Abstract
Purpose
The purpose of this paper is to develop comprehensive risk management tool, Intelligent Risk Mapping and Assessment System (IRMAS™) with a contingency for multi‐site, multi‐partner concurrent engineering projects with the aim of achieving above‐mentioned paradigms. Its unique knowledge warehouse enables the use of organisational knowledge, lessons learnt, captured as well as best practices to minimise risks in project management.
Design/methodology/approach
IRMAS is designed to identify, prioritise, analyse and assist project managers to manage perceived sources of concurrent engineering risks. Several knowledge elicitation techniques were used to compile the knowledge used for the intelligent system developed. The core of the research is the reasoning methodology that not only supports the decision‐making process of the user, but also aids the knowledge retrieving, storing, sharing and updating process of manufacturing organisations.
Findings
A total of 589 risk items were identified for different project types, as well as information on 4,372 risk items and 136 lessons learnt were gathered. IRMAS is a proactive tool supporting project management activities. It is designed as a web‐based portal compiled in Java facilitating effective and a common communication platform between project partners.
Research limitations/implications
Identification of risks during the complete product design, development and delivery process in a concurrent engineering environment is challenging. It covers the “product value stream” including partners, suppliers, research and development, design and manufacturing, marketing, purchasing, service and support personnel and customers. Within the context of concurrent engineering, the design style must be “Design WITH” approach where collaborative negotiation requires communication, consideration and collaboration. The full validation of IRMAS™ is successfully carried out in two large‐scale new product development projects. It has already been decided to be deployed by a large international aerospace company and is successfully commercialized.
Originality/value
The originality of the paper lies in its uniqueness in these areas: IRMAS provides a systematic engineering approach to risk management of concurrent product and process development based on risk management standards and Project Management Body of Knowledge, to leverage of success factors in manufacturing; concurrencies and relationships between several activities throughout product's life cycle are captured and mapped; the inheritance of risk between several phases are modelled and quantified; the wealth of knowledge stored in the knowledge repository and IRMAS's capability to reuse them for later elicitation in the system's knowledge base; and user‐interactive, unique dynamic risk management software package which will be available in the commercial market.
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Jean-Louis Ermine, Denise Bedford and Alexeis Garcia-Perez
Ying‐Chin Ho and Chih‐Hsin Lin
The problem that original design manufacturing (ODM) companies encounter with the request for quotation (RFQ) process is that there is no effective and efficient methodology for…
Abstract
Purpose
The problem that original design manufacturing (ODM) companies encounter with the request for quotation (RFQ) process is that there is no effective and efficient methodology for them to formulate accurate and profitable RFQs. The purpose of this paper is to present a quality function deployment (QFD)‐, concurrent engineering (CE)‐, and target costing‐based methodology for ODM companies to formulate accurate and profitable RFQs.
Design/methodology/approach
From eight Taiwan electronics ODM companies, 15 people are interviewed to understand their current methods for formulating RFQs and the problems of these methods. Based on the interview results, it was decided to make use of the merits of QFD, CE, and target costing by integrating them into the proposed methodology.
Findings
A case study is presented to illustrate a successful application of the proposed methodology in a case company. The case study shows integrating QFD, CE, and target costing into the proposed methodology allows the authors to effectively and efficiently formulate an accurate and profitable RFQ for the case company.
Research limitations/implications
The interview sample quantity of this study is limited to eight Taiwan electronics companies, which is insufficient to represent all ODM companies in various industries. For the future research, it is suggested researchers collect more samples from different industries in order to verify the effectiveness of the proposed methodology in ODM companies from different industries.
Originality/value
This paper aims to integrate QFD, CE, and target costing to come up with a systematic ten‐step approach that can accurately formulate the three parts of an RFQ: the product specifications proposal, the product price quotation, and the product development schedule. By adopting this methodology, ODM companies can provide accurate and profitable RFQs to ODM customers, thus increasing their chances of obtaining ODM business.
