Fair Service Research Articles

Increasing clinical medical service satisfaction: An investigation into the impacts of Physicians’ use of clinical decision-making support AI on patients’ service satisfaction

BackgroundThe medical industry is one of the key industries for the application of artificial intelligence (AI). Although it is believed that the combination of CDSS and physicians could improve the medical service, there are still many concerns about the usage of CDSS. Based on these concerns, limited studies have answered the question that when a physician makes decision independently or with AI’s help, will there be any differences in patients’ satisfaction with the medical service? MethodsThis study uses the service fairness theory as a theoretical lens and employs three vignette experiments to address this research gap. There are totally 740 subjects recruited to participate into the three experiments. Group comparison methods and structural equation model are used to verify the hypotheses. ResultsThe experimental results reveal that: (1) physicians using AI can reduce patients’ service satisfaction (Mdifference=0.404,p=0.004); (2) the negative relationship between AI usage and service satisfaction can partially be mediated through distributive fairness and procedural fairness; (3) physicians actively informing their patients about the usage of AI can help mitigate the reduction in service satisfaction (Mdifference=0.400,p=0.003) and three types of fairness Mdifferencedistributive=0.307,p=0.042;Mdifferenceprocedural=0.483,p<0.001;Mdifferenceinteractional=0.253,p=0.027. ConclusionThis study investigates the effect of physicians using decision-making support AI on their patients’ service satisfaction. These results contribute to the existing literature pertaining to AI and fairness theory, and also help in formulating some practical suggestions for medical staff and AI development companies.

The Moderating Role of Trade Shows Participation Cost Between Service Quality and Participant Loyalty: Findings from the Pilot Study

Success in business-to-business sales and marketing depends on a number of factors. Trade shows give clients and stakeholders the chance to interact directly, which is a more effective method of engagement. In the current research, surveys and analyses of empirical studies and models related to participant loyalty, service quality, and the moderating effect of participation cost at Jordanian trade shows are presented. Based on Cronbach's alpha coefficient test, the results show that all of the measures were very reliable, with coefficients ranging from 0.828 to 0.961 and no appreciable departure of skewness values from zero. Also, the study's findings showed that loyalty is significantly influenced by service quality and the expense of attending trade events. The model presented in this paper makes a substantial contribution to the relationship marketing literature by experimentally examining Jordanians' perceptions on their relationships with trade fair service providers.

COMMUNITY SATISFACTION LEVEL IN RECEIVING RECOMMENDATION SERVICES JKMM (HEALTH INSURANCE FOR THE POOR) AT THE SOCIAL SERVICE SIDOARJO REGENCY

Service satisfaction is the result of public opinion and evaluation of the performance of services provided by public service providers. Community Satisfaction Index (IKM) is data and information about the level of community satisfaction obtained from quantitative and qualitative measurement results of public opinion in obtaining services from public service providers and comparing their expectations and needs. This study analyzes the influence of service as a factor that influences people's satisfaction. According to Kepmen PAN No. 25 of 2004 concerning the Community Satisfaction Index (IKM), there are 14 matters related to the performance and services performed by service officers, including service procedures, suitability of requirements, employee clarity, employee discipline, employee responsibility, employee capabilities, service speed, service fairness, employee courtesy, cost fairness, cost certainty, schedule certainty, environmental comfort, and service security. This research was conducted to analyze the value of these variables, as well as their influence on community satisfaction. Community satisfaction is very influential in the field of services at the Sidoarjo Regency Social Service in managing the JKMM (Health Insurance for the Poor) recommendation letter. The quality of service at the Sidoarjo Regency Social Service is one of the important factors in utilizing the JKMM recommendation letter service at the Sidoarjo Regency Social Service.

