8-DuToitRoodt.qxd ORGANISATIONAL CULTURE A review of the literature revealed that the construct “organisational culture” 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 extend of its contribution to organisational performance (Erwee, Lynch, Millett, Smith & Roodt, 2001). According to Ajiferuke and Boddewyn’s (1970, p.154) “there are almost as many meanings of culture as people using the term”. Kroeber and Kluckhohn (1952) already suggested in 1952 that there were as many as 164 meanings of the term “culture’’. Since then it was hoped that the field may have been further refined and a more “common’’ definition may have been agreed upon. Instead, what culture is and the nature of it are still hotly contested (Bolman & Deal, 1991). Fortunately, some areas of overlap can be discerned. Most basic is that there seems to be general agreement that organisational cultures are based in sets of meanings shared by some groups of people. This focus on what is shared has been neglected by other constructs used to study organisations and thus gives the culture construct a useful distinctiveness for organisational research (Beyer, Hannah & Milton, 2000). The Culture Assessment Instrument (Martins, 1989) represents one line of inquiry in the field of organisational culture. Martins (1989, p. 45) defines 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.” This definition of culture conforms to Green’s (1989) notion of culture as the organisation’s equivalent of the individual’s personality. Culture provides an underlying pattern to the behaviour of organisations, just as personality provides an underlying pattern to the behaviour of the individual. Fundamental to the development of the CAI is the belief that organisational culture can be defined in terms of a set of uniform dimensions or characteristics. This approach falls firmly within the positivistic approach of culture (Denison, 1996). Within this perspective the central aim is the development of a set of dimensions across which culture could be compared (Denison, 1996) and measured and hence more effectively managed (Erwee et al., 2001). Groeschl and Doherty (2000) pointed out that culture consists of several elements of which some are implicit and others are explicit. 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. Figure 1: Schein’s Levels of Culture Adapted from Schein (1985, p.14) WILLIE DU TOIT GERT ROODT Department of Human Resource Management Rand Afrikaans University ABSTRACT The aim of this study was to assess the discriminant validity of the Culture Assessment Instrument (CAI); that is to distinguish between mean culture scores of different companies. The convenience sample consisted of 4066 respondents from five different companies, originating from various industries. CAI scores of 56 items were factor analysed on two levels, followed by iterative item analyses. Significant differences between company mean scores were identified, but only a small portion of the variance in these scores could be ascribed to culture differences. Based on these findings, it was concluded that the CAI in its current form does not possess discriminant validity. It is recommended that items attuned to deeper levels of culture, based on Schein’s three-level typology, be added to the instrument. OPSOMMING Die doel van die studie was om die diskriminante geldigheid van die ‘Culture Assessment Instrument’ (CAI) te beoordeel; dit is om tussen gemiddelde kultuurtellings van verskillende ondernemings te onderskei. Die geleentheidsteekproef het bestaan uit 4066 respondente uit vyf verskillende ondernemings afkomstig uit verskeie industrieë. CAI-tellings van 56 items is op twee vlakke gefaktoranaliseer, gevolg deur iteratiewe itemontledings. Beduidende verskille tussen ondernemings se gemiddelde kultuurtellings is gevind, maar slegs ’n klein proporsie van die variansie in die tellings kon aan kultuurverskille toegeskryf word. Gebaseer op hierdie bevindinge, is daar tot die slotsom gekom dat die CAI in sy huidige vorm nie oor diskriminante geldigheid beskik nie. Daar is aanbeveel dat items gerig op dieper kultuurvlakke, gebaseer op Schein se drievlaktipologie, tot die instrument gevoeg word. THE DISCRIMINANT VALIDITY OF THE CULTURE ASSESSMENT INSTRUMENT: A COMPARISON OF COMPANY CULTURES Requests for copies should be addressed to: G Roodt, Department of Human Resource Management, RAU University, PO Box 524, Auckland Park, 2006 77 SA Journal of Human Resource Management, 2003, 1 (1), 77-84 SA Tydskrif vir Menslikehulpbronbestuur, 2003, 1 (1), 77-84 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). 