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An Analysis of Decision-Making Arbitration and Settlement on Employee-Transfer Court Cases
Get PDFThe commercial enterprises have grown with branches in districts and states, national, regionally and internationally to accommodate ever-growing demands for quality products, services and consultancies, with affordable or reasonable costs. Deployment of capital and labour is the main key to supporting production operations and sustaining logistics-supply chain for all industries; one without the other cannot survive, develop and grow organization business profitability specifically and country
economic wealth and people welfare in general. Invariably, Associations representing the employers and Trade Unions representing the workers are confronted with labour-
relations issues that propel each of them to protect the welfare or negotiate the disputed interests of their respective members. In this context, as the dispute-negotiation process is disrupted or has reached a stalemate, for one reason or another, the so-called
Industrial Disputes and the aggrieved parties can continue to seek redress beyond the decision-arbitration intervention of the Industrial Relations Department of the
Industrial Court, into the ambit of review-settlement decisions by the High Court, Appeal Court and Federal Court in pursuit of a justifiable claim for judgmental
decision on reasonable compensation. In this thesis, Industrial Disputes arising from disputed employee-transfer cases are analysed, employing the legal bases for mainly Malaysian cases and the Commonwealth cases as references for judgmental decision-making, arbitration and settlement for contractual disputes involving diverse issues surrounding employee-transfer involving bona fide and mala fide transfers representing a widespread of grievances, grouses or complaints from mostly aggrieved and disrupted workmen. The 14 selected cases, based on a set of 7 pair-cause similar premise-issue such as transfer demotion, insubordination, change of ownership, change of job functions, departmental transfer, different legal entity, and no transfer clause in Appointment Letter are analysed and resolved legally. The expected output of this case-study based on the ex post facto method of review-analysis, in the form of judgement-resolution decisions, provide the retrospective insight into and critique of how, and to what extent, the impact of the decisions-outcome has affected the
employer (organizations), employee (workmen and Associations), legal arbitrators (courts) in terms of labour relations and its statutory provisions (the Acts), policy
governance (Ministry of Human Resource) and overall productivity of national economic wealth and citizenry welfare. The conclusion provides a directional indicator
of future redress-award solutions beyond the applications of conventional arbitration and settlement models into the advocacy of water-tight contract-specific terms and
conditions of employment into the digital era of industrial ventures and commercial enterprises, during and post-COVID19 pandemic era. The fourteen cases selected produce the final desired employer-employee output-outcome of the wisdom of
judicial judgmental decisions
A Conceptual Model for Promoting Information Security Policy Compliance Behaviour at Workplace
Get PDFSecuring sensitive and critical information is a significant challenge for many organisations, as leaks can cause financial, reputational, and competitiveness losses. Organisations can implement an Information Security Policy (ISP) that employees must comply with to minimise this risk. However, ensuring compliance with the ISP continues to be a problem. To address this issue, a conceptual model has been proposed that organisations can use to promote ISP compliance behaviour among their employees. The Health Action Process Approach (HAPA) Model is used to derive this model. The model consists of two phases -motivational and volitional which are expected to cover the elements needed to promote behavioural change for ISP compliance. The model's multi-processes approach, covering critical aspects such as risk assessment, self-efficacy, initiation, and maintenance, enables it to serve as a platform for organisations to sustain ISP compliance over the long term. Organisations can conduct employee assessments and provide ISP compliance training and awareness campaigns to implement the model. They can also disseminate cues about information security issues and how the ISP can assist employees in handling them, discourage behaviour that leads to complacency towards ISP compliance, and update the ISP to keep it relevant. The proposed model presents an opportunity for future research to evaluate its applicability in organisational settings
Exploring the impact of social media on political discourse: a case study of the Makassar mayoral election
