Mobile Services Research Articles

Influence of Digital Marketing Techniques on Consumer Behavior for Mobile Services

The aim of this research was to explore how different digital marketing techniques, such as video marketing, internet advertising, email marketing, and SEO, impact consumer behavior regarding mobile services offered by Zain Telecom in Amman, Jordan. A simple random survey method was employed, with 445 questionnaires distributed to Zain Telecom customers in Amman. After excluding incomplete responses, 405 completed questionnaires were analyzed using multiple regression, descriptive analysis, and reliability testing. The findings indicate that all the independent variables significantly influence consumer behavior in purchasing mobile services, with email marketing exhibiting the strongest impact. Consequently, the study suggests an increased investment in email marketing techniques

Assessing the substitutability of mobile and fixed internet: The impact of 5G services on consumer valuation and price elasticity

In this study, we explore the dynamics of consumer choices in the Polish telecommunications market, focusing on preferences and valuations for home fixed, home mobile, and purely mobile Internet connections. Key attributes such as speed, latency, data limits, and cost are examined. Central to our research is the investigation of how the integration of 5G technology might influence demand elasticity. Using a detailed discrete choice experiment, we apply a mixed logit model with random parameters to analyze stated choice data, enabling us to unravel the complexities of demand elasticity, especially in terms of own and cross-price elasticities. This approach facilitates an assessment of the degree of substitutability between fixed and mobile Internet services.Our findings indicate a moderate substitution effect between fixed and mobile Internet services. Results from a Small but Significant and Non-transitory Increase in Price (SSNIP) test suggest that these markets should continue to be regulated separately, mirroring the distinct regulation observed in fixed and mobile telephony. Furthermore, simulations provide insights into potential future market shifts with the advent of 5G services. This paper contributes significantly to the discourse on fixed-mobile Internet substitution and offers vital insights for defining markets in antitrust discussions, competitive agreements, and potential mergers within the telecom sector.

The Effect of Trust, Perceived Ease of Use, and Service Features on Trust and Customers’ Interest in Using Mobile Banking

This study aims to describe the effects of security, perceived ease of use, and service features on customers' interest in using mobile banking, with trust as an intervening variable. This study used quantitative approach as the research methodology. Data were garnered using a questionnaire. Participants were 200 customers of BPD DIY bank, recruited using purposive sampling technique. The result showed that service feature affects customers’ trust in using mobile banking, but not their interest. Security and perceived ease of use do not affect customers’ trust and interest. Thus, the bank is recommended to focus on building trust and ensuring the security of its mobile banking service in order to improve customers’ interest in using it. Future studies are recommended to explore other factors affecting customers’ interest in using mobile banking.

HCV testing and linkage to care for hepatitis C virus infection for marginalized drug user populations attending a harm reduction service in Bologna, Italy.

Our aim was to estimate the prevalence of HCV in a highly vulnerable population of substance users living with social difficulties and marginality who came into contact with the mobile harm reduction service in the city of Bologna (Northern Italy). Testing was offered in a van (mobile unit) by using a point-of-care HCV antibody test. For the HCV RNA test, the Xpert HCV Viral Load Fingerstick Test was used. Participants with a detectable HCV RNA were accompanied within two weeks to the Infectious Diseases Department Sant' Orsola Hospital Bologna to start HCV treatment. With regard to the main study findings, 54% reported having never been HCV tested before; a prevalence of HCV RNA of 6% among all participants and 22% among those injecting drugs was found; among the HCV RNA positive participants, 80% were accompanied to treatment. Our study suggests that mobile harm reduction services, in networks with healthcare facilities, are able to offer a continuous HCV screening service and linkage to care for people with drug use living in socially marginalized conditions.

Digital Divide dalam Adopsi Mobile Banking di Kota Purbalingga: Suatu Kajian

One sign of progress in the banking industry is the creation of mobile banking services that provide convenience for customers. However, the use of mobile banking is not evenly distributed in all regions, one of which is Purbalingga City which still has minimal use of digital transactions, especially mobile banking. This research aims to find out whether there is a digital gap regarding the use of mobile banking in Purbalingga City. This research uses digital divide variables consisting of motivation, physical & material access, mobile banking skills and also usage, using quantitative methods using PLS-SEM as a data analysis technique. The sampling technique used in this research is nonprobability sampling with purposive sampling. Data collection uses secondary data and primary data through distributing questionnaires. This research consists of 301 samples taken from the population of the Purbalingga City community who use mobile banking. The results of this research show that there are 4 (four) latent variables consisting of motivation, physical and material access, as well as skills and use of mobile banking have a positive and significant effect on the use of m-banking in Purbalingga City.

