Recent Advances in the Roles of Cultural and Personal Values in Organizational Behavior by Zlatko Nedelko;Maciej Brzozowski;

Author:Zlatko Nedelko;Maciej Brzozowski; [Неизв.]
Language: eng
Format: epub, pdf
Publisher: IGI Global

The conceptual model and the interrelations among national culture, innovation, corruption and human development are presented in Figure 1.

Figure 1. Conceptual model and causal relationships

METHODS

Measures Used

Values for Hofstede’s PDI, IND, MAS, UAI, PRA, and IVR were obtained from Hofstede's Website (2014) for the year 2010 with data ranging from 0-100, with 100 representing the maximum score for each dimension.

The CPI scores were gathered from the Transparency International Website (2014) for the year 2012. In the published index, values range from 0-100 with 0 representing the highest level of corruption and 100 the lowest. Data was reversed by subtracting each CPI score from 100. For this sample, the highest level of corruption was 81 (Venezuela) whilst the minimum was 10 (Denmark, Finland and New Zealand).

The GII is the average of two sub-indexes. The data was retrieved from the Global Innovation Website (2014) for 2012; this index ranges from 0-100 where the higher the score, the higher the innovation. The minimum and maximum values recorded were 23.06 (Pakistan) and 68.24 (Switzerland) respectively.

The HDI is composed of the following data: the life expectancy at birth provided by UNDESA; the mean years of schooling provided by UNESCO and the expected years of schooling provided by UIS; and the Gross National Income from the World Bank and the International Monetary Fund. The data was collected from the United Nations Development Programme (2014) for the year 2012. The index ranges from 0 to 1 where the higher the score, the higher the human development of a country.

Considering that the maximum range of HDI scores is between Norway (0.943) and Pakistan (0.562), we decided to use the Z-Scores for all variables in this chapter. Technically, Z-Scores are a conversion of individual scores into a standard form. The conversion allows to more easily compare different data, as it is based on the knowledge about the population’s standard deviation and mean (Moreira, Macedo, Lopes & Moutinho, 2011).

Empirical Methodology

The sample for this study included data for 61 countries located on five continents (Appendix A). The dataset was limited mainly by the availability of secondary data on culture. The countries included in this study represent around 76.2% world’s population and 90.7% world’s GDP in 2012 (The World Databank, 2014).

The statistical data analysis of the model was carried out using the partial least squares method structural equation modelling (PLS-SEM) and the SmartPLS 3.0 software. The use of this methodology is justified because this method is robust when testing and validating an exploratory model (Chin, 2010).

The proposed model was evaluated by (a) the sign, magnitude and statistical significance of the parameters of structural relations, and by (b) the explained variance (R2) of the endogenous variables, following Götz, Liehr-Gobbers and Krafft (2010).

RESULTS

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