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Purpose

This paper aims to apply complexity theory tenets to deepen understanding, explanation and prediction of how configurations of national cultures and need motivations influence national entrepreneurial and innovation behavior and nations’ quality-of-life (QOL). Also, the study examines whether or not high national ethical behavior is sufficient for indicating nations high in quality-of-life.

Design/methodology/approach

Applying core tenets of complexity theory, the study constructs asymmetric, case-based (nations), explanations and predictive models of cultures’ consequences (via Schwartz’s seven value dimensions) and implicit need motivations (via McClelland’s three need motivations) indicating national entrepreneur and innovation activities and subsequent national quality-of-life and ethical behavior. The study includes testing configurational models empirically for predictive accuracy. The empirical examination is for a set of data for 24 nations in Asia, Europe, North and South America and the South Pacific.

Findings

The findings confirm the usefulness of applying complexity theory to learn how culture and motivation configurations support versus have negative consequences on nations’ entrepreneurship, innovation and human well-being. Nurturing of entrepreneur activities supports the nurturing of enterprise innovation activity and their joint occurrence indicates nations achieving high quality-of-life. The findings advance the perspective that different sets of cultural value configurations indicate nations high versus low in entrepreneur and innovation activities.

Practical implications

High entrepreneur activities without high innovation activity are insufficient for achieving high national quality-of-life. Achieving high ethical behavior supports high quality-of-life.

Originality/value

This study is one of the first to apply complexity theory tenets in the field of entrepreneurship research. The study here advances the perspective that case-based asymmetric modeling of recipes is necessary to explain and predict entrepreneur activities and outcomes rather than examining whether variable relationships are statistically significant from zero.

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