Shared autonomous micro-mobility for walkable cities

The integration of autonomy into micro-mobility systems has given rise to a new solution known as shared autonomous micro-mobility (SAmM)11SAmM = Shared autonomous micro-mobility.. This paper delves into the opportunities that emerge from this concept, which is driven by the resurgence of walkable, human-centric cities and the advancements in autonomous vehicles. While most autonomous vehicle research has focused on cars and taxis, SAmM proposes more lightweight and environmentally friendly alternatives that align with the vision of more human-centered, walkable cities. At the same time, the integration of autonomy into micro-mobility systems holds the potential to enhance efficiency by reducing fleet sizes and increase convenience by transforming them into on-demand mobility services. This study presents a roadmap for the successful implementation of SAmM, covering essential aspects such as vehicle design, infrastructure requirements, and operational strategies. This research sheds light on the transformative potential of SAmM and provides insights for mobility operators, urban planners, policymakers, and researchers.

Mobile Service Quality’s Impact on Customer Repurchase Intention in Food and Beverage Mobile Applications

This study aims to assess the impact of mobile service quality on customer repurchase intention in Indonesia’s food and beverage mobile applications. The research identifies key dimensions such as application design, ease of use, privacy, and customer support and evaluates their influence on customer e-satisfaction and repurchase behavior. A quantitative approach was employed, utilizing purposive sampling to gather data from 401 active users of these applications. The analysis, conducted using Structural Equation Modeling-Partial Least Squares (SEM-PLS), revealed that these dimensions significantly enhance overall mobile service quality, which in turn positively affects customer e-satisfaction and repurchase intention. The findings underscore the importance of a minimalist and user-friendly design, robust privacy measures, and responsive customer support—particularly for Gen-Z users in Indonesia, where privacy concerns are increasingly prominent. This study contributes to the existing literature by providing insights specific to the Indonesian market and offering practical recommendations for the food and beverage industry to improve mobile service quality, thereby fostering stronger customer loyalty and increasing repurchase rates. The novelty of this research lies in its focus on the rapidly growing mobile app market in Indonesia, addressing unique regional challenges and opportunities. Doi: 10.28991/HIJ-2024-05-03-011 Full Text: PDF

Clarifying new urban mobility services based on a threefold business model framework

Market entrants have brought a variety of new urban mobility services over the past years, which are rooted in the sharing economy and have their origin in digitalization. Digital data serve as key resource of a business model and, accordingly, digital technologies are the basis of key activities. Building our analysis on the resource-based view and on the business model debate, we ask: what degrees of digitalization do urban mobility service business models exhibit? We perform a systematic literature review and a qualitative content analysis. As a result, we identify a continuum of highly and lowly digitalized business models. We derive a threefold business model framework, substantiated in conventional mobility, hybrid, and data-driven business models. (1) Conventional mobility business models are dominated by mobility as a key resource, digitalization is low and performed by key partners, (2) hybrid models contain both conventional mobility and data-driven key resources, and (3) data-driven models take digital data as key resources, while conventional mobility is carried out by key partners. As a first main contribution, we conceptualize conventional versus purely data-driven business models along the continuum of data-driven business model components. New urban mobility services are the group of both hybrid and data-driven business models, while conventional urban mobility stands on its own. As a second contribution, we clarify the Mobility-as-a-Service (MaaS) concept by corroborating it as a purely data-driven business model with key partners provisioning mobility.

Methodology for Design of Hydrogen Robot for Medical Needs

The paper examines the concept of creating a Collaborative Service Robot powered by a Hydrogen Fuel Cell designed to assist in medical facilities. The characteristics of this robot are analyzed and its advantages are highlighted, from the point of view of ecological operation and long life during the patient service activities in a hospital facility. Some key features and benefits of Hydrogen Fuel Cell-powered robots are compared to battery-powered robots and the positives in this comparison are shown. The advantages of modern Collaborative Robots used as Service Robots in inpatient service processes in a hospital are presented. It shows the possibility, based on the competence and expertise of the authors in the field of Service Mobile Collaborative Robots, to create and implement one for the needs of human service in medical facilities, which will be powered by a hydrogen fuel cell. The main characteristics of the created mobile collaborative service robots of the ``AnRI'' series (Anthropomorphic Robot with Intelligence) are briefly indicated, where ``AnRI-1'' is equipped with a manipulator with a three-finger gripper, and ``AnRI-2'' is an information robot equipped with a large screen on top. The article analyzes the process of creating these collaborative robots, realizing several important elements of the control system, such as its development with elements of Artificial Intelligence. The advantages of hydrogen power and increased reliability of the general complex of systems in these Collaborative Mobile Robots and their possibility to be used effectively in the realization of medical care are emphasized.