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Precious Dapaah Opoku, Richard Kwasi Bannor and Helena Oppong-Kyeremeh
The purpose of this paper was to analyse the demographic, crop choice, institutional and environmental factors that will influence the vegetable growers in Bono and Ahafo regions…
Abstract
Purpose
The purpose of this paper was to analyse the demographic, crop choice, institutional and environmental factors that will influence the vegetable growers in Bono and Ahafo regions of Ghana to produce organic vegetables. The study also assessed the knowledge level of vegetable growers on organic certification processes.
Design/methodology/approach
Primary data were collected with the help of a structured questionnaire from 120 vegetable growers via a multistage sampling technique. The Heckman selection model was used to analyse the factors that influence farmers' willingness to adopt organic production as well as the intensity of adoption.
Findings
In this study, pepper (Capsicum spp) production, residential status, knowledge of organic certification processes, perceived negative environmental effect of conventional farming on the soil, and climate change positively influenced willingness to produce organic vegetables. Likewise, pepper production perceived negative environmental effect of conventional farming on the soil positively influenced the intensity of adoption. Household headship status, garden egg (Solanum integrifolium) production, perceived knowledge on grading and standards of vegetables, as well as the perception that only pesticides can be used to control vegetable pests negatively influenced the willingness to produce organic vegetables however perceived expertise of the farmer on grades and standards influenced intensity of adoption negatively.
Originality/value
In Ghana, even though most vegetable farmers do not have the requisite knowledge in the safe handling of pesticides, usage is widespread. Subsequent to this, is a health risk to farmers, consumers and the environment. As a result, there is a growing awareness that organic agriculture has a role to play in addressing problems associated with agrochemical use and over usage. However, most studies are consumer oriented with limited empirical research on the willingness to produce organics by farmers.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2019-0723
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Santosh B. Rane, Prathamesh Ramkrishana Potdar and Suraj Rane
The purpose of this study is to investigate the best fleet for a new purchase based on multi-objective optimization on the basis of ratio (MOORA), reference point and multi-MOORA…
Abstract
Purpose
The purpose of this study is to investigate the best fleet for a new purchase based on multi-objective optimization on the basis of ratio (MOORA), reference point and multi-MOORA methods. This study further identifies critical parameters for fleet performance monitoring and exploring optimum range of critical parameters using Monte Carlo simulation. At the end of this study, fleet maintenance management and operations have been discussed in the perspectives of risk management.
Design/methodology/approach
Fleet categories and fleet performance monitoring parameters have been identified using the literature survey and Delphi method. Further, real-time data has been analyzed using MOORA, reference point and multi-MOORA methods. Taguchi and full factorial design of experiment (DOE) are used to investigate critical parameters for fleet performance monitoring.
Findings
Fleet performance monitoring is done based on fuel consumption (FC), CO2 emission (CE), coolant temperature (CT), fleet rating, revenue generation (RG), fleet utilization, total weight and ambient temperature. MOORA, reference point and multi-MOORA methods suggested the common best alternative for a particular category of the fleet (compact, hatchback and sedan). FC and RG are the critical parameters for monitoring the fleet performance.
Research limitations/implications
The geographical aspects have not been considered for this study.
Practical implications
A pilot run of 300 fleets shows saving of Rs. 2,611,013/- (US$36,264.065), which comprises total maintenance cost [Rs. 1,749,033/- (US$24,292.125)] and FC cost [Rs. 861,980/- (US$11,971.94)] annually.
Social implications
Reduction in CE (4.83%) creates a positive impact on human health. The reduction in the breakdown maintenance of fleet improves the reliability of fleet services.
Originality/value
This study investigates the most useful parameters for fleet management are FC, CE, CT. Taguchi DOE and full factorial DOE have identified FC and RG as a most critical parameters for fleet health/performance monitoring.
