International Research journal of Management Science and Technology

  ISSN 2250 - 1959 (online) ISSN 2348 - 9367 (Print) New DOI : 10.32804/IRJMST

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PRODUCTION - A COMPONENT OF P3 SYSTEM- STATISTICAL ANALYSIS, AUTOCORRELATION, AND FORECAST

    2 Author(s):  JAYNA PATEL ,DR VIRANCHI SHAH

Vol -  10, Issue- 11 ,         Page(s) : 32 - 47  (2019 ) DOI : https://doi.org/10.32804/IRJMST

Abstract

Central theme is to detect versatility of two different products I & II with reference to quarterly sales in accordance with market demand, consistency in terms of sales and future sales values [using autocorrelation].

1. Dr Jha P., Shah V. (Aug- 2015). *P3 System- A study of effectiveness of the system in real life situations through study of customer satisfaction levels. ISOR Journal of Business and Management (IOSR-JBM), 17(8), 46-50.
2. Dr Jha P., Shah V. (Nov. - Dec. 2013). Production Planning and stocking of Life-Saving Medicines at Vendor’s end and Buyer’s End [A Real Case Study and Suggested Feasible Solution]. ISOR Journal of Business Management (IOSR-JBM), 14(2), 54-63.
3. Dr Jha P., Shah V. (May – June 2014). Maintaining a seamless supply chain of Essential Medicines [A combination of various concepts converging into a novel P3 system]. European Journal of Research and Reflection in Management Sciences, 2(1), 12-24.
4. Dr Jha P., Shah V. (July 2014). Production Planning and Profit Design in P3 system. Management, 4(3), 64-70.
5. Dr Jha P., Shah V. (April 2015). P3 System- A robust inventory model for life saving medicines: A comparison with established inventory management systems. International Journal of Business and Management Invention, 4 (4), 17-24.
6. Patel J, Dr Shah V. (2018). Critical Analysis of some components of P3* System. The Pharma Innovation Journal, 7(12); 43-46.
7. Patel J, Dr Shah V., Dr Jha P (2019). A Study of components of P3 system- forecasting for business decisions. The Pharma Innovation Journal, 8(5); 211-215.
8. Serkan Aras, Ipek Deveci Kocakoc, Cigdem Polat (2017). Comparative study of retails sales forecasting between single and combination methods, Journal of Business Economics and Management, 18 (5), 803-832.
9. Dilek Penpece and Orhan Emre Elma (Oct. 2014). Predicting Sales Revenue by using artificial neural networks in grocery retailing industry: A case study in Turkey, International Journal of Trade, Economics and Finance, 5(5), 435-440.
 

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