Enterprise Resource Planning System Selection Research Articles

Geometric-arithmetic mean inequality for q-rung orthopair fuzzy Hamacher aggregations

The geometric-arithmetic mean inequality is undoubtedly the most important one in the area of information aggregation. Recently, some q-rung orthopair fuzzy aggregation operators were proposed based on the Hamacher operations. In this paper, we give a detailed theoretical and practical analysis of the developed Hamacher arithmetic and geometric operators for q-rung orthopair fuzzy values. First, we investigate the monotonicity of these Hamacher aggregation operators on q-rung orthopair fuzzy values with respect to the parameter within Hamacher operations. Then, we discuss the limiting cases of these q-rung orthopair fuzzy Hamacher aggregation operators as the parameter therein approaches to zero or infinity and give a new characterization of the boundedness of these aggregation operators. Subsequently, we establish the geometric-arithmetic mean inequality for q-rung orthopair fuzzy information based on Hamacher operations. Finally, we present a decision making method by use of these aggregation operators and apply it to the problem of enterprise resource planning system selection.

Analisis Pemilihan Enterprise Resource Planning (ERP) Menggunakan Analytical Hierarchy Process (AHP) Studi Kasus Pada PT. Laba Usaha Mandiri

Enterprise Resource Planning (ERP) can be used as a concept of organizational resource planning and management to generate added value for the company. PT. Laba Usaha Mandiri as an oil palm plantation startup is trying to improve its organization by trying to implement an ERP system to support daily operations. It is important that the ERP system selection process is carried out properly and correctly. And due to budget reasons, open source ERP was chosen for this problem. The selection of ERP system software for this company became the subject of a survey using quantitative methods using primary data and secondary data as samples. The results of testing and analysis using the Analytical Hierarchy Process (AHP) methodology are expected to be a guideline for the management of PT. Laba Usaha Mandiri to choose their ERP correctly

The importance of Industry 4.0 technologies when selecting an ERP system – An empirical study

The paper deals with the issue of the impact of the “Industry 4.0” concept on the process of selection of the enterprise resource planning (ERP) system. Firstly, review of the literature regarding the ERP system selection is presented, with the emphasis on the role of the new technologies in such selection. Secondly, the content of the term “Industry 4.0” is discussed, and put into context with the nature of ERP systems. The main part of the article then presents the results of the survey conducted among the medium and large industrial companies in the Czech Republic. Employees in the position of decision makers in the matter of selecting an ERP system were asked to participate. The survey used the form of questionnaire with close-ended questions with five-point scales, and investigated the attitude of the Czech manufacturing companies to the selected technologies of “Industry 4.0” and the importance of particular criteria for the selection of new ERP system. Investigated criteria were divided into 9 groups, where 5 of them were derived from previous research on the topic of ERP systems selections, and dealt with system price, portability, modularity, user experience and security. The remaining 4 groups were aimed at the selected technologies of “Industry 4.0” – big data, system integration, cloud computing and automatic identification and data capture. Kruskal-Wallis test and Neményi method of post-hoc analysis were used to compare the importance of particular criteria expressed by the respondents. The results show that although the companies are aware of the future challenges raised by the “Fourth Industrial Revolution,” in the selection of ERP systems they still emphasise mostly the previously used criteria such as price or modularity. As for the criteria connected to “Industry 4.0,” the ability of a system to deal with big data was assessed as the most important one.

