Search results for: database management

Authors: Chibuzo Okoye Daniels, Gillian Glegg, Lynda Rodwell

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Marine debris from fishing nets to medical equipment to food packaging that play major roles in boosting the economy and protecting human health is now more than an environmental problem that can be solved by legislation, law enforcement and technical solutions. It has also been identified as a cultural problem that can only be addressed by identifying instruments that can be used to change human attitudes and behaviors. This may be through management approaches, education and involvement of all sectors/interests, including the public. To contribute to the sustainable development of coastal Nigeria, two case study areas (Ikoyi and Victoria Islands of Lagos State) were used to evaluate the socio-economic impacts of marine debris problem in coastal Nigeria. The following methods were used: (1) semi-structured interviews with key stakeholders and businesses on beaches, waterfronts and waterways within the study areas and (2) observational study of beaches, waterfronts and waterways within the study areas. The results of the study have shown that marine debris is a cultural and multi-sectoral problem that poses great threat not only to the environmental sustainability of the study areas but also to the wellbeing of its citizens and the economy of coastal Nigeria. Current solid waste and marine debris management practices are inefficient due to inadequate knowledge of how to tackle the problem. To ensure environmental sustainability in coastal Nigeria and avoid waste of scarce financial resources, adequate, appropriate and cost effective solutions to the marine debris problem need to be identified and effectively transferred for implementation in the study areas.

Keywords: sustainability, coastal Nigeria, study areas, aquaculture

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Authors: Thampi Rawther, Jack Cecire, Andrew Sutherland

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Introduction: CT facilitates the diagnosis of potentially life-threatening injuries and facilitates early management. There is evidence that reduced CT acquisition time reduces mortality and length of hospital stay. Currently, there are variable recommendations for ideal timing. Indeed, the NHS standard contract for a major trauma service and STAG both recommend immediate access to CT within a maximum time of 60min and appropriate reporting within 60min of the scan. At Coffs Harbour Health Campus (CHHC), a CT radiographer is on site between 8am-11pm. Aim: To investigate the average time to CT at CHHC and assess for any significant relationship between time to CT and injury severity score (ISS) or time of triage. Method: All major trauma calls between Jan 2021-Oct 2021 were audited (N=87). Patients were excluded if they went from ED to the theatre. Time to CT is defined as the time between triage to the timestamp on the first CT image. Median and interquartile range was used as a measure of central tendency as the data was not normally distributed, and Chi-square test was used to determine association. Results: The median time to CT is 51.5min (IQR 40-74). We found no relationship between time to CT and ISS (P=0.18) and time of triage to time to CT (P=0.35). We compared this to other centres such as John Hunter Hospital and Gold Coast Hospital. We found that the median CT acquisition times were 76min (IQR 52-115) and 43min, respectively. Conclusion: This shows an avenue for improvement given 35% of CT’s were >30min. Furthermore, being proactive and aware of time to CT as an important factor to trauma management can be another avenue for improvement. Based on this, we will re-audit in 12-24months to assess if any improvement has been made.

Keywords: imaging, rural surgery, trauma surgery, improvement

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Authors: Marcella De Filippo, Delio Colangelo, Luca Farnia

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In recent decades, the hyper-competition of tourism scenario has implicated the maturity of many businesses, attributing a central role to innovative processes and their dissemination in the economy of company management. At the same time, it has defined the need for monitoring the application of innovations, in order to govern and improve the performance of companies and destinations. The study aims to analyze and define the innovation in the tourism sector. The research actions have concerned, on the one hand, some in-depth interviews with experts, identifying innovation in terms of process and product, digitalization, sustainability policies and, on the other hand, to evaluate the interaction between these factors, in terms of substitutability and complementarity in management scenarios, in order to identify which one is essential to be competitive in the global scenario. Fuzzy measures and Choquet integral were used to elicit Experts’ preferences. This method allows not only to evaluate the relative importance of each pillar, but also and more interestingly, the level of interaction, ranging from complementarity to substitutability, between pairs of factors. The results of the survey are the following: in terms of Shapley values, Experts assert that Innovation is the most important factor (32.32), followed by digitalization (31.86), Network (20.57) and Sustainability (15.25). In terms of Interaction indices, given the low degree of consensus among experts, the interaction between couples of criteria on average could be ignored; however, it is worth to note that the factors innovations and digitalization are those in which experts express the highest degree of interaction. However for some of them, these factors have a moderate level of complementarity (with a pick of 57.14), and others consider them moderately substitutes (with a pick of -39.58). Another example, although outlier is the interaction between network and digitalization, in which an expert consider them markedly substitutes (-77.08).

