Title: Determining a model for eliminating organisational lying: a grounded theory approach

Authors: Mohammad Hakkak; Khaled Nawaser; Mohammad Jalali; Samaneh Ghahremani; Ali Vafaei-Zadeh; Haniruzila Hanifah

Addresses: Department of Management, Lorestan University, Khoram Abad, Iran ' Institute of Scientific Research and Graduate School, Universidad de Lima, Lima, Peru ' Department of Management, Lorestan University, Lorestan, Iran ' Department of Management, Lorestan University, Lorestan, Iran ' Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia ' Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia

Abstract: The present study has been implemented to generate a theory in the field of organisational lying for better understanding and explaining the phenomenon in organisations. The subject of lying has been widely discussed in other fields such as psychology. However, little attention has been paid to this issue in the field of management and organisation. Therefore, it seems that this paper can open a new horizon to research on lying within the organisation. The research method is qualitative and based on the grounded theory. Semi-structured interviews were used for data collection and Strauss and Corbin method and paradigmatic model were adopted for data analysis. A total of 21 interviews were conducted with managers and experts who were familiar with the issue and context using judgmental and snowball sampling technique. The results of the analysis of the data obtained from the interviews during the open, axial and selective coding processes led to the formation of a grounded theory concerning the organisational lying based on which the purposeful lying, blind lying, and silent lying were introduced as the basic concepts of the organisational lying model.

Keywords: organisational lying; antecedents of lying; consequences of lying; grounded theory.

DOI: 10.1504/IJIDS.2023.134789

International Journal of Information and Decision Sciences, 2023 Vol.15 No.4, pp.345 - 365

Received: 26 Feb 2021
Accepted: 23 Apr 2021
Published online: 13 Nov 2023 *

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