A sequential transit network design algorithm with optimal learning under correlated beliefs

Mobility service route design requires demand information to operate in a service region. Transit planners and operators can access various data sources including household travel survey data and mobile device location logs. However, when implementing a mobility system with emerging technologies, estimating demand becomes harder because of limited data resulting in uncertainty. This study proposes an artificial intelligence-driven algorithm that combines sequential transit network design with optimal learning to address the operation under limited data. An operator gradually expands its route system to avoid risks from inconsistency between designed routes and actual travel demand. At the same time, observed information is archived to update the knowledge that the operator currently uses. Three learning policies are compared within the algorithm: multi-armed bandit, knowledge gradient, and knowledge gradient with correlated beliefs. For validation, a new route system is designed on an artificial network based on public use microdata areas in New York City. Prior knowledge is reproduced from the regional household travel survey data. The results suggest that exploration considering correlations can achieve better performance compared to greedy choices and other independent belief-based techniques in general. In future work, the problem may incorporate more complexities such as demand elasticity to travel time, no limitations to the number of transfers, and costs for expansion.

Impact of Cryptocurrency Adoption on Financial Inclusion in Myanmar

Purpose: Aim of the study was to analyze the impact of cryptocurrency adoption on financial inclusion in Myanmar. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Cryptocurrency adoption in Myanmar holds promise for enhancing financial inclusion by offering faster and cheaper remittance options, especially in underserved rural areas. However, challenges such as regulatory uncertainties and concerns over consumer protection must be addressed through clear and supportive regulatory frameworks. To maximize benefits, Myanmar should focus on improving financial literacy, developing user-friendly cryptocurrency platforms integrated with mobile money services, and establishing coherent regulatory guidelines in collaboration with international bodies. Unique Contribution to Theory, Practice and Policy: Diffusion of innovation theory, technology acceptance model (TAM) & institutional theory may be used to anchor future studies on impact of cryptocurrency adoption on financial inclusion in Myanmar. Practical initiatives should prioritize enhancing financial literacy and digital education programs tailored to Myanmar's population. Initiatives that promote understanding of blockchain technology and cryptocurrencies among consumers, businesses, and policymakers are crucial. Policymakers in Myanmar need to develop clear and supportive regulatory frameworks that balance innovation with consumer protection.

Generating sparse origin–destination flows on shared mobility networks using probabilistic graph neural networks

Shared mobility services, such as bike sharing, have gained immense popularity and emerged as an integral part of sustainable urban mobility solutions. The planning of such systems requires forecasting the potential origin–destination (OD) flows between mobility sites (e.g., bike sharing stations) within the proposed network. Existing methods primarily focus on mobility flows between large regions, and do not generalize well to detailed planning applications due to the high spatial resolution required, with increased uncertainty and data sparsity. This study proposes a zero-inflated negative binomial graph neural network (ZINB-GNN) to generate sparse OD flows while capturing complex spatial dependencies. To reflect sparsity, OD flows are modeled as following ZINB distributions parameterized via feed-forward networks. To capture spatial dependencies, localized graphs are constructed to represent proximity between OD pairs, with spatial features encoded using GNNs. ZINB-GNN is validated through a case study of the bike sharing system in New York City. The results verify its prowess in both prediction accuracy and uncertainty quantification under real-world network expansion scenarios. We also demonstrate its interpretability by revealing important factors affecting OD flows. These findings can directly inform the planning of bike sharing systems, and the methodology may be adapted for other shared mobility systems.

Robot Operating Systems–You Only Look Once Version 5–Fleet Efficient Multi-Scale Attention: An Improved You Only Look Once Version 5-Lite Object Detection Algorithm Based on Efficient Multi-Scale Attention and Bounding Box Regression Combined with Robot Operating Systems

This paper primarily investigates enhanced object detection techniques for indoor service mobile robots. Robot operating systems (ROS) supply rich sensor data, which boost the models’ ability to generalize. However, the model’s performance might be hindered by constraints in the processing power, memory capacity, and communication capabilities of robotic devices. To address these issues, this paper proposes an improved you only look once version 5 (YOLOv5)-Lite object detection algorithm based on efficient multi-scale attention and bounding box regression combined with ROS. The algorithm incorporates efficient multi-scale attention (EMA) into the traditional YOLOv5-Lite model and replaces the C3 module with a lightweight C3Ghost module to reduce computation and model size during the convolution process. To enhance bounding box localization accuracy, modified precision-defined intersection over union (MPDIoU) is employed to optimize the model, resulting in the ROS–YOLOv5–FleetEMA model. The results indicated that relative to the conventional YOLOv5-Lite model, the ROS–YOLOv5–FleetEMA model enhanced the mean average precision (mAP) by 2.7% post-training, reduced giga floating-point operations per second (GFLOPS) by 13.2%, and decreased the params by 15.1%. In light of these experimental findings, the model was incorporated into ROS, leading to the development of a ROS-based object detection platform that offers rapid and precise object detection capabilities.

