Classification of Lighting Design Aspects in Relation to Employees’ Productivity in Saudi Arabia

Ghada Abdulrahman Najjar (), Khaled Akkad () and Ahdab Hashim Almahdaly
Additional contact information
Ghada Abdulrahman Najjar: Department of Interior Design, Prince Sultan University, P.O. Box 66833, Riyadh 11586, Saudi Arabia
Khaled Akkad: Department of Engineering Management, Prince Sultan University, P.O. Box 66833, Riyadh 11586, Saudi Arabia
Ahdab Hashim Almahdaly: East Consulting Engineering Company, P.O. Box 1973, Riyadh 11441, Saudi Arabia

Sustainability, 2023, vol. 15, issue 4, 1-14

Abstract: Though the average employee spends a third of their day inside an office, designing a productive workspace can be challenging for designers. However, lighting design is a critical factor for the wellbeing of the employee. With the increasing number of local and international companies opening in Saudi Arabia, it is important to study the effect of natural and artificial lighting on the productivity of employees in the office environment. It is essential to consider that employee productivity leads to economic productivity. A questionnaire was shared with the employees of the head office of Ensan Charity for Orphans Care to collect data on the preferences of staff on the current lighting design in their offices. Office design is one of the most important aspects in need of special attention, since employees spend more than eight hours daily at their offices. Lighting design is one of the key aspects of office design that has a direct impact on employees’ satisfaction and productivity. The aim of this study was to discover employees’ preferences for office design in Saudi Arabia. The collected data are analyzed to uncover employee preferences as well as to predict two key design aspects using machine-learning techniques. The two design aspects of concern are direct sunlight in the office environment and manual control of light intensity. This research aimed to help improve the design of the office environment according to employees’ preferences and international standards through investigating sustainable lighting design elements. A further challenge to be overcome was the need for further data collection as it relates to the two design aspects mentioned above. This paper demonstrates relatively high prediction accuracies of the mentioned design considerations using a variety of machine-learning algorithms.

Keywords: economic productivity; office design; lighting design; employee satisfaction; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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