Yorkville University

Abstract Jean Grondin’s endeavor to revive metaphysics in a “post-metaphysical” age resonates with the ramifications of Cheng’s onto-generative hermeneutics for Western philosophy. However, Cheng also pinpoints a shortcoming in Grondin that undermines his aims, an underdeveloped understanding of the cosmological source of creativity. To ameliorate this dilemma, Grondin’s claim that Gadamer rejects the source of metaphysical light in Plato is reassessed based on (1) Heidegger’s rethinking of existence as the Daoist Fourfold and (2) a re-interpretation of “the Good beyond Being.” Rather than a boundary to understanding, for Cheng, “beyond Being” signals an existential encounter with the Daoist void. In this way, the light in Grondin’s metaphysical hermeneutics resurfaces from the ground up in Cheng’s cosmo-ontology.

Adopting new technologies changes how people once worked and performed, guaranteeing they get the best out of it while maintaining their leadership in their respective industries. Recently, the HR industry has started using machine learning (ML) as a way to become more innovative in their work. ML has been incorporated into many organizations to support data-based decisions in various areas, including the recruitment process. Traditional methods include the long process of filtering and analyzing resumes in order to identify suitable candidates. Furthermore, personal biases play a role in these selection processes, which may hinder their compatibility with the position. Another factor to consider is the inconsistency of evaluation criteria during the hiring process. Using ML-based techniques, the evaluation of all candidates is done in a shorter time, with more structured and evidence-based approaches utilized. The objective of this chapter is to give a deep understanding of applying ML technology in the candidate selection process and how it enhances the stages of the hiring process. It also highlights the benefits and challenges of using ML. A suggested model of how ML can be applied in practice to reduce bias in candidate selection will also be discussed. It also offers practical recommendations for HR professionals when applying ML techniques, training, and monitoring.

The increase in the awareness of sustainability practices in most companies and the intensity of the commitment of employees have made the workplace undergo noticeable changes in workplace socio-economic dynamics. This study explored the relationship between green work culture and the level of employee commitment in selected pharmaceutical companies in Nigeria, the most populous and largest consumer market in Africa. A total of 400 questionnaires were distributed, and 389 were returned and analyzed using the Pearson product moment correlation method. The results revealed a weak and negative relationship between green work culture and employee commitment within the pharmaceutical companies studied (R = -0.044, p > 0.05). The findings suggest that employees in these organizations demonstrated limited engagement with green work culture practices that could strengthen their commitment and socioeconomic levels. The study identified several factors contributing to this outcome, including inadequate physical and social parameters supporting green initiatives, poor cultural alignment, discouragement, and low employee motivation. These issues are further compounded by broader socioeconomic challenges that affect both organizational policies and individual attitudes toward sustainability. The study emphasizes the need for pharmaceutical organizations in Lagos State to reassess and enhance their green workplace strategies despite prevailing socioeconomic challenges. It recommends that both the physical and social work environments be redesigned to promote employee satisfaction and align with sustainable goals. Addressing socioeconomic challenges through improved incentives, supportive organizational culture, and inclusive workplace design can foster stronger employee commitment and create a more resilient, environmentally conscious workforce.

Decades of fertilization have led to the accumulation of phosphorus (P) in soils, complicating its management and contributing to degradation in Florida’s agricultural systems. Our objective was to quantify the impact of years of fertilization on P stocks and distribution within the soils of this agriculturally significant region. The study employed traditional methods and geostatistics to analyze data gathered from an intensive grid sampling approach across a network of paired sites in Lake City, St. Augustine, and Grandin, FL. The soil samples were analyzed for total P using X-ray fluorescence, bulk density (Db), and soil organic matter (SOM). Our findings revealed an average 44% increase in P due to long-term fertilizer application, with variability in accumulation across different sites. Agricultural practices also led to lower organic matter levels (21–68% decrease) and higher Db (7–24% increase) in cultivated soils. Fertilized fields showed a stronger spatial dependence for Db and SOM compared to unfertilized fields, measured by the nugget: sill (NS) ratio. Additionally, soil P exhibited stronger spatial correlations in fertilized fields, varying with crop type, soil type, and fertilizer application methods. The greater within-plot variances observed for most soil properties, especially in unfertilized fields, indicate the need for scientists to better match sample sizes to the variability of soil properties being studied. This research offers resource and land managers, policymakers, and scientists with quantitative insights into legacy P, guiding site-specific monitoring efforts (e.g., sample size requirements and field-scale variability) and regional forecasting and management strategies (e.g., regional variability).

Agile project management has become a dominant paradigm for managing complex projects, emphasizing flexibility, customer collaboration, and self-organizing teams. However, traditional, hierarchical leadership models often conflict with Agile’s core values, creating a significant leadership gap. Servant leadership, a philosophy where the leader’s primary goal is to serve the team, is theorized to be a natural fit. This study empirically investigates the impact of servant leadership on key project outcomes within Agile environments. A quantitative, cross-sectional survey was administered to 68 project management professionals, selected via purposive sampling, who were actively working in Agile teams. Data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results provide robust support for all hypotheses, indicating that servant leadership has a significant positive effect on team performance (β = 0.45, p < 0.001), team member satisfaction (β = 0.52, p < 0.001), and project success (β = 0.38, p < 0.001). These findings underscore that adopting servant leadership is a strategic lever for enhancing team dynamics and achieving superior project outcomes in Agile settings. The study offers practical implications for organizations and lays the groundwork for future research.