DEVELOPMENT OF INNOVATIVE DIGITAL TECHNOLOGIES FOR ENTERPRISE MANAGEMENT

The efficacy of the organization and corporate strategy are substantially impacted by enterprise resource planning (ERP) technologies. However, it might be difficult to manage and apply the anticipated benefits of ERP. Workarounds further complicate outdated and evolving business procedures, which impedes the ongoing development of ERP. As a result, reaping the rewards is sometimes challenging. The complexity of realizing advantages also rises when subsidiaries are not able to discover new benefits on their own, even though benefits may differ from subsidiary to subsidiary. ERP systems, which integrate, synchronize, and centralize corporate data, are frequently viewed as a key resource for businesses that thrive in a fast-evolving global market. The selection of ERP systems is a crucial and challenging strategic choice because of the high cost of purchasing, installation, and implementation as well as the variety of offers. Because there are many different tangible and intangible requirements. This paper presents data on the development of innovative digital technologies in enterprise management. The main theoretical concepts of innovative digital technologies are described, as well as automated control systems and methods of their development are studied. This paper presents a model of innovation management in an industrial enterprise, an analysis of the ICT market, and developed recommendations on the methodology for implementing an ERP (Enterprise Resource Planning) system.

Novel Decision-Making Techniques in Tripolar Fuzzy Environment with Application: A Case Study of ERP Systems.

The intuitionistic fuzzy set (IFS) and bipolar fuzzy set (BFS) are all effective models to describe ambiguous and incomplete cognitive knowledge with membership, non-membership, negative membership, and hesitancy sections. But in daily life problems, there are some situations where we cannot apply the ordinary models of IFS and BFS, separately. Hence, there is a need to combine both the models of IFS and BFS into a single one. A tripolar fuzzy set (TFS) is a generalization of IFS and BFS. In circumstances where BFS and IFS models cannot be used individually, a tripolar fuzzy model is more dependable and efficient. Further, the IFS and BFS models are reduced to corollaries due to the proposed model of TFS. For this purpose in this article, we first consider some novel operations on tripolar fuzzy information. These operations are formulated on the basis of well-known Dombi T-norm and T-conorm, and the desirable properties are discussed. By applying the Dombi operations, arithmetic and geometric aggregation operators of TFS are proposed, and we introduce the concepts of a TF-Dombi weighted average (TFDWA) operator, a TF-Dombi ordered weighted average (TFDOWA) operator, and a TF-Dombi hybrid weighted (TFDHW) operator and explore their fundamental features including idempotency, boundedness, monotonicity, and others. In the second part, we propose TF-Dombi weighted geometric (TFDWG) operator, TF-Dombi ordered weighted geometric (TFDOWG) operator, and TF-Dombi hybrid geometric (TFDHG) operator. The features and specific cases of the mentioned operators are examined. Enterprise resource planning (ERP) is a management and integration approach that organizations employ to manage and develop many aspects of their operations. The study's primary contribution is to employ TFS to create certain decision-making strategies for the selection of optimal ERP systems. The proposed operators are then used to build several techniques for solving multiattribute decision-making (MADM) issues with TF information. Finally, an example of ERP system selection is investigated to demonstrate that the techniques suggested are trustworthy and realistic.

Spherical fuzzy cross entropy for multiple attribute decision making problems

In this paper, we investigate the multiple attribute decision making problems with spherical fuzzy information. The advantage of spherical fuzzy set is easily reflecting the ambiguous nature of subjective judgments because the spherical fuzzy sets are suitable for capturing imprecise, uncertain and inconsistent information in the multiple attribute decision making analysis. Thus, the cross- entropy of spherical fuzzy sets called, spherical fuzzy cross-entropy, is proposed as an extension of the cross-entropy of fuzzy sets. Then, a multiple attribute decision making method based on the proposed spherical fuzzy cross entropy is established in which attribute values for alternatives are spherical fuzzy numbers. In decision making process, we utilize the spherical fuzzy weighted cross entropy between the ideal alternative and an alternative to rank the alternatives corresponding to the cross entropy values and to select the most desirable one(s). Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Cloud-based ERP system selection based on extended probabilistic linguistic MULTIMOORA method and Choquet integral operator

