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2757 items in total found

Working Papers | 2016

Interactive Discrete Choice Models

Manish Aggarwal

The interaction among the criteria plays an integral part in the human decision making
process. We propose new logit models of discrete choice to give the choice probability, taking into consideration the interaction among the attributes. We further extend the proposed models to also consider the complex human attitudinal character along with the interaction among the attributes. Concretely, we combine the established econometric models with Choquet integral, attitudinal Choquet integral, Choquet integral and generalized means, and generalized attitudinal Choquet integral. The proposed models of discrete choice can be seen as providing an overarching framework with the existing models as its special cases. The scope of the existing models are significantly expanded through the generation of a very wide range of choice probabilities arising in accordance with the adjustable attitudinal parameter(s).

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Working Papers | 2016

Review of Marketing / Business Analytics Infrastructure in SELECT India-based Organizations

Arindam Banerjee

The paper provides details of a detailed survey carried out in five Indian organizations operating in different industries-oil and gas, food products, stock trading, hospitality and industrial chemical. Diversity of industry was maintained to ensure some level of representativeness of the study to the typical India based organization. Study pertained to both the marketing and operations functions and was focused on how business data was managed and used for decision making.

One unique feature about these organizations was that none of them were of the profile of an active Analytics driven organization which would have a natural appetite for data science and data mining output. This was a deliberate strategy to the direct the study beyond the existing boundaries of what is perceived to be an "Analytics focused organization".

The major finding is that unlike popular perceptions, most organizations have a repository of useful information that can be utilized to support decision making. However, there are structural constraints such as top management commitments, culture, internal power and control, perceived value of analysis, near term priorities and exigency that impede organizational capabilities of developing processes for better analytical output. Also, focus seems to be erroneously targeted on analytical techniques and not on evaluating information value to decision making.

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Working Papers | 2016

Attitudinal Choquet Integrals for Strategic Decision Making

Manish Aggarwal

The compensation capabilities of Choquet integral are augmented by providing it with an additional parameter to relate the same with the complex attitudinal character of a decision maker (DM). The resulting operator is termed as attitudinal Choquet integral (ACI). ACI operator is further generalized to develop generalized attitudinal Choquet integral (GACI) that represents an exponential class of ACI operators. The special cases of ACI and GACI operators are investigated. The variants of ACI and GACI operators, termed as induced ACI and induced GACI, are introduced. The proposed operators promise a great potential in modelling any human aggregation process that inevitably characterizes the individual attitude of a DM, criteria importances, and interaction among the criteria at the same time.

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Working Papers | 2016

Discriminative Aggregation Operators for Multi Criteria Decision Making

Manish Aggarwal

A general aggregation formalism for multi criteria decision making (MCDM) applications is presented that allows us to represent the existing aggregation operators as well as generate the new ones. Using this formalism, we develop new discriminative aggregation operators for aiding MCDM. Four families of the proposed discriminative aggregation operators are developed and applied in a managerial decision making application.

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Working Papers | 2016

Rough Information Sets

Manish Aggarwal

The information sets are recasted as information granules by using the fuzzy equivalence relations. The proposed information granules can be visualized as the entropies corresponding to the information source values, drawn together by their similarity. The information granules are then further used to articulate rough information sets (RIS). The RIS are particularly useful in the approximation of decision concepts in terms of entropies (information). The usefulness of the rough information sets is demonstrated through a case-study.

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Working Papers | 2016

Uncertainty Modelling with Information and Probabilistic Information Granules

Manish Aggarwal

Linguistic representations by human brain are often characterized with an intertwined combination of imprecision (due to incomplete knowledge), vagueness or uncertainty. A powerful framework of information and probabilistic information granules is proposed to model this combination of different facets of uncertainty in natural representations without distortion of the underlying meaning. The proposed notions are deployed in formulation of a comprehensive approach to model complex uncertain situations involving imprecise/inexact probabilities of fuzzy events. The concepts are based upon the principle of information granulation that can be viewed as a human way of achieving data compression. The proposed approach closely resembles the implementation of the strategy of divide-and-conquer which brings it close to human problem-solving thought process. The study also makes an attempt to minimize distortion of information in its representation by fuzzy logic.

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Working Papers | 2016

Exploring Lin Kernighan neighborhoods for the indexing problem

Diptesh Ghosh

The indexing problem in automated machining environments aims to arrange tools in tool slots of a tool magazine for faster processing of jobs. This problem is called the indexing problem and has been widely studied in the literature. We present heuristics using Lin Kernighan neighborhood structures to solve the indexing problem. Two of the heuristics are local search heuristics and one is a tabu search heuristic. To the best of our knowledge this is one of the first implementations of tabu search on a Lin
Kernighan neighborhood structure.

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Working Papers | 2016

Contrasting Models of Incubation for Enterprise Creation: Exploring Lessons for Efficacy and Sustainability from Higher Education Institutions in India and the United Kingdom

Rakesh Basant and Sarah Cooper

Encouraging the establishment and growth of technology-based ventures continues to be the focus of attention from policy-makers globally, linked to enhanced levels of innovation, economic activity and wealth/employment creation. Higher education institutions (HEIs) are prominent among the public, private and not-for-profit organisations supporting the commercialisation of scientific outputs. Modes and vehicles adopted include spin-outs, science parks, intellectual property exploitation and different forms of incubation activity. Some HEIs in the United Kingdom have significant experience of commercialisation and technology transfer activities and have developed markedly different approaches. Meanwhile, HEIs in India are broadening their attention from their teaching-research focus to wider engagement in supporting venture creation. While approaches differ between HEIs all face issues of efficacy and sustainability. Set within the wider context of the HEI commercialisation agenda this paper focuses on incubation models, with particular attention to efficacy and sustainability dimensions. Using six case studies (three each from UK and India), we identify contrasting ways in which incubation was undertaken. Findings raise questions regarding whether and if so how HEIs should be involved in the business of incubation to enhance efficacy and provide a more broadly-based and robust platform for underpinning sustainability.

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Working Papers | 2016

Allocating tools to index positions in tool magazines using tabu search

Diptesh Ghosh

The arrangement of tools in tool slots of a tool magazine is an important problem in automated
machining environments. This problem is called the indexing problem and has been
widely studied in the literature. In this paper we propose a tabu search algorithm to solve the
indexing problem. We perform computational experiments on instances which are of reasonable
sizes.

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Working Papers | 2016

Earnings Management Strategies during Financial Distress

Neerav Nagar and Kaustav Sen

We examine whether financial distress and its severity have a role to play in managers' decisions with respect to the choice of earnings management strategies. Our results suggests that firms in initial stages of distress engage in real earnings management through a reduction in the spending on selling, general and administrative expenses, and engage in classification shifting to increase profitability and liquidity. When distress becomes severe, firms cut-back on production, engage in income-increasing accruals management, and increase their spending on selling, general and administrative expenses. Initial under-spending on selling, general and administrative expenses is opportunistic with an intention to show improved performance. In extreme distress, increase on such spending is a sound economic decision. Our findings provide insights into how managers of distressed firms trade-off between liquidity, profitability and solvency in both short-run and long-run.
JEL Codes: M41; G33.

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