The Impact of National Culture at the UK Head Office on Organizational Culture in Asian Regional Operations

This chapter presents the results of the research. It presents the data from the quantitative component, to set the framework for the interrelationship between the countries of the study: the UK and Singapore. The results chapter submits the data from the qualitative semi-structured interviews and the interrelationship between the quantitative and qualitative data that is the triangulation of the research findings.

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This chapter will also present the analytical tools employed and the rationale for their use and validation of their relevance to this research. The results of this idiographic research presented show that the similarity of British and Singaporean culture as defined by the organizations within this research is more similar than that of a deductive broad based cultural comparative research. The foundations of these positions is established with the quantitative results and reinforced by the qualitative findings. It presents the data addressing the magnitude of difference or similarity, and the impact and pervasiveness of such difference.

5.2 Research objective

The objective of this research was to explore the impact of national culture at head office on organizational culture and its pervasion in Asian regional operations of British financial services organizations.

The key questions addressed in the research were:

What fundamental cultural differences exist between head office national culture and the Singaporean national culture?

How is this difference influenced by head office national culture in the environment of the organisations regional operations? Is it neutral, exacerbated, or muted?

In exploring the impact of corporate national culture, explore the pervasion of head office specific language into Southeast Asian regional operations.

How head office views their SIM regional operations?

What concerns or risks that head office believe need to be controlled in relation to its SIM operations? Is, and if so, how is, the explicit deployment of consistent culture used to mitigate these perceived risks?

How do regional offices perceive their position in the global organization?

How pervasive do the regional offices believe is their head office national culture? Is this considered an inhibitor, an enhancer or neutral to organizational performance in their market?

These questions direct the research in the context of the assertions:

that to be successful an organization must adapt to the culture in which it operates;

that organizations struggle to resolve potentially or perceived contradictory pressures of profit and control;

further, to adapt to a culture, an organization must possess cultural awareness and understanding, which is often lacking.

5.4 Statistical methods and techniques

Descriptive statistics present the raw data in a structure that defines the comparative bodies in the research. These incorporated demographic presentation, central tendency measures and frequency tables.

Quantitative Analysis

The quantitative analytical assessments for the Schwartz Value Survey followed were those prescribed by Professor Schwartz (Schwartz, 2009)

The Schwartz Value Survey results were used to assess and compare culture at both the individual level and the cultural level. Different analyses were undertaken for each of the individual and cultural analyses.

Correlation Analysis

This analysis examines the relationship between variables, the magnitude and direction. A low correlation, that is, a relationship exhibiting a weak relationship between the variables is reflected in a score less than 0.21 to 0.4; a moderate correlation exists in scores from 0.41 to 0.70; high correlations exhibit values from 0.71 to 0.9 and a very high correlation is from 0.91 to1 (Lang and Secic, 2006). A very low correlation is determined as a score between 0.01 and 0.20.

Positive correlation scores reflect a direct relationship and negative scores an inverse relationship between the variables.

Regression Analysis

Regression analysis interrogates the relationships between a dependent variable and several independent variables. Regression analysis determines the existence or otherwise of a significant relationship between a dependent variable (for example organisational culture in the Southeast Asian organisations in this study) and independent variables (head office national culture of those corporations) (Khuri, 2013, p. 9).

Following the directives of Professor Schwartz, the researcher employed regression analysis as a measurement of validity of the Schwartz Value Survey research results. Specifically in relation to the SVS, these correlations were used to aid in understanding the results and to reduce confusion from multicollinearity or to inter-correlations among the values.

Schwartz reminds the researcher that individual differences in the mean of the values within specific research are due to a scale use bias. This was relevant as the body of participants in this research was smaller. Schwartz validates this comment as follows:

