One of the key attempts towards a collective African vision is the New Economic Partnership for African Development (NEPAD). Barnard and Vonk (2003) report that “53 countries have been urged to implement ICTs in three crucial development arenas: education, health and trade”. While NEPAD and other initiatives have contributed to the provision of ICT infrastructure with positive results as seen in the growth of Internet uses, the disparities in development across Africa are enormous. The challenge to Higher Education Institutions in Africa has been summarised by Colle (2005): “central to creating digital resources and academic infrastructure is the question of universities’ relevance to the world around them, and especially to the challenge of being an active player – ‘an anchor of a broad-based poverty alleviation strategy’ in an increasingly knowledge-based economy”. It can be inferred from Colle that the activities of HEIs in Africa ought to be geared towards contributing to the realisation of the Millennium development goals.

Aim/Purpose: Assess the affordances and constraints of SimReal+ in teacher education Background There is a huge interest in visualizations in mathematics education, but there is little empirical support for their use in educational settings Methodology: Single case study with 22 participants from one class in teacher education. Quantitative and qualitative methods to collect students’ responses to a survey questionnaire and open-ended questions Contribution: The paper contributes to the understanding of affordances and constraints of visualization tools in mathematics education Findings: The visualization tool SimReal+ has potential for learning mathematics in teacher education, but the user interface should be improved to make it more usable for different users. Teachers need to consider technological and pedagogical affordances of SimReal+ at the student, classroom, and mathematics subject level Recommendations for Practitioners: Address technological and pedagogical affordances of SimReal+ Recommendation for Researchers: Improve the design of SimReal+ to make it technologically and pedagogically more usable Impact on Society: Understand the affordances and constraints of visualization tools in education Future Research: Implement a next cycle of experimentation with SimReal+ in teacher education to ensure more validity and reliability

Aim/Purpose: This paper describes and information system for the maintenance and management of municipal lighting systems that also serves as a decision support tool for reducing power consumption on urban lighting. Background: Many municipalities are financially constrained and unable to invest in improving their lighting infrastructure. We propose a very efficient and inexpensive way to set up the database and provide city leaders with tools to improve their system efficiently. Methodology: An information database for the data management and an Integer Programming model for deriving the optimal investment plan. Contribution: This paper contributes to the fields of urban economics and sustainability. Findings: Informing management and workers about the status of the system and how to optimize it will reward the city with considerable savings and improve the service quality. Recommendations for Practitioners: The application of this model, even in a small scale such as a neighborhood can improve citizen’s quality of life without a heavy burden on the city budget. Recommendation for Researchers: There is a growing need for cost-effective means to improve urban management. Innovative ideas that meet these goals should be researched and developed. Impact on Society: First, it allows reduction in carbon emissions and light pollution by reducing power consumption and over-luminous lighting levels. Second, financially constrained municipalities can manage their systems at a very low cost. Future Research: A full scale application is needed in order to evaluate the city-wide benefits of the system.

Aim/Purpose: The aim of this project was to explore a method to enable an updated under-standing of digital literacy to be implemented in curricula in an environment of an existing, but outdated, understanding of digital literacy. . Background: The changing healthcare environment increasingly emphasizes the importance of digital literacy skills; therefore academics in the optometry discipline at Deakin University sought to better understand where digital literacy skills were taught in their program, and whether delivery was implicit or explicit. Methodology: This case study describes a systematic review of the optometric curriculum to first identify where and what digital literacy skills are currently being addressed in the curriculum, identify the gaps, and develop a strategy to address the gaps. Contribution: The main outcome of this work is the development of a spiraling curriculum to support the development of digital literacy skills required in later units of the program and for clinical practice post-graduation. Findings: Although the definition of digital literacy may be outdated, the digital literacy capabilities being addressed in the curriculum had grown as digital technology use by staff and students had expanded. This, together with the realization that students were not as digitally capable as expected, indicated that teaching digital literacy skills needed to be made overt throughout the curriculum. Recommendations for Practitioners: The process developed through this case study provides a strong foundation for course teams, curriculum developers and educational designers to efficiently analyze digital literacy expectations in existing, accredited health-related curricula and improve the curricula by more overtly embedding digital literacy teaching into it. Impact on Society: Graduates of the amended program of study are expected to be better prepared to undertake their future careers in a digitally enhanced and disrupted environment. Future Research: The framework will be used to explore digital literacy teaching practices in other disciplines. A systematic evaluation will be undertaken to identify the benefits and short comings of using the framework. The elements that make up the new definition of digital literacy need to be better articulated to allow curriculum developers to be better informed as to how to interpret the framework in their context.

