6-Petkoon.qxd Organisational culture In the past 20 years or so, the concept of culture has become an important issue that has been heightened with the realisation that, through technolog y and markets, organisations are becoming increasingly global (Kobrin, in Joynt & Warner, 1996). Erwee, Lynch, Millett, Smith and Roodt (2001) very well summarise the current status in respect of organisational culture by stating that it remains one of the most contested areas of academic inquiry within the broader field of organisational studies. It is characterised by competing definitions, epistemologies and research paradigms. Controversies exist about virtually all aspects of this construct including the mechanics and extent of its contribution to organisational performance. However, there is considerable consensus about the importance of organisational culture. In South Africa additional factors necessitate that organisations gain sound insight into their own cultures. South Africa is a highly heterogeneous society, consisting of many cultural groupings, which manifest in the work place. South Africa has been undergoing major transformation since becoming a democracy and being accepted as a full participant in the global economy. South Africa’s success in the global economy will be positively or negatively affected by the ability of individual companies and industries to adapt their cultures to fit the global challenges, without losing their unique characteristics. Organisational culture is the very fibre of the organisation. Thus the culture equates to the personality of the organisation (Kilmann, Saxton, Serpa & Associates 1985), which can either facilitate or restrain change and performance. Differently stated, one can safely say that an organisation has successfully changed only after its culture has changed. For this reason it is crucial to fully understand the culture of the organisation, as well as how it develops and can be changed. The Culture Assessment Instrument (Martins, 1989) represents one line of inquiry in the field of organisational culture. Martins (1989, p. 45) defined organisational culture as follows: “Organisational culture is an integrated pattern of human behaviour, which is unique to a particular organisation and which originated as a result of the organisation’s sur vival processes and interaction with its environment. Culture directs the organisation to goal attainment. Newly appointed employees must be taught what is regarded as the correct way of behaving.” The definition of Martins closely resembles the most commonly accepted definition of culture, i.e. the one by Schein (1985, p. 9): “A pattern of basic assumptions – invented, discovered, or developed by a group as it learns to cope with its problems of external adaptation and internal integration – that has worked well enough to be considered valid and, therefore, to be taught to new members as the correct way to perceive, think and feel in relation to those processes.” Schein (1985) identified three levels of culture, i.e. artefacts, values and assumptions (See Figure 1). Insight into these levels are fundamental to understanding the culture of organisations. Artefacts are visible, tangible and audible demonstration of behaviour supported by organisational norms, values and assumptions. Artefacts range from physical aspects such as architecture to forms of language to rituals. Values represent the principles and standards valued by organisational members. Values are the foundation as to what is acceptable and what is not acceptable. Assumptions and beliefs are the basis of an organisation’s culture. Where solutions to a problem work continuously, the solution is used unconsciously and becomes the way things are done by the group. Assumptions are the basis for how organisational members think and feel. Assumptions are unconscious and are taken for granted (Schein, 1985). To fully understand the complexity of the organisational culture literature, it is necessary to note the various perspectives of culture (Wilson, 2001). LEO PETKOON GERT ROODT Department of Human Resource Management Rand Afrikaans University ABSTRACT The primary purpose of this study was to assess the discriminant validity of the Culture Assessment Instrument (CAI); that is to distinguish between company mean sub-culture scores and between mean scores of a target company and that of a norm group. The primary data was obtained by a sample of convenience (N = 593) from a transport organisation. The secondary data of the norm group was constituted by