Service Selection Research Articles

Real-Time Evaluation of the Improved Eagle Strategy Model in the Internet of Things

With the rapid expansion of cloud computing and the pervasive growth of IoT across industries and educational sectors, the need for efficient remote data management and service orchestration has become paramount. Web services, facilitated by APIs, offer a modular approach to integrating and streamlining complex business processes. However, real-time monitoring and optimal service selection within large-scale, cloud-based repositories remain significant challenges. This study introduces the novel Improved Eagle Strategy (IES) hybrid model, which uniquely integrates bio-inspired optimization with clustering techniques to drastically reduce computation time while ensuring highly accurate service selection tailored to specific user requirements. Through comprehensive NetLogo simulations, the IES model demonstrates superior efficiency in service selection compared to existing methodologies. Additionally, the IES model’s application through a web dashboard system highlights its capability to manage both functional and non-functional service attributes effectively. When deployed on real-time IoT devices, the IES model not only enhances computation speed but also ensures a more responsive and user-centric service environment. This research underscores the transformative potential of the IES model, marking a significant advancement in optimizing cloud computing processes, particularly within the IoT ecosystem.

Implementation of a Mobile-Based Laundry Order Management System at Barack Laundry in Sleman

Barack Laundry is a laundry service business operating in Trini Sleman, a district in the Special Region of Yogyakarta. Laundry is an important household necessity, and many people are looking for trustworthy laundry service. Customer demand for laundry services continues to increase along with increasingly busy lifestyles. Although Barack Laundry's services continue to grow, there are still some problems faced by customers in the Trini Sleman area. One of the main problems is the lack of accessibility of information regarding service schedules, laundry status, and estimated costs. It is necessary to develop a mobile-based Barack Laundry application in Trini Sleman to overcome the problems that exist in Barack Laundry. The purpose of designing this mobile-based Barack Laundry application is to facilitate laundry management and customers so as to increase efficiency in the clothing ordering process. Apps can also extend the reach of laundry services to make them more accessible to customers. Features available on the app include a selection of clothing types and services with options such as washing, ironing, and both. The app also provides detailed booking information, scheduling of pick-up and drop-off times, and the option of online payment methods. The user-centered design method is used in this research by focusing on user needs. Kotlin programming language and MySQL database are also used in the process of developing this application. Based on the results of the research that has been done, it can be concluded that the mobile-based Barack Laundry application in Trini Sleman has successfully designed and implemented a mobile-based application for laundry ordering services in the region. This application has been carried out a black box testing process that has been carried out as many as 19 scenarios, with the final test results reaching 100%.

АНАЛІЗ ЦІНОВИХ СТРАТЕГІЙ ТА СПОЖИВЧА ПОВЕДІНКА В КОНТЕКСТІ МАРКЕТИНГОВИХ ДОСЛІДЖЕНЬ

Abstract introduction. The article examines the views of scientists regarding the formation of price strategies. The main approaches to pricing are considered, with the help of which companies set optimal prices for their services and goods. Factors affecting the company's choice of pricing strategy and affecting consumer behavior are considered. It is conducted research in relation to behavior of consumers and built model of satisfaction of consumer necessities. The purpose of the article. Consideration of pricing strategies of companies and their impact on consumer behavior. Researching consumer behavior and building a model for satisfying consumer needs in goods or services. Methods. Carrying out research the methods of abstraction, analysis, logical, theoretical and historical generalization and comparison are used. For basis of research a dialectical method is taken. Results. The article examines the main approaches to pricing, with the help of which companies set optimal prices for their services and goods. The factors affecting the company's choice of price strategy are considered, and the factors influencing consumer behavior are highlighted. Conducted research on consumer behavior. The proposed model of meeting the needs of consumers in goods or services, which contains 8 sections: the consumer's awareness of the need for the need for a product or service; collection of information; selection of goods or services; decision-making; purchase (payment) of goods or services; evaluation of the choice made and enrichment of experience; the degree of satisfaction of the need for a product or service and consumption of the results. Conclusiоns. After researching and analyzing the available types of marketing price strategies, business entities choose their own price strategy, taking into account certain existing tools, taking into account: characteristics of the service or product, market segment, market competition, competitor analysis, level of market demand, marketing strategies, etc. .. The use of the correct price strategy and the concept of pricing contributes to the achievement of goals: ensuring the stable financial condition of the business entity, meeting the needs of consumers. The offered model in relation to satisfaction of necessities of consumers in commodities or services gives understanding to the process of making decision by consumers in relation to a purchase that is the basic factor of success of company in a competition environment. Companies, that is able to adapt oneself to the necessities of consumers and, to their requirements, that understand the customers, have more chances to retain and attract clients, promote a competitiveness and score a success at the market. The question of the method of determining prices for certain types of services and the behavioral reaction of consumers requires further research.