The effect of electronic integrated marketing communication on consumers purchasing behavior of mobile service: A case study from Jordan

The purpose of this study was to examine the effect of E-integrated marketing communication on consumers’ purchasing behavior of mobile services. The population for the study involves all orange telecom mobile service customers in Jordan. Three hundred ninety-five questionnaires were distributed to orange telecom customers in Jordan, however, 375 only returned, which has been used for analysis. structural equation modeling using programs such as AMOS was used to investigate the impact of E-integrated marketing communication on consumers’ purchasing behavior. Data was collected through questionnaires was sent to study sample. The results of the study showed that E-integrated marketing communication had a positive impact on consumers’ purchasing behavior. Based on the findings, the study recommended that Orange Telecom should focus more on e-public relations to create a favorable image of the company among different groups of consumers, which can potentially enhance their purchasing behavior towards its mobile services. It is imperative for Orange Telecom to prioritize its e-integrated marketing communication strategy to effectively reach out to its target audience and influence their purchase decisions.

Measuring the effectiveness of incorporating mobile charging services into urban electric vehicle charging network: An agent-based approach

Mobile charging service (MCS) has emerged as a cost-efficient solution to compensate for the limitations of fixed charging stations (FCSs) in service capacity and coverage. Nevertheless, the impacts of incorporating the MCS into the charging infrastructure network have not been well understood. Therefore, this study introduces an exhaustive framework for devising Agent-based Modeling (ABM) to delineate electric vehicle (EV) drivers' daily travels and charging behaviors within the integrated charging network. Specifically, the developed ABM framework encompasses both internal attributes of individuals and external variables of charging and transport networks that potentially shape EV drivers’ public charging decisions. It generates authentic daily charging demands for FCSs and MCSs and provides a streamlined process to further incorporate more charging modes into the EV charging ecosystem. Subsequently, we opted for the Salt Lake City metropolitan area to implement our framework and showcase the effectiveness of MCS integration on the charging network over various EV adoption levels and network settings. The findings of the designed case study unravel the choice patterns of EV drivers when facing diverse charging options and pinpoint the strengths and weaknesses of MCS incorporating into the urban charging network at different stages.

Impact of Forced Relocation and Community Integration on Household Well-being of Urban Refugees in Kenya

Forced displacement is a global issue that affects millions of people all over the world. Refugees are forced to flee their homes due to conflict, persecution, or other forms of violence. The majority of refugees often end up in urban areas, where they face numerous challenges, including social exclusion, limited access to basic services, and economic marginalization. This study examines the relationship between forced displacement, social cohesion, and household welfare outcomes of urban refugees in Kenya. The study utilized household data on urban refugees in Kenya sourced from the United Nations High Commission for Refugees (UNHCR), 2020 [85], and, the Kenya Continuous Household Survey (KCHS), 2019 [41]. The study estimates were regressed using the Ordinary Least Squares method and diagnostic tests were done to determine the accuracy of the estimates. The study found that an additional member in an urban refugee household led to an asset increment of 6.7%. The study further found that an additional habitable dwelling in an urban refugee household increased family assets by 71.9%. Utilization of mobile banking services, having nuclear members abroad, and participation in community-based organizations also had a positive impact on family asset accumulation in a refugee household. The study also found that utilization of mobile money transfer (M-PESA), negatively influenced family assets. This study contributes to the literature on Urban refugees as it gives insights into factors that can improve welfare and enhance social cohesion between refugees and host communities in Kenya. Gaps have also been identified in the mandate of UNHCR beyond the camps and the role of the Kenyan Government in urban housing programs for refugees.

