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: In the United States, the Centers for Disease Control and Prevention (CDC) tracks the disease activity using data collected from medical practice's on a weekly basis. Collection of data by CDC from medical practices on a weekly basis leads to a lag time of approximately 2 weeks before any viable action can be planned. The 2-week delay problem was addressed in the study by creating machine learning models to predict flu outbreak. Background: The 2-week delay problem was addressed in the study by correlation of the flu trends identified from Twitter data and official flu data from the Centers for Disease Control and Prevention (CDC) in combination with creating a machine learning model using both data sources to predict flu outbreak. Methodology: A quantitative correlational study was performed using a quasi-experimental design. Flu trends from the CDC portal and tweets with mention of flu and influenza from the state of Georgia were used over a period of 22 weeks from December 29, 2019 to May 30, 2020 for this study. Contribution: This research contributed to the body of knowledge by using a simple bag-of-word method for sentiment analysis followed by the combination of CDC and Twitter data to generate a flu prediction model with higher accuracy than using CDC data only. Findings: The study found that (a) there is no correlation between official flu data from CDC and tweets with mention of flu and (b) there is an improvement in the performance of a flu forecasting model based on a machine learning algorithm using both official flu data from CDC and tweets with mention of flu. Recommendations for Practitioners: In this study, it was found that there was no correlation between the official flu data from the CDC and the count of tweets with mention of flu, which is why tweets alone should be used with caution to predict a flu out-break. Based on the findings of this study, social media data can be used as an additional variable to improve the accuracy of flu prediction models. It is also found that fourth order polynomial and support vector regression models offered the best accuracy of flu prediction models. Recommendations for Researchers: Open-source data, such as Twitter feed, can be mined for useful intelligence benefiting society. Machine learning-based prediction models can be improved by adding open-source data to the primary data set. Impact on Society: Key implication of this study for practitioners in the field were to use social media postings to identify neighborhoods and geographic locations affected by seasonal outbreak, such as influenza, which would help reduce the spread of the disease and ultimately lead to containment. Based on the findings of this study, social media data will help health authorities in detecting seasonal outbreaks earlier than just using official CDC channels of disease and illness reporting from physicians and labs thus, empowering health officials to plan their responses swiftly and allocate their resources optimally for the most affected areas. Future Research: A future researcher could use more complex deep learning algorithms, such as Artificial Neural Networks and Recurrent Neural Networks, to evaluate the accuracy of flu outbreak prediction models as compared to the regression models used in this study. A future researcher could apply other sentiment analysis techniques, such as natural language processing and deep learning techniques, to identify context-sensitive emotion, concept extraction, and sarcasm detection for the identification of self-reporting flu tweets. A future researcher could expand the scope by continuously collecting tweets on a public cloud and applying big data applications, such as Hadoop and MapReduce, to perform predictions using several months of historical data or even years for a larger geographical area.

According to the different behavior characteristics of knowledge contribution of enterprise employees, a multi-task principal-agent relationship of knowledge contribution between enterprise and employees is established based on principal-agent theory, analyzing staff’s knowledge contribution behavior of knowledge creation and knowledge participation. Based on this, a multi-task principal agent model for knowledge contribution of enterprise staff is developed to formulate the asymmetry of information in knowledge contribution Then, a set of incentive measures are derived from the theoretic model, aiming to prompt the knowledge contribution in enterprise. The result shows that staff’s knowledge creation behavior and positive participation behavior can influence and further promote each other Enterprise should set up respective target levels of both knowledge creation contribution and knowledge participation contribution and make them irreplaceable to each other. This work contributes primarily to the development of the literature on knowledge management and principal-agent theory. In addition, the applicability of the findings will be improved by further empirical analysis.

Aim/Purpose: A vital business activity within socio-technical enterprises is tacit knowledge externalization, which elicits and explicates tacit knowledge of enterprise employees as external knowledge. The aim of this paper is to integrate diverse aspects of externalization through the Enterprise Ontology model. Background: Across two decades, researchers have explored various aspects of tacit knowledge externalization. However, from the existing works, it is revealed that there is no uniform representation of the externalization process, which has resulted in divergent and contradictory interpretations across the literature. Methodology : The Enterprise Ontology model is constructed step-wise through the conceptual and measurement views. While the conceptual view encompasses three patterns that model the externalization process, the measurement view employs certainty-factor model to empirically measure the outcome of the externalization process. Contribution: The paper contributes towards knowledge management literature in two ways. The first contribution is the Enterprise Ontology model that integrates diverse aspects of externalization. The second contribution is a Web application that validates the model through a case study in banking. Findings: The findings show that the Enterprise Ontology model and the patterns are pragmatic in externalizing the tacit knowledge of experts in a problem-solving scenario within a banking enterprise. Recommendations for Practitioners : Consider the diverse aspects (what, where, when, why, and how) during the tacit knowledge externalization process. Future Research: To extend the Enterprise Ontology model to include externalization from partially automated enterprise systems.

