An integrated model for sustainable supplier selection and multi-period multi-product lot-sizing for packaging film industry in Iran

The emergence of sustainability issues has created increasing interest among those involved in the field of sustainable supply chain management. Companies are motivated to modify their supply chains activities based on sustainability issues to enhance their overall level of sustainability in order to fulfil demanding environmental and social legislation and to deal with increasing market forces from different stakeholder groups. Within supply chain activities, selecting appropriate suppliers based on the criteria of sustainability, e.g., economic, environmental, and societal might help companies move towards sustainable development. Although several studies have been accomplished to incorporate sustainability criteria into supplier selection problem, little attention has been paid to developing a comprehensive mathematical model that allocates the exact quantities of orders to suppliers considering lot-sizing problems. Moreover, the effect of inflation as an important issue for companies in the developing countries has been neglected in studies that examined multi-period multi-product lot-sizing along with supplier selection. In this study, a multi-objective mathematical model for sustainable supplier selection integrated with multi-period multi-product lot-sizing problem under the effects of inflation was developed. The model consists of four objective functions which are minimizing total cost, maximizing total social, total environmental score, and total economic qualitative scores. The mathematical model was developed based on the parameters discovered by preprocessing the social, environmental, and economic data of suppliers using a rule-based-weighted fuzzy approach and fuzzy analytical hierarchy process. The model attempted to simultaneously balance different costs under inflationary conditions to optimize the total cost of purchasing and other objective functions. A comprehensive framework was developed as a road map for procurement organizations in order to facilitate the allocation of optimal order quantities to suppliers in a sustainable supply chain. The proficiency and applicability of a proposed approach was illustrated using a case study of packaging films from the food industry. For each main criterion of sustainability, their related subcriteria and influencing factors were extracted from literature and the most related ones were selected by company’s experts. In this research, green competencies, environmental management system, pollution, occupational safety and health, training and education, contractual stakeholder, economic qualitative, and cost were selected by company’s experts as the main subcriteria of sustainable supplier selection. The consideration of sustainability criteria in the proposed multi-objective model revealed that a higher value of sustainable purchasing can be achieved in comparison with a single objective costbased model. In addition, the results show that the proposed model can provide a purchasing plan for the company while monitoring the effect of inflation and assuaging its concerns regarding sustainability issues

An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where traditional procedures are now transformed to sustainable initiatives. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attention of many scholars and industrial practitioners, which has not been comprehensively addressed. Therefore, a practical model of supplier selection and order allocation based on the sustainability Triple Bottom Line (TBL) approach is presented in this research article. The proposed approach utilizes Fuzzy Analytical Hierarchy Process combined with Quality Function Deployment (FAHP-QFD) for reflecting buyer’s sustainability requirements into the preference weights that are then exerted by an efficient Fuzzy Assessment Method (FAM) to assess the suppliers to obtain their sustainability scores. Thereupon, these scores are utilized in a fuzzy multi-objective mix-integer non-linear programming model (MINLP) for allocating orders to suppliers based on the manufacturer’s sustainability preference. A real-world application of food industry is presented to show the practicality of the proposed approach

Life Cycle-based Environmental Performance Indicator for the Coal-to-energy Supply Chain: A Chinese Case Application

Coal consumption and energy production (CCEP) has received increasing attention since coal-fired power plants play a dominant role in the power sector worldwide. In China, coal is expected to retain its primary energy position over the next few decades. However, a large share of CO2 emissions and other environmental hazards, such as SO2 and NOx, are attributed to coal consumption. Therefore, understanding the environmental implications of the life cycle of coal from its production in coal mines to its consumption at coal-fired power plants is an essential task. Evaluation of such environmental burdens can be conducted using the life cycle assessment (LCA) tool. The main issues with the traditional LCA results are the lack of a numerical magnitude associated with the performance level of the obtained environmental burden values and the inherent uncertainty associated with the output results. This issue was addressed in this research by integrating the traditional LCA methodology with a weighted fuzzy inference system model, which is applied to a Chinese coal-to-energy supply chain system to demonstrate its applicability and effectiveness. Regarding the coal-to-energy supply chain under investigation, the CCEP environmental performance has been determined as “medium performance”, with an indicator score of 39.15%. Accordingly, the decision makers suggested additional scenarios (redesign, equipment replacement, etc.) to improve the performance. A scenario-based analysis was designed to identify alternative paths to mitigate the environmental impact of the coal-to-energy supply chain. Finally, limitations and possible future work are discussed, and the conclusions are presented