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Fazleena Badurdeen, Mohannad Shuaib, Ken Wijekoon, Adam Brown, William Faulkner, Joseph Amundson, I.S. Jawahir, Thomas J. Goldsby, Deepak Iyengar and Brench Boden
Globally expanding supply chains (SCs) have grown in complexity increasing the nature and magnitude of risks companies are exposed to. Effective methods to identify, model and…
Abstract
Purpose
Globally expanding supply chains (SCs) have grown in complexity increasing the nature and magnitude of risks companies are exposed to. Effective methods to identify, model and analyze these risks are needed. Risk events often influence each other and rarely act independently. The SC risk management practices currently used are mostly qualitative in nature and are unable to fully capture this interdependent influence of risks. The purpose of this paper is to present a methodology and tool developed for multi-tier SC risk modeling and analysis.
Design/methodology/approach
SC risk taxonomy is developed to identify and document all potential risks in SCs and a risk network map that captures the interdependencies between risks is presented. A Bayesian Theory-based approach, that is capable of analyzing the conditional relationships between events, is used to develop the methodology to assess the influence of risks on SC performance
Findings
Application of the methodology to an industry case study for validation reveals the usefulness of the Bayesian Theory-based approach and the tool developed. Back propagation to identify root causes and sensitivity of risk events in multi-tier SCs is discussed.
Practical implications
SC risk management has grown in significance over the past decade. However, the methods used to model and analyze these risks by practitioners is still limited to basic qualitative approaches that cannot account for the interdependent effect of risk events. The method presented in this paper and the tool developed demonstrates the potential of using Bayesian Belief Networks to comprehensively model and study the effects or SC risks. The taxonomy presented will also be very useful for managers as a reference guide to begin risk identification.
Originality/value
The taxonomy developed presents a comprehensive compilation of SC risks at organizational, industry, and external levels. A generic, customizable software tool developed to apply the Bayesian approach permits capturing risks and the influence of their interdependence to quantitatively model and analyze SC risks, which is lacking.
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Tanmay Nitin Mhatre, J.J. Thakkar and J. Maiti
The purpose of this paper is to employ an integrated approach of interpretive ranking process (IRP) and system dynamics (SD) for modelling the key risk factors for a typical…
Abstract
Purpose
The purpose of this paper is to employ an integrated approach of interpretive ranking process (IRP) and system dynamics (SD) for modelling the key risk factors for a typical construction project.
Design/methodology/approach
The risk parameters and performance measures applicable in the construction industry have been identified through extensive literature review and discussions with experts from the construction industry. Based on the literature review, a questionnaire was designed and 64 responses were considered. The list of 20 risk parameters and 32 performance measures relevant for a construction industry is reduced to five risk factors and five performance measure factors using factor analysis. IRP modelling is employed to examine the contextual relationships among risk factors and to rank them with respect to performance measure factors. Subsequently, the results of IRP model were utilised as inputs to SD analysis. The SD analysis is conducted for two models, namely, risk factor model and risk variable model to understand the impact of interventions offered by project management team on risk reduction and mitigation.
Findings
The developed IRP model shows that the risk factor dimension “construction management” has a high likeliness to occur during the construction phase.
Research limitations/implications
The research demonstrates an application of proposed approach for a typical construction environment and hence the results cannot be generalised.
Originality/value
This research addresses real life complexities in construction project by modelling critical risk factors using an integrate approach of IRP and SD. The proposed approach would facilitate project managers to devise appropriate risk mitigation strategies for a construction project.
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Berman Kayis and Putu Dana Karningsih
Risk identification is the first and crucial step in supply chain risk management process. Due to the nature and complexity of supply chain networks of manufacturing…
Abstract
Purpose
Risk identification is the first and crucial step in supply chain risk management process. Due to the nature and complexity of supply chain networks of manufacturing organizations, risk identification nowadays has become more challenging. The purpose of this paper to present the development of a tool, called Supply Chain Risk Identification System (SCRIS), for assisting decision makers in identifying existing risks, and the interrelationship of risks in supply chain (SC) network, by considering different process strategies, namely make to stock (MTS), make to order (MTO) and engineering to order (ETO).
