Optimal Service Research Articles

Optimizing environmental regulation policies for digital transformation in energy enterprises in China: An evolutionary game theory approach

In response to the global consensus on achieving carbon reduction, China has introduced a series of policies aimed at accelerating the digital transformation of energy enterprises. However, these policies have revealed shortcomings such as deficiency in regulation methods and insufficient integration of regulation with technologies. This study applies evolutionary game theory (EGT) to evaluate the impacts of different environmental regulatory policies on the digital transformation and verifies the effectiveness of the theory in policy optimization. Utilizing modified real-world data, the study quantitatively examines the effects of alterations in various parameter combinations on players' strategic choices. The results indicate that: (1) increasing the regulatory intensity above 0.8, the carbon tax rate and penalties can promote the digital transformation, stimulating the low-carbon development in energy sector; (2) an interesting finding is that tax incentives such as carbon tax refund ratio can exacerbate enterprises’ reliance on government compensation, thereby slowing down their transition process; (3) this study highlights the optimal service provision intensity for technological service providers (TSP) is 0.9, which can expedite system evolution towards the ideal state and foster the construction of a favorable digital regulatory environment. The study provides valuable references for optimizing regulatory policies and promoting digital transformation to realize the decarbonization goal.

Exploring past research to move forward: a scoping review of aims, outcomes, and recommendations in parental mental illness qualitative research.

As parental mental illness is a global public health concern, rigorous qualitative research is central to understanding families' experiences, needs and outcomes to inform optimal service provision in adult mental health and children's social services. The current review identified, appraised and synthesized international qualitative research exploring Families and Parent Mental Illness (FaPMI) research to determine the focus, findings and outcomes and to summarize the recommendations made about the direction of future research. Findings are classified according to outcomes for children, parents, and families. While some children experienced positive outcomes from a parent's illness, most faced impacts on their social-emotional wellbeing, school performance, increased caregiving responsibilities, strained parent relationships, and lack of understanding about parental mental illness. Some family members endured abuse and struggled to adapt to an ill parent's unpredictable needs, with reluctance to discuss the situation. Parents found parenting challenging yet viewed having children as a protective factor. Future research should gather diverse perspectives, explore within-family factors and social environments, develop and test interventions, and address methodological issues like sampling. This review highlights the centrality of qualitative data in comprehensively understanding and evaluating outcomes of parental mental illness on families and provides clear recommendations regarding future research.

An Optimal Road Network Extraction Methodology for an Autonomous Driving-Based Demand-Responsive Transit Service Considering Operational Design Domains

In addition to addressing the labor shortage due to an aging population, the transition to autonomous vehicle (AV)-based mobility services offers enhanced efficiency and operational flexibility for public transportation. However, much of the existing focus has been on improving AV safety without fully considering road conditions and real-world service demand. This study contributes to the literature by proposing a comprehensive framework for efficiently integrating AV-based mobility services at the network level, addressing these gaps. The framework analyzes and optimizes service networks by incorporating actual demand patterns, quantifying road segment difficulty from an AV perspective, and developing an optimization model based on these factors. The framework begins by quantifying the operational difficulty of road segments through an evaluation of Operational Design Domains (ODDs), providing a precise measure of AV suitability under varying road conditions. It then introduces a quantitative metric to assess operational feasibility, considering factors such as the service margin, costs, and safety risks. Using these metrics alongside Genetic Algorithms (GAs), the framework identifies an optimal service network that balances safety, efficiency, and profitability. By analyzing real-world data from different mobility services, such as taxis, Demand-Responsive Transport (DRT), and Special Transportation Services (STSs), this study highlights the need for service-specific strategies to optimize AV deployment. The findings show that optimal networks vary with demand patterns and road difficulty, demonstrating the importance of tailored network designs. This research provides a scalable, data-driven approach for integrating AV services into public transportation systems and lays the foundation for further improvements by incorporating dynamic factors and broader urban contexts.

