In the process of completing the task of data collection, a preliminary analysis test was conducted to identify the response rate, inter-rate agreement, validity and reliability of the study construct. For this purpose, factor analysis and reliability analysis were conducted to identify the reliability and validity of independent variables, namely mentoring programme, individual personalization, individual codification, institutionalized personalization, institutionalized codification, managing self, managing tasks and managing others as well as the moderating variables of agreeableness, conscientiousness and openness to experience. The characteristics of respondents were described in descriptive statistics such as means and frequencies. To test the hypotheses, multivariate analyses, specifically Pearson correlation, ANOVA, T-test and hierarchical regression analyses were conducted.
These analyses were chosen in alignment with the nature of the data and for their appropriateness to answering the research questions, as suggested by previous studies. Because the variables in this study represent different levels of data, direct analysis methods were used. Knowledge sharing consists of a knowledge-sharing mechanism that has never been tested in a quantitative study; factor analysis was required to confirm the validity of the instrument in the context of the study. This approach is also applicable for items of personality traits, of which only a part of the inventory was employed in this study. Further, managerial tacit knowledge inventory items also involve transformation of data including standardised standard deviation (refer to
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section 6.4) to identify the differences between groups of respondents, consisting of experts, typical and novices.
In fact, some of the techniques in certain analyses are unnecessary in research if previous studies have shown that they are not appropriate. For example, Echambadi and Hess (2007) proved that mean-centring does not change the computational precision of parameters, the accuracy sample of main effects, or simple effects and that the R2 and collinearity problem in the moderator regression also remain unchanged by mean- centring. Therefore, the researcher employed moderated regression models without mean-centring in an attempt to mitigate collinearity between the linear and interaction terms.
The first research objective was achieved by carrying out a correlation analysis, as suggested by Suppiah and Sandhu (2011), who studied tacit knowledge-sharing behaviour in the Malaysian context using factor analysis and correlation to find and check convergent and discriminant validity. Melissa (1991), Sternberg et al. (2000), and Colonia-Willner (1998) also analyse correlation and regression analysis to study managerial tacit knowledge in the context of managerial work as initial studies in understanding the context of managerial tacit knowledge in different working environments.
This study draws on three different variables which are the implementations of KSP, TK and PT combined in the second research objective, to explain the mechanisms that underlie knowledge sharing between managers in organisations with different levels of performance: high and low. This study aims to investigate the different implementations of KSP, TK and PT among managers that can be distinguished by analysis enabling the comparison of two different groups; t-test analysis is appropriate to compare between these groups (Hair et al., 2010; Sekaran, 2003).
The third research objective was answered by the results of the hierarchical regression analysis to produce moderator roles of personality traits. As proposed by Baron and Kenny (1986), hierarchical regression analysis is a powerful technique for producing moderator effects. Furthermore, this analysis was also informed by previous studies in a
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similar research context such as Bryant (2005), Quigley et al. (2007), and Sternberg et al. (1995).
5.6.1 Goodness of Measures: Factor Analysis and Reliability
The present study involves multidimensional independent variables, moderating variables and a dependent variable. Independents are multi-dimensional constructs, therefore factor analysis was run in the study. Factor analysis was carried out using a principal axis factoring with oblimin rotation (Hair et al., 2010) to identify the underlying interrelationship of variables into a set of common dimensions. Factor analysis enables the production of descriptive summaries of data metrics, which are later used to detect meaningful patterns among the set of variables (Dess et al., 1997). Factor analysis was employed for all the independent and moderator variables. Hair et al. (2010) suggested that for a sample size more than 300, a factor loading of 0.30 is needed to assess statistical significance.
Factor analysis enables items separated into respective factors to be subjected to reliability analysis before further computerisation analysis to represent the latent variables. Reliability analysis demonstrates the internal consistency, which indicates the homogeneity of items in the measure that is measuring the latent variables (Cooper & Schidler, 2003). Hair et al. (2010) explained that the role of reliability analysis was to measure the extent to which a variable or a set of variables consistently measures what it is intended to measure. In order to measure internal consistency, Cronbach’s alpha is one of the most commonly used reliability coefficients (Coakes & Steed, 2003; Sekaran & Bougie, 2010). A reliability analysis was conducted on the scales used to measure items of mentoring programmes, knowledge sharing mechanisms, managing self, managing tasks, managing others, agreeableness, conscientiousness and openness. It is generally accepted that the lowest level of Cronbach’s Alpha reliability value should be more than Nunnally’s (1978) recommended 0.70. The items of each construct, following to factor analysis and reliability analysis, were used for further analysis. The results and factor analysis are reported in the following chapters.
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1. Bivariate Correlation and Multiple Regression
Bivariate correlation was carried out for different purposes; firstly to test the relationship between knowledge sharing practices (mentoring programme, individual personalization, individual codification, institutional personalization and institutional codification) with managerial tacit knowledge and secondly, to test the relationship between managerial tacit knowledge (managing self, managing tasks, managing others) with knowledge sharing practices.