convenience samples (N = 4066) from various companies originating from different industries. The 56 item scores of the CAI were factor analysed on two levels followed by iterative item analyses. Although significant differences were detected between mean culture scores, only a small proportion of the variance in these scores could be attributed to culture differences. On these grounds, the CAI does not possess discriminant validity. Suggestions for improving the CAI were made. OPSOMMING Die primêre doel van die studie was om die diskriminante geldigheid van die ‘Culture Assessment Instrument’ (CAI) te beoordeel; dit is om tussen ondernemings se gemiddelde kultuur-subtelling te onderskei en tussen die gemiddelde tellings van ‘n teiken onderneming en ’n normgroep. Die primêre data is verkry van ’n geleentheidsteekproef (N = 593) uit ’n transport-onderneming. Die sekondêre data van die normgroep is saamgestel uit geleentheidsteekproewe (N = 4066) van verskillende ondernemings afkomstig uit verskeie industrieë. Die 56 itemtellings van die CAI is op twee vlakke gefaktoranaliseer, gevolg deur iteratiewe itemontledings. Ofskoon beduidende verskille tussen gemiddelde kultuurtellings gevind is, kon slegs ’n klein proporsie van die variansie in die tellings aan kultuurverskille toegeskryf word. Op hierdie gronde beskik die CAI nie oor diskriminante geldigheid nie. Voorstelle ter verbetering van die CAI is gemaak. THE DISCRIMINANT VALIDITY OF THE CULTURE ASSESSMENT INSTRUMENT: A COMPARISON OF COMPANY SUB-CULTURES Requests for copies should be addressed to: G Roodt, Department of Human Resource Management, RAU University, PO Box 524, Auckland Park, 2006 46 SA Journal of Industrial Psychology, 2004, 30 (1), 46-54 SA Tydskrif vir Bedryfsielkunde, 2004, 30 (1), 46-54 CULTURE ASSESSMENT INSTRUMENT 47 Figure 1: Schein’s Levels of Culture Adapted from Schein (1985, p.14) Perspectives of Organisational Culture Martin and Meyerson (1988) identified three major perspectives in organisational culture research, i.e. the integration perspective; the differentiation perspective, and the fragmentation perspective. The integration perspective portrays a strong or desirable culture as one where there is organisation-wide consensus and consistency. Espoused values are consistent with formal practices, which are consistent with informal beliefs, norms and attitudes. Cultural members share the same values, promoting a shared sense of loyalty and commitment. Where inconsistencies, conflict or subcultural differentiation occur, this is portrayed as being a weak or negative culture. The differentiation perspective emphasises that rather than consensus being organisation-wide, it only occurs within the boundaries of a subculture. At the organisational level, differentiated subcultures may co-exist in harmony, conflict or indifference to each other. Van Maanen (1991), in his study of an organisation, found groups of employees who considered themselves as being distinct. These sub-cultures related to different jobs, different levels of organisational status, gender and class. Claims of harmony from management masked a range of inconsistencies and group antagonisms. What is unique about a given organisation’s culture, then, is the particular mix of subcultural differences within an organisation’s boundaries. The fragmentation perspective views ambiguity as the norm, with consensus and dissension co-existing in a constantly fluctuating pattern influenced by events and specific areas of decision making. As stated by Frost, Moore, Louis, Lundberg, and Martin (1991), consensus fails to coalesce on an organisation-wide or subcultural basis, except in transient, issue- specific ways. Rather than the clear unity of the integration perspective, or the clear conflicts of the differentiation viewpoint, fragmentation focuses on that which is unclear. Many of the studies in organisational culture focus on only one of these perspectives, arguing whether it and it alone is evident within the organisation. Martin and Meyerson (1988) argued that any cult ure contains elements that can be understood only when all three perspectives are used. Therefore, within a company there may be organisation-wide consensus on some issues, consensus only within certain subcultures on other issues and an ambiguous state on the remainder. Schein, in Frost et al. (1991), suggested that there may be a core set of ideological guidelines within an organisation that require a minimal consensus and consistency, otherwise organisations would not function. Therefore