A Markov chain-based multi-criteria framework for dynamic cloud service selection using user feedback

A Markov chain-based multi-criteria framework for dynamic cloud service selection using user feedback

Sosialisasi Peningkatan Pengetahuan Keamanan Dalam Jual Beli Online

The increasing number of internet users makes Indonesia a very potential market for e-commerce. The growth of the middle class and the literacy rate of online buyers and sellers is also growing. E-commerce itself is not new, but its rise marks a new milestone for this industry in the country. Although it is growing quite rapidly, there is still one major problem that is preventing e-commerce in Indonesia from taking off, namely the problem of consumer trust in e-commerce sites. Consumers still do not trust the sales system with a non-physical buying and selling process, do not trust to provide credit card numbers to e-commerce services and are still afraid of fraud. However, this crisis of trust can actually be solved. One of the many ways is to use a payment service that has guaranteed security. Not all e-commerce can provide their own payment system, now there are many services that provide a secure payment system and are especially easy to apply to online stores. E-commerce players can use this payment system easily, quickly and which can improve the performance process in their online stores. However, the selection of services that provide a payment system must also be considered carefully. A secure payment system provider will provide a sense of security to prospective buyers, meaning that consumer trust must be built by e-commerce service providers so that consumers can be comfortable and do not encounter problems in making purchases and paying for products in the online stores provided.Security is important, the use of credit cards is widely highlighted because there are still many unpleasant incidents or fraud that occur due to the use of credit cards. Education on this security needs to be carried out continuously, because it will be related to consumer behavior.

Typification of Projects for the Transition to Cloud Services

Introduction. Digital solutions make the operation of the company clearer, reduce staff costs, and provide data security. Various aspects of automation, digitalization and cloud technologies are described in the literature. The question is raised about the quality of the methodological basis for such transformations. Global and narrow technical approaches are presented. As a rule, materials are presented from the perspective of experts in the implementation of digital technologies. In this paper, for the first time, the author's scheme is proposed that can allow not only providers, but also their customers to navigate the upcoming transition to the cloud. The latter will receive systematic information on how to select a contractor and the most economically feasible option of cooperation.Materials and Methods. The information model was based on the semantic network as a system of nodes, their characteristics and connections. Management of the cloud migration project and the migration itself were visualized. The contraction practice between providers and their customers was summarized. The specifics of the tasks of such projects were taken into account. The part of the subject area related to the implementation of a cloud service is algorithmic — a step-by-step transition to the cloud, a generalized scheme of the process taking into account the hierarchy of elements are presented.Results. For the first time, a method of self-preparation of a company for the implementation of cloud solutions is proposed. The algorithm systematizes the cloud migration processes. The activities related to goal setting, audit, selection of cloud environment and services, calculation of the economic efficiency of the project, planning and implementation of migration, technical support and scaling of processes are described. The possibilities of determining the economic feasibility of measures for the transition to the cloud are shown. The costs of equipment, data storage and processing, software licenses, salaries, information security, etc., are taken into account. The amount received is compared to the providers' offers. For the final decision, the costs of infrastructure support are taken into account — by the customer or the outsourcer. The best option is selected. As a result, the customer gets the opportunity to work with better profitability and scale the project. Feedback is provided, and processes are adjusted, starting with IT reaudit.Discussion and Conclusion. The proposed solution will give the customer's management a system view of the execution sequence when migrating to the cloud, the issues and tasks to discuss with a potential outsourcer. Providers can use the algorithm to typify and unify projects, which can eventually simplify the coordination of the list of services and the migration procedure with customers. In this way, the parties can free up significant resources in terms of time, labor and other costs. In addition, customers and providers can partially use the described semantic network to develop not only the organizational, but also the technical aspect of the project.