Cloud-based enterprise resource planning (ERP) is a combination of standard ERP system and cloud flexibility. Adopting a suitable cloud-based ERP system is an uncertain multi-criteria decision-making problem. Probabilistic linguistic term sets (PLTSs) can be used to address the uncertainty in such problem. On the basis of PLTSs, we introduce an innovative two-step comparative method for the evaluation of cloud-based ERP systems. The extended multiple multi-objective optimisations by ratio analysis method within PLTSs are proposed to obtain the class of cloud-based ERP vendors. Two classes, namely, accepted and rejected, are obtained. Then, we select the suitable cloud-based ERP packages in the accepted class. We put forward the probabilistic linguistic Choquet integral operator to aggregate the ERP package evaluation matrices given the interrelationships between criteria. Subsequently, a new comparison method is introduced to obtain the final results. We conduct an illustrative example to prove the rationality of the presented method. The feasibility of this model is verified by comparative analysis and validity test.

Empirical decision analytics approach of advanced granularity-based models for identifying performance measures of ERPS application

There are four motivations in this study. First, recent machine learning techniques, such as decision trees, multi-layer perceptron, and Bayesian methods, for empirical decision analytics approach are spanning a wide research interest to understand and solve a real-world complex problem and thus attract significant concerns for identifying performance measures of extensive application domains. Second, integrated circuit design (IC) industry in Taiwan plays a prominent bellwether in triggering world’s economic markets, particularly for Taiwan Semiconductor Manufacturing Company. Third, enterprise resource planning system (ERPS) has been one of the most popular tools in total solution management across industries, and its relevant decision rules attract current trends in using an advanced soft computing approach. Lastly, with limited literature reviews, there is scarce investigation on picking right ERPS with effective decision rule-based knowledge for the IC design industry from application perspectives, and this research is first to bridge such a study gap for technical and managerial applications. Thus, this research synthesizes and proposes an advanced hybrid procedure to organize multi-expert granularity-based models with comprehensible decision rule-based wisdom to experience the ERPS selection and identify its determinants. The study finding implies that the determinants are varied from the class types and benefit interested parties useful references to facilitate positive migration of inter-industry. This research significantly contributes clear motivation and originality with good application values for an advanced hybrid analysis.

A large-scale data management and application analysis based on advanced classifier computing for the ERP system selection and adoption

Enterprise resource planning (ERP), promising trend of emerged large-scale data management, has urgent needs to enterprises that are faced with competitions under external environment and globalisation trend. It is an interesting issue to help ERP system vendor selecting a suitable customer through intelligent models. This motivates the study. We compare the empirical results of the decisional feature database constructed by two classification models, Models 1 and 2, and find out the critical factors for ERP system selection summarised from the analytical results and hypothesis. The empirical results include: 1) Model 1: the accuracy of percentage split without featureselection reaches 89.7810% at maximum; 2) Model 2: the accuracy of percentage split with expert feature-selection also reaches 89.7810% at maximum. This study yields the two management implications: 1) ERP vendors can find out hidden potential customers by the proposal models; 2) expert feature-selection of given data is an effective technique used to increase the purpose of classification quality.

Bipolar Fuzzy Hamacher Aggregation Operators in Multiple Attribute Decision Making

In this paper, we have investigated the multiple attribute decision-making problems with bipolar fuzzy information. Motivated by the Hamacher operations, we have proposed bipolar fuzzy Hamacher weighted average operator, bipolar fuzzy Hamacher ordered weighted average operator, bipolar fuzzy Hamacher hybrid average operator, bipolar fuzzy Hamacher weighted geometric operator, bipolar fuzzy Hamacher ordered weighted geometric operator, bipolar fuzzy Hamacher hybrid geometric operator. We investigate the characteristics and special cases of these operators. Then, we have utilized these operators to develop some approaches to solve the bipolar fuzzy multiple attribute decision-making problems. Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Additive consistent interval-valued Atanassov intuitionistic fuzzy preference relation and likelihood comparison algorithm based group decision making

