Online Services Research Articles

Yonder: Prescribing cascades, teacher wait time, online services for mental health conditions, and community deep vein thrombosis pathways.

Yonder: Prescribing cascades, teacher wait time, online services for mental health conditions, and community deep vein thrombosis pathways.

Real-time service task scheduling with fine-grained resource utilization to benefit important industrial business

Scheduling of service-oriented industrial businesses to meet the real-time requirements and improve the computing resources utilization is important. To this end, a Fine-grained Online Service Task Scheduling (FOSTS) method is proposed. First, a service task model that separates the invoked service from the task is established. Then, a service invocation-oriented allocation mechanism that allocates the invoked tasks based on priority is proposed to achieve fine-grained resource utilization. In addition, a task suspension mechanism to release resources for important tasks by suspending non-important tasks is proposed. The proposed FOSTS is tested in a typical industrial scenario and its performance is compared with many common and state-of-the-art methods. The simulation results show the effectiveness and superior performance of the proposed FOSTS compared to the other methods.

Online Age Verification: Government Legislation, Supplier Responsibilization, and Public Perceptions.

There are widespread concerns about the online harms to children operating online. As such, governments have enacted laws to require online service providers to deploy age verification to prevent such harms. We investigate the following three research questions regarding this topic: (1) To what extent have different governments legislated age verification controls? (2) Do governments embrace a responsibilization strategy when it comes to online age verification? and (3) How does the UK public feel about online age verification legislation? We find that governments are applying a responsibilization strategy, which has led to widespread deployment of privacy-invasive or ineffective age verification. The former violates the privacy of underage users, with the latter undermining the overarching aims of the legislation. We have also found general disengagement and a lack of trust in the government amongst the public with regards to new online age verification laws within the UK. To conclude, despite governments globally looking to put more robust online age verification mechanisms in place, there remains a general lack of privacy preservation and affordable technological solutions. Moreover, the overarching aims of the online safety and age verification legislative changes may not be satisfied due to the general public stakeholder group's disengagement and lack of trust in their government.

A combined AraBERT and Voting Ensemble classifier model for Arabic sentiment analysis

For sentiment analysis of short texts (e.g. movie reviews, tweets, etc.), one approach is to build machine learning models that can determine their tones (positive, negative, neutral). However, these natural language processing (NLP) studies are missing when there is a lack of high-quality and large-scale training data for specific languages such as Arabic. In this paper, we present three machine learning models designed to classify sentiment Arabic tweets developed for a Kaggle competition. We present a Voting Ensemble classifier taking advantage of both character-level and word-level features. We also propose an AraBERT (Arabic Bidirectional Encoder Representations from Transformers) model with preprocessing using Farasa Segmenter. Finally, we combine these first two approaches as a third approach (Voting Ensemble classifier using AraBERT embeddings). Performance measures of results show improvement over previous efforts for all models. The third model exhibits strong performance with a 73.98% F-score score. The work presented here could be useful for future studies and for new Arabic sentiment analysis online services or competitions.

Technological And Connectivity Conditions of Undergraduate Students of Economics, Accounting and Administrative Sciences at A Peruvian Public University

The purpose of the research was to identify the ICT and connectivity conditions of university students and how they use them in their undergraduate studies at a Peruvian public university. Data was collected from 208 students of the Professional Schools of Business Administration, Tourism Administration, Accounting and Economics enrolled in the Academic Semester 2024-1, with the support of a Google Forms survey. The results show that students mainly use laptops (90%) and cell phones (95%). They use wifi networks for their studies, 35% of them do not a c c e s s a network at the University or home. The preferred mobile operators are Claro (38.3%) and Bitel (35%). The preferred online service is Canva (48.3%). The most used social network is Facebook (88.3%), followed by Tik Tok (66.7%), Instagram (60%), YouTube (43.3%) and Twitter (25%). Technological conditions are limited to promote academic learning.

