Oreste Besson Rank and Certainty Factor for Digital Business Investment Decisions

Yulianto Umar Rofi'i
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Abstract

This study analyzes investment decision making in digital business using the Oreste Besson Rank and Certainty Factor methods. A mixed qualitative and quantitative approach is used to understand the qualitative factors that influence investment decisions and measure the effectiveness of analytical methods. The results of the qualitative analysis of the in-depth interviews highlight key factors: brand reputation (42% response), technology adaptability (35% response), and long-term growth potential (23% response). Uncertainty of technology and market changes (75% of respondents) affects investment strategy. Quantitative analysis uses the Decision Support System (SPK) and Besson-Rank methods to generate investment alternatives. Digital Properties rank the best, with Besson-Rank weighting the criteria score for a more in-depth look. The Certainty Factor (CF) method assesses investment options based on available data, with E-commerce Growth having the highest score, indicating a higher priority. The internal noise test confirms the Oreste Besson Rank and Certainty Factor methods as reliable tools, providing investment ratings and risk assessments consistent with simulated data. The results of this study underscore the importance of reputation, technology adaptability, and growth potential in digital business investment decisions. The Oreste Besson Rank and Certainty Factor methods are effective in providing accurate guidance. This research provides deeper insight into investment decision-making in a dynamic digital business and proposes recommendations for optimizing this analytical method in the face of market changes.
Oreste Besson 数字商业投资决策的等级和确定性因素
本研究使用奥雷斯特-贝松排名法和确定性因素法分析数字业务的投资决策。研究采用定性和定量混合方法,以了解影响投资决策的定性因素,并衡量分析方法的有效性。深入访谈的定性分析结果突出了关键因素:品牌声誉(42% 的回应)、技术适应性(35% 的回应)和长期增长潜力(23% 的回应)。技术和市场变化的不确定性(75% 的受访者)会影响投资战略。定量分析使用决策支持系统 (SPK) 和贝松排名法生成投资备选方案。数字地产排名最佳,Besson-Rank 对标准得分进行加权,以进行更深入的研究。确定性因子法(CF)根据现有数据对投资选择进行评估,其中电子商务增长得分最高,表明优先级较高。内部噪音测试证实,奥雷斯特-贝松排名法和确定性因子法是可靠的工具,提供的投资评级和风险评估与模拟数据一致。这项研究的结果强调了声誉、技术适应性和增长潜力在数字业务投资决策中的重要性。奥雷斯特-贝松排名法和确定性因子法能有效地提供准确的指导。这项研究为动态数字业务的投资决策提供了更深入的见解,并为在市场变化中优化这种分析方法提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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