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Post-COVID-19, public K–12 schools are still facing the consequences of the years of interrupted learning. Schools serving minoritized students are particularly at risk for facing challenges with academics, behavior and student social emotional health. The university counseling programs are in positions to build capacity in urban schools while also supporting counselors-in-training through service-learning opportunities.

The following conceptual manuscript demonstrates how counselor education counseling programs and public schools can harness the capacity-building benefits of university–school partnerships. While prevalent in fields like special education, counselor educators have yet to heed the hall to participate in mutually beneficial partnership programs.

Using the multi-tiered systems of support (MTSS) and the components of the university–school partnerships, counselor educators and school stakeholders can work together to support student mental health, school staff well-being and counselor-in-training competence.

The benefits and opportunities within the university–school partnerships are well documented. However, few researchers have described a model to support partnerships between the university counseling programs and urban elementary schools. We provide a best practice model using the principles of university–school partnerships and a school’s existing MTSS framework.

Preservice teacher (PST) professional development programs are crucial for cultivating high-quality STEAM teachers of the future, significantly impacting the quality of regional STEAM education. The Guangdong-Hong Kong-Macao Greater Bay Area, as a region of cross-border cooperation, integrates the resources and advantages of Guangdong, Hong Kong, and Macao, possessing rich cultural heritage and innovative capabilities. Transdisciplinary Education for Cultural Inheritance (C-STEAM) is an effective approach to promoting educational collaboration within the Greater Bay Area, facilitating the integration of both technological and humanities education. This study aims to develop a Technology-Enabled University-School-Enterprise (T-USE) collaborative education model and implement it in the Greater Bay Area, to explore its role as a support mechanism in professional development and its impact on C-STEAM PSTs' professional capital.

Adopting a qualitative methodology, the study interviewed PSTs who participated in a C-STEAM teacher education course under the T-USE model. Thematic coding is used to analyze their knowledge acquisition, interaction benefits with community members, and autonomous thinking and decision-making in theoretical learning and teaching practice.

The findings show that the T-USE model significantly enhanced the PSTs' human capital, including teaching beliefs, knowledge, and skills. In terms of social capital, PSTs benefited from collaboration with PST groups, university teaching teams, in-service teachers, and enterprises, though challenges such as varying levels of expertise among in-service teachers and occasional technical instability emerged. For decisional capital, the T-USE model provided opportunities for autonomous thinking and promoted teaching judgment skills through real teaching challenges and scenarios. Reflective practice activities also supported PSTs' professional growth.

This study reveals the effectiveness and internal mechanism of the T-USE model in C-STEAM PST training, offering significant theoretical and practical references for future PST education.

The purpose of this article is to clarify the social burden of Japan’s three major diseases including Long-term Care (LTC) burden.

A modification of the Cost of Illness (COI)—the Comprehensive-COI (C-COI) was utilized to estimate three major diseases: cancer, heart disease, and cerebrovascular diseases (CVD). The C-COI consists of five parts: medical direct cost, morbidity cost, mortality cost, formal LTC cost and informal LTC cost. The latter was calculated by two approaches: opportunity cost approach (OC) and replacement approach (RA), which assumed that informal caregivers were substituted by paid caregivers.

The C-COI of cancer, heart disease and CVD in 2017 amounted to 10.5 trillion JPY, 5.2 trillion JPY, and 6.7 trillion JPY, respectively (110 JPY= 1 US$). The mortality cost was preponderant for cancer (61 percent) and heart disease (47.9 percent); while the informal LTC cost was preponderant for CVD (27.5 percent). The informal LTC cost of the CVD in OC amounted to 1.8 trillion JPY; while the RA amounted to 3.0 trillion JPY.

The LTC burden accounted for a significant proportion of the social burden of chronic diseases. The informal care was maintained by unsustainable structures such as the elderly providing care for the elderly. This result can affect health policy decisions.

The C-COI is more appropriate for estimating the social burden of chronic diseases including the LTC burden and can be calculated using governmental statistics.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

The purpose of this paper is to examine the health sector reform toward 2040 of Japan as a super-aged society.

This paper discusses the current healthcare policies adopted in Japan and projects the challenges in future as a super-aged society.

Through Japanese experiences, it is considered that Community-based Integrated Care System is useful, which takes into account the perspective of health care users. Being a super-aged society, it is essential for Japan to have more consensus by further removing obstacles, and paying attention to the change of paradigm and the purpose of care.

Based on the case of Japan, this paper serves as a reference for other East Asian countries, which would sooner or later encounter the similar situation of becoming super-aged societies in the 21^st century.

Increasing incidents of privacy invasion on social networking sites (SNS) are intensifying the concerns among stakeholders about the misuse of personal data. However, there seems to be limited research on exploring the impact of specific privacy concerns on users’ intention to engage in various privacy protection behaviors. This study aims to examine the role of social privacy concerns, institutional privacy concerns and privacy self-efficacy as antecedents of privacy protection–related control activities intention among young adults active on SNS.