MEASURING TH INFLUENCE OF E-SERVICE QUALITY TOWARD E-CUSTOMER SATISFACTION AND E-CUSTOMER LOYALTY ON ONLINE STORE BUYING BEHAVIOUR

This research is aimed to analyze the effect of e-service quality on e- customer satisfaction and e-customer loyalty. item questionnaire used as many as 20 items. Data collection is done by distributing questionnaires to customers who at least routinely shop once in a month in one or more online store in Indonesia with the number of samples of 275 respondents determined by nonprobability sampling method. Data analysis technique used is Partial Least Square-Path Modeling Reflective Multidimensional Construct (Second Order Construct) with SmartPLS 3.0 software and 5% significance level. The results obtained in this study are e-service quality has direct effect to e- customer satisfaction, e-satisfaction has a direct effect on e-customer loyalty, e- service quality has direct effect on e-customer loyalty, and e-service quality has indirect effect to e-customer loyalty through e-customer satisfaction. The advice for the company is to improve online-based services online both in terms of management and infrastructure. Suggestions for future researchers are able to refine with better theories and data and research not only on the e-commerce sector but also in other technology-based business areas.

TAP with ease: a generic recommendation system for trigger-action programming based on multi-modal representation learning

The escalating popularity of smart devices has given rise to an increasing trend wherein users leverage customized trigger-action programming (TAP) rules within the Internet of Things (IoT) to automate various aspects of their lives. This article addresses the challenge of effectively combining functions provided by many smart devices and online services by introducing a novel multi-modal representation learning model called TAP-TAG. This model integrates both textual and graph structures inherent in TAP rules, offering a holistic method to rule recommendation. TAP-TAG comprises two branches: the Knowledge Graph Embedding model, which projects triplets extracted from the TAP dataset into embeddings, and convolution neural networks that extract semantic features from the textual content of TAP rules. Extensive experiments are conducted on real-world TAP datasets to evaluate our model’s ability to recommend relevant rules based on user preferences. The experimental results show that TAP-TAG can outperform the state-of-the-art method by 5% in Precision@5, indicating that TAP-TAG is highly effective in providing accurate and diverse recommendations for TAP rules.

A Modular Service for Causal Inference in the Context of the Gaia-X Ecosystem.

Causal inference seeks to learn the effect of interventions on outcomes. Its potential in the health domain has been dramatically increasing recently, due to advancements in machine learning, as well as in the growing amount of medical data collected. Gaia-X provides a framework to implement Health Data Spaces at scale, in a compliant, secure, and trustable manner. In this paper, we provide a modular online service for causal inference using observational data, building on the Gaia-X framework. While two versions of the IDA algorithm for causal inference are already provided, the service allows users to further contribute algorithms in various programming languages (not only for causal inference), as well as their data, and efficiently execute these on a central server. Additionally, the platform facilitates the exchange of algorithms and data among participants. Users of the platform can enter into agreements with other users over the use of algorithms and data. Calculations can be carried out directly on the platform without the need to locally store foreign data.

Evaluating Airline Passengers’ Satisfaction during the COVID-19 Pandemic: A Case Study of AirAsia Services through Sentiment Analysis and Topic Modelling

AirAsia has emerged as a dominant force among prominent low-cost airlines in recent years. However, the COVID-19 pandemic outbreak has severely impacted airline services, including AirAsia. There is a strong need for airline services to monitor customer experience and satisfaction from online customer reviews on the website to keep pace with changing customer perceptions toward their service quality. A growing number of travelers choose to express their experiences and emotions on online customer review platforms, resulting in substantial online airline service evaluations. The research analyzes 796 online customer reviews from Skytrax, a well-known online airline review website. The information hidden in customer-generated reviews is analyzed with the text mining technique, including topic modeling and sentiment analysis. The research uses the Latent Dirichlet Allocation (LDA) model for topic analysis and the Valence Aware Dictionary for Sentiment Reasoning (VADER) model for sentiment analysis. The sentiment ratio for AirAsia’s online reviews is approximately 59% positive and 41% negative. Only four reviews are neutral. The findings indicate that the online review of AirAsia has a greater proportion of positive sentiments than negative sentiments. In addition, the topic modeling shows hidden topics with the top high-probability keywords concerned with interior and seat, baggage, online service, staff service, flight schedule, and refund. The research demonstrates using sentiment analysis and topic modeling on customer review data as a more thorough alternative to survey-based models for researching airline service. The research contributes to the methodological advancements in text mining analysis and expands the current knowledge of customer review data.

