"Drive for Change: Investigating the Socio-Economic Landscape of Auto-Rickshaw Drivers in Panvel"

This study focus on the often overlooked yet critical socio-economic landscape of auto-rickshaw drivers in Panvel area. Auto-rickshaws serve as a lifeline for transportation in urban and suburban areas, and the drivers operating these vehicles constitute a vital but marginalized segment of society. The study is primarily based on primary source of information. For collection of primary data, we are using a schedule and interview method. The research aims to meticulously examine the multifaceted dimensions of auto rickshaw drivers and their socio-economic conditions, shedding light on their livelihoods, income levels, expenditure pattern, and other social aspects

Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A System Dynamics approach

Supply chains (SCs) are exposed to multiple risks and vulnerable to disruption propagation (i.e., the ripple effect). Despite established literature, quantitative analysis of the ripple effect in SCs considering simultaneous, long-term disruptions (i.e., induced by the COVID-19 pandemic) remains limited. This study defines, applies and demonstrates the capability of system dynamics modelling to recognise and visualise the ripple effect subject to supply, demand, and logistics disruptions as well as a combined, simultaneous disruption of supply, demand and logistics. Simulation results for these four risk scenarios indicate that disruption propagation and its impacts vary based on risk type, combination of risks and the impacting node. The bi-directional, increasing effect is significant for disruptions of longer duration. Retailers and manufacturers are most fragile to multiple disruptions due to broader risk exposure points. In generalised terms, systems theory-based study provides insights into the complex behaviour of simultaneous risks and associated disruptions occurring at a node and across the SC. The outcomes derived can help practitioners visualise and recognise the dynamic nature of the ripple effect cascading across the SC network. In addition, some novel insights on the systemic nature and delayed impact of disruption propagations are uncovered and discussed

An Impact of Migration on Urbanization Trends in Navi Mumbai: A Socio-Economic Perspective

The incessant flow of migration into urban centres has profoundly shaped the landscape of Navi Mumbai, heralding dynamic changes in its socio-economic fabric. This paper endeavours to explore the multifaceted impact of migration on the urbanization trends within Navi Mumbai, adopting a comprehensive socio-economic perspective. Through a nuanced analysis of demographic shifts, employment patterns, and settlement dynamics, this study aims to elucidate the intricate relationship between migration and the burgeoning urban landscape. The research delves into the transformative effects of migration on the socio-economic structure of Navi Mumbai, examining its implications on infrastructure, housing, and socio-cultural dimensions. By employing a mixed-method approach integrating qualitative interviews, quantitative data analysis, and spatial mapping techniques, the study seeks to unravel the intricate interplay between migration flows and urbanization dynamics. Furthermore, it aims to highlight the challenges and opportunities that arise from this interconnection, shedding light on potential avenues for sustainable urban development and inclusive growth. This investigation aspires to contribute to the scholarly discourse on migration and urbanization, offering valuable insights for policymakers, urban planners, and stakeholders invested in fostering resilient and equitable urban environments amidst the evolving landscape of Navi Mumbai

Supply chain risk assessment approach for process quality risks

Purpose- The purpose of the paper is to proactively analyse and mitigate root causes of the process quality risks. The case study approach examines the effectiveness of the fuzzy logic approach for assessing the product and process related failure modes within global supply chain context. Design/Methodology/approach- The case study of a printed circuit board company in China is used as a platform for conducting the research. Using data triangulation, the data is collected and analysed through interviews, questionnaires, expert opinions and quantitative modelling for drawing useful insights. Findings- The fuzzy logic approach to FMEA provides a structured approach for understanding complex behaviour of failure modes and their associated risks for products and processes. Supply Chain Managers should conduct robust risk assessment during the design stage to avoid product safety and security risks. Research Limitations/implications- The research is based on a single case study. Multiple cases from different industry sectors may support in generalising the findings. Originality/Value- The study attempts to mitigate the root causes of product and processes using fuzzy approach to FMEA in supply chain network

The Study Of Customer Satisfaction With The Special Reference To Panvel D-Mart

D-Mart is a popular supermarket chain in India. This study aims to understand the key factors influencing customer satisfaction, including product variety, pricing, store layout, staff behaviour, and overall shopping experience. Through qualitative and quantitative methods, the study analyses customer perceptions, identifies areas of strength and weakness for Panvel D-Mart, and recommends strategies to enhance customer satisfaction and loyalty. By focusing on this specific D-Mart location, the research offers valuable insights applicable to the broader D-Mart chain and the Indian retail landscape. The findings contribute to a deeper understanding of customer behaviour within the supermarket industry, ultimately guiding Panvel D-Mart and similar retailers towards improved customer satisfaction and sustained growth