Determinants of Patient Preference for Private Hospitals Over Public Hospitals: An Empirical Study

Introduction: There are several choices when it comes to choosing the type of hospital. In Nepal, the general public is free to seek medical attention from any facility they feel is suitable for them. People have to make vital decisions while choosing a hospital because these decisions relate to health and relieve them from any burden regarding their health. There is a preference for private hospitals over public ones. Despite the relatively cheaper cost of care in public hospitals, such a setup was not preferred by the people; this observation motivated us and created a need to conduct a research study to validate the observation statistically. This study examines reasons why private hospitals are preferred by patients over public ones. Methods: The quantitative description research methodology has been adopted for this study. Developmental research approach is used in conducting this study through quantitative descriptive research. The researcher has followed a deductive research approach to examine the hypotheses we had set up with respect to their significance. Only 117 responses out of the 120 persons of the sample were found to be significant for the research study. A structured questionnaire was designed based on a five-point Likert scale. Random sampling was selected because of the probability sampling methodology used for the research study. Findings: In Tarkeshwor Municipality, the general public does not select a private hospital over a public hospital considering their income. There is no visible relation between the level of hospital services, treatment costs, and hospital selection criteria with income level of respondents. Three dependent variables—service quality, cost, and individual selection motive—have an influence on hospital choice decisions. The vast majority of the respondents appeared to make some kind of valuation about the value for money of the hospitals they visited, irrespective of their income. Since there exists a strong positive correlation between the cost and service mean, they attach higher costs to higher quality of service. Service quality: When asked about service quality, most of the respondents replied that what inclined their preference towards private hospitals and not government-run ones was the short waiting time and up to date medical equipments. Conclusion: Hence, based on this, it can be concluded that the choice of hospitals among the public is determined in view of the cost of treatment and hospital selection motives, such as access to up-to-date medical technology and lesser wait times and so on, rather than by income, which is not related to any of the dependent variables: service quality, treatment costs, and selection motives for hospitals.

Research on Collaborative Strategy of Dual-Channel Supply Chain System for Product and Service Selection Driven by Experiential Demand

With the intensification of dual-channel competition, manufacturers are increasingly inclined to invest in offline showroom services to improve consumers' shopping experience, making it an emerging trend. Based on this background, this paper makes an in-depth study of how manufacturers choose the business strategy of physical showrooms in the dual-channel e-commerce environment, discusses the advantages and disadvantages of different service models, and analyzes the impact of these choices on consumer behavior and market competition. Through this research, this paper aims to provide valuable strategic suggestions for manufacturers to optimize their dual-channel service models. Four Stackelberg game models are constructed: 1) no service model (N), 2) manufacturers invest in service online products (MSM), 3) retailers invest in services online products (RSM), and 4) retailers invest in services online products (RSR). Then the optimal decision under the above four strategies is compared and analyzed, and the optimal choice of the manufacturer and the optimal service model of the whole supply chain are obtained.

QoS prediction of cloud services by selective ensemble learning on prefilling‐based matrix factorizations

SummaryWhen selecting services from a cloud center to build applications, the quality of service (QoS) is an important nonfunctional attribute to be considered. However, in actual application scenarios, the QoS details for many services may not be available. This has led to a situation where prediction of the missing QoS records for services has become a key problem for service selection. This article presents a selective ensemble learning (SEL) framework for prefilling‐based matrix factorization (PFMF) predictors. In each PFMF predictor, the improved collaborative filtering is defined by examining the stability of the QoS records when measuring the similarity of users (or services), and then used to prefill empty records in the initial QoS matrix. To ensure the diversity of the basic PFMF predictors, various prefilled QoS matrices are constructed for the matrix factorization. In this process, different reference weights are assigned to the original and the prefilled QoS records. Finally, particle swarm optimization is used to set the ensemble weights for the basic PFMF predictors. The proposed SEL on PFMF (SEL‐PFMF) algorithm is validated on a public dataset, where its prediction performance outperforms the state‐of‐the‐art algorithms, and also shows good stability.

