Indian Institute of Management Bangalore

About: Indian Institute of Management Bangalore is a education organization based out in Bengaluru, Karnataka, India. It is known for research contribution in the topics: Emerging markets & Corporate governance. The organization has 491 authors who have published 1254 publications receiving 23853 citations. The organization is also known as: IIMB.

Advanced Regression Analysis

Abstract: Three topics are covered in this chapter. In the main body of the chapter, the tools for estimating the parameters of regression models when the response variable is binary or categorical are presented. The appendices cover two other important techniques, namely, maximum likelihood estimate (MLE) and how to deal with missing data.

How do new ventures in MNC ecosystems proactively overcome interfirm asymmetries

Abstract: Several contemporary large multinational corporations (MNCs) have developed interfirm ecosystems that are likely to attract a heterogeneous set of actors, including new ventures. New ventures are asymmetric vis-a-vis the focal MNC in terms of organisational size, structure and power which could be an impediment to the development of social capital between these sets of firms. And yet MNCs are potentially a source of novel information, opportunities and ideas. An interesting question to consider therefore is how new ventures overcome interfirm asymmetries to develop and leverage social capital with large MNCs. Our synthesis of the academic literature suggests that some new ventures are more adept than others at partnering with MNCs because they are more proactive in forming and leveraging interfirm ties with large MNCs. Insightful observations of four panellists shed light on how startups’ proactive behaviours can be vitally important in forming, consolidating and extending relationships with large MNCs.

On Construction of Multi-class Binary Neural Network Using Fuzzy Inter-cluster Overlap for Face Recognition

Abstract: In this paper, we propose a Novel Fuzzy-based Constructive Binary Neural Network (NF-CBNN) learning algorithm for multi-class classification. Our method draws a basic idea from Expand and Truncate Learning (ETL), which is a neural network learning algorithm. The proposed method works on the basis of unique core selection, and it guarantees to improve the classification performance by handling overlapping issues among data of various classes by using inter-cluster overlap. To demonstrate the efficacy of NF-CBNN, we tested it on the ORL face data set. The experimental results show that generalization accuracy achieved by NF-CBNN is much higher as compared to the BLTA classifier.

Can Microfinance Promote Livelihoods and Reduce Vulnerability Among Adivasis? A Study of Some NGO Interventions from Karnataka and Tamil Nadu:

Abstract: To what extent have NGO microfinance programmes for adivasi households promoted livelihoods and reduced poverty and vulnerability among them? This question is analysed with the help of primary data collected from Karnataka and Tamil Nadu states. Although adivasi households have joined microfinance groups, made small savings and availed credit facility, microfinance activities have not significantly improved livelihoods and reduced vulnerability. In the absence of savings products to meet expenses on housing and marriage, and access to formal social security services such as health insurance, adivasis are forced to borrow from informal sources. This places them into inextricable debt traps, undoing whatever positive impact that microfinance programmes may have. To avoid such a situation, meaningful savings products and access to social security are needed.