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The purpose of this paper is to investigate how educators perceive and adapt their roles in the face of changes in technology-driven learning environments. The Gioia methodology explores how educators enable adaptive learning, broaden their pedagogical practice and promote cultural inclusivity to educate diverse students.

This paper involves a qualitative interpretive phenomenological research design using the Gioia methodology. Data was collected through semi-structured interviews with 14 educators across various disciplines. Gioia methodology is a structured exploration of first- and second-order themes and aggregate dimensions that capture the nuanced ways in which educators navigate adaptive learning contexts.

This study highlights how digital tools help enable personalized self-directed learning, how adaptive learning adapts educators to become more than just traditional teachers and how the culturally responsive teaching that is required in a globalized learning environment promotes inclusivity and resilience in a diverse group of learners.

This study contributes to the growing body of literature on adaptive learning and identifies educators’ critical, expanded roles in a technology-centred world. This research provides a structured, in-depth analysis of educator perspectives on adaptive learning using the Gioia methodology, offering unique insights into the policy and practice implications.

This research aims to systematically review studies on significant risks for Critical Infrastructure Projects (CIPs) from selected top-tier academic journals from 2011 to 2023.

In this research, a three-step systematic literature review methodology was employed to analyse 55 selected articles on Critical Infrastructure Risks (CIRs) from well-regarded and relevant academic journals published from 2011 to 2023.

The findings highlight a growing research focus on CIRs from 2011 to 2023. A total of 128 risks were identified and grouped into ten distinct categories: construction, cultural, environmental, financial, legal, management, market, political, safety and technical risks. In addition, literature reviews combined with questionnaire surveys were more frequently used to identify CIRs than any other method. Moreover, oil and gas projects were the subjects most often explored in the reviewed papers. Furthermore, it was observed that publications from Iran, the USA and China dominated CIRs research, making significant contributions, accounting for 49.65% of the analysed articles.

This research specifically focuses on five types of CIPs (i.e. roadways, bridges, water supply systems, dams and oil and gas projects). Other CIPs like cyber-physical systems or electric power systems, were not considered in this research.

Governments and contracting firms can benefit from the findings of this study by understanding the significant risks associated with the execution of CIPs, irrespective of the nation, industry or type of project. The results of this investigation can offer construction professionals valuable insights to formulate and implement risk response plans in the early stages of a project.

As a novel literature review related to CIRs, it lays the groundwork for future research and deepens the understanding of the multi-faceted effects of these risks, as well as sets practical response strategies.

This paper aims to explore sociocultural factors as determinants of entrepreneurial emergence and to examine their relative influence (i.e. the influence of each factor) on entrepreneurial emergence.

A survey design with a questionnaire instrument administered to 250 business owners selected randomly from a cross section of businesses was used. The data were analyzed using the descriptive method, pairwise comparison, Kendall’s W test and Mean Rank Statistics.

This study showed that the level of influence of sociocultural factors on the decision to own a business by an individual in Africa varies by factor. Family background is the factor that has the highest influence, whereas religious values has the least influence. Altogether, nine most significant factors influence the choice of business ownership in Nigeria and in Africa generally. These include family background, unemployment, family values, inadequate income, job displacement, stock of social capital, role models, social networks and lack of social security, in that order.

Although some scholars may have explored sociocultural factors as determinants of entrepreneurial emergence, there is no study on their relative influence on entrepreneurial emergence, at least not in the context of Africa or Nigeria in particular. This study extends previous studies by examining the relative influence of the factors, using Nigeria as a reference for Africa. A focus on their relative influence is a new perspective on the study of sociocultural factors as determinants of entrepreneurial emergence.

This study explores the pivotal role of artificial intelligence (AI) in revolutionizing knowledge organization within Nigerian libraries. The purpose of this study is to assess the challenges faced by these libraries, propose strategic approaches for successful AI integration and highlight the potential benefits and future directions of this transformative journey.

This study uses a comprehensive review of existing literature, case studies and a qualitative analysis of challenges faced by Nigerian libraries. Strategies for AI integration are proposed based on targeted capacity building, collaborative partnerships and phased implementation approaches. The methodology also involves assessing the current landscape of AI in Nigerian academic libraries, examining applications and exploring the perceived impacts of AI on library services.

Nigerian libraries face challenges such as limited resources, outdated systems and diverse information that hinder traditional knowledge organization methods. The integration of AI offers dynamic solutions, streamlining administrative tasks, optimizing search algorithms and enhancing user engagement. The findings of this study emphasize the potential benefits of AI, including improved accessibility, searchability and long-term efficiency gains in library collections.

This research contributes to the existing literature by providing insights into the specific challenges faced by Nigerian libraries and proposing practical strategies for AI integration. This study emphasizes the transformative potential of AI in addressing immediate challenges and unlocking enduring benefits. The originality lies in the context-specific exploration of AI in Nigerian libraries, offering a roadmap for stakeholders to embrace technological advancements and position libraries as leaders in providing innovative knowledge services.

