Does a creative identity encourage innovative behaviour? Evidence from knowledge-intensive IT service firms

Abstract

Purpose The purpose of this paper is to investigate the influence of an employee’s personal creative identity on their innovation behaviour in knowledge-intensive information technology (IT) service provider firms. It further investigates the mediating role of an employee’s creative process engagement (CPE) and the moderating effects of the organizational creative climate on creative identity-innovative behaviour (IB) relationships. Design/methodology/approach This study follows a quantitative method. Using a multi-item survey instrument, a total of 316 questionnaires were collected from the employees of IT service provider firms in Chittagong, Bangladesh. The collected data were analysed using structural equation modelling, factor analysis and path analysis to test the hypotheses and to assess the moderating and mediating effects of the variables. Findings The results revealed the significant influence of an employee’s creative personal identity (CPI) on their IB. The mediation analysis revealed that CPE mediates the association between a CPI and IB. The study also found a significant moderating effect of a creative organizational climate between a CPI and CPE. Research limitations/implications Based on the premise of the interactionist approach of creativity and role identity theory, this study contributes to the creativity and innovation literature by providing empirical support for the relationship between a personal creative identity, organizational creative culture, CPE and IB in IT service organizations. Originality/value This study adopts a distinct model comprising four different variables to investigate an employee’s IB from a multi-level perspective, i.e., a creative identity and CPE at the individual level and a creative climate and IB at the organizational level. This integrated model using predictors from multiple levels supports the theoretical assumption that IB results from the interaction of individual and organizational level factors.

The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study

“…Further, convergent validity refers to the magnitude of the constructs' suitability to measure what it intends to measure, and the minimum acceptable limit for being convergent valid is with no less than 0.50 of its average variance extracted (AVE) [75,76]. The present study has no issue with convergent validity, since the minimum score of AVE is 0.530 (Knowledge sharing) [57,79,80,82]. Furthermore, we also investigated the discriminant validity result.…”

“…This study used structural equation modeling (SEM), using AMOS 20. We applied multivariate regression analysis through SEM in place of simple regression because the former tested the whole model in an integrated manner [57,79,80]. In addition, bootstrapping of 5000 cases was used to test and examine the observed relationships.…”

Fighting ahead: Adoption of social distancing in COVID-19 outbreak through the lens of theory of planned behavior

“…Finally, discriminant validity is also assessed to determine the distinctiveness of each construct. In Table 3, bold diagonal scores exhibited that the square root of AVE of a target construct is higher than its correlation with other constructs (Astrachan et al, 2014;Hair, Black et al, 2014;Uddin, Priyankara et al, 2019). Thus, results in Table 3 endorsed that there is no concern in measurement model evaluation.…”

A Study of the Adoption and Implementation of Enterprise Resource Planning (ERP): Identification of Moderators and Mediator

“…The supremacy of using these theories underlies in its consideration of multi-level perspectives [51]. The study of Mahmood, Uddin and Luo [6] and Uddin et al [55] signify that multi-level variables are to be considered in open innovation cases. The UTAUT, based on a comprehensive review and synthesis of several theoretical models [2,41,53], constitutes five distinct constructs in multi-level perspectives, such as performance expectancy and effort expectancy (individual-level variables), social influences (social level variable) and facilitating conditions (organizational level variable), and behavioral intention for predicting actual use behavior (individual-level variables) [41,42].…”

“…Method bias and response bias are two significant concerns preventing the authenticity of the research outcomes [88,89]. Hence precautionary measures were taken in advance to guard the negativity of biasness issues [55]. Initially, the respondents were assured of their anonymity which driven them to provide us accurate responses without any phobia of identity disclosure [84,86,90].…”