Successful Enterprise Resource Planning (ERP) implementation depends upon various factors known as critical success factors (CSFs). This study developed a system dynamics model of ERP implementation based on CSFs to discuss ERP implementation complexities, which identifies the effect of CSF interrelations on different aspects of ERP project failure. Based on the model hypothesis, CSF interrelations include many causal loop dependencies. Some of these causal loops are called mortal loops, because they may cause the failure of risk reduction efforts to a more severe failure in effect of lack of system thinking on CSFs interrelations. This study discusses how system thinking works as a leverage point for overcoming ERP implementation challenges.

Evaluation of business processes plays a significant role in business development and improvement. Therefore, organizations need a systematic approach to evaluate all the changes through robust and powerful techniques that can formulate the relationship between the available information and the degree of the inherent uncertainty. In this paper, a set of operational variables are defined. Then, the SPSS software package is utilized to validate the gathered data. After that, the variables are categorized by the use of a clustering technique. Finally, five major factors are determined as the most effective components. According to the inherent uncertainty involved in the process of modelling, fuzzy set theory, a powerful mathematical tool is applied to handle the vagueness. In order to construct a knowledge base based on the fuzzy set theory, the linguistic concepts for each variable are defined. Lastly, membership functions are described and a set of fuzzy rules based on input-output parameters are written in MATLAB software environment. To demonstrate the potential application of the proposed approach, a real case study is illustrated. The results reflect the capability and effectiveness of the approach proposed in this paper.

This study aims to present a novel Self-regulating and Intelligence Meta-Heuristic-Fuzzy approach (As Methodological Contribution) for integrated and optimal Human Resource Allocation (HRA) in normal and critical conditions at SMEs (As Conceptual Contribution). In this research, a mathematical model of human resource allocation problem is presented, and then Sugeno Fuzzy Inference (SFI) model is used in the tasks rate adjustment layer. The SFI model is the main part of developing Gray Wolf Optimization (GWO) algorithm to reach the integrated and optimal allocation of available human resources under self-regulating attribute in the novel approach. The novel approach has tested and compared to the best researches using data previous researches and by the top five proposed methods in the researches (Includes: SGA, PRS, SRS, MIP, HM) based on three methods of evaluating the quality of solutions (GA-FSGS, MP-FSGS, GA-SGS). The results showed that increase of Ω from 15,000 to 25,000, and HM and SGA clearly performed better than other previous cases in the larger B100 and B200 datasets. Also, it is verified that the method had better results compare to all previous solving methods, and the quality of the solutions have been the best.

One of the greatest issues of project-driven organizations is the delay in their completion. Delay which has a nature of deviation basis and sometimes look so normal. Delay which instead of playing the role of a caution to managers, acts as a repetitive action. In such a situation the managers prefer to use the control tools and management of projects so that they can take a step for betterment. From these kinds of graphs we can mention Bullet Graph, Bar Graph, Pie Graph and S-Curve. Among these tools, S-Curve can be mentioned as one the essential ones. In this article, first we are going to define this curve; analysing its different usages, we will start with evaluating the role of this curve in management of deviation in the project and identify the problems and issues related to the usage of this curve in the second place. Finally, we will consider solving this problem, develop the S-Curve and introduce a new curve with the title of OS-Curve and apply it in two different projects and present its conclusions.

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