ABSTRACT
In the era of COVID-19, most of the business declined and a huge loss of jobs due to no demand and automobile sector is not the exception. Nearly 7.5% of India's GDP comes from the car industry, and supply chain is one of the key factors in a firm's overall value creation. The efficient and effective supply chain is dependent on information and communication technologies (ICTs) at present, and hence, it implies that ICT is spine of SCM. The major objective of the study was to draw conclusions on how information and communications technology practices affect supply chain management performance in the Indian auto-sector. The outcomes state that ICT practices have high correlation and direct impact on SCM performance, however, it does not have much impact on operational performance. The research also suggested that better and more effective ICT practices result better supply chain performance. The limitation of the research was the respondents' voluntary cooperation, and the ICT practices are limited to supply chain operational performance in various departments and functions only and not the applications in any vehicles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
As the Indian auto-industry entered BS-VI era from April 2020, the value proposition of used cars grew stronger, as the new cars became expensive due to additional technology costs. Moreover, the unavailability of public transport and fear of infection force people toward self-mobility during the outbreak of Covid-19 pandemic. But, the surge in demand for used cars made some car sellers to take advantage from customers by listing higher prices than normal. In order to help consumers aware of market trends and prices for used cars, there comes the need to create a model that can predict the cost of used cars by taking into consideration about different features and prices of other cars present in the country. In this paper, we have used different machine learning algorithms such as k-nearest neighbor (KNN), random forest regression, decision tree, and light gradient boosting machine (LightGBM) which is able to predict the price of used cars based on different features specific to Indian buyers, and we have implemented the best model by comparing with other models to serve our cause. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
By 2020, PPI year-on-year growth rate is negative, the CPI year-on-year increase continuously, in the overall economic environment, manufacturing continuous setbacks, at the same time, china automobile industry association information release data said that the auto industry in 2018 negative growth for the first time in ten years and the following two years continued to decline, the following two years continued to decline, the auto industry officially entered the cold winter period, In addition, in the background of Sino-US trade war, COVID-19, to cut overcapacity and inventory in the auto industry, The auto dealer reshuffle trend is obvious, the transformation is imperative, therefore, “Effectively help dealers reduce waste, improve efficiency and collaborate efficiently, promote customer consumption experience and increase transaction frequency and ultimately increase the overall profit of dealers” become the big issue that dealers require to solve immediately, based on the development trend of digital technology and the pain points of current automobile marketing management, the paper propose to improve the business process and marketing management methods of auto 4S shop through digital means, focusing on efficient customer acquisition, precise operation, content marketing and other aspects to adapt to the call of times and maximize profits. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.