Sustainability implementation challenges in food supply chains: a case of UK artisan cheese producers

Food supply chains are receiving increased attention due to rapid depletion of natural resources, increasing quality standards and rising food safety and security concerns. Implementing sustainability practices in food supply chains is believed to overcome such emerging challenges. However, limited studies address sustainability implementation concerns, particularly in cold food supply chains. Thus, this study attempts to identify factors hindering sustainability implementation in cold food chain networks by considering a case of UK artisan cheese producers. Survey data is utilised to identify and prioritise barriers for implementing sustainability following fuzzy analytic hierarchy process and sensitivity analysis. The analysis identified several key barriers, including initial investment cost, firm size and unawareness of government regulations. The internal barriers significantly dominate the implementation of sustainability practices in comparison to external barriers. Lack of consensus regarding the concept of sustainability by different stakeholders is observed to be an issue negatively affecting the level of integration in SMEs. Findings will help food and dairy SME's in gaining competitive advantage through the successful implementation of sustainability practices

A Community-based Bacteriological Study of Quality of Drinking-water and Its Feedback to a Rural Community in Western Maharashtra, India

A longitudinal study of the bacteriological quality of rural water supplies was undertaken for a movement towards self-help against diseases, such as diarrhoea, and improved water management through increased community participation. Three hundred and thirteen water samples from different sources, such as well, tank, community standpost, handpumps, percolation lakes, and streams, and from households were collected from six villages in Maharashtra, India, over a one-year period. Overall, 49.8% of the 313 samples were polluted, whereas 45.9% of the samples from piped water supply were polluted. The quality of groundwater was generally good compared to open wells. Irregular and/or inadequate treatment of water, lack of drainage systems, and domestic washing near the wells led to deterioration in the quality of water. No major diarrhoeal epidemics were recorded during the study, although a few sporadic cases were noted during the rainy season. As a result of a continuous feedback of bacteriological findings to the community, perceptions of the people changed with time. An increased awareness was observed through active participation of the people cutting across age-groups and different socioeconomic strata of the society in village activities

Supply chain simulation in a Big Data context: risks and uncertainty analysis

Due to their complex and dynamic nature, Supply Chains are prone to risks that may occur at any time and place. To tackle this problem, simulation can be used. However, such models should use Big Data technologies, in order to provide the level of data and detail contained in the data sources associated to the business processes. In this regard, this paper considered a real case of an automotive electronics Supply chain. Hence, the purpose of this paper is to propose a simulation tool, which uses real industrial data, provided by a Big Data Warehouse, and use such decision-support artifact to test different types of risks. More concretely, risks in the supply and demand end of the network are analyzed. The presented results also demonstrate the possible benefits that can be achieved by using simulation in the analysis of risks in a Supply Chain.This work has been supported by FCT–Fundação para a Ciência e Tec-nologia within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology andHigher Education, through national funds, and co-financed by the European Social Fund(ESF) through the Operational Programme for Human Capital (POCH)

Oxygen saturation and outcomes in preterm infants

BACKGROUN

On the use of simulation as a Big Data semantic validator for supply chain management

Simulation stands out as an appropriate method for the Supply Chain Management (SCM) field. Nevertheless, to produce accurate simulations of Supply Chains (SCs), several business processes must be considered. Thus, when using real data in these simulation models, Big Data concepts and technologies become necessary, as the involved data sources generate data at increasing volume, velocity and variety, in what is known as a Big Data context. While developing such solution, several data issues were found, with simulation proving to be more efficient than traditional data profiling techniques in identifying them. Thus, this paper proposes the use of simulation as a semantic validator of the data, proposed a classification for such issues and quantified their impact in the volume of data used in the final achieved solution. This paper concluded that, while SC simulations using Big Data concepts and technologies are within the grasp of organizations, their data models still require considerable improvements, in order to produce perfect mimics of their SCs. In fact, it was also found that simulation can help in identifying and bypassing some of these issues.This work has been supported by FCT (Fundacao para a Ciencia e Tecnologia) within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operational Programme for Human Capital (POCH)