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Forecasting of Demand and Supply of Pulpwood for Paper Industries in Tamil Nadu, India: an Artificial Neural Network Model


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1 Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu, India
2 Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu
     

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The present global demand for paper and paperboard is 402 million tonnes per annum. In future the paper production will be nearly 521 million tonnes in 2021. In India, the present demand of paper and paperboard including newsprint is at 11.15 million tonnes per annum and per capita consumption is nearly 10.5 kg. The growth in the number of paper mills was from 17 units in 1950 to 759 units in 2010 with the production of 10.11million tonnes per annum. In Tamil Nadu, Tamil Nadu News prints and Papers Limited (TNPL) and Seshasayee Paper and Board Limited (SPB) are the major pulpwood based paper industries. In the past, industries got the raw materials from Tamil Nadu Forest Plantation Corporation (TAFCORN), farmlands and open market. Recently, these industries have amplified their paper production capacity, which requires 8 to 9 lakh tonnes of pulpwood per year, whereas the availability of pulpwood is nearly 6 to 6.5 lakh tonnes per year. This short supply will affect their performance in the market. Hence, this study is warranted to assess the factual demand and supply gap of industrial raw materials with different forecasting methods viz., trend analysis, moving average, single exponential smoothing model and artificial neural network (ANN). Based on forecast accuracy, ANN is observed as a reliable method which measures that the demand supply gap of raw materials will be 1,05,406 and 2,41,512 lakh tonnes in 2015 and 2020 respectively. In order to bridge the gap, industries must additionally produce raw materials by promoting resourceful captive plantation and the farm forestry area of 1000 - 1200 hectares per year by an appropriate business model.

Keywords

Paper Industry, Demand Supply Gap, Pulpwood And Forecasted Value
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About The Authors

S. Varadha Raj
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu
India

N. Narmadha
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu

T. Alagumani
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu

M. Chinnadurai
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu


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  • Forecasting of Demand and Supply of Pulpwood for Paper Industries in Tamil Nadu, India: an Artificial Neural Network Model

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Authors

S. Varadha Raj
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu, India
N. Narmadha
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu
T. Alagumani
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu
M. Chinnadurai
Department of Agriculture Economics, TNAU, Coimbatore-3 Tamil Nadu

Abstract


The present global demand for paper and paperboard is 402 million tonnes per annum. In future the paper production will be nearly 521 million tonnes in 2021. In India, the present demand of paper and paperboard including newsprint is at 11.15 million tonnes per annum and per capita consumption is nearly 10.5 kg. The growth in the number of paper mills was from 17 units in 1950 to 759 units in 2010 with the production of 10.11million tonnes per annum. In Tamil Nadu, Tamil Nadu News prints and Papers Limited (TNPL) and Seshasayee Paper and Board Limited (SPB) are the major pulpwood based paper industries. In the past, industries got the raw materials from Tamil Nadu Forest Plantation Corporation (TAFCORN), farmlands and open market. Recently, these industries have amplified their paper production capacity, which requires 8 to 9 lakh tonnes of pulpwood per year, whereas the availability of pulpwood is nearly 6 to 6.5 lakh tonnes per year. This short supply will affect their performance in the market. Hence, this study is warranted to assess the factual demand and supply gap of industrial raw materials with different forecasting methods viz., trend analysis, moving average, single exponential smoothing model and artificial neural network (ANN). Based on forecast accuracy, ANN is observed as a reliable method which measures that the demand supply gap of raw materials will be 1,05,406 and 2,41,512 lakh tonnes in 2015 and 2020 respectively. In order to bridge the gap, industries must additionally produce raw materials by promoting resourceful captive plantation and the farm forestry area of 1000 - 1200 hectares per year by an appropriate business model.

Keywords


Paper Industry, Demand Supply Gap, Pulpwood And Forecasted Value