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Journal Articles | 2018

The Aadhaar Debate: Where are the sociologists?

Reetika Khera

Contribution to Indian Sociology

The Aadhaar project which aims to provide all residents in India with a unique identity number requires much more attention from sociologists of India. There are several areas of research where sociologists can help: one, the implications of new technologies of surveillance for (a) privacy and (b) society; two, the repercussions of the desire for social ordering and control and technocratic solutionism for people in their interactions with the state demands fuller sociological study. This brief note attempts to outline some of the issues that call out for enquiry.

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Journal Articles | 2018

Informed trading around earnings announcements Spot, futures, or options?

Sobhesh Kumar Agarwalla, Jayanth R. Varma, and Ajay Pandey

Journal of Futures Markets

Recent literature reports higher single stock options (SSO) volume before earnings announcements (EA). There are no studies that explore single stock futures (SSF) in this context because of illiquid SSF markets in developed countries. Similar to SSO, SSF provide embedded leverage and facilitate short selling although at a lower cost, but do not provide downside-risk protection. India’s liquid SSO and SSF provide a unique setting to study the preference of informed traders. We observe an increase in both SSO and SSF volume before EA. Further, SSF dominate SSO possibly due to SSO becoming expensive before EA and higher information leakage in India.

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Journal Articles | 2018

Efficient mining of high utility itemsets with multiple minimum utility thresholds

Srikumar Krishnamoorthy

Engineering Applications of Artificial Intelligence

Mining high utility itemsets is considered to be one of the important and challenging problems in the data mining literature. The problem offers greater flexibility to a decision maker in using item utilities such as profits and margins to mine interesting and actionable patterns from databases. Most of the current works in the literature, however, apply a single minimum utility threshold value and fail to consider disparities in item characteristics. This paper proposes an efficient method (MHUI) to mine high utility itemsets with multiple minimum utility threshold values. The presented method generates high utility itemsets in a single phase without an expensive intermediate candidate generation process. It introduces the concept of suffix minimum utility and presents generalized pruning strategies for efficiently mining high utility itemsets. The performance of the algorithm is evaluated against the state-of-the-art methods (HUI-MMU-TE and HIMU-EUCP) on eight benchmark datasets. The experimental results show that the proposed method delivers two to three orders of magnitude execution time improvement over the HUI-MMU-TE method. In addition, MHUI delivers one to two orders of magnitude execution time improvement over the HIMU-EUCP method, especially on moderately long and dense benchmark datasets. The memory requirements of the proposed algorithm was also found to be significantly lower.

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Journal Articles | 2018

Efficiently mining high utility itemsets with negative unit profits

Srikumar Krishnamoorthy

Knowledge-Based Systems

A High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers utilities of items (such as profits and margins) to discover interesting patterns from transactional databases. Several data structures, pruning strategies and algorithms have been proposed in the literature to efficiently mine high utility itemsets. Most of these works, however, do not consider itemsets with negative unit profits that provide greater flexibility to a decision maker to determine profitable itemsets. This paper aims to advance the state-of-the-art and presents a generalized high utility mining (GHUM) method that considers both positive and negative unit profits. The proposed method uses a simplified utility-list data structure for storing itemset information during the mining process. The paper also introduces a novel utility based anti-monotonic property to improve the performance of HUI mining. Furthermore, GHUM adapts key pruning strategies from the basic HUI mining literature and presents new pruning strategies to significantly improve the performance of mining. The proposed method is evaluated on a set of benchmark sparse and dense datasets and compared against a state-of-the-art method. Rigorous experimental evaluation is performed and implications of the key findings are also presented. In general, GHUM was found to deliver more than an order of magnitude improvement at a fraction of the memory over the state-of-the-art FHN method.

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Journal Articles | 2018

Mining top-k high utility itemsets with effective threshold raising strategies

Srikumar Krishnamoorthy

Expert Systems With Applications

Top-K High Utility Itemset (HUI) mining problem offers greater flexibility to a decision maker in specifying her/his notion of item utility and the desired number of patterns. It obviates the need for a decision maker to determine an appropriate minimum utility threshold value using a trial-and-error process. The top-k HUI mining problem, however, is more challenging and requires use of effective threshold raising strategies. Several threshold raising strategies have been proposed in the literature to improve the overall efficiency of mining top-k HUIs. This paper advances the state-of-the-art and presents a new Top-K HUI method (THUI). A novel Leaf Itemset Utility (LIU) structure and a threshold raising strategy is proposed to significantly improve the efficiency of mining top-k HUIs. A new utility lower bound estimation method is also introduced to quickly raise the minimum utility threshold value. The proposed THUI method is experimentally evaluated on several benchmark datasets and compared against two state-of-the-art methods. Our experimental results reveal that the proposed THUI method offers one to three orders of magnitude runtime performance improvement over other related methods in the literature, especially on large, dense and long average transaction length datasets. In addition, the memory requirements of the proposed method are found to be lower.