The correlation analyses demonstrate the direction, significance and strength of the bivariate relationships of the study variable (Sekaran & Bougie, 2010). At the same time, multiple regression testing was used to reveal the significance of dependent variables as predictors (individual performance) from the independent variables of mentoring programme, individual personalization, individual codification, institutional personalization and institutional codification, managerial tacit knowledge (managing self, managing tasks, managing others). Multiple regression analysis is the statistical analysis that provides an understanding of how much variance in the dependent variable is explained by independent variables when theorised to influence simultaneously the former (Sekaran & Bougie, 2010).
2. Hierarchical Multiple Regression
Hierarchical multiple regression analysis was selected to examine whether personality traits moderated the relationship between knowledge sharing practices and individual performance as well as to test whether personality traits moderated the relationship between managerial tacit knowledge and individual performance. This analysis was utilised in research concerning the detection of moderating effects, as recommended by Chaplin (1991), Cohen and Cohen (1983), Stone and Hollenback (1984) and Zedeck (1971). It is supported by Baron and Kenny (1986), who agreed that the use of multiple regression in detecting moderating effect was the most appropriate test.
The process of performing hierarchical multiple regression encompassed several steps. It began with entering the sets of predictors into the regression block in order. Firstly, the main effects of knowledge sharing practices variables were entered into the block regression. Secondly, the moderating variable, personality traits, was entered into the
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second block. Lastly, the final step was enter of the two-way interaction terms into the last block. These two-way interaction terms were obtained by multiplying the moderator with the variables of personality traits.
5.6.2 Reliability
Reliability analysis is used to evaluate the stability and consistency of the measurement items in each latent construct (Saunders et al., 2009). Reliability refers to the idea of a 'replication', 'replicability' and the ability to repeat the same study and obtain the same results not only from the same research but also from different research based on the same data (Collis & Hussey, 2009; Bryman & Bell, 2007). In other words, reliability is concerned with the stability of the measurement tools used and results obtained (Easterby Smith et al., 2002; Ghauri & Gronhaug, 2002). The questions in this survey were taken from previous studies to measure the components used. Therefore, there is consistency of instruments used to measure the construct of study and they expected to have a high level of reliability. This survey-based research used Cronbach’s alpha analyses to measure the reliability and confidence of the questions (Sekaran, 2003). The criteria that were determined to delete the items were dependent on (a) its corrected items to total correlation (b) whether this deduction improved the corresponding alpha values (Hu et al., 2009; Parasuraman, et al., 1988). The high reliability analysis identified indicates the questionnaires as reliable.
5.6.3 Validity
The validity of a measurement instrument is the degree to which the instrument accurately measures. This can be ascertained by a pilot test. Validity is important to make sure that data collected represent the intention of research (Collis & Hussey, 2009). In this research, a pilot test was carried out in order to make sure the respondents understood the questions and to avoid any error of measurement.
The validity of the instruments was anssured by the adoption of items tested in previous studies. For example, the value of personality as a predictor of job performance has received substantial research attention over the past 25 years (Guion & Gottier, 1965; Hunter & Hunter, 1984; Reilly & Chao, 1982; Schmitt et al., 1984). For the personality traits, Barrick & Mount (1993) indicated that conscientiousness is a valid predictor for job group and job related criterion types studied. These results show that highly
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conscientious individuals generally perform better than others who do not demonstrate this trait. Barrick and Mount (1991) reported that other trait dimensions are also valid predictors in some occupations with smaller validities.
Similarly, the tacit knowledge inventory has been used in tests for over 20 years. The Tacit Knowledge Inventory for Managers (TKIM) by Wagner and Sternberg (1991) is a test of tacit knowledge or practical know-how (Wagner, 1987). This inventory is used purposely to identify individuals whose tacit knowledge indicates the potential for successful performance in managerial or executive careers (Wagner & Sternberg, 1991). Wagner and Sternberg’s inventory (1991) has been tested in five studies to examine the criterion-related validity of their tacit knowledge measures in academic and business settings. A moderate correlation was found between their measures and a variety of criteria and some of them were considered as job performance measures.
Only the instruments in the knowledge sharing practices consisting of mentoring programme and knowledge sharing mechanism were not tested in previous studies, and testing these was therefore one of the main contributions of this study.
The discussion above refers to internal validity. External validity, on the other hand, refers to the extent to which the findings can be generalised to particular persons, setting and times, across organisations (Ghauri & Gronhaug, 2002). This research examined the practices of sharing managerial tacit knowledge among local government managers; external validity was used as a basis for generalising the implementation of sharing managerial tacit knowledge among managers in other public agencies as well.
The importance of understanding validity has an effect on the research findings. If the study lacks construct validity, the findings are meaningless, destroying also the internal and external validity of the findings (Ghauri & Gronhaug, 2002).