stdClass Object
(
    [id] => 17008
    [paper_index] => 202507-07-023081
    [title] => TIME SERIES FORECASTING OF VEHICLE SALES: A STRATEGIC APPROACH TO DEMAND PLANNING FOR TVS MOTORS IN SRI RAGHAVENDHRA AUTOMOBILES
    [description] => 
    [author] => M. Reddi Vani, Dr. E. Gnanaprasuna 
    [googlescholar] => 
    [doi] => 
    [year] => 2025
    [month] => July
    [volume] => 12
    [issue] => 7
    [file] => fm/jpanel/upload/2025/July/202507-07-023081.pdf
    [abstract] => The objective of this study is to develop a strategic approach to vehicle demand planning by applying time series forecasting techniques at Sri Raghavendra Automobiles LLP, an authorized dealership of TVS Motors located in Madanapalle. Accurate forecasting is crucial in the automotive sector for optimizing inventory levels, procurement planning, and marketing activities. This research analyses monthly vehicle sales data from January 2015 to December 2024 to identify significant trends, seasonal fluctuations, and the impact of promotional and festive periods on consumer demand.
The study employs quantitative methods, specifically the Autoregressive Integrated Moving Average (ARIMA) model, along with Python programming and EViews software, to model and forecast future sales. Among the models tested, ARIMA (3,1,1) demonstrated the best fit based on AIC and BIC criteria, enabling reliable short- to medium-term sales predictions up to 2027. The results reveal predictable demand surges during festival months and promotional campaigns, validating the effectiveness of time series forecasting in a dealership context.
These insights enable the dealership to adopt data-driven decision-making for managing stock levels, scheduling procurement cycles, and launching timely marketing campaigns. The findings underscore the strategic value of forecasting models in enhancing operational efficiency, minimizing costs, and aligning business functions with anticipated customer demand.

    [keywords] => Time Series Forecasting, Demand Planning, Sales Trend Analysis, Seasonality, Promotional Impact, Strategic Decision Making
    [doj] => 2025-07-18
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 14
    [journal_id] => 7
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Economics, Business and Management Studies (EBMS)
    [short_code] => IJHS
    [eissn] => 2347-4378
    [pissn] => 
    [home_page_wrapper] => images/products_image/2.EBMS.png
)
Error fetching PDF file.