Data collected from 284 young adults active on SNS was analyzed through partial least squares structural equation modeling using Smart PLS.

The results indicate that institutional privacy concerns, social privacy concerns and privacy self-efficacy positively influence the control activities intention of SNS users. The extent of privacy self-efficacy and privacy protection-related control activities intention differs among users based on gender.

This study is limited to a population of young adults in the age group of 18–25 years.

The findings of this study form the basis for specific recommendations addressing the different types of privacy concerns experienced by social media users, promoting responsible privacy control behaviors on online platforms and discouraging the possible misuse of information by third parties.

This study validates a theoretical framework that can contribute to future investigations concerning the use of SNS. The study findings form the basis for a set of practical recommendations for policymakers, SNS platforms and users.

This article analyzes the challenges of infectious disease control under a super-aged society through Japan’s experience with COVID-19.

This article provides an overview of Japan’s COVID-19 measures and their characteristics, discusses their successes and failures, and identifies future challenges.

Japan’s basic strategy for COVID-19 consists of three parts: the border defense (Stage 1), slowing down the spread (Stage 2), and damage control (Stage 3). One key policy feature in Stage 2 and Stage 3 is based on “voluntary restriction”. It had a certain effect, but it was prolonged with each recurring “wave of infection”, resulting in economic exhaustion and people’s dissatisfaction. Thus, the effect of the voluntary restriction has weakened, while the percentage of people who have been vaccinated is improving, making it difficult to predict the damage of the next “wave”. Under the hyper-aged society, it was necessary to identify and protect particularly vulnerable areas, i.e., psychiatry hospitals, chronic care hospitals, and long term care (LTC) facilities. On the other hand, secondary impacts extend to young people. The most serious one is the decrease in births which further accelerates the aging of society.

This study is original as it investigated why Japan’s unique countermeasures against COVID-19 without mandatory lockdown worked well for a considerable period. It also revealed that secondary impacts of the COVID-19 epidemic are broader and more significant than the direct loss of life, and that the social system, especially super-aged society with many vulnerable areas should be reformed in consideration of the threat of infectious diseases. Lessons from the Japanese case may contribute to other countries.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

The purpose of this study is to examine scholarly impact which is critical to universities in their aspiration to create, disseminate and apply knowledge. However, scholarly impact is an elusive concept. First, the authors present a conceptual model to clarify different dimensions of scholarly impact (i.e. theory and research, education, organizations and society) and four key stakeholders (i.e. other researchers, students, practitioners and policy makers). Second, the authors provide actionable recommendations for university administrators, researchers and educators on how to enhance impact. The scholarly impact model is flexible, expandable, scalable and adaptable to universities in different regions of the world and with different strategic priorities.

The authors conducted a general review of the literature and offered a multidimensional and multistakeholder model of scholarly impact to guide future actions aimed at enhancing scholarly impact.

The authors describe the multidimensional and multistakeholder nature of the critical and yet elusive concept of scholarly impact. The authors delineate multiple dimensions of impact, different stakeholders involved and recommendations for enhancing scholarly impact in the future.

The authors offer practical and actionable recommendations on how to enhance scholarly impact. For university administrators, the authors recommend aligning scholarly impact goals with actions and resource-allocation decisions; ensuring that performance management and reward systems are consistent with impact goals; being strategic in selecting a journal list; developing a strong doctoral program; and promoting practical knowledge and applications. For researchers and educators, the authors recommend developing a personal scholarly impact plan; becoming an academic decathlete; finding ways to affect multiple impact dimensions simultaneously; and leveraging social media to broaden impact on external stakeholders. Implementing these recommendations will benefit other researchers, students, practitioners (e.g. managers, consultants) and policy makers.

The authors provide an innovative way of conceptualizing scholarly impact. In turn, the conceptual analysis results in actionable recommendations for university administrators, researchers and educators to enhance impact.

Learning from errors is a complex process that requires careful support. Building on affective events theory, the purpose of this paper is to explore how a supportive learning from error climate can contribute to social learning from errors through affective and cognitive error responses by individual professionals.

A total of 139 early-career auditors completed an online questionnaire consisting of validated survey scales, allowing for serial mediation analysis to compare direct and indirect effects.

Learning from error climate was directly and positively related to engagement in social learning activities after committing an error. Furthermore, the authors found a double mediation by error strain (an affective error response) and reflecting on errors (a cognitive error response) on this relationship.

Organizations can actively encourage professionals to learn from their errors by creating a supportive learning from error climate and holding professionals accountable for their errors.

The present study enriches the authors’ understanding of the mechanisms through which learning from error climate influences engagement in social learning activities. It extends prior research on learning from errors by investigating the sequential effects of engagement in error-related learning activities performed individually and in social interaction.