The perpetual struggle to balance academics, work, and social commitments constitutes a profound challenge in academia, with significant repercussions for mental health. This chapter examines the intricate pressures faced by students and faculty, who must navigate conflicting demands of academic performance, financial obligations, and interpersonal relationships. For students, the pursuit of excellence is often overshadowed by economic precarity and social isolation, while faculty contends with the relentless demands of teaching, research, and administration. The chapter highlights how systemic issues-such as institutional hyper productivity, insufficient support systems, and digital encroachments-exacerbate stress and disrupt well-being. It also explores the structural inequities that compound these difficulties. To address these challenges, the chapter offers strategies such as effective time management, fostering supportive academic communities, and advocating for policy reforms that prioritize mental health. It seeks to inspire systemic change toward a more balanced and sustainable academic environment.

This study investigates the impact of macroeconomic factors—inflation, interest rates, exchange rates, money supply, and crisis events—on chemical industry index prices in the US and Germany, using the Autoregressive Distributed Lag (ARDL) model. The analysis identifies significant long-term relationships and short-term interdependence effects between the two markets. In the US, inflation and interdependence effects from Germany drive index prices, while Germany’s index is more sensitive to inflation, interest rates, and exchange rates. The US exerts a stronger influence on Germany, reflecting its global economic dominance. The findings also reveal faster adjustment to equilibrium in the US and greater resilience to crises compared to Germany. These insights provide valuable implications for investors, policymakers, and industry leaders.

This study investigates the impact of Large Language Models (LLMs) on automating business intelligence and financial processes, employing a quantitative approach to analyze their efficacy in enhancing decision-making efficiency. A structured survey was conducted with 268 industry professionals, utilizing a 7-point Likert scale to assess perceptions of LLMs in financial analytics. Regression analysis reveals a significant positive relationship (R2 = 0.635, β = 0.797, p < 0.001), indicating that LLMs substantially contribute to automation outcomes. The findings highlight LLMs' role in improving analytical accuracy and operational efficiency while addressing concerns such as interpretability and integration complexities. Despite their potential, a portion of respondents remain neutral, suggesting challenges in adoption. Diagnostic tests confirm model validity, ensuring robust inferences.

Purpose This study aims to synthesise existing research to provide a comprehensive understanding of the current state of food supply chains by evaluating technological advancements that can address the challenges in food supply chain management (SCM). Design/methodology/approach The scientometric analysis, a quantitative study using statistical methods, selected English publications from after 2014, excluding non-peer-reviewed articles. This study analysed 479 research papers, filtered from 621 articles indexed in Scopus. Findings The review highlights key challenges in food SCM: perishability, increased intermediaries, safety compliance and sustainability. Technological solutions such as blockchain, Internet of Things (IoT), artificial intelligence (AI) and big data (BD) analytics are promising tools to address these issues and attention to food wastage, security and catering services is also essential. Research limitations/implications The study relies on existing literature, possibly missing emerging technologies like multi-enterprise platforms for food certification. Practical implications This review offers valuable insights for food supply chain practitioners by highlighting current trends and contributions from different regions. It underscores the importance of technologies and considers adopting innovative technologies to enhance operations and efficiency. Social implications Accurate food SCM through technological solutions can reduce waste and lower the environmental impact of food production and distribution, emphasising sustainable SCM. Originality/value This study contributes to the existing body of knowledge by systematically reviewing the literature on food SCM and identifying the role of technology in overcoming its challenges. It also directs research on future trends of digitalisation of food SCM.

Background: Dementia is a syndrome with a high global prevalence that includes a number of progressive diseases of the brain affecting various cognitive domains such as memory and thinking and the performance of daily activities. It manifests as symptoms which often include significant mood and behaviour changes that are highly varied. Changed moods and behaviours due to dementia may reflect distress and may be stressful for both the person living with dementia and their informal and formal carers. To provide dementia care support specific to mood and behaviour changes, the Behaviours in Dementia Toolkit website (BiDT) was developed using human-centred design principles. The BiDT houses a user-friendly, digital library of over 300 free, practical, and evidence-informed resources to help all care partners better understand and compassionately respond to behaviours in dementia so they can support people with dementia to live well. Objective: (1) To characterize the users that visited the BiDT; and (2) to understand the platform's early impact on these users. Methods: A multi-method, descriptive study was conducted in the early post-website launch period. Outcomes and measures examined included the following: (1) reach: unique visitors, region, unique visits, return visits, bounce rate; (2) engagement: engaged users, engaged sessions, session duration, pages viewed, engagement rate per webpage, search terms, resources accessed; (3) knowledge change; (4) behaviour change; and (5) website impact: relevance, feasibility, intention to use, improving access and use of dementia guidance, recommend to others. Data was collected using Google Analytics and an electronic survey of website users. Results: From 4 February to 31 March 2024, there were 76,890 unique visitors to the BiDT from 109 countries. Of 76,890 unique visitors to the BiDT during this period, 16,626 were engaged users as defined by Google Analytics (22%) from 80 countries. The highest number of unique engaged users were from Canada (n = 8124) with an engagement rate of 38%. From 5 March 2024 to 31 March 2024, 100 electronic surveys were completed by website users and included in the analysis. Website users indicated that the BiDT validated or increased their dementia care knowledge, beliefs, and activities (82%) and they reported that the website validated their current care approaches or increased their ability to provide care (78%). Further, 77% of respondents indicated that they intend to continue using the BiDT and 81.6% said that they would recommend it to others to review and adopt. Conclusions: The BiDT is a promising tool for sharing practical and evidence-informed information resources to support people experiencing dementia-related mood and behaviour changes. Early evaluation of the website has demonstrated significant reach and engagement with users in Canada and internationally. Survey data also demonstrated high ratings of website relevance, feasibility, intention to use, knowledge change, practice support, and its contribution to dementia guidance.