Mohammad Shamsuzzaman, Mohammad Khadem, Salah Haridy, Ahm Shamsuzzoha, Mohammad Abdalla, Marwan Al-Hanini, Hamdan Almheiri and Omar Masadeh
The purpose of this study is to implement lean six sigma (LSS) methodology to improve the admission process in a higher education institute (HEI).
Abstract
Purpose
The purpose of this study is to implement lean six sigma (LSS) methodology to improve the admission process in a higher education institute (HEI).
Design/methodology/approach
In this study, case study research methodology is adopted and implemented through an LSS define-measure-analyze-improve-control (DMAIC) framework.
Findings
The preliminary investigation showed that the completion of the whole admission process of a new student takes an average of 88 min, which is equivalent to a sigma level of about 0.71 based on the targeted admission cycle time of 60 min. The implementation of the proposed LSS approach increased the sigma level from 0.71 to 2.57, which indicates a reduction in the mean admission cycle time by around 55%. This substantial improvement is expected not only to provide an efficient admission process but also to enhance the satisfaction of students and employees and increase the reputation of the HEI to a significant level.
Research limitations/implications
In this study, the sample size used in the analysis is considered small. In addition, the effectiveness of the proposed approach is investigated using a discrete event simulation with a single-case study, which may limit generalization of the results. However, this study can provide useful guidance for further research for the generalization of the results to wider scopes in terms of different sectors of HEIs and geographical locations.
Practical implications
This study uses several statistical process control tools and techniques through a LSS DMAIC framework to identify and element the root causes of the long admission cycle time at a HEI. The approach followed, and the lessons learned, as documented in the study, can be of a great benefit in improving different sectors of HEIs.
Originality/value
This study is one of the few attempts to implement LSS in HEIs to improve the administrative process so that better-quality services can be provided to customers, such as students and guardians. The project is implemented by a group of undergraduate students as a part of their senior design project, which paves the way for involving students in future LSS projects in HEIs. This study is expected to help to improve understanding of how LSS methodology can be implemented in solving quality-related problems in HEIs and to offer valuable insights for both academics and practitioners.
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Hooman Mansoori, Mohammad Reza Kohansal and Mohammd Farid Khadem Ghousi
Prosperity of the agricultural sector is very crucial not only for the national economy but also for the regional development. However, this prosperity has quite often a…
Abstract
Purpose
Prosperity of the agricultural sector is very crucial not only for the national economy but also for the regional development. However, this prosperity has quite often a significant environmental cost in terms of water resources overexploitation or pollution. The main purpose of this paper is to create, apply and evaluate a model that aims at the simultaneous maximization of farmer's welfare and the minimization of the consequent environmental burden.
Design/methodology/approach
Lexicographic goal programming technique is employed. This technique is implemented on a representative farm around Mashhad in Iran to seek for a solution – in terms of area and water allocation under different crops.
Findings
Results shows that application of a multi‐criteria analysis may lead to a win‐win situation.
Originality/value
A lexicographic goal programming is used to satisfy both goals of farm activity in a represented area in Iran.
Sujan Piya, Mohammad Miftaur Rahman Khan Khadem and Ahm Shamsuzzoha
The purpose of this paper is to develop a mathematical model of a make-to-order manufacturing company simultaneously negotiating multiple contingent orders that possess…
Abstract
Purpose
The purpose of this paper is to develop a mathematical model of a make-to-order manufacturing company simultaneously negotiating multiple contingent orders that possess conflicting issues in order to achieve order acceptance decisions (OADs).
Design/methodology/approach
The paper developed a mathematical model by incorporating probabilistic theory and some theories of negotiation in the OAD problem. The model helps to harness the relationship between the manufacturer and customers of contingent orders on conflicting issues. A numerical example is enumerated to illustrate the working mechanism and sensitivity of the model developed.
