Service Operators Research Articles

Associations of built environment with moped-sharing use: A vehicle-based approach

In recent years, moped-sharing services have become popular in Asian and European cities, but existing literature provides limited information about factors influencing moped-sharing use. This research explored the associations of built environments with the probabilities that idle shared mopeds become rented through survival analyses. The study observations are from the global positioning system records of an anonymous moped-sharing operator in Taipei, Taiwan. The empirical results indicate the following findings: (1) The associations of density and diversity attributes with moped-sharing use can refer to those of other shared vehicle uses but are dissimilar to those of general mopeds. (2) Moped-sharing service operators are suggested to move idle shared mopeds from employment centers to areas with dense residential, school, or retailing activities; diverse floor uses, industries, or transit services; and dense streetlights or moped parking spaces. (3) Moped-sharing service operators are also suggested to develop vehicle-rebalancing strategies in accordance with the built environment attributes within different catchment area sizes and periods. (4) Moped sharing is a complementary service rather than a competitive service to other intracity public transport services.

Optimized Composition of Business Process Web Services via QoS-Based Categorization Using Decision Tree Classifier and Knowledge-Based Decision Support

Determining web services according to Quality of Service (QoS) restrictions is the topic of discussion in this section. Decision tree classifiers are used to accomplish this classification. Because of the ever-changing and expanding nature of online services, it is necessary to accurately categorize them in order to make choosing them more efficient for consumers. It makes use of decision tree techniques, more especially the C5.0 classifier, this is an advancement over older approaches such as the C4.5 classifiers. It incorporates characteristics like as noisy handling, incomplete information administration, and improved decision-making correctness. Web services are classified into four distinct groups: Outstanding, Good, Average, and Poor. These classifications are determined by QoS metrics that include time to response, accessibility, performance, dependability, and success rate. The choice of features is accomplished utilizing an evolutionary algorithm with a wrapper technique with the goal to maximize the effectiveness of this category. This method minimizes the number of repetitive features and improves the method of classification for the purpose of optimization. The resilience and predicted reliability of the algorithm are ensured by additional approaches like as cross-validation and error reduction. These approaches also address difficulties such as overfitting and redundant characteristics. The construction of integrated web services for complicated corporate operations is a particularly valuable use of this technology, which also considerably improves the procedure for making choices for identifying services and consumption. Service 7 stands out with an impressive 98% performance, while Service 6 and Service 3 are also among the top-performing services. Compared to the others, Service 1, Service 2, Service 5, and Service 4 all exhibit comparatively poor results.

Optimal operation strategies for freight transport with electric vehicles considering wireless charging lanes

Unlike traditional recharging at fixed stations, wireless charging lanes equipped on the road network enable electric vehicles (EVs) to recharge while in motion, reducing the time required for EV recharging. Indeed, the availability of wireless charging lanes allows the urban freight transport service operators to consider adjusting EVs routing plan to do EV recharging in transit so that the total operational costs can be further reduced. Envisioning that wireless charging lanes would be practically constructed on the road network, this study aims to investigate how the optimal EV routing plan can be determined in a pickup and delivery problem in the future electrified mobility system. The problem is formulated into a mixed-integer programming model, and we propose a branch-and-price algorithm to solve it. Additionally, a large neighborhood search heuristic is incorporated within the column generation framework to effectively tackle the sub-problems. Computational experiments on test instances highlight the effectiveness of our proposed algorithm and demonstrate the potential of wireless charging lanes to reduce total operational costs.

Examining sustainable hospitality practices and employee turnover in Pakistan: The interplay of robotics awareness, mutual trust, and technical skills development in the age of artificial intelligence.