Unleashing the Potential of Internet Hospitals: An In-Depth Examination of Information Platform Functionality and Performance.

Internet hospitals (IHs) have rapidly developed as a promising strategy to address supply-demand imbalances in China's medical industry, with their capabilities directly dependent on information platform functionality. Moreover, a novel theory of "Trinity" smart hospital has provided advanced guidelines of IHs construction. To explore the construction experience, construction models, and development prospects based on operational data from IHs. Based on existing information systems and internet service functionalities, our hospital has built a "Smart Hospital Internet Information Platform (SHIIP)" for IHs operation, actively to expand online services, digitalize traditional healthcare, and explore healthcare services modes throughout the entire process and lifecycle. This article encompasses the platform architecture design, technological applications, patient service content and processes, healthcare professional support features, administrative management tools, and associated operational data. Our platform has presented a remarkable set of data, including 82,279,669 visits, 420,120 online medical consultations, 124,422 electronic prescriptions, 92,285 medication deliveries, 6,965,566 pre-diagnosis triages, 4,995,824 offline outpatient appointments, 2,025 medical education articles with a total of 15,148,310 views, and so on. These data demonstrate the significant role of IH as an indispensable component of our physical hospital services, with a deep integration between online and offline healthcare systems. Attributing to extreme convenience and improved efficiency, our IH has achieved a wide recognition and use from both the public and healthcare workers, and the upward trends in multiple data metrics suggest a promising outlook for its sustained and positive development in the future. Our pioneering exploration holds tremendous significance and serves as a valuable guiding reference for IHs construction and the progressive development of the internet healthcare sector.

PEBASI: A Privacy preserving, Efficient Biometric Authentication Scheme based on Irises

We introduce a novel privacy-preserving biometric authentication scheme based on irises that allows a user to enroll once at a trusted biometric certification authority (BCA) and authenticate to online service providers (SPs) multiple times without involving the BCA during the authentication. Our scheme preserves the user’s biometric privacy from the SPs and transactional privacy from the BCA, while providing security against a malicious user. During the enrollment, the BCA issues a signed token that encrypts the user’s biometrics. We introduce techniques enabling the SP and the user to perform secure computation of biometric matching between such encrypted biometrics and the user’s biometrics captured at the authentication time. We provide a prototype implementation, a performance evaluation, and a security analysis of the protocol.

Artificial intelligence for marketing product strategy in the online education market

The online education market has experienced tremendous growth, creating a competitive landscape where effective marketing solutions are crucial for success. Artificial intelligence (AI) has emerged as a powerful tool, offering innovative ways to enhance product marketing strategy. The purpose of the article was to highlight the integration of artificial intelligence into marketing product strategies in the online education market and to evaluate the chances of success for launching a new training course implemented through AI algorithms. A systematic review of advanced technologies and products in the AI market was carried out, along with a comparative analysis based on data from various authors and reports from organisations, considering the aspects of interpreting qualitative and quantitative market characteristics. Leaders in the global and Ukrainian online education market were analysed, and research was conducted on the marketing product strategy measures of successful players, indicating qualitative and quantitative data using SimilarWeb and Semrush online services. These results allowed for an analysis of the connection between the identified market segments and influencing factors to make practical recommendations for improving elements of marketing based on the identified issues of products and the online education market. To demonstrate the relevance and effectiveness of the proposals, an approach was applied to test if a product with enhanced AI marketing would fit into the market using the example of the Projector Institute company. The assessment obtained from the calculations showed that AI can strengthen the marketing of online education products, as they will fully meet the interests of interested economic counterparts. The results of the study could be used by marketing, AI experts, product experts, business owners in marketing, etc. to enhance marketing solutions

