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This research attempts to reveal ways of addressing challenges in open universities related to empowering lifelong learning; establishing policies and strategies in dropouts, student portfolio and support services for students with special needs; and implementing online instructional design and strategies. Two institutions were investigated, namely National Open University (NOU) Taiwan and Universitas Terbuka (UT) Indonesia, both founded in the 1980s to serve lifelong learners with diverse backgrounds and needs. This study was aimed at understanding good practices and challenges for improvement for the two open universities in those areas being investigated.

This research was qualitative using document analysis along with focus group discussions and interviews with administrators, academic staff, students and alumni to collect data for analysis.

Lifelong learning is the necessity of individual in societies for continuing professional development through enabling access to quality university education. Open universities have been tasked to cater for lifelong learners using non-traditional approaches, new technology and adapting to online learning and teaching in digital age. This research was exploratory, and the findings were expected to improve understanding of lifelong learning in open universities, particularly in NOU and UT.

Findings of this research are relevant to open universities to enhance its missions and define its possible new roles to serve lifelong learners.

This research reveals the roles of open universities in lifelong learning and enhances understanding of open universities that have a wide range of responsibilities in offering programs and courses to accommodate lifelong learners.

This study examined the impact of school leadership on teacher professional collaboration, with collective teacher innovativeness and teacher self-efficacy (TSE) playing the mediating role. Two most commonly used leadership styles, instructional leadership (IL) and distributed leadership (DL), were analyzed using a multilevel design, i.e. teachers are nested within schools.

The proposed model was validated using data of Taiwan TALIS 2018 collected from both teachers and principals and analyzed using hierarchical linear modeling.

Results showed that IL and DL influence teacher professional collaboration through different paths. IL had a significant direct impact on teacher professional collaboration alone, while DL had a significant direct impact on both teachers' collective innovativeness and their professional collaboration. While TSE had a direct effect on collective teacher innovativeness, TSE and collective teacher innovativeness had a direct effect on teacher professional collaboration.

This study highlights the significant impact of principal leadership as both principals and teachers work in the same environment and culture co-shaped through the interaction and collaboration. Research evidence regarding the effects of IL and DL on teacher professional collaboration is limited; this is even less evidential when the indirect effects of variables mediating between school leadership and teacher outcomes, including teacher collective innovativeness and TSE, are added to the total effects. The present findings provide useful references for principals and teachers when promoting professional collaboration to achieve desired outcomes in school and student improvement.

The purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.

The paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.

The study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.

This paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.

The inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.

The purpose of this paper is to address the opposing views of the relationship between directors’ and officers’ liability insurance (D&O insurance) and stock price crash risk in a major Asian emerging stock market.

This paper finds an endogenous relationship between D&O insurance and stock price crash risk. Hence, the two-stage least squares regression analysis is used to address the endogeneity issue when the relationship is examined. Moreover, this paper further controls the quality of other corporate governance mechanisms to investigate whether D&O insurance still has an effect on stock price crash risk.

The effect of D&O insurance coverage is significantly negatively related to firm-specific stock price crash risk in Taiwan. More importantly, even when the quality of other corporate governance mechanisms is controlled, the negative relationship between D&O insurance coverage and firm-specific stock price crash risk remains significant. The evidence supports that D&O insurance serves as an effective external monitoring mechanism, strengthens corporate governance, and thus reduces stock price crash risk.

Emerging Asian markets suffer a dearth of research on the relationship of D&O insurance coverage and the firm-specific stock price crash risk. Investigating the relationship in Taiwan, the present study fills the research void. The findings show that D&O insurance plays an important role in reducing stock price crash risk of Taiwanese firms even when other corporate governance mechanisms are in place.

This study aims to examine the effectiveness of an integrated intervention program for alcoholism (IIPA) for improving verbal encoding and memory, visuospatial construction, visual memory and quality of life (QoL) in persons with alcohol dependence.

The sample comprised treatment-seeking alcohol-dependent persons (n = 50), allotted into two groups: (1) the treatment as usual (TAU) group (n = 25) and (2) the treatment group (n = 25)]. The groups were matched on age (±1 year) and education (±1 year). The TAU group received standard pharmacological treatment, psychotherapeutic sessions on relapse prevention and yoga for 18 days, while the treatment group received IIPA sessions in addition to the usual treatment. Auditory verbal learning test, complex figure test and QoL scale were administered at pre- and post-treatment along with screening measures.

The two groups were comparable on demographic variables, clinical characteristics and outcome measures at baseline. Pre- to post-treatment changes (gain scores) comparison between the treatment and TAU groups revealed a significant difference in verbal encoding, verbal and visual memory, verbal recognition, visuospatial construction and QoL.

