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3558 items in total found

Working Papers | 2018

Leadership and Management of Public Sector Undertakings in an Emerging Economy

Vishal Gupta, Swanand Kulkarni, and Naresh Khatri

Public Sector Undertakings (PSUs) contribute significantly to the growth and economic development of any country. This study explores the key managerial challenges faced by the leaders and managers of public sector organizations. We interviewed 42 senior managers of PSUs from various industries representing 12 Indian states representing all the regions of India. Specifically, three key managerial challenges emerged in our study: political interference and lack of autonomy, rigid rules and HR practices, and lack of employee motivation. Positive leader personality, communication skills, change- and relation-oriented behaviors, HR skills, and decision-making emerged as top leader qualities. Staffing, training and development and performance management emerged as the top priorities of HR departments of PSUs. Public-service motivation, job security and work environment were the top reasons for continuing to work in PSUs for Indian leaders. Implications for theory and practice are discussed.

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Working Papers | 2018

Is the Past Still Holding Us Back? A Study on Intergenerational Education Mobility in India (revised as on 26.09.18)

Kishan P K V

This paper explores various aspects of, and factors affecting intergenerational education mobility in India. We employ IHDS-II (2011-12) and prepare a representative dataset that goes beyond 'co-resident only' son-father pairs by utilizing the retrospective information conveying the educational attainment of the father of the male household head. From the resulting sample of 44,532 son-father pairs and appropriate cohort analysis, we find that there is still a high degree of intergenerational persistence in education, although the same is decreasing steadily over time. Through quantile regressions, we detect a non-linearity in the relationship between fathers' and sons' schooling outcomes along the education distribution. Moreover, the mobility gap between the historically advantaged subgroups (urban population, upper castes, Hindus, etc.) and the others (rural population, lower castes, Muslim, etc.) increasingly widens along the middle and upper quantiles of the distribution. Finally, "Higher Inequality (during fathers' generation) à Lesser Mobility" nexus in education plays out for the Indian scenario and thus corroborates the 'Great Gatsby Curve'. Other macro variables, economic growth and public expenditure in education, bear a positive association with education mobility.

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Working Papers | 2018

Indian Antecedents to Modern Economic Thought

Satish Y. Deodhar

The history of economic thought begins with salutations to Greek writings of Aristotle and Plato. While the fourth century BCE Greek writings may have been the fount of modern economic thought that emerged in Europe starting 18th century CE, there has been a general unawareness of the economic thinking that emanated from the Indian subcontinent. Pre-classical thoughts that had appeared in Vedas dating a millennium prior to the Greek writings had culminated in their comprehensive coverage in the treatise Arthashastra by Kautilya in the fourth century BCE. In this context, the paper outlines various ancient Indian texts and the economic thoughts expressed therein, delves on the reasons why they have gone unnoticed, brings to the fore the economic policies laid down by Kautilya, shows how these policies exemplify pragmatic application of the modern economic principles, and brings out in bold relief, the contribution of this Pre-Classical literature in the history of economic thought.

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Working Papers | 2018

Marketplace Options in an Emerging Economy Local Food Marketing System- Producers' Choices, Choice Determinants and Requirements

Aashish Argade and A. K. Laha

One of the important objectives of reforms in Indian agricultural marketing was to stimulate competition in the local food marketing system dominated by the state-regulated APMC marketplaces. This study was taken up to understand the different kinds of marketplaces that were available to producers besides the APMCs. Based on survey conducted in one of the pioneering states that introduced reforms, it was found that APMC and farm-gate emerged as the dominant marketplace options. The factors influencing choice of marketplaces were identified using binary logistic regression. Perishability of the produce, and services such as grading, storage and transport provided by buyers were found to be significant determinants of marketplace choice. A post-hoc survey was conducted to gauge farmers' expectations of services and facilities of a marketplace by presenting four scenarios. Even as farmers seem to expect a full-fledged APMC with wide-ranging facilities, warehousing seemed to be their major requirement. Willingness to pay for facilities and services was an important takeaway from the findings. The study has important implications for policy design and implementation, and scope for private sector participation

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Journal Articles | 2017

Evolutionary algorithm for bilevel optimization using approximations of the lower level optimal solution mapping.

Ankur Sinha, Pekka Malo, and Kalyanmoy Deb

European Journal of Operational Research

Bilevel optimization problems are a class of challenging optimization problems, which contain two levels of optimization tasks. In these problems, the optimal solutions to the lower level problem become possible feasible candidates to the upper level problem. Such a requirement makes the optimization problem difficult to solve, and has kept the researchers busy towards devising methodologies, which can efficiently handle the problem. Despite the efforts, there hardly exists any effective methodology, which is capable of handling a complex bilevel problem. In this paper, we introduce bilevel evolutionary algorithm based on quadratic approximations (BLEAQ) of optimal lower level variables with respect to the upper level variables. The approach is capable of handling bilevel problems with different kinds of complexities in relatively smaller number of function evaluations. Ideas from classical optimization have been hybridized with evolutionary methods to generate an efficient optimization algorithm for a wide class of bilevel problems. The performance of the algorithm has been evaluated on two sets of test problems. The first set is a recently proposed SMD test set, which contains problems with controllable complexities, and the second set contains standard test problems collected from the literature. The proposed method has been compared against three benchmarks, and the performance gain is observed to be significant. The codes related to the paper may be accessed from the website http://bilevel.org.

