Department of Management Studies (MS)https://etd.iisc.ac.in/handle/2005/272024-03-28T16:30:46Z2024-03-28T16:30:46ZAbsorptive Capacity, Cluster Level Interactions, Innovation and Performance of Firms in the High-tech Manufacturing Cluster of BengaluruDeepak, Chttps://etd.iisc.ac.in/handle/2005/53682021-10-01T07:41:38ZAbsorptive Capacity, Cluster Level Interactions, Innovation and Performance of Firms in the High-tech Manufacturing Cluster of Bengaluru
Deepak, C
Researchers have identified absorptive capacity, which is a measure of dynamic capability of a firm, as one of the critical factors that drives interactions of a firm with other firms and associated institutions within and outside a cluster, and thereby enhance the innovation performance of a firm. To meet this end, this study quantified absorptive capacity of a firm through the development of index numbers of both internal and external factors of absorptive capacity. Further, it extended the conceptualization of degree of cluster linkages (comprising the degree of intra-cluster linkages and the degree of extra-cluster linkages) to include a gamut of interactions between a firm and other stakeholders within and outside a cluster. The study based on primary data from 101 firms belonging to electronics, electrical, machine tools and pharmaceutical industries, was carried out in the context of Bengaluru high-tech manufacturing cluster. Firstly, it examined the influence of absorptive capacity on the degree of cluster linkages, and in turn, on innovation performance of a firm. It was ascertained that while the internal factors of absorptive capacity drive both the degrees of intra-cluster and extra-cluster linkages, external factors of absorptive capacity drive only the degree of intra-cluster linkages but not the degree of extra-cluster linkages. But, both the degrees of intra-cluster and extra-cluster linkages contributed positively to firm-level innovation. In addition, the study probed the influence of factors of degree of cluster linkages on innovation performance of a firm at a micro-level. It was discovered that the ability of a firm to integrate global value chain both vertically and horizontally through extra-cluster linkages determined the innovation performance of a firm in a cluster. The study explored the factors that determine the propensity of a firm in a cluster to obtain patents. It was found that both the absorptive and invention capacities had a significant positive influence on the propensity of a firm to patent. In addition, while the traditional motivators, had a significant positive influence on the propensity of a firm to patent, de-motivator factors constituting time, market and cost constraints, and procedural issues had a significant negative influence on the propensity of a firm to patent. Further, prior to the analysis of role of patenting in enhancing firm level innovation and firm performance, the study examined the relationship between firm-level innovation and firm performance considering the interaction effect of various firm-specific factors. It was found that the firm performance was jointly determined by the innovation performance of a firm and certain firm-specific factors. Finally, the study probed the effect of patenting on innovation and firm performance. It was brought out that although patenting had a significant influence on the innovation performance of a firm, it had no significant influence on firm performance. Based on the comprehensive research findings, appropriate policy implications have been derived.
Algorithms For Geospatial Analysis Using Multi-Resolution Remote Sensing DataUttam Kumar, *https://etd.iisc.ac.in/handle/2005/22802020-05-11T10:14:36Z2014-02-28T00:00:00ZAlgorithms For Geospatial Analysis Using Multi-Resolution Remote Sensing Data
Uttam Kumar, *
Geospatial analysis involves application of statistical methods, algorithms and information retrieval techniques to geospatial data. It incorporates time into spatial databases and facilitates investigation of land cover (LC) dynamics through data, model, and analytics. LC dynamics induced by human and natural processes play a major role in global as well as regional scale patterns, which in turn influence weather and climate. Hence, understanding LC dynamics at the local / regional as well as at global levels is essential to evolve appropriate management strategies to mitigate the impacts of LC changes. This can be captured through the multi-resolution remote sensing (RS) data. However, with the advancements in sensor technologies, suitable algorithms and techniques are required for optimal integration of information from multi-resolution sensors which are cost effective while overcoming the possible data and methodological constraints. In this work, several per-pixel traditional and advanced classification techniques have been evaluated with the multi-resolution data along with the role of ancillary geographical data on the performance of classifiers.
Techniques for linear and non-linear un-mixing, endmember variability and determination of spatial distribution of class components within a pixel have been applied and validated on multi-resolution data. Endmember estimation method is proposed and its performance is compared with manual, semi-automatic and fully automatic methods of endmember extraction. A novel technique - Hybrid Bayesian Classifier is developed for per pixel classification where the class prior probabilities are determined by un-mixing a low spatial-high spectral resolution multi-spectral data while posterior probabilities are determined from the training data obtained from ground, that are assigned to every pixel in a high spatial-low spectral resolution multi-spectral data in Bayesian classification. These techniques have been validated with multi-resolution data for various landscapes with varying altitudes. As a case study, spatial metrics and cellular automata based models applied for rapidly urbanising landscape with moderate altitude has been carried out.
