Abstract
In this paper, a framework is presented to use data science to analyze human behaviour and cognition mechanisms in
organizations. To obtain the goal in any business, it is essential to manage people, whether they are intra-organizational
or extra-organizational. The objective of such management is to enhance people’s behaviour by identifying the influencing factors and mechanisms. The paper aims to present a framework that consists of three science domains: a)
organizational and management science, b) cognitive science, and c) data science. The goal of that framework is to
identify the cognitive mechanisms and cognitive factors of different groups of people to enable performance improvement within an organization. This framework is described by reviewing data science and machine learning techniques
and how they are applied to the framework. To explain the conceptual framework and bring examples, UNICEF’s
country office in Iran, with its intra- and extra-organizational people, is used. Bringing together previously mentioned
science domains in pairs has resulted in new facets of scientific growth in multiple fields. The main idea is that the
confluence of all domains will develop a new framework for analyzing the mental and professional skills and capabilities of each group involved in the organization. In this framework called Human-Centric Analytics (HCA), which is
described as the main finding of this study, data science is used as a scientific approach, and by using cognitive theories
and human-related datasets, the goal is to achieve analysis that can help organizational achievements by considering
the cognitive capabilities of human capital. The present paper is the first publication of a comprehensive and major
research project. This research relates to two purposes after introducing the mentioned framework. On one hand,
this framework can be used and customized for organizations to improve their performance, and on the other hand, it
opens a new perspective for researchers of the three main scientific domains to expand their research and conclusions
organizations. To obtain the goal in any business, it is essential to manage people, whether they are intra-organizational
or extra-organizational. The objective of such management is to enhance people’s behaviour by identifying the influencing factors and mechanisms. The paper aims to present a framework that consists of three science domains: a)
organizational and management science, b) cognitive science, and c) data science. The goal of that framework is to
identify the cognitive mechanisms and cognitive factors of different groups of people to enable performance improvement within an organization. This framework is described by reviewing data science and machine learning techniques
and how they are applied to the framework. To explain the conceptual framework and bring examples, UNICEF’s
country office in Iran, with its intra- and extra-organizational people, is used. Bringing together previously mentioned
science domains in pairs has resulted in new facets of scientific growth in multiple fields. The main idea is that the
confluence of all domains will develop a new framework for analyzing the mental and professional skills and capabilities of each group involved in the organization. In this framework called Human-Centric Analytics (HCA), which is
described as the main finding of this study, data science is used as a scientific approach, and by using cognitive theories
and human-related datasets, the goal is to achieve analysis that can help organizational achievements by considering
the cognitive capabilities of human capital. The present paper is the first publication of a comprehensive and major
research project. This research relates to two purposes after introducing the mentioned framework. On one hand,
this framework can be used and customized for organizations to improve their performance, and on the other hand, it
opens a new perspective for researchers of the three main scientific domains to expand their research and conclusions
| Original language | English |
|---|---|
| Journal | International Journal of Nonlinear Analysis and Applications |
| DOIs | |
| Publication status | Accepted/In press - 17 May 2025 |