Aim/Purpose: This study aimed to examine the relationships among compatibility, relative advantage, complexity, IT Infrastructure, security, top Management Support, financial Support, information Policies, employee engagement, customer pressure, competitive pressure, information integrity, information sharing, attitude toward adopting technology factors, and CRM adoption Background: Customer relationship management (CRM) refers to the use of the process, information, technology, and people for the management of the interactions between the organization and its customers. Therefore, there is a need for SMEs to implement CRM practices in their businesses for competitive advantage. However, in developing nations, the adoption rate of such practices remains low. This low rate may be attributed to the lack of important factors that guide CRM adoption, and as such, the present study attempts to investigate the factors affecting CRM adoption in Palestinian SMEs. This paper used the Diffusion of Innovation Theory (DOI), Resource-Based View (RBV), and Technology, Organization, and Environment Framework (TOE) framework to identify the determinant factors from the technological, organizational, environmental, and information culture perspectives. Methodology: This study uses a quantitative approach to investigate the relationships between the variables. A questionnaire was designed to collect data from 420 SMEs in Palestine. 331respondents completed and returned the survey. The Partial Least Square-Structural Equation Model (PLS-SEM) approach was used to assess both the measurement and structural models. Contribution: This study contributes to both theory and practitioners by providing insights into factors that affect CRM adoption in Palestinian SMEs, which did not explore before. Future research suggestions are also provided. Findings: The results of the study prove that the adoption of CRM depends on compatibility (CMP), security (SEC), top management support (TMS), information policies (INP), financial resources (FR), employee engagement (EEN), competitive pressure (COP), customers pressure (CUP), attitude toward adopting technology (ATA), information integrity (INI), and information sharing (INS). Surprisingly, complexity (CMX), IT infrastructure (ITI), and relative advantage (RLA) do not play any role in CRM adoption in Palestine. Recommendations for Practitioners: This study provides practitioners with the important factors for CRM adoption upon its successful implementation in the context of Palestinian SMEs. Recommendation for Researchers: Our findings may be used to conduct further studies about compatibility, security, top management support, information policies, financial resources, employee engagement, competitive pressure, customers pressure, attitude toward adopting technology, information integrity, information sharing factors, and CRM adoption by using different countries, procedure, and context. Impact on Society: The proposed framework provides insights for SMEs which have significant effects for research and practice to help facilitate the adoption of CRM Future Research: The findings may also be compared to other studies conducted in different contexts and provide deeper insights into the influence of the examined contexts on the employees’ intention toward CRM adoption in banking and universities. It would be fruitful to test whether the results hold true in developed and developing countries.

Aim/Purpose: This paper aims to discuss the activities involved in facilitating self-selecting teams for Agile software development projects. This paper also discussed how these activities can influence the successful expertise coordination in Agile teams. Background: Self-selecting teams enable Agile team members to choose teams based on whom they prefer to work with. Good team bonding allows Agile team members to rely on each other in coordinating their expertise resources effectively. This is the focal point where expertise coordination is needed in Agile teams. Methodology: This study employed Grounded Theory by interviewing 48 Agile practitioners from different software organizations mainly based in New Zealand. This study also carried out several sessions of observations and document analysis in conjunction with interviews. Contribution: This study contributes to the body of knowledge by identifying the way self-selecting teams support expertise coordination. Findings: Our findings indicated that the activities involved tend to influence the successful expertise coordination in Agile teams. Self-selecting teams are essential to supporting expertise coordination by increasing inter-dependencies between Agile team members, ensuring a diverse range of knowledge and skills in teams. Recommendations for Practitioners: The self-selecting team activities can be used as a guideline for Agile software organizations in forming self-selecting teams in the fastest and most efficient way. It is vital for management to facilitate the process of self-selecting teams in order to optimize successful expertise coordination. Recommendation for Researchers: There is potential for further Grounded Theory research to explore more activities and strategies involved in self-selecting teams. Impact on Society: Self-selecting teams in Agile software developments projects tend to boost the productivity of software development. Future Research: Several hypotheses can be tested through a deductive approach in future studies.

Aim/Purpose: Drawing on theories of organizational learning, this study analyzes the mechanism of Internet integration capability affecting knowledge generation by 399 Chinese enterprises. This paper will further explore whether there is a moderating role of learning orientation in the mechanism of Internet integration capability affecting enterprise knowledge generation. Background: The Internet has gradually integrated into the enterprise innovation system and penetrated into all aspects of technological innovation, which has promoted the integration and optimization of resources inside and outside the organization. However, there is limited understanding of how the combination of the Internet and integration capability can drive enterprise knowledge generation. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet integration capability, organizational learning, knowledge generation, and uses PROCESS macro program to test the mediated moderation effect of learning orientation. Contribution: First, this study provides empirical evidence for managers to better build Internet integration capability and ambidextrous learning to promote enterprise knowledge generation. Second, this study highlights the important moderating role of learning orientation in the mediating role of ambidextrous learning. Findings: First, the study confirms the mediating role of exploratory learning and exploitative learning in knowledge generation driven by Internet integration capability. Second, the results show that when organizations have a strong learning orientation, the indirect path of Internet integration capability influencing knowledge generation through exploratory learning will be enhanced. Recommendations for Practitioners: Enterprises should pay full attention to the improvement of internet integration capability and ambidextrous learning to promote knowledge generation. In addition, enterprises should establish a good learning atmosphere within the organization to strengthen the bridge role of exploratory learning between Internet integration capability and knowledge generation. Recommendation for Researchers: Researchers could collect data from countries with different levels of economic development to verify the universal applicability of the proposed theoretical model. Impact on Society: This study provides references for enterprises using Internet integration capability to promote their knowledge generation capability under the internet background. Future Research: Future research can compare the impact of Internet integration capability on knowledge generation in different industries.

