Academic literature on the topic 'Police performance-India-Odisha'

In March 2018, Rajan joined Wondersmoke India Ltd (WIL) as a sales executive for their cigarette business in Odisha, India. Although there was good demand for Wondersmoke as per the internal customer survey report of WIL on Kendrapara district of Odisha, a lot of the time, the demand was not fulfilled as the retailers did not have sufficient stock owing to inadequate working capital. Rajan needed to increase the cigarette sales from retail outlets in Kendrapara by ensuring that there was no loss of sales due to the lack of working capital of the retailers. Further, he needed to achieve the desired sales performance without making any exception to the company policy of no credit.

Background: Primary health care quality remains poor in many countries, despite its importance for universal health coverage. Evidence shows that better management of primary health care facilities improves service quality, and that facility managers’ autonomy and training levels can augment their management performance. In India, there is scant research in this area. Research questions include: 1) What is the effect of facility-level autonomy on management performance and is the effect modified by management training? 2) Which aspects of facility management are most sensitive to facility-level autonomy and is the effect augmented by management training? Methods: Using a multi-stage, regionally representative survey of health facilities in Odisha (n=396), a validated tool was used to measure management performance. An “autonomy score” was created to understand which facility management decisions are within a manager’s capacity. Multivariable linear regressions were used to assess the association of decision-making autonomy and management training with performance scores. Results: The mean performance score across all facilities was 0.657 (SD = 0.148) on a 0-1 scale; the mean autonomy score was 0.619 (SD = 0.305). Autonomy scores were not associated with a significant difference in performance scores; however, management training had an independent positive association with the human resources and monitoring domains of facility management. Conclusion: In Odisha, India management training may improve management performance, and targeted training initiatives may strengthen a primary care facility’s ability to retain staff and monitor performance. Our data did not demonstrate a significant association between decision-making autonomy and management performance, highlighting a need for further study on how decision-making autonomy may augment a manager’s ability to leverage their skills to improve facility outcomes. In summary, neither management training nor decision-making autonomy alone will sufficiently improve primary care management but targeting the improvement of management training may improve a subset of performance outcomes.

The success of any organization is measured in its ability to quickly respond to market changes with more efficient satisfaction and customer retention. The subject “quality” is nowadays, in a globalized world, one of the key concerns of businessmen to face the competition on industries and service areas. Financial groups are measuring no efforts to achieve quality excellence, starting by customer services and relationship. When the expression “Quality” is used, we usually think in terms of an excellent product or service that fulfills or exceeds our expectations. These expectations are based on the intended use and the selling price. Products are determined by its quality. Hence based on observation it is considered elusive. Quality can be quantified as Q = P/E. Where Q = Quality, P = Performance and E = Expectations. Quality is a complex phenomenon based on perceptions by individuals with different perspectives on products and services. These perceptions have been built up through the past experience of individuals and consumption in various contexts. Indian banking sector opened its doors to private and international players after the economic liberalization in 1991. It has been almost 2 decades of operation of the private banks in India. Much has evolved in the overall structure of banking during this time but have the private banks delivered the type of quality that the customers expect them to. This research is an effort to evaluate the service quality of the private banks in Southern parts of Odisha of the country India. The study is based on primary data collected in the cities of South Odisha through a structured questionnaire designed on the basis of SERVQUAL Model. The banks under study are the five top private banks from South Odisha region. The study has found that none of the banks have been able to meet the customer expectations and are still dwelling on the ‘zone of pain’. The research is very useful for managers, policymakers, implementers as well as academicians. The research provides implications for managers as well as policy makers to understand the customer expectations in India. It can be a guideline for a bigger role for the BCSBI (Banking Codes and Standard Board of India). Implications for future research are also discussed. The novelty of the research lies in the context that no effort has been made so far to effect research on sector specific contribution of banks. There is also very little literature available to identify the need-service gap in this area. The study adds value to the knowledge in the field of banking service quality for development and also opens new areas of research.