The impact of digitalization on promoting business during crisis: evidence from Armenian SMEs

Purpose This paper aims to analyze the factors that affect the attitudes of Armenian small and medium enterprises (SMEs) regarding digitalization, examining whether they view it as a tool to foster innovation and business growth, while also assessing the extent to which digitalization mitigated the negative impacts of the COVID-19 crisis. Design/methodology/approach The empirical approach is based on data collected from 452 Armenian SMEs, which were further analyzed using SPSS Statistics 23.0 software. Scales for assessing the COVID-19 impact, innovation and digitalization were constructed and validated. To test five hypotheses, binomial logistic regression was conducted to appraise the importance of digitalization for Armenian SMEs, including the ability to mitigate the consequences of the recent COVID-19 pandemic. Findings The results of the analysis showed that the economic sector plays a significant role in forming the expectations of firms on the positive impact of digitalization, while the company size does not affect them. This paper found that the provision of online services before the pandemic did not help Armenian SMEs to be less affected by the crisis. Furthermore, the perception of whether digitalization facilitated innovative processes, products and services did not depend on the degree of being affected by COVID-19. Finally, the findings indicate that the more agile companies which had the ability to convert their business model into an e-business model were less affected by the crisis. Originality/value This paper contributes to the literature by studying the effect of digitalization on SMEs, as well as how SMEs in small developing countries like Armenia mitigated the negative effects of the COVID-19 pandemic. The current work is unique as, to the best of the authors’ knowledge, there are no prior empirical studies focusing on impact of digitalization and innovation induced by exogenous shocks in an under-researched country like Armenia.

Expert recommendations for internet medical care treatment of tuberculosis

Tuberculosis, a chronic infectious disease caused by Mycobacterium tuberculosis, has long posed significant challenges to both medical professionals and patients in its diagnosis and treatment. The need for regular follow-up visits has resulted in a significant economic and logistical burden for patients and a strain on healthcare resources. However, the recent rapid development of Internet technology has significantly enhanced the role of telemedicine in the health care of tuberculosis. This proposal aims to provide a comprehensive overview of the various aspects of telemedicine in the management of tuberculosis. It covers functional positioning, medical qualifications, scope of application, management team, operational model, medical standards, medication evaluation, precautions, risk management. It is intended to serve as a reference for healthcare professionals in the practical application of telemedicine in tuberculosis care.【Expert Recommendation 1】: To provide the further online services for tuberculosis patients who have already had a face-to-face consultation and been diagnosed with tuberculosis. Telemedicine in tuberculosis care includes confirmation of diagnosis, treatment, health counseling, management, educational initiatives, and the initial assessment and management of new symptoms and signs.【Expert Recommendation 2】: The qualifications for telemedicine in tuberculosis care require that the attending physician has a valid medical license and has at least three years of clinical experience in tuberculosis.【Expert Recommendation 3】: The primary target group for online tuberculosis care are patients who are undergoing routine follow-up visits. Certain examinations and test results are mutually recognized within certain regions.【Expert Recommendation 4】: The management team for telemedicine in tuberculosis care is consist of specialist physicians from tuberculosis medical institutions or third-party internet medical organizations, together with information technology staff.【Expert Recommendation 5】: The informatization framework for telemedicine in tuberculosis care includes referrals between higher and lower-level institutions, as well as online and offline referrals. Methods for online follow-up consultations include text-based and video consultations.【Expert Recommendation 6】: Standards for telemedicine in tuberculosis care must be in line with government documents. Regular monitoring and evaluation of the safety and efficacy of anti-tuberculosis therapy is needed, with guidance for patients to seek further treatment at an offline medical institution if necessary.【Expert Recommendation 7】: The attending physician must comply with regulations when documenting patient care and issuing prescriptions, which are valid only after review and approval by a pharmacist.【Expert Recommendation 8】: Healthcare providers are encouraged to use digital platforms, including social media, short video platforms, and mini-programs, to disseminate health information to patients and their families.【Expert Recommendation 9】: If the attending physician discovers adverse events in internet medical treatment, it is necessary to report them immediately to the adverse reaction reporting system of the hospital relying on internet medical treatment.【Expert Recommendation 10】: The attending physician should handle any disputes or complaints about online diagnosis and treatment in accordance with applicable laws, regulations, and guidelines.【Expert Recommendation 11】: Strict confidentiality of patient information must be maintained in online tuberculosis care, and patient consent before data can be used for educational or research purposes.【Expert Recommendation 12】: For primary care facilities that do not have the necessary resources for online diagnosis and treatment, we recommend establishing satellite centers, implementing simplified remote care systems, and utilizing mobile devices in collaboration with nearby hospitals that can provide remote care. This approach aims to increase the capacity of primary care facilities to provide telemedicine service.