Exploring determinants influencing the selection of geriatric nursing care services in Thailand Bangkok metropolitan area

The global population structure is undergoing a significant transformation, marked by an increasing number of elderly individuals. Thailand, in particular, is transitioning into an aging society and exhibits the third-highest growth rate in Asia, following Japan and Singapore. This phenomenon is driven by various factors, including economic and social conditions, technological advancements, family dynamics, and evolving lifestyles. Consequently, a growing number of elderly individuals are either living alone or require caregivers and elderly care facilities if they are dependent. This study is prompted by a keen interest in the elderly care service industry, which demonstrates significant potential both currently and in the future. The primary objective of this research is to explore the determinants influencing the selection of Geriatric nursing care and to identify the challenges encountered in delivering these services. The study investigated demographic and social factors, the necessity for elderly care, and the decision-making process in selecting geriatric nursing care. Data was collected through online questionnaires and analyzed, employing both descriptive and inferential statistics, including factor analysis, reliability analysis, and correlations between variables. The target population comprises Thai individuals aged 50 and above residing in Bangkok and its metropolitan areas with a sample size of 426 participants. Findings suggest that demographic factors, excluding occupation, along with social factors, the necessity for dependency, and the decision-making process, affect the selection of Geriatric nursing care in the studied regions.

Service Selection under Uncertainty

Cloud computing has emerged as a popular computing paradigm, providing scalable and pay-per-use services to execute a variety of tasks. However, selecting the most suitable cloud services for a client can be challenging, as it involves taking into account the service characteristics and a set of client restrictions. In this paper, we formalize the problem of Service Selection under Uncertainty (SSuU) as an optimization problem. Our goal is to allocate tasks to appropriate cloud services while considering the probability of Service Level Agreement (SLA) violations and a set of client restrictions. We introduce an efficient dynamic programming approach to calculate the probability of SLA violations incrementally over time. We prove that the SSuU problem is strongly NP-complete, and propose an Integer Linear Programming (ILP) formulation and an Iterated Local Search-based algorithm for tackling it. To facilitate evaluation, we also introduce a set of benchmark instances for the SSuU problem. We extensively evaluate our proposed solutions on 94 input instances and compare them to the exact method (i.e., which always produces the optimal solution). Our results demonstrate that the metaheuristic approach is significantly faster and leads to exact solutions in the great majority of the evaluation scenarios.

The Impact of Environmental Factors and Perceived Benefits On Customers' Decisions to Outsource Logistics Services in Vietnam

Objective: The objective of this study is to investigate factors influencing customers' decisions to outsource logistics services in Vietnam, with the aim of evaluating the impact of environmental factors and trust on businesses' decisions to outsource logistics services. Theoretical Framework: In this section, the main concepts and theories that underpin the research are presented. Transaction Cost Economics (TCE), providing a solid basis for understanding the context of the investigation. Method: A quantitative research method was used, with a sample size of 315 selected through random sampling. The research was conducted from March 2024 to July 2024. The collected data was cleaned and processed using SPSS 20.0 software through a survey of 150 individuals with experience and expertise in the logistics field. The purpose was to gather insights and consider decisions regarding outsourcing logistics services. The research model was tested for suitability, including Cronbach’s Alpha reliability test and Exploratory Factor Analysis (EFA). Results and Discussion: The results obtained revealed that environmental factors and trust both have a positive impact on businesses' decisions to outsource logistics services. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of logistics. Originality/Value: This study contributes to the literature by evaluating the impact of environmental factors, an aspect that has received little attention in the selection of logistics services. The relevance and value of this research are evidenced by referencing previous studies and foundational theories to build the research model.