Get PDFSocial media has become a significant force in today's modern society, influencing several areas, including politics, education, the economy, and the spread of information. This study examines how social media platforms influence political discourse, focusing on the Makassar mayoral race. This study looks into how Twitter, a well-known social media site, encourages more user participation in communications related to the Makassar mayoral election. In light of the Makassar mayoral election, this study employs several approaches, including data collection, acquisition, consolidation, and analysis, to address topics that are becoming increasingly popular on social media. Election dynamics are examined using the naïve Bayes approach. To increase the accuracy and efficiency of text mining operations, especially in result validation, text clustering, and classification, the k-means algorithm and support vector machines (SVM) were used. A hybrid method is employed to combine the benefits of k-means, SVM, and naïve Bayes. This method seeks to thoroughly grasp how social media affects conversations about the mayoral race, offering insightful information to political scientists and practitioners. The research on the Makassar mayoral race explores the influence of social media on political communication, highlighting Twitter's influence and a hybrid algorithm for sentiment analysis. It indicates the importance of social media strategy in political campaigns, providing insights for decision-makers, parties, and the public and recommending future research in this dynamic field
The Impact of Transformational Leadership and Project Success: Mediating Role of Team Identity, Team Communication, and Team Empowerment
Get PDFThis study is grounded in the theoretical frameworks of the Resource Base View and Social-Identity Theories and intents to evaluate how the adoption of transformational leadership practices influences project success by considering facilitating function of team-identity, team-communication, and team empowerment. The study was conducted among 350 Software project professionals in Pakistan. The study utilized PLS-SEM to analyze both direct and mediating effects. The findings revealed a notable affiliation between TL and PS. Besides, the study confirmed that team identity, communication, and empowerment act as mediator in the connection amid TL and PS. This research addresses a gap in
empirical studies within developing countries, notably Pakistan by shedding light on how TL impacts PS through the lens of team-dynamics. This study stands as an early exploration into the interplay among proposed association
Entrepreneurship Development Among University Students: An Analysis of Barriers and Opportunities in Rawalpindi and Islamabad
Get PDFThis study examines the influence of financial, technical, and cultural barriers on entrepreneurial growth in Pakistan, focusing specifically on college students in Rawalpindi and Islamabad. The research addresses a critical issue: while Pakistan’s economic environment and various government initiatives offer substantial opportunities for business development, excessive government intervention is identified as a major impediment to entrepreneurial innovation and risk-taking. To investigate this, primary data was collected using a structured questionnaire administered to college students. The study employs correlation analysis to explore the relationship between these barriers and the capacity for business growth, as well as to assess the interactions among the different types of impediments. Financial barriers include limited access to funding and financial resources; technical barriers encompass a lack of technical skills and infrastructure; and cultural barriers involve societal attitudes and norms that may hinder entrepreneurial activities. The findings reveal that while government initiatives are well-intentioned, their excessive interference can undermine the entrepreneurial spirit by creating regulatory and bureaucratic hurdles. This research provides critical insights into how these barriers impact the entrepreneurial ecosystem and highlights the need for a balanced approach to government intervention. By offering a detailed analysis of these factors, the study aims to assist scholars and policymakers in developing more effective strategies to enhance Pakistan’s entrepreneurial environment, thereby fostering sustainable business growth and innovation
Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes
Get PDFThe growing utilization of solar panels as a renewable energy source requires efficient maintenance solutions to guarantee their best functioning. Identifying and categorizing faults on solar panel surfaces is essential for maintenance, as these defects considerably affect energy output and system efficiency. This study investigates the utilization of statistical feature extraction methods alongside Bernoulli Naive Bayes (BNB) and Gaussian Naive Bayes (GNB) algorithms to categorize different defect types, such as cracks, scratches, spots, and non-defective surfaces, through digital image analysis. Statistical criteria, including recall, specificity, and area under the curve (AUC), are employed to assess model performance. The findings indicate that the GNB algorithm surpasses BNB, with a mean average precision (mAP) of 39.83% with an 85:15 training-test ratio, whereas BNB reaches a maximum mAP of 29.25% at a 90:10 ratio. Nonetheless, both models demonstrate constraints in precision, as indicated by a total AUC of 0.644. This work illustrates the potential of statistical feature extraction approaches for defect classification, while emphasizing the necessity for future improvements to boost the efficacy of feature extraction and classification techniques in practical applications