Aim/Purpose: The purpose of this paper is to illuminate the learning that happens in assuming a supervisee’s role during the postgraduate study. Background: The facilitators and barriers students encountered while pursuing postgraduate studies, strategies to achieve success in postgraduate studies, and how to decrease attrition rates of students, have been sufficiently explored in literature. However, there is little written about the personal and professional impact on students when they are being supervised to complete their postgraduate studies. Methodology: Autoethnographic method of deep reflection was used to examine the learning that transpired from the supervisee’s perspective. Two lecturers (a Senior Lecturer in Nursing and an Aboriginal Tutor) focused on their postgraduate journeys as supervisees, respectively, with over 30 years of study experience between them, in Australia and abroad. Contribution: Future postgraduate students, researchers, would-be supervisors and experienced supervisors could learn from the reflections of the authors’ postgraduate experiences. Findings: Four themes surfaced, and these were Eureka moments, Critical friend(s), Supervisory relationship, and Transformative learning. The authors highlighted the significance of a supervisory relationship which is key to negotiating the journey with the supervisor. Essential for these students also were insights on finding the path as well as the destination and the transformative aspects that happened as a necessary part of the journey. Conclusion. The postgraduate journey has taught them many lessons, the most profound of which was the change in perspective and attitude in the process of being and becoming. Personal and professional transformative learning did occur. At its deepest level, the authors’ reflections resulted in self-actualization and a rediscovery of their more authentic selves. Recommendations for Practitioners: This article highlights the importance of the supervisory relationship that must be negotiated to ensure the success of the candidate. Reflections of the transformation are recommended to support the students further. Recommendation for Researchers: Quality supervision can make a significant influence on the progress of students. Further research on the supervisory relationship is recommended. Impact on Society: The support in terms of supervision to ensure postgraduate students’ success is essential. Postgraduate students contribute to the human, social, professional, intellectual, and economic capital of universities and nations globally. Future Research: Further reflections of the transformative learning will advance the understanding of the personal and professional changes that occur with postgraduate supervision.

Aim/Purpose: This research study explores the challenges, successes, and supports de-sired in implementing virtual learning following a survey of faculty for their experiences and interests. Faculty in higher education need quick, practical tools and strategies to enhance teaching and learning in a virtual classroom. Background The sudden and ongoing COVID-19 pandemic had created an urgency to transition to a virtual learning environment, yet expectations for faculty to teach virtually may not have matched best practice and current research. Methodology: This qualitative research begins with an anonymous, emailed survey of higher education faculty designed to explore participant thoughts and experiences related to their virtual teaching in Fall 2020. The survey included a series of demographic questions related to what type of faculty they were (full-time or adjunct), which discipline they taught, which format they were teaching in, as well as 5 open-ended questions to elicit feedback to teaching in this format of their challenges, some positives, strategies used, how they assessed learning, and which workshops they would like offered to better support them. A full year after the pandemic began, we sent out a follow-up survey to check in with faculty and find out specifically new skills/mindsets they developed, new tools they may have tried, their level of stress as well as how they perceived their students’ stress and their students’ level of learning. We decided to broaden our population by sharing the follow-up survey via social media to capture a diverse audience, which included international participants. Contribution: Despite the different stress levels for most faculty and students during the pandemic of 2020-2021, our research highlights that it was also a time of growth and learning. Learning from past experiences can help us be pre-pared for future challenges related to virtual learning. Findings: We found that the emergency remote teaching caused faculty to explore new ways of teaching and learning and helped them to develop a mindset that embraced a variety of skills such as flexibility, creativity, and innovation. We also learned that being aware of the stress levels of both faculty and students is of great value to institutions and with a good infrastructure and support, virtual learning can be successful. Recommendations for Practitioners: Through our research, we have found faculty are lacking the tools necessary to engage their learners in a virtual setting. As such, best practices need to be shared and then embedded into the instructional approach. However, given the pandemic, faculty were forced to transition face to face classes to a virtual format without having been provided these best practices. Recommendations for Researchers: We recommend researchers explore the habits of minds of faculty and how they have developed and continue to develop due to challenges they experienced related to virtual learning and continue to experience. Impact on Society: Many of the skills that faculty developed due to this emergency shift to virtual teaching during 2020 and beyond are skills faculty will have for life. With support and ideas faculty can implement quickly, faculty will be better prepared to provide instruction and create settings that enhance teaching and learning in a virtual setting. Future Research: Future research could include providing a voice for students by distributing a survey to the student body for their views and perceptions on virtual learning during the pandemic and moving forward.

