A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases

Ravasan, Ahad Zare; Mansouri, Taha

doi:10.1080/09537287.2015.1064551

Cited by 50 publications

(33 citation statements)

References 43 publications

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“…Others have highlighted user satisfaction (Almajali et al , 2016), change management (Altamony et al , 2016), information quality, and system quality (Blasini and Leist, 2013) as CSFs. Despite the availability of all these findings to help guide ERP implementation projects, these complex and costly investments continue to face serious failures (Zare Ravasan and Mansouri, 2016). Thus, ERP implementation success and failure remain an intriguing discussion in information systems (IS) and operations management research.…”

Section: Introductionmentioning

confidence: 99%

An ERP success model based on agency theory and IS success model

Kamdjoug

Bawack

Tayou

2020

BPMJ

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PurposeThe purpose of this paper is to propose an enterprise resource planning (ERP) implementation model based on the agency theory and the Delone and McLean information systems (IS) success model. This paper answers two major research questions: (i) how does client–consultant interaction affect the outcome of ERP implementation projects; and (ii) how can this interaction be managed effectively to ensure successful project outcomes?Design/methodology/approachAn electronic banking institution in Africa was used to conduct a case study research and examine the validity of the proposed conceptual framework.FindingsBased on the constructs of the conceptual framework, the study found that client–consultant relationships/interactions mediate the effect of human, organizational, and technological critical success factors (CSFs) on information quality, service quality, and information quality. Agency conflicts in client–consultant relationships can be managed using outcome incentive-based contracts and a conflict management committee.Research limitations/implicationsThis is a single case study research. Thus, despite its analytical validity and generalizability, there is a need for more studies on the statistical validity of the model in other contexts.Practical implicationsThis paper provides practical information needed to manage conflicts between clients and consultants, as well as factors that must be considered in order to keep the interest of both parties aligned.Originality/valueNo research has been conducted on how to manage client–consultant interactions and related conflicts in ERP implementation projects. This study fills this gap using a well-established theoretical foundation to propose a conceptual framework that would guide and drive further discussions on the topic. This is also one of the few studies in the context of developing countries.

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Section: Introductionmentioning

confidence: 99%

An ERP success model based on agency theory and IS success model

Kamdjoug

Bawack

Tayou

2020

BPMJ

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“…FCMs can be constructed either by experts or historical data. However, there are some limitations in relying on experts' subjective opinions (Kahvandi et al, 2018;ZareRavasan & Mansouri, 2016). The learning approaches for FCMs are concentrated on learning the weighted matrix W, based either on expert intervention or available historical data (Papageorgioua & Kannappan, 2012).…”

Section: I~(cicj)=min(w(cpcp+): (Pp+1) ~ (I K~…k~j))mentioning

confidence: 99%

A Learning Fuzzy Cognitive Map (LFCM) Approach to Predict Student Performance

2021

Self Cite

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Aim/Purpose: This research aims to present a brand-new approach for student performance prediction using the Learning Fuzzy Cognitive Map (LFCM) approach. Background: Predicting student academic performance has long been an important research topic in many academic disciplines. Different mathematical models have been employed to predict student performance. Although the available sets of common prediction approaches, such as Artificial Neural Networks (ANN) and regression, work well with large datasets, they face challenges dealing with small sample sizes, limiting their practical applications in real practices. Methodology: Six distinct categories of performance antecedents are adopted here as course characteristics, LMS characteristics, student characteristics, student engagement, student support, and institutional factors, along with measurement items within each category. Furthermore, we assessed the student’s overall performance using three items of student satisfaction score, knowledge construction level, and student GPA. We have collected longitudinal data from 30 postgraduates in four subsequent semesters and analyzed data using the Learning Fuzzy Cognitive Map (LFCM) technique. Contribution: This research proposes a brand new approach, Learning Fuzzy Cognitive Map (LFCM), to predict student performance. Using this approach, we identified the most influential determinants of student performance, such as student engagement. Besides, this research depicts a model of interrelations among the student performance determinants. Findings: The results suggest that the model reasonably predicts the incoming sequence when there is a limited sample size. The results also reveal that students’ total online time and the regularity of learning interval in LMS have the largest effect on overall performance. The student engagement category also has the highest direct effect on student’s overall performance. Recommendations for Practitioners: Academic institutions can use the results and approach developed in this paper to identify students’ performance antecedents, predict the performance, and establish action plans to resolve the shortcomings in the long term. Instructors can adjust their learning methods based on the feedback from students in the short run on the operational level. Recommendation for Researchers: Researchers can use the proposed approach in this research to deal with the problems in other domains, such as using LMS for organizational/institutional education. Besides, they can focus on specific dimensions of the proposed model, such as exploring ways to boost student engagement in the learning process. Impact on Society: Our results revealed that students are at the center of the learning process. The degree to which they are dedicated to learning is the most crucial determinant of the learning outcome. Therefore, learners should consider this finding in order the gain value from the learning process. Future Research: As a potential for future works, the proposed approach could be used in other contexts to test its applicability. Future studies could also improve the performance level of the proposed LFMC model by tuning the model’s elements.

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“…Ravasan and Mansouri [121] surveyed critical failure factors in enterprise resource planning (ERP) systems and modeled risks' interrelations in ERP implementation projects using FCM. Mezei and Sarlin [96] presented a hybrid approach to measuring systemic risk in a financial system.…”

Section: Modelingmentioning

confidence: 99%

Fuzzy cognitive maps in systems risk analysis: a comprehensive review

Bakhtavar

Valipour

Yousefi

et al. 2020

Complex Intell. Syst.

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Fuzzy cognitive maps (FCMs) have been widely applied to analyze complex, causal-based systems in terms of modeling, decision making, analysis, prediction, classification, etc. This study reviews the applications and trends of FCMs in the field of systems risk analysis to the end of August 2020. To this end, the concepts of failure, accident, incident, hazard, risk, error, and fault are focused in the context of the conventional risks of the systems. After reviewing risk-based articles, a bibliographic study of the reviewed articles was carried out. The survey indicated that the main applications of FCMs in the systems risk field were in management sciences, engineering sciences and industrial applications, and medical and biological sciences. A general trend for potential FCMs’ applications in the systems risk field is provided by discussing the results obtained from different parts of the survey study.

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A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases

Cited by 50 publications

References 43 publications

An ERP success model based on agency theory and IS success model

An ERP success model based on agency theory and IS success model

A Learning Fuzzy Cognitive Map (LFCM) Approach to Predict Student Performance

Fuzzy cognitive maps in systems risk analysis: a comprehensive review

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