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Journal Articles | 2017

A novel sandwich algorithm for empirical Bayes analysis of rank data

Arnab Kumar Laha, Somak Dutta, and Vivekananda Roy

Statistics and its interface

Rank data arises frequently in marketing, finance, organizational behavior, and psychology. Most analysis of rank data reported in the literature assumes the presence of one or more variables (sometimes latent) based on whose values the items are ranked. In this paper we analyze rank data using a purely probabilistic model where the observed ranks are assumed to be perturbed versions of the true rank and each perturbation has a specific probability of occurring. We consider the general case when covariate information is present and has an impact on the rankings. An empirical Bayes approach is taken for estimating the model parameters. The Gibbs sampler is shown to converge very slowly to the target posterior distribution and we show that some of the widely used empirical convergence diagnostic tools may fail to detect this lack of convergence. We propose a novel, fast mixing sandwich algorithm for exploring the posterior distribution. An EM algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed for estimating prior hyperparameters. A real life rank data set is analyzed using the methods developed in the paper. The results obtained indicate the usefulness of these methods in analyzing rank data with covariate information.

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Journal Articles | 2017

Approximated set-valued mapping approach for handling multiobjective bilevel problems

Ankur Sinha, Pekka Malo, and Kalyanmoy Deb

Computers & Operations Research

A significant amount of research has been done on bilevel optimization problems both in the realm of classical and evolutionary optimization. However, the multiobjective extensions of bilevel programming have received relatively little attention from researchers in both the domains. The existing algorithms are mostly brute-force nested strategies, and therefore computationally demanding. In this paper, we develop insights into multiobjective bilevel optimization through theoretical progress made in the direction of parametric multiobjective programming. We introduce an approximated set-valued mapping procedure that would be helpful in the development of efficient evolutionary approaches for solving these problems. The utility of the procedure has been emphasized by incorporating it in a hierarchical evolutionary framework and assessing the improvements. Test problems with varying levels of complexity have been used in the experiments.

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Journal Articles | 2017

Optimal management of naturally regenerating uneven-aged forests

Ankur Sinha, Janne Ramo, Pekka Malo, and Olli Tahvonen

European Journal of Operational Research

A shift from even-aged forest management to uneven-aged management practices leads to a problem rather different from the existing straightforward practice that follows a rotation cycle of artificial regeneration, thinning of inferior trees and a clearcut. A lack of realistic models and methods suggesting how to manage uneven-aged stands in a way that is economically viable and ecologically sustainable creates difficulties in adopting this new management practice. To tackle this problem, we make a two-fold contribution in this paper. The first contribution is the proposal of an algorithm that is able to handle a realistic uneven-aged stand management model that is otherwise computationally tedious and intractable. The model considered in this paper is an empirically estimated size-structured ecological model for uneven-aged spruce forests. The second contribution is on the sensitivity analysis of the forest model with respect to a number of important parameters. The analysis provides us an insight into the behavior of the uneven-aged forest model.

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Journal Articles | 2017

A review on bilevel optimization: from classical to evolutionary approaches and applications

Ankur Sinha, Pekka Malo, and Kalyanmoy Deb

IEEE Computational Intelligence Society

Bilevel optimization is defined as a mathematical program, where an optimization problem contains another optimization problem as a constraint. These problems have received significant attention from the mathematical programming community. Only limited work exists on bilevel problems using evolutionary computation techniques; however, recently there has been an increasing interest due to the proliferation of practical applications and the potential of evolutionary algorithms in tackling these problems. This paper provides a comprehensive review on bilevel optimization from the basic principles to solution strategies; both classical and evolutionary. A number of potential application problems are also discussed. To offer the readers insights on the prominent developments in the field of bilevel optimization, we have performed an automated text-analysis of an extended list of papers published on bilevel optimization to date. This paper should motivate evolutionary computation researchers to pay more attention to this practical yet challenging area.

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Journal Articles | 2017

Accounting for political opinions, power, and influence: A Voting advice application

Tommi Pajala, Pekka Korhonen, Pekka Malo, Ankur Sinha, Jyrki Wallenius, and Akram Dehnokhalaji

European Journal of Operational Research

Voting Advice Applications (VAAs) are online decision support systems that try to match voters with political parties or candidates in elections, typically based on how each responds to a number of policy issue statements. Such VAAs play a major role in many countries. In this paper, we describe the development and large-scale application of a new innovative matching algorithm for the most widely used VAA in Finland. We worked closely with the owner of the VAA, the largest daily newspaper in Finland, Helsingin Sanomat. Their previous algorithm, which one might call a “naive” approach, was improved by including measures of candidate’s political power and influence, using proxy variables of media visibility and incumbency status. The VAA was implemented for the 2015 Parliamentary Election in Finland; our matching algorithm was used by 140,000 voters (26.7% of the electorate) in the Helsinki election district. The innovative algorithm generated recommendations that many voters were happy about, followed by users’ incidental comments that this was the first time the VAA recommended candidates they wanted to vote for. This showed the importance of catering to different kinds of voters with a model not previously considered by any VAA in any country.

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