Information literacy and intention to adopt e-pharmacy: a study based on trust and the theory of reasoned action

BackgroundE-pharmacy has gained popularity as an increasingly utilized platform for accessing healthcare services online. However, its adoption exhibits regional variations and necessitates improvement in certain aspects. Guided by the Theory of Reasoned Action (TRA) and Trust theory, this research explores the pivotal role of information literacy in influencing attitudes, perceived control, word of mouth, and trust. The overarching aim is to understand how these factors collectively impact the adoption of E-pharmacy services.MethodsThe study employed Structural Equation Modeling to assess data collected from 473 participants in Nigeria. This methodology allowed for a comprehensive evaluation of the intricate relationships between information literacy, attitudes, perceived control, word of mouth, trust, and E-pharmacy adoption. By utilizing statistical tests within this framework, the research sought to provide a robust analysis of the data and derive meaningful insights.ResultsThe findings of the research underscore the significance of information literacy in shaping individuals' attitudes towards E-pharmacy. Higher information literacy levels were associated with more positive attitudes, an enhanced sense of perceived control, and increased positive word-of-mouth regarding the use of E-pharmacy services. Additionally, the study revealed that trust plays a crucial intermediary role between word-of-mouth communication and the actual adoption of E-pharmacy.ConclusionsIn summary, this research offers a novel and comprehensive explanation of the relationship between information literacy and the adoption of E-pharmacy services. The study's outcomes contribute valuable insights to the ongoing discourse on E-pharmacy adoption, emphasizing its potential to enhance healthcare accessibility and efficiency within the evolving landscape of digital healthcare. The implications of the findings extend to policymakers, healthcare providers, and other stakeholders interested in optimizing the adoption and integration of E-pharmacy services.

Exploring How Patients Are Supported to Use Online Services in Primary Care in England Through "Digital Facilitation": Survey Study.

