Technology management for innovation in organizations: an argumentation-based modified TISM approach

In the rapidly changing business world, innovation plays a vital role for organizations to gain a competitive advantage. Various factors associated with technology management and innovations in organizations are diverse in the existing literature. Therefore, there is a need to bridge these gaps in the fitting proportions toward innovations within organizations. The primary objective of this study is to identify, explain and interpret the relationships between the identified technology-related factors that are important for innovations in organizations.

In this study, a modified total interpretive structural modeling (M-TISM) methodology was used to examine and analyze the various interactions between identified factors for innovations in organizations. However, the argumentation of the links is relatively weak in M-TISM. In order to compensate for this, M-TISM is additionally altered by an “Argumentation-based Modified TISM”. Hence, this research strengthens the modified TISM methodology by incorporating argumentation and total interpretation of the relationships between the identified factors.

A total of six major factors were identified using a literature review. Results suggest that workforce technical skills, technological infrastructure, technological alliances, technology transfer and top management support have an impact on innovation in organizations. Results also suggest that top management support and the technological infrastructure of an organization have a greater impact on innovation.

For policymakers and practitioners, this study provides a suggestive list of critical factors, which may help to develop policies or guidelines for improving innovation in organizations. Policymakers should focus on technological infrastructure and collaborations to enhance innovations and productions within the organizations. For academicians, this study provides a modified TISM model that shows the impact of technology-related factors on innovations. Future researchers could expand this study by adding a greater number of technological factors and validate this model in other industries.

This study fills a gap in the literature by interpreting the various relationships among the identified factors and innovations. The model has been validated through a panel of seven experts from the Indian automotive industry of multiple organizations. This study is useful in the automobile industry as it determines what and how technology-related factors affect innovations, process improvement and R&D production for organizations.