Cost Advantages Research Articles

Review about Application of Nelumbo Nucifera

Natural Fibers are obtained from nature. The natural sources of these fibres can be plants, animals or minerals. We selected the plant sources as Lotus (Nelumbo nucifera). Lotus(Nelumbo nucifera) an aquatic perennial plant cultivated widely from Pallapalayam pond, Pollachi. Natural fibers have the advantages of low density, low cost, and biodegradability. Lotus fabric has the same significance but is less popular compared to other natural fibers. This fiber is a unique and luxurious natural fiber and its properties are Softness due to the fine and delicate fibers, breathability, antibacterial, moisture-wicking, UVresistant, sustainable alternative to synthetic fibers. It is used for Textiles like scarves, shawls and clothing, fishing nets and ropes because it has water resistant properties and other marine equipment, handicrafts such as baskets, bags and other woven goods, paper, medical purposes like napkins, wet wipes, sutures, absorbent core sheet, diapers etc. The industry is embracing nonwovens (pads, wipes, napkins) and single-use materials to cater to the huge demand from the consumer community. Nelumbo nucifera (Lotus) was used in their study to enhance the good medicinal property and eco- friendly in nature. Sustainability issues in textiles have an exploration of many new fibers from renewable sources. Lotus plants require minimal water and no chemicals or pesticides, making the fiber environmentally friendly. It is also naturally resistant to water and stains, making it’s a range of products.

Cost‐Effective DNA Storage System with DNA Movable Type

AbstractIn the face of exponential data growth, DNA‐based storage offers a promising solution for preserving big data. However, most existing DNA storage methods, akin to traditional block printing, require costly chemical synthesis for each individual data file, adopting a sequential, one‐time‐use synthesis approach. To overcome these limitations, a novel, cost‐effective “DNA‐movable‐type storage” system, inspired by movable type printing, is introduced. This system utilizes prefabricated DNA movable types‐short, double‐stranded DNA oligonucleotides encoding specific payload, address, and checksum data. These DNA‐MTs are enzymatically ligated/assembled into cohesive sequences, termed “DNA movable type blocks,” streamlining the assembly process with the automated BISHENG‐1 DNA‐MT inkjet printer. Using BISHENG‐1, 43.7 KB of data files are successfully printed, assembled, stored, and accurately retrieved in diverse formats (text, image, audio, and video) in vitro and in vivo, using only 350 DNA‐MTs. Notably, each DNA‐MT, synthesized once (2 OD), can be used up to 10000 times, reducing costs to $122/MB—outperforming existing DNA storage methods. This innovation circumvents the need to synthesize entire DNA sequences encoding files from scratch, offering significant cost and efficiency advantages. Furthermore, it has considerable untapped potential to advance a robust DNA storage system, better meeting the extensive data storage demands of the big‐data era.

An integrated optimization strategy for mission planning and control resource allocation for long-endurance unmanned aerial vehicle

PurposeWith burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.Design/methodology/approachWe consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.FindingsNumerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.Originality/valueDrawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.

Analyzing the Relationship between Risk Management Strategies and Supply Chain

Purpose: The purpose of this article examined how different risk management strategies affect supply chain resilience in Malaysia. It aims to identify effective strategies, such as supplier diversification and digitalization, that help Malaysian companies mitigate disruptions. The findings offer insights to enhance operational continuity and adaptability within Malaysia's unique risk environment. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that effective risk management strategies, like supplier diversification and real-time monitoring, significantly enhance supply chain resilience in Malaysia. Companies adopting these strategies experienced fewer disruptions and quicker recovery times. However, challenges such as high costs and limited technology access still hinder broader adoption among smaller firms. Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV), contingency theory & high reliability theory (HRT) may be used to anchor future studies on the relationship between risk management strategies and supply chain resilience in Malaysia. Practically, companies should implement risk management strategies that are tailored to their specific supply chain contexts and risks. At the policy level, governments and industry bodies should support the adoption of resilience-enhancing technologies by offering financial incentives or subsidies, particularly for small- and medium-sized enterprises.

