Journal Article

·2022 OPEN ACCESS

An evaluation on the motivation of employees in the logistics sector during the COVID-19 pandemic process

Öznur Gülen Ertosun YTU

Yıldız Sosyal Bilimler Enstitüsü Dergisi

Abstract

This study aims to reveal both the motivation sources of employees in extraordinary conditions (such as ) and the type of motivational sources that are dependent on individual and environmental conditions.Within the framework of the aim of the study, quantitative research was conducted.The universe of the study is logistics companies in the TMS 2020 report, with a sample consisting of 343 employees from various positions and professions.Data were obtained by questionnaire method.The questionnaire consist of a socio-demographic information form contains individual, work-related, and COVID-19 experience questions and the six-dimensional motivation at work scale.According to analysis findings, the 6-dimensional motivation scale was represented by 5 dimensions (as a result of CFA analysis), and introjected motivation was eliminated.Identified regulation levels of employees were calculated at quite high levels, while amotivation levels were quite low.As a result of the difference tests, material and social external regulations are differentiated according to personal differences.Amotivation is affected by position.In addition, parallel with the previous findings, while controlled motivation was open to these effects, autonomous motivation was not affected by environmental conditions and personal characteristics.Details are discussed in the relevant section.

Keywords

Amotivation Coronavirus disease 2019 (COVID-19) Scale (ratio) Psychology Personal protective equipment Work (physics) Sample (material) Intrinsic motivation Pandemic Process (computing) Marketing Applied psychology Business Social psychology Computer science Engineering Medicine Geography

Subject Areas

Belt and Road Initiative ·Economics and Econometrics ·Social Sciences
Education Practices and Challenges ·Philosophy ·Social Sciences
Organizational and Employee Performance ·Artificial Intelligence ·Physical Sciences