Unreliable Service Research Articles

The Coupling Coordination Relationship and Driving Factors of the Digital Economy and High-Quality Development of Rural Tourism: Insights from Chinese Experience Data

Globally, rural tourism development faces challenges such as inadequate infrastructure, insufficient marketing resources, and unreliable service quality, all of which limit its potential. However, digital technology offers unprecedented opportunities to address these barriers. China’s experience in integrating digital technology into rural tourism provides a valuable case study for understanding the digitalization of rural tourism. This study constructs an index system to assess the coupling coordination relationship between the digital economy and the high-quality development of rural tourism (HQDRT). By employing methods such as the entropy method, coupling coordination degree model, obstacle factor model, and geographic detector, the study examines the evolution of this coupling coordination relationship and its driving mechanisms across 31 provinces (including regions and municipalities) in China from 2012 to 2021. The findings reveal that (1) The development of the digital economy generally lags behind that of the rural tourism, but the coupling coordination relationship between the two is steadily improving. (2) The level of coupling coordination increases from west to east, with spatial distribution patterns evolving from ‘antagonism’ to ‘adaptation’ and then to ‘coordination’ as they move eastward. Most provinces belong to the ‘adaptation’ type. (3) From a nationwide perspective, the primary obstacles impeding the development of the digital economy include an insufficient internet penetration rate, which consequently leads to underdeveloped internet finance development and telecommunications industry development. The major barriers to the HQDRT stem from an inadequate number of tourists and a lack of physical infrastructure. (4) Population density, consumer spending, and R&D are significant drivers of the coupling coordination relationship, with the interaction between urbanization rates and other factors generally weakening the degree of coupling.

Revolutionizing the Rental Services in Siargao Island: Basis for Developing an Online Vehicle Rental Management System

The research paper addresses the inefficiencies faced by tourists and local rental service providers in the vehicle rental sector of Siargao Islandin the Philippines. Despite the thriving tourism industry in the island, the current manual processes for vehicle rentals are fraught with challenges such as unreliable service, booking difficulties, and inefficient fleet management. This study aims bridge the gap between these traditional practices and modern technological solutions by proposing an online vehicle rental management system designed to streamline operations and enhance customer experience. Using a mixed-methods approach, the exploration integrates qualitative insights from ethnographic studies and interviews while quantitative data from the surveys targeting tourists, residents, and rental service providers. This methodology enables a thorough understanding of the operational challenges and user needs within the rental ecosystem. The findings revealed significant inadequacies in manual booking thus highlighting a strong demand for an automated and user-friendly online platform. The proposed system incorporates advanced system software to automate bookings, optimize fleet management, and provide real-time updates and notifications by enhancing operational efficiency, reducing errors, and improving service reliability. Additionally, it seeks to empower local rental businesses through provision with tools to manage their operations more effectively and compete in the digital age. The research underscores the potential of the proposed system to revolutionize rental services in Siargao Island by improving accessibility, convenience, and customer satisfaction. The future implementation of this online platform is expected to contribute significantly to the sustainable growth of Siargao's tourism industry, ultimately benefiting tourists, local businesses, and the broader community

Good Governance, Public Service Delivery and Public Trust: Case of Banadir Regional Administration of Somalia

This paper aimed to assess the good governance practices in the Benadir Regional Administration (BRA) of Somalia and how they affect public service delivery and public trust. The paper utilized primary data obtained from the 157 respondents. The study reveals that BRA's inadequate governance practices lead to poor transparency, accountability, and a high prevalence of corruption due to incompliance with rules and regulations. Results also indicate that the public is dissatisfied with BRA leadership due to inefficient and unreliable service and lack of transparency in public funds utilization and management, resulting in a negative perception of BRA. The paper concluded that enhancing good governance practices and improving public service delivery can improve public trust. The article asserts that good governance, characterized by transparency, accountability, participation, rule of law, and equity, is the foundation of development and prosperity. The article emphasizes the importance of efficient public service delivery as a vital link between government and the public, fostering trust and sustainable development. Therefore, the paper suggests that BRA should improve its governance practices by adhering to laws and regulations, fostering a corruption-free environment, and implementing effective performance monitoring and control mechanisms. It also recommends investing in human resources, streamlining processes, prioritizing citizen-centricity, adopting technology, and fostering data-driven decision-making.