This work investigated the suitability of a new tool for decision support in training programs of high performance athletes. The aim of this study was to find a reliable and robust measure of the fitness of an athlete for use as a tool for adjusting training schedules. We examined the use of heart rate recovery percentage (HRr%) for this purpose, using a two-phased approach. Phase 1 consisted of testing the suitability of HRr% as a measure of aerobic fitness, using a modified running test specifically designed for high-performance team running sports such as football. Phase 2 was conducted over a 12-week training program with two different training loads. HRr% measured aerobic fitness and a running time-trial measured performance. Consecutive measures of HRr% during phase 1 indicated a Pearson’s r of 0.92, suggesting a robust measure of aerobic fitness. During phase 2, HRr% reflected the training load and significantly increased when the training load was reduced between weeks 4 to 5. This work shows that HRr% is a robust indicator of aerobic fitness and provides an on-the-spot index that is useful for training load adjustment of elite-performance athletes.

Aim/Purpose: This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the information to circumvent big data challenges for executive strategic decision making. Background: This journal paper seeks to understand what executives value in data visualization, based on the literature published from prior data studies. Methodology: The qualitative methodology was used to understand the sentiments of executives and data analysts using semi-structured interview techniques. Contribution: The preliminary findings can provide practical knowledge for data visualization designers, but can also provide academics with knowledge to reflect on and use, specifically in relation to information systems (IS) that integrate human experience with technology in more valuable and productive ways. Findings: Preliminary results from interviews with executives and data analysts point to the relevance of understanding and effectively presenting the data source and the data journey, using the right data visualization technology to fit the nature of the data, creating an intuitive platform which enables collaboration and newness, the data presenter’s ability to convey the data message and the alignment of the visualization to core the objectives as key criteria to be applied for successful data visualizations Recommendations for Practitioners: Practitioners, specifically data analysts, should consider the results highlighted in the findings and adopt such recommendations when presenting data visualizations. These include data and premise understanding, ensuring alignment to the executive’s objective, possessing the ability to convey messages succinctly and clearly to the audience, having knowledge of the domain to answer questions effectively, and using the right technology to convey the message. Recommendation for Researchers: The importance of human cognitive and sensory processes and its impact in IS development is paramount. More focus can be placed on the psychological factors of technology acceptance. The current TAM model, used to describe use, identifies perceived usefulness and perceived ease-of-use as the primary considerations in technology adoption. However, factors that have been identified that impact on use do not express the importance of cognitive processes in technology adoption. Future Research: Future research requires further focus on intangible and psychological factors that could affect technology adoption and use, as well as understanding data visualization effectiveness in corporate environments, not only predominantly within the Health sector. Lessons from Health sector studies in data visualization should be used as a platform.

Aim/Purpose: This work aims to present a knowledge modeling technique that supports the representation of the student learning process and that is capable of providing a means for self-assessment and evaluating newly acquired knowledge. The objective is to propose a means to address the pedagogical challenges in m-learning by aiding students’ metacognition through a model of a student with the target domain and pedagogy. Background: This research proposes a framework for social and meta-cognitive support to tackle the challenges raised. Two algorithms are introduced: the meta-cognition algorithm for representing the student’s learning process, which is capable of providing a means for self-assessment, and the social group mapping algorithm for classifying students according to social groups. Methodology : Based on the characteristics of knowledge in an m-learning system, the cognitive knowledge base is proposed for knowledge elicitation and representation. The proposed technique allows a proper categorization of students to support collaborative learning in a social platform by utilizing the strength of m-learning in a social context. The social group mapping and metacognition algorithms are presented. Contribution: The proposed model is envisaged to serve as a guide for developers in implementing suitable m-learning applications. Furthermore, educationists and instructors can devise new pedagogical practices based on the possibilities provided by the proposed m-learning framework. Findings: The effectiveness of any knowledge management system is grounded in the technique used in representing the knowledge. The CKB proposed manipulates knowledge as a dynamic concept network, similar to human knowledge processing, thus, providing a rich semantic capability, which provides various relationships between concepts. Recommendations for Practitioners: Educationist and instructors need to develop new pedagogical practices in line with m-learning. Recommendation for Researchers: The design and implementation of an effective m-learning application are challenging due to the reliance on both pedagogical and technological elements. To tackle this challenge, frameworks which describe the conceptual interaction between the various components of pedagogy and technology need to be proposed. Impact on Society: The creation of an educational platform that provides instant access to relevant knowledge. Future Research: In the future, the proposed framework will be evaluated against some set of criteria for its effectiveness in acquiring and presenting knowledge in a real-life scenario. By analyzing real student interaction in m-learning, the algorithms will be tested to show their applicability in eliciting student metacognition and support for social interactivity.