This paper investigates a group decision making (GDM) method based on additive consistent interval-valued Atanassov intuitionistic fuzzy (IVAIF) preference relations (IVAIFPRs) and likelihood comparison algorithm. Firstly, the likelihood of IVAIF values (IVAIFVs) is defined by the likelihood of intervals. Then a likelihood comparison algorithm is designed to rank IVAIFVs. According to the additive consistent interval fuzzy preference relation, we define the additive consistency of an IVAIFPR. Two special interval fuzzy preference relations are extracted from an IVAIFPR. They can be regarded as the lowest and highest preferred matrices of the IVAIFPR, respectively. Using a parametric linear program, the IVAIF priority weights of an IVAIFPR are generated from these two extracted special interval fuzzy preference relations. For the GDM with IVAIFPRs, the group consensus is defined by the distances between the individual IVAIFPRs and the collective one. To derive decision makers' weights, an optimization model is constructed by maximizing the group consensus and transformed into a linear program to resolve. Subsequently, utilizing the IVAIF weighted averaging operator, the collective IVAIFPR is obtained and applied to obtain the IVAIF priority weights. The order of alternatives is generated by ranking the IVAIF priority weights. At length, an enterprise resource planning system selection example is analyzed to verify the effectiveness of the proposed method.

System Selection and Performance Evaluation for Manufacturing Company’s ERP Adoption

Enterprise Resource Planning (ERP) system is an important investment for manufacturing companies that can affect their competitive advantages and operational performance. However, the implementation of ERP can be a complicated process, where many strategic decisions have to be made. We focus on two critical decisions in ERP implementation: (1) ERP system selection, and (2) ERP operational performance evaluation. For the former, we use Analytic Hierarchy Process (AHP) to design the key performance indicator (KPI) system. For the later, we combine AHP and Fuzzy Integrated Evaluation (FIE) methods to effectively evaluate the implementation of ERP. We use a typical industrial example and data analysis to illustrate our framework.

PICTURE FUZZY CROSS-ENTROPY FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS

In this paper, we investigate the multiple attribute decision making problems with picture fuzzy information. The advantage of picture fuzzy set is easily reflecting the ambiguous nature of subjective judgments because the picture fuzzy sets are suitable for capturing imprecise, uncertain, and inconsistent information in the multiple attribute decision making analysis. Thus, the cross entropy of picture fuzzy sets, called picture fuzzy cross entropy, is proposed as an extension of the cross entropy of fuzzy sets. Then, a multiple attribute decision making method based on the proposed picture fuzzy cross entropy is established in which attribute values for alternatives are picture fuzzy numbers. In decision making process, we utilize the picture fuzzy weighted cross entropy between the ideal alternative and an alternative to rank the alternatives corresponding to the cross entropy values and to select the most desirable one(s). Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

An integrated decision making approach for ERP system selection using SWARA and PROMETHEE method

Deployment of an enterprise resource planning (ERP) system is a critical investment for an organisation that may significantly affect competitiveness and performance of a company in future, as well as in monitoring the resources. It is necessary for an enterprise to select a competent and suitable ERP system for the existing environment or with minor change in environment. In the present work, with a target to attain success in implementation of an ERP, a comprehensive ERP system selection framework with a set of 30 pertinent attributes has been addressed to evaluate the selection of an ERP system, keeping in mind that the factors that have been extended due importance in available literature. The methodology based on stepwise weight assessment ratio analysis (SWARA) technique to evaluate weight of the criteria, integrated with preference ranking organisation method for enrichment of evaluations (PROMETHEE) for alternative ranking has been proposed, to produce a framework for selection of an ERP system.

Enterprise Resource Planning System Selection Methodologies in Electronic and Mobile Commerce

Enterprise Resource Planning System Selection Methodologies in Electronic and Mobile Commerce