Streaming Video Service Repertoire: Patterns, Drivers, and Decisions

ABSTRACT As subscription video-on-demand (SVOD) competition heats up with more newcomers beyond the quintessential Netflix, examining streaming video consumption from the perspective of an SVOD repertoire (a set of service subscriptions by a streaming user) can help the industry understand how consumers make decisions in forming their SVOD collection and their corresponding subscription patterns for marketing insights. Existing repertoire and SVOD studies still focus on users’ content selections and preferences, and the mechanisms and drivers affecting customer choices, without realizing that consumers are not seeking to pick the best SVOD out of all. Instead, consumers are attempting to curate an exquisite selection of services that satisfy their content needs for a reasonable price while avoiding streaming confusion (uncertainty about where to access the content) and fatigue (too many options). This study explored consumers’ SVOD repertoire within the U.S. context, investigating the SVOD repertoire patterns (size and composition) and differences in the SVOD repertoires regarding consumers’ demographics, media ecosystem, streaming behavior, and perceived repertoire adequacy through an online survey method. Through an analysis of responses from 1038 participants, the study demonstrated the value of the repertoire approach in examining SVOD subscriptions. Results showed the dynamic importance of certain SVOD services and configuration changes of one’s repertoire according to size. Netflix (as the likely core), Amazon Prime Video, and Hulu (as the two most likely complements) were the most subscribed SVODs. Differences were found in demographics, media ecosystem, streaming behavior, and perceived repertoire adequacy of users across different SVOD repertoire types.

Pengaruh Distrupsi Digitalisasi Terhadap Preferensi Konsumen: Studi Kasus pada Mahasiswa Tazkia di Pasar Dramaga

The purpose of this research is to analyze the influence of digital disruption on consumer preferences in product or service selection. This study utilizes the Structural Equation Modeling Partial Least Square (SEM-PLS) model. The results indicate that digital disruption significantly affects consumer preferences. Changes in consumer behavior triggered by digital advancements, such as the ease of shopping through online platforms, are crucial factors influencing consumer preferences. However, in this context, the influence of price on consumer preferences is not significant. Although important, price is not the primary factor in purchasing decisions, as other factors such as product quality, service, and halal labeling have a greater influence. Halal certification is also an important consideration for consumers, as it reflects values of halalness and cleanliness that are deemed important. This study provides valuable insights for businesses in understanding the impact of digital disruption on consumer behavior and implementing appropriate marketing strategies to enhance consumer preferences.

Two-stage optimization of computation offloading for ICN-assisted mobile edge computing in 6G network

This paper investigates QoS-aware computation offloading issues for mobile edge computing in the 6G network. To minimize the end-to-end delay, we harness the Information-Centric Network (ICN) to ensure resource-constrained mobile user offloading computation-sensitive tasks in a distributed manner. Then, a two-stage approach based on a Multi-Agent Reinforcement Learning (MARL) algorithm entwined with optimization-embedding offloading ratio is proposed to enhance server selection for load balancing. Numeral results demonstrate that, with reference to a workshop-scale scenario, the proposed method can achieve outperformed performance in reducing delay and balancing loads on edge servers than the other four baseline schemes.

Research on the Evolution Trend and Characteristics of Policy Tool Selection for Urban and Rural Community Services

Research on the Evolution Trend and Characteristics of Policy Tool Selection for Urban and Rural Community Services

Predictive digital twin driven trust model for cloud service providers with Fuzzy inferred trust score calculation

Cloud computing has become integral to modern computing infrastructure, offering scalability, flexibility, and cost-effectiveness. Trust is a critical aspect of cloud computing, influencing user decisions in selecting Cloud Service Providers (CSPs). This paper provides a comprehensive review of existing trust models in cloud computing, including agreement-based, SLA-based, certificate-based, feedback-based, domain-based, prediction-based, and reputation-based models. Building on this foundation, we propose a novel methodology for creating a trust model in cloud computing using digital twins for CSPs. The digital twin is augmented with a fuzzy inference system, which computes the trust score of a CSP based on trust-related parameters. The architecture of the digital twin with the fuzzy inference system is detailed, outlining how it processes security parameter values obtained through penetration testing mechanisms. These parameter values are transformed into crisp values using a linear ridge regression function and then fed into the fuzzy inference system to calculate a final trust score for the CSP. The paper also presents the outputs of the fuzzy inference system, demonstrating how different security parameter inputs yield various trust scores. This methodology provides a robust framework for assessing CSP trustworthiness and enhancing decision-making processes in cloud service selection.

Weight assignment in cloud service selection based on FAHP and rough sets

Cloud computing is becoming the most widely used technology as the next-generation platform for conducting business. Many cloud providers offer the same functionalities, but have different quality of service (QoS) attributes. Thus the selection of cloud services, which meets the user-desired QoS requirements, has become increasingly complex. In this paper, we present a method that integrates both subjective and objective weights for evaluating the cloud services. This method is based on rough set theory and a proposed extended version of Fuzzy Analytic Hierarchy Process (FAHP) and takes into consideration the trust level associated with the experts, whose evaluations are considered in the calculation of subjective weights, and the preferences of the end user.