Introduction: The success of any insurance scheme is contingent upon well-defined processes related to payment, referral, grievances and quality control mechanisms. Any deviation observed may result in unsatisfactory performance. This study attempts to examine various processes related to the implementation of Pradhan Mantri Jan Arogya Yojana (PMJAY) and a state-specific insurance scheme across three states of India. Objective: To describe the policies and process adapted by selected states in implementing a government-sponsored health insurance scheme. To examine the strategies that work effectively, how they operate and what contextual factors enable or disable the desired implementation mechanisms. Methodology: The three states of Karnataka, Chhattisgarh, and Odisha were selected to understand various processes related to the implementation of Publicly Funded Health Insurance Schemes (PFHIS) schemes in diverse settings. A realist evaluation framework was used to study the contexts and mechanisms and how this influences outcomes. Results: The three schemes differ in implementation modes and follow different strategies owing to the local contexts. Some mechanisms worked well in specific contexts, whereas similar things have hindered the process in other contexts. Conclusion: The evidence generated is helpful to strengthen implementation processes under PMJAY and allows learning from each other to increase uptake of the scheme.

The COVID-19 pandemic has adversely affected the health and economy of almost all the countries in the world including India. Almost thousands of people are getting affected by this daily. In this paper, analysis of the daily statistics of people who got affected and this proposed work is going to predict the future trend of the active cases in Odisha and India. Machine Learning based forecasting algorithms have proved their significance in generating predictive outcomes which are used to make decisions on actions that are going to happen in the future. ML algorithms have been using for a long time to do this kind of task. This proposed work is going to do analysis and prediction on the dataset which was created by COVID India organization. Linear and Multiple Linear Regression models are used to predict the future trend of active cases and also the number of active cases in fore coming days and to visualize the trend of future active cases. Here, the performance of Linear and Multiple Linear regression models are compared by using the R2 score. Linear and Multiple Linear regression got 0.99 and 1.0 as R2 scores respectively which shows that these are the strongest prediction models that are used to predict the future active cases of COVID - 19. Both these models acquired remarkable accuracy in COVID - 19 prediction. A strong correlation factor shows that there is a very strong relationship between a dependent variable (Active cases) and independent variables (positive, deceases, recovered cases)

Mid-infrared (MIR) spectroscopy is emerging as one of the most promising technologies, as it is a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. This study was conducted to evaluate the potential of mid-infrared spectroscopy for the rapid and nondestructive measurement of some important soil properties of Alfisols. A total of 336 georeferenced soil samples fromthe 0–15 cm soil layer of Alfisols that were collected from the eastern Indian states of Odisha and Jharkhand were used. The partial least-squares regression (PLSR), random forest, and support vector machine regression techniques were compared for the calibration of the spectral data with the wet chemistry soil data. The PLSR-based predictive models performed better than the other two regression techniques for all the soil properties, except for the electrical conductivity (EC). Good predictions with independent validation datasets were obtained for the clay and sand percentages and for the soil organic carbon (SOC) content, while satisfactory predictions were achieved for the silt percentage and the pH value. However, the performance of the predictive models was poor in the case of the EC and the extractable nutrients, such as the available phosphorus and potassium contents of the soil. Specific regions of the MIR spectra that contributed to the prediction of the soil SOC, the pH, and the clay and sand percentages were identified. The study demonstrates the potential of the MIR spectroscopic technique in the simultaneous estimation of the SOC content, the sand, clay, and silt percentages, and the pH of Alfisols from eastern India.

School enrollment rates in developing countries have increased substantially over the past few decades. However, due largely to budget constraints, hiring contract teachers has become an ad hoc, yet a popular solution to teacher shortages in Asia, Africa, and Latin America. Studies concerning contract teachers have primarily focused on their performance, efficiency, and cost-effectiveness. In light of the literature on precarity associated with contractual employment, this article seeks to explore how contractual employment affects teachers in India. The study analyzes narrative data obtained through semistructured interviews with 17 contract teachers employed in government-run schools in Odisha, a state in eastern India. According to thematic analysis of the data, participants experience precarity in six dimensions: prioritisation of non-teaching work over teaching, financial hardships, sense of inferiority, anxiety about transfer, experiences of discrimination and desire for course correction. We argue that these six dimensions contribute to the demoralization and disempowerment of teachers. We also explore possible explanations for why Odisha continues to employ contract teachers despite criticism. It is recommended that policymakers be sensitized to the plight of contract teachers and reconsider the policy of contractual employment.