Joint Optimization of Service Fairness and Energy Consumption for 3D Trajectory Planning in Multiple Solar-Powered UAV Systems

In this paper, we study the three-dimensional (3D) trajectory optimization problems of unmanned aerial vehicles (UAV) with a solar energy supply, aiming to provide communication coverage for mobile users on the ground. In general, the higher UAVs fly, the more solar energy they collect, but the smaller the range of coverage they could achieve, and vice versa. How to plan optimal trajectories for UAVs so that more users can be encompassed, while allowing UAVs to collect enough solar energy, is a challenging issue. Moreover, we also consider how geographically fair coverage for each ground user can be achieved. To solve these problems, we designed a multiple solar-powered UAV (SP-UAV) energy consumption model and a fairness model, while designed an observation space, state space, action space, and reward function. Then, we proposed a multiple SP-UAV 3D trajectory optimization algorithm based on deep reinforcement learning (DRL). Our algorithm is able to balance the energy consumption of UAVs to extend the system’s lifetime, while avoiding both collisions and flying out of communication range. Finally, we trained our model through simulation experiments and conducted comparative experiments and analysis based on real network topology data. The results show that our algorithm is superior to the existing typical algorithms in coverage, fairness, and lifetime.

Effects of and Prospects for the Hierarchical Medical Policy in Beijing, China.

Hierarchical medical policies are widely used worldwide to reduce healthcare costs, rationalize the use of healthcare resources, and improve accessibility and fairness of healthcare services. However, few case studies have evaluated the effects and prospects of such policies. Medical reform efforts in China have distinct goals and characteristics. Therefore, we investigated the effects of a hierarchical medical policy in Beijing and assessed the future potential of the policy to yield insights for other countries, especially developing countries. Different methods were used to analyze multidimensional data from official statistics, a questionnaire survey of 595 healthcare workers from 8 representative public hospitals in Beijing, a questionnaire survey of 536 patients, and 8 semi-structured interview records. The hierarchical medical policy had strong positive effects on improving access to healthcare services, balancing the workload of healthcare workers in various levels of public hospitals, and improving the management of public hospitals. The remaining obstacles include severe job stress among healthcare workers, the high cost of some healthcare services, and the need for improvement in the development level and service capacity of primary hospitals. This study provides useful policy recommendations regarding the implementation and extension of the hierarchical medical policy, including the need for governments to improve the hospital assessment system and for hospitals to actively participate in developing medical partnerships.

Fair multigroup multicast precoding design based on traffic demands for multibeam satellite systems

Onboard resources are limited for multibeam satellite communication systems, while differences exist in traffic demands among users. Since conventional multigroup multicast precoding methods do not take traffic demands for users into consideration, it is difficult to flexibly adjust the offered throughput to users’ demands. Users with higher demand may obtain lower throughput while users with lower demand may be over-satisfied, which results in the requested-offered throughput mismatch and resource waste. This paper proposes a fair multigroup multicast precoding design based on traffic demands. To obtain the precoding design, the optimization problem aimed at maximizing the minimum throughput satisfaction ratio, which is defined as the ratio of the offered throughput to the traffic demand, is formulated, so as to provide fair service for all users while satisfying per-feed power constraints and traffic demand constraints. To address this problem, an auxiliary variable is first introduced to equivalently simplify it. Then, the semidefinite relaxation and the bisection search strategies are adopted to further handle the problem. Finally, the optimal precoding vectors are obtained by employing eigenvalue decomposition or Gaussian randomization. Simulation results indicate the effectiveness of the proposed precoding algorithm and demonstrate that it can better adapt to the scenarios with different traffic demands.

Regional differences in primary healthcare utilization in Java Region-Indonesia.

Policymakers must understand primary healthcare utilization disparity to minimize the gap because they must seek fair service for every citizen. The study analyzes regional differences in primary healthcare utilization in Java Region-Indonesia. The cross-sectional research analyzes secondary data from the 2018 Indonesian Basic Health Survey. The study setting represented Java Region-Indonesia, and the participants were adults 15 years or more. The survey explores 629,370 respondents. The study used primary healthcare utilization as an outcome variable and province as the exposure variable. Moreover, the study employed eight control variables (residence, age, gender, education, marital, employment, wealth, and insurance). The study evaluated data using binary logistic regression in the final step. People in Jakarta are 1.472 times more likely to utilize primary healthcare than those in Banten (AOR 1.472; 95% CI 1.332-1.627). People in Yogyakarta are 1.267 times more likely to use primary healthcare than those in Banten (AOR 1.267; 95% CI 1.112-1.444). In addition, people in East Java are 15% less likely to utilize primary healthcare than those in Banten (AOR 0.851; 95% CI 0.783-0.924). Meanwhile, direct healthcare utilization was the same between West Java, Central Java, and Banten Province. They are sequentially starting from the minor primary healthcare utilization: East Java, Central Java, Banten, West Java, Yogyakarta, and Jakarta. Disparities between regions exist in the Java Region-Indonesia. They are sequentially starting from the minor primary healthcare utilization: East Java, Central Java, Banten, West Java, Yogyakarta, and Jakarta.