Aim/Purpose: This study uses a cosmetic virtual community (VC) as the research context and the UTAUT model as the theoretical structure aim to explore factors affecting the re-usage intentions of VC members. Background: The Internet use rate of VC was up to 50%, thereby implying that VC gained the attention of Internet users. Therefore, operating a VC will be an effective way to communicate with customers. However, to maintain an existing member is more efficient than creating a new one. As such, understanding determinants of VC members’ re-use intentions becomes important for firms. Methodology: Through an online survey, 276 valid responses were gathered. The collected data were examined by performing confirmatory factor analysis, structural equation modelling procedures, as well as the moderator analysis. Contribution: This study shows the importance in the context of online cosmetics-related VC, which was rarely explored before. We provide issues for future research, despite the accumulated academic literature related to UTAUT and VC. Findings: Results show that only performance expectancy and social influence significantly affecting re-usage intentions and only gender has moderating effects on the path from performance expectancy to VC re-use intention and from trust to VC re-use intention. Recommendations for Practitioners : This study found that users emphasized performance expectancy most of all. A cosmetic product-related VC should introduce products abundantly, offer useful information, and help people accomplish tasks quickly and productively. Recommendation for Researchers: Future researchers may use our findings to conduct further positivist research in the area of social influence using different subjects and research contexts.

Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes.

Aim/Purpose: The study attempts to analyse the influences of knowledge management capacity on company performance and supply chain practices. It also examines whether supply chain practices significantly and positively impact company performance. Background: Knowledge management capacity is an essential tactical resource that enables the integration and coordination among supply chain stakeholders, but research examining the link between knowledge management capacity and supply chain practices and their impacts on company performance remains scarce. Methodology: The study uses correlation analysis and factor analysis to confirm the theoretical framework’s validity and structural equation modelling to test hypotheses. The data are obtained from 115 halal food firms in China (with a response rate of 82.7%). Contribution: This study’s findings contribute to the Social Capital Theory by presenting the impacts of different supply chain practices on company performance. The findings also suggest the impact of intangible resources on enhancing company performance, contributing to the Resource-based View Theory. These results are a crucial contribution to both academicians and corporate managers working in the Halal food industry. Managers can apply these findings to discover and adopt knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Findings: This study is an initial effort that provides empirical evidence regarding the relationships among supply chain, knowledge management, and company performance from the perspective of China’s halal food industry. The results prove that knowledge management capacity is the supply chains’ primary success determinant and influencer. Besides, knowledge management capacity positively influences company performance, and supply chain practices directly influence company performance. Recommendations for Practitioners: Managers can apply these study findings to determine and increase knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Recommendation for Researchers: The study presents a new theoretical framework and empirical evidence for surveying halal food businesses in China. Impact on Society: These results are a significant contribution to the research field and industry focusing on halal foods. Future Research: First, this research focuses only on halal food businesses in China; thus, it is essential to re-examine the hypothesized relations between the constructs in other Chinese business segments and regions. Next, the effect of variables and practices on the theorized framework should be taken into account and examined in other industries and nations.

Aim/Purpose: The first goal is to develop a decision support system for pricing and production amounts for a firm facing high levels of product returns. The second goal is to improve the management of the product returns process. Background: This study was conducted at a food importer and manufacturer in Israel facing a very high rate of product returns, much of which is eventually discarded. The firm’s products are commonly considered to be a low-cost generic alternative and are therefore popular among low-income families. Methodology: A decision support module was added to the plant’s business information system. The module is based on a supply chain pricing model and uses the sales data to infer future demand’s distribution. Ergonomic models were used to improve the design of the returns warehouse and the handling of the returns. Contribution: The decision support system allows to improve the plant’s pricing and quantity planning. Consequently, it reduced the size of product returns. The new design of the returns process is expected to improve worker’s productivity, reduces losses and results in safer outcomes. This study also demonstrates a successful integration and of a theoretical economical model into an information system. Findings: The results show the promise of incorporating pricing supply chain models into informing systems to achieve a practical business task. We were able to construct actual demand distributions from the data and offer actual pricing recommendations that reduce the number of returns while increasing potential profits. We were able to identify key deficiencies in the returns operations and added a module to the decisions support system that improves the returns management and links it with the sales and pricing modules. Finally, we produced a better warehouse design that supports efficient and ergonomic product returns handling. Recommendations for Practitioners: This work can be replicated for different suppliers, manufacturers and retailers that suffer from product returns. They will benefit from the reduction in returns, as well as the decrease in the losses associated with these returns. Recommendation for Researchers: It is worthwhile to research whether decision support systems can be applied to other aspects of the organizations’ operations. Impact on Society: Product returns is a lose-lose situation for producers, retailers and customers. Moreover, mismanagement of these returns is harmful for the environment and may result in the case of foods, in health hazards. Reducing returns and improving the handling improves sustainability and is beneficial for society. Future Research: The decision support system’s underlying pricing model assumes a specific business setting. This can be extended using other pricing models and applying them in a similar fashion to the current application.

