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The purpose of this paper is to review research on options theory (OT) in the management information systems (MIS) field.

The paper reviews OT and suggests further ways it may be useful for MIS.

The paper explores current global trends and past uses of OT by MIS researchers within a framework. The objective is to broaden discussion of OT in the MIS field, facilitate theory development, close gaps in existing knowledge, and uncover areas where research is needed. It is believed that MIS researchers will benefit from this study.

The use of OT in MIS is still young. The discussions, issues, and ideas set forth in this paper should stimulate interest in incorporating OT in the field of MIS.

The paper identifies proper application of OT, thus enabling effective development. It seeks to build awareness and understanding of significant works in the field, providing a diversity of perspectives and approaches to MIS and more specific research of OT.

The paper helps future theorizing and makes research suggestions regarding OT and the MIS field based on past research, thereby forming a potential basis for future research.

There has been no systematic literature review of real options in the management field. This paper is the pioneer one to do this.

The purpose of this paper is to analyze supplier selection from an economic perspective. The conventional view of cost benefit analysis is that the cost dimension is static, and companies are urged to pursue the lowest bid price when choosing suppliers. However, this perspective does not consider uncertainty, which is an important characteristic of supply chains. To overcome this shortcoming, a model is proposed that views supplier selection under uncertainty.

The study proposes a model that analyzes supplier selection from an economic standpoint based on the switching options approach.

The results show that, contrary to the conventional wisdom, the buyer's choice of supplier makes a significant difference under conditions of uncertainty, and naïvely accepting the lowest bid price is not necessarily the best option.

The study extends the literature by quantifying previous studies of the buyer‐supplier relationship. This enhances understanding by quantifying the relationship under conditions of uncertainty, a topic that has been largely ignored by previous works.

The economic perspective, which considers uncertainty, helps managers examine their supply chain relationships in depth when choosing suppliers. In addition, this study could also help buyers access alternative supply chain partners. Managers can make the calculations easily by using Microsoft Excel software.

The paper presents an original discussion about viewing supplier selection from the switching options perspective. The modeling and analysis of switching options help managers better understand the supplier selection process from an economic perspective, and improve competitiveness by helping them to make appropriate decisions.

Failure of the materials occurs once the stress intensity factor (SIF) overtakes the material fracture toughness. At this level, the crack will grow rapidly resulting in unstable crack growth until a complete fracture happens. The SIF calculation of the materials can be conducted by experimental, theoretical and numerical techniques. Prediction of SIF is crucial to ensure safety life from the material failure. The aim of the simulation study is to evaluate the accuracy of SIF prediction using finite element analysis.

The bootstrap resampling method is employed in S-version finite element model (S-FEM) to generate the random variables in this simulation analysis. The SIF analysis studies are promoted by bootstrap S-version Finite Element Model (BootstrapS-FEM). Virtual crack closure-integral method (VCCM) is an important concept to compute the energy release rate and SIF. The semielliptical crack shape is applied with different crack shape aspect ratio in this simulation analysis. The BootstrapS-FEM produces the prediction of SIFs for tension model.

The mean of BootstrapS-FEM is calculated from 100 samples by the resampling method. The bounds are computed based on the lower and upper bounds of the hundred samples of BootstrapS-FEM. The prediction of SIFs is validated with Newman–Raju solution and deterministic S-FEM within 95 percent confidence bounds. All possible values of SIF estimation by BootstrapS-FEM are plotted in a graph. The mean of the BootstrapS-FEM is referred to as point estimation. The Newman–Raju solution and deterministic S-FEM values are within the 95 percent confidence bounds. Thus, the BootstrapS-FEM is considered valid for the prediction with less than 6 percent of percentage error.

The bootstrap resampling method is employed in S-FEM to generate the random variables in this simulation analysis.