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Working Papers | 2016

Speeding up neighborhood search for the tool indexing problem

Diptesh Ghosh

The arrangement of tools in tool holding pockets of a tool magazine in a CNC machining center plays an important role in reducing processing times of complex job processes in automated machining environments. This problem is called the ATC indexing problem (ATCIP). Computing the cost of a solution for an ATCIP instance of size $n$ requires $\\mathcal{O}(n^2)$ time, so that neighborhood search iteration for the ATCIP on an $\\mathcal{O}(n^2)$ neighborhood requires $\\mathcal{O}(n^4)$ time. We describe techniques to reduce this effort for two common neighborhood structures from $\\mathcal{O}(n^4)$ time to $\\mathcal{O}(n^2)$ time.

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Working Papers | 2016

Orphan Food? Nay, Future of Food !
Understanding the Pulse of the Indian Market

Satish Y. Deodhar

Pulses have been an important traditional food crop of India. India is the largest producer and consumer of pulses. However, pulse acreage and yield has not kept pace with the growing demand in India. As a result, India is also the single largest importer of pulses today. While Green Revolution in India focused on cereal crops, pulses remained an orphaned and neglected crop. However, from the triple perspective of economy, environmental sustainability, and provision of balanced nutrition; pulses have now been recognized as the future of food. India can substantially increase her production and yield in pulses with a strategic emphasis on research in public and private sector, expanding irrigation infrastructure, provision of MSP to pulses, assured procurement by government for PDS/MDMS, facilitation of mini dal mills and storage at village level, and allowing futures markets to function. Price stability for consumers can also be attained by reduction in middlemen margins through modern warehousing, FDI in wholesale and retail trade, introducing competition to APMC markets, and substantial reduction in import tariffs on substitute products such as chicken.

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Working Papers | 2016

Impact of Affirmative Action in Higher Education for the Other Backward Classes in India

Rakesh Basant and Gitanjali Sen

This paper measures the impact of quota-based affirmative action in higher education (HE) in India for Other Backward Classes (OBC), implemented from 2008. Since the immediate impact would be felt by OBCs who were eligible to go to college at the time of the implementation, we compare the differences in participation in HE by the younger (18-23 years) and the older (24-29 years) age groups within eligible OBCs, with similar differences in the general caste population. The same double difference is also compared across states with different histories of affirmative action to ascertain if there are regional variations in the impact of the policy, with the expectation that the impact would be higher in regions with no history of affirmative action. Our results from the Difference in Difference (DD) estimates based on National Sample Survey data for 2011-12 do not show a positive impact of the policy on the participation of OBCs. In fact, the impact seems to be negative in all regions, though statistically insignificant, except the East which lacks the long history of affirmative action. A comparison of the East without a long history of affirmative action with the South having a long history of such policy, using triple difference method, produces positive treatment effects, but the estimate loses statistical significance once we control for observable covariates. Our results suggest that the generalized nation-wide policy of this kind may not be relevant for issues which are more regional in nature. (JEL Codes: H75, I23, I24, I25, I28, J15, O15).

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Working Papers | 2016

Impact of Store format on Shopping Involvement

Piyush Kumar Sinha and Dwarika Prasad Uniyal

Store formats exist in three forms of convenience, variety and experience. Shopping involvement tends to change across these formats. This current study (a) establishes the role of store formats on shopping involvement, (b) understands the change in the nature of involvement as the shopper moves to an experience store from a variety or a convenience store format, and (c) measures shopping involvement as different from purchase involvement or purchase-decision involvement. A 3 X 3 factorial design was created using the three formats and three levels of extent of information search representing different buying decisions. Participant observations at different formats were carried out, which was followed by in-depth interviews to understand the motivations and gratifications with regard to shopping and store formats. A new scale to measure Shopping Involvement was developed as different from purchase and purchase-decision involvement.

The study found that store formats impacted shopping involvement levels. The convenience format showed a lower level of involvement compared to other formats. However, there was no significant difference between the involvement levels of the variety store format and experience store format. The study showed that the expressive aspect of involvement became more prominent in experience store, while the functional involvement did not increase to the same extent. Shopping involvement in each of these formats also varied with the extent of information search. Retailers would benefit by adopting in-store activities that enhance involvement for the format used. They need to provide the correct type and amount of increase information to the shoppers for better shopping experience and building loyalty.