consistency, consensus, harmony and integration may occur, but within the midst of inconsistencies, ambiguities, conflicts, disruption and dissolution. Noting the complexities associated with the different perspectives described above, this study is carried out from the differentiation perspective, which emphasises that rather than consensus being organisation-wide, it only occurs within the boundaries of a subculture. Measuring Organisational Culture Although the concept of organisational culture has been prominent in organisational and management literature since the 1970s (Barley, Meyer, & Gash, 1988), scholars still disagree on the best way to measure it (see O’Reilly, Chatman, & Caldwell, 1991; Rousseau, 1990). Some authors have suggested the use of multiple methods (e.g., Martin, 1992; Rousseau, 1990), but these methods are often complex, expensive, and time-consuming (Ashkanasy, Broadfoot & Falkus, 2000). Among authors who suggest some use of quantitative measures are Amsa (1986), Barnett (1988), Bookbinder (1984), Cooke and Rousseau (1988), Desatnick (1986), Hofstede (1986), Reynierse (1986), Reynierse and Harker (1986), Reynolds (1986) and Wiener (1988). Scholars such as Martin (1992) noted that quantitative assessment of organisational culture has been criticised in the past because of a strong mono-method bias in the field. Although Martin argues for a need to include qualitative data in culture studies, the essence of her case is that there is a need for a multilevel and multi-method conceptualisation. In this respect, Schein’s (1985) three level typology provides a distinctive role for both quantitative and qualitative measurement. As the elements of culture become more conscious and observable to participants in a study, they become more accessible to standardised assessment (Rousseau, 1990). For example, it is generally agreed that surveys represent an efficient and standardised means of tapping the shallower levels of Schein’s typology. The deepest level of culture, on the other hand, can be investigated only through more intensive observation, focused interviews, and the involvement of organisational members in self-analysis (Ott, 1989; Rousseau, 1990; Schein, 1990). The thrust of this argument is that there is a clear and continuing role for quantitative measures as a means of assessing the less abstract levels of organisational culture. All quantitative measures of culture are likely to suffer from the same limitations, with the main weakness being that basic assumptions are often non-debatable and unconscious. People’s written or oral answers to questions are not necessarily indicative of their basic assumptions. The usefulness of quantitative measurement may not be restricted to the shallower grounds for maintaining that the three levels of culture are unified especially when a culture is strong. In this case, quantitative measurement of organisational culture may have the potential to tap deeper levels of culture (Ott, 1989; Rentsch, 1990). Ashkanasy et al. (2000) noted that survey methods have characteristics that render them especially useful for organisational culture research. Self-report surveys allow respondents to record their own perceptions of reality. Because behaviour and attitudes are determined not by objective reality but by actors’ perceptions of reality (Rentsch, 1990), it is clearly appropriate to focus on perceptions rather than on reality. Further, self-report measures offer internal credibility to organisational members, which is likely to increase the likelihood that members will accept the results of the survey. Researchers have cited numerous other advantages of survey assessment and of quantitative techniques generally. These include allowing replication and cross-sectional comparative studies, providing an accepted frame of reference for interpreting data, helping the evaluation and initiation of PETKOON, ROODT48 culture change efforts in organisations, and providing data that can be analysed through multivariate statistical techniques (Cooke & Rousseau, 1988; Xenikou & Furnham, 1996). In summary, what is borne out by the literature, is that questionnaires can play an important role in the quantitative analysis of organisational culture (Reichers & Schneider, 1990) A Need for Assessing Discriminant Validity Hofstede (1980) defined culture as the “collective programming of the mind, which distinguishes the members of one category of people from another.” This definition stresses that culture is collective and not a characteristic of individuals (shared