The Utilization of Autoregressive Forecasting Models in Strategic Management

Mustafa Ozguven, Chong Yan Gao and Mohamed Yacine Si Tayeb
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Mustafa Ozguven: Business School, University of International Business and Economics, Beijing, China.
Chong Yan Gao: Business School, University of International Business and Economics, Beijing, China.
Mohamed Yacine Si Tayeb: Business School, University of International Business and Economics, Beijing, China.

International Journal of Science and Business, 2021, vol. 5, issue 7, 170-185

Abstract: This study explores the utilization of autoregressive forecasting models in strategic management. Business forecasting denotes one of the recent developments in the business environment. The approach complements strategic management to foster the optimal performance of businesses. Business strategists use forecasting models to develop foresight on the future performance of their respective firms; however, there is limited literature on the effectiveness of these models. For this reason, this exploratory inquiry delved into generating autoregressive models and further examining their predictive effectiveness. The methods entailed the collection of secondary data (Tesla Motors Inc. revenue data) and subjecting it to univariate regression analysis to generate the linear forecasting equation. The findings revealed that autoregressive models are generated from the current and past data and can be used to forecasting future business performance. However, the accuracy of these equations relies on the quality of data and the stability of the industry. Therefore, the results of this inquiry contribute to the existing literature on forecasting models. Policy planners can use the information to improve the accuracy of their prediction models.

Keywords: Business forecasting; Strategic management; Autoregressive models; Univariate regression analysis; Optimal performance (search for similar items in EconPapers)
Date: 2021
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