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Working Papers | 2016

Climate Change in Madhya Pradesh: Indicators, Impacts and Adaptation

Vimal Mishra, Reepal Shah, and Amit Garg

Climate variability and climate change pose an enormous pressure on population, infrastructure, livelihood, and socio-economic conditions. Evidences of climate change are already visible on many sectors such as agriculture, water resources, infrastructure, ecology, and biodiversity. While the problem of climate change is at global scales, its detrimental impacts are often visible at local scales, which highlight the need of climate change impacts assessment and policy making at a local administrative levels. Using the observed and projected data for the future, climate change assessment was performed for the state of Madhya Pradesh. Results indicate that a majority of the state of MP experienced a significant decline in the monsoon season precipitation during the period of 1951-2013. Air temperature increased significantly in the post-monsoon (October- December) season. Results also indicated that the frequency of severe, extreme, and exceptional droughts has increased in Madhya Pradesh. Droughts in the recent years were severe and wide-spread. The number of hot days has
increased significantly in the state. However, changes in hot nights, cool days, and cool nights were not found statistically significant during the period of 1951-2013. The number of heat waves became more frequent during the recent years in Madhya Pradesh. Projected changes under the future climate were estimated using the high resolution downscaled and bias corrected projections based on the five best models. The five best models were selected out of 40 CMIP5 models and 9 CORDEX South Asia models after a careful evaluation against the observed precipitation and air temperature. Results showed that for the majority of the state RCP 4.5 is the most representative while a few areas in the northern regions have experienced changes in air temperature that follow RCP 6.0 and 8.5. About 30% of the state is projected to experience more than 2ºC warming by 2050 under the RCP 8.5 scenario. The monsoon season precipitation is projected to increase in most of the RCPs by 5-15% under the projected future climate. However, the monsoon season precipitation is projected to decline in the Near (2016-2045) term climate under the RCP 4.5 scenario. Extreme precipitation events are projected to become more frequent in most of the regions of the state under the projected future climate. Frequency of severe, extreme, exceptional droughts is projected to increase under the RCP
4.5 scenario. Moreover, increased warming under the projected future climate may lead to more frequent, severe, and wide-spread droughts during the monsoons season. Almost in all the RCPs, the frequency of hot days, hot nights, and heat waves is projected to increase in Madhya Pradesh. Most of the district of the state are projected to experience 1-1.2 ºC increase in mean annual air temperature in Near term while 2-2.5 ºC warming in the Mid (2046-2075) term climate. A significant increase in the number of hot days, hot nights, droughts, and extreme precipitation is likely under the future climate, which may pose enormous pressure on agriculture, water resources, infrastructure, tourism,
and energy sectors. To effectively manage the detrimental impacts of climate change, local level policies will be required with a careful analysis of the natural resources and impacts of climate change on various sectors.

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Working Papers | 2016

Socio-ecological Systems Modeling for Climate and Community Resilience

Anamika Dey, Gurdeep Singh, and Anil K. Gupta

Variability, complexity, simultaneity and change in environmental parameters affect social groups. Homeostatic advantages due to resource surplus, institutional access technology and social network alter perception and community response to climate risks. Modelling requires consideration of socio-ecological and eco-institutional interactions with social, biological and climatic parameters. We model and manage the multi-layer interactions among social institutions, climatic fluctuations and the resultant changes in the rules governing these interactions with the objective of increasing resilience of social and ecological systems to climate change.

We enumerate coping strategies adopted across genders to suggest modelling approaches for climate-resilient socio-ecological systems. Statistical tools enable discrete and continuous perspectives in different classes: institutional; in different time frames and with varying degrees of freedom in heterogeneous social communities. Ecological systems under high climatic risks including drought / flood prone regions are inhabited by some of the poorest communities. Without modelling their compulsions, preferences, and possible consequences of their choices on socio-ecological systems, sustainable outcomes cannot be achieved. Interactions among crops, weeds, pest, temperature, fluctuating rainfall, agro-biodiversity, at farmer's plots affected by different flooding levels in eastern India were studied at decadal intervals over thirty years. The findings of this study are drawn upon while suggesting modelling needs for knowledge rich-economically poor communities in tropical contexts, to enable future resilience.

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Working Papers | 2016

Small Retailer's Merchandise Decision Making: A Grounded Theory Approach

Piyush Kumar Sinha, Hari Govind Mishra, and Surabhi Koul

This study is focused on small retail stores of Jammu province of J&K and examines the relationship between retailer's perceptions of the trading area and their assortment policy decisions and their reported performance levels for a FMCG product category. The study focuses on the external environment as well as internal environment of the small stores which affect the decision making of the assortment. Retailers keep a small range of assortments as market uncertainty is high. Moreover, the study focuses on the impact of store attributes on the assortment policies. This study controls for both store space and the store location factors. The impact of customer profile and the local market environment faced by small retailers is also analyzed as an important factor towards the assortment policy decision. A grounded theory based analysis was carried out. The analysis brought out four criteria used by the retailers in selecting products for their store based on the evaluation of the external and internal environment.

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Working Papers | 2016

A Practical Note on Predictive Analytics Usage in Marketing Applications

Arindam Banerjee and Tanushri Banerjee

Most Predictive Analytics discussions focus on methods that can be used for better quality prediction in a particular context. Realizing that the possibility of perfect prediction is a near impossibility, practitioners looking to support their futuristic initiatives wonder, what is a suitable model for their use.
In other words, if all prediction models are imperfect (have leakage) how much of this imperfection can be tolerated and yet better decisions can be taken with model output. This paper is an attempt to provide a simplified approach to this practical problem of evaluating model performance taking account of the decision context.
Two scenarios are discussed; a) a classification problem often used for profiling customers into segments and, b) a volume forecasting problem. In both cases, the leakage is defined (misclassification or uncertainty band) and their impact (adverse) on the subsequent decision is identified. Contextual dimensions that have an impact on the quality of the decision and the scope to alleviate the problem are also discussed.