Assessing the Effect of Green Supply Chain Practices on Corporate Performance in Philippines

Purpose: This article evaluated how environmentally sustainable practices impact corporate outcomes. It explores green supply chain strategies like eco-friendly sourcing and waste reduction, examining their effects on financial performance and brand reputation. The study aims to help businesses understand the benefits and challenges of integrating sustainability into their supply chains. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Green supply chain practices positively impact corporate performance by enhancing efficiency, reducing costs, and improving brand reputation. Companies adopting practices like sustainable sourcing and waste reduction report better operational outcomes and increased customer loyalty. Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV), stakeholder theory, institutional theory may be used to anchor future studies on the assessing the effect of green supply chain practices on corporate performance. For practitioners, the findings underscore the importance of implementing GSCM practices as part of a long-term strategic framework. At the policy level, governments should provide incentives and subsidies for companies that adopt GSCM practices, particularly in high-impact sectors like manufacturing and textiles.

Impact of E-Commerce Growth on Urban Logistics in France

Purpose: The article aims to examine how e-commerce growth is affecting urban logistics, including traffic congestion, environmental impact, and warehouse demand. It explores challenges posed by increased last-mile deliveries and suggests ways cities can adapt for efficient, sustainable logistics. This analysis seeks to provide solutions for balancing consumer demand with urban sustainability. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The findings revealed that e-commerce growth intensifies urban congestion, increases emissions from delivery vehicles, and drives up demand for warehouse space near cities. These changes challenge urban infrastructure and logistics efficiency. Sustainable solutions, like green vehicles and optimized delivery networks, are essential to mitigate these impacts. Unique Contribution to Theory, Practice and Policy: Urban growth theory, resource-based view (RBV) & sustainable urban logistics theory may be used to anchor future studies on the impact of e-commerce growth on urban logistics. Practically, logistics companies and urban planners should implement region-specific solutions to manage the unique challenges of e-commerce growth. From a policy perspective, city governments should establish clear guidelines and incentives to encourage sustainable urban logistics practices.

Examining How Blockchain Implementation Affects Supply Chain Visibility in Ghana

Purpose: This article investigate how blockchain technology enhances visibility in supply chains by enabling real-time, transparent data sharing among stakeholders. It explores blockchain's role in reducing information silos and improving traceability. The study aims to inform both industry practitioners and policymakers on blockchain’s benefits and adoption strategies. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Blockchain implementation enhances supply chain visibility by enabling real-time tracking and secure data sharing across stakeholders, reducing fraud and improving traceability. It also helps in verifying product origins, building consumer trust, and streamlining inventory management. However, challenges such as high costs and the need for standardized protocols can limit widespread adoption. Unique Contribution to Theory, Practice and Policy: Transaction cost economics (TCE), resource-based view (RBV) & institutional theory may be used to anchor future studies on the examining how blockchain implementation affects supply chain visibility. For practitioners, the implementation of blockchain technology offers significant potential to improve real-time visibility, data accuracy, and trust within the supply chain. Policymakers should develop standards and regulatory guidelines for blockchain implementation in supply chains to ensure secure and ethical data usage.

A reliable, practical and cost-effective portable wireless potentiostat for mobile chemical sensing and biosensing

Abstract Traditional electrochemical workstations are costly, complex, bulky, and primarily used in laboratories. This study develops a reliable, practical, and cost-effective portable wireless potentiostat to achieve real-time detection on-site and overcome the limitations of traditional electrochemical workstations. The system employs a general-purpose microcontroller unit (MCU), a dual-mode Bluetooth module and cost-effective multi-analog-to-digital converter (multi-ADC) to achieve differential sampling of the LMP91000. The system is equipped with buttons and OLEDs, enabling connection to mobile phones and computers for in-depth data analysis or independent operation. The system was successfully tested with [Fe(CN)6]3-, C6H12O6, and C3H6O3 solutions at concentrations ranging from 0 to 20 mM. The goodness-of-fit (R²) values are 0.984, 0.996, and 0.998, respectively. The average relative standard deviation of the three blank solutions is approximately 3.22%. The detection limits measured (0.003, 0.009, and 0.005 mM) are all lower than the minimum detection concentration (0.2, 0.1, and 0.1 mM). The coefficient of variation for repetitive experiments is less than 5.53%. The device accurately executed chronoamperometry (applied voltage range is ± 1.2 V, current range is ± 882 μA, accuracy is ± 1 %) with high sensitivity and good repeatability. Based on this circuit, a lactic acid detector and a urine glucose detector were developed, which work stably and support long-term operation, proving the stability and reliability of the circuit. Compared to commercial electrochemical workstations, PWES offers remarkable advantages in cost (< $6.4), size (41.5 mm × 76.5 mm), and practicality, making it suitable for a range of applications, including biomedical analysis, food safety, environmental monitoring, and smart wearables.

Two types of microorganisms isolated from petroleum hydrocarbon pollutants: Degradation characteristics and metabolic pathways analysis of petroleum hydrocarbons.