Aim/Purpose: The aim of this study is to identify Critical Success Factors (CSF) of Business Intelligence (BI) and provide a framework to classify CSF into layers or perspectives using an enterprise architecture approach, then rank CSF within each perspective and evaluate the importance of each perspective at different BI maturity levels as well. Background: Although the implementation of the BI project has a significant impact on creating analytical and competitive capabilities, the lack of evaluation of CSF holistically is still a challenge. Moreover, the BI maturity level of the organization has not been considered in the BI implementation project. Identifying BI critical success factors and their importance can help the project team to move to a higher maturity level in the organization. Methodology: First, a list of distinct CSF is identified through a literature review. Second, a framework is provided for categorizing these CSF using enterprise architecture. Interviewing is the research method used to evaluate the importance of CSF and framework layers with two questionnaires among experts. The first questionnaire was done by Analytical Hierarchy Process (AHP), a quantitative method of decision-making to calculate the weight of the CSF according to the importance of CSF in each of the framework layers. The second one was conducted to evaluate framework layers at different BI maturity levels using a Likert scale. Contribution: This paper contributes to the implementation of BI projects by identifying a comprehensive list of CSF in the form of a holistic multi-layered framework and ranking the importance of CSF and layers at BI maturity levels. Findings: The most important CSF in BI implementation projects include senior management support, process identification, data quality, analytics quality, hardware quality, security standards, scope management, documentation, project team skills, and customer needs transformation, which received the highest scores in framework layers. In addition, it was observed that as the organization moves to higher levels of maturity, the average importance of strategic business and security perspectives or layers increases. But the average importance of data, applications, infrastructure, and network, the project management layers in the proposed framework is the same regardless of the level of business intelligence maturity. Recommendations for Practitioners: The results of this paper can be used by academicians and practitioners to improve BI project implementation through understanding a comprehensive list of CSF and their importance. This awareness causes us to focus on the most important CSF and have better planning to reach higher levels of maturity according to the maturity level of the organization. Future Research: For future research, the interaction of critical success factors of business intelligence and framework layers can be examined with different methods.

Aim/Purpose: The understanding of disease spread dynamics in the context of air travel is crucial for effective disease detection and epidemic intelligence. The Susceptible-Exposed-Infectious-Recovered-Hospitalized-Critical-Deaths (SEIR-HCD) model proposed in this research work is identified as a valuable tool for capturing the complex dynamics of disease transmission, healthcare demands, and mortality rates during epidemics. Background: The spread of viral diseases is a major problem for public health services all over the world. Understanding how diseases spread is important in order to take the right steps to stop them. In epidemiology, the SIS, SIR, and SEIR models have been used to mimic and study how diseases spread in groups of people. Methodology: This research focuses on the integration of air traffic network data into the SEIR-HCD model to enhance the understanding of disease spread in air travel settings. By incorporating air traffic data, the model considers the role of travel patterns and connectivity in disease dissemination, enabling the identification of high-risk routes, airports, and regions. Contribution: This research contributes to the field of epidemiology by enhancing our understanding of disease spread dynamics through the application of the SIS, SIR, and SEIR-HCD models. The findings provide insights into the factors influencing disease transmission, allowing for the development of effective strategies for disease control and prevention. Findings: The interplay between local outbreaks and global disease dissemination through air travel is empirically explored. The model can be further used for the evaluation of the effectiveness of surveillance and early detection measures at airports and transportation hubs. The proposed research contributes to proactive and evidence-based strategies for disease prevention and control, offering insights into the impact of air travel on disease transmission and supporting public health interventions in air traffic networks. Recommendations for Practitioners: Government intervention can be studied during difficult times which plays as a moderating variable that can enhance or hinder the efficacy of epidemic intelligence efforts within air traffic networks. Expert collaboration from various fields, including epidemiology, aviation, data science, and public health with an interdisciplinary approach can provide a more comprehensive understanding of the disease spread dynamics in air traffic networks. Recommendation for Researchers: Researchers can collaborate with international health organizations and authorities to share their research findings and contribute to a global understanding of disease spread in air traffic networks. Impact on Society: This research has significant implications for society. By providing a deeper understanding of disease spread dynamics, it enables policymakers, public health officials, and practitioners to make informed decisions to mitigate disease outbreaks. The recommendations derived from this research can aid in the development of effective strategies to control and prevent the spread of infectious diseases, ultimately leading to improved public health outcomes and reduced societal disruptions. Future Research: Practitioners of the research can contribute more effectively to disease outbreaks within the context of air traffic networks, ultimately helping to protect public health and global travel. By considering air traffic patterns, the SEIR-HCD model contributes to more accurate modeling and prediction of disease outbreaks, aiding in the development of proactive and evidence-based strategies to manage and mitigate the impact of infectious diseases in the context of air travel.

