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The purpose of this study is to assess how higher education anchor institutions (HEIs) voluntarily report their non-economic impacts. Its goals are to quantify the ease of public access to this information; strengthen the conceptual foundation for HEI impact reporting; and provide guidance for making HEI voluntary disclosures more accessible, comparable and systematic.

Using an exploratory mixed methods design and purposeful sampling, this study analyzed voluntary public disclosures of 41 anchor institution universities in the USA to assess how they communicate their public value creation to stakeholders. Data sources included impact reports, donor reports, annual reports and sustainability reports. The study also analyzed the accessibility of this information by timing how long it took to locate.

The sampled US anchor institutions communicate their non-economic impact to stakeholders in myriad ways using a variety of formats. Time required to find the reports ranged from 37 to 50 min, with an average of 42.30 min. Disparate reporting formats inhibit comparability.

Only 41 anchor institutions were examined. The small sample may not be representative of the broader landscape of higher education institutions.

Findings offer guidance for improving voluntary nonfinancial disclosures to increase public confidence in higher education institutions while advancing community and global resilience. To strengthen voluntary disclosure practices, the study recommends using a standardized reporting format, framing HEI impact through socio-ecological resilience indicators, integrating reports and obtaining some form of assurance. These changes would enhance the credibility and comparability of the disclosures.

This research provides some of the first empirical insight into how US higher education anchor institutions report their value creation to the public. Its application of socio-ecological systems theory outlines an actionable conceptual foundation for HEI reporting by linking organizational, community and global resilience.

Develop a conceptual model for the training of Chilean engineers in the construction field that considers the facultative symbiosis between sustainable construction (SC) and nature-based solutions (NBS).

This study aims to develop conceptual model for the training of Chilean engineers in the construction field that considers the facultative symbiosis between sustainable construction (SC) and nature-based solutions (NBS). Bibliographic data linked to the complete collection of 7,163 articles published between 2011 and 2022 were extracted from Web of Science and Scopus for BA utilizing VOSviewer software.

A conceptual model for the education of engineers in SC and NBS was developed, based on Bloom’s taxonomy, initial knowledge and cross-cutting skills. This model includes four thematic clusters: green project management, green building, sustainable materials and bioengineering. Its development began with competencies and activities defined in systematic literature review (SLR), which were validated by engineering program directors and rated in the survey as “extremely important,” “very important” or “important.”

This research provides its readers with an extensive understanding of the salient research themes, trends and patterns for engineering education in SC and NBS. Furthermore, this research contributes to the development of clear guidelines for the rapid updating of training programs.

This study uses hedonism as a mediating variable to examine the relationship between mobile money adoption and financial inclusion in Sri Lankan small- and medium-sized businesses (SMEs).

We conducted a quantitative research study utilizing a survey strategy and distributing standardized questionnaires to 150 SMEs in Sri Lanka using a simple random sampling technique.

According to our analysis, a significant relationship exists between mobile money adoption and financial inclusion in SMEs in Sri Lanka. Furthermore, we found that this relationship is mediated by hedonism, offering insights into the phenomenon.

This study’s findings significantly impact Sri Lankan policymakers, financial institutions, and SMEs. Policymakers can use this research to create plans encouraging mobile money usage, potentially improving financial inclusion among SMEs. When SMEs adopt mobile money, financial institutions can adjust their services to match their demands. It is advantageous for SMEs to understand how adopting mobile money can enhance their financial inclusion and overall business stability.

Our study contributes to existing literature in two key ways. Firstly, it addresses a significant research gap by examining the impact of mobile money use on financial inclusion among SMEs in Sri Lanka. Secondly, we introduce the concept of hedonism as a potential mediator, providing a fresh perspective on the complex dynamics that shape the relationship between mobile money adoption and financial inclusion in this context.

While different attempts have been made to use artificial intelligence (AI) to codify communicative behaviors and analyze startups’ video presentations in relation to crowdfunding projects, less is known about other forms of access to entrepreneurial finance, such as video pitches for candidacies into startup accelerators and incubators. This research seeks to demonstrate how AI can enable the startup selection process for both entrepreneurs and investors in terms of video pitch evaluation.