Aim/Purpose: The present study examines the effect of perceived organisational and co-worker support on the adjustment of repatriates and its impact on their intention to transfer knowledge in multinational companies (MNCs). It also examines the relationship between perceived organisational support, co-worker support, and knowledge transfer through the mediating role of repatriate adjustment. Background: The ability of acquiring and utilising international knowledge is one of the core competitive advantages of MNCs. This knowledge is transferred by MNCs across their subsidiaries efficiently through repatriates, which will result in superior performance when compared to their local competitors. But in MNCs the expatriation process has been given more emphasis than the repatriation process; therefore, there is limited knowledge about repatriation knowledge transfer. Practically, the knowledge transferred by repatriates is not managed properly by the MNCs. Methodology: The proposed model was supported by Uncertainty Reduction Theory, Organisational Socialisation Theory, Organisational Support Theory, and Socialisation Resource Theory. The data were gathered from 246 repatriates working in Indian MNCs in the manufacturing and information technology sectors who had been on an international assignment for at least one year. The data obtained were analysed using Structural Equation Modeling (SEM) using AMOS 21 software. Contribution: The present study expands prior research on repatriate knowledge transfer by empirically investigating the mediating role of repatriate adjustment between perceived support and repatriate knowledge transfer in MNCs. The present study also highlights that organisational and co-worker support during repatriation is beneficial for repatriate knowledge transfer. It is important that MNCs initiate support practices during repatriation to motivate repatriates to transfer international knowledge. Findings: The results revealed that both perceived organisational and co-worker support had a significant role in predicting repatriate adjustment in MNCs. Furthermore, the results also revealed that perceived organisational and co-worker support increases repatriate knowledge transfer through repatriate adjustment in MNCs. Recommendations for Practitioners: This study indicates the role of management in motivating repatriates to transfer their knowledge to the organisation. The management of MNCs develop HR policies and strategies leading to high perceived organisational support, co-worker support, and repatriate adjustment. They need to pay particular attention to the factors that affect the repatriates’ intention to share knowledge with others in the organisation. Recommendation for Researchers: Researchers can use the validated measurement instrument which could be essential for the advancement of future empirical research on repatriate knowledge transfer. Impact on Society: The present study will assist MNCs in managing their repatriates during the repatriation process by developing an appropriate repatriation support system. This will help the repatriates to better adjust to their repatriation process which will motivate them to transfer the acquired knowledge. Future Research: Future research can adopt a longitudinal style to test the different levels of the adjustment process which will help in better understanding the repatriate adjustment process. Additionally, this model can be tested with the repatriates of other countries and in diverse cultures to confirm its external validity. Furthermore, future research can be done with the repatriates who go on an international assignment through their own initiative (self-initiated expatriates).