Sustainable humanitarian supply chains: a systematic literature review and research propositions

The purpose of this systematic review is to synthesise the body of knowledge related to sustainable humanitarian supply chains across disaster relief as well as those of logistics of development aid. The output of this paper is a set of research propositions that will help advance theory building and validation for the management of sustainable humanitarian supply chains. This systematic review identifies and categorises sustainable humanitarian supply chain management (SHSCM) themes, with a particular emphasis on theoretical development based on a categorical analysis of research articles. The thematic analysis reveals that sustainability in humanitarian supply chains encompasses a wide range of aspects, such as supply network configuration, coordination, and partnership, as well as performance measurement. However, theoretical studies typically do not integrate all sustainability dimensions. In particular, social sustainability factors are largely absent from current models of SHSCM, despite their inherent significance in humanitarian contexts. The categorical analysis explains how aspects related to the identified themes impact and pose opportunities for SHSCM. Insights from this systematic review can support humanitarian supply chain sustainability knowledge with policy-driven research directions. These policies can help achieve a greater level of sustainability in humanitarian supply chain management. The originality of this study lies in the development of detailed categories of sustainability studies, in its analytical focus on SHSCM theories, and in the development of research propositions to provide insights to researchers on how to advance theory and conduct impactful research on the topic of SHSCM

Burden of pediatric asthma in Kurdistan Province, West of Iran

BACKGROUND: Asthma is the most common chronic respiratory disease (CRD) and one of the most serious and important pediatric diseases in developing countries. The present study aims to estimate the burden of asthma among children in Kurdistan Province, Iran.METHODS: Disability-adjusted life year (DALY) was used in order to estimate the burden of asthma. In a cross-sectional study, with a sample size of 4000, and using the multi-stage sampling method and Asthma and Allergies in Childhood (ISAAC) questionnaire, the prevalence of asthma was estimated for two 6-7 and 13-14 age groups in Kurdistan Province in 2013. In addition, some necessary data were extracted from the death registration system in Kurdistan Provincial Health Center and Statistical Center of Iran (SCI).RESULTS: Burden of asthma for 6-7 age group was 71.6 DALYs in boys (2.77 DALYs per 1000 population) and 48 in girls (2.22 DALYs per 1000 population) with a total burden of 119.6 DALYs (2.52 DALYs per 1000 population). Moreover, its burden for 13-14 age group was 121.1 DALYs in boys (4.86 DALYs per 1000 population) and 82.3 in girls (3.98 DALYs per 1000 population) with a total burden of 203.4 DALYs (4.46 DALYs per 1000 population).CONCLUSION: Considering the significant prevalence of asthma and its burden among children in Kurdistan Province, it is suggested that prevention and management of this disease be considered as a priority by policy makers and in health programs, in addition to attempting to prevent and reduce its burden by setting out effective interventions

Sustainable Supplier Selection based on Self-organizing Map Neural Network and Multi Criteria Decision Making Approaches

Due to increasing public awareness, government regulation and market pressure on sustainability issues, companies have found out that in order to have a competitive edge, sustainable operational activities should be adopted with their supply chain. Sustainable supplier selection as a crucial decision can affect the overall degree of sustainability in a supply chain. In this paper, an integrated approach of clustering and multi criteria decision making methods have been proposed in order to solve sustainable supplier selection problem. Firstly, self- organizing map as one of the well-known neural network methods has been utilized in order to cluster and prequalify the suppliers based on customer demand attribute and sustainability elements. Then, multi criteria decision making methods will be utilized in order to rank the cluster of suppliers to make coordination between them and customers. A case study has been carried out in order to show the efficiency of proposed approach

Electric vehicles lithium-ion batteries reverse logistics implementation barriers analysis: A TISM-MICMAC approach