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 subcult ure. 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 subcult ural 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 culture 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. Not ing the complexit ies associated with the different perspectives described above, this study is carried out from the integration perspective, where cultural members share the same values, promoting a shared sense of loyalt y and commitment. 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). Following are examples of different ways of measuring organisational culture. Reynierse and Harker (1986) used a combination of quantitative and qualitative measures to measure culture. The qualitative methods involve interviews and group discussions, while the quantitative method, which they call organisational dynamics, is a survey questionnaire using 95 items on a five-point ordinal scale of definite agreement to definite disagreement. The method aims to provide managers with tangible feedback in managing culture, their “fundamental proposition” being “that you can’t manage organisational culture unless you can measure it” (Reynierse & Harker, 1986, p. 1). Reynolds (1986) used a questionnaire to measure culture differences between organisations to see if the measured differences relate to differences in performance. Barnett (1988) outlined details of what he calls a “Galileo tm” or “Galileo analysis” for measuring culture accurately. Some of the methods are common to those used in qualitative approaches, but Barnett quantifies the results. It is considered that the method is too narrow, using only language, symbols and concepts as measurable elements. Wiener (1988) measured “central value systems” and believes that by measuring the intensity and breadth of key values, one can measure culture. Nossiter and Biberman (1990, p.13) used a technique for studying and diagnosing culture they call “projective drawing and metaphorical analogy fantasising”, where questionnaires ask participants to draw an image and name an animal representing their organisation and department. They believe that the creativity involved may motivate employees to think more about their organisations. Tucker, McCoy, and Evans (1990) designed a comprehensive questionnaire, developed from interviews and discussions with 50 managers of organisations. They believe results from the questionnaire, which are quantified, will help provide some preliminary information on the organisation’s culture to managers attempting to deal with particular situations and problems with their cultures. Gabriel (1991) saw stories as the basis for the myths that act as coping mechanisms for individuals in organisations. Most of these techniques are as yet too recent for much empirical testing to have been carried out on them. A Case for Quantitative Measurement 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, DU TOIT, ROODT78 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 provided 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. (2000a) 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 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, but not the discriminant validity of the instruments (Ashkanasy, Wilderom & Peterson, 2000). 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 A convenience sample, consisting of 4066 participants from five different companies originating from various industries, was used. Particulars of organisations that are included in the study are provided in Table 1. From Table 1 it is clear that there are significant differences in sample size (ranging from 119 to 2459) between the different organisations. Noting that sample size effects levels of significance, due consideration was given to it during the analysis phase. TABLE 1 PARTICIPATING ORGANISATIONS Company No. Organisation N 1 Bank 1056 2 Bank – Home Loans 219 3 Retail 119 4 Information Technology 213 5 Services – Parastatal 2459 Total 4066 Table 2 provides a brief overview of the biographical properties of the survey sample. From Table 2 it can be inferred that the majority of respondents are white, male, Afrikaans speaking and in the age group 25 – 35. TABLE 2 BIOGRAPHICAL VARIABLES Category Count % Race White 1086 26.71% Coloured 294 7.23% Indian 125 3.07% Black 912 22.43% No response 1649 40.56% Total 4066 100% Age 24 and younger 438 10.77% 25 – 35 1808 44.47% 36 – 45 1006 24.74% 46 and more 638 15.69% No