A study of strategic factors affecting post-cross-border acquisition technological innovation performance of the acquiring firms using m-TISM and MICMAC

Purpose - This study aims to identify the strategic factors and their effects on the post-cross-border acquisitions (CBA) technological innovation performance of the acquiring firms. It develops a hierarchical model to examine the interrelationship between identified strategic factors such as strategic flexibility, strategic ambidexterity, environmental dynamism, etc. Design/methodology/approach - This study uses modified total interpretive structural modeling qualitative methodology (m-TISM) to develop a hierarchical model and conducts a Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis to show the interrelationship between strategic factors affects the acquirer’s post-CBA technological innovation performance. It determines the autonomous, dependent, linkage and independent strategic factors. It further uses comparative case analysis to empirically examine the strategic factors in real-time CBA situations. Findings - This study shows the m-TISM-based hierarchical model highlighting the interrelation, level of autonomy, dependence and linkage among strategic factors affecting the acquirer’s post-CBA technological innovation performance. It suggests that strategic factors such as environmental dynamism, R&D competence, innovation capability and technological capability are largely autonomous and have significant driving power, whereas strategic ambidexterity and strategic flexibility are the connecting factors. post-M&A integration is the governing factor for technological innovation performance in CBA. Research limitations/implications - The strategists and practitioners could evaluate the key strategic factors having significant driving power for strategy formulation and implementing efficient policies. By implementing the m-TISM model acquiring a firm’s post-CBA performance can be enhanced. Future researchers might utilize quantitative methods like regression and structural equation modeling in the CBA context. Originality/value - This study uses a novel m-TISM and MICMAC approach to identify the driving and dependent factors affecting post-CBA technological innovation performance. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched strategic factors in CBA.