Findings
In the negotiation-based OAD system, if more than one customer is willing to negotiate on the offer of manufacturer, rather than engaging in one-to-one negotiation, the manufacturer has to negotiate with all the customers simultaneously to maximize the expected contribution and acceptance probability from all the orders. Also, the numerical example illustrates that, sometimes, rejecting an order/orders from the order set gives better results in terms of the expected contribution than continuing negotiations on them.
Originality/value
Through continuing research efforts in this domain, certain models and strategies have been developed for negotiation on a one-to-one basis (i.e. negotiation by the manufacture with only one customer at a time). One-to-one negotiation will neither help companies to streamline their production systems nor will it maximize the expected contribution. To the best of the author’s knowledge, so far, this is the first instance of research work in the domain of a joint OAD and negotiation framework that attempts to develop a simultaneous negotiation method for arriving at OADs.
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The Islamic State group threat
Details
DOI: 10.1108/OXAN-DB206713
ISSN: 2633-304X
Keywords
Geographic
Topical
Ahm Shamsuzzoha, Sujan Piya and Mohammad Shamsuzzaman
This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in…
Abstract
Purpose
This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions.
Design/methodology/approach
The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations.
Findings
A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works.
Research limitations/implications
The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity.
Originality/value
The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.
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Mohammad Khaleel Okour, Chin Wei Chong and Fadi Abdel Muniem Abdel Fattah
The purpose of this study is to investigate the influence of technological antecedents on the usage of decision makers for the implemented knowledge management system (KMS…
Abstract
Purpose
The purpose of this study is to investigate the influence of technological antecedents on the usage of decision makers for the implemented knowledge management system (KMS) amongst Jordanian banks. This study extends the investigation by assessing the influence of knowledge or information quality on KMS usage. This study aims to assess whether knowledge or information quality is significantly correlated to system compatibility, relative advantage and complexity (technological antecedents).
Design/methodology/approach
The study model was developed by using Rogers’ diffusion of innovation (DOI) theory, on which seven hypotheses were developed. To examine these research hypotheses, a self-administered questionnaire was carried out with 341 decision makers who are using the KMS to perform their job-related activities. Structural equation modelling analysis of moment structures software was used for data analysis.
Findings
The findings revealed that decision makers usage of the implemented KMS’s is affected significantly by relative advantages, system complexity and knowledge quality, but not system compatibility. Moreover, the findings showed that knowledge quality is significantly correlated with DOI technological antecedents.
Practical implications
Bank managements are now in a better position to understand what kind of resources and supports are needed to achieve the maximum pay-off from KMS usage within their banks. This study has proved that it is not sufficient for Jordanian banks to focus solely on the system quality; they must also take the quality of knowledge or information (system output) as a critical factor that can affect their investments in KMS’s.
Originality/value
This study is one of the limited conducted studies to investigate the importance of KMS usage and related antecedents in the Arab world; particularly, in the context of the Jordanian banking sector. The findings of this study have contributed to the Jordanian financial sector for its vital evaluation of the KMS actual usage behaviour. Findings can be used by the Jordanian ministry of finance to improve the understanding of the factors influencing KMS usage in the financial sector. This study has contributed to reducing the gap of DOI literature amongst developed and developing countries, particularly in the Jordanian context.
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Hadi Mahamivanan, Navid Ghassemi, Mohammad Tayarani Darbandy, Afshin Shoeibi, Sadiq Hussain, Farnad Nasirzadeh, Roohallah Alizadehsani, Darius Nahavandi, Abbas Khosravi and Saeid Nahavandi
This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.
Abstract
Purpose
This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.
Design/methodology/approach
A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.
Findings
The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.
Practical implications
It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.
Originality/value
Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.