Pengembangan Aplikasi Mobile untuk Peningkatan Layanan Kesehatan di Klinik Menggunakan Metode Waterfall: Studi Kasus Klinik XYZ

In this digital era, patients expect ease of access and transparency in healthcare services. Klinik XYZ, currently using conventional methods, faces challenges in meeting these expectations, such as long queues, incomplete information, and difficulties in scheduling appointments with doctors. This study aims to develop a mobile application to enhance service quality at Klinik XYZ. The method used is Waterfall, involving the stages of needs analysis through observation and interviews, system design, coding, and testing. The findings show that the developed application can provide essential features such as doctor profiles, doctor schedules, appointment scheduling, service selection, ratings, news, and health tips. This application successfully improves the efficiency and quality of services at Klinik XYZ by reducing waiting times and providing a better user experience. The implications of this study indicate that integrating mobile technology into healthcare services can significantly enhance patient satisfaction and the operational effectiveness of the clinic. Arifin, M. N., & Siahaan, D. (2020). Structural and Semantic Similarity Measurement of UML Use Case Diagram. Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, 11(2), 88. https://doi.org/10.24843/lkjiti.2020.v11.i02.p03 Febriyanti, N. M. D., Sudana, A., & ... (2021). Implementasi Black Box Testing pada Sistem Informasi Manajemen Dosen. Jurnal Ilmiah …, 2(3). http://download.garuda.kemdikbud.go.id/article.php?article=3457876&val=30165&title=Implementasi Black Box Testing pada Sistem Informasi Manajemen Dosen Haerani, R., Hendriyati, P., Nugroho, P. A., & Lukman, M. (2023). Waterfall Model Implementation in Information Systems Web Based Goods Delivery Service. JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 9(3), 501–508. https://doi.org/10.33330/jurteksi.v9i3.2267 Lee Ventola, C. (2014). Mobile devices and apps for health care professionals: Uses and benefits. P and T, 39(5), 356–364. Luxton, D. D., Kayl, R. A., & Mishkind, M. C. (2012). MHealth data security: The need for HIPAA-compliant standardization. Telemedicine and E-Health, 18(4), 284–288. https://doi.org/10.1089/tmj.2011.0180 Martínez-Pérez, B., De La Torre-Díez, I., & López-Coronado, M. (2013). Mobile health applications for the most prevalent conditions by the world health organization: Review and analysis. Journal of Medical Internet Research, 15(6). https://doi.org/10.2196/jmir.2600 Nurbaiti Oktaviani, S., Fikri Aziz, C., & Maula Sulthon, B. (2022). Analisa UI/UX Sistem Informasi Penjualan Berbasis Mobile Menggunakan Metode Prototype. KLIK: Kajian Ilmiah Informatika Dan Komputer, 2(6), 225–233. https://doi.org/10.30865/klik.v2i6.401 Rambe, B. H., Pane, R., Irmayani, D., Nasution, M., Munthe, I. R., Ekonomi, F., & Bisnis, D. (2020). UML Modeling and Black Box Testing Methods in the School Payment Information System. Jurnal Mantik, 4(3), 1634–1640. https://iocscience.org/ejournal/index.php/mantik

How to optimize service-oriented cloud manufacturing

Within the context of Industry 4.0, service-oriented cloud manufacturing has emerged as a paradigm of significant interest, noted for enhancing manufacturing efficacy through integration, flexibility, and customization. The challenges of service selection and optimization, alongside transportation optimization, are pivotal for the effective implementation of service-oriented cloud manufacturing. This study explores an integrated problem that incorporates both sequential and parallel structures. To address this intricate issue, a binary-integer programming model is proposed, aiming to minimize the cumulative costs, including both manufacturing and transportation expenses. The validity and effectiveness of the proposed model are demonstrated through a real-world case study in mold manufacturing. Analysis of the experimental results provides managerial insights, which could inform the implementation and improvement of service-oriented cloud manufacturing strategies.