Search Results (20)

Background/Objectives: The COVID-19 pandemic has profoundly impacted healthcare systems worldwide, including the delivery of ophthalmic emergency services. This study examines the impact of the COVID-19 pandemic on the clinical presentation of emergencies and the accessibility of healthcare in ophthalmology. Methods: The study employed a single-center, consecutive case series design with historical controls to examine electronic health records over a 21-day period during the COVID-19 pandemic and a matched period from the preceding year. Records were analyzed for demographic variables, diagnosis, length of stay, travel distance, and referral status. The urgency of cases was evaluated by three independent graders using the BaSe SCOrE (BAsic SEverity Score for Common OculaR Emergencies). Results: A total of 1229 patients were included in the study, with 786 patients in the 2019 cohort and 443 patients in the 2020 cohort. During the pandemic period, there was a significant decrease in the number of patients and the duration of their visits (p < 0.0001, p < 0.0001, respectively). There was an increase in walk-in patients (p = 0.03), who took significantly longer journeys to be treated as compared to referred patients (p < 0.01). At the same time, the severity of emergencies increased (p = 0.02). The 2019 logistic regression model found that age (p = 0.003), referral status (p < 0.001), distance (p = 0.009), and first presentation (p = 0.02) were significant predictors of the severity, while gender was not (p = 0.78). The 2020 model found that only age (p < 0.001) and referral status (p < 0.001) were significant predictors of severity. Conclusions: The observed decline in patient volume, increased severity of emergencies, and shifts in predictive variables within the logistic regression models are indicative of significant barriers to healthcare access. Therefore, enhancing health literacy and ensuring low-threshold access to emergency services are crucial, especially during crises. Full article

As Khanh Hoa Sanest Soft Drink Joint Stock Company attempts to satisfy consumer requirements and maintain market share in the salangane nest industry, it is important to monitor the efficiency of its supply chain (SC). This paper identified metrics to evaluate the firm’s SC performance, using secondary data from firm records, primary data from a survey of 200 sales agents, and the Supply Chain Operations Reference (SCOR) model. Production records revealed a manufacturing lead time of 11 days and a production time of 24 h plus 7 days for refrigeration and observation. Order fulfillment delivery times ranged from 13 to 16 days. About 86.0 percent of customers rated the product as good or very good, and 60.5 percent claimed benefits from consuming the product. SC management costs of goods sold were 75.27% of total costs, while production cost was 41.99% of total costs. Total assets increased 16.6% from 2019 to 2021, but profits declined by 32.9% for the same period, while return on assets fell 42.4%. To maintain a competitive advantage, the company should apply information technology to improve SC performance. The results showed that the SCOR model is appropriate for evaluating the performance of this firm and similar business enterprises. Full article

The upstream segment of the minerals supply chain (MiSC) is the backbone for achieving the transition to clean energy by securing the supply of minerals. Recently, the MiSC has been disrupted, affecting mineral supply and generating uncertainty among clean energy producers. Supply chain (SC) mapping addresses this uncertainty, providing a holistic end-to-end view. However, MiSC mapping studies mainly focus on the downstream segment, leaving aside the upstream segment. In this context, the fundamental gap is the lack of standardized modelling frameworks that can accurately represent the upstream segment dynamics and, at the same time, seamlessly integrate with the downstream segment. This paper bridges this gap, designing a model for the MiSC upstream segment (MiSCOR). Framed within design science research methodology, MiSCOR is built by adapting two reference models, the Exploration and Mining Business Reference Model (EM) and the Supply Chain Operations Reference Model (SCOR), focusing on the commodity-making process. The MiSCOR demonstrates its applicability and robustness in real operational scenarios of one of the largest copper producers. MiSCOR provides a management tool for practitioners and decision-makers in the MISC’s upstream segment, offering blueprints to throw functional silos, foster collaboration, and a standardized framework that integrates seamlessly with the downstream segment. Full article

Background: Supply chain performance measurement is an integral part of supply chain management today, as it makes many critical contributions to supply chains, especially for companies and supply chains to identify potential problems and improvement fields, evaluate the efficiency of processes, and enhance the health and success of supply chains. The purpose of this study is to contribute to future research and practical applications by presenting a more standard, comprehensive, and up-to-date measurement scale developed based on the SCOR model version 13.0 performance measures in the disruptive technology era. Methods: The study was performed in seven stages and the sample size consists of 227 companies for pilot data and 452 companies for the main data. The stages comprise item generation and purification, exploratory factor analysis for the pilot study and main study, confirmatory factor analysis for the main study, convergent, discriminant, and nomological validity appraisal, and investigation of bias effect. Results: The scale was developed and validated as a five-factor and thirty-one item structure. Conclusions: Some key trends and indicators must be followed today to perceive the landscape of future supply chains. This measurement scale closely follows the future supply chains. Additionally, the findings have been confirmed by the contributions of disruptive technologies and the conceptual structure of supply chain management. Full article

Background: The passage from pre-adolescence to adolescence is presented as a turning point for the achievement of those abilities in social understanding as they commonly appear in adulthood. Developmental perspectives point to the possible role of neuro-cognitive maturation and social experiences to facilitate this growth. This paper has the goal to goalsto propose a valid and reliable measure of the new quantitative and qualitative advancements in social understanding occurring in the adolescent passage; relying on this, the research has two main objectives (a) to establish the associations between the advancements in social understanding and the executive functions held responsible for the neuro-cognitive rearrangements of adolescence; (c) to evidence the significant associations between attachment models and the development of social understanding in this phase of life. Methods: 100 subjects (50 boys and 50 girls, aged 11–15) were administered with AICA, SCORS, CNT, Stroop Color-Word Test, and WISC-III. Results: Advancements in the complexity of self–other representations and mentalization of interpersonal exchanges significantly occurs in the passage from pre-adolescence to adolescence and seem to be promoted by increased performances in executive control and cognitive shifting. Dismissing state of mind with respect to attachment is associated with lower development of social understanding in adolescence. The neurocognitive reorganization that underlies the passage from pre-adolescence to adolescence seems to provide the scaffolding for more sophisticated interpretations of the social world. Past and current affective experience can boost or hinder the full deployment of such human maturational potential. Given the importance of social cognition for adjustment and psychopathology, clinical intervention should target the amelioration of individual and family abilities in social reasoning and mentalization. Full article

People with type 1 diabetes require insulin, a lifesaving and essential medication, to maintain their blood sugar levels below dangerous levels. Unfortunately, the insulin industry faces supply and affordability issues, and patients and their families face an enormous burden. As a result of high prices and lack of availability, individuals are turning to other options for purchasing insulin, such as online pharmacies, which may or may not be legitimate. Despite the necessity of safe insulin for diabetics in the legitimate Pharmaceutical Supply Chain (PSC), few researchers have considered implementing strategies to maximize patient safety for purchasing insulin. Therefore, the current research seeks to bridge this gap and provide cohesive information on overcoming this challenge and maximizing insulin safety. This study employs a Multi-Criteria Decision-Making (MCDM) model that combines Supply Chain Operations Reference (SCOR) metrics, Analytic Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a model that can prioritize and select the best criteria for maximizing insulin safety and achieving the study objective. A comparison of two insulin supply chain scenarios was performed. As a result of this research, adding a traceability technology to the insulin supply chain, specifically blockchain (T42) in scenario 2 provides the best results to the supply chain for maximizing and ensuring the safety of insulin, as compared to scenario 1, where the final score achieved almost 71%. This research provides a useful tool for assessing the safety of other critical goods that customers value in strategic and complex decision-making. Academics, professionals, and decision-makers can benefit from this research using a rigorous scientific decision-support system. Full article

This work is a unique integration of three different areas, including smart eye status monitoring, supply chain operations reference (SCOR), and system dynamics, to explore the dynamics of the supply chain network of smart eye/vision monitoring systems. Chronic eye diseases such as glaucoma affect millions of individuals worldwide and, if left untreated, can lead to irreversible vision loss. Nearly half of the affected population is unaware of the condition and can be informed with frequent, accessible eye/vision tests. Tonometry is the conventional clinical method used in healthcare settings to determine the intraocular pressure (IOP) level for evaluating the risk of glaucoma. There are currently very few (under development) non-contact and non-invasive methods using smartphones to determine the risk of IOP and/or the existence of other eye-related diseases conveniently at home. With the overall goal of improving health, well-being, and sustainability, this paper proposes Eye-SCOR: a supply chain operations reference (SCOR)-based framework to evaluate the effectiveness of smartphone-based eye status monitoring apps. The proposed framework is designed using system dynamics modeling as a subset of a new causal model. The model includes interaction/activities between the main players and enablers in the supply chain network, namely suppliers/service providers, smartphone app/device factors, customers, and healthcare professionals, as well as cash and information flow. The model has been tested under various scenarios and settings. Simulation results reveal the dynamics of the model and show that improving the eye status monitoring device/app factors directly increases the efficiency/Eye-SCOR level. The proposed framework serves as an important step towards understanding and improving the overall performance of the supply chain network of smart eye/vision monitoring systems. Full article

Worldwide manufactures are redesigning supply chains, often outsourcing with the aim of maintaining a competitive advantage and gaining market share. When selecting and purchasing fabrics, firms should actively cooperate with suppliers, to meet customers’ needs. In this view, the supplier selection process plays a key role in keeping a competitive edge in global markets. Therefore, this study proposes a multicriteria decision-making model (MCDM) to ease supplier evaluation and selection. Supply chain operation reference metrics (SCOR metrics) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) are combined to build a model for supplier selection. The former allows us to conduct a very thorough fact-based analysis of all features in the supply chain, while the combination of fuzzy theory and SCOR model allows us to deal with uncertainty. The main novelty of this method is that it incorporates a consolidated supply chain management criteria within the framework of fuzzy set theory and multicriteria decision-making model (MCDM) facilitating their application into practice. The proposed approach is tested by considering the case of a manufacturing firm in the fashion industry willing to designate the most appropriate supplier within a set of three potential ones. Full article

Consumers increasingly prefer more direct and more transparent food distribution channels, such as short food supply chains (SFSCs). Nonetheless, SFSCs face a variety of issues and challenges in their creation and functioning, resulting in limited performance and sustainability, as well as in difficulties of upscaling. This study aims at improving our understanding of SFSCs’ issues/challenges through a systematic review of the most recent literature. We perform a full-text content analysis of 44 studies, looking for answers to the research questions: At which parts of the SFSCs do the issues/challenges occur? How can we characterize the issues/challenges in SFSCs? While doing so, we offer a holistic perspective on SFSCs. We make use of the SCOR model to define SFSC processes as well as to describe the nature of these issues/challenges. The findings of this study shed light on the nature and strategic-tactical-operational level of the issues/challenges in SFSCs and point out the limitations in the existing literature such as the SFSC processes that are neglected. The holistic approach we suggest and the insight on SFSCs’ issues/challenges we provide can help researchers offer effective solutions and strategies to support the overall development of SFSCs. Full article

This study aims to highlight the usefulness of studying the performance of supply chains (SC) at the sectoral level in greater detail through the combination of a disaggregated supply chain operations reference (SCOR) model, with a multicriteria decision-making approach, specifically using an AHP, to adjust the analysis to the particularities of the sector under study by stakeholders’ judgements. The methodology was applied to the Ecuadorian flower industry, and the data for the analysis was from a survey of a group of companies that represent this sector. In addition, a focus group of SC experts weighted the model constructs as part of the analytic hierarchy process (AHP), and then the performance level for each construct was determined. According to the results methodologies, this model allows the classification of companies by their performance, as well as the performance of the aggregate sector. The processes that Ecuadorian flower companies need to improve on are planning, procurement, and manufacturing. The study’s main contribution is developing a general framework for measuring the overall performance of SCs and how the results are obtained. This tool could help managers, consultants, industries, and governments to assess the performance of SCs, as well as improving SC management in order to increase the sector’s competitiveness in the international market. Full article

Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions. Full article

Despite increasing global environmental concerns, we continue to consume large amounts of products with little regard to what happens before, during, and after their use. Roughly one-third of the food produced is wasted. Because the world’s population is expected to grow to 10 billion by 2050, adopting circular economy practices will become essential. The transition towards a circular economy requires adopting business processes that support circular economy practices across supply chains. Currently, the SCOR (Supply Chain Operations Reference) model is the most widely used, and widely known, approach for studying and evaluating supply chain business processes. It is, however, unclear to what extent circular principles are included in the SCOR model. Past studies indicating missing processes for circular supply chain management in the SCOR model have made limited efforts in capturing the current state-of-the-practice. We conducted an online survey of 60 companies engaged in 14 different types of economic activities to study the SCOR level 2 business processes adopted in practice. In addition to the 22 level 2 business processes documented in SCOR, we identified six additional level 2 circular business processes that the respondents recognized as being commonly applied within their businesses. The results clearly show that the current SCOR model does not fully represent circular business processes in the state-of-the-practice. Full article

Due to fierce competition in the global market, success in product innovation has always been challenging for most enterprises to be able to stand out in business values and product novelty. Typically, available technological features in the market are taken into consideration in the innovation process for differentiation from existing products. In order to enhance the likelihood of innovation success, project portfolio management (PPM) has recently been advocated to examine the supply chain performance of new product development (NPD) projects in terms of economic, social, and sustainable aspects. In this study, a two-stage methodology is proposed to formulate and select the most appropriate NPD project portfolio by means of multi-criteria decision-making (MCDM) approaches in probabilistic and group decision-making processes. In stage one, the available product features on the market are searched for and ranked to indicate a number of potential NPD projects. In stage two, such projects are evaluated by the sustainable supply chain operation reference (SustainableSCOR) model to select the most sustainable NPD project for product development. Moreover, a case study of developing augmented reality (AR) smart glasses is conducted to demonstrate the above methodology, with the result indicating that the functions of voice commands, 3D visualization, and phone calls should be focused on for the next generation of smart glasses. Full article

This paper aims to present a study of the type of advanced technologies used across manufacturing supply chains in supporting the main processes of the supply chain operations reference model (SCOR). It also intends to identify a set of sustainable performance indicators (environmental, economic, and social) suitable to evaluate a supply chain 4.0 (SC4.0). To attain this objective, based on the literature review, a conceptual model is proposed. The multiple case study is used with a cross-case comparison to identify the type of advanced technologies more commonly used in SC4.0, and the performance indicators more suitable for assessing a SC4.0 sustainability performance. A sample of ten case studies was considered with companies belonging to different manufacturing SCs, from different countries, and belonging to different echelons. Main findings revealed that the level of adoption of advanced technologies in the Supply Chain SCOR processes varies amongst the case studies. Some technologies are quite commonly used among the several SCOR processes and companies while others are seldom applied. Some indicators were also identified that are regarded as very or extremely suitable to evaluate the sustainability performance of a SC4.0. The main contribution of this research to the body of knowledge is the empirical insights on the SC4.0 field and on Supply Chain Sustainability performance measurement. The results provide guidelines for the selection of advanced technologies to support SC processes and for the design of sustainable SC4.0 performance measurement systems. Full article

In recent years, the market of textile and garment materials has been volatile, and the ongoing US-China trade war is creating good opportunities for other markets such as Vietnam, Bangladesh and Mexico to continue to expand their market share in the United States. Vietnam is expected to have great advantages thanks to cheap labor cost and strong production capacity. Raw material supplier selection in a volatile competitive environment is crucial for a company to succeed, and supplier selection is a complicate process in which decision-makers must consider multiple quantitative and qualitative features, along with their symmetrical impact, in order to achieve an optimal result. The purpose of selecting the right supplier is to improve competitiveness and product quality, while satisfying customer demand at a minimum production cost. The aim of this paper is to propose a multicriteria decision making model (MCDM) for garment and textile supplier selection. In the first stage, all criteria affecting this process are defined by using the supply chain operations reference model (SCOR) and experts’ opinion. Incorporating hybrid fuzzy set theory into the analytical network process (ANP) model is the most effective tool for addressing complex problems of decision-making, which has a connection with various qualitative criteria; thus, the Fuzzy Analytical Hierarchy Process (FAHP) was applied for determining the weight of all potential suppliers, and the preference ranking organization method for enrichment of evaluations (PROMETHEE II) was used for ranking the supplier. The results of this research will assist researchers and decision makers in identifying, adapting and applying appropriate methods to identify the optimal material suppliers in the textile and garment industry. This research can also be used to support supplier selection decisions in other industries. Full article