Aim/Purpose: The aim of this research paper is to suggest a comprehensive model that incorporates the technology acceptance model with the task-technology fit model, information quality, security, trust, and managerial support to investigate the intended usage of big data analytics (BDA) in banks and insurance companies. Background: The emergence of the concept of “big data,” prompted by the widespread use of connected devices and social media, has been pointed out by many professionals and financial institutions in particular, which makes it necessary to assess the determinants that have an impact on behavioral intention to use big data analytics in banks and insurance companies. Methodology: The integrated model was empirically assessed using self-administered questionnaires from 181 prospective big data analytics users in Moroccan banks and insurance firms and examined using partial least square (PLS) structural equation modeling. The results cover sample characteristics, an analysis of the validity and reliability of measurement models’ variables, an evaluation of the proposed hypotheses, and a discussion of the findings. Contribution: The paper makes a noteworthy contribution to the BDA adoption literature within the finance sector. It stands out by ingeniously amalgamating the Technology Acceptance Model (TAM) with Task-Technology Fit (TTF) while underscoring the critical significance of information quality, trust, and managerial support, due to their profound relevance and importance in the finance domain. Thus showing BDA has potential applications beyond the finance sector. Findings: The findings showed that TTF and trust’s impact on the intention to use is considerable. Information quality positively impacted perceived usefulness and ease of use, which in turn affected the intention to use. Moreover, managerial support moderates the correlation between perceived usefulness and the intention to use, whereas security did not affect the intention to use and managerial support did not moderate the influence of perceived ease of use. Recommendations for Practitioners: The results suggest that financial institutions can improve their adoption decisions for big data analytics (BDA) by understanding how users perceive it. Users are predisposed to use BDA if they presume it fits well with their tasks and is easy to use. The research also emphasizes the importance of relevant information quality, managerial support, and collaboration across departments to fully leverage the potential of BDA. Recommendation for Researchers: Further study may be done on other business sectors to confirm its generalizability and the same research design can be employed to assess BDA adoption in organizations that are in the advanced stage of big data utilization. Impact on Society: The study’s findings can enable stakeholders of financial institutions that are at the primary stage of big data exploitation to understand how users perceive BDA technologies and the way their perception can influence their intention toward their use. Future Research: Future research is expected to conduct a comparison of the moderating effect of managerial support on users with technical expertise versus those without; in addition, international studies across developed countries are required to build a solid understanding of users’ perceptions towards BDA.

Aim/Purpose: This study investigates the intention to invest in online peer-to-peer (P2P) lending platforms among the bottom 40% (B40) Malaysian households by income. Background: The B40 group citizens earn less than USD 1,096.00 (i.e., RM 4,850.00) in monthly household income, thereby possessing relatively small capital investments suitable for online P2P lending. Methodology: Drawing on the technology acceptance model (TAM), this research developed and tested the relevant hypotheses with data collected from 216 respondents. The partial least square structural equation modelling (PLS-SEM) technique was employed to analyse the collected data. Contribution: This study contributes to the body of knowledge on financial inclusion by demonstrating the relevance of modified TAM in explaining the intention to invest in online P2P lending platforms among investors with lower disposable income (i.e., the B40 group in Malaysia). Findings: The findings revealed that information quality, perceived risk, and perceived ease of use are relevant to B40 investment intention in P2P online lending platforms. However, contrary to expectations, trust and financial literacy are insignificant predictors of B40 investment intention. Recommendations for Practitioners: The P2P lending platform operators could enhance financial inclusion among the B40 group by ensuring borrowers provide sufficient, relevant, and reliable information with adequate security measures to minimise risk exposure. The financial regulators should also conduct periodic audits to ensure that the operators commit to enhancing information quality, platform security, and usability. Recommendation for Researchers: The intention to invest in online P2P lending platforms among the B40 group could be enhanced by improving information quality and user experience, addressing perceived risks, reassessing trust-building strategies and financial literacy initiatives, and adopting holistic, interdisciplinary approaches. These findings suggest targeted strategies to enhance financial inclusion and investment participation among B40 investors. Impact on Society: The study’s findings hold significant implications for financial regulators and institutions, such as the Securities Commission Malaysia, Bank Negara Malaysia, commercial and investment banks, and insurance companies. By focusing on these key determinants, policymakers can design targeted interventions to improve the accessibility and attractiveness of P2P lending platforms for B40 investors. Enhanced information quality and ease of use can be mandated through regulatory frameworks, while effective risk communication and mitigation strategies can be developed to build investor confidence. These measures can collectively promote financial growth and inclusion, supporting broader economic development goals. Future Research: Future research could expand the sample size to consider older B40 individuals across different countries and use a longitudinal survey to assess the actual investment decision of the B40 investors.