Analysis of the Implementation of the Merit System in the Mataram City Government from a Gender Perspective

Human resources (apparatus) are the basis of the bureaucratic reform movement. Human resources are one aspect of achieving the goals of government organizations, namely providing optimal public services. Therefore, it is necessary to implement a merit system to obtain human resources, in this case specifically the best State Civil Apparatus (ASN) who do not consider male or female gender, including in the process of filling pratama high leadership positions (JPT) in scope of the Mataram City Government. This research aims to describe the implementation of the merit system in the Mataram City government from a gender aspect. This research uses a qualitative approach with data collection methods consisting of in-depth interviews and document review. Data analysis uses qualitative data analysis techniques. The validity of the data was tested using triangulation techniques. Research provides an illustration that the Mataram City government has basically implemented a merit system in ASN management. When filling out the JPT, preparation, implementation and evaluation stages have been carried out in accordance with the provisions. Basically, the number of female ASNs in the city of Mataram is more than male. Likewise, the educational level of female ASN is better than that of men. However, if we look at it in terms of rank and class, the number of men is increasing, this will make the opportunity for men to occupy top positions in the bureaucracy greater. The Mataram city government consistently provides opportunities for women at the rate of 10 percent and hopes that in the future this will be further increased.

Comprehensive Geriatric Assessment (CGA) and Optimisation Services before Kidney Transplantation in Older Potential Recipients: Results from the First UK-Wide Transplant Centre Survey Study

Comprehensive Geriatric Assessment (CGA) and Optimisation Services before Kidney Transplantation in Older Potential Recipients: Results from the First UK-Wide Transplant Centre Survey Study

Understanding after-market service channel selection for complex product-services supply chains: A game-theoretical approach

Today, cooperation between an OEM (Original Equipment Manufacturer) of Complex Products and Systems (CoPS) and her multiple Key Component Suppliers (KCSs) is characterized by a strategic partnership where long-term benefits are sought for both parties. Since CoPS after-market service can be provided by the KCS, the OEM, or an MRO (Maintenance, Repair, and Overhaul) party, different after-market service channels can be established. In this paper, we model each of these channels using game theory, compare their main features, and discuss the selection of the optimal after-market service channel. We show that the duration of the after-market service is not influenced by the service channel if the service cost remains constant. If the after-market service costs are equal for all parties, each party would prefer the other to perform the service. In the case of different costs, both the cost of the service and potential market size have the same effect on the OEM’s preference for the after-market service channel as on the CoPS ordered quantities. Furthermore, OEM and KCS after-market service channel preferences depend on market size, and “win-win” situations are discussed for the different channels, along with their impact on the long-term stability of the strategic partnership between KCS and OEM. Finally, a sensitivity analysis is carried out to examine the impact of several key parameters. The results presented in the paper serve to deepen the understanding of complex product-service systems and offer a number of managerial insights to select an appropriate after-market service channel for KCSs.

Interest-aware joint caching, computing, and communication optimization for mobile VR delivery in MEC networks

In the upcoming B5G/6G era, Virtual Reality (VR) over wireless has become a typical application, which is an inevitable trend in the development of video. However, in immersive and interactive VR experiences, VR services typically exhibit high delay, while simultaneously posing challenges for the energy consumption of local devices. To address these issues, this paper aims to improve the performance of VR service in the edge-terminal cooperative system. Specifically, we formulate a joint Caching, Computing, and Communication (3C) VR service policy problem by optimizing the weighted sum of the total VR delivery delay and the energy consumption of local devices. To design the optimal VR service policy, the optimization problem is decoupled into three independent subproblems to be solved separately. To improve the caching efficiency within the network, a Bert-based user interest analysis method is first proposed to accurately characterize the content request behavior. Based on this, a service cost minimum-maximization problem is formulated under the consideration of performance fairness among users. Then, the joint caching and computing scheme is derived for each user with a given allocation of communication resources while a bisection-based communication scheme is acquired with the given information on the joint caching and computing policy. With alternative optimization, an optimal policy for joint 3C based on user interest can be finally obtained. Simulation results are presented to demonstrate the superiority of the proposed user interest-aware caching scheme and the effectiveness of the joint 3C optimization policy while considering user fairness. Our code is available at https://github.com/mrfuqaq1108/Interest-Aware-Joint-3C-Optimization.

Pricing and Service Decisions of Products in a Dual-Channel Supply Chain Introducing Ship-to-Store

This study investigates the optimal pricing and service decisions when implementing ship-to-store (STS) in a dual-channel supply chain comprising one BM store and one manufacturer. Homogeneous products within the market are categorized into mainstream and niche products. The effects of consumer service sensitivity, channel preference, and degree of personalization on optimal decisions and profitability are analyzed, followed by numerical simulation and analysis. It is found that (1) the supply chain should charge high prices for mainstream products and low prices for niche products to maximize profits. (2) Implementing STS is conducive to expanding niche products in the market when facing highly service-sensitive consumer groups. (3) Based on highly service-sensitive consumer segments, supply chains are more profitable implementing STS strategies in a centralized decision-making model than in a traditional dual-channel one; however, under decentralized decision-making, it is only profitable to implement an STS strategy if consumers have a low level of personalization and have a particularly pronounced preference for online direct marketing channels.