This study suggests that IIPA is effective for improving learning and memory in both modality (verbal and visual) and QoL in persons with alcoholism. The IIPA may help in better treatment recovery.

The IIPA may help in treatment for alcoholism and may enhance treatment efficacy.

IIPA is effective for improving learning and memory in both modalities and QoL in persons with alcohol dependence. The IIPA may help in better treatment recovery.

This article explores the emergence of organizational digital transformation in the rapidly advancing technological era. It discusses the origins, driving forces, strategies, challenges and broader implications.

The article employs a scoping review methodology that synthesizes knowledge from the existing literature, research, case studies and other relevant sources.

The findings underscore the pivotal role that organizational digital transformation plays in an era of relentless technological advancement. Leadership, organizational culture and technological enablers are identified as crucial drivers of innovation and competitiveness within organizations. The article also emphasizes ethics as a crucial element of digital transformation, focusing in particular on concerns about data privacy and the morality of artificial intelligence. Additionally, the author talks about anticipated future trends that are anticipated to influence the future of digital transformation, such as the growing influence of artificial intelligence, the trend toward hyper-personalization and the emergence of quantum computing.

The assessment has failed to provide recommendations for the actual implementation because it has mainly concentrated on conceptual and strategic aspects. Furthermore, it does not clearly define the criteria for choosing real-world examples, which limits the representation of the different industries, size ranges of organizations and outcomes associated with digital transformation.

The article stresses the significance of paying attention to the forces driving digital transformation while navigating ethical and societal concerns. In addition to highlighting the importance of anticipating future trends for strategic planning in the rapidly changing digital landscape, it emphasizes the advantages as incentives for organizations to invest in digital initiatives.

The investigation demonstrates how technology contributes to progress while posing complex ethical and change management issues. In light of increased connectivity, data analytics and artificial intelligence, it highlights the crucial need for societal adaptability and highlights the crucial role that cooperative human–machine coexistence plays in responsible development and transformative societal evolution.

The article stands out because it examines organizational digital transformation in-depth while considering its historical roots, ethical implications and future prospects. It is a priceless contribution to the field because real-world case studies and a scoping review provide a distinctive viewpoint and a comprehensive view of the effects of digital transformation on organizations and society.

Voice assistant (VA) technology is one of the fastest-growing artificial intelligence applications at present. However, the burgeoning scholarship argues that there are ethical challenges relating to this new technology, not the least related to privacy, which affects the technology’s acceptance. Given that the media impacts public opinion and acceptance of VA and that there are no studies on media coverage of VA, the study focuses on media coverage. In addition, this study aims to focus on media coverage in Indonesia, a country that has been underrepresented in earlier research.

The authors used critical discourse analysis of media texts, focusing on three levels (text, discourse practice and social practice) to study how VA technology was discussed in the Indonesian context and what power relations frame the representation. In total, 501 articles were collected from seven national media in Indonesia from 2010 to 2020 and the authors particularly focus on the 45 articles that concern ethics.

The ethical topics covered are gender issues, false marketing, ethical wrongdoing, ethically positive effects, misuse, privacy and security. More importantly, when they are discussed, they are presented as constituting no real critical problem. Regarding discursive practices, the media coverage is highly influenced by foreign media and most of the articles are directed to well-educated Indonesians. Finally, regarding social practices, the authors hold that the government ideology of technological advancement is related to this positive portrayal of VAs.

First, to provide the first media discourse study about ethical issues of VAs. Second, to provide insights from a non-Western context, namely, Indonesia, which is underrepresented in the research on ethics of VAs.

Research about tourism impacts is abundant. However, existing studies often investigate tourism impacts from residents’ and tourists’ perspectives. The study targeting students is absent. The students’ perception and evaluation of tourism impact must be investigated independently to have more insights into improving the current education curriculum, which covertly addresses the impacts. Therefore, this study aims to examine university students’ perception of tourism impacts as young tourists to provide implications for better teaching of such content in the future.

Vietnam was chosen as the context, and a mixed method was employed. First, free elicitation with 118 university students was carried out to identify the students’ perceived impacts (109 items, four categories). Second, structured surveys using the previously generated content with 243 and 224 university students were implemented to identify the latent structures of the impacts (3-4 factors per impact category).

Tourism impacts can be dually perceived. In other words, they can come in positive or negative forms or are directed toward the destinations or the residents. However, being positive or negative, or affecting the place or the people, tourism impacts have some general and universal elements concerning the economic, sociocultural and environmental ones. In addition, they have some specific and contextual aspects, such as cross-border marriages, child labor and economic autonomy loss.

Tourism impacts seen from the perspective of university students are relatable and valuable for tourism education. Educators in Vietnam should consider revising the current curriculum to address all the tourism impacts overtly.

The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.