values); is interesting only to the extent that it differentiates between categories of people (Maull et al., 2001). Yet, despite the fact that it’s the differences in culture that makes it an interesting phenomenon, the literature review revealed that reporting on the ability of organisational culture instruments to assess cultural differences bet ween companies is grossly neglected The literature often reports on the consensual, construct, and criterion validit y of organisation culture instruments (Ashkanasy et al., 2000), but not the discriminant validity of the instruments. Hence, clearly there is a need to assess the discriminant validity of organisational culture instruments. This need is addressed in this study. METHOD The research participants For this study two sets of data were used. The primary data were obtained from a sample drawn from the departments (seven) of a transport organisation. It yielded 593 responses (See Table 1). The secondary data set consists of a convenience sample of 4066 participants from five different organisations from various industries. TABLE 1 RESPONSES PER DEPARTMENT Responses Freq. Percent Cumul. Asset Life Cycle Management 99 16,7 16,7 Railway Engineering 100 16,9 33,6 Evaluation, Acquisition and Review 32 5,4 39,0 Traction 88 14,8 53,8 Wagons 70 11,8 65,6 Governance 16 2,7 68,3 Infrastructure Maintenance 188 31,7 100,0 Total 593 100,0 100,0 Table 2 provides a brief overview of the biographical properties of the respondents in the survey sample and the norm group. From Table 2 it can be inferred that the majority of respondents in the survey sample are white, male, and in the age group 36 – 45, whilst the majority of respondents in the norm group are white, male, Afrikaans speaking and in the age group 25 – 35. Broadly speaking the attributes of the survey sample and the norm group are very similar. The measuring instrument The items included in the measuring instrument (Culture Assessment Instrument) were developed by Martins (1989). The original questionnaire, the Organisational Culture Survey consisted of 89 items. However, only 56 items (renamed as the Culture Assessment Instrument), common to all the organisations in the sample of the secondary data set, were included in the study. These 56 items are proportionally representative of the six dimensions of the questionnaire. The overall reliabilit y (Cronbach Coefficient Alpha) of the instrument is 0,933. The internal consistencies of the dimensions vary between 0,655 and 0,932. TABLE 2 BIOGRAPHICAL VARIABLES NORM GROUP TRANSPORT ORGANISATION Category Count % Count % RACE White 1086 44,9% 409 69% Coloured 294 12,2% 19 3,2% Indian 125 5,2% 21 3,5% Black 912 37,7% 144 24,3% Total 4066 100% 593 100% AGE 24 and younger 438 11,3% 8 1,3% 25 – 35 1808 46,5% 166 28,0% 36 – 45 1006 25,9% 186 31,4% 46 and more 638 16,4% 233 39,3% Total 4066 100% 593 100,0% GENDER Male 2034 52,0% 512 86,3% Female 1876 48,0% 81 13,7% Total 4066 100% 593 100,0% LANGUAGE Afrikaans 1014 80,5% * * English 225 17,9% * * Other 21 1,7% * * Total 4066 100% * * The theoretical model, which underpins the CAI, is depicted in Figure 2. According to Martins (1989) an organisation is a complex social system in which individual and group activities take place. The various subsystems together form the culture of the organisation. Organisational culture influences the behaviour of employees, suppliers and customers as well as the organisation’s relationship with the community. Culture has an effect on the internal as well as the external environment and is in turn influenced by both environments. The reason being that the organisation has to continuously adapt to the external environment. In order for the organisation to adapt to the external environment its internal processes have to change and adapt on a continuous basis. From Figure 2 it can be seen that the model consists of three main elements, i.e. the organisational system, survival functions and dimensions of culture. The organisational system consists of five subsystems i.e., goal-, technical-, struct ural-, psychosocial-, and management subsystem. These five subsystems form the internal subsystem. The external system consists of the environment in which the organisation operates. The organisation thus has to stay abreast of shareholders, customers, competitors, the communit y, as well as political, stat utory, economic and ecological factors. The way, in which all the external factors are dealt with, could have a major impact on the success and survival of the organisation. As a result