An innovative approach for QoS-aware web service composition using whale optimization algorithm

With the proliferation of services and the vast amount of data produced by the Internet, numerous services with comparable functionalities but varying Quality of Service (QoS) attributes are potential candidates for meeting user needs. Consequently, the selection of the most suitable services has become increasingly challenging. To address this issue, a synthesis of multiple services is conducted through a composition process to create more sophisticated services. In recent years, there has been a growing interest in QoS uncertainty, given its potential impact on determining an optimal composite service, where each service is characterized by multiple QoS properties (e.g., response time and cost) that are frequently subject to change primarily due to environmental factors. Here, we introduce a novel approach that depends on the Multi-Agent Whale Optimization Algorithm (MA-WOA) for web service composition problem. Our proposed algorithm utilizes a multi-agent system for the representation and control of potential services, utilizing MA-WOA to identify the optimal composition that meets the user’s requirements. It accounts for multiple quality factors and employs a weighted aggregation function to combine them into a cohesive fitness function. The efficiency of the suggested method is evaluated using a real and artificial web service composition dataset (comprising a total of 52,000 web services), with results indicating its superiority over other state-of-the-art methods in terms of composition quality and computational effectiveness. Therefore, the proposed strategy presents a feasible and effective solution to the web service composition challenge, representing a significant advancement in the field of service-oriented computing.

Role of Physical Evidence and Empathy in Influencing Patient Visit Rates at Hialu Health Center, North Konawe

Introduction: The number of patient visits to the Hialu Health Center continues to increase with an average number of patient visits in 2021 of 225 visits per month. This study was conducted at the Hialu Health Center, Landawe District, North Konawe Regency. The purpose of this study was to analyze the Relationship between Physical Evidence and Empathy to the Level of Patient Visits at the Hialu Health Center, Landawe District, North Konawe Regency. Method: This study uses a quantitative method with a comparative research design. The population of the entire Landawe District community is 2,843 people and a sample of 351 using the Slovin formula. Result: Based on the linearity test between variables, the variables of physical evidence and empathy generally have an effect on the level of patient visits to the Hialu Health Center, Landawe District, North Konawe Regency. Conclusion: The relevant government, especially the Health Service, must continue to provide easy access for the Hiau Health Center to improve health facilities and infrastructure in order to provide more optimal health services to the community.

Factors informing funding of health services for Aboriginal and Torres Strait Islander children: perspectives of decision-makers.

Background The factors informing decisions to fund health services for Aboriginal and Torres Strait Islander children are unclear. This study's objective aimed to describe decision-makers' perspectives on factors informing decisions to fund health services for Aboriginal and Torres Strait Islander children. Methods We conducted semi-structured interviews with 13 participants experienced in making funding decisions at organisational, state, territory and national levels. Decision-makers were from New South Wales, Northern Territory, Queensland, Victoria and Western Australia. Transcripts were analysed thematically following the principles of grounded theory. Results We identified five themes, each with subthemes. First, prioritising engagement for authentic partnerships (opportunities to build relationships and mutual understanding, co-design and co-evaluation for implementation). Second, valuing participant experiences to secure receptiveness (cultivating culturally safe environments to facilitate acceptability, empowering for self-determination and sustainability, strengthening connectedness and collaboration for holistic care, restoring confidence and generational trust through long-term commitments). Third, comprehensive approaches to promote health and wellbeing (linking impacts to developmental milestones, maintaining access to health care, broadening conceptualisations of child health). Fourth, threats to optimal service delivery (fractured and outdated technology systems amplify data access difficulties, failure to 'truly listen' fuelling redundant policy, rigid funding models undermining innovation). Fifth, navigating political and ideological hurdles to advance community priorities (negotiating politicians' willingness to support community-driven objectives, pressure to satisfy economic and policy considerations, countering entrenched hesitancy to community-controlled governance). Conclusion Decision-makers viewed participation, engagement, trust, empowerment and community acceptance as important indicators of service performance. This study highlights factors that influence decisions to fund health services for Aboriginal and Torres Strait Islander children.