Keywords: innovation, business model, tourism, fuzzy

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Authors: Spada Alessia, Fiore Mariantonietta, Lamonaca Emilia, Contò Francesco

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Bioeconomy can give the chance to face new global challenges and can move ahead the transition from a waste economy to an economy based on renewable resources and sustainable consumption. Air pollution is a grave issue in green challenges, mainly caused by anthropogenic factors. The agriculture sector is a great contributor to global greenhouse gases (GHGs) emissions due to lacking efficient management of the resources involved and research policies. In particular, livestock sector contributes to emissions of GHGs, deforestation, and nutrient imbalances. More effective agricultural research systems and technologies are crucial in order to improve farm productivity but also to reduce the GHGs emissions. Using data from FAOSTAT statistics and concern the EU countries; the aim of this research is to evaluate the impact of ASTI R&D (Agricultural Science and Technology Indicators) on GHGs emissions for countries EU in 2015 by generalized propensity score procedures, estimating a dose-response function, also considering a set of covariates. Expected results show the existence of the influence of ASTI R&D on GHGs across EU countries. Implications are crucial: reducing GHGs emissions by means of R&D based policies and correlatively reaching eco-friendly management of required resources by means of green available practices could have a crucial role for fair intra-generational implications.

Keywords: agricultural research systems, dose-response function, generalized propensity score, GHG emissions

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Authors: Cecilia Moreira, Rita Paiva, Daniela Macedo, Leonor Ribeiro, Isabel Fernandes, Luis Costa

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Background: Head and neck paragangliomas are a rare group of tumors with a large spectrum of clinical manifestations. The approach to evaluate and treat these lesions has evolved over the last years. Surgery was the standard for the approach of these patients, but nowadays new techniques of imaging and radiation therapy changed that paradigm. Despite advances in treating, the growth potential and clinical outcome of individual cases remain largely unpredictable. Objectives: Characterization of our institutional experience with clinical management of these tumors. Methods: This was a cross-sectional study of patients followed in our institution between 01 January and 31 December 2017 with paragangliomas of the head and neck and cranial base. Data on tumor location, catecholamine levels, and specific imaging modalities employed in diagnostic workup, treatment modality, tumor control and recurrence, complications of treatment and hereditary status were collected and summarized. Results: A total of four female patients were followed between 01 January and 31 December 2017 in our institution. The mean age of our cohort was 53 (± 16.1) years. The primary locations were at the level of the tympanic jug (n=2, 50%) and carotid body (n=2, 50%), and only one of the tumors of the carotid body presented pulmonary metastasis at the time of diagnosis. None of the lesions were catecholamine-secreting. Two patients underwent genetic testing, with no mutations identified. The initial clinical presentation was variable highlighting the decrease of visual acuity and headache as symptoms present in all patients. In one of the cases, loss of all teeth of the lower jaw was the presenting symptomatology. Observation with serial imaging, surgical extirpation, radiation, and stereotactic radiosurgery were employed as treatment approaches according to anatomical location and resectability of lesions. As post-therapeutic sequels the persistence of tinnitus and disabling pain stands out, presenting one of the patients neuralgia of the glossopharyngeal. Currently, all patients are under regular surveillance with a median follow up of 10 months. Conclusion: Ultimately, clinical management of these tumors remains challenging owing to heterogeneity in clinical presentation, the existence of multiple treatment alternatives, and potential to cause serious detriment to critical functions and consequently interference with the quality of life of the patients.

Keywords: clinical outcomes, head and neck, management, paragangliomas

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Authors: Keshav Raj Acharya, Thakur Silwal, Neelam C. Poudyal

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Buffer zones, the peripheral areas around the national parks and wildlife reserves, are available for the purpose of benefitting the local inhabitants by providing forest products for subsistence needs of basic forest products outside the protected areas. The forest area within the buffer zone has been managed as a buffer zone community forest (BZCF) for the last 25 years after the approval of the buffer zone management regulation 1996. With a case study of select BZCF in Bardia National Park, this study aims to analyze whether the benefit provided by BZCF is equally available to poor users among other socioeconomic classes of the users. The findings are based on the analysis of cross-sectional data involving household surveys (n=305) and key informants’ interviews (n=10) as well as office records available at different 5 buffer zone community forest user groups offices. Results indicate that despite the provisions of subsidized rates for poor; poor households were more deprived due to higher forest products price particularly, the timber price in buffer zone. Evidence also indicate that due to the increased forest coverage, the incidence of wildlife damage has also increased and impacted the poor more due to lack of land ownership as well as limited alternatives. Clear community forest management guidelines with equitable benefit sharing and compensatory mechanisms to the users of poor socioeconomic class have been identified as a solution to increase the benefit to poor users in BZCFUGs.