of the interact ion and reciprocal inf luence of the various subsystems on one another, a unique cult ure is created in each organisation, which makes it unique and distinguishes it from other organisations. CULTURE ASSESSMENT INSTRUMENT 49 From Figure 2 it is clear that the two main variables that must be taken into account in assessing the culture of an organisation are the problems of survival and adaptation of the organisation to the (a) external environment and (b) the internal organisational system. Dimensions of culture are subdivided into two categories, i.e. those that relate to the external environment and those that relate to the internal environment (See Figure 2). Dimensions relating to the external environment are: a) Strategy, mission, goals and objectives; b) Shareholders, customers, competitors and community; and c) The means to reach goals. Dimensions relating to the internal environment are: a) Employees in the organisation; b) Interpersonal relations; c) Management processes; and d) Management orientation. The research procedure The primary data set was obtained from a sample drawn from a transport organisation, whilst the secondary data set was built from data gathered from participating organisations over the last few years. The primary and secondary data were originally gathered mainly with a view to improve the performance of the specific organisations. The main difference between the analysis of organisational culture between the primary and secondary data is that the organisations in the secondary data were also researched by means of interviews and focus groups to analyse the deeper levels of organisational culture. The aim of gathering the information was thus the same in all the cases. Statistical analysis The statistical procedures were selected for their suitability to test the research hypotheses of the study. These procedures include descriptive statistics, factor analyses and analyses of variance. In respect of factor analyses a procedure developed by Schepers (1992) was followed. This procedure includes first as well as second levels factor analyses. The Statistical Consultation Service of the Rand Afrikaans University conducted the analyses. All calculations were done by means of the SPSS- Windows program of SPSS – International. RESULTS First level factor analysis on the inter-correlation matrix The 56 items of the Culture Assessment Instrument were intercorrelated and rotated to a simple structure by means of the Varimax rotation. Owing to limited space, the intercorrelation matrix (56 x 56) is not reproduced here. Twelve factors were postulated according to Kaiser’s (1961) criterion (eigenvalues-greater-than-unity) and extracted by means of a principal factor analysis, also called Principal Axis Factoring. The factor matrix obtained was rotated to simple structure by means of Varimax rotation. The t welve factors explain about 60% of the variance in the factor space. Subse- quently, sub-scores (SS) were calculated on the t welve obtained factors and they were subjected to a second level factor analysis. Second level factor analysis on the inter-correlation matrix The twelve sub-scores (obtained from the first factor analysis) were inter-correlated and the results of the inter-correlation of the sub-scores are displayed in Table 3. During second level factor analysis t wo factors were extracted by means of a principal factor analysis according to Kaiser’s (1961) criterion (eigenvalues-greater-than- unit y). Table 4 provides the eigenvalues of the unreduced factor matrix. From Table 4 it can be seen that these t wo factors explained about 58% of the variance in the factor space. Figure 2: A Model of Organisational Culture (Martins, 1989, p.92) PETKOON, ROODT50 TABLE 4 EIGENVALUES OF THE UNREDUCED INTER-CORRELATION MATRIX OF SUBSCORES EXPLAINED Initial Eigenvalues Root Eigenvalue % of Variance Cumulative % 1 5,858 48,819 48,819 2 1,103 9,191 58,010 3 0,893 7,443 65,453 4 0,659 5,489 70,942 5 0,641 5,338 76,280 6 0,566 4,719 80,999 7 0,550 4,580 85,578 8 0,479 3,988 89,566 9 0,343 2,857 92,424 10 0,333 2,776 95,200 11 0,307 2,555 97,755 12 0,269 2,245 100,000 Trace = 12 TABLE 5 SORTED AND ROTATED FACTOR MATRIX OF SUBSCORES Sub Scores Factor 1 2 SS2 0,878 SS3 0,834 SS1 0,830 SS12 0,707 SS4 0,679 SS8 0,645 SS6 0,635 SS5 0,597 SS9 0,591 SS10 0,791 SS7 0,473 SS11 0,222 The sorted and rotated factor matrix appears in Table 5. Scale One represents Culture excluding Opportunity and Scale Two is referred to as “Opportunity”. For convenience sake Scale One will generally be referred to as “Culture”. The sub-scores on the CAI data set were subsequently forced into a one factor solution to enable comparison with the norm group. The factor matrix for the one factor solution appears in Table 6. TABLE 6 SUB-SCORE LOADINGS ON A SINGLE FORCED FACTOR Sub Scores Factor 1 h 2 j SS1 0,841 0,707 SS4 0,818 0,670 SS2 0,807 0,651 SS3 0,771 0,595 SS8 0,739 0,547 SS5 0,690 0,475 SS6 0,667 0,444 SS12 0,631 0,398 SS9 0,612 0,374 SS7 0,541 0,293 SS10 0,439 0,193 SS11 0,201 0,040 Extraction Method: Principal Axis Factoring. a 1 factors extracted. 