Optimal Service Strategies of Online Platform Based on Purchase Behavior

In the rapidly evolving platform economy, online platforms have emerged as pivotal providers of digital services to sellers. The paper investigates how online platforms optimize service strategies based on consumers’ purchase behavior, influencing sellers’ pricing and social welfare. Using a two-period Hotelling model and a cooperative game framework, we discover that the optimal service strategies of a platform with data collecting capabilities are collaborating with two sellers to offer to extend services to new consumers in the second period, maximizing profits for all sellers and platform. Applying Shapley value analysis, we determine the platform’s equitable service charge strategies. When sellers adopt behavior-based pricing (BBP), the pricing escalates in the first period, and the platform’s optimal service strategies also enhance the pricing of sellers. However, in the second period, BBP intensifies competition, leading to generally lower pricing. Our findings suggest that optimal pricing in the second period for new consumers should increase with enhanced quality perception, which is provided by the platform’s digital services and heightened by consumers’ privacy concerns, while decreasing for regular consumers. Lastly, we offer policy recommendations, exploring optimal regulatory scenarios—limiting or not limiting data collection—to maximize social welfare or consumer surplus, and the Mathematica software is used to identify distinct optimal policy intervals.

Escalation of Transportation Service Quality at the Angkoetan Motor Repoeblik Indonesia (Damri) Surabaya

The development of the times encourages the community to focus on the advancement of science and technology, to create optimal public services. Transportation is one of the sectors that is greatly affected by technological advances. The escalation of people's mobility demands has led to an increase in very significant means of transportation that are not proportional to the number of existing vehicles, resulting in congestion on the streets. Given the importance of the role of transportation, the government needs to provide mass transportation services that are by the needs of services that are regular, safe, comfortable, fast, precise, and affordable. This study uses a qualitative descriptive approach through observation, direct interviews, and documentation to collect data. The goal is to collect detailed information on improving the quality of DAMRI transportation services and analyze the factors that support and hinder these services. The results of the study show that the escalation of DAMRI service quality focuses on the Minimum Service Standards for Road-Based Mass Transportation, namely security, safety, comfort, affordability, equality, and order.

The Effect of Career Development and Compensation on Employee Performance Through Job Satisfaction at PT Bank Tabungan Negara Kudus Branch Office

Career development and compensation are factors that play a role in improving employee performance and job satisfaction. With a career development program and fair compensation, employees will provide optimal service to the community. This study aims to determine the direct influence of career development and compensation on employee performance and to examine the role of job satisfaction mediation in the relationship between the influence of career development and compensation on the performance of banking employees. The study involved 50 organic employees. Data collection was carried out using the survey method. The analysis test used is the Structural Equation Model (SEM) approach using the Partial Least Square (PLS) program. The results of the test on the influence of career development on employee performance through job satisfaction showed an insignificant value (p-value = 0.448) and the results of the test on the influence of compensation on employee performance through job satisfaction showed a significant value (p-value = 0.001). This is because employee performance and satisfaction are influenced by various factors other than career development and compensation

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.

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

Optimal resource management for multi-access edge computing without using cross-layer communication

We consider a Multi-access Edge Computing (MEC) system with a set of users, a base station (BS) with an attached MEC server, and a cloud server. The users can serve the service requests locally or can offload them to the BS which in turn can serve a subset of the offloaded requests at the MEC and can forward the requests to the cloud server. The user devices and the MEC server can be dynamically configured to serve different classes of services. The service requests offloaded to the BS incur offloading costs and those forwarded to the cloud incur additional costs; the costs could represent service charges or delays. Aggregate cost minimization subject to stability warrants optimal service scheduling and offloading at the users and the MEC server, at their application layers, and optimal uplink packet scheduling at the users’ MAC layers. Classical back-pressure (BP) based solutions entail cross-layer message exchange, and hence are not viable. We propose virtual queue-based drift-plus-penalty algorithms that are throughput optimal, and achieve the optimal delay arbitrarily closely but do not require cross-layer communication. We first consider an MEC system without local computation, and subsequently, extend our framework to incorporate local computation also. We demonstrate that the proposed algorithms offer almost the same performance as BP based algorithms. These algorithms contain tuneable parameters that offer a trade off between queue lengths at the users and the BS and the offloading costs.

