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This paper will discuss one university’s efforts to initiate a process to better support PK-12 continuous school improvement goals for all 13 schools in their PDS network as a way to broaden the university’s mission and respond more formally to the individual school communities with which they partner.

The paper is conceptual in that it presents an innovative idea to stimulate discussion, generate new ideas and advance thinking about cross-institutional collaboration between universities and professional development schools.

The paper provides insights and ideas for bringing about change and growth in a seasoned PDS partnership network by connecting PK-12 continuous school improvement efforts to PDS partnership work.

This paper fulfills an identified need to study how seasoned partnerships can participate in simultaneous renewal by offering ideas that school–university partnership leaders can build upon as they make efforts to participate in the process of growth and change.

This study aims to determine the pedagogical and socio-emotional impacts of school closures caused by the COVID-19 pandemic in Guinea.

A descriptive, survey-based methodology was used to collect quantitative and qualitative data directly from parents and caregivers. Between February 24 and March 13, 2022, data was gathered from a study population comprising 2,955 adults residing in five communes and five prefectures of Guinea.

Half of all respondents stated that school closures had no particular impact on children in their household, and 42% stated that no intentional pedagogical activities took place during school closures. Approximately 15% of respondents stated that children experienced boredom, loneliness, sadness, depression, stress and anxiety during the school closures.

The study underscores the significance of school closure readiness and interactive learning while revealing limited emotional impact on children. The findings, while specific to Guinea, provide a foundational understanding, highlighting the complexity of pandemic effects on education and the need for adaptive strategies in vulnerable regions.

Organizations have started using the metaverse to sell non-fungible tokens, execute engineering processes and conduct business meetings. A condition of creating value by moving business processes to the metaverse is acceptance of this technology. In business-to-business scenarios, internal employees and external partners may have different views on the topic but must agree upon new practices. Understanding common motivations and challenges associated with using the metaverse is crucial to its success.

The authors interviewed managers from a pharmaceutical company considering conducting meetings with clients in the metaverse. A series of 23 statements on reasons for (non)-use was generated. Twenty-five individuals (13 employees and 12 clients) then ranked these statements against each other, revealing what would drive or hinder their metaverse use. The authors compared these perspectives to identify common issues.

The authors identified four different views. Views 1 and 2 correspond to internal and external participants, while Views 3 and 4 correspond to external ones only. View 1 is skeptical and underlines the role of peers in acceptance. View 2 is a positive perspective centered on usefulness. View 3 is ambivalent and is centered on efforts required to use the metaverse. View 4 reveals a reversed perspective wherein using the metaverse is a low-effort activity.

This paper proposes a case study probing acceptance of a realistic business use of the metaverse. This paper identifies risks to mitigate and motivations to leverage when proposing metaverse usage in a business-to-business context.

This study aims to investigate a startup accelerator’s decisions toward exerting effort in an information acquisition process and selecting an information disclosure strategy. In particular, the authors are interested in examining which factors may cause the accelerator to report more or less accurate information, which will subsequently affect the investment decision and the outcome of the ventures. This study examines the impact of the equity share taken by the accelerator on the effort level being exerted in the information acquisition process, as well as the accelerator’s decision on the information disclosure regime.

The authors use mathematical models built upon well-established theoretical and practical concepts to analyze the research problems and derive the findings.

The authors show that when the accelerator takes a sufficiently large equity share from the entrepreneur in exchange for admitting the entrepreneur’s venture into the acceleration program, the accelerator is motivated to exert a significant level of effort to observe an accurate signal for the quality of the venture, and then disclose the information about the venture’s quality consistently with the observed signal (informative disclosure regime). On the other hand, if the accelerator takes a small equity share, it is optimal for her to exert no effort in the information acquisition process and simply adopt the basic disclosure regime, where the accelerator reports the quality of the venture based solely on the ex ante expected payoff of the venture, regardless of the observed signal.

The results indicate that an equity sharing scheme, which awards a sufficient amount of equity to the accelerator, can be an effective tool to help obtain accurate information about the quality of a startup venture and make a well-informed investment decision.

