Assessing the primary schools—A multi-dimensional approach: A school level analysis based on Indian data

Sengupta, Atanu; Pal, N.

doi:10.1016/j.ijedudev.2011.04.006

Cited by 13 publications

(5 citation statements)

References 5 publications

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“…The urban poor has, most of the time, experienced uncertainty of livelihood with scarcity of very basic needs such as safe water, food, sanitation and shelter (Han and Han, 2020; Moser, 1998; Sanderson, 2000). There might be several reasons behind the vulnerability of urban poor households all over the world, but also, it is widely accepted that the idea of shortage suffered by the urban poor in developing countries is multidimensional (Radhakrishna et al, 2010; Saleem et al, 2019; Sengupta & Pal, 2012; Tang, 2019). Infrequently, these urban poor are also deprived of admittance to other basic privileges such as quality education, healthcare and fiscal services (Datta, 2010; Klasen, 1997; Wilson et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Does Credit Utilization Pattern Promote Poverty Alleviation? An Evidence from India

Singh

Sharma

Batra

2020

Global Business Review

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Government of India has introduced various schemes for the uplift of the deprived section of the urban poor. As a result, the proportion of India’s poor with respect to total population has dropped in both urban and rural areas, but then again, the absolute number of the urban poor is growing. Therefore, this article tries to analyse the utilization pattern of credit availed through various credit expansion avenues by the urban poor households, thereafter examining its impact on poverty alleviation at different levels. Snowball sampling method was used to collect data from 598 respondents living in the most populous cities of Punjab and the union territory (UT) of Chandigarh using the references of registered deprived urban poor, who are continuously being recorded and monitored by top non-governmental organizations (NGOs) and banks. Apart from descriptive statistics, exploratory factor analysis was used to categorize the utilization pattern and poverty alleviation dimensions into the valid factors. Finally, structural equation modelling (SEM) was employed to test the proposed hypothesis. The study found that the productive utilization of credit availed by the Economic Weaker Section (EWS) of the urban poor through various government credit schemes is highly associated with poverty alleviation at individual level (β = 0.55 and p = 0.000) followed by that at regional (β = 0.29 and p = 0.009) and community levels (β = 0.18, and p = 0.001). Social structure of the families is found to be an important deciding factor in how productively a household channelizes its loan amount or grants to move out of poverty and to become self-reliant. The article is limited to only government-backed credit expansion schemes for the EWS of the urban poor residing in the most populous areas of Punjab and Chandigarh. The development of the evaluation model is expected to lead towards better implementation of government credit schemes for the EWS of the urban poor, which would be practically helpful in policymaking. Also, the development of suggestive measures is expected to complement effective, efficient and more cohesive implementation of government schemes for the urban poor, which would be socially more sustainable. With policy emphasis in recent times for the urban poor, the topic is of utmost importance for research.

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Section: Introductionmentioning

confidence: 99%

Does Credit Utilization Pattern Promote Poverty Alleviation? An Evidence from India

Singh

Sharma

Batra

2020

Global Business Review

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“…Sengupta and Pal (2012) argued that apart from better infrastructural facilities and efficient staffs, a production process of school should incorporate the environmental factors. They applied regression analysis to measure the impact of various environmental impacts (like various types of poverty levels) on the corresponding Charnes, Cooper and Rhodes (CCR) DEA-based efficiency scores of various zones of the Burdwan district in West Bengal, while considering four inputs and two outputs.…”