Optimized Dynamic Service Placement for Enhanced Scheduling in Fog-Edge Computing Environments

The traditional cloud computing model struggles to efficiently handle the vast number of Internet of Things (IoT) services due to its centralized nature and physical distance from end-users. In contrast, edge and fog computing have emerged as promising solutions for supporting latency-sensitive IoT applications by distributing computational resources closer to the data source. However, these technologies are limited by their size and computational capacities, making optimal service placement a critical challenge. This paper addresses this challenge by introducing a dynamic and distributed service placement policy tailored for edge and fog environments. By leveraging the inherent advantages of proximity in fog and edge nodes, the proposed policy seeks to enhance service delivery efficiency, reduce latency, and improve resource utilization. The proposed method focuses on optimizing the placement of high-demand services closer to the data generation sources to enhance scheduling efficiency in fog computing environments. Our method is divided into three interconnected modules. The first module is the service type estimator, which is responsible for distributing services to appropriate nodes. Here, we use the Political Optimizer (PO) as a new metaheuristic algorithm for deploying IoT services. The second module is service dependency estimator, which manages service dependencies. Here, we load dependent services near the data using a path matrix based on the Warshall algorithm. Finally, the third module is resource demand scheduling, which estimates resource demand to facilitate optimal scheduling. Here, we use a popularity-based policy to manage resource demand and service execution scheduling. Implementation results demonstrate significant improvements over existing state-of-the-art policies, highlighting the efficacy of the proposed policy in enhancing service delivery within fog-edge computing frameworks.

Optimalisasi Penggunaan Conveyor Belt Dalam Menunjang Pelayanan Di Bandar Udara Internasional Syamsudin Noor Banjarmasin

This study examines the optimization of conveyor belt usage in supporting passenger services at Syamsudin Noor International Airport, Banjarmasin. Conveyor belt is one of the important facilities in handling luggage that has a crucial role in accelerating the process of handling goods and reducing passenger waiting time. The less than optimal use of conveyor belts at Syamsudin Noor International Airport causes less than optimal passenger service, especially causing a buildup of passengers in the arrival terminal area. Therefore, the author conducted this research with the aim of finding out the causes of non-optimal use of conveyor belts at Syamsudin Noor Airport and the solutions that must be implemented to overcome them.This research was conducted from January 31 to February 10 2024 at Syamsudin Noor International Airport, Banjarmasin. This research uses qualitative research methods in the form of primary and secondary data. Primary data in this research was obtained from interviews conducted with 1 technical officer and 2 Terminal Service Officers. Meanwhile, secondary data in this research was obtained from literature reviews and journals related to this research. Qualitative data analysis techniques used include Data Reduction, Triangulation, and Drawing Conclusions. The research results show that optimizing and increasing conveyor belt capacity as well as implementing automatic monitoring and maintenance technology can reduce the risk of operational disruption and increase passenger satisfaction. This research also identifies solutions for terminal service area officers and mechanics to improve conveyor belt conditions that are not optimal, where the solutions suggested by the author include replacing rollers and pulleys, cleaning and lubricating components, and applying strengthening techniques.

Implementation of Village Governance on Public Services in Langensari Village

This research explains public services in Langensari Village by emphasizing aspects of accountability, transparency, effectiveness and efficiency. The focus includes planning and development to advance village welfare. In regional development, the government emphasizes the bottom-up system, namely villages. Village governance is a form of government administration in realizing development in the village. In this case, creating good governance can improve public services in the village which can support the performance of village officials in serving the community. Optimal service must always be provided by regional government officials, especially village governments. That one of the goals of village regulation is to improve public services for service providers as well as possible is one of the performance results that village governments can carry out to achieve the goals set out in national service standards, namely service quality. Optimal public services can create village government that is professional, efficient and effective, open and responsible, or good governance. This research explains public services in Langensari Village by emphasizing aspects of accountability, transparency, effectiveness and efficiency. The focus includes planning and development to advance village welfare. In regional development, the government emphasizes the bottom-up system, namely villages. Village governance is a form of government administration in realizing development in the village. In this case, creating good governance can improve public services in the village which can support the performance of village officials in serving the community. Optimal service must always be provided by regional government officials, especially village governments. That one of the goals of village regulation is to improve public services for service providers as well as possible is one of the performance results that village governments can carry out to achieve the goals set out in national service standards, namely service quality. Optimal public services can create village government that is professional, efficient and effective, open and responsible, or good governance.