Production Cost Forecasting for a Given Volume of Output in Organizations: Case Study Based on Regression Model




Cost Forecasting, Management Analysis, Regression Equation, Trend Analysis, Producation Costs, Expenses


Purpose: The objective of this study is the analysis and forecasting of  Enterprise Production Cost for a given volume of output on the basis of historical data.


Theoretical framework: The theoretical framework of the study includes studies conducted by various researchers and professional regulatory bodies (ACCA) related to the  the Production Cost forecasting in organizations.


Design/methodology/approach: The authors use trend analysis to determine a regression equation for the organisaton under investigation. Having the planned volume of production , it gives the opportunity to calculate the projected amount of production costs.  The financial and managerial accounting reports (from 2015 to 2022) provided by “Effect Group” CJCS were used to study the topic.


Findings: Using the revealed dependences and the trend equation, the forecasting of Production Cost of the organization under investigation is obtained  for the next two reporting periods.  


Research, Practical & Social implications: The main findings of the article can be useful in the practical management of businesses, for financial analysis and forecasting. In addition, the results of this research can be used in scientific and teaching activities in covering the issues of financial management and analysis.


Originality/value:  The value of the study is the contribution it makes to the literature on the cost analysis issues. Therefore, the article can be of benefit to the scientific community with an interest in the study of the subject.


Download data is not yet available.


Alsugair, Abdulah M., Naif M. Alsanabani, and Khalid S. Al-Gahtani. 2023. "Forecasting the Final Contract Cost on the Basis of the Owner’s Cost Estimation Using an Artificial Neural Network" Buildings 13, no. 3: 786.

Association of Chartered Certified Accountants, ACCA, The official website

Atiya A. F., (2019) Why does forecast combination work so well?, Int. J. Forecast., 2020, 36, 197–200.

Bowser, D.M., Henry, B.F. & McCollister, K.E. (2021) Cost analysis in implementation studies of evidence-based practices for mental health and substance use disorders: a systematic review. Implementation Sci 16, 26 (2021).

Clemen R. T., (1989)Combining forecasts: A review and anno- tated bibliography, Int. J. Forecast., 5, 559– 583.

Duffner F., Mauler L., Wentker M., Leker J. and Winter M.,( 2021) Large-scale automotive battery cell manufacturing: Analyzing strategic and operational effects on manufacturing costs, Int. J. Prod. Econ., 232, 107982

Dunn, P., 2023 Generalized linear models. International Encyclopedia of Education (Fourth Edition), Elsevier,

EFFECT Group CJSC, The official website,

Few Sh., Schmidt O., Offer G. J., Brandon N., Nelson J., Gambhir A.,( 2018) Prospective improvements in cost and cycle life of off-grid lithium-ion battery packs: An analysis informed by expert elicitations, Energy Policy, Volume 114, Pages 578-590,

Flayyih, H. H., & Khiari , W. (2022). A Comparative Study to Reveal Earnings Management in Emerging Markets: Evidence from Tunisia and Iraq. International Journal of Professional Business Review, 7(5), e0815.

Gritcyuk, K. (2017). Forecasting of production cost and other indices of activity of industrial enterprise. Technology Audit and Production Reserves, 3(2(35), 47–52.

Hueber, C., Horejsi, K., & Schledjewski, R. (2016). Bottom-up parametric hybrid cost estimation for composite aerospace production. In ECCM 2016 - Proceeding of the 17th European Conference on Composite Materials (ECCM 2016 - Proceeding of the 17th European Conference on Composite Materials). European Conference on Composite Materials, ECCM.

Mauler, L., Duffner, F., Zeier, W.G., & Leker, J. (2021). Battery cost forecasting: a review of methods and results with an outlook to 2050. Energy & Environmental Science.

Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Ben Taieb, S., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., Browell, J., Carnevale, C., Castle, J. L., Cirillo, P., Clements, M. P., Cordeiro, C., Cyrino Oliveira, F. L., De Baets, S., Dokumentov, A., ... Ziel, F. (2022). Forecasting: theory and practice. International Journal of Forecasting, 38(3), 705-871.

Sorrels John L. , Walton Thomas G. , (2017) Air Economics Group Health and Environmental Impacts Division Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, NC 27711 , Cost Estimation: Concepts and Methodology

Schmidt, F., Weisblum, Y., Muecksch, F., Hoffmann, H. H., Michailidis, E., Lorenzi, J. C. C., Mendoza, P., Rutkowska, M., Bednarski, E., Gaebler, C., Agudelo, M., Cho, A., Wang, Z., Gazumyan, A., Cipolla, M., Caskey, M., Robbiani, D. F., Nussenzweig, M. C., Rice, C. M., Hatziioannou, T., … Bieniasz, P. D. (2020). Measuring SARS-CoV-2 neutralizing antibody activity using pseudotyped and chimeric viruses. bioRxiv : the preprint server for biology, 2020.06.08.140871.

Schwabe O., Shehab E., Erkoyuncu J., (2016, a) An Approach for Selecting Cost Estimation Techniques for Innovative High Value Manufacturing Products, Procedia CIRP, Volume 55, 2016, Pages 41-46, ISSN 2212-8271,

Schwabe, O., Shehab, E., Erkoyuncu, J., (2016, b) “A Framework for Early Life Cycle Visualisation, Quantification and Forecasting of Cost Uncertainty in the Aerospace Industry”, Journal Progress in Aerospace Sciences

Serafim-Silva, S., Spers, R. G., Vázquez-Suárez, L., & Peña Ramírez, C. (2022). Evolution of Blended Learning and its Prospects in Management Education. International Journal of Professional Business Review, 7(1), e0291.

Smith A. & Mason A. (1997) Cost estimation predictive modeling: regression versus neural network, the engineering economist, 42:2, 137-161,

Soler-Toscano, F., Zenil, H., Delahaye, J-P., Gauvrit, N. (2014) “Calculating Kolmogorov Complexity from the Frequency Output Distributions of Small Turing Machines”, Preprint submitted to the Journal of Theoretical Computer Science, March 2015

Timmermann A., (2006) Chapter 4 Forecast Combinations, Editor(s): G. Elliott, C.W.J. Granger, A. Timmermann, Handbook of Economic Forecasting, Elsevier, Volume 1, 2006,Pages 135-196, ISSN 1574-0706, ISBN 9780444513953,




How to Cite

Grigoryan, L. H., & Hakobyan, A. S. (2023). Production Cost Forecasting for a Given Volume of Output in Organizations: Case Study Based on Regression Model. International Journal of Professional Business Review, 8(11), e03216.