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3819 items in total found

Journal Articles | 2017

Ownership structure and internationalization of Indian firms

Chitra Singla, Rejie George, and Rajaram Veliyath

Journal of Business Research

This paper examines the relationship between ownership structure and the firm internationalization, in a longitudinal sample of Indian firms. Drawing from principal-principal (PP) agency theory and the resource-based view (RBV) of the firm, we argue that divergent motivations among the firm's owners affect the firm's inclination to pursue internationalization, while resource heterogeneity among the firm's owners affects the firm's capability to pursue internationalization. Since both motivation and capability are required for a firm to pursue any strategic initiative, we argue that differences in ownership, which influences both the motivation and the capability of firms, impact firm's internationalization strategies in different ways. In addition, through examining two modes of internationalization, i.e., outward foreign direct investment (FDI) and exports from a prominent emerging economy, we uncover an interesting dichotomy. While family and other domestic owners favor exports (and not FDI), foreign owners favor both exports and FDI. Further, we find that family owners have a dominant influence on internationalization and their preferences appear to supersede those of the other owners.

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Journal Articles | 2017

Classification shifting: impact of firm life cycle

Neerav Nagar and Kaustav Sen

Journal of Financial Reporting and Accounting

Purpose - This paper examines whether firms in the decline stage of life cycle manipulate core or operating income through misclassification of operating expenses as income-decreasing special items. Design/methodology/approach - Our sample comprises of firms from an emerging market, India with data from 1996-2011. We use the methodology given in McVay (2006) and multiple regressions. Findings - Managers of Indian firms also engage in classification shifting, primary incentive being desire to avoid reporting of operating losses. Further, the use of classification shifting is dependent upon the stage of life cycle in which firm is in. Specifically, firms in the decline stage of life cycle are more likely to use classification shifting to avoid reporting of operating losses. Practical implications - The paper sheds light on a critical phase of the firm life cycle-decline, which increases the possibility of use of classification shifting-an earnings management technique which auditors, investors and regulators find tough to detect. Originality/value - We extend the literature on classification shifting, and present first evidence that such shifting is more likely to take place during the decline phase of firm life cycle.

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Journal Articles | 2017

Brand adoption by BoP retailers

Piyush Kumar Sinha, Suraksha Gupta, and Saurabh Rawal

Qualitative Market Research: An International Journal

Previous studies with regard to brand adoption by retailers have focussed on large retailers who are approached directly by the brands. There is a lack of studies on how BoP retailers adopt brands who sell to a very different set of customers and are served indirectly through long indirect channels. Most studies have approached the subject from a distribution perspective of reaching to these markets. Sixty retailers belonging to different villages of Central and North Gujarat, were interviewed to understand their brand adoption process. The interviews were audio recorded, transcribed and analysed. A grounded theory based analysis was carried out. The analysis brought out six criteria used by the retailers in selecting brands with demand for the brand as the most dominant factor. Other criteria included brand adoption by other retailers, profitability, influence of wholesaler/distributor, and packaging.

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Weaving Analytics for Effective Decision Making" SAGE India, August 2017

Books | 2017

Weaving Analytics for Effective Decision Making" SAGE India, August 2017

Banerjee A and Banerjee T.

Sage

Working Papers | 2017

What Does Matched Bank-Firm Data Tell Us about the Moral Hazard in Lending Decisions of State-Owned Banks in India? (Revised as on January 3, 2018)

Balagopal Gopalakrishnan

In this study, we examine quality of the lending decisions of public sector banks (PSBs) in India with a novel dataset which allows the identification of both the banks by the ownership types and their borrowers. We use a lender type prediction model where the bank type is determined by observable risk proxies such as ex-ante credit ratings, which influence the lending decision. The analysis of the lending decisions indicate that the PSBs are more likely to lend to observably less creditworthy firms relative to the private banks (PBs). We also find that smaller firms have a higher likelihood of obtaining credit exclusively from PSBs, possibly, consistent with the directed lending programs of the government. If we exclude systemically important banks and their borrowers from the sample, the likelihood of riskier firms obtaining credit exclusively from PSBs increases. Finally, firms which are likely to be impacted by political regime changes have a higher likelihood of an exclusive borrowing relationship with PSBs. The study contributes to the contemporary debates on the role of market discipline, disclosures, and moral hazard in banking.