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Working Papers | 2016

Measuring the Perceived Impact of Internet on
Individuals in Rural India

Rekha Jain

Internet has greatly influenced the way individuals socialize, create and exploit economic opportunities and knowledge resources. However, previous studies on assessment of impact have largely been empirical and limited to examining the factors influencing adoption and usage of Internet only from a social and economic perspective. These have not considered the role of knowledge enhancement and exchange. In addition, few studies measure impact in an integrated manner and are based on theory. Consequently, the constituent dimensions of impact, their inter-relationships and their intensity have not been articulated.

To develop a construct for measuring impact of Internet use, we have used two theoretical and complementary domains: Social Capital and Social Cognitive Theory. Since Internet is considered a network for social exchanges, a study of Perceived Impact of Internet would need to take into account the aspect of social capital consequent to adoption and usage of Internet. On another dimension, usage of Internet could lead to increase in economic capital due to enhanced opportunities for business or profession. Internet is also a source of knowledge that could enhance economic or social benefits by creating opportunities for businesses or professional growth. Thus what constitutes impact is a complex construct broadly manifested along social, economic and knowledge dimensions. Further, most studies of Internet impact have not examined the role of outcome expectations and self-efficacy, two important constructs from theory of Social Cognition, in driving Internet use.

Our study is driven by the need to develop a theoretical model for measuring impact by identifying the underlying dimensions that constitute impact and creating a construct for measuring the same. Lack of studies of impact of Internet in developing countries, especially in rural areas was another driver.

We have used a survey based instrument administered to Internet users covering two of the poorer districts in Jharkhand, and Madhya Pradesh, India. Principal Component Analysis was used to identify the latent perceptual dimensions that constitute impact. Subsequently, we used linear regression to posit the strengths of each identified dimension in contributing to Perceived Impact.

The model highlights the importance of using Internet for overcoming vulnerabilities in a rural context, negative disconfirmation with respect to having Enhanced Scope of Work through Internet use and social context of knowledge creation and cognition. The negative disconfirmation could be attributed to possibly low self-efficacy or not completely fulfilled outcome expectations from available services. Lack of content in local language, poor presence of local websites, low presence of associates and partners on the Internet, and inadequate quality of Internet connectivity contribute to this.

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Working Papers | 2016

Factors Influencing Outcome Expectations and
Self-Efficacy in Driving Internet Use in Rural India

Rekha Jain

Past studies of individual Internet adoption and usage have been mostly empirical and in developed countries or in urban settings of developing countries. These have largely examined socio-economic factors such as age, earnings, education, in driving adoption and use. Several of the past studies were done at a time when the Internet was a novelty and was primarily considered as a source of information for enhancing knowledge. Over time, with developments in social media and ecommerce, Internet is considered an effective medium for social networking, enabling knowledge creation and exchange and enhancing economic benefits. Using theory of social capital and social cognition helps us to understand the drivers of Internet use from the perspective of outcome expectations and self-efficacy along the social, economic and knowledge dimensions. The primary research question is: What factors drive outcome expectations and self-efficacy in Internet use?

Our study is based on a survey in two rural areas (Ranchi, Jharkhand, India) and (Guna, Madhaya Pradesh, India). We used theory to develop a survey instrument on Internet users for understanding the drivers of Internet use based on outcome expectations and self-efficacy. We used data from the Principal Component Analysis (PCA) done previously, to identify the latent constructs as measures of outcome expectations and self-efficacy (Jain, 2016). Using ANOVA, the current study identified the differential across Age, Occupation, Digital Literacy, Earning, and Education on dimensions uncovered by PCA and related the findings to the rural context in a developing country.

The PCA revealed three dimensions that were labelled as 'Empowerment', 'Enhanced Scope of Work' and 'Transaction Efficacy'. There are statistically significant differences across those who are at different levels of Digital Literacy and Earnings and for 'Transactional Efficacy', in the two groups identified by type of Occupation as 'Business' and 'Others'. Along the other two dimensions of 'Empowerment' and 'Enhanced Scope of Work', there is no statistically significant difference across these two categories of Occupation. Further, there are no statistically significant differences across different categories of Age and Education.

Our results indicate that while a basic level of education may determine whether a user adopts Internet, once the user starts using the Internet with a goal orientation in terms of outcome expectations and self-efficacy, 'Education' level does not matter. A similar logic applies to 'Age'.

Since digitally literate users tend to have positive outcome expectations from Internet use, they may benefit far more than those who are not Digitally Literate. Therefore, public policy must not only focus on increasing Internet availability specifically in rural areas, there must be programs for increasing digital literacy as well. Without such support programs, Internet use outcomes would exclude those who are not as digitally literate. Since Internet is increasingly becoming the vehicle for economic growth, such exclusions could slow inclusive growth.

Those with higher incomes had possibly higher levels of negative disconfirmations with Internet use than those with lower incomes. A similar logic applies for the 'Transactional Efficacy' component in the 'Occupation' category. The study identifies the possible drivers for the disconfirmations.

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