Nonhomogeneous Continuous-Time Markov Chain (NH-CTMC) is a stochastic process that can be used to model problems where the future state depends only on the current state and is independent of the past. The transition intensity in NH-CTMC is not constant but is a function of time. In this paper, NH-CTMC is employed to model information dissemination on Twitter, where transitions occur only from followee groups to follower groups. Information is considered spread on Twitter when followers retweet posts from their followees. The tweet-retweet process on Twitter satisfies the Markov property, as a retweet from a follower depends only on the tweet posted just before by the corresponding followee. The probability of a tweet spreading is determined by the transition intensity, assumed to be a Sigmoid function whose parameters are estimated using Maximum Likelihood Estimation (MLE). This method is applied to Twitter data from Indonesia related to discussions on Covid-19 vaccination. The results indicate that information about Covid-19 vaccination on Twitter spreads rapidly from followees to followers in the first 20 hours, and then slows down after 40 hours. The NH-CTMC model outperforms the Homogeneous Continuous-Time Markov Chain (H-CTMC) approach, where the transition intensity (tweet spreading intensity) is assumed to be constant.

Cordyceps are a form of herb that is nurtured and propagated utilizing organic farming techniques. This study investigated consumers’ intention towards adopting the organic herb cordyceps, also referred to as “Thungchao” in Thai language. The research was driven by increased health awareness among people, and skewness towards use of organic as compared to conventional medication. In Thailand, the herb has been consumed traditionally for years, because of its medical benefits. The Theory of Planned Behavior (TPB) was applied to investigate the outcomes of users’ perceptions (perceived experience with organic product, perceived health benefit, information awareness) and TPB aspects (subjective norm, perceived behavioral control, attitude towards organic herb) to examine intentions of consumers’ towards adopting codyceps. The research collected primary data from 452 Thai respondents. Collected data were evaluated utilizing Structural Equation Modeling analysis. Results revealed that for the perceived customers’ experience, intention to use organic herb cordyceps was positively and significantly influenced by perceived experience with organic hers and information awareness. All the TPB variables – subjective norm, perceived behavior control, and attitude towards organic herbs – significantly and positively influence consumers’ intention towards organic herb cordyceps. The research recommended that organic herb cordyceps “Thungchao” has many medical benefits, and its consumption should be encouraged. Information awareness and sharing of the knowledge of the herb’s medical requirement and benefits, resources and dosage are necessary to encourage or rather influence consumers intention.

Online shopping has developed rapidly in Indonesia since the Covid-19 outbreak, making potential customers frequently browse e-commerce. In e-commerce there is a social commerce construct which is a construction originating from social commerce such as online reviews. Depth from online reviews on a product cannot necessarily be trusted and prospective customers also cannot use other people's experiences as an assessment of product quality. Customer review also considers perceived value from a utilitarian and hedonic perspective. Therefore, this study analyzes the effect of perceived value on browsing behavior in C2C e-commerce with the antecedent depth of review in Indonesia. This study uses SOR (stimulus-organism-response) theory. The population of this study are individuals who live in Indonesia and have done shopping online in one commerce which has facilities online review such as Tokopedia, Blibli, Amazon, Alibaba, and JD.ID. Sampling technique nonprobability sampling by using techniques convenience sampling total 137 samples. The data collection method uses the survey method, while the data analysis method used is PLS-SEM. The results of the study show that depth review affects perceived utilitarian and hedonic values, and perceived utilitarian and hedonic values also affect browsing. Thus, all hypotheses are accepted, which means that there is an influence of perceived value on browsing behavior in C2C e-commerce with an antecedent of review depth. This research can be used as a reference for further studies by digging deeper into the effect of the depth of review on other variables that can have an impact on the viability of a seller's business in e-commerce. This research can be used as a reference for sellers to evaluate and create strategies to encourage customers to give positive reviews so that they can influence other readers when browsing e-commerce where it is hoped that purchases will occur. This research pioneered the study of perceived value of browsing behavior in C2C e-commerce with antecedents of depth of review in Indonesia.