Quasi and metaheuristic optimization approach for service system with strategic policy and unreliable service

Quasi and metaheuristic optimization approach for service system with strategic policy and unreliable service

ENHANCING SERVICE DISCOVERY IN MOBILE AD HOC NETWORKS USING SEMANTIC CLUSTERING AND HYBRID TRUST MANAGEMENT

Mobile Ad Hoc Networks (MANETs) facilitate communication among mobile devices without relying on fixed infrastructure. However, service discovery in MANETs faces challenges due to the dynamic topology and limited resources of nodes. Existing solutions often lack efficient resource utilization and fail to address trust management adequately. The conventional approaches for service discovery in MANETs are inefficient due to their inability to incorporate semantic clustering and robust trust management. Semantic clustering enhances the accuracy of service discovery by grouping nodes based on similar interests or functionalities. Meanwhile, traditional trust management mechanisms are inadequate in dynamic environments, leading to unreliable service discovery results. The proposed methodology involves developing a semantic clustering algorithm to organize nodes based on their semantic similarities. Additionally, a hybrid trust management system is implemented to assess the reliability of discovered services. The system combines both reputation-based and recommendation-based trust models to enhance the accuracy of trust evaluations. Through extensive simulations and experiments, the effectiveness of the proposed approach is demonstrated. The results indicate that the integration of semantic clustering and hybrid trust management significantly improves service discovery efficiency and reliability in MANETs. The approach achieves higher precision and recall rates compared to conventional methods, even under dynamic network conditions.

The Impact of Privatization of the Power Sector on the Economy in Nigeria 2013-2022

This study explores the impact of Privatization of the Power Sector on the Economy in Nigeria and proposes strategies to enhance efficiency and sustainability. The findings, based on data collected through a semi-structured interviews from various stakeholders, reveal diverse perspectives on the performance of privatization reforms. While some stakeholders acknowledge improvements in electricity supply, others highlight the loss of benefits. Challenges faced by the power sector after privatization include insecurity, vandalization of equipment, imbalance in load distribution, outdated infrastructure, and unreliable service delivery. The evaluation of privatization on electricity tariffs and the economy shows mixed views, with some stakeholders expressing dissatisfaction and others noting positive impacts on business performance. Strategies for improvement include government intervention, improved infrastructure, customer engagement, fair distribution of prepaid meters, anti-corruption measures, training and expertise. Implementing these recommendations can enhance the efficiency and sustainability of the power sector, supporting economic growth and development in Nigeria. The study emphasizes the crucial role of the power sector in the economy and highlights the need for collaboration among stakeholders for a robust and reliable power supply system.

Investigating the changes in travel behaviour during an economic crisis in a developing country: A case study of the Greater Beirut Area, Lebanon

Lebanon is currently facing one of the worst economic crises in its history, which has been compounded by the economic consequences of the COVID-19 pandemic and the devastating explosion at the Port of Beirut in August 2020. This research focuses on the Greater Beirut area in Lebanon, aiming to examine the impact of the ongoing economic crisis on travel behavior. The study analyzes changes in travel behavior before and during the crisis for various trip purposes, including the number of trips and modes of transportation used. Socio-economic factors that may have influenced these changes are also considered. Descriptive analyses and multivariate statistics reveal that the economic crisis had a significant influence on people's travel behavior. Multinomial logistic regression models highlight the impact of factors such as age, nationality, occupation, household size, income, and spending fluctuations on trip frequency changes during the crisis. The analysis of the data indicates a decrease in all trip types during the crisis, partly due to the adoption of online study and work, resulting in fewer commuting trips. Private car usage declined for shopping trips, while motorcycles and public transport witnessed an increase. Recreational trips reduced significantly, with more respondents opting for fewer trips per year, showing a noticeable preference for buses. Despite the shift away from private cars, the adoption of public transport remains modest, partly due to limited accessibility, safety concerns, and unreliable services.

Schedule-based transit assignment with online bus arrival information

Most public transportation services deviate from their published schedule. To cope with the delay caused by the unreliable service, passengers use online information about the bus arrival time which affects their route choice behavior. Current schedule-based transit assignment models fail to capture the passengers’ adaptive response to unreliable service, resulting in an inaccurate estimation of passenger wait time and passenger loads on various transit routes. The current study proposes schedule-based transit assignment models that incorporate online bus arrival information when modeling the passenger route choice in a stochastic and time-dependent transit network. The authors propose that passengers employ strategies when traveling between different origin–destination pairs not only due to the limited capacity of vehicles but also to cope with the transit delay. The passenger routing problem is modeled as a Markov Decision Process, and efficient algorithms are developed to solve this problem. Depending on the vehicle capacity, two types of assignment models are presented, namely, uncapacitated and capacitated assignments. When penalties for arriving at the destination outside the desired arrival time window are not applied, the uncapacitated assignment problem is formulated as a linear program. On the other hand, the capacitated assignment is formulated as a variational inequality problem for which an efficient Method of Successive Averages-based heuristic solution algorithm is proposed. Computational experiments are presented for a small and a large schedule-based transit network. The results show that denied boarding in an unreliable network leads to higher expected costs to passengers compared to the reliable and uncongested network. Furthermore, the analysis shows that the strategies evaluated with reliable schedule assumption lead to unreliable paths in the network and produces more transferring flow than should happen in practice. The application of our method to a subnetwork of the Twin Cities transit network with artificial demand reveals that passengers traveling from a residential area to the University of Minnesota campus may prefer taking a path with transfer in the event of highly unreliable transit service on the direct routes.