The petroleum hydrocarbons in seawater have been worldwide concern contaminants. Biological method, with the advantages of low cost, minimal environmental impact, and no secondary pollution, is a promising method for petroleum hydrocarbon treatment. In this study, two strains, identified as Stenotrophomonas acidaminiphila and Ochrobactrum, were demonstrated to possess the ability to degrade petroleum hydrocarbons. The mixed culture composed of Stenotrophomonas acidaminiphila and Ochrobactrum at a 2:1 ratio was able to achieve 79.41% degradation of the total petroleum hydrocarbons after 5 days. Besides, the average removal efficiencies of C10-C30 components in petroleum hydrocarbons by Stenotrophomonas acidaminiphila, Ochrobactrum, and mixed culture were 62.98%, 59.14% and 73.30%, respectively. The possible degradation pathways of petroleum hydrocarbons had been speculated through gas chromatography-mass spectrometry (GC-MS) and differential gene expression metabolomics analyses. The toxicity of products from the biodegradation of petroleum hydrocarbons was greatly reduced.

Visible light visual indoor positioning system for based on residual convolutional networks and image restoration

Abstract Visible light positioning technology, with its advantages of low cost, strong anti-interference, and high precision, is widely researched and applied in various different scenarios. In this paper, for the complexity of indoor environments, considering the problem of occlusion by various obstacles that may exist in indoor spaces, which may lead to incomplete imaging of CMOS image sensors, a maximum gray value-based occlusion recovery and decoding scheme is proposed. This scheme effectively solves the problem of visible light transmission channel being blocked and accomplishes LED-ID decoding. In addition, the overflow effect due to uneven light irradiation gathered in each pixel row affects the accuracy of decoding LED-ID, which in turn leads to poor positioning accuracy. In this paper, we propose to use an adaptive gamma correction method to eliminate the influence of the overflow effect and to improve the accuracy of decoding. In order to improve the positioning accuracy, a visible light positioning algorithm based on residual convolutional network (VisiResNet) is proposed to achieve high accuracy positioning. The experimental results show that the average positioning error is 9.7 cm in a space of 9m× 3m× 3m, and a decoding accuracy of 90% within 1.4m is achieved in the face of different occlusion situations. The system can achieve centimeter-level positioning accuracy and meet the indoor positioning requirements.

High-Precision Rotor Position Fitting Method of Permanent Magnet Synchronous Machine Based on Hall-Effect Sensors

The high-performance vector control technology of permanent magnet synchronous machines (PMSMs) relies on high-precision rotor position. The Hall-effect sensor has the advantages of low cost, simple installation, and strong anti-interference ability. However, it can only provide six discrete rotor angles in an electrical cycle, which makes high-precision vector control of PMSMs difficult. Hence, to obtain the necessary rotor position of PMSMs, a rotor position fitting method combining the Hall signal and machine flux information is proposed. Firstly, the rotor position signal output by the Hall-effect sensors is used to calibrate and update the stator flux obtained under pure integration. Then, based on the corrected stator flux and its relationship with current and angle, the rotor position and speed are obtained. Experimental verification shows that the rotor position observer combining Hall signal and flux information can reduce the initial value bias and integral drift caused by traditional average speed method hysteresis and pure integration method calculation of flux and can quickly and accurately track and estimate the rotor position, achieving high-performance vector control of PMSMs.

What automatic speech recognition can and cannot do for conversational speech transcription

Transcripts are vital in any research involving conversation. Most transcription is conducted manually, by experts; a process which can take many times longer than the conversation itself. Recently, there has been interest in using automatic speech recognition (ASR) to automate transcription, driven by the wide availability of ASR platforms such as OpenAI’s Whisper. However as studies typically focus on metrics such as the word error rate, there is a lack of detail about ASR transcript quality and the practicalities of ASR use in research. In this paper we review six state-of-the-art ASR technologies, three commercial and three open-source. We assess their capabilities as automatic transcription tools. We find that the commercial ASR systems mostly capture an accurate representation of what was said, and overlapping speech is handled well. Unlike prior work, we show that commercial ASR also preserves the location, but not necessarily the spelling of a large majority of non-lexical tokens: short words such as uh-hum which play vital roles in conversation. We show that the open-source ASR systems produce substantially more errors than their commercial counterparts. However, we highlight how the cost and privacy advantages of open-source ASR may outweigh performance issues in certain applications. We discuss practical considerations for ASR deployment in research, concluding that present ASR technology cannot yet replace the trained transcriber. However, a high-quality initial transcript generated by ASR can provide a good starting point and may be further refined by manual correction. We make all ASR-generated transcripts available for future research in the supplementary material.