response 176 4.33% Total 4066 100% Gender Male 2034 50.02% Female 1876 46.14% No response 156 3.84% Total 4066 100% Language Afrikaans 1014 24.94% English 225 5.53% Other 21 0.52% No response 2806 69.01% Total 4066 100% The measuring instrument The measuring instrument (Culture Assessment Instrument) was developed by Martins (1989). The latest version of the CAI consists of 89 items, but only 56 items, that were common to all the companies in the sample, were included in the study. These 56 items are proportionally representative of the six dimensions of the questionnaire. The overall reliabilit y (Cronbach DISCRIMINANT VALIDITY OF THE CAI 79 Coefficient Alpha) of the 5-point response scale version of the instrument, used in this study, is 0,933. The internal consistency of the dimensions varies between 0,655 and 0,932. 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 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 -, structural -, 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 community, as well as political, statutory, 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 interaction and reciprocal influence of the various subsystems on one another, a unique culture is created in each organisation, which makes it unique and distinguishes it from other organisations. 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 data set was built from data gathered from the five participating companies over the past few years. The information was gathered mainly with a view to improve the performance of the companies. Hence, the aim in gathering the information was 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 level 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. Principal Axis Factoring was used as the extraction method. Based on Kaiser’s (1961) (eigenvalues-greater-than-unit y) criterion nine factors were postulated. Subsequently, sub-scores (SS) were calculated for these nine factors. Meaningful item DU TOIT, ROODT80 Figure 2: A Model of Organisational Culture (Martins, 1989, p.92) loadings were obtained on eight of the nine postulated factors. These eight factors, which explain about 46% of the variance in the factor space, were retained for second level factor analysis. Second level factor analysis on the inter-correlation matrix The eight 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. TABLE 3 MATRIX OF INTER-CORRELATIONS OF SUB-SCORES (SS) SS 1 SS 2 SS 3 SS 4 SS 5 SS 6 SS 7 SS 8 SS 1 1,000 SS 2 0,628 1,000 SS 3 0,682 0,615 1,000 SS 4 0,556 0,414 0,433 1,000 SS 5 0,612 0,603 0,555 0,504 1,000 SS 6 0,417 0,457 0,517 0,294 0,411 1,000 SS 7 0,353 0,214 0,246 0,109 0,141 0,136 1,000 SS 8 0,319 0,311 0,255 0,195 0,273 0,246 0,145 1,000 All Correlations are significant at the 0,01 level (2-tailed). According to Kaiser’s (1961) criterion a single factor was postulated. Table 4 provides the eigenvalues of the unreduced factor matrix. This factor explained 48% of the variance in the factor space. TABLE 4 EIGENVALUES OF THE UNREDUCED INTER-CORRELATION MATRIX OF SUBSCORES Initial Eigenvalues Root Total % of Cumulative Variance % 1 3,827 47,841 47,841 2 0,942 11,775 59,616 3 0,844 10,556 70,172 4 0,703 8,790 78,962 5 0,610 7,629 86,591 6 0,504 6,304 92,895 7 0,321 4,006 96,901 8 0,248 3,099 100,000 Trace = 8 The factor solution converged after 5 iterations. Table 5 provides the rotated factor matrix of the CAI. TABLE 5 SORTED FACTOR LOADINGS ON POSTULATED FACTOR Sub-Scores Scale h2j 1 SS 1 0,858 0,660 SS 2 0,823 0,591 SS 3 0,811 0,595 SS 4 0,616 0,372 SS 5 0,601 0,330 SS 6 0,564 0,316 SS 7 0,374 0,131 SS 8 0,304 0,129 Extraction Method: Principal Axis Factoring. 1 factor extracted. 5 iterations required. An iterative item analysis procedure was conducted on this single scale and a very high Cronbach Coefficient Alpha of 0,945 was obtained. Table 6 provides the item statistics for the CAI. TABLE 6 ITEM STATISTICS OF THE CAI Scale Scale Corrected Alpha Mean Variance Item- if Item if Item if Item Total Deleted Deleted Deleted Correlation Q2 182,310 1120,033 0,300 0,945 Q3 182,416 1113,948 0,327 0,945 Q4 182,917 1094,479 0,526 0,944 Q5 183,421 1102,019 0,441 0,944 Q6 183,172 1093,445 0,473 0,944 Q7 182,126 1125,377 0,194 0,945 Q8 182,333 1109,236 0,396 0,944 Q10 182,539 1104,559 0,474 0,944 Q11 182,775 1100,582 0,560 0,944 Q12 182,822 1094,317 0,513 0,944 Q13 182,912 1095,447 0,460 0,944 Q14 182,835 1095,843 0,506 0,944 Q15 182,434 1106,652 0,381 0,944 Q19 183,246 1097,836 0,443 0,944 Q20 182,797 1104,650 0,366 0,945 Q21 182,518 1110,650 0,324 