Utilization and performance of long-term care system for older people with disabilities and dementia in Zhejiang Province, China.

To explore changes in performance, weaknesses, and utilization of the long-term care (LTC) system for older people with disabilities and dementia (OPWDD) in Zhejiang Province, China, thereby providing a reference for decision-making amid a progressively aging population. A performance evaluation model of the LTC system for OPWDD was constructed using three dimensions: input, process, and outcome. Performance indicators and trends were calculated based on data collected from statistical yearbooks, documents, and work reports of the Bureau of Statistics and other government departments in Zhejiang Province, China, published in 2015-2021. Significant improvements were observed in most LTC performance indicators for OPWDD, such as input, process, and outcome, with notable enhancements in fairness, accessibility, and affordability of LTC services. By 2021, there were 6.20 nursing and rehabilitation beds in medical institutions and 3.77 general practitioners per 1,000 people aged 65 and above, up 144.14% and 13.73%, respectively, from 2015. The rate of health management for older people was 70.91%, representing a 10.33% increase from 2015. The actual reimbursement ratio of hospitalization expenses covered by basic medical insurance for older people rose 7.05%, from 72.76% in 2015 to 77.89% in 2021. Social security satisfaction rose 12.4%, from 71.3% in 2015 to 83.7% in 2021. Certain indicators, however, showed no significant improvement and tended to decline, such as the number of beds at older care institutions and caregivers per 1,000 people aged 65 and over. It is imperative to further balance the allocation of care resources, using a people-centered and integrated LTC system. The proportion of rehabilitation and nursing beds for older people should be consistently increased to effectively alleviate the shortage of care beds. Furthermore, a talent incentive policy should be improved to train caregivers and provide whole-person and whole-life course care based on OPWDD needs.

Community home elderly care services, multidimensional health and social participation of chronically ill elderly-Empirical analysis based on propensity score matching and multiple mediation analysis.

In recent years, China's aging process has deepened rapidly, the disease spectrum of the population has undergone major changes, the proportion and scale of elderly patients with chronic diseases are growing rapidly, and the multidimensional health problems of the chronically ill elderly are prominent, seriously affecting the participation of the chronically ill elderly in family, community, and social development. In response, China has implemented the "active response to population aging strategy," accelerated the development of community home elderly care services, and encouraged the chronically ill elderly to continue to play a role through social participation. So how does the community-based home-based medical care service affect the social participation of the chronically ill elderly? Is an important subject. Based on the 2018 China Longitudinal Aging Social Survey and the propensity score matching method to measure the impact of community home elderly care services on the four types of social participation of chronically ill elderly, including economic participation, family participation, voluntary participation, and political participation, and group differences, and uses the multiple mediation analysis method to explore the mechanism and effect of community home elderly care services on the four types of social participation of chronically ill elderly. (1) Community home elderly care services have an asymmetric impact on the social participation of the chronically ill elderly, and have generally promoted the level of social participation of the chronically ill elderly. (2) Community home elderly care services change the social participation arrangements of the chronically ill elderly by driving and inhibiting effects, so that it has a tendency to reduce economic participation and increase voluntary participation and political participation as a whole. This feature shows group differences among the chronically ill elderly of different ages, education levels, living arrangements and community types. (3) Community home elderly care services have an asymmetric impact on various social participation of the chronically ill elderly through the multidimensional health mediation mechanism. (1) With the continuous deepening of the interweaving between the growth of chronic diseases and the aging of the population in China, the development of a positive aging society must attach great importance to the important role of social participation for the chronically ill elderly. (2) Strengthen the development of physical, psychological, and social adaptation and other health abilities of the chronically ill elderly, shape their awareness of social participation, and give the chronically ill elderly a reasonable social role orientation. (3) Through policy incentives, promote the realization of fairness, justice, adequacy, and sustainability of community home elderly care services. (4) Pay special attention to the penetration, integration, and application of digital technology into the field of community home elderly care services to effectively protect the health of chronically ill elderly, ensure that the elderly with different chronic diseases participate in social activities of high quality, enjoy a high-quality happy life, and promote the high-quality development of the aging society.

