Purpose -This research aims to improve supply chain management performance through the successful usage of ERP system. This can be through investigating the relationship between enterprise resource planning (ERP) system and supply chain management (SCM) performance in the context of Malaysian manufacturing companies that use ERP system. Design/methodology/approach -The questionnaire survey was posted to the Malaysian manufacturing companies that are using ERP system in order to investigate the relationship between ERP system and SCM performance. The respondents of this study were the MIS or IT executives. A total of 80 usable responses were received and used in the analysis. Findings -The findings of this research indicated that there is a positive and significant relationship between ERP system i.e. (integration, material management, production planning, and controlling), and SCM performance. The workflow management, however, does not have a significant relationship with SCM performance. The findings of this study imply that the successful implementation and the effective usage of ERP system can contribute toward enhancing supply chain management performance in many ways such as, integration of internal business processes, enhancement of information flow among different departments inside the company, improvement of the company's relationships and collaboration with outsourcing suppliers, customers, and supply chain partners. Research limitations/implications -This research focuses only on post-implementation of ERP system life cycle, where ERP system passes through three implementation stages of system life cycle and that includes pre-implantation stage, implementation stage, and finally post-implementation stage. Two or three stages of ERP system life cycle could be investigated simultaneously. Practical implications -There should be many success records in ERP system and this is to prove to companies that ERP systems can contribute toward improving their overall business performance. Therefore, this research encourages companies to adopt ERP systems and then contribute to technology diffusion. The finding of this study supports this justification and records a new success of ERP systems in Malaysian manufacturing companies. Originality/value -The results of this study will enable companies to achieve optimum usage of ERP system after the implementation stage and help to avoid system failure and achieve better SCM performance. The study contributes toward technology diffusion between companies through reducing the likelihood of ERP systems failure, and therefore introduces ERP systems to other manufacturing companies in Malaysia.
Abstract:Enterprise Resource Planning (ERP) system is a great solution to many cutting-edge businesses if implemented successfully and if not will cause a gigantic destruction in the organization. This research paper describes the Critical Success Factors (CSFs) in ERP system implementation across the three implementation stages in Sohar University which are pre-implementation stage, implementation stage, and postimplementation stage. A case study approach was used to investigate the perceptions of the key stakeholders in the university to pinpoint the CSFs of the ERP project. Based on a review of the ERP literature and in-depth interviews with the key stakeholders, 10 CSFs for ERP implementation have been identified. These findings extend our understanding of the CSFs that are perceived as critical for the key stakeholders involved in introducing, installing, and updating ERP system I higher education setting.
Enterprise Resource Planning (ERP) system is a very powerful solution to many academic and non-academic institutions in case it has been implemented and used effectively. Otherwise, the system will interrupt several business processes. This research paper investigates the impact of ERP system on academic performance at Sohar University. A survey questionnaire is distributed to several academic stakeholders to investigate the impact of ERP system on academic performance within the University context. A total of 110 questionnaires was received from the key academic stakeholders to examine the relationship between the three core ERP modules i.e. the students’ information module, the financial module, and human resource module. The research outcomes indicate that there is a relationship between the three modules and the academic performance. However, only students’ information module and financial management module demonstrate a significant impact on academic performance, though the human resource module shows no impact on the academic performance at Sohar University. This study is a single case study approach, which might limit the findings to be generalized on other education institutes, but it gives a chance to other researchers to do multiple case studies in other Universities in the region.
Summary Nowadays, there is an emerging need for applications based on the Internet of Things (IoT). The sensor nodes present in the IoT network produce data constantly, which directly influences the durability of the network. Therefore, two major challenges while designing IoT systems are network lifetime and energy consumption. Although the ability of IoT applications is huge, there are several limitations such as energy optimization, heterogeneity of devices storage, load balancing, privacy, and security that have to be addressed. These constraints have to be optimized for improving the efficiency of the networks. Hence, the main intention of this paper is to develop the intelligent‐based cluster head selection model for accomplishing green communication in IoT. The two famous algorithms like spotted hyena optimization (SHO) and sun flower optimization (SFO) are integrated to form sun flower‐spotted hyena optimization (SF‐SHO) by utilizing the hybrid meta‐heuristic concept for the optimal cluster head selection. The most significant parameters in IoT networks like delay, distance, energy, temperature, and load are considered for deriving a multi‐objective function to offer optimal clustering. The cluster head of the model is optimally tuned based on the hybrid SF‐SHO, to solve the multi‐objective problem, thus showing the enhanced green communication performance. The proposed model is analyzed and evaluated over different approaches in terms of energy‐specific factors, and the attained results confirm the efficiency of the developed method.