Section: Introductionmentioning

confidence: 99%

Detection of cost leaders in case of private primary school services

Sarkar

2017

BIJ

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Purpose The purpose of this paper is to provide an insight into distinguish cost leaders from the architects of diversification (Porter, 1985) using a non-central principal component analysis (PCA)-based approach. The central theme of this paper is based on the assumption that the operational strategy of a competing firm can be understood by observing its resource consumption and technological practice vis-à-vis its rivals present in the market. Design/methodology/approach Depending on the previous surveys, two inputs (spending per student and percentage of non-poor income group) and two outputs (average scores attained by students in science group and in language group six private schools, located within the outskirt of Durgapur) were analyzed. Findings Out of six schools (A, B, C, D, E and F), A, E and F were found efficient; however, the proposed model identifies that out of them, only E and F remain cost efficient. The efficiency scores, due to cost, are very close to the outputs of other three accepted papers. Research limitations/implications The input and output vectors have to be non-negative. In case of a negative input (output) set, separate treatment must be applied on them before the application of non-central PCA. Any decision-making unit (DMU) producing an output of 0 will prohibit the use of the non-central PCA. Practical implications It can be applied to problems which may or may not be having the information regarding input price for detecting cost-efficient DMUs as in the case of the Banker’s model. Banker’s model remains inconclusive about the fact, whether a DMU is a mere cost leader or it is reigning in both fields. Present model does not have such limitations. Targets to remain cost efficient can be obtained for any competing DMU. Unlike the Banker’s model, the proposed one ascribes unequal weight to the cost of consumption to each resource. This weight vector is determined from the industrial practice. It remains unique in the sense that it relies on few intermediate input variables to measure the performance of a DMU. These variables are dependent on large number of other independent variables, which reflect the extent of its control on the resources to signify the strategic position of it. Moreover, the proposed model offers an ideal frontier of ultimate performers, which provides a very stringent benchmark based on constant return to scale for incorporating those renowned organizations, which operate in various places in West Bengal. However, it also offers lower limits of performance to the strongly efficient performers by using the goal-oriented data envelopment analysis for analyzing the problem on a local basis. The extended model, in addition, is worthy of carrying out SDEA operations. Social implications Under the present scenario, a new model is proposed here to concentrate on the variation present in the market due to specific consumption of resources. All inputs are assumed scarce and desirable for the production of each output (Liu et al., 2010). Thus, a good cost-cutting performance occurs because of an economic use of resources while fulfilling the standards. Unlike Taguchi et al. (1989) and Taguchi (1991), a linear societal loss function, which is solely adhered to the resource consumption, is added here instead of a formal cost function. Originality/value The central theme of this paper is as follows: determination of technical efficiency scores for the schools; determination of economic efficiency (with partial information about price); identification of cost leaders and differentiation architects; to prescribe the model of a cost leader so that education can be imparted to a full potential; and to prescribe a non-central PCA and a slack-based optimization model. Superiority in the domain of cost leadership is decided based on the closeness of any DMU from this frontier.

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“…An effort has been made by the National University of Educational Planning and Administration (NUEPA) and the Government of India (MHRD, Department of School Education and Literacy, 2004) to compute an Educational Development Index (EDI) ( Table 1), separately for Upper primary and Upper primary levels of education and also a composite index for the entire Elementary education which is exclusively based on the DISE data (DISE Flash Statistics, 2005-2006, 2006-2007, 2007-2008, 2008-2009, 2009-2010, 2010-2011, 2011-2012, 2012-2013, 2013-2014 for the nine consecutive academic sessions periods from 2005-06 to 2013-14. The first such attempt was made in 2005-06.…”

Section: Methodsmentioning

confidence: 99%

“…The effort at present needs to be to improve the inter stage transition ratios from primary to upper primary levels of education. DISE data set to generate a host of indicators directly related with educational performance Again (Sengupta and Pal 2012).…”

Section: Introductionmentioning

confidence: 99%

Modeling of hotspot detection using cluster outlier analysis and Getis-Ord Gi* statistic of educational development in upper-primary level, India

Jana

Sar

2016

Model. Earth Syst. Environ.

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In recent years educational variability has threatened the sustainability of elementary level in Indian educational system. Systematic methodology to assess the educational development of the elementary sector to educational variability is currently not available. Towards this end, the present paper pays attention with the assessment of spatial structure of Indian educational development to elementary levels in 35 states including union territories (UTs) of all over country. For this purpose, a set of indicators was selected for each of the four components of educational development index (EDI). The data were arranged in the form of diagonal matrix and normalized them using functional relationship. Upon receiving normalized values, here researchers consider a method of unequal weights followed. The choice of the weights in this manner would ensure that large variation in any one of the indicators would not unduly dominate the contribution of the rest of the indicators and distort inter states as well as union territories (UTs) comparisons. It is well known that, in statistical comparisons, it is more efficient to compare two or more means after equalizing their variances. The principal objectives of this article to identification of Hotspot and cold-spot and delineate the spatial cluster of upper primary education level in India based on Getis-Ord Gi* statistic using fixed distance band in ArcGIS software.

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Assessing the primary schools—A multi-dimensional approach: A school level analysis based on Indian data

Cited by 13 publications

References 5 publications

Does Credit Utilization Pattern Promote Poverty Alleviation? An Evidence from India

Does Credit Utilization Pattern Promote Poverty Alleviation? An Evidence from India

Detection of cost leaders in case of private primary school services

Modeling of hotspot detection using cluster outlier analysis and Getis-Ord Gi* statistic of educational development in upper-primary level, India

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