A Privacy-Preserving Time-Aware Method for Next POI Recommendation

Compared with traditional point-of-interest (POI) recommendation, next POI recommendation is more difficult and requires comprehensive consideration of users’ behavior patterns, spatial–temporal context, and other information. In addition, unreliable service providers may disclose the privacy of users when providing recommendation services. For next POI recommendation, a privacy-preserving time-aware recommendation method (PPTA-RM) is proposed in this paper. The PPTA-RM method is based on centralized differential privacy and combines coarse-grained recommendation with fine-grained recommendation. At the coarse-grained level, the users’ POI category preference is modeled by improved matrix factorization and predicted by singular spectrum analysis (SSA), and gradient perturbation is carried out during the matrix factorization process to protect the POI category preference of users. At the fine-grained level, the users’ POI preference is modeled and predicted by an improved hyperlink-induced topic search (HITS) algorithm, which considers the weighted combination of users’ social attributes and POI geographic distance attributes, and a privacy budget allocation strategy considering the visit count of POIs is designed to add Laplace noise to the check-in data of users. The experimental analysis on two real datasets shows that the proposed method improves F1-Score@10 by 0.4–21.8% under different privacy budgets, which validates that the proposed method holds the next POI recommendation accuracy better while preserving the user’s privacy.

Impacts of electricity quality improvements: Experimental evidence on infrastructure investments

Hundreds of millions of households depend on electricity grid connections providing low quality and unreliable services. Understanding the impacts of and consumer response to electricity quality improvements is important for development and the environment. We investigate this in the Kyrgyz Republic through randomized improvements in the grid, which can improve electricity service quality. Treated households experience significantly fewer voltage fluctuations per day, an indicator of improved electricity quality post-intervention. Treated households’ billed consumption of electricity services increased during peak months post-intervention, with increases in consumption of 4% and 18% for homeowners and renters, respectively. Consistent with this, treated households, particularly renters, significantly increased ownership of electric heaters. Treated households invested more in energy efficiency, potentially mitigating their electricity bill increases post-intervention.

Achieving optimal resource utilization in industrial environments: Combining polling methods and an exhaustive service discipline with an unreliable service

Achieving optimal resource utilization in industrial environments: Combining polling methods and an exhaustive service discipline with an unreliable service

Rescheduling Unreliable Service Providers in a Dynamic Multi-objective Cloud Manufacturing

Rescheduling Unreliable Service Providers in a Dynamic Multi-objective Cloud Manufacturing

A novel privacy protection scheme for internet of things based on blockchain and privacy set intersection technique

In the era of big data, an ocean of data generated by Internet of Things (IoT) devices will be analyzed and processed by cloud computing. However, outsourcing of data can lead to leakage of user privacy to those unreliable service providers. In this paper, we propose a novel privacy-preserving scheme for IoT device by employing privacy set intersection (PSI) and blockchain technique to achieve data privacy. First, a homomorphic encryption PSI technique based on 0-1 encoding is proposed, which well hides the set base to ensure data privacy. Second, combining blockchain structure and smart contract, the proposed scheme can improve the efficiency of data sharing by storing the shared data on a blockchain. Third, the security analysis shows that the scheme has extremely high control over the individual data and can ensure the security and privacy of the data. Finally, we compare the functionality with other relevant schemes and demonstrate that our scheme functions well with low communication and computational overhead.

Beyond technical: delineating factors influencing recycled water acceptability

ABSTRACT Globally, demand for water resources is projected to increase due to climate change and population growth. In many developing contexts, water demand already far exceeds supply and alternatives are already required. Recycled water is increasingly seen as a source of alternative water supply to plug demand-supply gaps. This study examined the factors that influence recycled water acceptance amongst residents of Accra, Ghana. We found that irrespective of the technical specifications on water quality, consumers were only willing to use recycled water for some purposes due to low levels of trust in water service providers because of their inefficiencies and unreliable service provision. Cultural beliefs relating to human waste and the ingestion of waste underlines peoples’ acceptability of recycled water. Thus, future water reuse planning must include community engagement at the planning stage to create the level of trust needed for reuse acceptability.

