Purpose

The paper aims to present an approach to cost-benefit analysis with stochastic data. Determining the type and the values of alternative’s factors are probably the most important issue in this approach. Therefore, in the proposed approach, a competitive advantage model was built to measure the values of alternative’s factors. Then, a satisfactory cost-benefit analysis model with random data was proposed to evaluate the alternatives. The cost-benefit analysis of each alternative was carried out to obtain the real and satisfactory cost-benefit of the decision-maker.

Design/methodology/approach

This paper is orientationally expressed as a mathematical problem in which the optimization problem needs to analyze the approach. This paper is written based on uncertainty linear optimization. Optimization under uncertainty refers to this branch of optimization where there are uncertainties involved in the data or the model and is popularly known as stochastic optimization problems.

Findings

As was seen in the purpose part, in this paper, an approach is presented to cost-benefit analysis by the use of competitive advantage with stochastic data. In this regards, a stochastic optimization problem to assess competitive advantage is proposed. This optimization problem recognizes the values of alternative’s factors which is the most important step in cost-benefit analysis. An optimization problem is proposed to cost benefit analysis, as well.

Practical implications

To investigate different aspects of the proposed approach, a case study with random data of 21 economic projects was considered.

Originality/value

Cost–benefit analysis is a systematic approach to estimating the strengths and weaknesses of alternatives used to determine options which provide the best approach to achieving benefits while preserving savings. Cost–benefit analysis is related to cost-effectiveness analysis. Benefits and costs are expressed in monetary terms and are adjusted for the time value of money; all flows of benefits and costs over time are expressed on a common basis in terms of their net present value, regardless of whether they are incurred at different times. As seen the paper using competitive advantage tries to determine the values of alternative’s factor. As competitive advantage model analyze the advantages and disadvantages of alternatives, this paper by the use of this idea tries to determine the costs and benefits. Two stochastic optimization problems in the middle of this approach are proposed, which assess competitive advantage and cost–benefit analysis, respectively.

中文翻译：

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一种利用随机数据通过竞争优势进行成本效益分析的方法

目的

本文旨在提出一种使用随机数据进行成本效益分析的方法。确定替代因素的类型和值可能是这种方法中最重要的问题。因此，在所提出的方法中，建立了一个竞争优势模型来衡量替代因素的价值。然后，提出了一个令人满意的随机数据成本效益分析模型来评估备选方案。对每个备选方案进行成本效益分析，以获得决策者真正满意的成本效益。

设计/方法/方法

本文定向表示为一个数学问题，其中优化问题需要分析方法。本文是基于不确定性线性优化编写的。不确定性优化是指数据或模型中存在不确定性的优化分支，通常称为随机优化问题。

发现

正如在目的部分所看到的，在本文中，通过使用随机数据的竞争优势，提出了一种成本效益分析方法。在这方面，提出了一个评估竞争优势的随机优化问题。该优化问题识别替代因素的值，这是成本效益分析中最重要的一步。还提出了成本效益分析的优化问题。

实际影响

为了研究所提出方法的不同方面，我们考虑了一个包含 21 个经济项目的随机数据的案例研究。

原创性/价值

成本效益分析是一种系统的方法，用于估计替代方案的优势和劣势，用于确定提供实现效益的最佳方法同时保持节约的选项。成本效益分析与成本效益分析有关。收益和成本以货币形式表示，并根据货币时间价值进行调整；一段时间内的所有收益和成本流量均以其净现值表示，无论它们是否在不同时间产生。正如所见，论文使用竞争优势试图确定替代因素的值。作为竞争优势模型分析备选方案的优缺点，本文试图利用这一思想确定成本和收益。