Information Overload and National Culture: Assessing Hofstede’s Model Based on Data from Two Countries Ned Kock, Ph.D. Dept. of MIS and Decision Science Texas A&M International University

Information overload Situation characterized by an individual having more information to handle, in order to carry out one or more activities of a business process, than allowed by his or her (cognitive, time, technology etc.) resources.

Scores and ranks for the US and NZ - cultural dimensions in Hofstede’s model

Hofstede’s country and region clusters framework There is similarity in the scores, and particularly closeness in the ranks, for the US and New Zealand on each of the five cultural dimensions. This similarity in the scores and ranks is reflected in Hofstede’s (2001, p. 62) country and region clusters framework. The US and New Zealand are part of the same cluster, namely cluster 8, which also includes the following countries: Australia, Canada, Great Britain, and Ireland.

Research questions RQ1: Is information overload a relevant phenomenon from a business perspective? RQ2: Does perceived information overload vary significantly between the US and New Zealand? RQ3: Is the variation in perceived information overload consistent with predictions based on Hofstede’s cultural dimensions?

Data collection Perceptual and demographic data were collected from a sample of 108 MBA students. Of those students, 59 were from a large university in Northeastern US, and 49 from a midsized university in New Zealand. Nearly all students held professional or management positions at the time the data were collected.

Data analysis The data were analyzed through a variety of methods, with the goal of answering each of the research questions. Those methods include summarization of percentages, comparisons of means, structural equation modeling, and spreadsheet-based simulations. For the comparisons of means, both parametric (t) and nonparametric (Mann-Whitney U) tests were employed. For structural equation modeling, the partial least squares (PLS) technique was employed (Chin, 1998; 2001; Chin et al., 1996).

Variables and measures Source: Assessment instrument developed and validated by Kock (2000).

Descriptive statistics

Results

RQ1: Is information overload a relevant phenomenon from a business perspective?

RQ2: Does perceived information overload vary significantly between the US and New Zealand?

RQ2: Does perceived information overload vary significantly between the US and New Zealand?

RQ3: Is the variation in perceived IO consistent with Hofstede’s model? The distribution of scores provided by Hofstede (2001, p. 500) for the power distance dimension suggests a mean of 56.83 and a standard deviation of 21.81. Therefore, the difference in power distance scores of 18 between the US and New Zealand is close to a full standard deviation. The issue turns to whether the difference in power distance between the US and New Zealand could account for the significant country effects on perceived information overload and related predictors, particularly those observed in the PLS analysis.

RQ3: Is the variation in perceived IO consistent with Hofstede’s model? A spreadsheet simulation was conducted to verify whether the difference in power distance between the US and New Zealand could explain the significant country effects on perceived information overload and related predictors. The simulation presumed a relatively strong bivariate correlation of .575 between scores ranging from 1 to 100 (which is the approximate range of power distance scores in Hofstede’s model), and perceived information overload. Such a correlation would account for the .179 bivariate correlation between the variables country and perceived information overload. The results of that simulation suggest that even a difference in scores of 18 would be enough to produce a difference between two perceived information overload means that would be significant at the p < .05 level.

Conclusion Final slide If power distance were a strong predictor of information overload (something that cannot be strongly ascertained based on this study), the difference in power distance scores between the US and New Zealand could be large enough to explain the difference in the mean perceived information overload scores, and likely also the country effects suggested by the PLS analysis. However, if this were the case, it would call into question the inclusion of the US and New Zealand in the same country cluster, since those two countries would appear to differ substantially in terms of power distance, and certainly in perceived information overload, which in turn appear to be relevant variables from a business perspective.