Tapas Mishra

Dynamics of Inter-firm Linkages in Indian Automotive Industry: A Social Network Analysis

With the objective of delineating a clear understanding of the nature, intensity and geographic traits of the inter-relatedness between the component suppliers and automotive manufacturers, this chapter presents an analysis of the Indian automotive industry from a network perspective. Based on secondary data of the industry, we elaborated in the preceding two chapters on the characteristic features of the industry, viz., regional distribution of firms, distribution of products across firm size and regions, etc. The illustration, while equipped us with substantial information on the general trend and structure of the industry, does not lend adequate insight into the way firms interact, coordinate and how certain firms can potentially ply influence on others in the industry. Moreover, given that distinct regionalization is visible in the Indian automotive industry, a natural question arising in this context is whether the ‘relational structure’ of the auto-component and automotive firms in this industry is ‘localized’ in nature. This chapter tries to shed some light on this specific aspect although complementary analysis on the general structure, intensity and nature of the relation is also performed to get an insight into the structure of the Indian automotive industry. By thus invoking a concrete network framework to describe the industry structure and nature of interrelatedness, this chapter complements and extends our previous analysis (in the preceding chapter) in unravelling some of the underlying dynamics of the Indian automotive industry.

Human capital, age structure and growth fluctuations

This article assesses the empirical relationship between per capita income growth fluctuations and the age-structured human capital variations across four groups of geographically clustered developed and developing countries from spatial perspective. We estimate a spatial Vector Autoregressive (VAR) model of income dynamics where the distance between countries is defined on relational space based on their similarity in appropriation tendency of human capital in the production processes. These distances are computed using a newly developed human capital data set which fully characterizes the demographic structure of human capital, and thus underlines the joint relevance of demography and human capital in economic growth. Spatial effects on growth interdependence and complementarity are then explored with respect to the proposed distance metrics. Our results imply that significant cross-country growth interdependence based on human capital distances exists among defined country groups suggesting the need for a cooperative policy programme among them. We also find that the relationship between economic growth and human capital is highly nonlinear as a function of the proposed human capital distance.

Asymmetric Growth Impact of Fiscal Policy: Evidence from Egypt

This paper empirically explores how fiscal policy - represented by changes in government spending- exerts asymmetric effects on economic growth in the context of a developing country, Egypt in particular. By allowing for the theoretical plausibility of asymmetric effects of fiscal policy on economic activity, our research suggests that nothing can guarantee linearity between the growth impact of increasing and decreasing government expenditures. Using a non-linear ARDL model on Egypt data - at both aggregated and disaggregated levels- for the period 1980-2013, this paper provides new evidence of a non-linear relationship between government spending and economic growth.

Geographical Proximity and Adoption of AMTS in Indian Auto Components Industry

This chapter provides a complementary analysis on the embedding of firms and its effect on the process of adoption from a spatial perspective. The main objective of this chapter thus is to study the impact of geographical proximity on new technology adoption in the context of Indian Auto component industry. Taking further the analysis of the determinants of adoption, which was the thrust of the preceding chapter, herewith we explicate the diffusion phenomenon in a geographical setting and investigate the facilitative role of proximity (both in the geographical and relational sense) on the adoption of AMTs.

Technological and Organizational Innovations in Auto Components Industry: An Analysis of Survey Data from Diffusion Perspective

This chapter presents an empirical investigation of the adoption of AMTs by providing a first-pass assessment of the technology adoption of auto component firms in India. Before delving into the econometric investigation, it is important to examine the incidence of use of the advanced manufacturing technologies and practices in the industry in order to have a grasp of the pattern and extent of usage of the various AMTs and their dynamics. Thus, we provide a descriptive overview of the adoption pattern among the firms based on the survey data that lays the foundation for the econometric analysis presented in the next chapters.

