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3548 items in total found

Journal Articles | 2018

Disparity in the wages of agricultural labourers in India: An interval-valued data analysis

B.S.Yashavanth and Arnab Kumar Laha

Indian Journal of Agricultural Sciences

This study explores the interval-valued data analysis techniques to witness the spatial disparity in the wage rates of farm labourers in India. Farm labourers constitute more than half of the total workforce engaged in Indian agriculture. Also, farmers' expenses towards labour charges account for more than 50 per cent of the total variable cost of production for most crops.Using the time series data on the nominal farm wage rates paid at different agriculturally important states, the interval-valued series are built. The inflation-adjusted real wage rates are found and both nominal and real wage rate data are used to find the average range of the farm wage rates over the agricultural years for a decade. Using the time series analysis techniques, viz. autoregressive integrated moving average-artificial neural network (ARIMA-ANN) hybrid model and vector autoregressive moving average (VARMA) model, the interval-valued data on nominal wage rates are modelled and the best model for forecasting is identified using forecast evaluation methods. The results established the presence of spatial disparity and the forecasts indicated that this disparity is not going to narrow down in future unless some policy intervention takes place. © 2018 Indian Council of Agricultural Research. All rights reserved.

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Journal Articles | 2018

Turning over a golden leaf? Global liquidity and emerging market central bank's demand for gold after the financial crisis

Balagopal Gopalakrishnan and Sanket Mohapatra

Journal of International Financial Markets, Institutions and Money

The quantity of gold reserves held by central banks in emerging markets and developing economies (EMDEs) has risen sharply in the years following the global financial crisis of 2008. EMDE central banks’ gold holdings rose in both absolute terms and as a share of GDP across the developing regions and in most of the EMDE countries, suggesting a pervasive phenomenon. Using a dynamic panel data model, we find that expansion of central bank balance sheets in the advanced economies and increase in global liquidity are robustly related to the post-crisis increase in EMDE gold reserves, after controlling for domestic factors and changes in the global risk environment. This finding is robust to different model specifications, inclusion of additional covariates, and alternative estimation methods. We argue that quantitative easing undertaken by central banks in the advanced economies resulted in a search for alternative safe assets such as gold, which may explain the continued accumulation of EMDE gold reserves even after the peak of the financial crisis.

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Journal Articles | 2018

Underlying determinants of health provider Ccoice in urban slums: Results from a discrete choice experiment in Ahmedabad, India

Vilius Cernauskas, Federica Angeli, Anand Kumar Jaiswal, and Milena Pavlova

BMC Health Services Research

Background:

Severe underutilization of healthcare facilities and lack of timely, affordable and effective access to healthcare services in resource-constrained, bottom of pyramid (BoP) settings are well-known issues, which foster a negative cycle of poor health outcomes, catastrophic health expenditures and poverty. Understanding BoP patients’ healthcare choices is vital to inform policymakers’ effective resource allocation and improve population health and livelihood in these areas. This paper examines the factors affecting the choice of health care provider in low-income settings, specifically the urban slums in India.

Method:

A discrete choice experiment was carried out to elicit stated preferences of BoP populations. A total of 100 respondents were sampled using a multi-stage systemic random sampling of urban slums. Attributes were selected based on previous studies in developing countries, findings of a previous exploratory study in the study setting and qualitative interviews. Provider type and cost, distance to the facility, attitude of doctor and staff, appropriateness of care and familiarity with doctor were the attributes included in the study. A random effects logit regression was used to perform the analysis. Interaction effects were included to control for individual characteristics.

Results:

The relatively most valued attribute is appropriateness of care (β=3.4213, p = 0.00), followed by familiarity with the doctor (β=2.8497, p = 0.00) and attitude of the doctor and staff towards the patient (β=1.8132, p = 0.00). As expected, respondents prefer shorter distance (β= − 0.0722, p = 0.00) but the relatively low importance of the attribute distance to the facility indicate that respondents are willing to travel longer if any of the other statistically significant attributes are present. Also, significant socioeconomic differences in preferences were observed, especially with regard to the type of provider.

Conclusion:

The analyses did not reveal universal preferences for a provider type, but overall the traditional provider type is not well accepted. It also became evident that respondents valued appropriateness of care above other attributes. Despite the study limitations, the results have broader policy implications in the context of Indian government’s attempts to reduce high healthcare out-of-pocket expenditures and provide universal health coverage for its population. The government’s attempt to emphasize the focus on traditional providers should be carefully reconsidered.

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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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