FAIR data and metadata: GNSS precise positioning user perspective

ABSTRACTThe FAIR principles of Wilkinson et al. [1] are finding their way from research into application domains, one of which is the precise positioning with global satellite navigation systems (GNSS). Current GNSS users demand that data and services are findable online, accessible via open protocols (by both, machines and humans), interoperable with their legacy systems and reusable in various settings. Comprehensive metadata are essential in seamless communication between GNSS data and service providers and their users, and, for decades, geodetic and geospatial standards are efficiently implemented to support this. However, GNSS user community is transforming from precise positioning by highly specialised use by geodetic professionals to every-day precise positioning by autonomous vehicles or wellness obsessed citizens. Moreover, rapid technological developments allow alternative ways of offering data and services to their users. These transforming circumstances warrant a review whether metadata defined in generic geospatial and geodetic standards in use still support FAIR use of modern GNSS data and services across its novel user spectrum. This paper reports the results of current GNSS users’ requirements in various application sectors on the way data, metadata and services are provided. We engaged with GNSS stakeholders to validate our findings and to gain understanding on their perception of the FAIR principles. Our results confirm that offering FAIR GNSS data and services is fundamental, but for a confident use of these, there is a need to review the way metadata are offered to the community. Defining standard compliant GNSS community metadata profile and providing relevant metadata with data on-demand, the approach outlined in this paper, is a way to manage current GNSS users’ expectations and the way to improve FAIR GNSS data and service delivery for both humans and the machines.

Fairness-aware data offloading of IoT applications enabled by heterogeneous UAVs

With the widespread application of IoT devices, some new scenarios with insufficient coverage of communication infrastructure have arisen, such as wildlife habit monitoring. For these IoT applications, how to efficiently backhaul data collected by IoT devices has become a key technology. As a new data collecting mode for environments lacking communication infrastructure, UAV-enabled data offloading has attracted increasing research interest. Nevertheless, the fairness of data offloading is rarely studied, which directly influences the quality of service. Therefore, we investigate the fairness-aware task scheduling for data offloading enabled by heterogeneous UAVs. To reduce the uncertainty of user status information caused by poor communication, a service time related data arrival rate estimation model is proposed. The fairness-aware heterogeneous UAV-enabled data offloading model is proposed to ensure that all users share system resources fairly. Then, we creatively propose a dynamic incentive-based coordinate descent optimization framework-DISCO, which can progressively improve resource utilization while maximizing service fairness. Besides, we theoretically analyze and experimentally demonstrate its convergence and low time complexity. The performance of DISCO is verified by a series of simulation experiments. Compared with four baseline algorithms, DISCO shows distinct advantages in terms of service fairness, energy efficiency, adaptability and data throughput.

Examining the Indonesia Bureaucracy Response and Problem in Pandemic Times: A Preliminary Diagnostic Study

This investigation was prompted by the conditions of the COVID-19 pandemic, which created very rapid changes in the bureaucratic environment. This initial study is intended to explain how the Indonesian bureaucracy responds to changes due to the pandemic. A literature study is used to aggregate some of the findings of the latest research in Indonesia and official and accountable reports on bureaucratic governance. General results show that the bureaucracy in Indonesia is still stuttering in carrying out its functions. When the public requires quick and fair service, bureaucratic formalism, as an effect of Weberian bureaucracy, finds its contradiction. Still, the response required by the public does not accompany it. Further studies must be initiated to formulate an agile and public-centered bureaucratic model in the post-pandemic era.&#x0D; Keywords: bureaucracy, COVID-19, pandemic

Influence of Lean and Agile Management, Digital Transformation, and Transformational Leadership Toward Performance of Sumedang Government Apparatus