Aim/Purpose: This study identifies the scale types and measurement units used in the measurement of enterprise architecture (EA) and analyzes the admissibility of the mathematical operations used. Background: The majority of measurement solutions proposed in the EA literature are based on researchers’ opinions and many with limited empirical validation and weak metrological properties. This means that the results generated by these solutions may not be reliable, trustworthy, or comparable, and may even lead to wrong investment decisions. While the literature proposes a number of EA measurement solutions, the designs of the mathematical operations used to measure EA have not yet been independently analyzed. It is imperative that the EA community works towards developing robust, reliable, and widely accepted measurement solutions. Only then can senior management make informed decisions about the allocation of resources for EA initiatives and ensure that their investment yields optimal results. Methodology: In previous research, we identified, through a systematic literature review, the EA measurement solutions proposed in the literature and classified them by EA entity types. In a subsequent study, we evaluated their metrology coverage from both a theoretical and empirical perspective. The metrology coverage was designed using a combination of the evaluation theory, best practices from the software measurement literature including the measurement context model, and representational theory of measurement to evaluate whether EA measurement solutions satisfy the metrology criteria. The research study reported here presents a more in-depth analysis of the mathematical operations within the proposed EA measurement solutions, and for each EA entity type, each mathematical operation used to measure EA was examined in terms of the scale types and measurement units of the inputs, their transformations through mathematical operations, the impact in terms of scale types, and measurement units of the proposed outputs. Contribution: This study adds to the body of knowledge on EA measurement by offering a metrology-based approach to analyze and design better EA measurement solutions that satisfy the validity of scale type transformations in mathematical operations and the use of explicit measurement units to allow measurement consistency for their usage in decision-making models. Findings: The findings from this study reveal that some important metrology and quantification issues have been overlooked in the design of EA measurement solutions proposed in the literature: a number of proposed EA mathematical operations produce numbers with unknown units and scale types, often the result of an aggregation of undetermined assumptions rather than explicit quantitative knowledge. The significance of such aggregation is uncertain, leading to numbers that have suffered information loss and lack clear meaning. It is also unclear if it is appropriate to add or multiply these numbers together. Such EA numbers are deemed to have low metrological quality and could potentially lead to incorrect decisions with serious and costly consequences. Recommendations for Practitioners: The results of the study provide valuable insights for professionals in the field of EA. Identifying the metrology limitations and weaknesses of existing EA measurement solutions may indicate, for instance, that practitioners should wait before using them until their design has been strengthened. In addition, practitioners can make informed choices and select solutions with a more robust metrology design. This, in turn, will benefit enterprise architects, software engineers, and other EA professionals in decision making, by enabling them to take into consideration factors more adequately such as cost, quality, risk, and value when assessing EA features. The study’s findings thus contribute to the development of more reliable and effective EA measurement solutions. Recommendation for Researchers: Researchers can use with greater confidence the EA measurement solutions with admissible mathematical operations and measurement units to develop new decision-making models. Other researchers can carry on research to address the weaknesses identified in this study and propose improved ones. Impact on Society: Developers, architects, and managers may be making inappropriate decisions based on seriously flawed EA measurement solutions proposed in the literature and providing undue confidence and a waste of resources when based on bad measurement design. Better quantitative tools will ultimately lead to better decision making in the EA domain, as in domains with a long history of rigor in the design of the measurement tools. Such advancements will benefit enterprise architects, software engineers, and other practitioners, by providing them with more meaningful measurements for informed decision making. Future Research: While the analysis described in this study has been explicitly applied to evaluating EA measurement solutions, researchers and practitioners in other domains can also examine measurement solutions proposed in their respective domains and design new ones.

DSSP stands as a foundational tool in the domain of protein secondary structure prediction, yet it encounters notable challenges in accurately annotating irregular structures, such as β-turns and γ-turns, which constitute approximately 25%-30% and 10%-15% of protein turns, respectively. This limitation arises from DSSP's reliance on hydrogen-bond analysis, resulting in annotation gaps and reduced consensus on irregular structures. Alternatively, PROMOTIF excels at identifying these irregular structure annotations using phi-psi information. Despite their complementary strengths, previous methodologies utilised DSSP and PROMOTIF separately, leading to disparate prediction methods for protein secondary structures, hampering comprehensive structure analysis crucial for drug development. In this work, we bridge this gap using an annotation fusion approach, combining DSSP structures with beta, and gamma turns. We introduce IRNN-SS, a model employing deep inception and bidirectional gated recurrent neural networks, achieving 77.4% prediction accuracy on benchmark datasets, outpacing current models.

Alzheimer's disease (AD), a leading cause of dementia and mortality, presents a growing concern due to its irreversible progression and the rising costs of care. Early detection is crucial for managing AD, which begins with memory deterioration caused by the damage to neurons involved in cognitive functions. Although incurable, treatments can manage its symptoms. This study introduces a hybrid AlexNet+ResNet-50 model for AD diagnosis, utilising a pre-trained convolutional neural network (CNN) through transfer learning to analyse MRI scans. This method classifies MRI images into Alzheimer's disease (AD), moderate cognitive impairment (MCI), and normal control (NC), enhancing model efficiency without starting from scratch. Incorporating transfer learning allows for refining the CNN to categorise these conditions accurately. Our previous work also explored atlas-based segmentation combined with a U-Net model for segmentation, further supporting our findings. The hybrid model demonstrates superior performance, achieving 94.21% accuracy in identifying AD cases, indicating its potential as a highly effective tool for early AD diagnosis and contributing to efforts in managing the disease's impact.

Epidemiologists recommended contact-tracing as an effective control measure for the global infection like COVID-19 pandemic. Despite its effectiveness in infection containment, it has many limitations such as labour-intensive process, prone to human errors and most importantly, user privacy concerns. To address these shortcomings, we proposed location-aware blockchain-based hierarchical contact-tracing framework for anonymised data collection and processing. This infectious disease control framework serves both the infected users with localised alerts as well as stakeholders such as city officials and health workers with health statistics. Our proposed solution uses hierarchical network design that offloads individual infection block data to create hospital and city-level 'chains' for generating macro-level infection statistics. Results demonstrate that our system can represent the dynamic complexities of contract tracing in highly infection situations. Overall, our design emphasises on data processing and verification mechanism for large volume of infection data over a significant period of time for active risk assessment.

Aim/Purpose: The research work investigated the information seeking process of undergraduates in a specialised university in Nigeria, in the course of a group assignment. Background: Kuhlthau’s Information Search Process (ISP) model is used as lens to reveal how students interact with information in the affective, cognitive and physical realms. Methodology: Qualitative research methods were employed. The entire seventy-seven third year students in the Department of Petroleum and Natural Gas and their course lecturer were the participants. Group assignment question was analysed using Bloom’s Taxonomy while the information seeking process of the students was garnered through dialogue journaling on WhatsApp Messenger. Contribution: The research explicates how students’ information seeking behaviour can be captured beyond the four walls of a classroom by using a Web 2.0 tool such as WhatsApp Messenger. Findings: The apparent level of uncertainty, optimism, and confusion/doubt common in the initiation, selection, and exploration phases of the ISP model and low confidence levels were not markedly evident in the students. Consequently, Kuhlthau’s ISP model could not be applied in its entirety to the study’s particular context of teaching and learning due to the nature of the assignment. Recommendations for Practitioners: The study recommends that the Academic Planning Unit (APU) should set a benchmark for all faculties and, by extension, the departments in terms of the type/scope and number of assignments per semester, including learning outcomes. Recommendation for Researchers: Where elements of a guided approach to learning are missing, Kuhlthau’s ISP may not be employed. Therefore, alternative theory, such as Theory of Change could explain the poor quality of education and the type of intervention that could enhance students’ learning. Impact on Society: The ability to use emerging technologies is a form of literacy that is required by the 21st century work place. Hence, the study demonstrates students’ adaptation to emerging technology. Future Research: The study is limited to only one case site. It would be more helpful to the Nigerian society to have this study extended to other universities for the purpose of generalisation and appropriate intervention.

