Service Operators Research Articles

ФОРМУВАННЯ АСОРТИМЕНТУ ПОСЛУГ - ПРІОРИТЕТНИЙ НАПРЯМ МАРКЕТИНГОВОЇ ДІЯЛЬНОСТІ ТУРИСТИЧНОЇ ФІРМИ

The modern system of organized mass tourism is characterized by the fact that end buyers, interacting with producers of primary tourism services, use the services of tour operators, whose activity is to develop a tourism product, its implementation and coordination of interaction between these market parties in the production and consumption of primary tourism services. At the same time, in the conditions of organized tourism in market transactions the object of purchase and sale are not individual primary tourist services (intended to directly meet the needs of tourists), but a complex tourist product as a set of services sold by a tour operator directly or through intermediary structures (travel agencies). Assortment policy as part of the sales policy of the enterprise is primarily in the formation of production and sales program, ie the definition of those types of products (services) that will be sold in certain markets in the planning period. In accordance with the division of the company's goals into long-term and short-term, the assortment policy is structured into a strategic and operational component. To manage the assortment policy, the company's management must carefully study and assess the situation in the external environment, identify internal reserves that allow for measures to improve the range. Estimates require current demand in the field of various services, which will effectively manage the range. The management of the range of products or services may be hindered by the internal problems of the organization that have accumulated, so you should analyze the state of affairs, solve problems if they exist and only then implement measures to change the range

Role and challenge of technology toward a smart sustainable city: Topic modeling, classification, and time series analysis using information and communication technology patent data

This research defines and classifies essential technology groups that comprise a smart sustainable city (SSC) and explores patterns of technological growth by analyzing patents. First, topic modeling and network analysis are conducted using patent text data and international patent classification code, respectively. Patents are classified and defined based on the technology theme and the type of technology provider. Second, hardware-oriented and service application-oriented technologies are classified and predicted using machine learning. Third, the similarities in growth patterns of different technology groups are explored using dynamic time warping (DTW). Moreover, lagging or preceding relationships are examined using multivariate time series analysis. Network infrastructure and Internet-of-things (IoT) application technologies have short-term lagging and preceding relationships along with long-term equilibrium relationships. In terms of player groups, long-term relationships between device vendors, chipset makers, network operator and IoT service provider, and network equipment vendors are confirmed. Technologies for realizing a sustainable city must be prioritized, and the strategic direction of technology must be established to realize truly smart sustainable cities. The supplier of technologies along with possible collaboration opportunities must also be selected. This study proposes the role and direction of technology for SSC and presents a comprehensive methodology for analyzing technology using patents.

Deep Learning in Network-Level Performance Prediction Using Cross-Layer Information

Wireless communication networks are conventionally designed in model-based approaches through utilizing performance metrics such as spectral efficiency and bit error rate. However, from the perspectives of wireless service operators, network-level performance metrics such as the 5%-tile user data rate and network capacity are far more important. Unfortunately, it is difficult to mathematically compute such network-level performance metrics in a model-based approach. To cope with this challenge, this work proposes a data-driven machine learning approach to predict these network-level performance metrics by utilizing customized deep neural networks (DNN). More specifically, the proposed approach capitalizes on cross-layer information from both the physical (PHY) layer and the medium access control (MAC) layer to train customized DNNs, which was considered impossible for the conventional model-based approach. Furthermore, a robust training algorithm called weighted co-teaching (WCT) is devised to overcome the noise existing in the network data due to the stochastic nature of the wireless networks. Extensive simulation results show that the proposed approach can accurately predict two network-level performance metrics, namely user average throughput (UAT) and acknowledgment (ACK)/negative acknowledgment (NACK) feedback with great accuracy.