The term “metaverse” refers to a virtual reality setting where users may engage in sustained and immersive interactions with other users and digital information. The metaverse offers new potential for entertainment, education, commerce, sociability, and creativity; therefore, it is anticipated to play a significant role in the future of the digital economy. However, the metaverse presents additional difficulties in resolving conflicts that can develop between its users, producers, and providers. Intellectual property rights, privacy, contract enforcement, fraud, harassment, and cybercrime are some of the concerns that may be raised in these conflicts. The existing legal system for settling these conflicts is disjointed and insufficient since it does not consider the metaverse’s unique qualities and complexity. This study investigates the present legal framework to provide fair and effective conflict resolution in the metaverse. It then establishes tenable fundamentals within the context of scientific and legal foundations. and propose a theoretical model named Hybrid Legal Framework for Metaverse Dispute Resolution (HLFMDR).

The present study attempted to determine the elements affecting users' opinions about using electronic auctions in Jordan. The study's target audience was Jordanian university students. We randomly selected 600 students from three public universities in Jordan after 600 users from each of the three universities responded to the surveys. The primary data for this study were gathered using a specially created questionnaire that was based on earlier research. SEM software (smart PLS 4.0.8.3) was employed in the evaluation of data. This study looked into the factors that led Jordanians to use electronic auctions and found four indirect significant relationships and ten direct significant relationships. First, user attitudes and independent variables (usefulness, awareness, ease of use, and techno trust) are directly significant antecedents of utilizing e-auctions in Jordan. The use of e-auctions is related to the independent variable in five direct and significant ways: usefulness, awareness, ease of use, digital divide, and techno trust. Thirdly, there are direct and statistically significant correlations between user attitudes and the independent variables (usefulness, awareness, ease of use, and techno trust). Fourthly, there appears to be a clear and significant link between user attitudes and the intention to use e-auctions. Fifth, there are four mediated meaningful indirect correlations between the intention to use e-auctions and the independent variable. The findings of the current study are based on a number of factors that affect the demand for e-commerce in Jordan. They also include some recommendations for academics and decision-makers in e-marketing affairs. The current study also contributes in identifying challenges and suggestions that would overcome obstacles related to shopping operations through e-auctions. The factors examined in this study have been the subject of prior research. The data gathered in this study are valuable to Jordanian decision-makers and web developers, as the data can be used to create efficient policies and strategies to launch work on electronic auction platforms.

The present research endeavors to comprehend the determinants that impact the inclination to utilize financial technology within the context of Islamic banking clientele. The study undertakes an examination of various determinants that may exert an influence on the consumer's intention. These determinants encompass financial risk, legal risk, security risk, operational risk, consumer innovativeness, perceived ease of use, and perceived usefulness. The technology acceptance model is employed as the theoretical framework for the research. The requisite data for hypothesis testing is collected through the administration of an online survey to consumers of Islamic banks who possess a high degree of adaptability and proficiency in utilizing financial technology. The study employs the methodology of structural equation modelling with partial least squares to assess the proposed relationships among a sample of 399 participants. The results indicate that the acceptance of Islamic Financial technology services is contingent upon the perceived ease of use, perceived usefulness, and consumer innovativeness. In contrast, it is observed that various other factors, namely financial risk, legal risk, security risk, and operational risk, do not hold significant sway in shaping the level of acceptance of Islamic Financial technology among users of Islamic banking services. The concept of Technology Acceptance Model (TAM) is expanded within the realm of Islamic financial technology, and it is utilized to examine the impact of a novel factor, specifically consumer innovativeness. The untested nature of consumer innovativeness makes this paper a valuable resource for policymakers, academics, and researchers in the future.