Assessing the Impact of Digital Supply Chain Management on the Sustainability of Construction Projects
Get PDFThe implementation of digital supply chain management (DSCM) has brought about a paradigm shift in the construction industry, which is known for its complex and dynamic nature. This study examines the advantages of implementing a digital supply chain into building projects, focusing on efficient procurement, real-time tracking, and its effects on the sustainability of the project. A stratified sampling approach is used in the research methodology to collect quantitative data from construction project managers and supply chain specialists using surveys and questionnaires. The study’s main objective is to measure how improved stakeholder coordination, real-time tracking, and streamlined procurement procedures affect sustainability and efficiency. The results of this study highlight the significant advantages of DSCM in raising the effectiveness
of building projects. The results include shortened lead times, improved supply chain visibility, streamlined
procurement procedures, and optimal resource allocations. This paper is focused on the potential difficulties and roadblocks to a successful DSCM implementation. The study provides insightful information for decision-makers and practitioners in the construction sector. To successfully apply DSCM, organizations need to make investments in technology and training, improve teamwork, and create risk-reduction plans
Impact of Information Security Policies Compliance (ISPC) on Reducing the Incidence of Security Breaches in Organizations: Systematic Literature Review
Get PDFInformation security policy compliance plays an important role in reducing the incidence of security breaches in organizations. Recently, information security practices in firms have been widely examined. Therefore, inadequate efforts have been made to assess and systematically review the present study status to offer insights into prior study findings. This systematic literature review investigated the impact of ISPC on reducing the incidence of security breaches in organizations. After inclusion and exclusion criteria process conducted, 42 research publications from Google scholar, Sage, IEEE, ACM, ScienceDirect, Springer, Jstor, Wiley, Taylor & Francis databases (2009 – 2024) included, most of the studies utilized quantitative research methods to explore factors influencing compliance with information security policies, such as employee demographics, organizational strategies, and deterrence mechanisms, A few studies adopted qualitative methods to assess the effectiveness of security programs or to propose measures to enhance compliance. The findings suggested that not only information security policy compliance reduce incidences of security breaches in organizations but also other factors such as employee training, awareness, management support, regular audits, and the integration of advanced security technologies are identified as crucial for reducing security breaches. The implications of these findings for organizational practices and future research directions are discussed, providing valuable insights for policymakers, IT professionals, and researchers aiming to strengthen information security frameworks and reduce the incidence of security breaches
MobileNet Backbone Based Approach for Quality Classification of Straw Mushrooms (Volvariella volvacea) Using Convolutional Neural Networks (CNN)
Get PDFStraw mushrooms (Volvariella volvacea) are a crucial commodity in Indonesia, with consumption on the rise due to their nutritional value and increasing demand for healthy food options. Despite this growth, farmers often struggle with accurately assessing the post-harvest quality of mushrooms according to market standards, which can diminish their economic value. Manual classification, which relies on human judgment and estimation, is frequently inefficient and susceptible to errors such as inconsistencies in quality assessment and limitations in detecting subtle variations. This study aims to automate the classification of straw mushrooms based on quality using deep learning, specifically by employing MobileNetv3 as the backbone for classifying mushrooms based on their shape and color by the Indonesian National Standards (SNI). The MobileNet-CNN Backbone model implemented in this study demonstrated exceptional performance, achieving a classification accuracy of 99%, thus proving its effectiveness and reliability in replacing traditional manual methods. The results of this research indicate significant potential for applying deep learning models to enhance the efficiency and precision of mushroom quality assessment. However, there remain challenges that require further development, including adding more diverse background data, improving image resolution, and refining data augmentation techniques. Addressing these challenges is essential for achieving optimal results in varying environmental conditions, ensuring the model can be broadly implemented in the agricultural industry. Such advancements could lead to more consistent and accurate quality assessments, benefiting producers and consumers in the mushroom market