Integrating robots and artificial intelligence (AI) into workplaces is becoming increasingly prevalent across various sectors, including hospitality. This trend has raised concerns regarding employee anxiety and the potential for higher turnover intentions, particularly when AI technologies are perceived to undermine professional expertise. This study explores the relationship between awareness of robotics and AI and employee turnover intentions, framed within the Conservation of Resources Theory (COR). To address the challenges posed by AI in the workforce, hotel managers must prioritise organizational support in areas such as financial resources, policy development, career advancement, and employee adaptation. The hospitality industry is leveraging AI and robotics to enhance guest interactions and service delivery, yet this technological shift may inadvertently increase employees' intentions to leave their positions. Employing a cross-sectional design, we gathered data through a structured questionnaire utilizing a five-point Likert scale, targeting 435 employees from 5- and 7-star hotels in Lahore, Pakistan, including CEOs, managers, directors, supervisors, executives, and room service operators. Our findings reveal a significant positive relationship between awareness of robotics and AI and employee turnover intentions. Moreover, mutual trust (MT) emerged as a moderating factor positively affecting the association between robotics awareness and turnover intentions. While technical grooming (TG) and job insecurity (JI) were not previously discussed in the literature, our research indicates that they also play critical roles in this context, highlighting the complex interplay of factors influencing turnover intentions in the face of advancing technology.

SERVICE QUALITY IN FRONTIER-BASED BENCHMARKING MODELS: A PROPOSAL FOR BRAZILIAN TRANSMISSION SERVICE OPERATORS BY LITERATURE REVIEW

This study investigates the incorporation of service quality into frontier-based benchmarking models, focusing on Brazilian Transmission Service Operators (TSOs). Service quality is a critical variable in the regulatory context, as it directly reflects operational efficiency and consumer impacts. However, benchmarking models adopted in the Brazilian electric transmission sector, particularly those proposed by ANEEL for the 2017-2022 tariff review cycle, still exhibit gaps in the effective inclusion of quality proxies. The research is grounded in a systematic literature review conducted across the Web of Science and SciELO databases, covering studies published between 2000 and 2023. Articles discussing the integration of quality into benchmarking models were analyzed, with emphasis on methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). Data analysis included 32 Decision Making Units (DMUs) from Brazilian TSOs, covering the period from 2013 to 2016, based on ANEELs Technical Notes 160/2017 and 164/2017. Results indicate that service quality, when represented as a monetary variable, is most effective when incorporated as an input to adjust operational costs. The research highlights that ANEELs proposed model for the 2017 tariff review still lacks a consistent methodology for fully integrating service quality into benchmarking processes. The study concludes that adopting more robust proxies, such as the Parcel Variable (PV), could enhance the accuracy of efficiency assessments and ensure that TSOs meet appropriate performance standards, aligning with international best practices. This research contributes theoretically and practically to the ongoing debate on the optimal integration of service quality in regulated industries benchmarking models.

Urbanisation from the margins: auto-construction of urban spaces for paratransit services in Kumasi, Ghana

ABSTRACT In Ghana, paratransit services (three-wheeler taxis) have gained prominence because of their role in solving urban mobility challenges in major cities. While they are good at solving urban mobility challenges, they cause accidents and create congestion and inconveniences in the central business districts of cities. However, the literature on how paratransit service operators organise and create spaces for their operations is limited. We draw on peripheral urbanisation theory to understand how the operators produce urban spaces to conduct business in Kumasi. We hope to provide information for the planning and design of infrastructure that meets the needs of the different modes of urban mobility. In doing so, we adopt interviews and focus group discussions involving 35 purposively selected operators, 16 union executives, and two officials from the Kumasi Metropolitan Assembly to elicit the data. The responses were coded and categorised into themes for presentation. Findings indicate that the operators create space through negotiation and site selection. We conclude that securing spaces to conduct business is a major challenge to operators. Therefore, Kumasi Metropolitan Assembly should partner with communities, investors, and operators to create spaces for paratransit operators as it can provide a major source of revenue for development projects.

