A Multi-Dimensional Intelligence Framework to Explain Sustainable Employee Productivity

In the context of sustainable development and the growing emphasis on decent work and productivity, understanding the human factors that shape employee performance has become a central concern for organizations and policymakers. While intelligence has long been linked to work outcomes, existing research remains fragmented and predominantly focused on single dimensions, offering limited insight into how different forms of intelligence interact across employees’ career life cycles. Addressing this gap, the present study advances a multi-dimensional perspective on intelligence and examines its relevance for sustainable employee productivity, thereby contributing to the human resource management literature and to the achievement of Sustainable Development Goal 8 (Decent Work and Economic Growth). The study assesses the impact of five types of intelligence (cognitive—IQ, emotional—EQ, physical—PQ, vitality—VQ, and social—SQ) on employee productivity across distinct career life cycle stages. The research was conducted in two phases: (1) measurement of intelligence dimensions and employee productivity using standardized psychometric instruments, including MSCEIT V2.0, the Guilford–O’Sullivan test, the Eysenck test, the Chekhov vitality method, and biological age indicators; (2) statistical analysis of the relationships between intelligence, productivity, and career stages using open-source Python tools. Empirical data were collected from enterprises in the Ukrainian construction industry. The findings demonstrate that the influence of intelligence on productivity varies across career stages. Emotional intelligence emerges as a consistently significant factor throughout the employee life cycle, while other intelligence dimensions exhibit stage-specific effects. These results confirm the dynamic and non-uniform nature of intelligence–productivity relationships. The study provides practical insights for sustainable human resource management by highlighting the need for stage-sensitive development strategies that align intelligence profiles with career phases. Implementing such targeted approaches can enhance employee productivity, organizational effectiveness, and long-term economic sustainability, thereby supporting progress toward SDG 8.

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Publication Details

Journal
Sustainability
Published
2025-12-30
DOI
https://doi.org/10.3390/su18010368
Primary Topic
Emotional Intelligence and Performance
Type
article
Field-Weighted Citation Impact
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article

A Multi-Dimensional Intelligence Framework to Explain Sustainable Employee Productivity

Oleksandr Dluhopolskyi, Dmytro Zherlitsyn, Yuliia Shyron, Natalia HORBAL et al.
Sustainability
Emotional Intelligence and Performance
article

A Multi-Dimensional Intelligence Framework to Explain Sustainable Employee Productivity

Oleksandr Dluhopolskyi, Dmytro Zherlitsyn, Yuliia Shyron, Natalia HORBAL, Liana Chernobay, Sylwester Bogacki
article en

Abstract

In the context of sustainable development and the growing emphasis on decent work and productivity, understanding the human factors that shape employee performance has become a central concern for organizations and policymakers. While intelligence has long been linked to work outcomes, existing research remains fragmented and predominantly focused on single dimensions, offering limited insight into how different forms of intelligence interact across employees’ career life cycles. Addressing this gap, the present study advances a multi-dimensional perspective on intelligence and examines its relevance for sustainable employee productivity, thereby contributing to the human resource management literature and to the achievement of Sustainable Development Goal 8 (Decent Work and Economic Growth). The study assesses the impact of five types of intelligence (cognitive—IQ, emotional—EQ, physical—PQ, vitality—VQ, and social—SQ) on employee productivity across distinct career life cycle stages. The research was conducted in two phases: (1) measurement of intelligence dimensions and employee productivity using standardized psychometric instruments, including MSCEIT V2.0, the Guilford–O’Sullivan test, the Eysenck test, the Chekhov vitality method, and biological age indicators; (2) statistical analysis of the relationships between intelligence, productivity, and career stages using open-source Python tools. Empirical data were collected from enterprises in the Ukrainian construction industry. The findings demonstrate that the influence of intelligence on productivity varies across career stages. Emotional intelligence emerges as a consistently significant factor throughout the employee life cycle, while other intelligence dimensions exhibit stage-specific effects. These results confirm the dynamic and non-uniform nature of intelligence–productivity relationships. The study provides practical insights for sustainable human resource management by highlighting the need for stage-sensitive development strategies that align intelligence profiles with career phases. Implementing such targeted approaches can enhance employee productivity, organizational effectiveness, and long-term economic sustainability, thereby supporting progress toward SDG 8.

SustainabilityVol. 18(1)
West Ukrainian National University (UA), University of National and World Economy (BG), University of Economics and Innovation (PL), Lviv Polytechnic National University (UA)
Openalex Percentile: Top 26%
Emotional Intelligence and Performance
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