Bankruptcy prediction of construction businesses:Towards a big data analytics approach

Bankruptcy prediction models (BPMs) are needed by financiers like banks in order to check the credit worthiness of companies. A very robust model needs a very large amount of data with periodic updates (i.e. appending new data). Such size of data cannot be processed directly by the tools used in building BPMs, however Big Data Analytics offers the opportunity to analyse such data. With data sources like DataStream, FAME, Company House, etc. that hold large financial data of existing and failed firms, it is possible to extract huge financial data into Hadoop database (e.g. HBase), whilst allowing periodic appending of data from the data sources, and carry out a Big Data analysis using a machine learning tool on Apache Mahout. Lifelong machine learning can also be employed in order to avoid repeated intensive training of the model using all the data in the Hadoop database. A framework is thus proposed for developing a Big Data Analytics based BPM

Predicting Completion Risk in PPP Projects using Big Data Analytics

Accurate prediction of potential delays in public private partnerships (PPP) projects could provide valuable information relevant for planning and mitigating completion risk in future PPP projects. However, existing techniques for evaluating completion risk remain incapable of identifying hidden patterns in risk behavior within large samples of projects, which are increasingly relevant for accurate prediction. To effectively tackle this problem in PPP projects, this study proposes a Big Data Analytics predictive modeling technique for completion risk prediction. With data from 4294 PPP project samples delivered across Europe between 1992 and 2015, a series of predictive models have been devised and evaluated using linear regression, regression trees, random forest, support vector machine, and deep neural network for completion risk prediction. Results and findings from this study reveal that random forest is an effective technique for predicting delays in PPP projects, with lower average test predicting error than other legacy regression techniques. Research issues relating to model selection, training, and validation are also presented in the study

Developed Model to Control Congestion on Converge Network

Congestion control techniques like Active Queue Management (AQM), Carrier Sense Multiple Access/Carrier Detection (CSMA/CD) have not proven to be very efficient in the presence of overwhelming complex converge network. Thus, vast packets in a complex converged network leads to collisions, network degradation and high degree of packet loss. Bandwidth utilization factor has a high effect on the network such that controlling the level of utilization via the management of the number of users and the amount of packets on the network rendered the latency very insignificant. As a consequence of this, high throughput and very minimal packet loss was achieved in the experiment. This was confirmed analytically by varying the utilization factor between 40% and 90% while keeping other parameters in the experiment constan

Evaluating the Advantages and Disadvantages of Centralized vs. Decentralized Purchasing: A Case Study of a Nigerian Grocery Store Chain

Purchasing decisions in grocery business accounts for a substantial part of the operating cost. Considering its significance, the advantages and disadvantages of centralized and decentralized purchasing methods in Nigerian grocery store chains were evaluated. The challenges faced by a Nigerian grocery chain in optimizing resource allocation while achieving operational efficiency and effectiveness were investigated. A qualitative case study examined the advantages and disadvantages of centralized versus decentralized purchasing within Nigerian grocery store chains. Semi-structured interviews were conducted with procurement teams and store managers from a single chain operating across multiple locations in Southwest Nigeria. The research investigated the impacts of each purchasing model on operational efficiency, inventory management, supplier relationships, and responsiveness to market demands. Findings revealed that centralized purchasing offered significant cost savings and streamlined operations, but also resulted in communication challenges and reduced responsiveness to localized demands. Decentralized purchasing, conversely, demonstrated enhanced flexibility and responsiveness but lacked the economies of scale achievable through centralization. The study concludes by highlighting the im-portance of aligning purchasing strategy with overall business goals and suggests areas for future research

Geological and Geochemical Characterisation of Pegmatites around Olode, Southwestern Nigeria

Olode is prolific in terms of pegmatites, occurring in different ways as large intrusive bodies, as veins and dykes, discordantly intruding the host rocks of mica schist, gneiss and granite. This study is aimed at the geological and geochemical characterisation of pegmatites around Olode. Field investigation was undertaken to determine the occurrences and relationships of the pegmatites with the host rocks. Fresh pegmatite samples were studied petrographically and geochemically. Two main lithologically and chronologically different groups of pegmatites were distinguishable in the study area. These were the tourmaline pegmatites associated with the Older Granite rocks and the NE-SW trending beryl-bearing pegmatites typically occurring as dykes, hosted by the mica schist. Results of the geochemical analysis showed variations in the chemical compositions of the two varieties of pegmatites, reflecting their mineralogical differences, but with common peraluminous provenance. The discrimination plots of Cs and Rb versus K/Rb have classified most of the beryl-bearing pegmatites as mineralised, with mean K/Rb ratio of 85, and the tourmaline pegmatites as barren. The Olode pegmatites have emanated from a common source, a higly mineralised magma, and their differences in chemical composition and occurrences have resulted from fractional crystallisation of the parent magma and varied evolutionary trends. Keywords: Olode; Pegmatites; Beryl-bearing; Tourmaline; Mineralised

Adoption of Green Practice (Waste Management) in the Hotel Industry, Kwara State, Nigeria.

Despite the significance of hotels and their influence on tourism and industrial growth, the hotel industry is often associated with significant contributions to green practice challenges such as global warming, pollution, and resource depletion. As a result, there is a global call for adherence to green practice within the industry. This research studied the practice of the adoption of green practices in waste management hotels in Kwara State, Nigeria. This research data was collected using qualitative and quantitative research methodologies to analyze the factors affecting hotel management and the adoption of waste management strategies by members of the staff. Research reveals that although methods such as trash segregation and recycling are prevalent, inconsistencies exist between self-reported behaviors and actual observations, attributable to social desirability bias. The research highlights environmental awareness, cost, regulatory pressures, and managerial support as primary determinants of waste management adoption. Nonetheless, obstacles such as insufficient training, limited infrastructure, and logistical complications impede efficient waste management systems. Ultimately, efficient waste management improves operational performance and reputation, fostering environmental responsibility in the hotel industry. Keywords/tags (Waste, Waste management, Green practices, Hotel classification, hotel waste management, Kwara State) Miscellaneous (None)