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Salimeh Sadat Aghili, Mohsen Torabian, Mohammad Hassan Behzadi and Asghar Seif
The purpose of this paper is to develop a double-objective economic statistical design (ESD) of (
Abstract
Purpose
The purpose of this paper is to develop a double-objective economic statistical design (ESD) of (
Design/methodology/approach
The design used in this study is based on a double-objective economic statistical design of (
Findings
Numerical results indicate that it is not possible to reduce the second type of error and costs at the same time, which means that by reducing the second type of error, the cost increases, and by reducing the cost, the second type of error increases, both of which are very important. Obtained based on the needs of the industry and which one has more priority has the right to choose. These designs define a Pareto optimal front of solutions that increase the flexibility and adaptability of the
Practical implications
This research adds to the body of knowledge related to flexibility in process quality control. This article may be of interest to quality systems experts in factories where the choice between cost reduction and statistical factor reduction can affect the production process.
Originality/value
The cost functions for double-objective uniform and non-uniform sampling schemes with the Weibull shock model based on the Linex loss function are presented for the first time.
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Saber Souri, Zahra Nejatifar, Mohammad Amerzadeh, Fariba Hashemi and Sima Rafiei
Health-care workers (HCWs) are at increased risk of exposure to the COVID-19 virus, which necessitates implementing transmission prevention measures in health-care delivery…
Abstract
Purpose
Health-care workers (HCWs) are at increased risk of exposure to the COVID-19 virus, which necessitates implementing transmission prevention measures in health-care delivery facilities, particularly hospitals. This study aims to assess COVID-19 risk in a health-care setting and recommend managerial strategies to cope with existing risk procedures.
Design/methodology/approach
This cross-sectional study was conducted among HCWs working in a general hospital in Qazvin, northwest of the country. A total of 310 employees working at different clinical and non-clinical occupational levels participated in the study. The WHO COVID-19 risk assessment tool categorised HCWs in high- or low-risk groups exposed to COVID-19 infection.
Findings
Findings revealed statistically significant relationships between workplace exposure to the COVID-19 virus and variables, including job type, performing the aerosol-generating procedure, access to personal protective equipment (PPE) and being trained on Infection Prevention and Control (IPC) guidelines (p < 0.05). HCWs older than 36 years were at 8% more risk of COVID-19 virus. Being a medical doctor or delivering health-care services as a nurse were relatively 28% and 32% times more likely to be at high risk of infection than other hospital staff categories. Having inadequate access to PPE and lack of training on IPC guidelines were also key determinants of high-risk infection.
Originality/value
As most cases at risk of COVID-19 infection belonged to frontline health-care staff in older age groups, this study recommend limiting the exposure of vulnerable staff to COVID-19 patients, increasing protective measures for HCWs and providing essential information about infection control procedures.
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Abdullah Al Mamun, Mohammad Nurul Hassan Reza, Qing Yang and Norzalita Abd Aziz
Implementing big data analytics (BDA) for supply chain ambidexterity (agility and adaptability) and green supply chain (GRSC) presents various organizational challenges. These…
Abstract
Purpose
Implementing big data analytics (BDA) for supply chain ambidexterity (agility and adaptability) and green supply chain (GRSC) presents various organizational challenges. These include leveraging BDA capabilities to balance agility and adaptability, integrating this combined approach with GRSC and aligning these efforts to enhance firm performance. This study explores the associations between BDA, supply chain agility and adaptability, GRSC and their impact on firm performance.
Design/methodology/approach
Incorporating a resource-based view and contingency theory, we developed a research framework and validated it with data from 355 Chinese firms. Partial least squares structural equation modeling was used to analyze the data.
Findings
The findings demonstrate that BDA capabilities had direct impact on supply chain agility and adaptability, GRSC and firm performance. Moreover, the combination of supply chain agility and adaptability affected GRSC; which in turn significantly influenced firm performance. Supply chain agility and adaptability mediated the relationship between BDA capabilities and GRSC. Additionally, GRSC mediated the relationship between BDA capabilities, supply chain agility and adaptability and firm performance.
Originality/value
This study offers both a theoretical and empirical examination of the relationships between BDA capabilities, supply chain agility and adaptability, GRSC and firm performance. By assessing the direct and mediating effects of these factors on China’s industrial sector, it presents new theoretical and practical insights into BDA and GRSC, thereby enhancing the value of the existing literature.