Aim/Purpose: To understand the process of social change creation in social entrepreneurial ventures (SEVs), specifically emphasizing the role and nature of the communicative process in social change creation. Background: Drawing on data from seven SEVs from India and the US and employing a grounded theory methodology, this research scrutinizes the social change process and uncovers the role and characteristics of dialogue in this process. Methodology: Qualitative data was collected from seven social entrepreneurial organizations over a period of eight months from July 2011 to February 2012. Semi-structured interviews were conducted with a wide range of members within these social entrepreneurial organizations (n=27) with additional informal interviews with field workers and volunteers. Data from the semi-structured interviews and notes from observations were integrated with analyses of archival resources. Contribution: There is little scholarship about the process of social change creation and the necessary conditions to promote social change over time. Understanding the process of social change creation and the individual, interpersonal, and organizational conditions that facilitate the process is central to design of effective trans-sector TD problem solving ventures. This paper focuses on the process of social change creation in social entrepreneurial settings, specifically emphasizing the role and nature of the communicative process in social change creation. Findings: The reflections and experiences of the members of SEVs revealed that social entrepreneurship is a collective endeavor and this collective character is essential to its success. Collective organization and synergy, deep intra-organizational communication, and a conducive organizational context are critical for the creation of collective wisdom and knowledge networks for long-term collaborative community capacity building. Dialogue emerged as a central category linking the other categories to explain the process of social change creation. Organic organizational structure enables knowledge creation and integration through the process of organizational learning through deep and continuous social interaction, or dialogue. Recommendations for Practitioners: This research elucidated the key characteristics of the organizational context required to support the creation of social change. It also identified the critical role and characteristics of the communicative process required to generate structural knowledge and collective wisdom at the organizational level. Recommendation for Researchers: For individual and organizational learning, trans-sector transdisciplinary organizations require an appropriate organizational context. Key elements of such an organizational context include (1) understanding the ecology of the social problem; (2) organic organizational structure; (3) continuous and deep social interaction among all levels of the organization; (4) employee and community autonomy and empowerment; and (5) attention to subtle environmental changes in the system. These elements in combination lead to the creation of collective wisdom. Collective wisdom then feeds back into the conception, planning, and action stages of the iterative cycle of organizational knowledge creation to create positive social change. Impact on Society: Same as above Future Research: Future research model theoretically and study empirically the ecology of social entrepreneurship and trans-sector TD problem solving more broadly. For example, the ways in the personal attributes of social entrepreneurs (e.g., their leadership style, networking abilities) combine with circumstances at organizational, institutional, and international levels to influence the effectiveness of their efforts to promote positive social change within local and global communities. Second, the grounded theoretical framework developed here should be further refined and elaborated through the identification of additional key contextual factors that affect SEVs’ capacity to promote positive social change and to achieve sustainability in different socio-environmental contexts. There is also a need to translate the findings from this research to facilitate the creation of more inclusive problem solving contexts and practices.