The Internet of Things (IoT) system is composed of several numbers of sensor nodes and systems, which are wirelessly interlinked to the internet. Generally, big data is the storage of a huge amount of information, which causes the classification process to be very challenging. Numerous big data classification approaches are implemented, but the computational time and secure handling of information are the major problems. The aim of the study is the development of big data approach in Internet of Things (IoT) healthcare application. Hence, this paper presents the proposed Dragonfly Rider Competitive Swarm Optimization-based Deep Residual Network (DRCSO-based DRN) for big data classification in IoT. First, the IoT nodes are simulated, and the heart disease patient data are collected through sensors. The routing is done using the Multi-objective Fractional Gravitational Search Algorithm (Multi-objective FGSA). In the Base Station (BS), the big data classification is done. Here, the classification is done using MapReduce (MR) framework, which includes two phases, like mapper and the reducer phase. The input data is initially fed to the mapper phase in the map-reduce (MR) framework. In the mapper phase, feature selection is carried out based on Dragonfly Rider Optimization Algorithm (DROA) in order to select the appropriate features for further processing. The DROA is modeled through merging Dragonfly Algorithm (DA) and Rider Optimization Algorithm (ROA). In the reducer phase, the classification is performed using DRN, which is trained by the developed DRCSO algorithm. The DRCSO is modeled by incorporating DA, ROA and Competitive Swarm Optimization (CSO). In addition, the performance of the developed method is outperformed than the existing approaches such as Linguistic Fuzzy Rules with Canopy Mapreduce (LFR-CM) + Fuzzy classifier, Machine learning-dependent k-nearest neighbors (FML-KNN), MapReduce-Fuzzy Integral-dependent Ensemble Learning Model+Single hidden layer feedforward neural network (MR-FI-ELM + SLFN) and DROA-recurrent neural network (RNN) based on the accuracy, average residual energy and throughput with the value of 0.929, 0.086[Formula: see text]J and 86.585. The proposed method is used to manage and derive meaningful information from the patient’s medical records, medical examinations results and hospital records.
Cloud-based ERP systems are substantially expanding, which is expected shortly to demonstrate a significant impact on the current business model. Identifying the Critical Success Factors (CSFs) and the major challenges of the cloud-based ERP systems implementation will pave the pathway for prospective clients to adopt cloud ERP systems and take advantage of this novel IT-based cloud revolution. This research identifies the top 10 CSFs that contribute to delivering a successful cloud-based ERP systems implementation. A survey instrument was distributed to 70 enterprises using cloud-based ERP systems. The research outcomes indicate a positive and significant relationship between eight CSFs and the cloud-based ERP systems implementation. However, only two factors demonstrate a positive but not significant correlation. Overall, the results of this study show a notable impact of the CSFs on the cloud ERP systems implementation.
BACKGROUND: In the last few months, e-learning witnessed a considerable demand due to the Covid-19 pandemic that made it the pragmatic solution for all Higher Education Institutions (HEI). Currently, all public and private universities relying on technology to make education continues with few interruptions. The migration of HEI into the virtual education model experienced several challenges in delivering rich education content to educators and learners. OBJECTIVE: Critical Success Factors (CSFs) enabled many universities to transform efficiently into the virtual environment. Before this transition, universities should carefully consider the key challenges and the CSFs to achieve successful migration to the virtual environment. E-learning is not a substitute anymore, it is gradually becoming a de-facto technology transformation in the current exceptional situation. This paradigm shift contributes to the success of education continuity in higher education settings. METHODOLOGY: A survey instrument was distributed to 500 students effectively using e-learning systems. Out of which only 330 were completed and used in the analysis which determined 66%as the overall response rate. RESULTS: The results of the study indicate a positive and significant relationship between the 13 CSFs and the e-learning systems usage, and that also indicates a notable impact of the CSFs on the e-learning systems usage. CONCLUSION: The outcome of this research identifies the top 13 CSFs that contribute to delivering successful e-learning systems usage. The top 13 CSFs are positively and significantly correlated with e-learning systems usage.
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