PENERAPAN METODE WASPAS DAN ROC DALAM PEMILIHAN BANK TERBAIK UNTUK PELAYANAN MOBILE BANKING

Technological developments encourage increased use of banking services via mobile devices. Choosing the optimal bank for mobile banking services is an important challenge in meeting customer needs. This research uses a Decision Support System with the application of the Weighted Aggregated Sum Product Assessment (WASPAS) and Rank Order Centroid (ROC) methods. The WASPAS method helps find positive and negative ideal solutions in solving problems. The ROC method was chosen to reduce the level of subjectivity and uncertainty in determining weights. The weights in ROC are determined based on priority criteria. In this research, 5 alternatives are used, namely BCA Mobile, Livin' by Mandiri, BSI Mobile, BNI Mobile Banking, BRImo BRI, and apply criteria such as security, many enthusiasts, user friendly, rating, and cost. This research aims to provide a comprehensive picture of the quality of mobile banking services provided by various banks so as to help customers choose mobile banking according to the criteria they need. The research results show that BCA Mobile owned by BCA bank is the best alternative with the highest value of 0.940, followed by BRImo with a value of 0.613, BNI Mobile with a value of 0.612, Livin' by Mandiri 0.611, and the lowest value of 0.323 for BSI Mobile. Thus, BCA Mobile is declared the best choice for mobile banking services.

Investigation of Perception Differences in Shared Mobility between Driver’s License Holders and Nonholders: A Case Study of Seoul, Gyeonggi, and Incheon in South Korea

Shared mobility (SM) services are transitioning from the introduction stage to the growth stage, driven by the growth of the sharing economy, the promotion of smart cities, the diverse personal transportation modes, and the development of autonomous driving technologies. SM services, such as car sharing, car-hailing, shared bikes, and e-scooters, have emerged as solutions to address issues related to carbon neutrality and traffic congestion in densely populated areas. The purpose of this study is to investigate potential disparities in user perception and satisfaction among groups with or without driving experience when using SM services—through hypothesis testing using the two-proportion Z-test. Subsequently, a satisfaction analysis is conducted. This research creates foundational data for future SM services. The survey targeted 1041 residents living in Seoul, Gyeonggi Province, and Incheon, and was conducted over two weeks in March 2020. This study aims to derive associations between two groups using SM—those with and without driving experience. The results indicate that car sharing and bike sharing showed significant differences in user patterns based on driving experience, whereas e-scooters and car-hailing did not exhibit significant differences. This contradicts the assumption that people without a driver’s license would use SM more frequently. Moreover, the results of each SM’s analysis show different usage patterns and satisfaction between driver’s license holders and nonholders. This study will serve as foundational data for researching strategies to reduce personal car ownership through the promotion of public transportation and SM services. Furthermore, it can be a basis for suggesting policy recommendations to facilitate future mobility systems.

Mobile Government Service Promotion Strategies: Exploring Sustainable Development Pathways Based on Provincial Government Practices in China

The level of mobile government services has become a crucial metric for modernizing a government’s governance capabilities, and it plays a significant role in promoting sustainable development. This study aims to explore the key factors influencing the level of mobile government services across 31 provinces in China, along with their combinatory pathways. Using the technology–organization–environment (TOE) framework and employing fuzzy-set qualitative comparative analysis (fsQCA), this study conducts an in-depth analysis of mobile government service levels across these provinces, focusing on the dimensions of technology, organization, and environment. The results identify three pathways that promote high levels of mobile government services: technology–organization, technology–environment, and internal–external linkage-driven pathways. These pathways offer viable strategies for achieving sustainable development in mobile government services. Additionally, this study identifies two pathways associated with lower service levels, technology deficiency, and organization–environment misalignment, highlighting key factors that hinder sustainable development. The findings suggest that organizational and environmental factors can complement each other based on technological conditions, internet penetration rates, and citizen participation levels. Based on these insights, this study recommends that provincial governments proactively explore sustainable development pathways, optimize the “technology–organization–environment” conditions to harness synergies, and work towards enhancing mobile government service levels, thereby reducing inter-provincial disparities and advancing sustainable development.

A shift scheduling model for ridepooling services

AbstractThe planning of efficient shift schedules is a key challenge for many service companies whose economic success heavily relies on the efficient employment of personnel. In spite of the recent advances in autonomous driving, mobility services, such as ride pooling, still heavily rely on the use of human drivers and will presumably remain in this category in the near to midterm. As a consequence, shift scheduling of drivers is one of the key success factors in the current industry environment. Determining appropriate shifts that minimize an under- and oversupply of vehicles for all planning periods is a challenging task, since demand can vary heavily over time and the assignment flexibilities are limited due to driver preferences and regulations. In this work, we present a shift scheduling model for ridepooling services. Moreover, we introduce a data generator for instances with realistic properties of a ridepooling service. Using it, we study the effect of different kinds of flexibilities on solution quality.