This research illustrates that the ownership stake of the accelerator can potentially indicate the accuracy of the information about the venture provided by the accelerator to outside investors. That is, when the stake held by the accelerator is large, the investors can conjecture that the information about the venture reported by the accelerator may be highly accurate and reliable. In contrast, if the accelerator holds a small stake, then it is likely that the information provided by the accelerator may not add any value to the publicly available information. These insights can guide investors (e.g. angle investors, venture capitalists, etc.) in making well-informed startup investment decisions.

This short case challenges students to review an array of corporate financial metrics and to match them to one of 13 listed industries. As such, students must use their intuition and common sense pertaining to the distinctive characteristics of, and the key differences between, the 13 named industries, and then identify the financial metrics that are most indicative of those traits.

The study seeks to contribute to a deeper understanding of the relationship between remediations and participation in new media. By lending some transparency, the analysis hopes to contribute toward generating a critical optics aware of the potentials and pitfalls of emergent media.

The methodology is visual semiotic analysis. The author make no claim for one, true interpretation or critical judgment about the images.

In demonstrating some shortfalls of Instagram affordances, the analysis shows how social media sites can develop tools that encourage users to engage in civic consciousness and respectful political debate. The study makes clear that new media tools can hamper or aid participatory logics.

To author’s knowledge, no other study that has analyzed remediated images related to the controversial confirmation of Brett Kavanaugh to the U.S. Supreme Court. It is also important to place these images in the contexts of “iconicity” in emergent media (a concept increasingly being eroded in new media environment).

The main aim of this study is to explore the appropriate factors in measuring COVID-19-induced supply chain disruptions and the impact of these disruptions on the economic vulnerability of small-scale farmers in Sri Lanka.

The findings revealed that most of the farmers have continued to cultivate even during the pandemic despite several challenges which affected their economic status. Therefore, it is concluded that COVID-19-induced transportation and demand disruptions exacerbated the economic vulnerability of small-scale farmers over the disruptions in supply and production.

The findings of this study are crucial for formulating novel policies to improve the sustainability of the Sri Lankan agricultural sector and alleviate the poverty level of Agri-communities in the countryside. As farming is a vital sector in the economy, increased attention ought to be given on facilitating farmers with government-encouraged loans or allowances for their financial stability. Further, the respective government authorities should develop programs for importing and distributing adequate quantities of fertilizers among all the farmers at controlled prices so that they can continue their operations without any interruption. Moreover, the government could engage in collaboratively work with private organizations to streamline the Agri-input supply process. There should be a government initiative for critical consideration of the issues of farming families and their continued motivation to engage in agriculture. Thus, farmers' livelihoods and agricultural prosperity could be upgraded through alternative Agri-inputs and marketing strategies, providing financial assistance, encouraging innovative technology, etc.

Despite the significance and vulnerability of the vegetable and fruit sector in Sri Lanka, there is a limitation in the empirical studies conducted on the supply chain disruptions caused by COVID-19 measures and their implications on the farmers' livelihood. Furthermore, previous empirical research has not employed adequate quantitative tools to analyze the situation or appropriate variables in evaluating COVID-19-induced disruptions. Hence, the current study explored the appropriate factors for measuring COVID-19-induced supply chain disruption using exploratory factor analysis. Then, the impact of those factors on the economic vulnerability of the small scale farmers was revealed through the ordinal logistics regression analysis.

Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

The tech savvy generation Z consumers constitute a significant market of online shopping. Understanding their shopping behavior is thus a pressing need to expand the e-commerce business. Under this backdrop, the study aims to predict the online shopping behavior of generation Z customers in Bangladesh.

This study used the theory of consumption values (TCV) along with shopping enjoyment to understand the online shopping behavior of generation Z. A structured set of questionnaire was used to gather the responses on a five point Likert scale. A total of 411 valid responses were considered after discarding incomplete responses. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) approach with the help of smart PLS 4.0 software.

The statistical findings reveal that functional value is the most significant determinant of online shopping behavior among generation Z followed by social value, conditional value and epistemic value. The study also reveals that relationship between emotional value and online shopping behavior and relationship between conditional value and online shopping behavior is moderated by shopping enjoyment.

The paper contributes to the consumer behavior literature as the findings provide a comprehensive model from values perspectives to understand online shopping behavior among Gen Z customers in a developing country like Bangladesh. The findings of this study offer important insights to the marketers also since it reveals the values consumers consider while shopping online. The findings might help practitioners develop their online strategies to expand the business.