The SELECTION of ERP SYSTEMs has been considered as one of the most influential and risky managerial decisions due to its heavy burden of purchase and implementation costs. The purpose of this paper is designing a fuzzy expert SYSTEM for selecting the appropriate ERP SYSTEM based on the internationally selected and validated criteria for minimizing the risks of inappropriate SELECTION. If an option does not have the sufficient correspondence to the organizational criteria; the fuzzy logic provides the opportunity to the other options to taken into account for not only cover the weaknesses of measurement, but also easily lower the opportunity of selecting the appropriate alternatives. This leads to a comprehensive fuzzy evaluation of all of the alternatives. From another point of view, the fuzzy expert SYSTEM rules evaluate the options according to the demands and requirements of organization and accordingly, the SELECTION process will require no direct bi-comparison of options for the desired organizational status. For the sake of better validation and presentation, this paper has been conducted and provided through a case study of one of the Iranian industrial organizations.

An entERPrise resource planning SYSTEM (ERP) is the information backbone of a company that integrates and automates all business operations. Implementation of these SYSTEMs is expensive and difficult and takes many time and resources. Beside, SELECTION of suitable ERP SYSTEM to realization of all strategies and goals is a vital issue. This paper presents an approach to select a suitable ERP SYSTEM using fuzzy AHP with respect to BSC in Behpakhsh Company. Firstly, vision and strategy of company with respect to BSC is surveyed. A request for proposal was prepared according to the company’s vision, strategies and KPIs. Then, pair-wise questionnaires are designed and distributed among experts of Behpakhsh Company based on the criteria and indices related to ERP SYSTEM SELECTION extracted from ERP literature. Finally, covering the highest weight, package one selected as a most suitable ERP SYSTEM. The results of this paper show that proposed approach is a useful tool to ERP SELECTION and it can be used in other industries and service sectors.

Although Blockchain can significantly change the future of ERP SYSTEMs as an innovative tech-nology, few researchers have gone into the details of this development. Most have given an overview of the changes ahead. Therefore, in this research, we have tried to use the method of Exploratory Content Analysis (ECA) by reviewing more than three hundred scientific articles in the field of Blockchain to analyze the effects of this technology on ERP SYSTEM modules such as supply chain management, maintenance, finance, project management, manufacturing, and hu-man capital management. The result of this exploratory research is an architectural model for a blockchain-based ERP SYSTEM. The researchers describe the functions of this SYSTEM carefully, and the role of supporting technologies such as Smart Contract, IoT, Digital Wallet, Cloud Com-puting, and Building Information Model is clarified. We genuinely believe that this research could use as a reference model for ERP vendors and researchers in information SYSTEMs and business process management

This article seeks to establish a logical connection between the basic concepts and create a framework for better understanding of ERP and its implementation. Also, the paper tries to be understandable and gives a better description of the EntERPrise Resource Planning SYSTEM with non-technical method in ERP software packets by showing of a page of operation in maintenance unit.Since most of managers know and deal with 4P business model and its components and they can communicate with it easily, the primary structure of the ERP SYSTEM is derived from this model. ERP SYSTEM is divided into four main components: 1. Software, 2. Customer points of view, 3. Change management, and 4. Internal processes of SYSTEM.Methodology is another component which is involved in abovementioned four components for providing integration/unity and implementation in organized method. Maintenance planning is used for continuity of production with manpower to help keeping the equipment in normal conditions. As equipment is considered as the main sources of the organization, their maintenance would be important and this could be done easily by using this software SYSTEM. Consequently, we can develop the better understanding of ERP complexity in SYSTEM and processes which contribute to performance by creating conceptual model and features of different elements.

The implementation of modern ERP solutions has introduced tremendous opportunities as well as challenges into the realm of intensely competent businesses. The ERP implementation phase is a very costly and time-consuming process. The failure of the implementation may result in the entire business to fail or to become incompetent. This fact along with the complexity of data streams has led the researchers to develop a hierarchical multi-level predictive solution to automatically predict the implementation success of ERP solution. This study exploits the strength and precision of the Adaptive Neuro-Fuzzy Inference SYSTEM (ANFIS) for predicting the implementation success of ERP solutions before the initiation of the implementation phase. This capability is obtained by training the ANFIS SYSTEM with a data set containing a large number of ERP implementation efforts that have led to success, failure, or a mid-range implementation. In the initial section of the paper, a brief review of the recent ERP solutions as well as ANFIS architecture and validation procedure is provided. After that, the major factors of ERP implementation success are deeply studied and extracted from the previous literature. The major influential implementation factors in the businesses are titled as Change Orchestration (CO), Implementation Guide (IG), and Requirements Coverage (RC). The factors represent the major elements that guide the implementation project to a final success or to a possible failure if mismanaged. Accordingly, three initial ANFIS models are designed, trained, and validated for the factors. The models are developed by gathering data from 414 SMEs located in the Islamic Republic of Iran during a threeyear period. Each model is capable of identifying the weaknesses and predicting the successful implementation of major factors. After this step, a final ANFIS model is developed that integrates the outputs of three initial ANFIS models into a final fuzzy inference SYSTEM, which predicts the overall success of the ERP implementation project before the initiation phase. This model provides the opportunity of embedding the previous precious experiences into a unified SYSTEM that can reduce the heavy burden of implementation failure.

To select an entERPrise resource planning (ERP) SYSTEM is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively SYSTEMatic SELECTION policy for ERP SYSTEM is very important to the success of ERP project. In this paper, we propose a fuzzy analytic hierarchy process (FAHP) method to evaluate the alternatives of ERP SYSTEM. The SELECTION criteria of ERP SYSTEM are numerous and fuzzy, so how to select an adequate ERP SYSTEM is crucial in the early phase of an ERP project. The framework decomposes ERP SYSTEM SELECTION into three main factors. The goal of this paper is to select the best alternative that meets the requirements with respect to product factors, SYSTEM factors and management factors. The sub-attributes (sub-factors) related to ERP SELECTION have been classified into twelve main categories of Functionality, Reliability, Usability, Efficiency, Maintainability, Cost, Implementation time, User friendliness, Flexibility, Vendor Reputation, Consultancy Services, and R&D Capability and arranged in a hierarchy structure. These criteria and factors are weighted and prioritized and finally a framework is provided for ERP SELECTION with the fuzzy AHP method. Also, a real case study from Iran is also presented to demonstrate efficiency of this method in practice.