This assertion is grounded both in theory and empirically. A first theoretical ground is the assumption that, across the full range of value contents, everyone views values as approximately equally important. Some attribute more importance to one value, others to another. But, on average, values as a whole are of equal importance. This assumption is dependent on the further assumption that the value instrument covers all of the major types of values to which people attribute importance. Empirical evidence to support this assumption appears in Schwartz 1992, 2004. To the extent that individuals' attribute the same average importance to the full set of values, their mean score (MRAT) should be the same. Differences in individual MRATs therefore reflect scale use and not value substance. Of course, differences in MRAT may reflect some substance, but the empirical analyses suggest that substance is a much smaller component of MRAT than scale use bias is (Schwartz, et al., 1997). A second theoretical ground is that values are of interest because they form a system of priorities that guide, influence, and are influenced by thought, feeling and action. Values do not function in isolation from one another but as systems. For example, a decision to vote for one or another party is influenced by the perceived consequences of that vote for the attainment or frustration of multiple values--promoting equality or freedom of expression versus social power or tradition. It is the trade-off among the relevant values that affects the vote. Consequently, what is really of interest are the priorities among the values that form an individual's value system. Correcting for scale use with MRAT converts absolute value scores into scores that indicate the relative importance of each value in the value system, i.e., the individuals value priorities. The empirical basis for viewing differences in MRAT as bias is the findings of many analyses (50 or so, at least) that related value priorities to other variables--attitudes, behavior, background. The associations obtained (mean differences, correlations) when using scores corrected for MRAT are consistently more supportive of hypotheses based on theorizing about how values should relate to these other variables than the associations with raw scores. Indeed, with raw scores associations sometimes reverse. In no case have raw score associations made better sense than those corrected for MRAT.

(Schwartz, 2009).The processes followed for analysis of the Schwartz Value Survey analysis were as follows.

Data Cleaning

Consistent with the directions for analysis from Professor Schwartz, data was cleaned by checking to determine if any participants used the same response more than 35 times. Responses were cleaned for excessive blank responses in the same manner. This was defined as fifteen or more blank responses (Osborne, 2008). There were no such participants. At a subject level to determine the dimension scores, the data was checked in the cleaning process and if more than 30% of items were absent for a particular scale, that subject was to be removed from the analysis. There were no such cases.

The forty five SVS value items exhibiting the strongest reliability across cultures were used to calculate value types through determination of the mean importance rating of the value items of each value type. Subsequently each individual participants mean response was calculated across the 57 questions in the survey. The purpose of this was to control for scale. Thence, by averaging the value types the Schwartz higher order dimensions were determined.

Correlation Analyses

Correlation analysis determining the strength or otherwise of the numerical scores of the variables were conducted at individual and group level.

Individual level

Each participants individual SVS scores across the 57 value items were computed and divided by fifty seven- the number of items. This generated the MRAT or Mean Rating for that individual.

Each participants scores for every item in the questionnaire were centred around their individual MRAT. Following that, the results, or scores, for the ten values were computed by taking the means of the centred items.

The ten values at the individual level are presented in table 5.1 (Schwartz, 2009)

Table 5.1 Schwartz Value Survey Individual Level Values

Conformity 11, 20, 40, 47

Tradition 18, 32, 36, 44, 51

Benevolence 33, 45, 49,52, 54

Universalism 1, 17, 24, 26, 29, 30, 35, 38

Self-Direction 5, 16, 31, 41, 53

Stimulation 9, 25, 37

Hedonism 4, 50, 57

Achievement 34, 39, 43, 55

Power 3, 12, 27, 46, 58

Security 8, 13, 15, 22, 56

Group mean Comparisons

Group mean comparisons were employed to assess variance at the cultural level. The Mean MRAT was computed in the equivalent manner as at the individual level by summation of scores at the individual level. For the individual level, the scores were centred and the MRAT and these scores used in regression analysis. Professor Schwartz advised that up to eight centred values be used as predictors in the regression but not all ten unless the objective of the research is in the total variance from the variables only. As such eight values were used and the two excluded were those deemed least relevant to the research topic (Schwartz, 2009).

The results of these methods are presented below.

Qualitative Analysis

The qualitative analysis in this research exists to probe the impact of the quantified differences or lack of differences, the perceptions and interpretations of the participants, and the impact on the organisational culture. It is to present the why of the research to the quantitatively derived what.

The audio recordings of the semi structured interviews were transcribed, annotated with observations from the researcher made at the time of the interviews, and coded. Audio recording of the semi-structured interviews get the feeling of the participants in the culture practices both in the individual and organisational level. Observations further assist in getting the real feelings and the mood of the participants.

5.5 Reliability and Validity

Validity in research is demonstration of scientific rigour. It is a synonym for truth (Silverman, 2000). Truth in quantitative research is less contentious and demonstrated through known and adhered to principles: repeatability, reliability, statistical significance (Noble and Smith, 2015) .The Schwartz Value Survey obtains its validity as the most widely scientific quantitative cultural survey (Lee and Soutar, 2009). It is widely used amongst more than two thousand studies.

The process of demonstrating validity in qualitative research is by comparison more problematic....