I need it I can always rely on my department members to make my job easier by sharing their knowledge I can talk freely to my department members about my personal knowledge I intend to share my knowledge with more departmental members I intend to share my knowledge with anyone in the department if it is helpful to the department I intend to share my knowledge with other department members more frequently in the future I intend to share my knowledge with other department members in an effective way I will receive a higher reward in return for my knowledge sharing within this department I am more likely to receive increased promotion opportunities in return for my knowledge sharing This department offers attractive rewards to employees for their knowledge sharing There is no time to share my knowledge with my colleagues due to pressure of work in this organisation This organisation does not create time for discussion with our colleagues I am too busy to attend training courses or workshops in my department Our IT facilities make it easier to cooperate with others within our department Our IT facilities make it easier to cooperate with others outside our department The IT facilities within this department provide a positive contribution to the development of my knowledge The IT facilities within this department provide important support for knowledge sharing IT makes it is easier for me to get in contact with employees who have knowledge that is important to me

0.86

0.83

0.51

0.76

0.52

0.86

0.60

0.89

0.68

0.87

0.62

0.85

0.65

0.76

0.80

0.56

0.79 0.71 0.75

0.92

0.68

LE2 LE3 LE4 LE5 ST1 ST2 ST3 AT1 AT2 AT3 AT4 TR1 TR2 TR3 TR4 IN1 IN2 IN3 IN4 RE1 RE2 RE3 TI1 TI2 TI3 IT1 IT2 IT3 IT4 IT5

Police Force, all except one of the proposed relationships in the model have been supported. Firstly, consistent with TRA (Fishbein & Ajzen, 1975), and with earlier research on knowledge sharing (e.g. Bock et al., 2005; Lin, 2007), it has been found that employee

0.87 0.55 0.68 0.60 0.66 0.86 0.65 0.58 0.71 0.89 0.90 0.83 0.97 0.83 0.65 0.67 0.76 0.88 0.85 0.85 0.85 0.72

0.73 0.91 0.92 0.87

attitudes to knowledge sharing have a strong influence on intention to knowledge share. Indeed, the strength of this relationship is such that it may not be necessary to differentiate between attitudes and intentions.

Table 4 Variances extracted.

LE ST AT TR IN RE TI IT

LE

ST

AT

TR

IN

RE

TI

IT

0.51 0.46 0.13 0.44 0.15 0.45 0.34 0.28

0.52 0.24 0.37 0.21 0.37 0.23 0.37

0.60 0.38 0.46 0.17 0.10 0.23

0.68 0.48 0.33 0.42 0.37

0.62 0.13 0.22 0.20

0.65 0.11 0.41

0.56 0.21

0.68

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Leadership (H2).19***

Organization Structure (H3)-1.6***

Trust (H4).26***

Attitude Reward

(H1).84***

Intention

(H5).06

(H6).22***

Time (H7).25***

Information Technology

Fig. 2. Results of structural model analysis. Table 5 Overall fit of models. Fit index

Recommended criteria

Results

Suggested by authors

GFI AGIF NFI CFI 2 /d.f. RMSEA

>0.8 >0.8 >0.9 >0.9 <3 <0.08

0.98 0.90 0.98 0.99 1.6 0.04

Seyal et al. (2002) Scott (1994) Bentler and Bonett (1980) Bentler and Bonett (1980) Bentler and Bonett (1980) Hair et al. (1992)

In addition, all of the following variables influence attitude towards knowledge sharing: leadership, organisational structure, trust, time, and information technology. There is general agreement that leadership, trust, time, and information technology have a moderate positive impact on attitudes to knowledge sharing. With regards to the role of leadership, and two key variables that are often heavily influenced by leadership, time to engage in knowledge sharing, and trust in colleagues, these findings are consistent with earlier research in both the public and private sectors, which were conducted in a variety of geographical locations (e.g. Hock et al., 2009; Pardo et al., 2006; Rivera-Vazquez, 2009; Sandhu et al., 2011). In addition, the support for the hypothesis regarding the impact of information technology lends further support to findings from other studies that the quality of information systems can influence attitudes towards knowledge sharing (e.g. Al-Alawi et al., 2007; Cong et al., 2007; Sandhu et al., 2011). Two factors deserve specific mention. First, organisational structure is normally shown to influence attitudes to knowledge sharing, but in this instance the influence is negative, suggesting that employees in this research feel that organisational structure has a negative impact on their attitude towards knowledge sharing. This is supported by the earlier qualitative phase of this research (Rowley et al., 2012) and is consistent with proposals from Gorry Table 6 Results of structural model. Hypothesis

Hypothesis path

Path coefficient

Results

H1 H2 H3 H4 H5 H6 H7

Attitude → intention Leadership → attitude Structure → attitude Trust → attitude Reward → attitude Time → attitude IT → attitude

(0.84*** ) (0.19*** ) (−0.62*** ) (0.26*** ) (0.06) (0.22*** ) (0.25*** )

Supported Supported Supported Supported Not supported Supported Supported

*p < 0.05. **p < 0.01. *** p < 0.001.

