Identification and analysis of the driving factors for product modularity by Interpretive Structural Modelling

Goal: The purpose of this study is to identify the driving factors that affects modular product design and development and to determine the contextual relationships between the identified factors. Design / Methodology / Approach: This research study adopted both qualitative and quantitative methodologies. In qualitative part, an extensive literature review is conducted along with interviews with the experts experienced in product design and development in order to identify and sorted out the driving factors for product modularity. In quantitative part, all the identified factors were analyzed through Interpretive Structural Modeling (ISM) method. MICMAC (Matrice d'Impacts Croisés Multiplication Appliquéeáun Classement (cross-impact matrix multiplication applied to classification) analysis is carried out to determine the relative driving and dependency power of the factors. Results: The contribution of this paper is the identification of the factors associated with developing a modular product. Through the use of ISM diagraph, the identified factors were clustered into different layers based on their driving and dependency characteristics. The ISM diagram also presented the relationship between one factor over others and the reason for such relationship. Such a diagram offers decision maker better visibility on the factor that they need to consider or strategy they need to implement to improve their modular product design and development architecture. The results from this research study encompass organizational managers for handling multiple design views, controlling design related interfaces and ranking the status and progress of product modularity and design completeness. Practical implications: The study outcomes support product designers to optimize their product development processes, especially to develop modular products. The presented methodology can be used extensively used by the product designers/planners/managers to find the driving factors related to modular product design and development. Originality / Value: The originality of this research study is to deploy the ISM approach, which can be used by the organizational managers and/or product designers to plan product development strategies. Such strategies help to them to make necessary decisions on resources allocations. Limitations of the investigation: The outcomes from this research may not be generalize sufficiently due to subjectivity of the interviewers.© 2020 Brazilian Association of Production Engineering (ABEPRO). This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Influence of circular economy phenomenon to fulfil global sustainable development goal:Perspective from Bangladesh

This paper highlights the extent of the relationships between circular economy (CE) practices and the implementation of the United Nations Sustainable Development Goals (SDGs). Specifically, the paper takes part in academic debates regarding CE and SDGs. It qualitatively investigates national governments’ policy response and practices, with a focus on Bangladesh. The study finds varying degrees of momentum in the national policy response to SDGs and thus, it answers two research questions: (i) what is the relevance of CE practices to the United Nations (UN) SDGs? (ii) What are the responses from the Bangladeshi government to fulfil the UN SDGs regarding sustainable consumption and production with CE? As CE is a global trend, the research suggests that broad, conscientious connection and collaboration at the national level are essential. The findings implicate national governments in developing countries and UN SDGs for their policies and programme reassessment, considering the impact of the COVID-19 pandemic on sustainable development.© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Application of fuzzy TOPSIS framework for selecting complex project in a case company

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.© 2021, Ahm Shamsuzzoha, Sujan Piya and Mohammad Shamsuzzaman. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcodefi=vertaisarvioitu|en=peerReviewed

An approach for analysing supply chain complexity drivers through interpretive structural modelling

Today’s greater product variety, shorter product life cycle, and lower production costs are pushing companies to look beyond their own boundaries, thereby, creating complexity in the management of the supply chain. To manage such complexity, it is imperative that the management understand the associated complexity drivers and their interrelationships. This study identified twenty-three drivers responsible for supply chain complexity and classified them by using various criteria. In addition, the study presents a structural model using interpretive structural modelling (ISM) methodology to understand the inter-relationships between one driver to another. The research findings showed that drivers such as customer need, competitor action, and government regulation are beyond the control of supply chain partners, and have found the highest dominance with respect to supply chain complexity. Conversely, drivers related to tactical issues such as production planning and control, logistics and transportation, forecasting error, and marketing and sales are found to be the dependent drivers. Remaining drivers, such as company culture, number of suppliers, product variety, and organizational structure fall between the former two classifications. These drivers are related to strategic issues and require action from the upper level of the management hierarchy.fi=vertaisarvioitu|en=peerReviewed

Heuristic methods for the periodic Shipper Lane Selection Problem in transportation auctions

none3siopenTriki, Chefi; Mirmohammadsadeghi, Seyedmehdi; Piya, SujanTriki, Chefi; Mirmohammadsadeghi, Seyedmehdi; Piya, Suja