Health service policy in many jurisdictions is driving greater investment into digital primary care services. While some patients and practices may benefit, there are concerns that not all are able or wish to access primary care services online. "Digital facilitation" is the "range of processes, procedures, and personnel seeking to support patients in their uptake and use of online services" and may address such concerns. As part of a multimethod research program, we undertook surveys of practice staff and patients to gain insight into the support being offered by practices and explore patients' experiences of this support. General practices from 4 regions of England were sent a questionnaire exploring the modes of digital facilitation offered, the personnel involved in its delivery, and views on the motivations and drivers for providing support. Moreover, 12,822 patients registered with 62 general practices (predominantly those providing practice survey responses) were sent a questionnaire exploring their experiences of any support offered by their practice to use online services. Almost one-third of practices (156/500, 31.2%) responded to the practice survey, with most reporting using passive modes of digital facilitation (eg, display, leaflets, and SMS text messages) and few using active modes (eg, offering tablets or computers or using practice champions). However, 90.9% (130/143) reported providing ad hoc support. Practices agreed that it was the responsibility of both the practice (105/144, 72.9%) and the wider National Health Service (118/143, 82.5%) to support patients in using online services and that providing such support benefited the practice (126/144, 87.5%) and their patients (132/144, 91.7%). Nearly a quarter of the patients (3051/12,822, 23.8%) responded to the patient survey, with few (522/3051, 17.11% or less) reporting awareness of any modes of digital facilitation apart from text messages and emails (1205/3051, 39.5%) and only 13.36% (392/2935) reporting receiving support to use online services. Adjusted logistic regression analyses showed that older patients had a lower likelihood of 4 outcomes: being aware of, or of using, digital facilitation efforts, or being told about or being helped to use online services (all P<.05), particularly with regard to being helped to use online services (adjusted odds ratio for patients aged 85 years versus those aged 55-64 years: 0.08, 95% CI 0.02-0.36). However, ethnic minority participants or those for whom their first language was not English had positive associations with these outcomes. General practices recognize that patients would benefit from support to access online services. However, the support provided is often passive or ad hoc, and patients were seldom aware of digital facilitation efforts that their practice provided. There is potential to increase engagement with online primary care services by providing more support for all patients, particularly to provide targeted support for older patients.

Alternative cancer clinics’ use of Google listings and reviews to mislead potential patients

BackgroundAlternative cancer clinics, who provide treatment associated with earlier time to death, actively seek to create favorable views of their services online. An unexplored means where alternative cancer clinics can shape their appeal is their Google search results.MethodsWe retrieved the Google listing and Google reviews of 47 prominent alternative cancer clinics on August 22, 2022. We then conducted a content analysis to assess the information cancer patients are faced with online.ResultsGoogle listings of alternative treatment providers rarely declared the clinic was an alternative clinic versus a conventional primary cancer treatment provider (12.8% declared; 83.0% undeclared). The clinics were highly rated (median, 4.5 stars of 5). Reasons for positive reviews included treatment quality (n = 519), care (n = 420), and outcomes (n = 316). 288 reviews presented the clinics to cure or improve cancer. Negative reviews presented alternative clinics to financially exploit patients with ineffective treatment (n = 98), worsen patients’ condition (n = 72), provide poor care (n = 41), and misrepresent outcomes (n = 23).ConclusionsThe favorable Google listing and reviews of alternative clinics contribute to harmful online ecosystems. Reviews provide compelling narratives but are an ineffective indicator of treatment outcomes. Google lacks safeguards for truthful reviews and should not be used for medical decision-making.

Large-Scale Satisfaction Rating-Driven Selection of New Energy Vehicles: A Basic Uncertain Linguistic Information Bonferroni Mean-Based MCGDM Approach Considering Criteria Interaction

