The apex planning body of India, NITI Aayog launched an Aspirational District Programme (ADP) in January 2018. The programme aimed to the quick and effective transformation of 112…
Abstract
The apex planning body of India, NITI Aayog launched an Aspirational District Programme (ADP) in January 2018. The programme aimed to the quick and effective transformation of 112 (14%) districts of the country. This programme is considered as world's biggest result-based governance initiative having reached up to 250 million people. It is based on a ranking that is done on monthly basis. This ranking is based on 49 KPIs across six broad socio-economic themes.
The study attempts to inquire and assess the progress made by 112 Aspirational Districts under Financial Inclusion, Skill Development and Basic Infrastructure theme from the inception of the programme to June 2022 (i.e. 54 months). Instead of ranking districts with delta rank or composite scores, the study divorce from NITI Aayog's methodology of monthly delta ranking. The study explores 8 indicators under the basic infrastructure theme and 16 indicators under the financial inclusion and skill development themes. For this purpose, the study explores the availability of individual household latrines, drinking water, electricity and road connectivity. Districts are also tracked for the number of Internet-connected Gram Panchayats, and panchayats with Common Services. Every district is provided with the target as per national development priority, the study makes an effort to grasp the distance of each district from the national target. This allows researchers to develop a scale Very Far, Far, Near, Very Near, Achieved with descriptive statistics techniques. Juxtaposing the scale with timelines results in a pattern of progress made by these 112 districts.
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Somnath Chattopadhyay and Suchismita Bose
The financial system of an economy, especially banking, facilitates efficient allocation of resources from savers to borrowers for productive investments, and thus promotes…
Abstract
The financial system of an economy, especially banking, facilitates efficient allocation of resources from savers to borrowers for productive investments, and thus promotes economic growth. State-wise bank credit in India shows a growing divergence, despite the aim of central planning to reach a degree of convergence in macroeconomic performance over time. This chapter analyzes how diverging bank credit affects macroeconomic performances of the Indian states, through an alternative approach of composite indicators-based rankings of states adopting the methodology of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) that is used in operations research or more specifically MCDM (multiple criteria decision-making). A composite indicator of the states’ annual macroeconomic performances has been constructed taking indicators of output growth, per capita state domestic product, inflation, and fiscal indicators for years 2006–2018. States are ranked by both macroeconomic performance and bank credit to states, and the correlation between the two indicators, known in the literature to be interlinked,is studied here to understand how the availability of credit or lack of it has influenced State level macroeconomic development in India. The results thus show that wealthier and better performing states continue to attract the larger chunk of bank credit, while weaker states have not been able to catch up. An important policy implication would be to place even more emphasis on higher levels of credit growth for weaker states, particularly infrastructure credit, to achieve a degree of income convergence throughout the Indian economy.
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Manzoor Hussain, Syed Uzma Kubravi and Fayaz Ahmad Loan
Social networking sites (SNS) have become popular destinations for college students all over the world. The minds of the college students have been steadily taking over by the…
Abstract
Purpose
Social networking sites (SNS) have become popular destinations for college students all over the world. The minds of the college students have been steadily taking over by the influence of social networking, and this can impact their ability for doing research. Against this backdrop, this paper aims to investigate the role of SNS in enhancing the research activities of the degree college students in the Srinagar district of Kashmir, J&K, India.
Design/methodology/approach
A survey method was used to conduct the study, and Cochran’s sampling formula was applied to select the sampling size. Data were collected with the aid of a well-designed and structured questionnaire using Google forms. Besides, the focus group discussions were conducted to get varied opinions.
Findings
The findings revealed that the majority of the students agree or strongly agree that SNS help them in interacting with researchers, reading research content, keeping them abreast of research articles, knowing research trends, developing research aptitude and facilitating logical thinking and reasoning. The study confirmed that SNS help in enhancing the research traits of college students. However, students have been cautioned to make proper and judicious use of SNS.
Research limitations/implications
The study is limited to the college students of Srinagar, Jammu and Kashmir (India), and the results cannot be generalised across regions and countries.
Originality/value
To the best of the authors’ knowledge, the study, being a part of PhD programme, is the original work of great value. It investigates the role of SNS in enhancing the research traits of college students and brings into light various hidden facts.