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Journal Articles | 2018

Food value chain investments and the small farmer linkage: Indian experience, potential, and policy

Sukhpal Singh

World Food Policy

The agri-food value chains in the developing world are evolving fast due to many changes in policy and practice. In India, modern domestic food supermarkets have been present for more than 15 years now. Furthermore, in late 2012, foreign direct investment in multi-brand retail trade, including food, was permitted up to 51% of equity with other conditions of investment and operations. This paper tries to understand the role of investment (both domestic and foreign) in food/fibre value chains in improving the farmer/producer linkage. It uses empirical evidence from the experience of Indian domestic food retail supermarkets, and (mostly) foreign investment-based wholesale supermarkets in India, to examine the role such investments can play. It specifically examines the role and implications of investments in supermarkets for farmer income improvement, from a value chain perspective. It also explores various mechanisms which could be used to leverage the presence of such investments in food supermarkets and analyses the role of policy and regulation to promote/protect the small producer interests in food markets.

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Journal Articles | 2018

Land and livelihoods in rural India: Does farm size matter?

Sukhpal Singh

Indian Journal of Agricultural Marketing

This paper examines the question of role of land in rural livelihoods and that of small farms in the Indian smallholder and large landlessness context by focusing on the issue of size of the farm. It reviews evidence on the changing profile of farms globally and in India from the perspective of small and landless farmers. The paper argues that the size of the farm is not an issue for modern and sustainable agriculture and makes inferences about managing land in a sustainable way, including institutional approaches like group approaches and contract farming, from a smallholder and farm worker perspective.

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Journal Articles | 2018

Promoting and managing FPOs in India for efficiency, effectiveness and sustainability: Challenges, policies and best practices

Sukhpal Singh

Cooperative Perspective, Spl Issue(September)

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Journal Articles | 2018

Nocebo effects from negative product information: when information hurts, paying money could heal

Sukhpal Singh and Arvind Sahay

Journal of Consumer marketing

Purpose

This research aimed to find whether information about a product can give rise to negative perceptions even in inert situations (nocebo effects), and to understand how price levels impact such judgments.

Design/methodology/approach

In all experiments, participants were exposed to negative product information in the form of potential side-effects. In an initial study, a higher non-discounted versus a discounted price frame was presented for a health drink after customers were exposed to negative aspects. Then, in experiment 1, price (high vs low) and exposure to information (no information vs negative information) was manipulated for skin creams where participants physically evaluated the cream. In experiment 2, price was manipulated at three levels (low, high, discounted) orthogonally with product information (no negative information vs with negative information) to get a more nuanced understanding.

Findings

In the initial study, after exposure to negative information, the non-discounted group had more positive ratings for the drink. Study 1 showed that reading about negative information resulted in a nocebo effect on perception of dryness (side-effect). Moreover, when no information was presented, perception of dryness by low and high price groups were similar but in the face of negative information, perception of dryness by low-price group was more pronounced compared to a high-price group. Study 2 conceptually replicated the effect and also confirmed that not only discounts (commonly linked with product quality), but absolute price levels also show a similar effect.

Practical implications

Nocebo effects have been rarely documented in consumer research. This research showed how simply reading generically about potential side effects gives rise to nocebo effects. In addition, even though marketers might find it tempting to lower prices when there is negative information about certain product categories, such an action could backfire.

Originality/value

To the best of our knowledge, the link between observable nocebo effects and its link with pricing actions is a novel research thread. We were able to show a nocebo effect on product perception after reading about negative information and also find that a higher price can mitigate the nocebo effect to some extent.

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Journal Articles | 2018

Digital social media: Enabling performance quality of Indian Railways

Sundaravalli Narayanaswami

Journal of Public Affairs

Indian Railways (IR) is the single largest organization that manages and operates a mammoth of transportation services in the World's largest democracy. IR services are operated through 7,137 stations, a route length of 66,030 km, and a total track of 117,996 km. The number of passengers carried every day is 23 million with passenger earnings of INR 42190 crores. Scale of operations translates to humungous everyday challenges. Quite understandably, customer dissatisfaction is prevalent, in spite of subsidized travel fares and multiple initiatives. In recent times, IR has become very active in the digital social media space to provide real-time and dynamic service improvements. In this talk, we will be discussing the beginning of technology intervention in IR, managerial challenges in exploiting technology advancements, and the current status in managing a large-scale public transport operations. We will also discuss about the insights, deployability in comparative segments, and the way forward.

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IIMA