Authors: Aggarwal, Veena | Krithika, P R | Garg, Deepika
Article Type: Research Article
Abstract: Increasingly, urban local bodies (ULBs) in India are facing challenges in attending to the day-to-day needs of the citizens due to systemic inefficiencies in service provision. ULBs provide basic amenities to citizens and constitute the third tier of governance systems. Hence, it is of utmost importance that they align their services to effectively cater to citizens' needs. Recognizing the requirement to strengthen the ULBs and usher in reforms geared towards efficient service delivery mechanisms, the Government of India (GoI) launched the Jawaharlal Nehru National Urban Renewal Mission (JNNURM) in 2005. The mission is a centrally sponsored scheme, providing financial assistance …to ULBs based on their performance related to specific governance-related reforms. This paper deals with one such mandatory governance reform, namely, introduction of e-governance by ULBs in their key services and functions. The paper specifically discusses the effectiveness of e-governance reforms for consumer grievance redressal (CGR). Through a detailed study of the functioning of Information Technology (IT) enabled redressal systems in a few cites of India, this article argues that these IT-enabled redressal systems will remain ineffective in providing resolution of complaints until they are backed by effective municipal governance. Effective governance, in this context, would include accountability of municipal staff, community involvement, transparency, and capacity. The paper offers specific governance-related recommendations that need to be in place to make the IT-enabled systems effective. The paper is organized into four sections. Section 1 provides an overview of the GoI initiatives towards strengthening grievance redressal systems in ULBs, particularly the introduction of IT-enabled CGR system. Section 2 discusses the functioning of CGR systems in cities, while highlighting the gaps that exist. Section 3 contains some of the key features of the redressal system in the electricity sector. Section 4 makes recommendations for an effective IT-enabled CGR system, while drawing from the experience of cities that have already implemented similar systems. Show more
DOI: 10.3233/IJR-120095
Citation: International Journal of Regulation and Governance, vol. 10, no. 2, pp. 63-75, 2010
Authors: Garg, Deepika | Roy, Nihar Ranjan | Khanna, Ashish
Article Type: Research Article
Abstract: During the 2 nd phase of COVID-19 pandemic, pharmaceutical plant industry is facing lot of production pressure and machine availability plays vital role in maximizing the manufacturing pharmacy product output. In this paper, Artificial Neural Networks (ANNs) based information processing algorithm has been used to provide a solution to this problem and it has been found suitable to predict machines availability as a prediction function. The considered pharmaceutical plants are dealing with production of medicines related common symptoms in case of COVID-19 (fever, coughing, and breathing problems). The pharmaceutical plant data corresponding to different values of repair and failure rates …of different subsystems is collected from plant and analyzed with the help of validated neural network value of availability. This configuration of ANNs approach developed in this research allowed simplifying computational complexities of conventional approaches to solve a large plant machines availability problem. The ANNs methodology in the paper permitted making no assumption, no explicit coding of the problem, no complete knowledge of system configuration, only raw input and clean data found to be sufficient to determine the value of machine availability function for different value of failure and repair rates considered in the paper. The results obtained in the paper are useful for the plant leadership, as the value of failure and repair rates of various subsystems can be fine-tuned at a require clear-cut level to achieve higher availability, and avoid considerably loss of production, loss of man power, and by-pass complete breakdown of concerned system. Show more
Keywords: Availability prediction, Artificial Neural Networks, back propagation algorithm, failure rate, repair rate, pandemic
DOI: 10.3233/IDT-210075
Citation: Intelligent Decision Technologies, vol. 16, no. 2, pp. 325-335, 2022