This investigation was prompted by the conditions of the COVID-19 pandemic, which created rapid changes in the bureaucratic environment. This initial study is intended to explain how the Indonesian bureaucracy responds to changes due to the pandemic. A literature study is used to aggregate some of the findings of the latest research in Indonesia and official and accountable reports on bureaucratic governance. General results showed that the bureaucracy in Indonesia is still very stuttering in carrying out its functions. Bureaucratic formalism, as an effect of the Weberian bureaucracy, finds its contradiction when the public needs fast and fair service. Still, the response required by the public does not accompany it. Further studies must be initiated to formulate an agile and public-centered bureaucratic model in the post-pandemic era.&#x0D; Keywords: bureaucracy, COVID-19, pandemic

Time‐space‐power allocation for enhanced IoT‐terminal services in cognitive satellite‐aerial networks

AbstractIn remote and inaccessible areas, the traffic request for Internet‐of‐Things (IoT) terminals is growing. This paper proposes a cognitive satellite‐aerial network (CSAN) to provide sufficient access services. The proposed CSAN consists of the primary beam‐hopping (BH) satellite and secondary aerial‐based station (ABS) systems. Since the two systems share spectrums, co‐channel interference (CCI) between the two systems is complicated, and the quality of service (QoS) is seriously degraded. To improve the QoS, the dynamic BH (DBH) pattern, ABS access in the time domain, and ABS power control in the power domain are studied. First, based on the sparsity of the DBH pattern, the greedy quick tracking (GAT) algorithm is proposed to design the DBH pattern quickly. Then, subject to the DBH pattern, a greedy access monitor (GAM) algorithm is determined for timely ABS access and power control. Since each ABS only serves terminals within a suitable distance, the placement and terminal cluster of multi‐ABSs in the space domain are required to ensure full terminal coverage. Thus, the mutual selection K algorithm is proposed to save required ABS numbers and improve service fairness among terminal clusters. Simulation results demonstrate the efficacy of time‐space‐power allocation for enhanced IoT‐terminal services in the proposed CSAN.

Equalizing service probability in UAV-assisted wireless powered mmWave networks for post-disaster rescue

Unmanned aerial vehicles (UAVs) are widely used in the areas where ground network infrastructure is inadequate (or crippled by accidents and disasters) to provide services for ground user equipments (UEs). However, the existing related works cannot serve ground UEs fairly. Due to the original intention of post-disaster emergency network construction with the highest goal of saving lives, fair access service for ground UEs is particularly important in this scenario. Therefore, we address this problem by jointly optimizing the number of service grids, the flight trajectory and the hovering position of a UAV. Firstly, an adaptive area division and consolidation (AADC) method is proposed to optimize the number of service grids of a UAV. Then, a new fair service policy is designed to plan the UAV flight trajectory. Finally, the hovering position of UAV is optimized in each service grid to improve service efficiency. The simulation results show that the proposed scheme both ensures fairness of services to ground UEs and improves system throughput.

A multi-objective optimization model for outpatient care delivery with service fairness

PurposeOutpatient care delivery is one of the key revenue sources of a hospital which plays a salient role in timely care delivery. The key purpose of the study is to propose a multi-objective simulation-based decision support model that considers the cost of care delivery and patient dissatisfaction as its two key conflicting objectives. Patient dissatisfaction considers service fairness. Patient idiosyncrasies such as no-show, unpunctuality and balking have been considered in the model involving multiple classes of patients.Design/methodology/approachA model has been designed using data collected from field investigations. In the first stage, queuing theory based discrete event simulation model has been developed. Genetic algorithm has been used to solve the scalarized problem and obtain actionable insights. In the second stage, non-dominated sorting genetic algorithm II (NSGA-II) has been involved to achieve the Pareto optimal fronts considering equal priority of the two objectives.FindingsThe computational results considering various parameter settings can help in efficient resource planning while ensuring better care delivery. The model proposed in the study provides structural insights on the business strategy of healthcare service providers on optimizing the dual goals of care delivery cost and service fairness.Originality/valueThe study is one of the early works that helps to improve the care delivery process by taking into consideration the environmental factors as well as service fairness. The study demonstrates the usage of simulation-based multi-objective optimization to provide a more sustainable patient centric care delivery.