0,945 Q23 183,352 1083,842 0,584 0,943 Q24 183,410 1089,231 0,612 0,943 Q25 183,228 1086,502 0,560 0,943 Q26 182,655 1117,183 0,242 0,945 Q27 182,657 1112,705 0,361 0,944 Q28 183,209 1086,742 0,573 0,943 Q29 182,781 1096,212 0,520 0,944 Q30 182,934 1091,020 0,586 0,943 Q31 183,243 1091,040 0,561 0,943 Q33 183,098 1092,359 0,580 0,943 Q34 183,024 1082,393 0,667 0,943 Q36 182,333 1122,885 0,203 0,945 Q37 182,636 1116,514 0,304 0,945 Q39 183,280 1089,542 0,536 0,944 Q41 183,374 1093,897 0,529 0,944 Q42 183,493 1084,821 0,602 0,943 Q43 183,256 1093,593 0,529 0,944 Q44 182,838 1104,725 0,415 0,944 Q45 182,919 1103,466 0,453 0,944 Q46 183,076 1090,547 0,569 0,943 Q47 183,350 1103,241 0,405 0,944 Q49 182,981 1092,726 0,578 0,943 Q51 183,080 1104,398 0,427 0,944 Q52 182,617 1106,825 0,444 0,944 Q54 182,556 1116,923 0,310 0,945 Q55 182,939 1084,958 0,621 0,943 Q57 182,958 1092,115 0,470 0,944 Q59 183,427 1097,552 0,465 0,944 Q60 183,652 1097,560 0,480 0,944 Q62 182,614 1096,302 0,567 0,943 Q63 182,702 1095,184 0,577 0,943 Q64 182,889 1089,848 0,596 0,943 Q65 182,856 1093,133 0,586 0,943 Q66 182,451 1098,969 0,499 0,944 Q67 182,801 1096,741 0,547 0,944 Q68 183,284 1106,092 0,406 0,944 Q70 182,767 1098,537 0,507 0,944 Q71 182,827 1102,382 0,471 0,944 Q73 182,823 1088,629 0,603 0,943 Q72 183,072 1128,213 0,095 0,946 N of Cases = 4066 N of Items = 56 Cronbach Coefficient Alpha = 0,945 DISCRIMINANT VALIDITY OF THE CAI 81 Analysis of variance (ANOVA): comparison between companies In order to test the hypothesis of the study, which states that there are significant differences in the culture scores between companies from various industries, an analysis of variance was carried out on the data set. The results of these analyses are depicted in Tables 7 – 10. In Table 7 the aggregate mean for each organisation is depicted. TABLE 7 DESCRIPTIVE STATISTICS Company Mean Std. N Deviation Bank 191,460 26,800 1056 Bank – Home Loans 191,877 27,940 219 Retail 186,244 33,051 119 Information Technology 177,545 29,061 213 Services – Parastatal 184,244 36,821 2459 Total 186,237 33,749 4066 From Table 7 it is clear that the company in the banking industry has the highest mean (192), whilst the company in the information technology industry has the lowest mean (177). This means that the culture of the company in the banking industry was most positively assessed, whilst the culture of the company in the IT industry was least positively assessed. Analysis of variance was preceded with the Levene’s test for the equality of error variances. The results are depicted in Table 8. TABLE 8 LEVENE’S TEST OF EQUALITY OF ERROR VARIANCES (A) F-ratio df1 df2 P(F) 45,214 4 4061 0,000 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. From Table 8 it can be inferred that the error variance of the dependent variable is not equal across the companies, and the Dunnett post hoc tests should therefore be interpreted (See Table 10). The differences in variance between the companies are depicted in Table 9. At a first glance it would appear that there are significant differences in mean culture scores between the different companies. TABLE 9 ANOVA: COMPARISON BETWEEN ORGANISATIONS IN RESPECT OF CULTURE Source Type III Sum df Mean F-ratio P(F) Partial of Squares Square Eta Squared Corrected Model 61640,548(a) 4 15410,137 13,698 0,000 0,013 Intercept 45611830,805 1 4561183,805 40545,511 0,000 0,909 COMP 61640,548 4 15410,137 13,698 0,000 0,013 Error 4568437,846 4061 1124,954 Total 145655506,000 4066 Corrected Total 4630078,394 4065 a) R Squared = 0,013 (Adjusted R Squared = 0,012) However, it must be kept in mind that the sample sizes differ considerably. Thus, in order to make accurate inferences, it was necessary to make provision for the differences in sample size. For this purpose the Partial Eta Squared was calculated. Partial Eta Squared revealed that only an insignificant portion, namely 1,3% of the variance could be attributed to culture differences. The results of the Dunnett post hoc tests are depicted in Table 10. From Table 10 it can be seen that the Bank and Home Loans are significantly different from IT and Services, but as mentioned above only an insignificant small portion of the variance could be explained. TABLE 10 DUNNETT POST HOC TESTS (I) (J) Mean Std. Error Sig. 95% Confidence Company Company Difference Interval (I-J) Lower Upper Bound Bound Bank Home Loans -,4165 2,060 1,000 -6,224 5,391 Retail 5,216 3,140 0,639 -3,712 14,145 IT 13,916(*) 2,155 0,000 7,838 19,994 Services 7,216(*) 1,110 0,000 4,107 