Post-Traumatic Stress Disorder Among U.S. Army Drone Operators

INTRODUCTION: Exposure to traumatic events could increase post-traumatic stress disorder (PTSD) risk among enlisted U.S. Army drone operators. Published research on PTSD risk in this population is unavailable.METHODS: We used a combined medical and administrative longitudinal dataset to examine adjusted associations between drone operator service among U.S. Army enlisted members and three PTSD indicators: whether screened via the PTSD Checklist - Civilian (PCL-C); PCL-C scores; and incident PTSD diagnoses. We compiled summary statistics for and conducted tests of differences in independent variable distributions when comparing drone operators and others. Two multivariable survival regression models and an ordinary least squares model were used to estimate adjusted associations.RESULTS: There were 1.68 million person-years of observed time in the study population (N = 678,548; drone operator N = 2856). Compared to other servicemembers, the adjusted likelihood of undergoing PTSD screening was 35% lower [95% confidence interval (CI) for the adjusted hazard ratio (aHR): 0.56-0.76]. Among subjects who took the PCL-C, scores did not differ significantly on the basis of drone operator service (adjusted change: -1.26 points; CI: -3.41-0.89). The adjusted hazard of receiving a PTSD diagnosis was 34% lower among drone operators (CI: 0.54-0.80).DISCUSSION: These findings provide reassurance that enlisted U.S. Army drone operators are not at increased risk of PTSD. Further research is needed in order to identify the mechanisms of the decreased PTSD risk observed, and whether other or longer-term mental health risks are present among those in this occupation.Nelson DA, Wilson M, Kurina LM. Post-traumatic stress disorder among U.S. Army drone operators. Aerosp Med Hum Perform. 2022; 93(7):562-570.

The Impact of Public Bus Service Quality on the Users’ Satisfaction: Evidence from a Developing Asian City

In a country where there is a high level of car ownership, public buses is considered as another modes of transport that is more sustainable. Despite that, there is a very low level of public bus ridership in Malaysia which questions the users’ satisfaction on its service quality. This study investigates the role of public buses service quality (tangibility, reliability, assurance, empathy and responsiveness) by the utilizing the SERVQUAL model towards users’ satisfaction. A sample of 300 questionnaires were obtained from public bus users in Kota Samarahan, Malaysia as the case study area. Using Partial Least Square-Structural Equation Model, the results show that tangibility, reliability and responsiveness are significant service quality factors that influence users’ satisfaction of public buses in the case study area. Of the factors, tangibility is considered as the most critical factor that influence users’ satisfaction. This study provides imperative knowledge which will be advantageous for stakeholders specifically policy-makers, transport ministries, town planners, local authorities and service operators in strategizing policies and plans that could encourage the public buses usage.

Influencing Factors and Measures of Users’ Privacy Disclosure in Social E-commerce

This paper integrates Utility Theory and Communication Privacy Management Theory to explore the influencing factors of privacy disclosure in social e-commerce scenarios. The aim of this research is to provide references to optimize service for platform operators and encourage users to participate in content creation. Social e-commerce websites are the platforms based on social networking. It shortens the distance with consumers and promote e-commerce transaction activities. However, the leakage of personal privacy on the platform has cracked down on the willingness of users to disclose information. This paper collects sample data through questionnaire survey for analysis. Based on users’ psychology, suggestions are given on upgrading data encryption technology to strengthen platform image marketing and give information management rights to users. It is found that perceived revenue, perceived information control and trust stimulate users’ privacy disclosure, while perceived risk suppresses user’s privacy disclosure in social e-commerce website.

Le competenze di cittadinanza dei volontari del Servizio Civile Universale. Uno studio empirico

The citizenship competences of the volunteers of the universal civil service. An empirical study. The paper presents the results of the research on citizenship competences of civil service operators, carried out with the participation of the Third Sector National Forum and with Arci Civil Service. The issue of citizenship competences and their enhancement is considered crucial both from the policy level and from the point of view of international studies. Eleven focus groups were conducted, aimed at volunteer operators, distributed in ten different Italian regions, for a total of 56 participants. All the discursive material produced was recorded and transcribed and made suitable to be subsequently subjected to statistical analysis, conducted in particular through correspondence analysis and cluster analysis. The choice of the method, and consequently of the tool, for the treatment and analysis of the data arose from a semiotic theoretical perspective. The data obtained from the analysis and interpretation of the speeches produced in the focus groups tell us that competence is mainly assumed as a synonym of knowledge, especially for what concerns civic competences. Even with respect to the meaning and role that the volunteer seems to assign to communication competences, the control of emotions and interpersonal skills, it seems necessary to problematize the development of these competences, considering how much the activities related to the world of volunteering have a high relational and emotional content.