Aim/Purpose: This paper examines the impact of the transformational, servant, and paternalistic leadership styles on employee performance at the middle and senior levels. Background: Transdisciplinary research promotes the integration and development of various sciences. It provides more choices for leaders to adopt ways and practical activities to promote enterprise development. Complexity leadership theory emphasizes that effectively functioning organizations need distinct forms of leadership to work together. Leaders rely on different leadership practices in an emergent collaborative context, and finding an optimal balance is challenging. Many scholars have attempted to explore which leadership styles have a more significant impact on employees by distinguishing and defining types of leadership styles and explaining the process by which they influence employee behavior and performance. Various scholars have further explored and empirically demonstrated the impact of these three types of leadership styles (transformational, servant, paternalistic)on employee performance. While transformational and servant leadership have their roots in the West, paternalistic leadership has roots in China. Few scholars have conducted comparative studies on their positive impact on employee performance. How do these three leadership styles affect employee performance at the middle and senior levels in the Chinese context? Which combination of middle and senior leadership styles performs best? These are the second area that this paper will attempt to explore. Methodology: This study constructs a three-tier model at the senior, middle, and grassroots levels. A questionnaire survey was used to collect data. SPSS 22.0 and Amos were used for data analysis. Contribution: Through its construction of a three-tier model (senior, middle, and grassroots levels), the paper explores the combined effect of three leadership styles (transformational, servant, and paternalistic) on grassroots employees. It explores the impact of senior leaders across levels on grassroots employee performance, which is expected to provide a valuable addition to theories on leadership styles. It is also instructive to examine which leadership style performs better and what middle and senior leadership configurations are more conducive to driving beneficial employee behavior and, ultimately, corporate growth. Findings: The transformational, servant, and paternalistic leadership styles, both at the top and middle levels, have a significant positive relationship with employee performance; the middle leadership style plays a positive mediating role between the top leadership style and employee performance. In terms of impact on employee performance, transformational leadership shows the best results at both the top and middle levels, with paternalistic leadership second and servant leadership at the same level. Regarding which middle and senior leadership style pairing is the best, the sample is relatively small, and the gap between various pairing combinations is not evident from the data. If the sample size is enlarged, the coefficient will likely expand year-on-year. Therefore, we can assume that the pairing effect of top servant leadership and middle transformational leadership is the best, top paternalistic leadership and middle transformational leadership is the second-best, and the combination of top paternalistic leadership and middle-level servant leadership leaders is the weakest. Recommendation for Researchers: This paper extends the study of top and middle leadership’s combined effect on employee performance as a positive response to the call for multi-layer or cross-layer analysis in leadership research. The findings further enrich the literature on leadership style-related theories. The middle leadership style plays a positive mediating role between the top leadership style and employee performance. The trickle-down effect is further verified, i.e., the top leadership will have a permeating influence on employees through the middle leadership, and the top’s influence on the middle is generally more significant than the influence on grassroots employees. However, the difference between the influence of the middle leadership on the grassroots and that of the top on the grassroots is not apparent, which is inconsistent with the trickle-down effect that the middle leadership communicates more with the grassroots and has more influence on the grassroots, and further verification is needed. All three types of leaders positively affected employee performance, with the best being transformational leadership, paternalistic leadership, and servant leadership. This finding is consistent with some scholars and inconsistent with some scholars. The interested scholars can do further research. The better performance of diverse pairings in middle and senior leadership combinations is consistent with previous research suggesting that leadership styles have their own strengths and can be complementary. This paper further provides a comparative study of multiple leadership styles to validate the recognition and adaptability of leadership styles and further explain the complex relationship between leadership styles and employee job performance. Scholars can conduct comparative research on other leadership styles, and there may be different results. Future Research: Because of the cross-sectional data taken, the findings’ generalizability still needs further validation. There are many types of leadership styles, and there are other types of leadership styles that can be explored comparatively, perhaps leading to different findings. From another point of view, various leaders have their strengths, and they are not mutually hindering. More research is needed on team formation in a variety of contexts. Organic organizational structure enables knowledge creation and integration through the process of organizational learning through deep and continuous social interaction or dialogue. So we can further examine the influence process of leaders on employees from how to give full play to their advantages, such as improving shared leadership and shared communication.

Aim/Purpose: The aim of the present paper is to present a Noise Decision (ND) scale. First, it reports the development and validation of the instrument aimed at examining organizational factors that have an influence on decision-making and the level of noise. Second, it validates this rating scale by testing its discriminant and convergent validity with other measures to assess decision-making qualities. Background: According to the literature, the concept of noise is the unwanted variability present in judgments. The notion of noise concerns the systematic influence to which individuals are exposed in their environment. The literature in the field has found that noise reduction improves the perception of work performance. Methodology: The first study involves the development of a scale (composed of 36 items) consisting of semi-structured interviews, item development, and principal component analysis. The second study involves validation and convergent validity of this scale. In the first study, there were 43 employees from three medium-sized Italian multinationals. For the second study, a sample of 867 subjects was analysed. Contribution: This paper introduces the first scale aimed at assessing noise within individuals and, in the organizational context, within employees and employers. Findings: Results show that the estimated internal reliability for each of the ND subscales and also the correlations between the subscales were relatively low, suggesting that ND correctly measures the analyzed components. Furthermore, the validation of the psychometric qualities of the ND allowed for the assertion that the influence of noise is present in the decision-making process within the context of work environments, validating the initial hypotheses. Recommendation for Researchers: This paper aims to improve theory and research on decision-making; for example, by providing a possible implementation for scales for evaluating decision-making skills. Furthermore, detecting and limiting noise with a systematic method could improve both the quality of decisions and the quality of thought processes. Future Research: Given the measurement of ND, the study can be a starting point for future research on this topic. Since there is no literature about this construct, it would be necessary to spend more time researching, so that the topic becomes clearer. System noise has been tested by some researchers with a “noise audit,” which means giving the same problem to different people and measuring the differences in their responses. Repeating this kind of audit in conjunction with the ND in a specific work environment could be helpful to detect but also measure the influence of noise.

This paper proposes an efficient solution for personalised web directories recommendation using fast FCM+DQN. At first, web directory usage file obtained from given dataset is fed into the accretion matrix computation module, where visitor chain matrix, visitor chain binary matrix, directory chain matrix and directory chain binary matrix are formulated. In this, directory grouping is accomplished based on fast FCM and matching among query and group is conducted based on Kumar Hassebrook and Kulczynski similarity. The user preferred directory is restored at this stage and at last, personalised web directories are recommended to the visitors by means of DQN. The proposed approach has received superior results with respect to maximum accuracy of 0.910, minimum mean squared error (MSE) of 0.0206 and root mean squared error (RMSE) of 0.144. Although the system offered magnificent outcomes, it failed to order web directories in the form of highly, medium and low interested directories.

This paper presents a novel deep learning technique called quantum dilated convolutional neural network-DenseNet (Q-DenseNet) for prediction of heart disease in spark framework. At first, the input data taken from the database is allowed for data partitioning using fast fuzzy C-means clustering (FFCM). The partitioned data is fed into spark framework, where pre-processed by missing data imputation and quantile normalisation. The pre-processed data is further allowed for selection of suitable features. Then, the selected features from the slave nodes are merged and fed into master node. The Q-DenseNet is used in master node for the prediction of heart disease. The performance improvement of the designed Q-DenseNet model is validated by comparing with traditional prediction models. Here, the Q-DenseNet method achieved superior performance with maximum of 92.65% specificity, 91.74% sensitivity, and 90.15% accuracy.