End of life (EoL) management of the electric vehicles lithium-ion batteries (EVs-LIBs) has become a vital part of circular economy practices, especially in the European Union (EU). Consequently, manufacturers must develop EoL management of EVs-LIBs through reverse logistics (RLs) activities, which are bounded with many implementation barriers. Although several studies have been accomplished for RLs barrier analysis in various industries, less attention has been devoted to identifying and systematically analysing barriers of EVs-LIBs RLs. The purpose of this study is to identify a comprehensive list of the main barriers to the successful implementation of EVs-LIBs RLs practices. Based on the inputs from European industrial experts, an integrated approach of Total Interpretive Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) was applied to develop a hierarchical model based on the defined barrier categories. Finally, the most dominant barrier categories to the successful implementation of RLs activities for EVs-LIBs were prioritised to provide insights to industrial decision-makers and policymakers. Data were gathered using a questionnaire survey, which was distributed to various experts in EVs-LIBs manufacturing/recycling and EVs manufacturing companies. The findings revealed that ‘market and social’, and ‘policy and regulations’ categories are the two most influencing barriers to the implementation of EVs-LIBs RLs. This study lays the foundation for future research on the RLs activities for EVs-LIBs in a time that EU regulations on the circular economy are mandating all auto manufacturing companies to deal with their EoL wastes

A hybrid model of data mining and MCDM methods for estimating customer lifetime value

The 41st International Conference on Computers and Industrial Engineering (CIE41), Los Angeles, United States of America, 23-26 2011Due to competitive environment, companies want to create a long-term relationship with their customers throughout customer relationship management (CRM). Building effective customer relationship management, companies should estimate customer lifetime value (CLV). CLV is normally calculated in terms of recency, frequency and monetary (RFM) variables. In this paper, a model for estimating CLV based on RFM variables integrated with data mining and multi criteria decision making (MCDM) methods has been proposed. The proposed methodology contains three phases in which Fuzzy Analytical Hierarchy Process (FAHP) has been used to determine RFM variables' weights. Then, Kmeans clustering method was employed in order to customer clustering and segmentation. Customer clusters were then ranked using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Finally, the proficiency of the model was shown by conducting a case study of cosmetics industry

A comprehensive performance measurement framework for business incubation centres: Empirical evidence in an Irish context

During the last 20 years, there has been an increased interest among academics and practitioners in the area of business incubation. However, limited attention has been devoted to developing a comprehensive framework that can measure business incubators' performances. Therefore, there is an urgent need for an appropriate, robust and useable performance framework. In this paper, we present a comprehensive framework using a weighted fuzzy inference system for business incubation centres' (BIC) performance measurement. The proposed approach utilises the input of a Delphi panel to identify criteria and subcriteria. Then a fuzzy analytic hierarchy process is used to weigh the criteria. Subsequently, a weighted fuzzy inference system is developed and applied to provide results based on the identified criteria and subcriteria. To show the proficiency and applicability of the proposed framework, a case study of Irish BICs is applied. The comprehensive performance measurement framework presented in this paper provides for accurate evaluation and monitoring across six criteria. The six criteria are facilities and infrastructure; clients; networking and marketing; products and services; finance; and human capital. The results show that although most of the BICs focus on facilities and infrastructure, there is a need to concentrate more on factors such as networking, marketing and finance. The detailed approach presented in this paper can be used by academics and practitioners who wish to apply fuzzy inference systems to performance measurement. In addition, the results from our pilot can be used by BIC managers and policymakers to improve performance

A weighted fuzzy approach for green marketing risk assessment: Empirical evidence from dairy industry

The green marketing concept encompasses the consumers' perception and response to the green initiatives and activities that companies implement such as design for environment, green production systems and processes development, and green improvements in packaging. Despite the growing interest in the green marketing domain, few studies have been carried out on the risk assessment of green marketing implementation, especially in the dairy industry. In this study, using a developed integrated fuzzy decision-making methodology, the green marketing risk factors in the dairy industry are assessed. Firstly, the fuzzy analytic hierarchy process is used for weighting the identified risk assessment criteria. Then, a weighted fuzzy inference system is proposed for green marketing risk assessment. Finally, risk mitigation strategies are proposed to deal with the highly ranked risk factors. This research study fills the gaps in the literature by (1) proposing a comprehensive list of green marketing risk factors in the dairy industry, (2) developing a novel weighted fuzzy inference system approach for assessing those risk factors, and (3) providing a final ranking of the dairy industry risk factors together with risk mitigation strategies for the highly ranked risk factors. The level of environmental awareness in society was found as the most important risk factor followed by governmental policies, rules, and regulations for supporting green products risk factors. Finally, some remarks are concluded together with presenting the future works