Farmer Producer Companies (FPCs) have emerged as a solution to the problems that small and marginal farmers confront with. This study probed into the reasons for the farmer-producer companies’ establishment, as stated in different policy documents and past literature. Performance of Farmers Producer Companies has improved significantly; however, the emergence of FPCs in India has not been consistent across the states. This paper examines the current status, geographical spread and functions of Farmer's Producer Companies (FPCs) across India, as well as suggests suitable measure to their performance. The study indicated that a total of 6471 FPCs were formed, in which around 80 per cent i.e. 5145 FPCs were promoted by Small Farmers Agri-business Consortium (SFAC) and National Bank for Agriculture and Rural Development (NABARD), 1263 FPCs were promoted by various state government and other agencies, and 63 of them were self-promoted. More than 50 per cent of the FPCs are set up in Maharashtra, Madhya Pradesh, Uttarakhand, West Bengal, Karnataka, Odisha and Telangana. SFAC promoted large number of FPCs in Madhya Pradesh (149 FPCs) and NABARD has promoted large number of FPCs in Uttarakhand (362). The number of farmers mobilised through FPCs by SFAC and NABARD were highest in the state of Madhya Pradesh with 183517 farmer members, followed by Karnataka with 176732 farmer members. There were a number of factors that influenced state performance, and this study suggested some strategies to overcome them in order to promote the growth of FPCs in India.

Purpose To overcome the spread of the noble coronavirus, the lockdown was imposed on March 25, 2020 by the Government of India which adversely affected the education system in the country and changed the traditional classroom teaching to online teaching. This paper aims to explore the factors encouraging university teachers to use and adopt e-learning systems during the COVID-19 pandemic and to find out the major challenges faced by them in adopting e-learning systems in Odisha, an Indian State. Design/methodology/approach The population of this study was teachers of different universities in Odisha, India. An online questionnaire was administered to collect data from the teachers of the state who were involved in the e-learning system for taking their online classes during the COVID-19 situation. During the study 610 valid responses were processed for data analysis. The results of the analysis were presented through factor analysis, t-test and structural equation model. Findings The findings revealed three major factors as user-friendly, convenient and performance encouraged teachers to use and adopt e-learning systems. The results also identified major challenges such as accessibility to the internet, information and communication technologies literacy and skills and technological support, faced by university teachers in adopting e-learning systems. Research limitations/implications The findings of the study have suggested that the university authorities can develop an effective e-learning system to support their teachers for the continuance of education and learning opportunities. The insights of this study can help the regulatory authorities of higher education to redesign policy and infrastructure for promoting effective e-learning systems. Originality/value Many studies have been conducted in relation to e-learning during COVID-19. However, this is a unique study that identifies supporting factors and addresses the challenges faced by university teachers in adopting an e-learning system.

Abstract Background Since 2005, India has experienced an impressive 77% reduction in maternal mortality compared to the global average of 43%. What explains this impressive performance in terms of reduction in maternal mortality and improvement in maternal health outcomes? This paper evaluates the effect of household wealth status on maternal mortality in India, and also separates out the performance of the Empowered Action Group (EAG) states and the Southern states of India. The results are discussed in the light of various pro-poor programmes and policies designed to reduce maternal mortality and the existing supply side gaps in the healthcare system of India. Using multiple sources of data, this study aims to understand the trends in maternal mortality (1997–2017) between EAG and non EAG states in India and explore various household, economic and policy factors that may explain reduction in maternal mortality and improvement in maternal health outcomes in India. Methods This study triangulates data from different rounds of Sample Registration Systems to assess the trend in maternal mortality in India. It further analysed the National Family Health Surveys (NFHS). NFHS-4, 2015–16 has gathered information on maternal mortality and pregnancy-related deaths from 601,509 households. Using logistic regression, we estimate the association of various socio-economic variables on maternal deaths in the various states of India. Results On an average, wealth status of the households did not have a statistically significant association with maternal mortality in India. However, our disaggregate analysis reveals, the gains in terms of maternal mortality have been unevenly distributed. Although the rich-poor gap in maternal mortality has reduced in EAG states such as Bihar, Odisha, Assam, Rajasthan, the maternal mortality has remained above the national average for many of these states. The EAG states also experience supply side shortfalls in terms of availability of PHC and PHC doctors; and availability of specialist doctors. Conclusions The novel contribution of the present paper is that the association of household wealth status and place of residence with maternal mortality is statistically not significant implying financial barriers to access maternal health services have been minimised. This result, and India’s impressive performance with respect to maternal health outcomes, can be attributed to the various pro-poor policies and cash incentive schemes successfully launched in recent years. Community-level involvement with pivotal role played by community health workers has been one of the major reasons for the success of many ongoing policies. Policy makers need to prioritise the underperforming states and socio-economic groups within the states by addressing both demand-side and supply-side measures simultaneously mediated by contextual factors.