The moderating effect of information technology capabilities on the relationship between marketing mix and corporate entrepreneurship

Purpose The purpose of this paper is to investigate the relationship between marketing mix (MM), information technology capabilities (ITCAP) and corporate entrepreneurship (CE). Additionally, the study has attempted to address the moderating influence of ITCAP on MM–CE relationship. Design/methodology/approach To achieve the objectives of the study, data was collected from managers working in the upper and middle departments in some major Algerian banks. To test the hypotheses of the study, simple regression and PROCESS macro with moderated multiple regression were used. Findings The results of the study revealed that the MM and ITCAP positively affect entrepreneurship, and the ITCAP of banks and their interaction with the MM contributed positively to promoting entrepreneurship for companies through the moderate influence of ITCAP on the relationship between the MM and CE. Research limitations/implications It is very difficult to present the generalization of the results of this study because some of the major banks mainly drove the study sample. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications The results of the study suggested that policymakers in the banking sector in Algeria seriously consider developing the MM for its direct role in the CE. Specifically, the moderate role of ITCAP indicated that an effective alignment of the bank’s ITCAP with elements of the MM could enhance the entrepreneurship position of the bank. Therefore, it is necessary to pay attention to the importance of these factors to foster entrepreneurship in the services sector. Originality/value The role of MM in CE has been overlooked in the extant literature, especially in the emerging economies. In addition, this study extends the body of knowledge through evaluating the moderating role of ITCAP using the effect of interaction in PROCESS macro with moderated multiple regression for path analysis.