Excellent Wavelength Selectivity of p-AlGaN/n-Ga2O3 Solar-Blind UVC PD.

Due to the advantages of ultrawide bandgap, chemical stability, self-powered, and low cost, gallium oxide (Ga2O3) based photodetectors (PDs) are considered as one of the most promising solar-blind ultraviolet PDs, having garnered significant attention in fields such as missile warning and flame arc detection. High selective ratios and excellent responsivity are important to reduce the false alarm rate in solar-blind detection. However, due to the lack of p-type Ga2O3, existing Ga2O3-based PN PDs utilized heterostructures with narrower bandgap p-type semiconductors (e.g., p-GaN, p-SiC, etc.), inducing poor selective ratios with visible light and ultraviolet-A/B (UVA/B). Therefore, a high Al content AlGaN was used in this study to form a p-AlGaN/n-Ga2O3 solar-blind ultraviolet-C (UVC) PD. Since the bandgap of p-AlGaN aligned with the UVC region, the device exhibited exceptionally high selective ratios with R247nm/R360nm = 3.71 × 105 and R247nm/R300nm = 1.47 × 105 at 0 V, which surpassed the reported Ga2O3-based PN PDs. The formation of the type-II heterojunction facilitated the effective separation and transport of photogenerated carriers, resulting in high responsivity (0.36 A/W) under zero bias. Overall, the high selective ratios and high responsivity of the p-AlGaN/n-Ga2O3 PD in this paper provided a reliable pathway for self-powered solar-blind PDs with a low false alarm rate.

Application of Bivariate Reproducing Kernel-Based Best Interpolation Method in Electrical Tomography

Electrical Tomography (ET) technology is widely used in multiphase flow detection due to its advantages of low cost, visualization, fast response, non-radiation, and non-invasiveness. However, ill-posed solutions lead to low image reconstruction resolution, which limits its practical engineering applications. Although existing interpolation approximation algorithms can alleviate the effects of the ill-posed solutions to some extent, the imaging results remain suboptimal due to the limited approximation capability of these methods. This paper proposes a Bivariate Reproducing Kernel-Based Best Interpolation (BRKBI) method, which offers smaller approximation errors and clearer image reconstruction quality compared to existing methods. The effectiveness of the BRKBI method is validated through theoretical analysis and experimental comparisons.

Study on the hard carbon anode from different precursors for sodium ion batteries

Sodium-ion batteries (SIBs) are commonly utilized in power storage applications. It can be used as alternatives to lithium-ion batteries. Nevertheless, the development of SIBs is restricted by anode materials due to the high redox potential and large irreversible capacity. As a common anode material of SIBs, hard carbon exhibits a substantial interlayer spacing and a excellent reversible specific capacity, while the properties and costs are affected by its precursors. This article mainly describes the sodium storage principle of hard carbon and compares the performances as well as modification methods of hard carbon produced from various precursors. The hard carbon basing on coal has the advantages of low cost due to the abundant reserves of coal precursors and low redox potential. Biomass-based hard carbon has natural pores which can assist the sodium ions transport in carbon materials. We further explain the effects of modification strategies such as heteroatom doping, activation treatment and mechanical ball milling on electrochemical properties of hard carbon. Finally, this paper recognizes the existing problems and corresponding solutions of materials made of hard carbon and looks forward to the future research focus on hard carbon materials.

Engineering in situ heterometallic layer for robust Zn electrochemistry in extreme Zn(BF4)2 electrolyte environment

The performance of zinc metal batteries is critically affected by the electrolyte environment originating from various zinc salt formulations. Zn(BF4)2, in particular, offers a notable cost advantage and its fluoride-containing groups facilitate the formation of a beneficial ZnF2 interfacial layer, thereby making it a promising candidate for application. Nonetheless, the strong acidity of the Zn(BF4)2-based electrolyte exacerbates the dendrite formation and promotes parasitic reactions, leading to rapid battery failure. Herein, M(BF4)n (M: Cu, Sn, In) salts were adopted as additives in Zn(BF4)2 electrolyte to in situ construct the heterometallic layers. Through comparison, the In(BF4)3-derived ZnIn interface demonstrates superior corrosion-resistance capability and the strongest zinc affinity, protecting the anode from acidic erosion and accelerating the Zn2+ transportation kinetics. The symmetric cell with the optimized electrolyte exhibits a long lifespan of 2500 cycles while the full cell involving the polyaniline cathode also presents a high capacity retention of 81.3 % after 1500 cycles, outperforming the cell with the original Zn(BF4)2 electrolyte. The strategy of generating an interface layer within the battery through electrolyte additives can be readily applied to other metal battery technologies.