Aim/Purpose: This research aims to design a website-based group decision support system (DSS) user interface to support an integrated and sustainable waste management plan in Jagatera. The main focus of this research is to design a group DSS to help Jagatera prioritize several waste alternatives to be managed so that Jagatera can make the right decisions to serve the community. Background: The Indonesian government and various stakeholders are trying to solve the waste problem. Jagatera, as a waste recycling company, plays a role as a stakeholder in managing waste. In 2024, Jagatera plans to accept all waste types, which impacts the possibility of increasing waste management costs. If Jagatera does not have a waste management plan, this will impact reducing waste management services in the community. To solve this problem, the group DSS assists Jagatera in prioritizing waste based on aspects of waste management cost. Methodology: Jagatera, an Indonesian waste recycling company, is implementing a group DSS using the soft system methodology (SSM) method. The SSM process involves seven stages, including problem identification, problem explanation using rich pictures, system design, conceptual model design, real-life comparison, changes, and improvement steps. The final result is a prototype user interface design addressing the relationship between actors and the group DSS. The analytical hierarchy process (AHP) method prioritized waste based on management costs. This research obtained primary data from interviews with Jagatera management, a literature review regarding the group DSS, and questionnaires to determine the type of waste and evaluate user interface design. Contribution: This research focuses on determining waste handling priorities based on their management. It contributes the DSS, which uses a decision-making approach based on management groups developed using the SSM and AHP methods focused on waste management decisions. It also contributes to the availability of a user interface design from the DSS group that explains the interactions between actors. The implications of the availability of DSS groups in waste recycling companies can help management understand waste prioritization problems in a structured manner, increase decision-making efficiency, and impact better-quality waste management. Combining qualitative approaches from SSM to comprehend issues from different actor perspectives and AHP to assist quantitative methods in prioritizing decisions can yield theoretical implications when using the SSM and AHP methods together. Findings: This research produces a website-based group DSS user interface design that can facilitate decision-making using AHP techniques. The user interface design from the DSS group was developed using the SSM approach to identify complex problems at waste recycling companies in Indonesia. This study also evaluated the group DSS user interface design, which resulted in a score of 91.67%. This value means that the user interface design has met user expectations, which include functional, appearance, and comfort needs. These results also show that group DSS can enhance waste recycling companies’ decision-making process. The results of the AHP technique using all waste process information show that furniture waste, according to the CEO, is given more priority, and textile waste, according to the Managing Director. Group DSS developed using the AHP method allows user actors to provide decisions based on their perspectives and authority. Recommendations for Practitioners: This research shows that the availability of a group DSS is one of the digital transformation efforts that waste recycling companies can carry out to support the determination of a sustainable waste management plan. Managers benefit from DSS groups by providing a digital decision-making process to determine which types of waste should be prioritized based on management costs. Timely and complete information in the group DSS is helpful in the decision-making process and increases organizational knowledge based on the chosen strategy. Recommendation for Researchers: Developing a group DSS for waste recycling companies can encourage strategic decision-making processes. This research integrates SSM and AHP to support a comprehensive group DSS because SSM encourages a deeper and more detailed understanding of waste recycling companies with complex problems. At the same time, AHP provides a structured approach for recycling companies to make decisions. The group DSS that will be developed can be used to identify other more relevant criteria, such as environmental impact, waste management regulations, and technological capabilities. Apart from more varied criteria, the group DSS can be encouraged to provide various alternatives such as waste paper, metal, or glass. In addition to evaluating the group DSS’s user interface design, waste recycling companies need to consider training or support for users to increase system adoption. Impact on Society: The waste problem requires the role of various stakeholders, one of which is a waste recycling company. The availability of a group DSS design can guide waste recycling companies in providing efficient and effective services so that they can respond more quickly to the waste management needs of the community. The community also gets transparent information regarding their waste management. The impact of good group DSS is reducing the amount of waste in society. Future Research: Future research could identify various other types of waste used as alternatives in the decision-making process to illustrate the complexity of the prioritization process. Future research could also identify other criteria, such as environmental impact, social aspects of community involvement, or policy compliance. Future research could involve decision-makers from other parties, such as the government, who play an essential role in the waste industry.