The Effect of Informal Food Service Operators’ Capabilities on Their Performance in Nigeria

Technology has become crucial for businesses of all scales, enhancing operational efficiency, customer experience, and overall performance. While many formal businesses have embraced technology, small and informal businesses, particularly in rural areas, often struggle with adoption due to resource constraints. This study examines the impact of technological capability (TC) on the performance of informal food service operators (IFO) in southwestern Nigeria. This study employed a quantitative approach whereby a closed-ended questionnaire was administered to 180 IFOs across different LGAs in Oyo State to elicit information about the effect of their activities on performance indicators. The response rate was 93.8%. Data was analyzed using a binary logistic regression model. Findings revealed that the innovation capability (β—1.657; p—0.003*) and production capability (β—3.276; p—0.009*) of the IFOs significantly influenced their sales turnover and profit level is influenced by innovation capability (β—1.657; p—0.013*), investment capability (β—2.013; p—0.004*) and linkage capability (β—2.716; p—0.003*) within the study area. The study recommends that there should be strong linkages between the operators and technology-providing organisations to enhance their innovation capability.

Vessel trajectory prediction in harbors: A deep learning approach with maritime-based data preprocessing and Berthing Side Integration

This study proposes a novel deep learning approach for vessel trajectory prediction in harbor environments, emphasizing the integration of berthing side information. Using Automatic Identification System (AIS) data from Busan Port, we compare Bidirectional Long Short-Term Memory (Bi-LSTM), Bidirectional Gated Recurrent Unit (Bi-GRU), and Transformer models. We identify the berthing side (port or starboard) as a crucial factor that influences vessel trajectories during berth approach, revealing significant differences in final approach paths. Port-side berthing vessels typically take the shortest course from the fairway endpoint, while starboard-side vessels approach parallel to the berth before final berthing. We employed advanced data preprocessing techniques, including DBSCAN clustering, cubic spline interpolation, and Gaussian noise-based data augmentation. Models were trained and evaluated on datasets with and without berthing side information. The Bi-LSTM model outperformed others in most scenarios, improving prediction accuracy by up to 23% when using berthing side-specific datasets. Paired t-tests confirmed statistically significant performance improvements for the Bi-LSTM model. This research enhances maritime safety and efficiency by providing more accurate trajectory predictions, enabling Vessel Traffic Services Operators (VTSOs) to respond to potential hazards swiftly and assisting pilots in developing safer berthing plans.

Promotion Strategies and Performance of Taxi-Hailing Services in Calabar Metropolis

This study examined promotion strategies and performance of taxi-hailing services in Calabar Metropolis. It specifically aimed to determine the effects of sales promotion, direct marketing, advertising, and influencer marketing on the performance of taxi-hailing services. The study adopted cross-sectional survey research design. A structured questionnaire was used to obtain primary data from 232 passengers of Bolt taxi services in Calabar. Descriptive statistics were applied for data analysis and interpretation, while the hypotheses developed for the study were tested using multiple linear regression in the Statistical Package for the Social Sciences (SPSS 23). The findings of the study revealed that the promotional strategies applied by taxi-hailing services (sales promotion, direct marketing, advertising and influencer marketing) have been effective in substantially improving their marketing performance in Calabar. Hence, it was recommended that operators of taxi-hailing services in Nigeria can enhance their marketing performance through sales promotion by implementing targeted promotional discounts during off-peak hours, introducing loyalty rewards for frequent users, and partnering with local businesses to offer bundled service packages, thereby attracting new customers and increasing customer retention. The study also recommended that operators of taxi-hailing services should integrate direct marketing strategies such as leveraging targeted social media campaigns to engage local communities, implementing personalized email promotions based on user preferences, utilizing strategic telemarketing to re-engage inactive users, offering exclusive in-app discounts and promotions, and creating compelling content marketing that highlights service benefits, thereby increasing customer acquisition, retention, and long-term engagement significantly. Other recommendations were made to provide a practical framework for operators of taxi-hailing services to improve marketing performance through effective promotional strategies.