Open access (OA) resources are free to access and help in research and teaching/learning, allowing libraries to manage resources more sustainably and effectively. Hence, this study aims to examine use of OA resources for economic sustainability among librarians in selected university libraries in Kwara State, Nigeria.

This study adopts descriptive survey research design. Using total enumeration sampling technique, a sample of 46 professional librarians were drawn from the selected universities. Questionnaire was used for data collection, and descriptive statistics was used for data analysis.

The findings show that most of the librarians had high level of awareness about OA resources. Results demonstrate that majority of the librarians used PubMed Central bi-weekly. Findings show that the librarians used OA resources to support academic research, enhance library’s collection without additional cost and facilitate information access for users with limited financial resources. Results indicate that most of the librarians perceived that OA resources impact library’s operational cost and goal of economic sustainability.

This study highlights the need for targeted training and resource development to enhance the effective use of OA resources. Meanwhile, the consistent usage of OA resources suggests the importance of the resources to librarians, aligning with previous studies on frequent use of established OA repositories.

This study provides evidence on the relevance and impact of OA resources use on economic sustainability, demonstrating the importance of OA resources in knowledge dissemination and fostering innovation.

Polytechnics in Nigeria are conventional institutions where academic board records are being managed in paper form. It has been observed that accessing these academic board records is difficult due to factors associated with the absence of preservation techniques and lack of clear-cut conservation practices. This study, therefore, aims to examine the preservation techniques and conservation practices adopted for the management of academic board records in polytechnics in South-West Nigeria.

This study adopted a qualitative method with the population comprising 54 records management personnel enumerated in the four selected polytechnics in South-West Nigeria. Triangulation method (questionnaire, interview and observation checklist) was used for data collection. The responses were analysed with descriptive statistics and thematic analysis.

Findings revealed that photocopying, binding and use of insecticides were the most rated preservation techniques adopted. The security and shelving of academic board records to allow for free flow of air were the most available conservation practices, whereas staff training was not adequately available. The topmost rated constraints were non-challant attitude of personnel in-charge, insufficient funds and inadequate infrastructure.

This study concluded that preservation and conservation practices are vital in the management of academic board records in polytechnics in South-West Nigeria. For efficient and effective management of academic board records, modern-day preservation and conservation practices need to be adopted.

This paper fulfils an identified need to study how preservation and conservation practices adopted for the management of academic board records in Nigerian polytechnics.

This paper aims to present the development of a holistic campus facility management (CFM) performance assessment framework that incorporates a fuzzy logic approach and integrates a comprehensive set of key factors for successful management of campus facilities. The devised framework aims to cater to the needs of campus facilities management firms and departments for the purpose of gauging and assessing their performance across different management domains. Through this approach, facility management organizations can detect potential areas of enhancement and adopt preemptive steps to evade issues, foster progress and ensure success.

After a comprehensive analysis of the literature, conducting in-depth interviews with industry experts and employing the Delphi technique in two rounds, a total of 45 indicators critical to CFM success were identified and subsequently sorted into seven distinct groups. Through an online questionnaire, 402 subject-matter experts proficiently assessed the significance of the critical success indicators and their groups. A fuzzy logic framework was developed to evaluate and quantify a firm's compliance with the critical success indicators and groups of indicators. The framework was subsequently weighted using computations of the relative importance index (RII) based on the responses received from the questionnaire participants. The initial section of the framework involved a comprehensive analysis of the firm's performance vis-à-vis the indicators, while the latter part sought to evaluate the impact of the indicators groups on the overall firm's performance.

The utilization of fuzzy logic has uncovered the significant effects each effective CFM key indicator on indicators groups, as well as the distinct effects of each CFM indicators group on the overall performance of CFM. The results reveal that financial management, communications management, sustainability and environment management and workforce management are the most impactful indicators groups on the CFM performance. This suggests that it is imperative for management to allocate increased attention to these specific areas.

This study contributes to the advancement of current knowledge by revealing vital indicators of effective CFM and utilizing them to construct a thorough fuzzy logic framework that can assist in evaluating the effectiveness of CFM firms worldwide. This has the potential to provide crucial assistance to facility management organizations, facility managers and policymakers in their quest for informed decision-making.

We developed the Goal Achievement Scale in Colleges of Education (GASCE) to address the lack of context-specific assessment tools for evaluating goal achievement in Nigerian colleges of education. Existing instruments fail to capture the unique challenges of these institutions, making a reliable and valid scale essential for assessing educational success.