Asymptotic Diffusion Analysis of Retrial Queueing System M/M/1 with Impatient Customers, Collisions and Unreliable Servers

In this paper, a retrial queueing system of the M/M/1 type with Poisson flows of arrivals, impatient customers, collisions, and an unreliable service device is considered. To make the problem more realistic and, hence, more complicated, we include the breakdowns and repairs of the service in this research study. The retrial times of customers in the orbit, service time, impatience time of customers in the orbit, server’s lifetime (depending on whether it is idle or busy), and server recovery time are supposed to be exponentially distributed. The problem of finding the stationary probability distribution of the number of customers in orbit is solved by using the method of asymptotic diffusion analyses under the condition of a heavy load of the system and the patience of customers in orbit. Numerical results are presented that demonstrate the effectiveness of the obtained theoretical conclusions, and a comparative analysis of the method of asymptotic analysis and the method of asymptotic diffusion analysis for the considered problem is given.

Fuzzy analysis of a queueing system featuring an unreliable service provider and geometric arrivals by incorporating constant retrial policy and delayed threshold recovery

Fuzzy analysis of a queueing system featuring an unreliable service provider and geometric arrivals by incorporating constant retrial policy and delayed threshold recovery

Examining the Factors that Impact Public Transport Commuting Satisfaction

The first objective of this research was to examine the level of stress caused by commuting into Dublin city centre. The second objective was to determine the value placed on the comfort and reliability of public transport services. An on-line survey of workers who commute daily into Dublin city centre was conducted, which collected data on the respondents’ typical commute, commute-related stress, and socio-economic background. Commute satisfaction levels among public transport users were found to decrease for those who travel on crowded or unreliable services and those who have long wait-times. Stated preference scenarios relating to crowding and reliability were analysed using a multinomial logit model. The model showed that utility derived increases as crowding decreases and as reliability increases.

Multicolor Licklider Transmission Protocol: An LTP Version for Future Interplanetary Links

The Licklider Transport Protocol (LTP) is the “convergence layer” of choice in Interplanetary networks based on Delay-/Disruption-Tolerant architecture. It was designed for long-delay scheduled-intermittent links, offering either a reliable or an unreliable service, with “red” and “green” parts, respectively. The aim of this article is to present multicolor LTP, an LTP version consisting in a series of enhancements of which the most significant are the use of monochrome sessions, the introduction of an additional orange color offering a “notified” service, and the definition of default link colors. After a thorough examination of basic LTP mechanisms for all color variants, this article discusses two scenarios where orange seems particularly appealing: video streaming and optical interplanetary links. Numerical results offer further insight into the complex LTP mechanisms and also highlight the difference between LTP retransmissions and bundle protocol retransmissions, the latter benefitting from routing reprocessing. Multicolor LTP has already been implemented as an interplanetary overlay network (ION) plug-in and its enhancements have been proposed to Consultative Committee for Space Data Systems Space Internetworking Services Delay-/Disruption-Tolerant Networking working group for a possible inclusion in the next version of LTP specifications (LTPv2).

State monopoly on urban transport system and human (in)security in Harare during the COVID-19 pandemic

ABSTRACT This study discusses the human security costs and benefits generated by the coronavirus (COVID-19) pandemic-induced state monopoly on the urban public transport system in Zimbabwe through the Zimbabwe United Passenger Company (ZUPCO) since March 2020. Using empirical evidence from Harare, it argues that the ZUPCO initiative had far-reaching safety and security implications on urban residents’ lives during the COVID-19 pandemic. The study found that though the ZUPCO initiative mainly benefited commuters through affordable fares, it had many human security costs. The costs included reduced safety and decreased and unreliable services, which exposed the commuting public to the risk of contracting COVID-19 and other security challenges. The state monopoly on urban transport exacerbated the social and economic impact of COVID-19, promoted inequalities, police corruption and urban residents’ use of informal transport services, which were unsafe and costly. The study concludes that the Zimbabwean government lacks the capacity to provide services in the urban transport sector, akin to nearly every sector in the country. As a stop-gap measure, the government is encouraged to regulate and allow private players to complement its efforts for the benefit, convenience, security, and safety of commuters until it develops an efficient urban public transport system.

ANALYSIS OF THE FINANCIAL STATUS OF COMMERCIAL BANKS

This article reveals the need to study the financial position of the bank, the results of which can be used to justify the decisions of regulatory authorities. The financial position of commercial banks in Kyrgyzstan is being investigated, as the results of the financial position survey warn consumers against using unreliable banking services. The Bank strives to give an objective assessment of the current and future situation. Recent events in the world, especially the situation with the pandemic, require an analysis of the financial situation of commercial banks. In modern, more competitive conditions, bank employees and customers need reliable information about the financial condition of the bank, financial stability trends, liquidity and factors affecting its change. The effectiveness of commercial banks also depends on the ability to conduct business based on the analysis of information and comparison with other banks.