4 iterations required. An iterative item analysis procedure was conducted on the scales 1 and 2 as well as the single scale and high Cronbach Coefficients Alpha of 0,954; 0,707 and 0,953 were respectively obtained. Table 7 provides the item statistics for the single scale. Analyses of variance: comparison of internal sub-cultures and comparison with the norm group In order to test Hypothesis 1, which states that there are significant differences in mean culture scores between the sub- cultures based on demographic variables of the transport organisation, and Hypothesis 2, which states that there are significant differences in mean culture scores between sub- cultures based on various functional departments of the transport organisation, a multivariate analysis of variance was conducted on the two scales. TABLE 3 MATRIX OF INTER-CORRELATIONS OF 12 SUB-SCORES (SS) S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 SS1 1,000 SS2 0,678 1,000 SS3 0,669 0,651(**) 1,000 SS4 0,698 0,637(**) 0,586(**) SS5 0,591 0,580(**) 0,497(**) 0,569(**) 1,000 SS6 0,564 0,586(**) 0,511(**) 0,519(**) 0,500(**) 1,000 SS7 0,403 0,384(**) 0,393(**) 0,469(**) 0,413(**) 0,340(**) 1,000 SS8 0,635 0,587(**) 0,652(**) 0,578(**) 0,471(**) 0,469(**) 0,412(**) 1,000 SS9 0,505 0,486(**) 0,488(**) 0,497(**) 0,455(**) 0,383(**) 0,332(**) 0,420(**) 1,000 SS10 0,345 0,264(**) 0,265(**) 0,421(**) 0,292(**) 0,289(**) 0,438(**) 0,373(**) 0,254(**) 1,000 SS11 0,151 0,185(**) 0,084(*) 0,173(**) 0,184(**) 0,142(**) 0,138(**) 0,147(**) 0,102(*) 0,185(**) 1,000 SS12 0,538 0,547(**) 0,506(**) 0,579(**) 0,355(**) 0,418(**) 0,290(**) 0,452(**) 0,438(**) 0,207(**) 0,072 1,000 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). N = 593 CULTURE ASSESSMENT INSTRUMENT 51 TABLE 7 RELIABILITY ANALYSIS – SCALE (ALPHA) Scale Mean Scale Variance Corrected Alpha if if Item if Item Item – Total Item Deleted Deleted Correlation Deleted Q2 170,162 891,011 0,436 0,953 Q3 170,798 875,121 0,589 0,952 Q4 170,570 874,874 0,592 0,952 Q5 170,911 874,007 0,559 0,952 Q6 170,892 878,174 0,469 0,953 Q7 170,263 880,367 0,509 0,953 Q8 170,767 884,368 0,413 0,953 Q10 170,690 886,444 0,475 0,953 Q11 170,474 885,344 0,579 0,953 Q12 170,499 879,933 0,534 0,953 Q13 170,465 888,378 0,384 0,953 Q14 170,592 877,793 0,526 0,953 Q15 170,374 878,164 0,484 0,953 Q19 171,044 875,738 0,511 0,953 Q20 171,086 877,555 0,452 0,953 Q21 170,562 885,328 0,419 0,953 Q23 171,390 878,647 0,409 0,953 Q24 171,218 880,116 0,530 0,953 Q25 171,634 881,756 0,413 0,953 Q26 170,499 895,521 0,203 0,954 Q27 170,897 884,873 0,409 0,953 Q28 171,933 883,678 0,492 0,953 Q29 170,673 879,619 0,519 0,953 Q30 170,796 878,933 0,521 0,953 Q31 170,842 877,725 0,555 0,953 Q33 170,793 883,188 0,513 0,953 Q34 170,648 877,323 0,645 0,952 Q37 171,064 876,378 0,584 0,952 Q38 170,577 873,785 0,617 0,952 Q40 170,968 868,453 0,711 0,952 Q44 171,477 878,355 0,565 0,952 Q45 170,889 875,910 0,552 0,953 Q46 171,196 877,354 0,491 0,953 Q47 170,631 882,993 0,460 0,953 Q49 170,880 875,808 0,613 0,952 Q50 170,159 883,282 0,539 0,953 Q51 171,300 877,342 0,578 0,952 Q53 170,988 873,606 0,642 0,952 Q55 170,096 888,253 0,478 0,953 Q56 170,127 889,351 0,451 0,953 Q58 170,619 877,108 0,578 0,952 Q59 170,110 890,936 0,395 0,953 Q61 169,366 904,790 0,196 0,954 Q63 170,639 878,718 0,554 0,953 Q64 171,464 884,357 0,408 0,953 Q66 170,361 890,525 0,462 0,953 Q67 170,363 880,123 0,588 0,952 Q68 170,533 884,638 0,473 0,953 Q69 170,702 877,700 0,539 0,953 Q70 170,557 881,234 0,517 0,953 Q71 169,858 891,774 0,357 0,953 Q72 170,772 876,798 0,617 0,952 Q73 170,705 875,073 0,639 0,952 Q74 170,496 875,896 0,617 0,952 Q75 170,405 878,819 0,602 0,952 Q76 170,567 877,189 0,633 0,952 Reliability Coefficients N of Cases = 593 N of Items = 56 Alpha = 0,953 In order to test hypothesis 3, which states that there are significant differences in mean culture scores between the transport organisation and organisations in the norm group, an univariate analysis of variance was conducted on