Aim/Purpose: This research aims to develop a smart agricultural knowledge management framework to empower emergent farmers and extension officers (advisors to farmers) in developing countries as part of a smart farming lab (SFL). The framework utilizes knowledge objects (KOs) to capture information and knowledge of different forms, including indigenous knowledge. It builds upon a foundation of established agricultural knowledge management (AKM) models and serves as the cornerstone for an envisioned SFL. This framework facilitates optimal decision support by fostering linkages between these KOs and relevant organizations, knowledge holders, and knowledge seekers within the SFL environment. Background: Emergent farmers and extension officers encounter numerous obstacles in their knowledge operations and decision-making. This includes limited access to agricultural information and difficulties in applying it effectively. Many lack reliable sources of support, and even when information is available, understanding and applying it to specific situations can be challenging. Additionally, extension offices struggle with operational decisions and knowledge management due to agricultural organizations operating isolated in silos, hindering their access to necessary knowledge. This research introduces an SFL with a proposed AKM process model aimed at transforming emergent farmers into smart, innovative entities by addressing these challenges. Methodology: This study is presented as a theory-concept paper and utilizes a literature review to evaluate and synthesize three distinct AKM models using several approaches. The results of the analysis are used to design a new AKM process model. Contribution: This research culminates in a new AKM process framework that incorporates the strengths of various existing AKM models and supports emergent farmers and extension officers to become smart, innovative entities. One main difference between the three models analyzed, and the one proposed in this research, is the deployment and use of knowledge assets in the form of KOs. The proposed framework also incorporates metadata and annotations to enhance knowledge discoverability and enable AI-powered applications to leverage captured knowledge effectively. In practical terms, it contributes by further motivating the use of KOs to enable the transfer and the capturing of organizational knowledge. Findings: A model for an SFL that incorporates the proposed agricultural knowledge management framework is presented. This model is part of a larger knowledge factory (KF). It includes feedback loops, KOs, and mechanisms to facilitate intelligent decision-making. The significance of fostering interconnected communities is emphasized through the creation of linkages. These communities consist of knowledge seekers and bearers, with information disseminated through social media and other communication integration platforms. Recommendations for Practitioners: Practitioners and other scholars should consider implementing the proposed AKM process model as part of a larger SFL to support emergent farmers and extension officers in making operational decisions and applying knowledge management strategies. Recommendation for Researchers: The AKM process model is only presented in conceptual form. Therefore, researchers can practically test and assess the new framework in an agricultural setting. They can also further explore the potential of social media integration platforms to connect knowledge seekers with knowledge holders. Impact on Society: The proposed AKM process model has the potential to support emergent farmers and extension officers in becoming smart, innovative entities, leading to improved agricultural practices and potentially contributing to food security. Future Research: This paper discusses the AKM process model in an agrarian setting, but it can also be applied in other domains, such as education and the healthcare sector. Future research can evaluate the model’s effectiveness and explore and further investigate the semantic web and social media integration.

There is a need to emphasise and educate future business leaders on emerging technologies' disruptive and transformative impact on business processes. Allen (2020) suggests the need for a digital mindset and tech literacy in business management education. In our study, we define cyber literacy and cyber ethical mindset emphasising the importance of informing future leaders in business schools about the ethical dilemmas arising while using these emerging technologies. Additionally, we highlight various ethical pitfalls of using technologies enabling disruption (TED). Further, we contribute to the understanding of cyber literacy, cyber ethics and business ethics, how to incorporate cyber ethics into the management curriculum, and why there is a need to integrate cyber ethics into management education.

This study examined a professional development program designed to support Civics teachers in their efforts to promote empathy among Israeli Jewish students towards Israeli Arabs. The design rationale for the program is that teachers should experience empathic processes themselves before supporting their students in such an endeavor and that meaningful empathic processes can occur online if activities are properly designed. All phases of the program were designed to support teachers to participate as part of an online community of practice. Sixty Jewish teachers participated in two iterations of the design study. Refinements were made in the second iteration to provide teachers with explicit definitions of empathy and specific instructions for reflection. Findings indicate that these changes were reflected in higher degrees of empathic responses among teachers. Teachers also indicated that being a part of an online learning community contributed to the learning process they experienced during the program. We interpret this as a first step in enabling teachers to assist their students to develop a more empathetic approach toward the minority group and conclude with a discussion of recommended design principles for promoting such an approach.

This is a five-year study conducted with junior high school students studying in a 1:1-laptop program in order to test the effects of the program on various measures related to the students: their attitudes, motivation, perceived school norms, self-efficacy, and behavioral intention towards learning with laptops, according to the Theory of Planned Behavior (TPB). These variables were tested at two dimensions: ‘duration of learning’ – the effect of learning in the program on the same students; ‘duration of program in school’ – the effect of the program on different students in different school years. Participants (N=770) answered a questionnaire structured according to motivational and TPB variables. Findings show that attitudes changed over time, but differently for each dimension. For the ‘duration of learning’, attitudes declined between 7th to 9th grade. Structural equation modeling analysis showed that students’ attitudes and self-efficacy explain part of their intention to learn with laptops, therefore ways of maintaining positive attitudes, self-efficacy, and strengthening school norms should be considered. However, for the ‘duration of program in school’, students’ attitudes increased over the years: The attitudes of students who started the program at a later stage were more positive than those who began earlier. This may indicate that students who experience the program at an advanced stage are better prepared, with more realistic expectations. Findings can assist teacher trainers and policymakers with the implementation of similar programs.