The objective of this study was to explore through the Model of Theory of Planned Behaviour the most important variables that influence the practice of physical and sports activity at home supported by virtual training in the context of the COVID-19 pandemic. A cross-study was proposed between countries from three continents, distributing the questionnaire in Spain (Europe), Pakistan (Asia), and Colombia (South America) to ensure a comprehensive study. The methodology of structural equations using partial least squares was used. The empirical exploratory study supported the hypotheses proposed, with the most important result that confinement due to the COVID-19 pandemic has been a factor causing the practice of physical and sports activity at home. This is one of the first studies to examine sports practice at home and the new context of sports practice that has generated disruptive technologies and the global crisis of the COVID-19 pandemic.

In this inductive study, we shift the focus of stigma research inside organizational boundaries by examining its relationship with organizational identity. To do so, we draw on the case of Keystone, a social enterprise in the East of England that became stigmatized after it initiated a program of support for a group of migrants in its community. Keystone's stigmatization precipitated a crisis of organizational identity. We examine how the identity crisis unfolded, focusing on the forms of identity work that Keystone's leaders enacted in response. Interestingly, we show not only that the internal effects of stigmatization on identity can be managed, but also that they may facilitate unexpected positive outcomes for organizations.

Exit is a critical part of the entrepreneurial process. At the same time, research indicates that founders are likely to form strong identity connections to the organizations they start. In turn, when founders exit their organizations, the process of psychological disengagement might destabilize their identities. Yet, limited research addresses how founders experience exit or how they manage their identities during this process. Through a qualitative, inductive study of founders of technology-based companies, I developed a theoretical model of founder psychological disengagement that delineates how founder work orientations relate to the disengagement paths that founders follow when leaving one organization and starting another. In elaborating theory on psychological disengagement, this study has implications for understanding the psychology of founders, how founders exit and begin again, and psychological disengagement, more broadly.

Over the past decade, the terms "crisis" and "crisis management" have become increasingly popular topics of interest for business professionals and management academics alike. According to the Institute for Crisis Management (2013), "Newsworthy business crises have been on a steady upward trend since 2009.

Social enterprise has gained widespread acclaim as a tool for addressing social and environmental problems. Yet, because these organizations integrate the social welfare and commercial logics, they face the challenge of pursuing goals that frequently conflict with each other. Studies have begun to address how established social enterprises can manage these tensions, but we know little about how, why, and with what consequences social entrepreneurs mix competing logics as they create new organizations. To address this gap, we develop a theoretical model based in identity theory that helps to explain: (1) how the commercial and social welfare logics become relevant to entrepreneurship, (2) how different types of entrepreneurs perceive the tension between these logics, and (3) the implications this has for how entrepreneurs go about recognizing and developing social enterprise opportunities. Our approach responds to calls from organizational and entrepreneurship scholars to extend existing frameworks of opportunity recognition and development to better account for social enterprise creation.

Studies suggest that category-spanning organizations receive lower evaluation and perform worse than organizations focused on a single category. We propose that (1) these effects are contingent on clients' theory of value and that as clients expect more sophisticated services, they tend to value category spanners more positively and (2) the evaluation of producers mediates the relationship between category spanning and performance. We test our hypotheses using original data on corporate legal services in three markets (London, New York City, and Paris) over the decade 2000-2010. We find that (1) category spanners receive a better evaluation, and more so when their categorical combination is more inclusive and (2) evaluation mediates significantly the relationship between category spanning and performance. This study enriches our understanding of how audiences apprehend a whole market category system and why organizations span categories.

Chancellor Rachel Reeves has said firms will have to absorb higher taxes through their profits.

President-Elect Donald Trump reaffirmed his commitment to protecting the Second Amendment by announcing his push for national concealed carry reciprocity.

THE Human Rights Commission of Malaysia (Suhakam) acknowledges the efforts of the government under Prime Minister Datuk Seri Anwar Ibrahim in presenting Budget 2025.

The initiatives aimed at equitable economic growth, fiscal responsibility and governance reforms are commendable.

While the budget reflects positive steps in Malaysia’s fiscal policy and development, it falls short in addressing critical human rights concerns, especially in areas affecting marginalised and vulnerable groups.

Suhakam welcomes the government’s focus on children, including incentives for special needs children and tax breaks for parents of children with autism.

Efforts to tackle child malnutrition in public housing and the increased allocation to agencies dealing with online safety, child pornography and cyberbullying are positive.

The strengthening of relevant laws to address scams and cybercrimes targeting children as well as the introduction of new legal frameworks represent a proactive step towards protecting children in the digital age.

Despite these improvements, Suhakam stresses that the budget lacks clear plans to safeguard the rights of migrant workers, refugees and stateless individuals. These communities continue to face exploitation, with limited access to healthcare, education and legal protection.

Stronger frameworks are needed to prevent human trafficking and exploitation, ensuring these groups can access justice and basic services, in line with Malaysia’s international obligations.

The budget mentions infrastructure projects for rural and indigenous communities but fails to address the protection of indigenous peoples’ land rights.

Their participation in decision-making on development projects remains limited, often resulting in displacement and loss of traditional lands.

Suhakam emphasises the importance of the principle of free, prior and informed consent in all development activities to preserve their rights and cultural heritage.

On gender equality, Budget 2025’s focus on gender-based violence remains inadequate.

The absence of specific allocations for strengthening legal frameworks and support services for victims is alarming.

Suhakam urges the government to prioritise protection for women, particularly in addressing domestic violence, sexual harassment and workplace discrimination.

Malaysia’s ageing population continues to grow, yet their specific needs remain largely unaddressed. Access to healthcare, social protection and protection from abuse are essential human rights that cannot be overlooked. Suhakam calls for a comprehensive national ageing policy that guarantees the dignity and rights of elderly citizens.