the scores of the single scale. The main findings, based on the results of the analyses of variance, summarised in Table 8, are: � Respondents with less than 10 year’s service are more positive than respondents with more than 10 years service about opportunities in the organisation. � Respondents in the age group 46-54 are least positive, whilst respondents in the age group 36-45 are most positive about the culture of the division. � Respondents in the age groups 46 years and older feel negative about opportunity, while respondents in the age group 45 years and younger feel positive about opportunity in the company. � Females are significantly more positive than males in respect of both culture and opportunity in the company. � Blacks are positive about opportunity, while whites are negative about opportunity in the company. � Management is negative about opportunity, while junior officials are positive, although not highly positive about opportunity. � Governance is significantly more positive about culture than the rest of the departments. � Governance is significantly more positive than the rest of the departments about opportunity, It must be kept in mind that the above findings are based on the significance of differences in variance bet ween groups, the percentage of variance attributable to differences in cult ure scores are in most cases very low or nearly insignificant in proportion, based on Partial Eta Squared. The percentage of variance explained in all these findings varies bet ween 2% and 8% with one exception, i.e. the variable “race” on Scale 2, in which case 17% of the variance is explained. Based on above findings Hypothesis 1, which states there are significant differences in mean culture scores between the sub- cultures based on demographic variables of the transport organisation as well as Hypothesis 2, which states that there are significant differences in mean culture scores between sub- cultures based on various functional departments of the transport organisation, are rejected. These findings imply that the Culture Assessment Instrument (consisting of 56 items) only possess very limited internal discriminant validit y, because only very small proportions of variance could be accounted for. In comparing the culture of the transport organisation with the organisations in the norm group further analyses were conducted to counter the effects of sample size. The statistical procedures carried out for this purpose, are the Chi-square and the Partial Eta Squared. The results of these statistics revealed that there are significant differences in mean culture scores , but only 1,5% of the variance could be explained after provision was made for difference in sample size. Based on these results Hy pothesis 3, which states that there are significant differences in mean culture scores between the transport organisation and organisations in the norm group, is also rejected. DISCUSSION It is clear from the factor and the item analyses that the construction of the CAI is based on a number of sound psychometric principles. The CAI complies with most of the criteria, which according to Schepers (1992) as cited in Swart, PETKOON, ROODT52 Roodt and Schepers (1999) are important in constructing a questionnaire: � The construct “culture” is theoretically clearly founded. � There is no doubt about which domain the construct belongs to, i.e. “organisational culture” � Sub domains were identified, i.e. Mission/Vision; Management Processes; Employee Needs and Objectives; External Environment; Means to Achieve Objectives; and Interpersonal Relations. � Behavioural indicators were identified for the sub domains. These behavioural indicators were used to link the theoretical concepts with the empirical variables. The one criterion that was somewhat neglected is item format. Item format is important to ensure that the questions support the behavioural indicators. Item format covers aspects such as the correct use of language, questions versus statements, the type of response scale and the instructions of the instrument. The correct use of these elements influences the validity of the questionnaire. In the construction of the CAI these guidelines were not strictly applied. As far as the questionnaire response scale is concerned, the questionnaire uses a 5-point Likert response scale where all the response categories are labelled. According to Schepers (1992) the equal interval qualit y of a scale is lost if more than t wo points are anchored. Schepers (1992) recommended that it is better to use an intensit y response scale where only the t wo extreme categories are labelled as depicted in Figure 3. 