The continuous revolution of new energy technologies and the introduction of subsidy policies have promoted green consumers’ willingness to purchase new energy vehicles and automotive online service platforms have disclosed vehicle reputation and consumer satisfaction ratings information. However, due to issues such as uncertain data quality, large data volumes, and the emergence of positive reviews, the cost for potential car buyers to acquire useful decision-making knowledge has increased. Therefore, it is necessary to develop a scientific decision-making method that leverages the advantages of large-scale consumer satisfaction ratings to support potential car buyers in efficiently acquiring credible decision-making knowledge. In this context, the Bonferroni mean (BM) is a prominent operator for aggregating associated attribute information, while basic uncertain linguistic information (BULI) represents both information and its credibility in an integrated manner. This study proposes an embedded-criteria association learning BM operator tailored to large-scale consumer satisfaction ratings-driven scenarios and extends it to the BULI environment to address online ratings aggregation problems. Firstly, to overcome the limitations of BM with weighted interaction (WIBM) when dealing with independent criteria, we introduce an adjusted WIBM operator and extend it to the BULI environment as the BULIWIBM operator. We discuss fundamental properties such as idempotence, monotonicity, boundedness, and degeneracy. Secondly, addressing the constraints on interaction coefficients in BM due to subjective settings, we leverage expert knowledge to explore potential temporal characteristics hidden within large-scale consumer satisfaction ratings and develop a method for learning criteria and interaction coefficients. Finally, we propose a conversion method between user credibility-based ratings and BULI. By combining this method with the proposed adjusted BM operator, we construct a multi-criteria group decision-making (MCGDM) approach for product ranking driven by large-scale consumer satisfaction ratings. The effectiveness and scientific rigor of our proposed methods are demonstrated through solving a new energy vehicle selection problem on an online service platform and conducting comparative analysis. The case analysis and comparative analysis results demonstrate that the interaction coefficients, derived from expert knowledge and 42,520 user ratings, respectively, fell within the ranges of [0.2391, 0.7857] and [0.6546, 1.0]. The comprehensive interaction coefficient lay within the range of [0.4674, 0.7965], effectively mitigating any potential biases caused by subjective or objective factors. In comparison to online service platforms, our approach excels in distinguishing between alternative vehicles and significantly impacts their ranking based on credibility considerations.

Public Satisfaction with Online Services: (Case Study on the JEPIN Application)

Purpose: This study aims to analyze the use of the JEPIN application for users, namely the community in Pontianak City. JEPIN stands for Jendela Pontianak Integration This application was launched by the Pontianak City Communication and Information Office. Measurement uses variables consisting of infrastructure, ICT, human resources, budgeting, and digital government implementation. Methods: The method used is a quantitative type, primary data in the form of a survey of 100 respondents who come from JEPIN application users in Pontianak City. Using the Likert Scale (1: strongly disagree, 2: disagree, 3: neutral, 4: agree, and 5: strongly agree). The analysis technique for this study uses SmartPLS 4. Result: The results of the study show that the infrastructure variables have a P-Value of (0.000), an ICT P-Value of (0.000), and a P-Value Budgeting of (0.002), respectively, which shows a positive and significant influence on the implementation of digital government in the implementation of the JEPIN application. On the other hand, the human resources variable has a P-Value of (0.998), which shows a positive and significant influence on the implementation of digital government in the implementation of the JEPIN application in Pontianak City. Novelty: This study is unique because it looks at users who use the JEPIN application with a measurement indicator, namely the online services index (OSI). Most previous research on this theory has focused only on measuring how satisfied people are with online services, but this study offers a new perspective on the use of OSI in the context of application-based online services.

‘Do not be Deteriorated by service failures, Learn from them and start managing it’: Conditions and mechanisms for managing online service failures

Online consumers rely on two hospitality channels, direct websites and online travel agents (OTAs), to search for and book hospitality services. Although these online service channels improve service delivery efficiency, service failures have become common and unavoidable. Although online service failures and recovery efforts have received significant research attention, studies have ignored whether customer evaluations following a service failure differ based on the type of failure (informational, functional, or system) occurring in different online service booking channels (direct or OTA). Additionally, despite the significance of customer participation in service recovery, no research has examined the suitability of different recovery types based on varying levels of customer participation, such as firm, joint, and customer recovery. Thus, utilising three between-subjects experiments, this study demonstrated that information failures are more detrimental in a direct channel, whereas functional failures are more harmful to OTAs. However, system failures affect both platforms equally. The results also revealed that firm recovery is most appropriate when an information failure occurs in a direct channel. Joint recovery is suitable for functional failures in OTAs, while customer recovery is sufficient to rectify system failures. Finally, customer expectations (outcome, process, and cost) drive these positive outcomes. This research offers unique contributions to the literature and managerial practice on online service failure and recovery.