Optimization Modeling of a Poultry Industry Supply Chain Network

Supply chain management is an asset to every industry globally due to its positive outcomes such as faster response time, reduction of unwanted inventory and lower sales costs with enhanced customer service. It is therefore important to focus on improving the supply chain network of any industry. The objective of this research study is to model a supply chain network for poultry Industry in Oman. The study analyzes the existing supply chain network within a poultry industry and recommended its improvement based on the identified factors while giving more emphasis on the routing and distribution network aspects of supply chain. The recommendation, in the form of optimization model, is verified and validated using Lingo optimization software. Also, heuristic method is proposed and tested to overcome the complexity of optimization model

Modular product architecture to manage product development complexity

Shorter product life cycles, together with heterogeneous market demands, are forcing manufacturing companies to eliminate or reduce complexities in product development and supply chain. These complexities arise due to high level of interdependencies between component interfaces and supply chain participants. To address such complexities, companies need to focus on their product architecture and supply chain design. In this research, the impact of product architecture on developing modular products is highlighted. This modular principle is elaborated with the objective to reduce product development complexities. A case example is presented to define the importance of product architecture with the help of a design structure matrix (DSM) tool to reduce product development complexity. In addition, various drivers responsible for supply chain complexities are identified and categorised, and the relationship between product architecture and supply chain complexities are defined within the scope of this research.fi=vertaisarvioitu|en=peerReviewed

Integrated analytical hierarchy process and grey relational analysis approach to measure supply chain complexity

Purpose – The purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC). Design/Methodology/Approach of the paper – Through extensive literature review, we discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study. Findings – We identified twenty-two drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing, and company culture. Originality/Value – In this paper, we propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors’ knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.© 2020 Emerald Publishing Limited. This manuscript version is made available under the Creative Commons Attribution–NonCommercial 4.0 International (CC BY–NC 4.0) license, https://creativecommons.org/licenses/by-nc/4.0/fi=vertaisarvioitu|en=peerReviewed

Supply Chain Complexity Drivers and Solution Methods

Increased globalization, shorter product life cycle and rapid technological advancement in the manufacturing as well as service companies necessitates the company to have multiple supply chain partners. The partnership may be physical or virtual, thus making the chain more challenging and complex to manage. Therefore, the present supply chain network is characterized by its complexity, which requires proper management and strategy for its mitigation. In addition, the dynamic world in this complex supply chain system demands the manager to make faster and efficient decision. To manage the overall supply chain complexity and to make an efficient decision it is important that the manager understand the associated complex interactions within a supply chain, as well as, proper solution method or strategy to mitigate them. In this paper, a generic supply chain complexity drivers are identified and proposed solutions methods to manage the complexity in supply chain

Integrated Fuzzy AHP-TOPSIS Method to Analyze Green Management Practice in Hospitality Industry in the Sultanate of Oman

Climate change is the most serious threat that the modern world has ever faced. This has led to increasing attention from the government, industries, researchers, and practitioners on the theme of green practice. Due to the heightened awareness of climate change, the hospitality industry is under pressure to implement green practices and reduce the environmental impact of their operation. The research aims at understanding the indicators that define green practice in the hospitality industry and then developing a model that can be used to measure the green score. The research identifies twenty-six indicators of green practice in the hotel industry. These indicators were clustered into six different criteria. Based on the identified indicators and criteria, an integrated fuzzy AHP-TOPSIS method is proposed to calculate the green score. The fuzzy AHP method is used to calculate the weight of the criteria and indicators, while the fuzzy TOPSIS method is used to calculate the green score and rank hotels. The fuzzy AHP result shows that the criterion “Recycling and Reuse” has the highest weight among the identified criteria, while “Green Training and Incentives” has the lowest weight. The application of the proposed method is demonstrated by using a case study of hotels situated in the Sultanate of Oman. The result shows that the 4-star and 5-star hotels in the Sultanate have green scores between 0.56 and 0.641 out of 1.0 at a 95% confidence interval. The results further show that having a high star ranking hotel does not necessarily mean that the hotel is better in terms of green practice. The developed model helps the hotel industry to understand the indicator and criteria, as identified in this research work, they need to improve in order to improve their overall green management practice.© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed