Decision Analytics Journal最新文献

{"title":"A deep learning model to assist visually impaired in pothole detection using computer vision","authors":"Arjun Paramarthalingam ,&nbsp;Jegan Sivaraman ,&nbsp;Prasannavenkatesan Theerthagiri ,&nbsp;Balaji Vijayakumar ,&nbsp;Vignesh Baskaran","doi":"10.1016/j.dajour.2024.100507","DOIUrl":"10.1016/j.dajour.2024.100507","url":null,"abstract":"<div><p>Visually impaired individuals encounter numerous impediments when traveling, such as navigating unfamiliar routes, accessing information, and transportation, which can limit their mobility and restrict their access to opportunities. However, assistive technologies and infrastructure solutions such as tactile paving, audio cues, voice announcements, and smartphone applications have been developed to mitigate these challenges. Visually impaired individuals also face difficulties when encountering potholes while traveling. Potholes can pose a significant safety hazard, as they can cause individuals to trip and fall, potentially leading to injury. For visually impaired individuals, identifying and avoiding potholes can be particularly challenging. The solutions ensure that all individuals can travel safely and independently, regardless of their visual abilities. An innovative approach that leverages the You Only Look Once (YOLO) algorithm to detect potholes and provide auditory or haptic feedback to visually impaired individuals has been proposed in this paper. The dataset of pothole images was trained and integrated into an application for detecting potholes in real-time image data using a camera. The app provides feedback to the user, allowing them to navigate potholes and increasing their mobility and safety. This approach highlights the potential of YOLO for pothole detection and provides a valuable tool for visually impaired individuals. According to the testing, the model achieved 82.7% image accuracy and 30 Frames Per Second (FPS) accuracy in live video. The model is trained to detect potholes close to the user, but it may be hard to detect potholes far away from the user. The current model is only trained to detect potholes, but visually impaired people face other challenges. The proposed technology is a portable option for visually impaired people.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100507"},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001115/pdfft?md5=6ba37c16b7b3913b63959c8ebb277ada&pid=1-s2.0-S2772662224001115-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141953679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated Cognitive Reliability and Error Analysis Method (CREAM) and optimization for enhancing human reliability in blockchain","authors":"Azam Modares ,&nbsp;Vahideh Bafandegan Emroozi ,&nbsp;Hadi Gholinezhad ,&nbsp;Azade Modares","doi":"10.1016/j.dajour.2024.100506","DOIUrl":"10.1016/j.dajour.2024.100506","url":null,"abstract":"<div><p>Minor errors in smart contract coding on the blockchain can lead to significant and irreversible economic losses for transaction parties. Therefore, mitigating the risk posed by coding errors is crucial, necessitating the development of approaches to enhance human reliability in coding. The Cognitive Reliability and Error Analysis Method (CREAM) is one such approach, examining how environmental conditions affect the human error probability (HEP). Within CREAM, Common Performance Conditions (CPCs) influence error probability. This study ranks CPCs in smart contract coding based on their importance in coding reliability using the Bayesian Best Worst Method (BWM). Two methods are developed based on basic CREAM. In the first method, experts specify the control mode based on their opinions, and the probability of experts’ coding errors is determined according to the control level. In the second method, an optimization problem is formulated to select the most suitable programs, enhancing experts’ coding reliability. The proposed model considers energy, cost, and organizational budget factors to identify the optimal smart contract while minimizing the risks and costs associated with human errors. A case study in the electronics supply chain validates the applicability and efficacy of the proposed methods. Results from the first method indicate an opportunistic control mode. In contrast, the proposed model shows that improving CPC levels has a more significant effect, shifting the control mode towards a tactical control and reducing HEP to 0.00249.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100506"},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001103/pdfft?md5=fb2cb6c291465368aa5428981750d253&pid=1-s2.0-S2772662224001103-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141951320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated evaluation framework for Environmental, Social, and Governance-driven social media performance through Multi-criteria Decision-Analysis","authors":"Frank Stevens,&nbsp;Evangelos Grigoroudis ,&nbsp;Constantin Zopounidis,&nbsp;Konstantinos P. Tsagarakis","doi":"10.1016/j.dajour.2024.100505","DOIUrl":"10.1016/j.dajour.2024.100505","url":null,"abstract":"<div><p>Social media is crucial in providing data for networking with individuals, companies, or industries. This study deals with the topic of Environmental, Social and Governance (ESG). These can be seen as a set of standards which impacts a corporation’s structure and performance. Twenty years ago, when ESG started to gain notoriety, ESG initiatives were labeled as a tool to ensure ‘ethical’ and/or ‘responsible’ investing. This study collects data from LinkedIn company profiles on the industry, the staff, the number of followers, and the state where the company has its headquarters. In addition, the media’s take on pending legislation on ESG was assessed. Based on data from 537 companies, indicators were created, either normalized, the median, or ranked, and analyzed with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The current work provides information on this variation of ESG activity within the different states in the USA. Multi-criteria Decision Analysis (MCDA) was applied by weighing four criteria. The overall assessment was presented depending on the combined weighted performance score of the four criteria. The results showed that 36% of the companies active within the ESG landscape represent the “Financial Services” and “Management Consulting” industries. 65% of the investigated sample represented companies with up to 10 employees. Moreover, eight states perform well on both median of staff and followers (in alphabetical order: Michigan, Mississippi, Missouri, New Hampshire, New Mexico, Ohio, Oklahoma, and Wisconsin). Lastly, through the MCDA method, it was also observed that there are not many variations when different weights are applied to the four criteria: i.e., “the normalized number of companies by state,” “the median of the followers of the company per state,” “the median of the staff of the company per state,” and the “sentiment of the legislation.” Finally, the top five highly ranked states considering ESG visibility on LinkedIn through their companies are Ohio, Michigan, Delaware, Georgia, and Pennsylvania. The results indicate that companies can more proactively advertise themselves as compliant with current ESG principles. This methodology can also be applied to other topics and regions to assess online activity in line with existing indicators.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100505"},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001097/pdfft?md5=4522494ca16b652cf82e2a46fe5f33c7&pid=1-s2.0-S2772662224001097-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated AHP-TOPSIS approach for bamboo product evaluation and selection in rural communities","authors":"Wirachchaya Chanpuypetch ,&nbsp;Jirawan Niemsakul ,&nbsp;Walailak Atthirawong ,&nbsp;Tuangyot Supeekit","doi":"10.1016/j.dajour.2024.100503","DOIUrl":"10.1016/j.dajour.2024.100503","url":null,"abstract":"<div><p>This study introduces a decision support model integrating the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select an economic tree product champion (bamboo) to benefit rural communities. An extensive literature review and expert discussions identified sixteen sub-criteria distributed across five main criteria. The study proposes four categories of bamboo products as alternatives, emphasizing community-level production capacity. The AHP determines priority weights, while TOPSIS prioritizes alternatives conducive to becoming the product champion within a community case study. The findings affirm the efficacy of Multi-Criteria Decision-Making (MCDM) in identifying a champion, with “Value addition potential,” “Domestic market demand,” and “International market (export) demand” identified as pivotal criteria. Bamboo culm-based products for energy-related applications emerged as the chosen product champion in a community case study in Thailand. This study offers practical implications for rural communities and potential investors in economic tree ventures, allowing the customization of decision criteria and alternatives for specific contexts. Socially, the focus on bamboo highlights diverse benefits along the entire supply chain, from upstream to downstream. The research pioneers a decision support model, providing insights into market opportunity analysis and supply chain network design based on the selected product champion.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100503"},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001073/pdfft?md5=80c7243b46569562344ccee4a077ca34&pid=1-s2.0-S2772662224001073-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141845644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide","authors":"Ying-Chih Sun ,&nbsp;Ozlem Cosgun ,&nbsp;Raj Sharman ,&nbsp;Pavankumar Mulgund ,&nbsp;Dursun Delen","doi":"10.1016/j.dajour.2024.100504","DOIUrl":"10.1016/j.dajour.2024.100504","url":null,"abstract":"<div><p>As artificial intelligence (AI) begins to take center stage in technological innovations, it is essential to understand the business value of AI innovation efforts and investments. While some early work at the firm level exists, there is a shortage of literature that takes a larger country-level perspective. This study investigated the effect of AI innovation efforts on production efficiency across countries using stochastic production frontier approaches. In addition, our model also included the traditional economic inputs of capital and labor. We used both the Cobb–Douglas function and Constant Elastic Substitution model specifications. The significant findings of this study are as follows: Innovation efforts in AI measured by the number of AI-related patents and capital investment in AI have a substantial effect on economic output. The significance of AI investments indicates the need for a robust digital infrastructure as a prerequisite for harnessing AI capabilities. The complementary relationship between labor and AI-related patents implies that high-skilled labor is often necessary to incorporate AI inputs into production. However, as AI capabilities develop, they weaken the effect on labor input. The study also distinguishes between AI innovation (research and development activities indicated by AI patents) and the production efficiency of AI investments (return on every dollar invested), highlighting that more AI innovation does not always translate into better production efficiency. The findings indicate that while the United States leads innovation in AI, the UK has the best production efficiency. China ranked fourth in AI innovation and has the lowest production efficiency among the countries included in the study.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100504"},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001085/pdfft?md5=5575a0c4ac70d0a61890121fcff2341f&pid=1-s2.0-S2772662224001085-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141841674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of Digital Twins in efficient pandemic management with challenges and emerging trends","authors":"Ettilla Mohiuddin Eumi","doi":"10.1016/j.dajour.2024.100502","DOIUrl":"10.1016/j.dajour.2024.100502","url":null,"abstract":"<div><p>In recent years, Digital Twins (DTs) implementation has significantly impacted various sectors like industry, healthcare, engineering, and technology. However, the examination of these areas concerning pandemic management is still in its early stages. To bridge this gap, a systematic literature review was conducted here spanning from 2017 to March 2024, with a specific focus on COVID-19-related issues from 2020 to March 2024. Employing a five-step filtering process, nearly 10,000 articles were initially identified based on specific search strings. Subsequently, 297 publications were selected and examined across pre-pandemic, pandemic, and post-pandemic phases to discern emerging patterns, limitations, and future research directions. Drawing from these insights, a concept for a ‘Digital-Twin-based Smart Pandemic City’ was proposed, aiming to ensure contemporary amenities while preparing for potential pandemics by leveraging advanced cloud storage and blockchain technology for secure data aggregation. Anticipated challenges that may arise in implementing this model in the future were also explored in this review study.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100502"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001061/pdfft?md5=7d8d793ea8cd137f12979c7693e88bba&pid=1-s2.0-S2772662224001061-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141630519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An assessment of nature-inspired metaheuristic algorithms for resilient controller placement in software-defined networks","authors":"Sagarika Mohanty,&nbsp;Bibhudatta Sahoo,&nbsp;Subham Sai Behera","doi":"10.1016/j.dajour.2024.100501","DOIUrl":"10.1016/j.dajour.2024.100501","url":null,"abstract":"<div><p>Software-defined Networking (SDN) offers flexibility and programmability, making it a desirable option for modern network architecture. SDN provides numerous benefits to network administrators due to its centralized control architecture. This allows network administrators to manage and configure the network from a single location, making it easier to manage and automate network tasks. In a network of multiple controllers, the control plane’s resiliency may impact the overall system’s performance. In a controller failure scenario, switches must be reassigned to other active controllers with adequate capacity. Thus, we define a resilient controller placement (RCP) as an optimization problem. The aim is to design physically distributed and redundant controllers to manage switches with varying resilience levels. The propagation latency may increase due to the reassignment, increasing the network cost. The objective is to determine the number of controllers required, their positions, and the allocation of the network nodes to a particular controller while reducing the average propagation latency and cost in meeting the capacity constraint of the controller. Due to the wide area network (WAN) structure, four nature-inspired metaheuristic algorithms are proposed namely, simulated annealing (RCP-SA), moth-flame optimization algorithm (RCP-MFO), particle swarm optimization (RCP-PSO), and grey wolf optimization algorithm (RCP-GWO). These algorithms are evaluated on three network datasets to determine the optimum controller number and their positions. The experimental results show that RCP-GWO performs better than RCP-SA, RCP-MFO, RCP-PSO, and the Random methods.