Customer requirements based ERP customization using AHP technique

Purpose– Customization is a difficult task for many organizations implementing enterprise resource planning (ERP) systems. The purpose of this paper is to develop a new framework based on customers’ requirements to examine the ERP customization choices for the enterprise. The analytical hierarchy process (AHP) technique has been applied complementarily with this framework to prioritize ERP customization choices. \ud \ud Design/methodology/approach– Based on empirical literature, the paper proposed an ERP customization framework anchored on the customer's requirements. A case study research method was used to evaluate the applicability of the framework in a real-life setting. In a case study with 15 practitioners working on the vendor's and the client's sides in an ERP implementation, the paper applied the framework jointly with the AHP technique to prioritize the feasible customization choices for ERP implementation. \ud \ud Findings– The paper demonstrates the applicability of the framework in identifying the various feasible choices for the client organization to consider when they decide to customize their selected ERP product. \ud \ud Research limitations/implications– Further case studies need to be carried out in various contexts to acquire knowledge about the generalizability of the observations. This will also contribute to refining the proposed ERP customization framework. \ud \ud Practical implications– Very few literature sources suggest methods for exploring and evaluating customization options in ERP projects from requirements engineering perspective. The proposed framework helps practitioners and consultants anchor the customization decisions on the customer's requirements and use a well-established prioritization technique, AHP, to identify the feasible customization choices for the implementing enterprise. \ud \ud Originality/value– No previously published research studies provide an approach to prioritize customization choices for ERP anchored on the customer's requirements

A Decision Support System for Investment Evaluation in Information Systems / Information Technology in Public Administration Organisations

Mestrado em Gestão de Sistemas de Informaçãoinfo:eu-repo/semantics/publishedVersio

Application of analytic hierarchy process to prioritize urban transport options: Comparative analysis of group aggregation methods

The present study presents a comparative analysis of different group aggregation methods adopted in AHP by testing them against social choice axioms with a case study of Delhi transport system. The group aggregation (GA) methods and their correctness were tested while prioritizing the alternative options to achieve energy efficient and less polluting transport system in Delhi. It was observed that among all group aggregation methods, geometric mean method (GMM) - the most widely adopted GA method of AHP - showed poor performance and failed to satisfy the most popular "pareto optimality and non-dictatorship axiom" raising questions on its validity as GA method adopted in AHP. All other group aggregation methods viz. weighted arithmetic mean method with varying weights and equal weights (WAMM, WeAMM) and arithmetic mean of individual priorities (AMM) resulted in concurring results with the individual member priorities. This study demonstrates that WeAMM resulted in better aggregation of individual priorities compared to WAMM. Comparative analysis between individual and group priorities demonstrates that the arithmetic mean (AMM) of priorities by individual members of the group showed minimum deviation from the group consensus making it the most suitable and simple method to aggregate individual preferences to arrive at a group consensus.AHP, decision making, GMM, group aggregation, transportation, WAMM

Application of Analytic Hierarchy Process to Prioritize Urban Transport Options - Comparative Analysis of Group Aggregation Methods

The present study presents a comparative analysis of different group aggregation methods adopted in AHP by testing them against social choice axioms with a case study of Delhi transport system. The group aggregation (GA) methods and their correctness were tested while prioritizing the alternative options to achieve energy efficient and less polluting transport system in Delhi It was observed that among all group aggregation methods, geometric mean method (GMM) - the most widely adopted GA method of AHP - showed poor performance and failed to satisfy the most popular pareto optimality and non-dictatorship axiom raising questions on its validity as GA method adopted in AHP. All other group aggregation methods viz. weighted arithmetic mean method with varying weights and equal weights (WAMM, WeAMM) and arithmetic mean of individual priorities (AMM) resulted in concurring results with the individual member priorities. This study demonstrates that WeAMM resulted in better aggregation of individual priorities compared to WAMM. Comparative analysis between individual and group priorities demonstrates that the arithmetic mean (AMM) of priorities by individual members of the group showed minimum deviation from the group consensus making it the most suitable and simple method to aggregate individual preferences to arrive at a group consensus.AHP, decision making, GMM, group aggregation, transportation, WAMM

ERP-ORE: A Framework to Measure Organizational Risk during ERP Systems Evolution in a Distribution Business

Enterprise Resource Planning systems evolution initiatives often represent the single largest investment (and therefore risk) for distribution corporations yet there exist few management frameworks in the literature to help decision makers measure risk during this organization-wide change process. We have customized our original ORE framework as a multi-criteria, relative risk, condition consequence management decision framework enabling executive decision makers in distribution businesses to calculate and compare risk evolution at fixed points of the ERP change cycle. The framework emphasizes the political and process dimensions of evolution and utilizes the Analytic Hierarchy Process to enable management to make structured and balanced risk mitigation decisions. This paper describes the development of ORE into ERP-ORE and illustrates the application of the framework through a case study description of a medical supplies distributor implementing an ERP system

A Process Model for ERP Upgrade and Replacement Decisions

Background: This paper aims to develop an effective decision making (DM) process for ERP change or replacement. ERP in most organizations constitutes a key critical system of high complexity with many stakeholders. A major change activity for such a system therefore exposes an organization to great risks, and thus should be well organized. Method: A design science approach was chosen for this research. Based on a review of related literature and evidence of the DM process at different companies, a general process of DM for ERP upgrade was designed, and later evaluated and improved through a case study approach. Results: The decision process assumes a model with variables describing characteristics and performance of possible alternatives, and the decision is decomposed into steps with three loops that are executed iteratively. We believe that the findings and approach can be useful both for the immediate problem context and also for other IT-related DM problems. Conclusions: The main outcome is the new process of DM that includes several novel contributions: three main loops of DM, multiple repetition of loops, and possible returns to the starting point

Supplier selection in automobile industry: A mixed balanced scorecard–fuzzy AHP approach

AbstractThis study proposed an integrated Balanced Scorecard–Fuzzy Analytic Hierarchical Process (BSC–FAHP) model to select suppliers in the automotive industry. In spite of the vast amount of studies on supplier selection, the evaluation and selection of suppliers using the specific measures of the automotive industry are less investigated. In order to fill this gap, this research proposed a new BSC for supplier selection of automobile industry. Measures were gathered using a literature survey and accredited using Nominal Group Technique (NGT). Finally, a fuzzy AHP was used to select the best supplier

Fuzzy AHP and Modified Fuzzy TOPSIS based Supplier Selection Model

The methods of AHP and Fuzzy AHP provide supports for decision making process, go through normalization procedure, produce different values for decision criteria weights and finally determine decision result. Interestingly both the method produces same decision result in various cases. The model for supplier selection showed by Foriborz Jolai (2011) based on AHP with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a matter of modification replacing by Fuzzy AHP and Modified Fuzzy TOPSIS methods in order to introduce ‘Fuzzification’ and ‘Defuzzification’ which is not available in existing model. The proposed model is verified with an illustrative example and comparing the results generated by both the existing and proposed model in consensus decision making. Keywords: AHP, Fuzzy, MCDM, TOPSIS, Supplier Selection DOI: 10.7176/JIEA/10-4-07 Publication date:October 30th 202

A review of fuzzy AHP methods for decision-making with subjective judgements

Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work