Role of Technological Advancements on Customer Satisfaction in Japan’s Hospitality

Purpose: The aim of the study was to analyze the role of technological advancements on customer satisfaction in Japan’s hospitality. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Technological advancements have significantly enhanced customer satisfaction in Japan’s hospitality industry by improving service efficiency, personalization, and overall guest experience. Innovations such as AI-driven customer service robots, automated check-in systems, and smart hotel rooms equipped with IoT devices offer convenience and seamless interactions for guests. These technologies reduce waiting times, streamline operations, and allow for personalized services, such as customized room settings and tailored recommendations, increasing guest satisfaction. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM), service quality model (SERVQUAL) & expectancy-confirmation theory (ECT) may be used to anchor future studies on the role of technological advancements on customer satisfaction in Japan’s hospitality. Hospitality businesses should adopt integrated management systems that combine customer relationship management (CRM), property management systems (PMS), and online booking platforms. Industry regulators should promote standards for technology integration in the hospitality sector.

Effect of Cultural Heritage on Tourism Development in Italy

Purpose: The aim of the study was to analyze the effect of cultural heritage on tourism development in Italy. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The cultural heritage of Italy plays a significant role in its tourism development, attracting millions of visitors annually to historic cities like Rome, Florence, and Venice. Italy's rich history, art, architecture, and traditions make it a global cultural destination, with UNESCO World Heritage Sites such as the Colosseum, the Vatican, and the Uffizi Gallery serving as major draws. This cultural wealth not only boosts the tourism industry but also supports local economies and preserves historical landmarks. Unique Contribution to Theory, Practice and Policy: Cultural capital theory, sustainable tourism theory & heritage conservation theory may be used to anchor future studies on the effect of cultural heritage on tourism development in Italy. Implementing practical measures such as visitor quotas, dynamic pricing, and timed entry tickets can help regulate tourist flow to high-traffic cultural heritage sites. Policymakers should develop sustainable tourism frameworks that balance economic growth with cultural heritage preservation.

Impact of Eco-Friendly Practices on Resort Profitability in the Maldives

Purpose: The aim of the study was to analyze the impact of eco-friendly practices on resort profitability in the Maldives. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Studies on the impact of eco-friendly practices on resort profitability in the Maldives show that sustainable practices, such as renewable energy use, water conservation, and waste reduction, positively affect profitability. Resorts adopting green initiatives benefit from lower operational costs, such as reduced energy and water consumption, while also attracting environmentally conscious tourists willing to pay premium prices. These practices also enhance brand reputation and long-term resilience, reducing dependency on finite resources. However, the initial investment in eco-friendly infrastructure can be high, and profitability gains are more evident in the long term. Unique Contribution to Theory, Practice and Policy: Sustainable tourism theory, corporate social responsibility (CSR) theory, resource-based View (RBV) theory may be used to anchor future studies on the role of technological advancements on customer satisfaction in Japan’s hospitality. Practically, resorts in the Maldives can use this research to improve their profitability while simultaneously enhancing their environmental sustainability. At a policy level, this research can provide empirical evidence for policymakers in the Maldives to promote and regulate eco-friendly practices in the tourism sector.

Influence of Social Media Marketing on Destination Choice among European Travelers

Purpose: The aim of the study was to analyze the influence of social media marketing on destination choice among European travelers. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Social media marketing has a significant influence on destination choice among European travelers, as it shapes their perceptions and decision-making processes. Studies show that platforms like Instagram, Facebook, and YouTube serve as key sources of inspiration and information, with user-generated content and influencer recommendations often playing a pivotal role in shaping travel preferences. Travelers are particularly drawn to visually appealing content, which showcases destinations' attractions, culture, and experiences in an engaging manner. Unique Contribution to Theory, Practice and Policy: Uses and gratifications theory (UGT), social proof theory & elaboration likelihood Model (ELM) may be used to anchor future studies on the influence of social media marketing on destination choice among European travelers. Travel businesses should invest in creating visually compelling content that showcases their offerings. Destination marketing organizations (DMOs) should adopt policies that prioritize high-quality visual content in their marketing strategies.