An IoT-based residential energy metering and protection system

The fairness of electricity services lies in the provider being able to deliver the expected quality power, and recover the returns on investment. Energy theft, metering lapses, billing errors, and cumbersome payment procedures constitute the bulk of the non-technical power losses and contribute majorly to the incapacity of electricity vendors to run a profitable business and serve customers effectively. A real-time approach has been identified as the innovative need at resolving the enumerated issues within the electricity value chain. This study is leveraging the Internet of Things (IoT) technology to propose an extended modelled system capable of providing real-time data management, residential power system control, and an interactive platform for vendors and consumers. The energy billing was modelled and developed from resourceful components. A website was developed with a user-friendly interface. The unique features of the system design are the possibility of customers loading their electricity credit online, and the supplier being able to lock or disconnect any defaulting customer remotely.

System-Level Analysis of Full-Duplex Self-Backhauled Millimeter Wave Networks

Integrated access and backhaul (IAB) facilitates cost-effective deployment of millimeter wave (mmWave) cellular networks through multihop self-backhauling. Full-duplex (FD) technology, particularly for mmWave systems, is a potential means to overcome latency and throughput challenges faced by IAB networks. We derive practical and tractable throughput and latency constraints using queueing theory and formulate a network utility maximization problem to evaluate both full-duplex (FD)-IAB and half-duplex (HD)-IAB networks. We use this to characterize the network-level improvements seen when upgrading from conventional HD IAB nodes to FD ones by deriving closed-form expressions for (i) latency gain of FD-IAB over HD-IAB and (ii) the maximum number of hops that a HD- and FD-IAB network can support while satisfying latency and throughput targets. Extensive simulations illustrate that FD-IAB can facilitate reduced latency, higher throughput, deeper networks, and fairer service. Compared to HD-IAB, FD-IAB can improve throughput by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times $ </tex-math></inline-formula> and reduce latency by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> for a fourth-hop user. In fact, upgrading IAB nodes with FD capability can allow the network to support latency and throughput targets that its HD counterpart fundamentally cannot meet. The gains are more profound for users further from the donor and can be achieved even when residual self-interference is significantly above the noise floor.

Robust collaborative passenger flow control on a congested metro line: A joint optimization with train timetabling

With the rapid increase in residents in megacities, the passenger demand of metro systems is rising sharply and steadily, bringing immense pressure to train operations. To improve the service quality, this paper discusses systematically investigating a joint optimization of the robust passenger flow control strategy and train timetable on a congested metro line. A deterministic model for train timetabling and passenger flow control at each station is first developed to make a trade-off between operation efficiency and service fairness. Then, the uncertain passenger demand is further considered at each station, and three integer linear programming models are formulated to derive the robust passenger flow control strategies. The first two models are related to the technique of Light Robustness, in which the uncertainty is handled by inserting expected protection levels at stations or on trains. In addition, with a stochastic scenario set that characterizes the uncertain passenger information, the last model aims to find a solution that is feasible for all involved scenarios, and thus, reduces the impact of the uncertainty in metro systems. To improve the computational efficiency of large-scale instances, a customized decomposition-based algorithm is developed. Finally, some real-world case studies based on the operation data of the Beijing metro Batong line are conducted to verify the performance and effectiveness of the proposed approaches.

The study of the influence of service quality, service fairness and trust on customer loyalty in the Malaysian motor insurance industry

The objective of this study was to examine the influence of service quality and service fairness on customer loyalty in the Malaysian motor insurance industry. Further, it also aimed to examine how the above relationships mediated by trust. The quantitative research was conducted based on 399 completed survey questionnaires collected on convenience sampling basis within Klang Valley, Malaysia. The analysis of the study primarily based on partial least square-structural equation modelling (PLS-SEM) approach using the Smart PLS 3.0 software. The result indicated that both service quality, service fairness and trust had a significant positive influence on customer loyalty with trust appeared to be a significant mediation variable which partially mediates the relationship between the constructs understudied. This study observed that service fairness which mediated by the trust had a more substantial impact on the determination of customer loyalty for motor insurance relationship exchange as compared to service quality.