A value-added IoT service for cellular networks using federated learning

The number of Internet-of-Things (IoT) devices is expected to reach 64 billion by 2025. These IoT devices will mostly use cellular networks for transferring a huge amount of IoT data to the cloud for machine learning (ML) based forecasting. Keeping in view a large number of application scenarios for highly resource constraint IoT devices connected with the cellular networks, we propose a value-added IoT service (VAIS) for the cellular network operators based on the federated learning (FL) paradigm. Through simulation experiments, we show, for real air quality data and specific ML models, the proposed VAIS reduces the backhaul data by 70× and requires less energy than its equivalent cloud-based conventional approach, however, with a slight increase in communication time. From the insights we gained, we believe that a properly designed VAIS would efficiently utilize network resources, not only reduce management for IoT users but also the operating costs for cellular operators, and encourage IoT applications on limited backhaul cellular networks.

An Assessment of the Impact of COVID-19 on the Agri-Food System in Caribbean Small Island Developing States

The COVID-19 pandemic impacts have arguable been more pronounced in the developing world, such as the Small Island States (SIDS) of the Caribbean, where a plethora of geophysical and socio-political factors have led to increased vulnerability, particularly in fragile sectors such as agriculture. The pandemic added another layer of complexity to the unstable agri-food systems of SIDS in the Caribbean. Measures to contain the unfolding crisis have tremendously disrupted food systems by threatening the production, distribution, and marketing of commodities which exposed the frailty of the region's food security. Caribbean SIDS are highly dependent on food imports and relies on international markets to secure food. Many are also dependent on agricultural exports and have a large portion of their population involved in agriculture making them particularly vulnerable to the rigors of the pandemic. Export restrictions on foodstuff and prohibitions due to lockdowns and border closures further exacerbated these challenges. Additionally, food and nutrition security in the region is also subjected to the effects of climate change and climate-related disasters. Dealing with the impacts of co-occurring disasters is, therefore, an ever-present threat. This study examines the impact of COVID-19 on the agri-food supply in the Caribbean. It also identified measures and initiatives adopted to cope with these disruptive consequences. The study involves the use of internet-based surveys and focus group discussions and internet-based surveys with stakeholders and online searches for related literature. A total of 96 farmers, 60 food distributors, 84 food service operators, and 237 consumers from the region participated in the online survey and 4 focus group discussions between January and November 2021. The results confirmed that the impacts of the COVID-19 pandemic were evident along the entire agri-food supply chain and numerous challenges and shocks were identified across all participating groups and countries. Some challenges and shocks such as loss of income and related challenges including lower sales and loss of markets affected all groups in the study but to varying degrees and based on socio-demographic factors. In general people of lower income status and smaller businesses were more susceptible to the negative impacts of the pandemic.

Safe water and sanitation in remote indigenous communities in Australia: conditions towards sustainable outcomes

ABSTRACT Safe drinking water and effective sanitation is a basic human right. The health of Aboriginal and Torres Strait Islander Peoples living on traditional Country in remote Australia can be supported or undermined by these essential services. Despite global and Australian commitments to the Sustainable Development Goals, water and sanitation service levels have regularly been identified as unreliable, unsafe, and of a lower standard than non-Indigenous and non-remote settlements. This research sought to identify the optimal conditions to enable consistent delivery of safe water and sanitation in remote Indigenous communities of Australia. Using a combination of literature reviews, interviews with key stakeholder groups and applied research findings, key conditions for improved water and sanitation outcomes were identified. These included technology for water and sanitation that is fit for purpose, people and place; capacity-building, training and ongoing support for local Indigenous service operators; and that all personnel involved in delivery require a level of cultural competency to the local and Indigenous context. These findings are intended to contribute to informing more sustainable water and sanitation outcomes in Indigenous communities.