An AI startup (Speechannel) was used to predict the outcomes of startup video presentations by analyzing text, audio, and video data from 294 video pitches sent to a leading European startup accelerator (LUISS EnLabs). 7 investors were also interviewed in Silicon Valley to establish the differences between humans and machines.

This research proves that AI has profound implications with regards to the decision-making process related to fundraising and, in particular, the video pitches of startup accelerators and incubators. Successful entrepreneurs are confident (but not overconfident), engaging in terms of speaking quickly (but also clearly), and emotional (but not overemotional).

This study not only fills the existing research gap but also provides a practical guide on AI-driven video pitch evaluation for entrepreneurs and investors, reshaping the landscape of entrepreneurial finance thanks to AI. On the one hand, entrepreneurs could use this knowledge to modify their behaviors, enabling them to increase their likelihood of being financially backed. On the other hand, investors could use these insights to better rationalize their funding decisions, enabling them to select the most promising startups.

This paper makes a significant contribution by bridging the gap between theoretical research and the practical application of AI in entrepreneurial finance, marking a notable advancement in this field. At a theoretical level, it contributes to research on managerial decision-making processes – particularly those related to the analysis of video presentations in a fundraising context. At a practical level, it offers a model that we called the “AI-enabled video pitch evaluation”, which is used to extract features from the video pitches of startup accelerators and incubators and predict an entrepreneurial project’s success.

Fresh and short food supply chains in grocery quick commerce (q-grocery FSFSCs), while valued for swift delivery, face challenges in sustainability, resource efficiency and scalability. This study aims to redesign the last mile of q-grocery FSFSCs by identifying and validating a framework of applicable circular economy (CE) practices. Furthermore, the study assesses the impact of these practices across various sustainability dimensions to understand their level of contribution to sustainable livelihoods and supply chain resilience.

The study employs a multi-phase approach. First, an integrative literature review identifies CE practices and strategies. Second, a survey gathers data on the relationship between these practices and strategies and their impact on sustainability. Third, the framework is validated using the partial least squares structural equation modeling (PLS-SEM) method in WarpPLS 8.0. Finally, k-means cluster analysis in Tableau 2019.4 groups CE practices based on their impact across five sustainability dimensions: environmental, economic, social, resource efficiency and scalability.

The study validates a framework and identifies high-impact CE practices, such as waste reduction, sustainable packaging, sustainable sourcing, route optimization, sustainable processes and customer convenience. Medium-impact practices include energy efficiency, sustainable fleet, resale and redistribution and information flow. Low-impact practices cover composting, reverse logistics and appropriate storage.

The findings assist q-grocery companies to adopt CE practices and strategies that support sustainable livelihoods and strengthen supply chain resilience while offering policymakers guidance to promote circularity.

This study is unique in the exploration of the intersection of quick commerce, FSFSCs and CE principles, providing actionable insights for sustainability in the q-grocery industry.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.

The extraction of relevant knowledge from data is called knowledge discovery (KD). The KD process requires a large amount of data and it must be reliable before mining. Complexity is not only in deriving knowledge from data but also in improving system performance with a psycho-cognitive approach. KD demands a high level of human cognition and mental activity to generate and retrieve knowledge. Therefore, this study aims to explain how psychological knowledge is involved in KD.

By understanding the cognitive processes that lead to knowledge production, KD can be improved through interventions that target psychological processes, such as attention, learning and memory. In addition, psycho-cognitive approaches can help us to better grasp the process of KD and the factors that influence its effectiveness. The study attempted to correlate interdependence by interpreting cognitive approaches to KD from a psychological perspective. The authors of this paper draw on both primary and secondary literary warrants to empirically prove psychological bending in KD.

Understanding the psychological aspects of data and KD can identify the development of tools, process and environments that support individual and teams in making sense of data and extracting valuable knowledge. The study also finds that interdisciplinary collaboration, bringing together expertise in psychology, data science and domain specific knowledge fosters effective KD processes.

The KD system cannot function well and will not be able to achieve its full potential without psycho-cognitive foundation. It was found that KD in the KD system is influenced by human cognition. The authors made a contribution to KD by fusing psycho-cognitive approaches with data-driven technology and machine learning.