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Working Papers | 2017

Exploring Linkages between Innovation and public policy- challenges and Opportunities

Rakesh Basant

Significant research has gone into the analysis of the complex linkages between public policy and innovation. While this research has generated a lot of interesting insights, it has also identified several gaps in our understanding of these linkages. This paper is an attempt to pool together some of the ideas that academic research has highlighted on the linkages between innovation and public policy and identify the current challenges as well as opportunities for meaningfully exploring these linkages further. Through a select review of the literature the paper (i) provides a broad overview of the public policy-innovation interface; (ii) discusses issues of conceptualizing and measuring innovation, innovation related activities and policy changes; (iii) summarizes mechanisms through which various policies impact innovation along with available evidence on the same; and (iv) identifies challenges in exploring policy-innovation interface along with a few potential areas of research in the context of India.

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Working Papers | 2017

Mathematical Modelling for Time-of-Use Pricing of Electricity in Monopoly and Oligopoly

Nidhi Kaicker, Goutam Dutta, Debamanyu Das, and Subhashree Banerjee

This study establishes the feasibility condition for efficiency gains to arise from time-of-use pricing in the electricity market in a monopolistic and oligopolistic set up using constrained optimization. In an oligopolistic set-up, the strategic interaction between producers depends on the level of demand. In case of high demand, the producers compete on the basis of output they will produce, resulting in a Cournot-type competition. On the other hand, in case of low demand, an oligopolistic structure may break with only the most efficient firm operating, or results in the emergence of leader firms and follower firms, i.e. the Stackleberg model.

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Working Papers | 2017

Vertical Integration, Market Structure and Competition Policy: Experiences of Indian Manufacturing Sector during the Post Reform Period

Rakesh Basant and Pulak Mishra

In the context of declining degrees of vertical integration in major industries of Indian manufacturing sector during the post-reform period, the present paper is an attempt to examine how such 'vertical disintegration' has affected firms' market power and its implications for competition policy. Using panel dataset of 49 majors industries of Indian manufacturing sector for the period 2003-04 to 2010-11 and applying the system GMM approach to estimate of dynamic panel data models, the paper finds that vertical integration does not cause any significant impact on average market power of firms in an industry. Instead, it is influenced by market size, and selling and technology related efforts. While selling intensity has a positive impact on market power, the impact of market size and technology intensity is found to be negative. Notably, like vertical integration, market concentration, import to export ratio, and capital intensity also do not have any significant impact on market power. The findings of this paper, therefore, have important implications for competition law and policy in general and policies and regulation relating to technology development and international trade in particular.

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Working Papers | 2017

Globalization and Inequality- A Pathway Through Education (Revised as on 02.04.18)

Kishan P K V

This study investigates the effect of globalization on economic inequality in a country through the channel of education. We measure globalization by the KOF globalization index (a composite index consisting of elements of economic, social, and political dimensions of globalization), economic inequality by the Gini coefficient of consumption/income distributions, and education outcomes by mean years of schooling in a country. An econometric model using appropriate panel data techniques is estimated for a sample of about 150 countries over the period 1980-2013. The results suggest that globalization improves the situation of economic inequality in a country, i.e. inequality in the country decreases. However, the precondition to this is that the population of the country is very less educated. As the country becomes more globalized, and the educational outcomes improve, the restorative effects of globalization on income inequality go down. At a turnaround point of about 6.73 mean years of schooling, globalization works towards worsening income inequality. The empirical results are robust to the use of inequality index from a separate data source and the change in time span of the study (1980-2008).

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Working Papers | 2017

New Approaches to Prediction using Functional Data Analysis

A. K. Laha and Poonam Rathi

In this paper we address the problem of prediction with functional data. We discuss several new methods for predicting the future values of a partially observed curve when it can be assumed that the data is coming from an underlying Gaussian Process. When the underlying process can be assumed to be stationary with powered exponential covariance function we suggest two
new predictors and compare their performance. In some real life situations the data may come from a mixture of two stationary Gaussian Processes. We
introduce three new methods of prediction in this case and compare their performance. In case the data comes from a non-stationary process we propose a modification of the powered exponential covariance function and study the performance of the three predictors mentioned above using three real-life data sets. The results indicate that the KM-Predictor in which the training data is clustered using the K-Means algorithm before prediction can be used in several real life situations.

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