A Proposal for Formulating a Spectrum Usage Fee for 5G Private Networks in Indonesian Industrial Areas

The Indonesian spectrum usage fees—the so-called Biaya Hak Pengguna Frekuensi Izin Pita Frekuensi Radio (BHP IPFR)—are currently calculated using a formula determined by the three following main parameters: the frequency band, the country’s economic parameter, and the nationwide population. As spectrum usage fees are proportional to the width of the bandwidth, the current formula would result in an extremely high price when applied to 5G-mmWave private networks, with the cost burden being a direct consequence for the service operator. In this paper, we propose the formulation of a new spectrum usage fee for 5G-mmWave private network implementation in Indonesian industrial areas. To do so, we evaluate the current formula, adopt the framework offered by the ITU-R SM.2012-5 (06/2016), and use an industrial reference index—the Indonesia Industry Readiness Index 4.0 (INDI 4.0) score. We test the proposal by applying the new formula to calculate the 5G-mmWave private network spectrum usage fee for the Jakarta industrial area. The result shows that the new formula gives a lower spectrum usage fee than the current formula, which benefits 5G-mmWave private network service operators. Such savings can be regarded as a government subsidy for the service operators to use in various ways in the industry, providing further economic benefits. Using the input–output model, we prove that despite the proposed new formula brings a lower spectrum usage fee, resulting in a loss in state income, it will lead to a much greater positive impact on the national economic output. Applying the new formula will eventually have a multiplier effect on various sectors and encourage digital economic growth and national digital transformation, especially for vertical industries in Indonesia. This study may serve as a guideline or initial reference for Indonesian policymakers and service operators for applying the CAPEX and OPEX cost of using the new spectrum for 5G-mmWave private network service implementation and estimating the economic multiplier for 5G-mmWave private network service deployment in industrial areas. It can also be used as a benchmark case for other countries to apply spectrum usage fees for private networks in industrial areas.

Intent-based zero-touch service chaining layer for software-defined edge cloud networks

Edge Computing, along with Software Defined Networking and Network Function Virtualization, are causing network infrastructures to become as distributed clouds extended to the edge with services provided as dynamically established sequences of virtualized functions (i.e., dynamic service chains) thereby elastically addressing different processing requirements of application data flows. However, service operators and application developers are not inclined to deal with descriptive configuration directives to establish and operate services, especially in case of service chains. Intent-based Networking is emerging as a novel approach that simplifies network management and automates the implementation of network operations required by applications.This paper presents an intent-based zero-touch service chaining layer that provides the programmable provision of service chain paths in edge cloud networks. In addition to the dynamic and elastic deployment of data delivery services, the intent-based layer offers an automated adaptation of the service chains paths according to the application’s goals expressed in the intent to recover from sudden congestion events in the SDN network. Experiments have been carried out in an emulated network environment to show the feasibility of the approach and to evaluate the performance of the intent layer in terms of network resource usage and adaptation overhead.

A critical contribution in a time of crisis: Examining motivations and deterrents to COVID-19 convalescent plasma donation and future donation intentions among prospective Canadian donors.

ObjectivesTo understand motivations and deterrents to donate COVID‐19 convalescent plasma for a clinical trial and determine whether they predict intention to donate source plasma.BackgroundDuring the COVID‐19 pandemic, Canadian Blood Services was involved in three nationally coordinated convalescent plasma clinical trials, requiring the recruitment of several thousand prospective convalescent plasma donors. Understanding the motivations and deterrents of donors in the unique context of a clinical trial and ongoing pandemic can inform recruitment for source plasma donation beyond a clinical trial.Methods and MaterialsWe invited 2785 Canadians who had registered interest in donating COVID‐19 convalescent plasma to participate in an online survey containing a 42‐item scale on motivators of and deterrents to donation. Between April 26th and May 19th, 2021, 979 responded (35.1%). We included a final sample of 820 participants with sufficient data across all scales. Exploratory and confirmatory factor analysis determined the factor structure of the scale. Regression analysis assessed the extent to which the factors predicted intention to donate.ResultsFour factors were identified: ‘helping relationally’, ‘deterrents to donation’, ‘social facilitators’, and ‘access to the donation centre’, each with good internal consistency (α = 0.78–95). Higher scores on the helping relationally scale were associated with higher odds of intention to donate, whereas higher scores on the deterrents scale were associated with lower odds of intention to donate.ConclusionParticipants were motivated by an interest in helping people who are ill and contributing to research committed to finding treatments in a time of crisis. Outside the crisis context, blood service operators seeking to recruit source plasma donors should emphasise its lifesaving potential and the impact of donation on the community.