The use of social media for young people has encouraged communication and socialization with other users massively and excessively. Besides, activities by the community of social media users have allocated much time. This condition exposed productivity as a challenge in the place and family communication. This study explores the effect of excessive use of social networking sites on customer loyalty with the mediating role of perceived usefulness, behavioral intention, and essential information. This research focused on adult-young people who use social networking media daily. Data collection used questionnaires designed with a five-point Likert scale and distributed online through Google Forms link. The respondents were given rewards through internet charge vouchers to encourage them, respondents, to complete the questionnaires. The questionnaire was distributed successfully to 932 prospective respondents during 2019-2023 through social media (WhatsApp, Line) and e-mail. Four hundred seventy-two (472) respondents were considered to meet the sample criteria as an adult-young group—data processing using Partial Least Square (PLS) with SmartPLS Software version 4.0. The results found that excessive use of social networking sites positively affects perceived usefulness, essential information, and behavioral intention. Perceived usefulness positively influences essential information and behavioral intention. The essential information increases behavioral intention and customer loyalty. The results also found that behavioral intention positively impacts customer loyalty. The practical contribution of research to young adults can determine the top priority in using social networking sites so as not to interfere with work activities and good relationships between family members. The film industry can promote products through social media effectively and efficiently. The theoretical contribution of research by enriching marketing behavior theory and technology acceptance model to improve user welfare and comfort.

IoT devices with weak security designs are a serious threat to organizations. They are the building blocks of Botnets, the platforms that launch organized attacks that are capable of shutting down an entire infrastructure. Researchers have been developing IDS solutions that can counter such threats, often by employing innovation from other disciplines like artificial intelligence and machine learning. One of the issues that may be encountered when machine learning is used is dataset purity. Since they are not captured from perfect environments, datasets may contain data that could affect the machine learning process, negatively. Algorithms already exist for such problems. Repeated Edited Nearest Neighbor (RENN), Encoding Length (Explore), and Decremental Reduction Optimization Procedure 5 (DROP5) algorithm can filter noises out of datasets. They also provide other benefits such as instance reduction which could help reduce larger Botnet datasets, without sacrificing their quality. Three datasets were chosen in this study to construct an IDS: IoTID20, N-BaIoT and MedBIoT. The filtering algorithms, RENN, Explore, and DROP5 were used on them to filter noise and reduce instances. Noise was also injected and filtered again to assess the resilience of these filters. Then feature optimizations were used to shrink the dataset features. Finally, machine learning was applied on the processed dataset and the resulting IDS was evaluated with the standard supervised learning metrics: Accuracy, Precision, Recall, Specificity, F-Score and G-Mean. Results showed that RENN and DROP5 filtering delivered excellent results. DROP5, in particular, managed to reduce the dataset substantially without sacrificing accuracy. However, when noise got injected, the DROP5 accuracy went down and could not keep up. Of the three dataset, N-BaIoT delivers the best accuracy overall across the learning techniques.

During Covid-19, organizations, particularly hospitals, encountered difficulties in providing services. Telemedicine has shown to be an alternative in service provision during these times. Based on this, acceptance of telemedicine in Jordanian public hospitals has become a very important issue to increase the attention of the health care organization toward it. A conceptual model was constructed based on previous literature. The model includes government policy, the capacity of external suppliers, and the capacity of the project team, top management support, as independent variables where their influence on the acceptance of telemedicine in Jordanian public hospitals as a dependent variable is examined. Respondents were chosen using a Purposive sampling technique. Questionnaires were delivered to 320 respondents using Google Forms. SEM was used for statistical analysis. The findings revealed that all the proposed factors including government policy, external supplier capacity, project team capacity, and top management support have a significant influence toward accepting telemedicine. The results of this study may aid Jordanian public hospitals in making the best use of the proposed factors to increase the acceptance of telemedicine in Jordanian public hospitals.

Technological advancements affect everyday life; they benefited our daily routines, habits, and activities. Underwater diving is one of the most interesting and attractive activities for tourists worldwide but could be risky and challenging. When paths are not clear, diving might take additional time and effort leading to some health problems. Thus, providing divers with proper direction information to surf underwater can be useful and helpful. Also, monitoring diverse health statuses and alerting them in case of any undesirable condition can increase their safety. Smart devices such as mobiles, watches, sensor devices, cellular networks along with the Internet of Things (IoT) can all provide location-based services. Such services can help in providing the best path for the divers and monitor their health status during diving. This paper proposes a new underwater routing approach, called Underwater Routing for Smart Diving “URSD”, which provides divers with routing information to visit underwater cultural or natural resources and monitors their health status during the diving period. The URSD approach was simulated and compared with the shortest path. Results showed that the URSD helped divers to route within paths that have a larger number of nodes, furthermore, it could enhance and improve divers experience and help them mitigate underwater risks.