AN INTEGRATED MODEL TO SELECT AN ERP SYSTEM FOR CHINESE SMALL- AND MEDIUM-SIZED ENTERPRISE UNDER UNCERTAINTY

Enterprise Resource Planning (ERP) system is a vital investment that can significantly affect future competitiveness and performance of small- and medium-sized enterprises (SMEs). Selecting the best desirable ERP software covering both qualitative and quantitative factors has been the most critical problem for a long time. On the other hand, multiple criteria decision making has been found to be a useful approach to analyze conflicting factors. Qualitative criteria are often accompanied by ambiguities and vagueness. This makes fuzzy and grey logic become more natural approaches to handle this kind of problem. This paper presents a new approach for the selection of SME-specific ERP systems. Firstly, criteria for SMEs in China to evaluate the most suitable ERP system are put forward using group-discussing and anonymous questionnaire methods. An effective and practical algorithm, which is integrated of modified Delphi, analytic hierarchy process, fuzzy comprehensive evaluation and grey relational analysis, is utilized to convert the qualitative description to quantitative data to select the most appropriate alternative in the presence of vagueness and uncertainty. Finally, the potential use of the proposed model is illustrated through a case study.

Development of a hybrid methodology for ERP system selection: The case of Turkish Airlines

Enterprise resource planning (ERP) systems that aim to integrate, synchronize and centralize organizational data are generally regarded as a vital tool for companies to be successful in the rapidly changing global marketplace. Due to its high acquisition—purchasing, installation and implementation—cost and the wide range of offerings, the selection of ERP systems is a strategically important and difficult decision. Since there is a wide range of tangible and intangible criteria to be considered, it is often defined as a multi-criteria decision making problem. To overcome the challenges imposed by the multifaceted nature of the problem, herein a three-stage hybrid methodology is proposed. The process starts with the identification of most prevailing criteria through a series of brainstorming sessions that include people from different organizational units. Then, due to the varying importance of the criteria, a fuzzy Analytic Hierarchy Process, which handles the vagueness inherent in the decision making process, is used to obtain the relative importance/weights of the criteria. These weighted criteria are then used as input to the Technique for Order Preference by Similarity to Ideal Solution method to rank the decision alternatives. As a real-world illustrative case, the proposed methodology is applied to the ERP selection problem at Turkish Airlines. Because of the collaborative and systematic nature of the methodology, the results obtained from the process were found to be highly satisfactory and trustworthy by the decision makers.

Fit Gap Analysis – The Role of Business Process Reference Models

Enterprise resource planning (ERP) systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

Avaliação da importância relativa dos critérios para a seleção de Sistemas Integrados de Gestão (ERP) para uso em empresas da construção civil

A adoção de Sistemas Integrados de Gestão, também denotados sistemas ERP (Enterprise Resource Planning), introduziu a necessidade de se discutir o processo de avaliação deste tipo de sistemas, o qual está inserido em um contexto de múltiplas percepções ou critérios de avaliação. No presente trabalho, efetua-se uma revisão bibliográfica sistematizada em um conjunto de artigos publicados em periódicos indexados nas bases Scopus, ISI Web of Science ou Engineering Village, os quais relatam a construção/aplicação de modelos multicritério para avaliação de sistemas ERP. Com base nesta revisão bibliográfica, foi construído um conjunto de critérios e subcritérios, o qual foi submetido à validação por um conjunto de especialistas com experiência na seleção e implantação de ERP, resultando em uma árvore composta por 45 subcritérios agrupados em cinco critérios. Posteriormente, foi desenvolvida uma pesquisa de campo, da qual participaram 79 respondentes, principalmente das áreas de TI e Construção Civil, para captar percepções quanto à importância relativa destes critérios. A pesquisa revelou que os respondentes consideram os critérios Financeiro, Negócio e Software os mais importantes.

A Set of Criteria for Selection of Enterprise Resource Planning (ERP)

Information systems have evolved at a continual pace since administrations began to develop greater interest in production processes and supply chains. This created systems like Enterprise Resource Planning (ERP), Material Requirements Planning (MRP), and Manufacturing Resources Planning (MRPII). This research discusses a literature search conducted to map the multicriteria models used to select ERP systems. As a result, this article proposes criteria and subcriteria to be used in the selection of ERP systems. The basic structure is developed around a tree and subcriteria tree that can be used as a checklist for companies wishing to acquire an ERP system.