10,326 Home Loans Bank ,416 2,060 1,000 -5,391 6,224 Retail 5,633 3,570 0,704 -4,462 15,720 IT 14,332(*) 2,744 0,000 6,612 22,052 Services 7,633(*) 2,029 0,002 1,912 13,355 Retail Bank -5,216 3,140 0,639 -14,145 3,712 Home Loans -5,633 3,570 0,704 -15,728 4,462 IT 8,699 3,626 0,159 -1,549 18,948 Services 2,000 3,119 0,999 -6,873 10,874 IT Bank -13,916(*) 2,155 0,000 -19,994 -7,838 Home Loans -14,332(*) 2,744 0,000 -22,052 -6,612 Retail -8,699 3,626 0,159 -18,948 1,549 Services -6,699(*) 2,125 0,018 -12,695 -0,703 Services Bank -7,217(*) 1,110 0,000 -10,326 -4,107 Home Loans -7,633(*) 2,029 0,002 -13,355 -1,912 Retail -2,000 3,119 0,999 -10,874 6,873 IT 6,699(*) 2,125 0,018 0,703 12,695 * The mean difference is significant at the .05 level. Hence, the hypothesis, which states that there are significant differences in mean culture scores between the different companies in the sample, is rejected. It can thus be concluded that the instrument does not posses discriminant validity, i.e. the capability to distinguish culture between companies from different industries. DISCUSSION It is clear from the factor analyses and the item analysis 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, 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. DU TOIT, ROODT82 The one criterion that was somewhat neglected is item format, which includes aspects such as: � The question should be short and simple. � The question should be clear and unambiguous. � The respondent should have the necessary knowledge to answer the question. � The question should be phrased neutrally. � The question should not make the respondent feel guilty. � The question should be asked on the highest level of measurement that would still make sense. The questionnaire uses a 5-point Likert response scale where all the response categories are labelled. According to Schepers (1992) the equal interval quality of a scale is lost if more than t wo points are anchored. Schepers (1992) recommended that it is better to use an intensity response scale where only the two extreme categories are labelled as depicted in Figure 3. Figure 3: Proposed Intensity Response Scale Schepers (1992, p.14) The factor analyses resulted in a robust single factor that indicates 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 0,945. 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 bet ween the various companies. However, as mentioned before only 1,3% of these differences could be attributed to differences in cultures. In other words the culture of the bank is the same as the culture of the retail chain store, is the same as the culture of the public service organisation and is the same as the culture of the information technology organisation. However, based on the literature review, a priori differences in cultures between companies, 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 ability to distinguish differences in cultures between companies from different industries. These findings suggest that the CAI lacks discriminant validity. On the other hand the CAI reliably assessed communalities in culture between companies. This is the strength of the instrument. It is good at detecting communalities between companies. See Figure 4 for a graphic representation of what the findings suggest. In Figure 4 each circle represents a different company and the shaded area represents the similarities between the companies, as identified by the instrument. The areas not shaded represent the unique differences between the companies, not identified by the instrument. These communalities, 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 companies may appear to have the same culture. The reason for this phenomenon is that companies 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 companies. 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. Figure 4: Similarities between Companies Emanating from the findings of the literature 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 between companies from the positivistic paradigm. Finally, It is recommended that the application of the Culture Assessment Instrument be supplemented with methods from the interpretative paradigm for a holistic and comprehensive view on the culture of a company. REFERENCES Ajiferuke, M. & Boddewyn, J. (1970). Socioeconomic indicators in comparative management. Administrative Sciences Quarterly, December, 453-458. Amsa, P. (1986). Organizational culture and work group behaviour: an empirical study. 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