International Journal of Supply and Operations Management
Volume:10 Issue: 1, Winter 2023

During natural disasters, emergency sections try to find the best way to serve defective points and gradually find the optimal location of these service points as blood collection centers in safe areas to restore the system to its previous state. This research proposed a multi-objective mathematical model for the design of a four echelon comprehensive Blood Supply Chain (BSC) network in earthquakes. Here, the impact of the Earthquake Destruction Radius (EDR) on the BSC network and blood group compatibility have been considered simultaneously.In order to be more realistic the effect of multimodal capacitated transportation vehicles accompanied with lateral transshipment have been investigated. In our proposed model four multi-objective decision-making (MODM) methods, as well as the augmented ε-constraint method is adopted for finding Pareto optimal solutions. Finally, the validation of the problem has been explored by Bounded Objective Method (BOM). This model has been implemented based on the real data of Tehran; the capital of Iran; as one of the volunteer cities for tremendous earthquake in the world.

Ascertaining and prioritising the various factors that can influence the performance of a supply chain system is vital towards creating measures that are tailored towards controlling these factors, in order to ensure a sustainable supply chain. This research subject matter has been solved in the literature using multi-criteria decision making techniques, whose prioritization solutions are generated using experts opinions, which are subjective, thereby decision obtained could be prone to biases. In light of this, this study present an Hierarchical Structural Interaction Matrix (HSIM) approach, whose prioritisation computation is premised on the theory of subordination derived via systems thinking, to prioritize various factors influencing the performance of a supply chain system. In order to achieve this, firstly, all the factors that could influence the performance of a supply chain system were identified from the literature. Thereafter, a Binary Interaction Matrix, which unveil the arrays of subordinations that exist amidst a number of the identified factors was developed. The result of this exercise was thereafter numerically analysed using appropriate mathematical equations to determine the intensity rating score of each supply chain performance factor. Furthermore, Pareto analysis was conducted using the latter results, to unveil the vital few factors that could influence the performance of a supply chain system used in an organisation. The result of the study unveiled that supply chain performance of an organisation can be exponentially improved, if supply chain managers can focus and concentrate their management efforts more on 11 critical factors obtained from the prioritisation analyses.

In this paper, we investigate an integrated procurement and capacitated vehicle routing problem for the distribution of multiple relief goods after the disaster, to determine the best tour for vehicles as well as the best selection of multiple relief goods and their quantity to be loaded on vehicles. Due to the uncertain nature of the parameters, the demand distribution and cost parameters are considered as fuzzy parameters. Furthermore, this paper examines the impact of information and communication technology in the affected areas so that instant information, communicate between the affected areas and the disaster coordination center due to new events caused by the disaster. We have examined the impact of information and communication technology on reducing demand uncertainty such that with consideration of the cost of equipping GPS in affected areas, as well as its impact on reducing demand uncertainty and the cost of dissatisfaction as a result; the best affected areas are selected to be equipped with GPS. To have robust solutions, a robust possibilistic programming model is proposed. The results of the model are shown in a real case study in district 7 of Tehran which acclaim that the proposed model achieves a better result than the traditional models without considering ICT.

Organisations are attempting to make their supply chain eco-friendly due to rising carbon emissions and unsustainable use of natural resources. In this context, this study seeks to give an up-to-date literature review on green supply chain management (GSCM) from 2011 to December 2021. Initially, 375 articles were collected from the Web of Science (WoS) database for metadata analysis. In metadata analysis, the descriptive statistics of research trends of GSCM; most contributing authors, countries/regions and institutions; and most prominent journals, keywords and subject areas are discussed in detail. Later, 50 scholarly publications were selected according to their citations for content analysis. Based on their contents, the papers were classified into four categories: GSCM practices and performances, mathematical techniques, drivers and barriers of GSCM, and general articles related to GSCM. According to the in-depth analysis, most of the publications are theoretical works that contribute to the theory-building of GSCM. Likewise, mathematical techniques are gaining appeal among researchers, whereas research on drivers and barriers is limited. In articles regarding GSCM practices and performance, the structural equation modelling methodology was often employed. The results and future research directions presented may assist beginners in exploring new GSCM research domains.

One of the most important issues in smart cities is recognizing the factors that affect the success of services in smart cities. The purpose of this study is to provide a model for the success of services in smart cities based on information and communication technology and to identify its indicators. In this research, data collection has been done from the method of library studies and field studies, during which the factors affecting the success of services in smart cities have been identified. These factors include: smart economy, smart citizens, smart governance, smart transportation, smart environment and smart living. After that, a research questionnaire was designed and distributed. At this stage, by fuzzy Delphi method, the indicators related to the identified factors were also identified. In the next step, using the structural equations and Smart PLS software, the effect of research factors on the main component of research (success of services in smart cities based on information and communication technology) was evaluated. The results show that all factors have a significant and positive impact on the success of services in smart cities and government actions to create a smart city have the greatest impact on the success of services in smart cities based on information and communication technology.

Model-based approaches remain an important option for modelling customer demand. While this approach allows to analyse demand using a model based on theoretical arguments, each choice of model is associated with specific  assumptions under which this model is valid. Customer demand in retail is typically modelled as a Poison-type process, in particular using a negative binomial distribution. Poisson-type processes are associated with an exponential inter-arrival time that describes the probability distribution between subsequent events. Using a public dataset from a large  supermarket, the analysis of the data shows that while the general assumption of a Poisson process is reasonable, the purchasing behaviour strongly depends on the type of product. Additionally, customers in this supermarket show astrong preference for a weekly shopping trip.

New dynamics in consumer behavior demand a review of methods for the provenance of consumer products, especially the evolution of supply chains in the mining and manufacturing industry. This phenomenon has intrigued academic and corporate communities to foster research in supply chain sustainability. Globalization has introduced complexities to the traditional implementation of mining supply chain networks that require quantification within a unified framework for commensurable qualitative analysis. Irrespective of valuable opportunity presented by the mining industry to benefit national economies and local communities, there are still however, environmental, and social impacts that beseech a global heed. A more systemic approach to conceptualize within the context of developing assessment tools is imperative. This study investigates the effects of globalization on supply chain networks, while leveraging the Triple Bottom Line (TBL) theory to determine relationships with various sustainability dimensions as well as proposes a practical mathematical model to estimate the impact of globalization on the mining supply chain networks. The developed model is validated against measures of gross domestic products (GDP) per capita. However, findings suggest that a determination of the impact of globalization on mining supply chain sustainability cannot exclusively peg with the GDP.