2014-02-28T00:00:00ZThe Allure of Departed Colleagues : An Examination of Career Mobility in Competitive Labor MarketsGopakumar, M Ghttps://etd.iisc.ac.in/handle/2005/37312019-09-13T11:12:19Z2018-06-19T00:00:00ZThe Allure of Departed Colleagues : An Examination of Career Mobility in Competitive Labor Markets
Gopakumar, M G
In global corporations, work is increasingly organized around projects and individuals are constantly working with new constellations of partners across locational and temporal boundaries. In order to be successful in such settings, individuals have to form and maintain relationships with those they need to learn from and coordinate with. Recent studies suggest that these social ties provide resources and support as well as create normative pressures that strengthen the attachment of employees with the firm and lead them to stay with the firm. In contrast, the strength of an individual’s attachment with the organization given the departure of connected colleagues remains largely under theorized, and consequently, its implications have not been adequately studied. We address these gaps by examining whether ties to colleagues who leave the firm activate different mechanisms which can weaken their binds with the organization. This study assume significance in the context of contemporary free-agent labor markets where career trajectories are proposed to unfold in a series of short stints at multiple firms as opposed to life-long career in a single firm.
We develop theoretical arguments predicting the effect of workplace relationships on career mobility decisions by building on prior research into distributed work, changing nature of careers, social comparison, homophily, and structural equivalence. The main contention of this study is that the departure of one or more coworkers serves as powerful signals that unsettle the feeling of belongingness the focal employee enjoys with other teammates who choose to stay with the firm. Further, we propose that the influence of those departed employees will be higher when they are collocated and occupied similar professional roles as the focal employee.
To test the arguments, we analyze entire project co-assignment data across five years that linked 728 geographically distributed employees who were engaged in software development and delivery activities at a multi-national high technology firm. Our findings suggest that instead of seeking belonging and viability with coworkers, employees are actively seeking cues from their network of colleagues and continuously making subjective assessments of career success. In distributed work settings, such cues circulate more among physically proximate than distant employees and formal roles of coworkers serve as referent points for those signals. These mechanisms collectively influence voluntary turnover decisions. Using a classification model, we further demonstrate how insights from this study can be used by human resource management practitioners to assess and contain the flight risk of their valuable talent.
2018-06-19T00:00:00ZAnalyses of Performance, Risk and Underpricing of Indian IPOsHotkar, Vinay Chttps://etd.iisc.ac.in/handle/2005/57732022-07-21T10:36:10ZAnalyses of Performance, Risk and Underpricing of Indian IPOs
Hotkar, Vinay C
Across geographies, unlisted firms raise capital from individuals and institutions by issuing Initial Public Offering (IPO) through finanical markets. IPOs are of great interest to investors, regulators, issuing firms and financial researchers alike. In this thesis we longitudinally analyze the daily performance (in terms of buy and hold abnormal returns) for three years and daily (total, systematic and unsystematic) risk for one year after the launch for Indian IPOs. We also study the globally occurring stylised phenomenon of underpricing in the context of Indian IPOs. We consider a comprehensive set of financial fundamentals of the issuing firms and several IPO specific variables that might be significantly associated with these IPO characteristics, after controlling for the prevailing market and macroeconomic conditions in which the IPOs are launched. While we employ routine multiple and logistic regression, and regression and classification trees to investigate the associative relationships, we enhance and use an existing algorithm for time series factor analysis to measure and quantify the control variables capturing the prevalent macroeconomic conditions.
Using the above methodology and a sample of 324 IPOs launched in the National Stock Exchange, India from 1999 to 2016, it is found that on an average, the performance of Indian IPOs deteriorates both in the short and long run. Though endogenous firm/IPO-specific variables such as age, percentage of stakes diluted by the promoter and non-promoter group in the IPO, etc. are found to be significantly associated with the IPO performance, the exogeneous market and macro-economic conditions during the launch of an IPO are also found to play critical roles in determining its performance. It is found that the IPO risk is primarily associated with the macro-economic conditions in which the IPOs are launched and no firm/IPO-specific variable is found to have any significant association with the risk of investing in an IPO. The average quantum of underpricing (first day return) for the sample of 324 IPOs is found to be 22.5%, with 66.1% of them being (just categorically) underpriced. Like their performances, while several endogenous firm/IPO-specific variables such as earnings per share, percentage of secured loan, growth rate of pre-tax profit margin etc. are found to be significantly associated with underpricing, the main takeaway of the analysis is that it is the exogeneous market sentiment that is the primary determinant of underpricing. IPOs launched in a bull market are more likely to be underpriced, and it is also found that most IPOs are also launched when the market is ascending. This is proferred as an alternative explanation for the empirically observed global phenomenon of IPO underpricing, at least for the case of the Indian IPOs.