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100501"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277266222400105X/pdfft?md5=789051d6bc046617e9a2e7dbc59bb92a&pid=1-s2.0-S277266222400105X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141622307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An analysis of the equilibrium strategies for route-choosing customers in a two-station queueing system","authors":"Geofferey Jiyun Kim ,&nbsp;Jerim Kim","doi":"10.1016/j.dajour.2024.100500","DOIUrl":"10.1016/j.dajour.2024.100500","url":null,"abstract":"<div><p>We investigate a two-station queueing system where strategic customers must be sequentially serviced at both stations. We prove that an established property — that the distribution of the total time spent in a two-station system is independent of the chosen route when services times are exponentially distributed — is not a general one by providing a counterexample with deterministic service times. In doing so, we also prove a concomitant property — that any routing strategy is an equilibrium — is peculiar to a system with a particular assumption of an exponential service time distribution. Using simulations, we show that — depending on the distribution of service times — there can be (1) cases with three equilibria, (2) cases with one pure strategy equilibrium, and (3) cases with one mixed strategy equilibrium.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100500"},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001048/pdfft?md5=e54bb5543da6529fffda68c81e3d2365&pid=1-s2.0-S2772662224001048-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141637189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simulation-based optimization model for balancing economic profitability and working capital efficiency using system dynamics and genetic algorithms","authors":"Ehsan Badakhshan,&nbsp;Ramin Bahadori","doi":"10.1016/j.dajour.2024.100498","DOIUrl":"10.1016/j.dajour.2024.100498","url":null,"abstract":"<div><p>Economic uncertainty has been increasing, as evidenced by recent fluctuations in global markets and unpredictable economic indicators such as volatile demand, stock market fluctuations, and unpredictable interest rates. Economic profitability and working capital efficiency are pivotal indicators of a business’s financial health, both of which are adversely impacted by economic uncertainty. However, these metrics may diverge as distinct objectives drive them. There exists a gap in the literature regarding effective strategies for managing the trade-off between these metrics under economic uncertainty. This study addresses this gap by introducing a simulation-based optimization model that integrates system dynamics simulation and genetic algorithms. The proposed model aims to balance economic profitability and working capital efficiency within inventory management under partial trade credit. A recent real case study demonstrates the model’s applicability and reveals its superiority over conventional system dynamics simulation modeling. With its capacity to inform strategic and tactical decision-making, this model emerges as a valuable tool for supply chain and financial managers seeking to ensure financial stability amidst economic volatility.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100498"},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001024/pdfft?md5=62f59f94ce962ac5970764df10c38a7c&pid=1-s2.0-S2772662224001024-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141622306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An explainable artificial intelligence model for multiple lung diseases classification from chest X-ray images using fine-tuned transfer learning","authors":"Eram Mahamud ,&nbsp;Nafiz Fahad ,&nbsp;Md Assaduzzaman ,&nbsp;S.M. Zain ,&nbsp;Kah Ong Michael Goh ,&nbsp;Md. Kishor Morol","doi":"10.1016/j.dajour.2024.100499","DOIUrl":"https://doi.org/10.1016/j.dajour.2024.100499","url":null,"abstract":"<div><p>Traditional deep learning models are often considered “black boxes” due to their lack of interpretability, which limits their therapeutic use despite their success in classification tasks. This study aims to improve the interpretability of diagnoses for COVID-19, pneumonia, and tuberculosis from X-ray images using an enhanced DenseNet201 model within a transfer learning framework. We incorporated Explainable Artificial Intelligence (XAI) techniques, including SHAP, LIME, Grad-CAM, and Grad-CAM++, to make the model’s decisions more understandable. To enhance image clarity and detail, we applied preprocessing methods such as Denoising Autoencoder, Contrast Limited Adaptive Histogram Equalization (CLAHE), and Gamma Correction. An ablation study was conducted to identify the optimal parameters for the proposed approach. Our model’s performance was compared with other transfer learning-based models like EfficientNetB0, InceptionV3, and LeNet using evaluation metrics. The model that included data augmentation techniques achieved the best results, with an accuracy of 99.20%, and precision and recall of 99%. This demonstrates the critical role of data augmentation in improving model performance. SHAP and LIME provided significant insights into the model’s decision-making process, while Grad-CAM and Grad-CAM++ highlighted specific image features and regions influencing the model’s classifications. These techniques enhanced transparency and trust in AI-assisted diagnoses. Finally, we developed an Android-based system using the most effective model to support medical specialists in their decision-making process.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"12 ","pages":"Article 100499"},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224001036/pdfft?md5=b430bd720529ecff7f7f19d1a65e9d47&pid=1-s2.0-S2772662224001036-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141607905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}