In addition, while poverty alleviation is a government focus, the budget lacks a human rights-based approach to economic and social rights.

Marginalised communities continue to struggle with inadequate housing, food security and fair wages. Suhakam stresses the need for legal protections that ensure equitable access to resources, affordable housing and decent work for all, especially low-income families.

Mental health services, especially post-pandemic, remain critically underfunded.

While economic recovery is emphasised, there is limited attention to community-based mental healthcare.

Additionally, the budget does not sufficiently address the rights and needs of persons with disabilities (PwD). The lack of focus on accessibility, inclusive education and employment opportunities is concerning.

Suhakam urges the government to align its policies with the United Nations Convention on the Rights of Persons with Disabilities, ensuring equal access to public services and economic opportunities for all PwD.

While institutional reforms are mentioned, Budget 2025 falls short in addressing access to justice for vulnerable groups.

Suhakam advocates for comprehensive legal reforms to ensure marginalised communities can access justice and hold perpetrators of human rights violations accountable.

On a positive note, Suhakam recognises the increased budget for the judiciary, the boost to the National Cyber Security Agency in tackling online safety issues, including for children, and the anticipated Online Safety Bill.

The increase in cash aid under Sumbangan Tunai Rahmah and the allocations for combatting child malnutrition in public housing areas are steps in the right direction.

Despite these initiatives, the minimum wage still does not reflect the actual cost of living, as evidenced by reports from Employees Provident Fund, Bank Negara Malaysia and Credit Counselling and Debt Management Agency.

Additionally, the Baitul Mahabbah programme continues with no expansion to cover all children below 18 years, nor an indication of family or community placement.

Suhakam acknowledges the government’s commitment to fiscal responsibility and governance reforms.

However, we urge the government to ensure that its economic growth strategies are inclusive.

A budget must address not only fiscal concerns but also the protection of fundamental rights for all.

Suhakam

The Elephant Care Association of South Africa (ECASA) responds to Dr. Adam Cruise’s article, ‘Rules of Engagement: South Africa to ban captive wildlife interactions for tourists’ The Elephant Care Association of South Africa is deeply concerned by Dr Cruise’s article,...

KUALA LUMPUR: A group of planters and stakeholders in the East West One Group (EWOG) schemes urgently calls on Pacific Trustees Bhd (PTB) to release the funds necessary for the company’s approved rehabilitation and restructuring (R&R) exercise.

The majority of EWOG’s investors, represented by Thirunavukarasu Illamurugan, Yong Chin Koi, and Mahadevan Kathirgamathamby, are concerned that PTB’s continued withholding of these funds could further damage the company’s financial health, potentially leading to irreversible losses.

To recap, EWOG obtained planters’ approval of the company’s R&R exercise across all three schemes: East West One Planter’s Scheme (EWOP), East West Horizon Planter’s Scheme, and East-West Planter Scheme 1.

EWOG, in a statement, said the past few years have seen significant challenges that have severely impacted plantation operations, including the global Covid-19 pandemic, La Niña weather phenomena, industry-wide labour shortages, land disputes with landowners, and repeated injunctions that prevented timely convening of planters’ meetings from addressing these issues.

These cumulative challenges have compounded the company’s cash flow problems, resulting in an inability to meet payment obligations.

According to a statement by EWOG, despite the overwhelming support for the R&R plan from planters and stakeholders at the August 12 Planters’ Meeting, critical rehabilitation work on EWOG’s plantation assets remains stalled due to this delay.

For over a year, the plantation palms have relied solely on natural soil fertility, with no structured fertilisation or agronomic practices.

Prompt initiation of the R&R program is essential to restoring the plantation’s productivity.

This program leverages enhanced agronomic practices and inputs to increase fresh fruit bunch (FFB) production.

With crude palm oil (CPO) prices currently above RM4,000 per ton and projected to hold through 2025, the company has a unique window to capitalise on these favourable market conditions.

Proceeds from FFB sales could also partially offset ongoing rehabilitation costs, creating a sustainable pathway to recovery.

“Every day of delay further impacts our ability to restore the plantation and diminishes potential returns for all investors,” said Thirunavukarasu in the statement.

“These funds, specifically held in trust for the plantation’s rehabilitation, need to be released without further delay,“ he said in the statement.

According to a recent court filing by East West Horizon Plantation Bhd, the management continues to face challenges due to PTB’s reluctance to finalise necessary trust deeds despite ongoing efforts from EWOG’s management and legal team.

This impasse prevents the release of funds crucial for the R&R efforts, posing increased risks to the plantation assets and investor returns.

The investors’ representatives stressed that “a swift resolution is essential to launch the rehabilitation efforts and generate returns for all stakeholders.”

“It is time to move past the standstill and allow the EWOG group to implement the R&R plan for the benefit of all involved.”

The state weather bureau has placed several areas under Signal No. 2 as Typhoon Ofel makes its way to Northern Luzon.

I didn’t think Google News (http://news.google.co.uk/) could get any worse but I was wrong. The previous revamp was bad enough: no more advanced search, useless and irrelevant personalisation options, and don’t even think about trying to set up sensible alerts. Alerts were never that good at the best of times but were not improved one iota … Continue reading Somebody, please put Google News out of its misery →

Random Photo: Bridge Surprise

In its recently released mobile device best practices guide, the National Security Agency (NSA) goes old-school geek and advises people to turn their phones off and on again....

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When you go on a cruise, it’s a time to relax, free your mind of the cares of the world and be waited on – but there’s a cost to the latter. The people behind the great customer service you experience deserve to be rewarded. You may be wondering when it comes to cruises, which […]

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