A novel control strategy in mitigating bus bunching: Utilizing real-time information

A variety of control mechanisms have been recommended to concentrate on the issue of bus bunching. However, the majority of existing measures focus on controlling the bus operation directly from the operator's perspective. This study, nevertheless, presents a novel control technique by providing passengers with real-time wait time information and degrees of in-vehicle congestion. Specifically, passengers are expected to use the given information to calculate the overall travel cost and, therefore, make decisions on whether boarding on the arriving bus or waiting for the next buses. In this way, bus service operators would reduce bus bunching by adjusting passengers' boarding choice behavior rather than controlling the bus vehicles directly. We propose a bus traffic propagation model to simulate the bus movements, through which several system performance metrics, such as the shortest vehicle spacing distribution and the average ridership per bus vehicle at each stop, can be evaluated for different bus bunching control measures. The numerical results show that providing in-vehicle congestion information is as effective as the schedule-based and headway-based control methods in achieving mitigation of bus bunching. Passengers on long trips are more inclined to wait for a few more shifts for a bus that is not very crowded. This study proposes a novel control strategy by offering passengers real-time information to serve as a supplement, never a substitute, to the existing control measures in mitigating bus bunching problems.

Modelling reservation-based shared autonomous vehicle services: A dynamic user equilibrium approach

Shared Autonomous Vehicles (SAVs) are expected to be used for regular and pre-planned trips. Such trips are suitable for reservation-based services, wherein the customer needs to book for a trip in advance. Systems enabling reservation of trips can allow for better planning of routes and schedules, and if optimally designed, enable higher efficiency. The primary objective of this research is to model the effects of such a system, by formulating and solving the combined Dynamic User Equilibrium and Shared autonomous vehicle Chain Formation (DUESCF) problem. The problem is formulated as a bilevel model based on game theory, involving road users and SAV service operator. Given a situation where conventional private and shared autonomous vehicles co-exist, road users select paths and departure times to maximize a perceived utility (commonly treated as minimizing a disutility) by forming a DUE (fixed point problem), and the SAV service operator tries to maximize the performance by forming appropriate SAV chains (combinatorial problem). The final objective of this bilevel model is a traffic assignment that includes SAV chain formation, such that both road users and SAV service operator obtain optimal solutions by reaching a Nash equilibrium, where no player is better off by unilaterally changing their decisions. A solution approach, based on Iterative Optimization and Assignment (IOA) method, is proposed with path flow and SAV performance changes as convergence criteria. Furthermore, the solution approach is tested for its robustness, and a scenario analysis is carried out to evaluate the impacts of reservation-based SAV services. The results show that a ridesharing SAV system is better compared to a carsharing and a mixed system consisting of both, in terms of total system travel time, congestion levels, total vehicle kilometres travelled and vehicle requirements.

Virtualised network security is not a one-size-fits-all approach

As the deployment of next-generation networks accelerates, and promises of new technologies and IoT devices bring new opportunities worldwide, with virtualisation becoming key, there is an increasing awareness of the need for a secure network to ensure a secure ecosystem. As networks grow, service operators have a huge responsibility to provide both reliable and secure services to end users.

Long term assessment of a successful e-bike-sharing system. Key drivers and impact on travel behaviour

The many benefits of cycling, such as eco-friendliness, low cost, health benefits, and efficiency in congested areas, had encouraged governmental strategies to promote it, triggering a global growth of bike-sharing systems (BSS). In this line, it is important to avoid service termination by assessing the evolution, identifying drawbacks and success factors, that could be determinant on the system’s future. Nonetheless, in many cases, subjective and objective information regarding BSS was not collected nor compared. In this study, we analyse the evolution of Madrid’s pioneer electric system, by combining the subjective data of three surveys, conducted since 2014 to 2019, with objective data from the service operator. The insights extracted shed light on the key factors determining the system’s success, and its influence on travel behaviour. Results suggest that the user profile of the young early adopters evolved to middle-aged workers. Strong maintenance campaigns and network expansions improved bikes availably and user satisfaction. Slope of the streets is one of the lowest importance factors, whereas pedelec assistance the highest. It is likely to believe that there is a relationship between both, suggesting that electric assistance encourages cycling in a hilly city like Madrid. Transferable experiences to other cities evolving from traditional to e-BSS could be valuable, like the results suggesting that the introduction of an electric BSS is a potential trigger for bicycle adoption in dense urban environments. In addition, that subscribers tend to reduce the use of private car while increase cycling. This longitudinal analysis offers valuable policy implications, like those related with bike maintenance, network extension, and measures focused on keeping the new subscribers of the COVID-19 post-lockdown.

