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Working Papers | 2016

Does odd or even make a difference

Sanjeev Tripathi

The evidence from literature on ultimatum games suggests that proposers often split the stake equally when they make an offer. In this study we investigate the effect of odd size stakes (OSS) in ultimatum games. OSS prevents the proposer from splitting the stake in two equal parts. The results suggest that when stakes are odd, proposers do not stay in the neighborhood of an equal split, rather they are tempted to move away and make lower offers.

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Working Papers | 2016

Intention to Participate in Cause Related Marketing:
Influence of Cause

Sonal Kureshi and Sujo Thomas

The most widely accepted definition for CRM is provided by Varadarajan and Menon (1988) and it defines CRM as "a process of formulating and implementing marketing activities that are characterized by an offer from the firm to contribute a specified amount to a designated cause when customers engage in revenue-providing exchanges that satisfy organizational and individual objectives". Several organizations in India like Dabur, Marico, P&G and ITC have implemented this form of social marketing practice.
In the view of the growing significance of CRM in countries like India which have been facing numerous social challenges, it becomes crucial to understand what factors lead to effective implementation of CRM. This study will provide insights into both type and scope of cause and their bearing upon consumer CRM participation intention.
Consumer data was collected using a structured questionnaire from the western region of India. Reponses pertaining to two aspects about the cause of the initiative, 'type of cause' and 'scope of cause' were collected. Results showed that consumer's interest in participation were found to differ significantly across both type of cause and scope of cause.

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Working Papers | 2016

Intuitionistic Fuzzy Model of Discrete Choice

Manish Aggarwal

The discrete choice models yield a decision-maker (DM)'s choices on the basis of the criteria values. In practice, however, the choices depend on the degree of enjoyment that an evaluating agent derives from a criterion, and which varies from individual to individual. To this end, we introduce an intuitionistic fuzzy variant of multinomial logit model of discrete choice that is able to explicitly consider the imprecision in the utility value, a DM associates with a criterion.

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Working Papers | 2016

Simulation of Expected Value Method in Project Risk Management in Two Different Construction Projects

Goutam Dutta

In this paper, we discuss the application of the expected value method of risk management. In the expected value method, there are two possible state of activity - as planned and risky. In a risky state, an activity will require additional time or cost, known as corrective cost and time, over and above the basic cost estimate or basic time estimates. We simulate two different construction projects - a metro construction project and a rural tourism project. The time and cost of an activity have been assumed to follow four different distributions - beta, uniform, normal and triangular. The simulation is performed on the basis of EVM and the expected cost and expected times are computed. We compare and contrast the project completion time and project cost of these four distributions.

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Working Papers | 2016

FRIW: Free Radicle Inspired Walk
Capturing Social Bonds for a Realistic Human Mobility Model

Kavitha Ranganathan

Studies on mobile applications for ad-hoc networks predominantly rely on simulations to evaluate various distributed algorithms. This has given rise to the need for realistic mobility models that incorporate social characteristics of human mobility. Based on basic properties of user movements captured via GPS traces and user interviews, we propose FRIW (Free Radicle Inspired Walk). FRIW leverages the free radicle concept from chemistry and social network theory to model social ties and group mobility in a campus setting. We find that FRIW is successful in generating realistic mobility patterns that can be used for modelling user movements in ad hoc network simulations.

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Working Papers | 2016

Nonlinear 0-1 knapsack problem with capacity selection

Sachin Jayaswal

We study a nonlinear 0-1 knapsack problem with capacity selection decision, as it arises as a part of facility location/service system design problems with congestion. The capacity selection decision gives rise to a non-convex objective function. We present two cutting plane based solution approaches: one based on Generalized Benders decomposition based, and the other based on a reformulation of the problem using additional auxiliary variables, followed by outer linearization of a resulting simple concave func-
tion in the constraint.

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Working Papers | 2016

Soft Information Set and its Application in Multi Criteria Decision Making

Manish Aggarwal

An information source value is perceived
differently by different agents. In this paper, we present a new knowledge representation structure, termed as soft information set (SIS), to provide a parameterized representation of the information values, as perceived by an agent. The properties of SIS are investigated and the
notion of relations in SIS is devised. SIS has potential to facilitate multi-criteria decision making (MCDM) under uncertainty, involving different information source values and agents. Its usefulness as a uncertainty representation
tool in MCDM is illustrated through case-studies.

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Working Papers | 2016

A Game Theoretic Approach to Community based Data Sharing in Mobile Ad hoc networks

Premm Raj H. and Kavitha Ranganathan

Government interventions on usage of free speech
for communication has been rising of late. The government of Iraq's ban on the Internet, ban of mobile communications in Hong Kong student protests highlight the same. Applications
like Firechat which use mobile ad hoc networks (MANETs) to enable off the grid communication between mobile users, have gained popularity in these regions. However, there have been limited studies on selfish user behavior in community
data sharing networks. We wish to study these data sharing communities using game theoretic principles and propose a normal form game. We model selfishness in community data sharing MANETs and define the rationality for selfishness
in these networks. We also look at the impact of altruism in community data sharing MANETs and address the issue of minimum number of altruistic users needed to sustain the MANET. We validate the novel model using exhaustive
simulations and empirically derive important observations.

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Working Papers | 2016

Web Content Analysis of Online Grocery Shopping Web Sites in India

Arindam Banerjee and Tanushri Banerjee

In this paper the authors evaluate online grocery shopping web sites catering to customers primarily in India. The process of evaluation has been carried out in 3 parts; by comparing the web content on their homepages, analysing customer reviews and also analysing their business performance as summarized on public web sites that use search optimization tools and analytical processes. This paper aims to study attributes from structured and unstructured data that lead to success of online grocery business in India. Results of the study will help identify the keywords that Indian consumers prefer to use while searching for information on online grocery websites. It will also identify consumer preferences from the customer review analysis. Additionally, it will identify the parameters from web site traffic metrics that drive per day revenue for the online retailer.

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Working Papers | 2016

Learning of Utilitarian Decision Model through Preferences

Manish Aggarwal

Understanding and predicting the decision making behaviour of individuals is a
subject of interest for marketers, strategists, economists and the computer scientists
alike. We develop an aproach to learn a decision maker (DM)'s behavioral process
by combining recent possibilistic discrete choice models with the emerging machine
learning methods. The proposed approach considers the utility values derived by a
DM from each of the attribute values (information source values). We take the
training information in the form of the exemplary multi-attribute preferences, and
the decision model is specified in terms of two vectors that are unique to a DM. The
experimental results on a set of 10 benchmark datasets suggest that our approach is
both intuitively appealing and competitive to state-of-the-art methods in terms of the
prediction accuracy.

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