A hybrid neutrosophic-grey analytic hierarchy process method : decision-making modelling in uncertain environments

The analytic hierarchy process (AHP) is recognised as one of the most commonly applied methods in the multiple attribute decision-making (MADM) literature. In the AHP, encompassing uncertainty feature necessitates using suitable uncertainty theories, since dealing efficiently with uncertainty in subjective judgements is of great importance in real-world decision-making problems. The neutrosophic set (NS) theory and grey systems are two reliable uncertainty theories which can bring considerable benefits to uncertain decision-making. The aim of this study is to improve uncertain decision-making by incorporating advantages of the NS and grey systems theories with the AHP in investigating sustainability through agility readiness evaluation in large manufacturing plants. This study pioneers a combined neutrosophic-grey AHP (NG-AHP) method for uncertain decision-making modelling. The applicability of the hybrid NG-AHP method is shown in an illustrative real-case study for agility evaluations in the Iranian steel industry. The computational results indicate the effectiveness of the proposed method in adequately capturing uncertainty in the subjective judgements of decision makers. In addition, the results verify the significance of the research in group decision-making under uncertainty. The practical outcome reveals that, to become a more sustainable agile steel producer in the case country, they should first focus on the “organisation management agility” as the most significant criterion in the assessment followed by “manufacturing process agility,” “product design agility,” “integration of information system,” and “partnership formation capability,” respectively

Multiple criteria decision analysis under uncertainty in sustainable construction : a neutrosophic modified best-worst method

Capturing uncertainty in multiple criteria decision analysis (MCDA) is not a new theme but a largely developing topic which is in close connection with uncertainty theories such as fuzzy set and grey systems theories. Due to growing complexity of construction processes mainly because of implementation of sustainability aspects it would be necessary to take advantage of a novel MCDA methodology as an efficient tool to handle the uncertainty in sustainable construction decision making. In this study, we utilise a novel neutrosophic modified best-worst method (NM-BWM) to deal with the uncertainty in decision making in the context of sustainable construction. The method is an integration of neutrosophic set theory (NST) and the modified best-worst method (M-BWM). The NST can provide insights on efficient uncertainty handling of decision makers (DMs) subjective judgements. The BWM is a MCDA method which utilises two vectors of pairwise comparisons (the best criterion to others and others to the worst criterion) to obtain the weights of evaluation criteria. Merits of the BWM include its capability in effectively remedying the inconsistency derived from pairwise comparisons as well as simplicity and less pairwise comparisons compared to other similar methods like analytic hierarchy process (AHP). We show the applicability of the method in a case study with focus on the implementation of sustainable construction

A novel grey multi-objective binary linear programming model for risk assessment in supply chain management

Robust and resilient agri-food supply chain management (AFSCM) is paramount to agribusinesses, given the many challenges and risks that this increased demand will bring in the coming decades. Interruptions caused by various risks to this crucial supply chain network, particularly in emerging economies, can put the lives of millions in danger, not to mention creating devastating impacts on the economy and the environment. Even so, there are only a limited number of quantitative risk management studies in the AFSCM literature. In this study, an integrated modified risk mitigation matrix (M-RMM) is developed to analyze the mitigation strategies for dealing with various risks in the context of the agri-food supply chain. The M-RMM is integrated with the grey multi-objective binary linear programming (GMOBLP) model to obtain the optimal risk mitigation strategies related to the three objective functions of risk, cost, and time minimization. The proposed model is a useful tool for formulating sustainable business policies and reducing food waste, and acquiring a context-specific (i.e., a developing economy), sector-specific (i.e., the agri-food processing sector), and multi-product (i.e., fresh and non-perishable) approach. The findings reveal that continuous training and development and vulnerability analysis of IT systems are the most effective risk mitigation strategies to lessen the impacts of lack of skilled personnel, sub-standard leadership, failure in IT systems, insufficient capacity to produce quality products, and poor customer relationships. The findings assist practitioners in managing risks in supply chains

Understanding interdependencies among social sustainability evaluation criteria in an emerging economy

Organizations need to consider the triple bottom line (3BL) model of sustainability to maintain competitiveness in global markets. Of 3BL, environmental and economic sustainability pillars are more often discussed, as they are most directly related to a firm’s bottom line and regulatory compliance. Unfortunately, social sustainability receives relatively little attention even though it remains a significant threat to organizational sustainment, particularly in emerging economies. This study builds upon a social sustainability evaluation framework to investigate the interrelationships among social sustainability criteria in an effort to better understand how to improve social sustainability performance. A unique hybrid of interpretive structural modeling (ISM) and hesitant fuzzy matrix of cross impact multiplications applied to classification (HF-MICMAC) methodology is introduced and employed to determine the interrelationships (drivers and dependences) among social sustainability criteria. Then, a manufacturing company is used as the backdrop to test the efficacy of the expanded framework. The findings can aid industry decision-makers, especially in developing countries, to better understand and manage social issues, improve social dimension of sustainability, enhance the sustainability in operations and shift towards sustainable development

An artificial immune algorithm for ergonomic product classification using anthropometric measurements

© 2016 Elsevier Ltd Product classification using anthropometric measurements leads to ergonomic product design and user satisfaction. We propose an effective artificial immune algorithm (AIA) to classify ergonomic products with multi-criteria anthropometric measurements and tune the AIA parameters with a full factorial experimental design approach. We demonstrate the applicability and efficacy of the proposed algorithm by considering the anthropometric measurements of the hand, developing an ergonomic computer mouse, and classifying consumers into three categories. The resulting classifications are compared with expert opinions to facilitate the conformity of the computer mouse to user requirements