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Zulkefly Abdul Karim, Danie Eirieswanty Kamal Basa and Bakri Abdul Karim
This paper aims to investigate the relationship between financial development (FD) and monetary policy effectiveness (MPE) on output and inflation in ASEAN-3 countries (Singapore…
Abstract
Purpose
This paper aims to investigate the relationship between financial development (FD) and monetary policy effectiveness (MPE) on output and inflation in ASEAN-3 countries (Singapore, Malaysia and the Philippines).
Design/methodology/approach
This study uses an open economy structural vector autoregressive model to generate MPE. Then, an autoregressive distributed lagged (ARDL) model is used to analyze the effect of FD on MPE across countries.
Findings
The findings revealed that FD plays a different role in MPE across countries. In Malaysia, a more developed financial system tends to reduce the MPE on output, whereas in Singapore, results show that the more developed financial system (stock market capitalization) tends to increase MPE on output. However, in the Philippines, the main results show that the effect of FD (liquid liabilities) upon MPE on output is depending on the policy variable (interest rates or money supply).
Originality/value
This paper fills this gap by providing the first study of ASEAN-3 countries in examining how effective is a monetary policy in response to the development of the financial market across the country. Second, this paper considers two FD indicators, namely, the banking sector and capital market development in investigating its effect on MPE on output and inflation. Third, the authors construct the MPE in each country using a structural (identified) VAR model by aggregating the response of output growth and inflation rate on monetary policy changes (interest rate and money supply) using impulse–response function. Regarding this, the results of this study provide new empirical evidence and insight into the long debate on the relationship between FD and the MPE.
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Rudra Pradhan, Mak B. Arvin, Sahar Bahmani and John H. Hall
The purpose of this paper is to consider the heterogeneous relationship among financial development, foreign direct investment (FDI) and economic growth, examining the possible…
Abstract
Purpose
The purpose of this paper is to consider the heterogeneous relationship among financial development, foreign direct investment (FDI) and economic growth, examining the possible directions of causality among them in both the short and long runs.
Design/methodology/approach
A sample of the G-20 countries over the period 1970–2016 is utilized. A vector error-correction model is used to consider the possible directions of causality among financial development, FDI and economic growth.
Findings
Results suggest a cointegrating relationship among the three series. Although short-run links among the variables are mostly non-uniform, both financial development and FDI matter in the determination of long-run economic growth.
Practical implications
Attention must be paid to policies that promote financial development. This, in turn, calls for fostering incentives to guarantee continued support to liberalize the economy and promoting capital openness. Additionally, financial infrastructure should be improved to improve financial innovation. The establishment of a well-developed financial market, including well-functioning banks and other financial institutions, can facilitate further investment and an easier means of raising capital to support the activities of FDI. Economic growth can ultimately be elevated through both financial development and FDI.
Originality/value
The study considers a sample of the G-20 countries, which have received relatively little attention in the existing literature. In addition, the study concurrently analyses the trivariate causal relationship among financial development, FDI and economic growth, a topic on which there has been a dearth of research.
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Showmitra Kumar Sarkar, Swapan Talukdar, Atiqur Rahman, Shahfahad and Sujit Kumar Roy
The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random…
Abstract
Purpose
The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).
Design/methodology/approach
The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.
Findings
The very high (831–1200 km2) and high groundwater potential areas (521–680 km2) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).
Originality/value
Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.
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Swati Sucharita Pradhan, Raseswari Pradhan and Bidyadhar Subudhi
The dynamics of the PV microgrid (PVMG) system are highly nonlinear and uncertain in nature. It is encountered with parametric uncertainties and disturbances. This system cannot…
Abstract
Purpose
The dynamics of the PV microgrid (PVMG) system are highly nonlinear and uncertain in nature. It is encountered with parametric uncertainties and disturbances. This system cannot be controlled properly by conventional linear controllers. H− controller and sliding mode controller (SMC) may capable of controlling it with ease. Due to its inherent dynamics, SMC introduces unwanted chattering into the system output waveforms. This paper aims to propose a controller to reduce this chattering.
Design/methodology/approach
This paper presents redesign of the SMC by modifying its sliding surface and tuning its parameters by employing water-evaporation-optimization (WEO) based metaheuristic algorithm.
Findings
By using this proposed water-evaporation-optimization algorithm-double integral sliding mode controller (WEOA-DISMC), the chattering magnitude is diminished greatly. Further, to examine which controller between H8 controller and proposed WEOA-DISMC performs better in both normal and uncertain situations, a comparative analysis has been made in this paper. The considered comparison parameters are reference tracking, disturbance rejection and robust stability.
Originality/value
WEO tuned DISMC for PVMG system is the contribution.
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Lyndel Judith Bates, Ashleigh Filtness and Barry Watson
Purpose – Driver education and licensing are two mechanisms used to reduce crash rates. The purpose of this chapter is to provide an overview of these countermeasures and consider…
Abstract
Purpose – Driver education and licensing are two mechanisms used to reduce crash rates. The purpose of this chapter is to provide an overview of these countermeasures and consider how simulators can be used to augment more traditional approaches.
Approach – A literature review was undertaken evaluating key concepts in driver licensing including graduated driver licensing (GDL), the role of parents in licensing, compliance and enforcement, driver testing and how the driver licensing system impacts on levels of unlicensed driving. Literature regarding driver education for individuals who have and not yet obtained a licence was also reviewed.
Findings – GDL is a successful countermeasure for reducing the crash rates of young novice drivers as it limits their exposure to higher risk situations. The support for driver education initiatives is mixed. As there are big differences between education programs, there is a need to consider each program on its own merits. Driving simulators provide a safe environment for novices to gain experience. In particular, they may be bifacial for development of hazard perception and visual scanning skills.
Practical Implications – GDL systems should be introduced where appropriate. Existing systems should be strengthened where possible by including additional, best-practice and restrictions. When considering driver education as a countermeasure, the type of program is very important. Education programs that have been shown to increase crashes should not be introduced. Further research and development are necessary to ensure that driver education and licensing adequately equip novice drivers with the skills necessary to drive in the 21st century.
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Tariqur Rahman Bhuiyan, Mohammad Imam Hasan Reza, Er Ah Choy and Joy Jacqueline Pereira
Kuala Lumpur, the capital of Malaysia, is exposed to several natural hazards, among which flash floods are most common and frequent. Expanding development and higher intensity of…
Abstract
Kuala Lumpur, the capital of Malaysia, is exposed to several natural hazards, among which flash floods are most common and frequent. Expanding development and higher intensity of rainfall are the primary causes of flash floods. As the urbanisation is growing, the number of exposed properties, people and business premises are also increasing. This may have a detrimental impact on the socio-economic state of the city. Therefore, the purpose of this chapter is to investigate the frequency and intensity of flash flood occurrences between 2011 and 2016 and to delineate how it is impacting the urban livelihood. For this study, several news reports of flash flood events, previously published and reports were reviewed to elicit information so that the frequency and intensity of flash floods can be analysed for identifying flash flood risk areas. Along with the information from newspapers, Google map was used to identify the spatial locations of flash flood events, thus identifying the risk zones. This study found the City Centre as the most risk prone to flash floods. It was noted that 39% of flash floods occurred in this place. The Damansara-Penchala area comes in the second position with 20% of flash floods occurring in this place. Most of the people of these zones are exposed to flash flood and the affected people suffer from road blocking and heavy traffic jam. This study will help researchers and policymakers to understand the impact of flash floods in the city. This will also help to identify the most flood-prone areas of the city.
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Jitender Kumar, T.B. Kavya, Amit Bagga, S. Uma, M. Saiteja, Kashish Gupta, J.S. Harish Ganapathi and Ronit Roy
The purpose of this article is to revisit the mean reversion in profitability and earnings among Indian-listed firms, based on the idea that changes in profitability and earnings…
Abstract
Purpose
The purpose of this article is to revisit the mean reversion in profitability and earnings among Indian-listed firms, based on the idea that changes in profitability and earnings are somewhat predictable.
Design/methodology/approach
The study used a sample of 445 Bombay Stock Exchange (BSE)-listed companies and 309 companies from the manufacturing sector in India for the period from 2007 to 2020. The study employed cross-sectional regressions. Both linear and non-linear Partial Adjustment Models (PAM) were used to forecast profitability and earnings.
Findings
The study revealed that profitability and earnings mean revert for both the BSE-listed companies and the manufacturing sector companies from 2007 to 2012. However, for the years from 2013 to 2020, it was found that there is no significant evidence of mean reversion in both the BSE-listed companies or the manufacturing sector companies.
Practical implications
The findings have larger implications for security analysts who forecast future stabilisation or recovery of historically high or low growth rates. Investors and analysts would benefit from having a better understanding of how competitive attacks affect profitability as well as how the overall economic growth of a country affects earnings and valuations.
Originality/value
Most of the empirical research in India has focused on mean reversion in stock prices or stock returns. The present study looked at the mean reversion of profitability and earnings in Indian firms.