비대면 상담서비스 운영 변화와 과제: 국내 사이트를 중심으로

Objectives This study aims to identify operational changes and challenges in the development of non-face- to-face counseling by comparing the past and present usage of contactless counseling in the context of the rapid increase in the use of contactless counseling due to the spread of COVID-19 and the development of information technology. Methods For comparison with the past, we used the survey methodology from a previous study (Kim, Kye-hyun, & Lim, Eun-mi, 2000) and analyzed 113 counseling sites, including five items (‘service target’, ‘service operator’, ‘counseling method’, ‘counseling content’, and ‘usage fee’) and two additional items (‘counselor’s expertise’ and ‘guidance on using non-face-to-face counseling’) as survey indicators. Results First, we found that counseling methods, which were limited in the early days of non-face-to-face coun-seling, are now being diversified through the development of technology and the expansion of media use. Second, we observed a new way of connecting counselors by establishing platforms for non-face-to-face counseling at large portal sites and private counseling organizations, not limited to the free services provided by public in-stitutions in the past. Third, although guidance for non-face-to-face counseling is currently provided, there is a lack of information on the expertise and confidentiality of counselors. Conclusions This study aims to identify the current status of non-face-to-face counseling in Korea by comparing the past and present operation status of non-face-to-face counseling in Korea, and to identify development tasks. It is expected to provide various implications on the need to strengthen the awareness, professionalism, and eth-ical considerations of non-face-to-face counseling.

A prospect theoretical choice model incorporating profitable and punctual uncertainties: an investigation in the participation of private car sharing

This study aims to examine people’s propensity to share private cars between peers accounting for the potential impacts of uncertainties underlying the sharing profit and vehicle returns. A mixed logit prospect theoretical model is developed to estimate the effects of uncertain variables and examine the unobserved heterogeneity using the data collected through a stated choice experiment in Hiroshima City, Japan. Results show that car owners are generally sensitive to the gains and losses for the revenue and the time of delayed returns, and people respond to uncertain situations differently. Individual participation in private car sharing is significantly influenced by the choices made by different social group members like family/relatives and friends/colleagues. These insights on individuals participation mechanism are helpful for service operators to promote the market share of private car sharing.

Enhancing Worker Safety Behaviors Through Proactive Interventions in the Lifting and Transport Equipment Industry

Unsafe worker behavior remains a prevalent issue leading to workplace accidents, particularly within companies specializing in services for head truck operations, maintenance, and lifting equipment. This study aims to enhance worker safety behaviors through proactive interventions utilizing behavioral observation and intervention (BO&I). Additionally, trend analysis is employed to predict the impact of interventions on worker safety behaviors. Mechanical workers involved in lifting and transport equipment operations are surveyed as respondents. The findings reveal a notable increase in the percentage of safe behaviors post-intervention compared to pre-intervention levels. Moreover, disparities in worker safety behaviors between pre- and post-intervention stages are identified, particularly in work stages associated with a high frequency of accidents. Trend analysis forecasts that the maximum percentage of safe worker behavior will be observed at the 91st intervention. Furthermore, binary logistic regression analysis indicates that variables such as age, tenure, utilization of personal protective equipment (PPE), and education significantly influence worker behaviors.

Traffic advisory for ship encounter situation based on linear dynamic system

Enhancing Situation Awareness (SA) is crucial for maritime traffic safety. Various indicators have been developed to assess risks in encounter situations and support the SA of Vessel Traffic Service Operators (VTSOs) and Officers on Watch (OOW), including collision risk and traffic complexity. Despite the widespread use of these navigational aids, ship collision incidents have not been effectively reduced. This paper abstracts ship encounter situations as linear dynamic systems to enhance the understanding of traffic situations. A traffic advisory framework based on the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) is proposed by integrating complexity metrics with risk indicators. The proposed method is validated through simulations of head-on, overtaking, and crossing scenarios, demonstrating its ability to accurately assess encounter complexity and issue advisories for free navigation, complexity, and resolution. Finally, we discuss the practical application of the proposed method through real-world experiments conducted in the waters of Qiongzhou Strait. The results indicate that the proposed method effectively quantifies the complexity of ship encounter situations and identifies high-collision-risk vessels from a microscopic perspective while providing insights into maritime traffic surveillance from a macro perspective.