Unpacking critical success factors to improve supply chain effectiveness, efficiency and performance: a 7Vs framework for consideration

This paper seeks to guide supply chain managers regarding critical success factors (CSFs) by examining decision-making themes associated with effectiveness. It builds on previous theoretical and operational perspectives relating to CSFs for supply chain management. The research uses a quantitative survey instrument informed by responses from 303 supply chain decision makers. This enabled the identification of 7 key clusters from 48 variables which are directly linked to supply chain efficiency by applying Principal Component Analysis. CSFs are somewhat neglected in the supply chain literature and to address this, an evidence-based 7Vs framework is proposed, incorporating CSFs to aid the successful operation of supply chain performance. The results suggest that managing CSFs improves supply chain efficiency and performance, whilst assisting organisations in attaining a competitive advantage. This research takes a holistic view of organisations’ operational efficiency and contributes to the evidence base for successful operation of supply chains utilising CSFs

A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria

The best–worst method (BWM) is a multiple criteria decision-making (MCDM) method for evaluating ≤a set of alternatives based on a set of decision criteria where two vectors of pairwise comparisons are used to calculate the importance weight of decision criteria. The BWM is an efficient and mathematically sound method used to solve a wide range of MCDM problems by reducing the number of pairwise comparisons and identifying the inconsistencies derived from the comparison process. In spite of its simplicity and efficiency, the BWM does not consider the decision-makers’ (DMs’) confidence in their pairwise comparisons. We propose a neutrosophic enhancement to the original BWM by introducing two new parameters as the DMs’ confidence in the best-to-others preferences and the DMs’ confidence in the others-to-worst preferences. We present two real-world cases to illustrate the applicability of the proposed neutrosophic enhanced BWM (NE-BWM) by considering confidence rating levels of the DMs

A hierarchical reference-based know-why model for design support of sustainable building envelopes

In current complex building designs, sustainability assessments are often performed after project completion, with limited impact on building performance which results in missed goals in terms of quality, cost, and time. We address this problem by proposing a hierarchical reference-based know-why model to answer the research question “what is a suitable decision support model to successfully integrate the sustainability requirements in the early design phase of buildings?”. The model presents a process that incorporates a life-cycle perspective and calculates design alternatives based on a defined reference and the DGNB building certification system. The results show that criteria synergies and trade-offs can be identified, leading to improved design by engineers and better building performance. Our findings pave the way for full integration of the model into building information modeling, combined with artificial intelligence. This can help manage the complexity of the sustainable design process on the path to carbon-neutral buildings

Services procurement : a systematic literature review of practices and challenges

Organizations are paying greater attention to the potential advantages that can be achieved by adopting a more strategic approach to the procurement of services. Despite services being very different from physical items in many respects, and despite their outsourcing having achieved limited gains, the procurement of services remains under-researched. To address this challenge and develop a strategic platform for new directions in future research in the area, this paper undertakes a systematic literature review of 51 articles published in 21 peer-reviewed academic journals. It reviews the applicability of supply theories to services sourcing, and compares and demonstrates the distinctiveness of services purchasing through problematizing the literature reviewed. A descriptive and thematic analysis concluded that services procurement can be classified into seven research domains: ‘service production’, ‘governance’, ‘purchasing approach’, ‘supplier selection’, ‘performance management’, ‘the service triad’ and ‘specification of requirements’. We offer a comparative framework of the services procurement process and emphasize different supply practices. The provided research directions assist scholars in identifying avenues for integrating and expanding existing knowledge

Assessment of consumers' motivations to purchase a remanufactured product by applying Fuzzy Delphi method and single valued neutrosophic sets

© 2018 Elsevier Ltd Environmental issues have been worldwide matters of concern especially in the recent decade and have made many firms implement end-of-life strategies such as remanufacturing. In prior studies, the supply side of remanufacturing supply chain has been vastly brought into focus compared to the demand side. Motivational factors that encourage consumers to purchase remanufactured products are getting firms attentions in developing effective marketing strategies to assist them being more productive in the current competitive market. However, consumer acceptance of remanufactured products has been regarded as one of the main reasons why remanufacturing has remained a majorly untapped opportunity for improving supply chain productivity. This study aims at exploring the major motivational factors for buying a remanufactured bike based on the consumers' and experts' opinions. Firstly, twelve motivations identified by scrutinising the literature. Secondly, single valued trapezoidal neutrosophic numbers (SVTNN) and trapezoidal neutrosophic weighted arithmetic averaging (TNWAA) operator were employed to obtain seven significant motivations using the survey data collected from potential customers. This method is applied owing to its capability in capturing the uncertainty of consumers' subjective judgements. Thirdly, the resulted seven motivations are prioritised in accordance with the experts' judgements utilising a proposed modified fuzzy Delphi (FD) method. Ultimately, the most significant motivation to purchase a remanufactured bike identified as quality that suggests quality is the major factor affecting purchase decision of a remanufactured bike. It indicates remanufacturers should focus on quality and attempt to improve the quality of products to gain more competitive advantage. The other six factors that should be stressed by remanufacturer's marketing strategies are prioritised as warranty, price, information provision, remanufacturer's reputation, value-added services and retailer's reputation respectively