Integrating Models of Diffusion: A Conceptual Framework for Research

The mechanism and explanation of the diffusion process underlies competing and most often many complementary theorisations, which are broadly interrelated but often explicated as independent thoughts. Based on the rather integrated and multi-dimensional perspective of diffusion process, the identification of a set of determinants delivering robust explanation of diffusion and adoption pattern of new technologies is an upheaval task. It is therefore necessary to develop a conceptual framework with the objective of a broader encompassing of set of determining factors of diffusion, in particular keeping up with the ‘multi-dimensional’ perspective of the ‘process’ as highlighted in Chap. 2. Given our focus on the role of inter-firm networking and their spatial considerations, the analytical and conceptual framework in this chapter will be tailored to address the specific issues of our research.

A Synoptic Review of the Indian Automotive and Auto Components Industry

The aim of this chapter is to draw a broad overview of the Indian automotive industry so as to lend a preliminary step for the empirical investigation to be carried later in the Book. Indian automotive industry has attracted a great deal of attention from industry, academia, and policy circles alike due to its sheer potential and gradual but notable performance in the recent decades. The industry has evolved as a dynamic one being chiseled by India’s liberalizing trade and investment regimes on the one hand, and the structural readjustments from within (propelled mostly by the changes in global automotive industry), on the other. In light of this, the present chapter critically documents the recent changes in the Indian auto industry vis-a-vis the global industry trends and discuses its current status. Since the core of this research centers on the auto component segment of the automotive industry, a major part of this chapter will deal with the discussion of this segment with a purpose of evaluating the current state of the industry from the perspective of advanced technology usage.

A Comparative Regional Analysis of Indian Auto Components Industry

Since its inception, the automotive industry is observed to be characterized—at a global level—by a high degree of regional concentration or clustering. This striking feature has nonetheless tended to be encrypted in many countries’ automotive sector depicting that the industry is often guided by regional/cluster dynamics. Clusters in the automotive industry however, differ in fundamental aspects from the usual ‘clusters’ or small firm agglomerations identified by Alfred Marshall. In fact, clusters in the automotive industry appear to take the form of ‘hub-spoke agglomerations’ consisting of complexes of suppliers surrounding a central hub or assembly facility. Similar to the global pattern, Indian automotive sector exhibits regionalization of the automotive firms scattered over four regions (North, South, West, and East) (see Fig. 5.1). The auto components firms are accordingly distributed in and around the principal automotive manufacturers thus creating a distinct geographical demarcation in terms of their location in regions.

AMT Diffusion in Indian Auto Components Industry: An Examination of the Determinants of Adoption

In Chap. 7 we found that firm-specific (structural) factors have explicit impact on the adoption pattern. There were also evidences at the micro-level on the role of external linkages on the adoption, having clear spatial connotations. This chapter extends our analysis by providing an econometric framework for explicating the impact of an array of the variables on firms’ adoption behaviour. The aim of this chapter is to test the empirical evidence on the possible set of factors determining adoption of AMTs in the Indian auto component industry. In line with our framework discussed in Chap. 3, the empirical exercise in this chapter is purported to take into account the influence of structural, (i.e., internal to the firm), and socio-economic (external to the firm) factors on the process of adoption. In congruence with the recent studies of technology adoption in the literature (as discussed in Chap. 2), the general framework of our analysis is specified where we distinguish a series of explanatory variables.

Theoretical and Empirical Literature on Diffusion: A Move Towards a Broader Perspective

Diffusion of new technologies broadly refers to the mechanism or process that spreads the improved technologies across socio-economic structure such as individuals, firms, or societies. It has been rightfully pointed out that the process of ‘diffusion’ is a quintessential part in innovation since without being widely circulated the new technology would have little productive or socio-economic significance. In many ways, understanding the mechanisms by which innovations are being adopted among a group of firms or individuals also renders insights as to how firms and other agents pursue innovative activities (viz., launching new products or creating new processes) to generate higher economic and social welfare as the learning and feedback effects which arise during the process of adoption enhance the original innovation (Hall 2004). Thus, the process of adoption/diffusion is not only significant in itself due to its impacts but is also instrumental in triggering further improvements in technology that leads to higher innovation at large.