Using a descriptive survey research design, we developed and validated the GASCE through expert review, pilot testing, and statistical analyses. Our sample of 450 respondents from Nigerian colleges of education participated in exploratory factor analysis (EFA), graded response modeling (GRM-IRT), confirmatory factor analysis (CFA) and multiple group confirmatory factor analysis (MG-CFA). We assessed reliability using composite reliability and validated construct and criterion-related validity through correlations with external goal achievement measures.

CFA confirmed a six-factor structure – critical thinking, committed teaching, high motivation, intellectual fitness, professional fitness and social fitness – with strong model fit indices. Reliability testing showed high internal consistency (Omega alpha: 0.845–0.919). MG-CFA confirmed measurement invariance across academic and non-academic staff (Δcomparative fit index < 0.015, Δroot mean square error of approximation < 0.010), while criterion-related validity was supported by significant correlations with external measures.

While the sample size supports validation, it may not fully represent all Nigerian colleges of education. Future research should expand the sample and incorporate objective performance data for further validation.

The GASCE provides policymakers, educators and administrators with a robust tool to assess and improve educational performance, facilitating targeted interventions and efficient resource allocation.

The GASCE fills a critical gap in educational assessment by offering a reliable, context-specific tool for Nigerian colleges of education. It enables comprehensive evaluation of goal achievement, supporting continuous improvement in teacher education programs across Nigeria.

This study aims to apply machine learning techniques to efficiently predict leisure firms’ financial performance. Accurate financial forecasting is crucial in leisure and tourism, greatly affecting firms’ strategic decisions and competitive positioning. This study emphasizes the roles of intellectual capital to offer a nuanced understanding of how these types of capital influence firm success.

Using comprehensive firm-level data, this study examines several machine learning algorithms’ predictive capacity across a spectrum of industry sectors (general, manufacturing, service) to identify the most effective model and training dataset. These tools are used to evaluate financial metrics such as return on sales, return on assets and sales growth. A range of variables are incorporated into this process to enhance model accuracy and relevance.

Results demonstrate the support vector machine algorithm’s exceptional performance based on a training data set from the service sector in predicting leisure firms’ return on sales and sales growth. This algorithm is thus an efficacious strategic forecasting instrument. The variables significantly affecting firm performance include demand variation; organizational, product and technological innovation; synergistic innovation between multiple domains; salary levels; market strategy; and the number of employees.

By integrating advanced machine learning techniques with the strategic management of intellectual capital, this study presents a sophisticated approach to predicting leisure firms’ financial performance. Findings enrich the discourse on firm performance forecasting and offer actionable insights into strategic planning and resource allocation for practitioners in the leisure and tourism sectors.

本研究应用机器学习技术来高效预测休闲企业的财务表现。准确的财务预测对于休闲和旅游业至关重要, 极大影响企业的战略决策和竞争定位。本研究强调智力资本的作用, 以深入理解这些资本类型如何影响企业的成功。

本研究使用全面的企业层面数据, 考察多种行业领域（综合、制造、服务）中多个机器学习算法的预测能力, 识别出最有效的模型和训练数据集。这些工具用于评估财务指标, 如销售回报率、资产回报率和销售增长率。过程纳入多种变量, 以提高模型的准确性和相关性。

结果表明, 基于服务行业训练数据集的支持向量机算法在预测休闲企业的销售回报率和销售增长率方面表现出色。因此, 该算法是一种有效的战略预测工具。影响企业绩效的显著变量包括需求变化、组织、产品和技术创新、多领域之间的协同创新、工资水平、市场战略和员工数量。

通过将先进的机器学习技术与智力资本的战略管理相结合, 本研究提出了一种复杂的方法来预测休闲企业的财务表现。研究结果丰富了关于企业绩效预测的讨论, 并为休闲和旅游业的从业者提供了有关战略规划和资源分配的实用见解。

By exploring the halalness and food safety risks from the perspective of technology and the relationship among them, this study aims to make quantitative predictions of such risks in the broiler supply chain to determine the critical control points (CCPs) in Hazard Analysis Critical Control Point (HACCP).

This study integrates Interpretive Structural Modeling (ISM) and Bayesian Network (BN) to achieve the objectives. Data were collected from focus group discussions (FGDs) with experts and direct observations at the broiler supply chain.

This paper identified 19 risks in the Indonesian broiler supply chain. The risk for halalness and food safety reached 30.92%, indicating that assuring halalness and food safety remains improbable or unlikely. The two CCPs of halalness and food safety are the knife’s sharpness and the vehicle’s storage temperature.

This study quantifies the halalness and food safety risks in the Indonesian broiler supply chain, but it only involves one step forward and one step backward in the slaughterhouse’s chain.

The findings can provide insights for stakeholders, such as business owners, employees, management system auditors and consumers, regarding the critical control points of halalness and food safety in the broiler supply chain to improve the halalness and food safety management systems.

This study’s novelty lies in the examination of halalness and food safety risks using a risk prediction model to determine CCPs for the HACCP plan in the broiler supply chain in Indonesia.