Determinants of alliance productivity and performance: evidence from the automobile industry

Purpose - This study aims to identify critical factors and examine their impact on alliance performance from an organizational learning point of view. Design/methodology/approach - A modified total interpretive structural modeling (M-TISM) methodology was used in this study. The different paths/links in the developed M-TISM model were further validated by using the Mahindra-Ford alliance case study. Findings - In this study, a total of seven critical factors were identified using an extensive literature review, and a hierarchical model was developed. Results show that prior alliance experience, inter-partner learning, knowledge transfer, absorptive capacity and knowledge internalization have a positive on the alliance productivity and performance. Furthermore, the findings indicate that prior alliance experience remains essential for alliance productivity and performance, while knowledge transfer and absorptive capacity can contribute to inter-partner learning and knowledge internalization in strategic alliances. Research limitations/implications - This study can help managers and policymakers to understand the identified critical factors from an organizational learning perspective and understand their impact on the alliance performance in a competitive environment. The managers should know that previous alliance experience, learning from partner firms, building an absorptive capacity, etc., are necessary to achieve superior alliance productivity and performance. For academicians, the M-TISM methodology used in this study can provide a mechanism to perform exploratory research and build a hierarchical model in different management research fields. Originality/value - The study fills research gaps by identifying key factors, developing a hierarchical model, and examining their impact on the performance of strategic alliances in the Indian automotive industry.