To reduce costs and improve organizational efficiency, the adoption of innovative services such as Cloud services is the current trend in today’s highly competitive global business venture. The aim of the study is to guide the software development organization (SDO) for Cloud-based testing (CBT) adoption. To achieve the aim, this study first explores the determinants and predictors of Cloud adoption for software testing. Grounded on the collected data, this study designs a technology acceptance model using fuzzy multicriteria decision-making (FMCDM) approach. For the stated model development, this study identifies a list of predictors (main criteria) and factors (subcriteria) using systematic literature review (SLR). In the results of SLR, this study identifies seventy subcriteria also known as influential factors (IFs) from a sample of 136 papers. To provide a concise understanding of the facts, this study classifies the identified factors into ten predictors. To verify the SLR results and to rank the factors and predictors, an empirical survey was conducted with ninety-five experts from twenty different countries. The application value in the industrial field and academic achievement of the present study is the development of a general framework incorporating fuzzy set theory for improving MCDM models. The model can be applied to predict organizational Cloud adoption possibility taking various IFs and predictors as assessment criteria. The developed model can be divided into two main parts, ranking and rating. To measure the success or failure contribution of the individual IFs towards successful CBT adoption, the ranking part of the model will be used, while for a complete organizational assessment in order to identify the weak area for possible improvements, the assessment part of the model will be used. Collectively, it can be used as a decision support system to gauge SDO readiness towards successful CBT.

中文翻译：

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用于衡量软件测试采用云的可能性的模糊多标准决策方法

为了降低成本并提高组织效率，采用云服务等创新服务是当今竞争激烈的全球商业风险的当前趋势。该研究的目的是指导软件开发组织 (SDO) 采用基于云的测试 (CBT)。为了实现这一目标，本研究首先探讨了软件测试采用云的决定因素和预测因素。基于收集到的数据，本研究使用模糊多准则决策（FMCDM）方法设计了一个技术接受模型。对于所述模型开发，本研究使用系统文献综述 (SLR) 确定了一系列预测因素（主要标准）和因素（子标准）。在 SLR 的结果中，本研究从 136 篇论文的样本中确定了 70 个子标准，也称为影响因素 (IF)。为了提供对事实的简明理解，本研究将确定的因素分为十个预测因素。为了验证 SLR 结果并对因素和预测因素进行排序，我们对来自 20 个不同国家的 95 位专家进行了实证调查。本研究在工业领域的应用价值和学术成果是开发了一个包含模糊集理论的通用框架，用于改进 MCDM 模型。该模型可用于以各种 IF 和预测变量作为评估标准来预测组织云采用的可能性。开发的模型可以分为两个主要部分，排名和评级。为了衡量单个 IF 对成功采用 CBT 的贡献，将使用模型的排名部分，而对于完整的组织评估，以确定可能改进的薄弱环节，将使用模型的评估部分。总的来说，它可以用作决策支持系统来衡量 SDO 对成功 CBT 的准备情况。