(2008) and others who suggest that organisational structure has a significant impact on knowledge sharing, but that different organisational structures have differing impacts, and, the potential impact of bureaucratic organisational structures in the public sector (Chiem, 2001). Secondly, rewards, or the expectation of rewards, were not found to have a significant influence on attitudes towards knowledge sharing. Respondents, in general, as public sector employees, may not have been expecting rewards, although further mining of the descriptive statistics does suggest that they appreciated intrinsic rewards, taking pleasure in knowledge sharing. The current research model contains six factors, three of which (leadership, time, and organisational structure) are not very frequently cited in other research models despite being mentioned in the literature as important factors affecting knowledge sharing (Ipe, 2003; Rivera-Vazquez, 2009; Syed-Ikhsan & Rowland, 2004). Many researchers claim that these factors act as barriers to knowledge sharing if not appropriately managed (e.g. Michailova & Husted, 2003; Srivastava, Bartol, & Locke, 2006). This suggests that more research is needed that focuses on the organisational context for knowledge sharing. 7. Conclusions and recommendations 7.1. Contribution This research has used a questionnaire-based survey in order to establish the factors that influence attitude and intention towards knowledge sharing in the Dubai Police Force. As such it makes an important contribution to the exploration of knowledge sharing in the under-researched areas of public sector organisations, specifically police forces, and organisations in the Middle East. The structural model suggested a strong relationship between attitude towards knowledge sharing and intention to knowledge share. This suggests that in future research it might not be necessary to measure both attitude and intention, and that, as suggested by Lin (2007), on the basis of TRA (Fishbein & Ajzen, 1975), there is a close coupling between attitudes and intentions in this context. As regards the independent variables, leadership, trust, organisational structure, time and information technology were demonstrated to influence attitude towards knowledge sharing. This generally concurs with previous research, although no other model has specifically developed a model incorporating all of these factors. The replication in terms of key factors, between a number of studies conducted in different parts of the world, may suggest that the key factors that affect knowledge sharing are the same across cultures and organisations. For example, whilst trust is often recognised as an inherent facet of business relationship in the Muslim world, and is certainly an important precursor to knowledge sharing in this context, other researchers have also suggested that trust is important in both private and public sector organisations in a wide range of geographical and cultural settings. Undoubtedly, many of these factors may impact differently in different contexts. For example, appropriate, reliable, and easy to use information technology resources will facilitate knowledge sharing, whilst a less effective IT infrastructure dominated by functional inadequacies or political agendas may act as a barrier to knowledge sharing. An interesting characteristic of the model proposed and tested in this study is that it was informed not only by previous literature, but also by an earlier phase of this research in which interviews were conducted with officers in the Dubai Police Force. This has led to a model that is less complex than some previously proposed from an entirely theoretical perspective, and also importantly, has avoided an approach that is overly dominated by motivation theory,

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as is evident in much prior research (e.g. Ardichvili, 2008; Bock et al., 2005; Lin, 2007). Given that other researchers have recognised rewards to be problematic (e.g. Fathi et al., 2011; Holman, 2005; Sandhu et al., 2011), and this study has found rewards not to have any significant impact on attitudes to knowledge sharing, it may be time to re-visit the appropriateness of motivation theory as a basis for research in knowledge sharing.

7.2. Recommendations 7.2.1. Recommendations for practice Although this research has focussed on the challenges facing one public sector organisation in the Middle East, its findings are of potential interest to other organisations, especially, but not exclusively those in the public sector:

1. Leadership is pivotal to successful knowledge sharing across an organisation, because leadership can affect so many of the factors in the work environment and organisational culture that will influence attitudes towards knowledge sharing. Managers need to lead in knowledge sharing and, in order to do this, they themselves need to appreciate the value of knowledge sharing to ‘getting the job done’ and they need education and training on ways in which they can support and encourage knowledge sharing. 2. Trust is pivotal, both between colleagues and between staff and their managers but trust is fragile, especially in politicised departments. Managers need to behave in ways that enhance perceptions of trustworthiness, and which support the creation of good working relationships between team members so that team members learn from one another. 3. Managers need to allow their teams to ‘make time’ for knowledge sharing, including time for formal meetings and also for social interaction, and to encourage reflection on the effectiveness of meetings and other interactions. 4. Consideration should be given to the effect of organisational structure on knowledge sharing, and the availability of organisational resources, such as IT infrastructure to facilitate communication and knowledge sharing.

7.2.2. Recommendations for research The findings from this study suggest a number of areas for further research:

1. Further research should be conducted in other organisations to investigate whether the findings of this study are supported or not, and to investigate the relative impact of the various factors on attitude towards and intention to knowledge share. 2. In this study, two cultural issues have been intertwined, Arab culture and police force culture. Further studies should be conducted in both contexts in order to disaggregate these two issues and generate further insights into the factors that affect knowledge sharing in police forces and in organisations in the Middle East. 3. A significant proportion of previous research on knowledge sharing has been dominated by motivation theory, which has led to much discussion of the rewards associated with knowledge sharing. This research, suggests that employees are not especially interested in rewards. Further inductive studies in other contexts would be a useful platform for establishing the most appropriate theoretical approach to understanding and measuring the impact of the antecedents to knowledge sharing.

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