Purpose The purpose of this paper is to elucidate the methodology of total interpretive structural modeling (TISM) in order to provide interpretation for direct as well as significant transitive linkages in a directed graph. Design/methodology/approach This study begins by unfolding the concepts and advantages of TISM. The step-by-step methodology of TISM is exemplified by employing it to analyze the mutual dependence among inhibitors of smartphone manufacturing ecosystem development (SMED). Cross-impact matrix multiplication applied to the classification analysis is also performed to graphically represent these inhibitors based on their driving power and dependence. Findings This study highlights the significance of TISM over conventional interpretive structural modeling (ISM). The inhibitors of SMED are explored by reviewing existing literature and obtaining experts’ opinions. TISM is employed to classify these inhibitors in order to devise a five-level hierarchical structure based on their driving power and dependence. Practical implications This study facilitates decision makers to take required actions to mitigate these inhibitors. Inhibitors (with strong driving power), which occupy the bottom level in the TISM hierarchy, require more attention from top management and effective monitoring of these inhibitors can assist in achieving the organizations’ goals. Originality/value By unfolding the benefits of TISM over ISM, this study is an endeavor to develop insights toward utilization of TISM for modeling inhibitors of SMED. This paper elaborates step-by-step procedure to perform TISM and hence makes it simple for researchers to understand its concepts. To the best of the authors’ knowledge, this is the first study that analyzes the inhibitors of SMED by utilizing TISM approach.

Purpose – The purpose of this paper is to identify and analyze various critical success factors (CSFs) that can facilitate smartphone manufacturing in India. This paper further aims to understand the mutual interactions among these CSFs through identification of the hierarchical relationships among them. Design/methodology/approach – A framework for a smartphone manufacturing system has been developed, wherein the hierarchical inter-relationships between identified CSFs have been presented and interpreted using total interpretive structural modeling (TISM). Cross-impact matrix multiplication applied to classification analysis has been further employed to identify the driving power as well as dependence power of these CSFs. Findings – In the present research, 15 CSFs have been identified through literature review and expert opinions. The hierarchical framework developed using TISM has revealed the inter-dependencies among these CSFs. This research further categorizes CSFs into three clusters. The first cluster comprises of CSFs having high dependence power, the second cluster identifies CSFs having high driving power and the third cluster identifies CSFs which act as linkages between the driver CSFs and dependent CSFs. Research limitations/implications – This study has implications for both practitioners and academia. It provides a comprehensive list of CSFs that are relevant to develop a smartphone ecosystem in India. In addition, this study will help decision makers to strategically focus on the main drivers of the ecosystem that requires the immediate attention of decision makers. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework. Originality/value – The proposed framework developed through qualitative modeling is an effort to understand relevant factors that can promote the smartphone manufacturing ecosystem. This study makes a significant contribution in the literature of smartphone manufacturing, which captures the perspective of different stakeholders.

In this study we provide an overview of ecosystem indices of successfully smartphone manufacturing countries like China, USA, Taiwan, and South Korea by comparing some key parameters with that of peer average. The main purpose of this research is to compare various key manufacturing statistical parameters of other countries with that of India. It also brings out the current state of manufacturing in India, the market potential and the institutional frameworks developed to create an ecosystem conducive for manufacturing to grow. A SWOT (strengths, weaknesses, opportunities and threats) analysis is performed across all countries and analyzed for working out the SWOT matrix in Indian context to help formulating the strategy.