Vessel Trajectory Prediction at Inner Harbor Based on Deep Learning Using AIS Data

This study aims to improve vessel trajectory prediction in the inner harbor of Busan Port using Automatic Identification System (AIS) data and deep-learning techniques. The research addresses the challenge of irregular AIS data intervals through linear interpolation and focuses on enhancing the accuracy of predictions in complex port environments. Recurrent neural network (RNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU), and Bidirectional GRU models were developed, with LSTM delivering the highest performance. The primary scientific question of this study is how to reliably predict vessel trajectories under varying conditions in inner harbors. The results demonstrate that the proposed method not only improves the precision of predictions but also identifies critical areas where Vessel Traffic Service Operators (VTSOs) can better manage vessel movements. These findings contribute to safer and more efficient vessel traffic management in ports with high traffic density and complex navigational challenges.

Virtual/Mobile Overdose Response in Canada: A Social Return on Investment Analysis

ObjectivesThe overdose epidemic continues to be one of the leading causes of death in North America and continues to contribute to high healthcare costs. Although harm reduction initiatives have significantly reduced the aforementioned costs, there is a dearth of evidence regarding overdose response hotlines and applications. We aim to evaluate the social return on investment from a payer perspective of one such overdose response hotline, Canada’s National Overdose Response Service, and its implications for service users, service operators, the Canadian healthcare system, and program funders. MethodsOutcome variables determined from theory of change models were developed in consultation with the aforementioned vested interest groups. Proxy values were attributed to each variable identified through values present within existing literature and databases. These values were then compared with operational costs accounting for deadweight, attribution, and displacement to determine a final social return on investment ratio. A discount rate was then applied based on the influence of risk on the outcome achieved. ResultsThe ratio illustrating the value created for all stakeholders, resulting from the $1 592 000 investment made over 2 years, is $15.84 per single dollar invested. The value generated stems primarily from overdose prevention, mental health support, staff employment, reductions in emergency service utilization, service referrals, and volunteer well-being, which outweigh costs including operational funding, work-related stressors, compassion fatigue, and false calls. ConclusionsThe results of our study demonstrate that the National Overdose Response Service provides a social value that far outweighs the costs attributed to the program’s operation.

Onion Services in the Wild: A Study of Deanonymization Attacks

Tor, the leading anonymization network, routes traffic over multiple relays to ensure client anonymity. Its Onion Services allow users to host services within the Tor network without revealing their location. While these techniques are crucial for users in authoritarian regimes and whistleblowers, they are also exploited by criminals. This paper diverges from the common focus on the technical vulnerabilities of the Tor protocol and instead explores the practical aspects of deanonymizing Onion Service users and operators. Despite Tor's robust security mechanisms, human errors in its usage and operation frequently lead to deanonymization. This study models law enforcement agencies as powerful attackers and evaluates documents from 136 court cases to determine investigative methods. We find that investigators employ different methods depending on the offense, with user mistakes being the dominant angle. Technical attacks, though comparatively rare, are highly effective and can potentially impact a large number of users simultaneously. Attacks on the well-researched Tor protocol are exceptionally rare, but their impact is even more significant. We argue that the human aspect of using Tor is the most critical deanonymization angle and that tailored guidelines for ethical users can help protect them from oppressive retaliation while still enabling the prosecution of criminal activity.

A Formalism for Scalable Maritime Traffic Monitoring and Explainable Anomaly Detection and Resolution at Vessel Traffic Services