1 2 3 4 5 Strongly disagree Strongly agree Figure 3: Proposed Intensity Response Sale The factor analyses resulted in two robust factors that indicate a fairly sound theoretical basis as well as a sound procedure in the construction of the CAI. This assumption is supported by a high internal consistency of 0,953. This indicates a high reliability and only a limited amount of error variance in the measurement of the construct “organisational culture”. The results of the analysis of variance revealed that there are differences in mean culture scores between the demographic variables and the departments in the transport organisation and between the transport organisation and the norm group. However, only a limited portion of these differences could be attributed to differences in cultures. However, based on the literature review, a priori differences in cultures between demographic variables and departments and organisations, especially if they are from various industries, were postulated. The CAI did not detect these differences. It can thus be inferred that the instrument does not possess the abilit y to distinguish differences in sub-cult ures in an organisation or in cult ures bet ween organisations from different industries. These findings suggest that the CAI lacks discriminant validity. TABLE 8 ANALYSIS OF VARIANCE: COMPARISON OF INTERNAL SUB-CULTURES LEVENE’S TEST ANOVA POST HOC TEST Partial Eta Squared Mean Difference Scale F-Ratio Df1 Df2 P(F) Df F-Ratio P(F) (1) (J) (I-J) (P) Tenure 1 1,365 1 591 0,243 1 0,175 0,676 0,000 2 3,719 1 591 0,054 1 52,586 0,000 0,082 Age 1 3,027 3 589 0,029 3 4,243 0,006 0,021 36-45 46-54 0,208* 0,003 2 0,898 3 589 0,442 3 14,258 0,000 0,068 <35 46-54 0,392* 0,000 <35 �55 0,367* 0,002 36-45 46-54 0,298* 0,000 36-45 �55 0,274* 0,034 Gender 1 0,133 1 591 0,715 1 19,429 0,000 0,032 2 3,603 1 591 0,058 1 16,422 0,000 0,027 Race 1 13,492 1 493 0,000 1 1,527 0,217 0,003 2 1,272 1 493 0,260 1 101,922 0,000 0,171 Grade 1 1,692 2 590 0,185 2 2,028 0,132 0,007 2 4,986 2 590 0,007 2 5,285 0,005 0,018 Jnr Off Snr Mng 0,189* 0,021 Jnr Off Jnr Mng 0,164* 0,017 Department 1 6,505 6 586 0,000 6 3,515 0,002 0,035 Governance EAR 0,543* 0,035 Governance Traction 0,654* 0,004 Governance Infra 0,518* 0,028 2 2,370 6 586 0,029 6 3,174 0,005 0,031 * The mean difference is significant at the 0.05 level CULTURE ASSESSMENT INSTRUMENT 53 On the other hand the CAI reliably assessed commonalities in culture between organisations. This is the strength of the instrument. It is good at detecting commonalities between entities. See Figure 4 for a graphic representation of what the findings suggest. In Figure 4 each circle represents a different entity and the shaded area represents the similarities between the entities, as identified by the instrument. The areas not shaded represent the unique differences between the entities, not identified by the instrument. Figure 4: Similarities between Entities These commonalities, however, are mainly at surface level – the level of artefacts and creations with reference to Schein’s (1985) three-level typology (See Figure 1). At this level entities may appear to have the same culture. The reason for this phenomenon is that organisations are quick to embrace the latest management tools and practices in their striving to keep up with the fast changing business environment. There is a possibility that the instrument detected these practices which are common to all organisations. In sum, the instrument identifies similarities at surface level but not differences at the deeper levels. The scale was designed for the tangible, espoused level (the level of practice if you wish) but not for the deeper (unconscious) level of tacit values and basic assumptions. Inferences can be made about the deeper levels, but the items in the instrument did not purposefully and systematically expose the deeper levels of organisational culture. Emanating from the findings of the literat ure and the empirical research it is recommended that further research be undertaken to operationalise the construct organisational culture at the deeper levels, which are, the levels of tacit values, taken for granted assumptions and basic beliefs. The authors believe that with proper operationalisation at the more fundamental levels it will be possible to successfully distinguish cultures bet ween entities from the positivistic paradigm. 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