Application of Quantitative Forecasting Models in a Manufacturing Industry

Time series forecasting analysis has become a major tool in different applications for the Manufacturing Company. Among the most effective approaches for analyzing time series data is ARIMA (Autoregressive Integrated Moving Average). In this study we used Box-Jenkins methodology to build ARIMA model for annual sales forecast for 7up Bottling Company Plc for the period from January 2010 to December 2015, given the available monthly sales data. After the model specification; the best model for production was ARIMA (1, 1, 1) and for utilization was ARIMA (0, 1, 1). A 12 months forecast have also been made to determine the expected amount of sales revenue in year 2016. The time plot reveals seasonal variation. It thus concludes that that there is increase in sales revenue of Company with time, hence these models can be adopted for sales, production, utilization and demand forecasting in Nigeria, Keywords: ARIMA, Box-Jenkins, forecasting, production and utilization model, Time series analysis

Evaluation of Cluster Paradigm as a Tool for Agricultural Development in Nigeria

Cluster development is a conspicuous and common feature in today’s economy. However, this concept is not exactly new and has been the object of attention from a wide variety of management and social scientists for much of this century. In recent years, this phenomenon has attracted renewed interest from academics, practitioners, and the African continent - which have become aware of its central importance in competitive strategy. An understanding of clusters adds an important dimension to the more commonly debated role of personal contact networks in the success of Agricultural. The study adopts a Meta analysis and the use of secondary data. It was concluded that Agriculture in the 21st century requires an urgent turn around. It was recommended that the government should formulate policies, provide legal framework and create enabling environment to support cluster development. Keywords: Cluster Development, Agricultural Development, Innovation, Governmen