Information Overload and National Culture: Assessing Hofstede

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Information Overload and National
CultureAssessing Hofstedes Model Based on Data
from Two Countries

• Ned Kock, Ph.D.
• Dept. of MIS and Decision Science
• Texas AM International University

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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.

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Scores and ranks for the US and NZ - cultural
dimensions in Hofstedes model
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Hofstedes 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 Hofstedes (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.

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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
  Hofstedes cultural dimensions?

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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.

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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).

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Variables and measures
Source Assessment instrument developed and
validated by Kock (2000).
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Descriptive statistics
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Results
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RQ1 Is information overload a relevant
phenomenon from a business perspective?
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RQ2 Does perceived information overload vary
significantly between the US and New Zealand?
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RQ2 Does perceived information overload vary
significantly between the US and New Zealand?
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RQ3 Is the variation in perceived IO consistent
with Hofstedes 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.

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RQ3 Is the variation in perceived IO consistent
with Hofstedes 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 Hofstedes
  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 lt .05 level.

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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.