Business strategy: The influence of Strategic Competitiveness on competitive advantage

Business strategy: The influence of Strategic Competitiveness on competitive advantage ( Vol-6,Issue-2,March - April 2021 )

Author: Bayad Jamal Ali, Govand Anwar

eecjournal doi crossrefDOI: 10.22161/eec.62.1

Keyword: Competitiveness strategies, competitive advantage, Business Strategy.

Abstract: The study's aim was to look into the different aspects of strategic competitiveness and how they affect competitive advantage in the private sector in Iraq's Kurdistan region. The researchers used four Strategic Competitiveness dimensions to assess the current analysis (Competitive strategies, innovation culture, managerial ethics, and Innovative Ideas). In order to interpret the current analysis, a quantitative methodology was used. The technique or process that the researcher is willing to accept in selecting objects for the sample is referred to as sample design. The research sample was chosen using a random sampling method and was carried out in various banks. A total of 125 questionnaires were distributed, but only 112 participants completed them correctly. Competitive strategies as a Strategic Competitiveness dimension has an important and positive impact on competitive advantage at a 5% level, according to the findings. The findings indicate that the Strategic Competitiveness dimension of Skills & Competencies has an important and positive impact on competitive advantage at a 5% stage. The findings show that entrepreneurial thought has an important and positive impact on the Strategic Competitiveness dimension, with a competitive advantage of 5%. The findings indicate that the Strategic Competitiveness dimension of Innovative Ideas has an important and positive impact on competitive advantage at a 5% stage. Furthermore, all beta values are greater than.001. The modified R2 for all models is quite large (0.693, 0.621, 0.712, and 0.763, respectively), meaning that the models' ability to explain variance in competitive advantage due to variation in independent variables is quite good. The F-value indicates that the explanatory variables in the model are jointly statistically important, and the Durbin-Watson (DW) statistics indicate that the models have autocorrelation.

Article Info: Received: 19 Dec 2020; Received in revised form: 12 Feb 2021; Accepted: 20 Mar 2021; Available online: 22 Apr 2021

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