Design/methodology/approach
SCRIS is developed using a knowledge‐based system (KBS) approach. The knowledge is represented in ruled based form and written using CLIPS expert system language program. To ensure its feasibility, SCRIS is validated using real case studies in several manufacturing industries.
Findings
Feedback gathered from organizations involved in validations processes imply the benefit of using SCRIS as a decision support tool in identifying SC risks. SCRIS also has additional positive role in supply chain risk management (SCRM) by promoting communication and collaboration between SC partners.
Originality/value
SCRIS provides an extensive tool using KBS approach which covers hundreds of SC risk sub‐factors, risk factors, and risk events, as well as mapping the interactions and considering different process strategies which have not been developed to date. A novel SC risks taxonomy is also proposed which encompasses broader issues in the SC network.
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Iqra Masroor and Jamshed Aslam Ansari
Compact and wideband antennas are the need of modern wireless systems that preferably work with compact, low-profile and easy-to-install devices that provide a wider coverage of…
Abstract
Purpose
Compact and wideband antennas are the need of modern wireless systems that preferably work with compact, low-profile and easy-to-install devices that provide a wider coverage of operating frequencies. The purpose of this paper is to propose a novel compact and ultrawideband (UWB) microstrip patch antenna intended for high frequency wireless applications.
Design/methodology/approach
A square microstrip patch antenna was initially modeled on finite element method-based electromagnetic simulation tool high frequency structure simulator. It was then loaded with a rectangular slit and Koch snowflake-shaped fractal notches for bandwidth enhancement. The fabricated prototype was tested by using vector network analyzer from Agilent Technologies, N5247A, Santa Clara, California, United States (US).
Findings
The designed Koch fractal patch antenna is highly compact with dimensions of 10 × 10 mm only and possesses UWB characteristics with multiple resonances in the operating band. The −10 dB measured impedance bandwidth was observed to be approximately 13.65 GHz in the frequency range (23.20–36.85 GHz).
Originality/value
Owing to its simple and compact structure, positive and substantial gain values, high radiation efficiency and stable radiation patterns throughout the frequency band of interest, the proposed antenna is a suitable candidate for high frequency wireless applications in the K (18–27 GHz) and Ka (26.5–40 GHz) microwave bands.
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Connie Zheng, Shazia Nauman and Nida Usman Jahangir
This study explores the under-researched phenomenon of workplace bullying against women in male-dominated Pakistani society, highlighting its severe impacts and bridging the…
Abstract
Purpose
This study explores the under-researched phenomenon of workplace bullying against women in male-dominated Pakistani society, highlighting its severe impacts and bridging the research gap on intersectional effects of gender and cultural dynamics in developing countries.
Design/methodology/approach
Using a mixed-method research approach, we conducted two-wave surveys with 308 female workers in Pakistan's educational and health sectors. Data analysis examined relationships between workplace bullying and job outcomes like productivity and satisfaction, complemented by insights from in-depth interviews with 18 female workers.
Findings
The study reveals that workplace bullying significantly undermines job productivity, increases emotional exhaustion mediated by job anxiety and decreases job satisfaction among female workers. Bullying persists due to weak institutions and inadequate law enforcement, with perceived social support found to be an insignificant moderator.
Practical implications
The study findings underscore the economic implications of workplace bullying, as it drives female workforce attrition, hindering economic development. The study recommends conflict resolution strategies, effective HR policies, national law enforcement and supportive social networks to combat bullying and create a conducive work environment.
Social implications
This study aligns with the UN's SDG goals #5 (gender equality) and #8 (decent work and economic growth), addressing pertinent issues related to workplace bullying in pursuit of these global objectives.
Originality/value
This study represents a unique attempt to address the intersectional dynamics of gender and culture concerning workplace bullying in Pakistan.