Abstract Vessel traffic service (VTS) centres around the globe monitor and manage the ship traffic in their areas of responsibility and respond to arising unsafe or inefficient situations. Decision support tools (DST) help vessel traffic service operators (VTSO) to enhance their situational awareness and decision-making process, thus to recognise and assess dangerous situations. However, current DST have unsophisticated features and require manual configuration by the operator. Firstly, triggers for alerts are mostly based on the creation of geographical polygons for spatial-dependent assignment of rules, thresholds, ranges and limits for specific features. Secondly, calculations for the detection of safety-critical situations rely on measurements based on the closest point of approach (CPA) without taking contextual information into account. Thirdly, trajectory predictions are performed considering a constant velocity model (CVM) which does not depict reality. Due to these and other peculiarities, current DST are prone to false alerts. This results into a high workload where unsafe situations may be overlooked. In this paper, we propose a hierarchical formalism as foundation for an anomaly detection and resolution which generates less false alerts. The formalism consists of three hierarchical layers which represent, objects, measurements and situations. The formalism ensures adaptability and extensibility to various VTS areas and traffic patterns. Moreover, due to the given structure, the presented formalism is easily implementable, adaptable and scalable taking the currently available technological capabilities at VTS centres into account. We demonstrate the feasibility of this formalism by implementing a proof-of-concept and assessing it with realistic scenarios. Our implementation utilizes a rule-based system as central framework and it is configured through statistical methods, e.g. machine learning. Given this hybrid approach, the implementation provides reasonable and explainable results. This enables comprehensibility and verifiability by authorities and operators which is crucial for acceptance.

Efficiency versus market power in the rail industry

Although an extensive literature exists that examines efficiency in rail markets, analyses that also study the market power of rail operators are scarce. We examine the effects of competition and vertical separation on efficiency and price-cost margins. In doing so we propose a two-stage procedure. Firstly, efficiency and Lerner indexes will be obtained for a sample of rail operators for the period 2000–2016. Secondly, the determinants of both indexes are jointly estimated. Results indicate that integrated incumbents not facing competition perform worst and exert the highest market power. Vertically separated and specialized in passenger services operators display the strongest improvements in efficiency levels, while integrated incumbents facing competition show the lowest market power indexes. Finally, more efficiency translates to smaller values of the Lerner index.

IMPLEMENTATION OF PRESIDENTIAL REGULATION NUMBER 26 OF 2009 ON E-KTP SERVICE POLICY AT SUB-DISTRICT OFFICES IN BANJARBARU CITY

The E-KTP programme was initiated in response to the conventional ID card system in Indonesia, which allowed individuals to possess more than one ID card. The policy for changing the administration of population registration, as mandated by Law Number 23 of 2006, aims to establish an orderly population database, proper issuance of Population Identification Numbers (NIK), and accurate population documents. To achieve the main goals of population administration, it is necessary to implement a Nationally-based NIK ID card (Electronic ID Card) for all eligible residents. This study aims to examine the implementation of Presidential Regulation Number 26 of 2009 concerning the E-KTP service policy in sub-districts within Banjarbaru City, focusing on the challenges encountered and possible solutions. The research was conducted using a qualitative method, with data collected through interviews, documentation, and field observations. Primary data sources included informants, supported by observations and documentation from the research location. The data analysis was conducted using qualitative descriptive techniques. The study's findings reveal that the implementation of Presidential Regulation Number 26 of 2009 regarding the E-KTP service policy at sub-district offices in Banjarbaru City has been effective, with clear procedures and free services. However, challenges remain, including residents who are registered but have not yet completed the E-KTP recording, a shortage of service staff or operators (only one person available), and a lack of information and socialisation regarding E-KTP knowledge among the local population. The implications of this research suggest the need to raise public awareness about the importance of the E-KTP programme, increase the number of service staff or operators, and enhance the dissemination of information and socialisation efforts related to E-KTP awareness among the community. Keywords: Evaluation, Implementation, E-KTP

Measuring concentration in the Colombian telecommunications market

Telecommunications markets have a giant impact on countries’ economies. An example of this is the great potential offered by the internet service, which allows growth in various aspects such as productivity, education, health, and connectivity. A few companies dominate telecommunications markets, so there is a high market concentrations risk. In that sense, the state has to generate strong regulation in the sector. Models for measuring competition in telecommunications markets allow the state to monitor the concentration performance in these markets. The prediction of competition in the telecommunications market based on artificial intelligence techniques would allow the state to anticipate the necessary controls to regulate the market and avoid monopolies and oligopolies. This work’s added value and the main objective is to measure the current concentration level in the Colombian telecommunications market, this allows for competitive analysis in order to propose effective strategies and methodologies to improve competition in the future of Colombian telecommunications services operators. The main result obtained in the research is the existence of concentration in the Colombian telecommunications market.