Nowadays, there are many organizations and institutions have realized the significant effect of the Internet of Things (IoT). The IoT technologies can enhance the quality of processes and services that make organizations seek to integrate these technologies to their products especially their smart devices. The IoT can be considered as one of the most important requirements that influences on detecting the best supplier. Therefore, every organization should take into account the effect of IoT on detecting the best supplier. So that, there is a need to a framework to help organizations for detecting the suitable supplier based on the effect of IoT. This work aims to introduce a proposed framework using trapezoidal neutrosophic numbers to detect the suitable supplier for purchasing smart systems based on the effect of IoT. The proposed framework consists of six phases. The proposed framework integrates the values and ambiguities index method with Single Valued Trapezoidal Neutrosophic Numbers (SVTN-numbers) which generalized fuzzy set and intuitionistic fuzzy to give more accurate results. The proposed framework is applied with a case study and the results concluded that the proposed framework can handle unclear information which exists in the purchasing process for detecting the suitable supplier of smart devices based on the effect of IoT.  Also, the proposed framework can handle uncertainty in decision making and link between customers and suppliers which can improve Supply Chain Management (SCM).

Cloud computing has been adopted widely by information systems due to its scalability and availability of resources and services. Cloud computing can provide different types of services through internet for Information Systems (IS). There are many cloud computing providers such as Google, Microsoft, and IBM are seeking for adopting of cloud services. Selecting the suitable cloud provider can maximize the benefits of cloud services. There is a need to determine the suitable cloud computing provider to achieve organizations' goals and maximize the benefits of cloud services. This work aims to introduce a decision support model based on trapezoidal neutrosophic numbers for determining the suitable cloud computing provider. The proposed model is applied by the Zagazig University (ZU) and the results indicated that the model can provide flexible method that can handle uncertainty in decision making for detecting the suitable provider. Also, the results show that the proposed model can support information systems in the choosing the suitable cloud computing provider.

One of the most important reasons for information systems failure is lack of quality. Information Systems Quality (ISQ) evaluation is important to prevent the lack of quality. ISQ evaluation is one of the most important Multi-Criteria Decision Making (MCDM) problems. The concept of Single Valued Triangular Neutrosophic Numbers (SVTrN-numbers) is a generalization of fuzzy set and intuitionistic fuzzy set that make it is the best fit in representing indeterminacy and uncertainty in MCDM. This paper aims to introduce an ISQ evaluation model based on SVTrN- numbers with introducing two types of evaluating and ranking methods. The results indicated that the proposed model can handle ill-known quantities in evaluating ISQ. Also by analyzing and comparing results of ranking methods, the results indicated that each method has its own advantage that make the proposed model introduces more than one option for evaluating and ranking ISQ.

Information Systems (IS) are increasingly becoming regarded as crucial to an organization's success. Information Systems Development Methodologies (ISDMs) are used by organizations to structure the information system development process. ISDMs are essential for structuring project participants’ thinking and actions; therefore ISDMs play an important role to achieve successful projects. There are different ISDMs and no methodology can claim that it can be applied to any organization. The problem facing decision makers is how to select an appropriate development methodology that may increase the probability of system success.
This paper takes this issue into account when study ISDMs and provides a Rule-based Expert System as a tool for selecting appropriate ISDMs. The proposed expert system consists of three main phases to automate the process of selecting ISDMs.
Three approaches were used to test the proposed expert system. Face validation through six professors and six IS professionals, predictive validation through twenty four experts and blind validation through nine employees working in IT field.
The results show that the proposed system was found to be run without any errors, offered a friendly user interface and its suggestions matching user expectations with 95.8%. It also can help project managers, systems' engineers, systems' developers, consultants, and planners in the process of selecting the suitable ISDM. Finally, the results show that the proposed Rule-based Expert System can facilities the selection process especially for new users and non-specialist in Information System field.