Conflicts Encountered with Bridge Team from the Perspective of Vessel Traffic Service Operators: A Research Within E-Navigation Concept

The hazards that threaten marine navigation safety in the intensive routes and critical straits need to be managed effectively. To manage these risks, the concept of e-navigation has been offered to all stakeholders of marine transportation. E-navigation basically aims to organize, serve, and exchange marine information systematically. It is considered that the relations between the stakeholders may constitute significant conflicts in exchanging marine information. The main purpose of this study is to reveal the sources of conflicts and risk scores on navigation operations encountered with the bridge team from the perspective of vessel traffic services operators (VTSOs). In order to determine the sources of the conflicts, the conflict-related literature has been thoroughly reviewed, a semi-structured interview form was developed, and the VTS supervisors have been interviewed. In discovering the sources of conflicts, content analysis has been carried out from the interviews. The findings have been discussed with the relevant experts, and risk scales have been developed to evaluate the risks of conflicts. The frequency of conflicts and the results have been evaluated by the VTSOs employed at the Center of VTS in İstanbul, and risk scores have been defined. The risk scores related to the conflicts indicated on the risk matrix and e-navigation designed solutions have been compared and discussed. The findings reveal that there are certain similarities between the high-scored risks regarding communication quality and reporting systems. Although e-navigation solutions focus on improving technical issues. Conflicts caused by interpersonal, cognitive, and personal features that are not covered by e-navigation solutions have an important place among the conflict sources.

Resource Allocation using Genetic Algorithm in Multimedia Wireless Networks

Resource allocations in wireless networks is a very challenging task, at one hand wireless networks have scarce resources and suffers from many limitations. At the other hand, typical resource allocation problems requires extensive amount of computations and are usually NP-hard problems. Hence, there is dire need for effective and feasible solutions. Resource allocation problems are concerned in distributing the available network’s resources to all active users in a fair way. Although fairness is hard to define, this work considers the fairness aspects for both, the users and the network operator (service provider). Bio-inspired algorithm are used in many context to provide simple and effective solution tochallenging problems. This works employs Genetic Algorithm to provide effective solution to resource allocation problem for multimedia allocation in wireless networks. The performance of the proposed solution is evaluated using simulation. The obtained simulation results show that the proposed solutionachieved better performance.

PROACTIVE SUSTAINABLE APPROACHES BY MALAYSIAN FEEDER SERVICE COMPANIES IN THE DISRUPTIVE ERA

Feeder services play a significant role in Malaysian shipping economy. A total of 87.5 per cent of feeder companies have established themselves in Port Klang, as their focal point of service, while the remaining 12.5 per cent have chosen neighbouring Singapore Port as their base. Recently, the industry players have faced many challenges, such as hyper-competition, price wars, the COVID-19 pandemic, and threats of bankruptcy, which leads to the situation known as the disruptive era. While plenty of studies have discussed the issues of feeder services by focusing on the “hub and spoke” design, route design and environmental context, there is lack of research on proactive sustainable approach in the case of Malaysia feeder services. As a result, this paper reviews the impact of the United States-China trade war, COVID-19 pandemic and hyper-competition among feeder service companies in Malaysia. An extensive literature review and online interviews are conducted with feeder service operators, government agencies and port authorities, and the data analysed using Thematic Analysis. The results show that offering competitive freight rates, reliable services and alliance between feeder operators are important in business sustainability. Meanwhile, unstable oil prices, high chartering costs and less creativity in problem-solving are factors that reduce business sustainability. This paper hopes to assist feeder service operators, researchers and government agencies in understanding and planning sustainable strategies for the industry in the disruptive era.