Keywords: crop depredation, forest products, users, wellbeing ranking

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Authors: Tingting Liu, Yufeng Wu, Xi Tian, Yu Gong, Tieyong Zuo

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The household solid waste generated by household in Beijing is increasing quickly due to rapid population growth and lifestyle changes. However, there are no rigorous data on the generation and collection of the recyclable household solid wastes. The Beijing city government needs this information to make appropriate policies and plans for waste management. To address this information need, we undertook the first comprehensive study of recyclable household solid waste for Beijing. We carried out a survey of 500 families across sixteen districts in Beijing. We also analyzed the quantities, spatial distribution and categories of collected waste handled by curbside recyclers and permanent recycling centers for 340 of the 9797 city-defined residential areas of Beijing. From our results, we estimate that the total quantity of recyclable household solid waste was 1.8 million tonnes generated by Beijing household in 2013 and 71.6% of that was collected. The main generation categories were waste paper (24.4%), waste glass bottle (23.7%) and waste furniture (14.3%). The recycling rate was varied among different kinds of municipal solid waste. Also based on our study, we estimate there were 22.8 thousand curbside recyclers and 5.7 thousand permanent recycling centers in Beijing. The problems of household solid waste collecting system were inadequacies of authorized collection centers, skewed ratios of curbside recyclers and authorized permanent recycling centers, weak recycling awareness of residents and lack of recycling resources statistics and appraisal system. According to the existing problems, we put forward the suggestions to improve household solid waste management.

Keywords: Municipal waste; Recyclable waste; Waste categories; Waste collection

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Authors: Kgomotso Matobole, Pascal Mwenge, Tumisang Seodigeng

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The global urbanisation and worldwide economic growth have caused a high rate of food waste generation, resulting in environmental pollution. Food waste disposed on landfills decomposes to produce methane (CH₄), a greenhouse gas. Inadequate waste management practices contribute to food waste polluting the environment. Thus effective organic fraction of municipal solid waste (OFMSW) management and treatment are attracting widespread attention in many countries. This problem can be minimised by the employment of anaerobic digestion process, since food waste is rich in organic matter and highly biodegradable, resulting in energy generation and waste volume reduction. The current study investigated the Biomethane Potential (BMP) of the Vaal University of Technology canteen food waste using anaerobic digestion. Tests were performed on canteen food waste, as a substrate, with total solids (TS) of 22%, volatile solids (VS) of 21% and moisture content of 78%. The tests were performed in batch reactors, at a mesophilic temperature of 37 °C, with two different types of inoculum, primary and digested sludge. The resulting CH₄ yields for both food waste with digested sludge and primary sludge were equal, being 357 Nml/g VS. This indicated that food waste form this canteen is rich in organic and highly biodegradable. Hence it can be used as a substrate for the anaerobic digestion process. The food waste with digested sludge and primary sludge both fitted the first order kinetic model with k for primary sludge inoculated food waste being 0.278 day^-1 with R² of 0.98, whereas k for digested sludge inoculated food waste being 0.034 day^-1, with R² of 0.847.

Keywords: anaerobic digestion, biogas, bio-methane potential, food waste

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Authors: Reka Zsuzsanna Mathe

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The globalization and the Europeanization have significantly contributed to a change in the role of the nation-states. The global economic crisis, the climate changes, and the recent refugee crisis, are just a few among many challenges that cannot be effectively addressed by the traditional role of the nation-states. One of the main roles of the states is to solve collective action problems, however due to their changing roles; apparently this is getting more and more difficult. Depending on political culture, collective action problems are solved either through cooperation or conflict. The political culture of Central and Eastern European (CEE) countries is marked by low civic participation and by a weak civil society. In this type of culture collective action problems are likely to be induced through conflict, rather than the democratic process of dialogue and any type of social change is probably to be introduced by social movements. Several studies have been conducted on the social movements of the CEE countries, yet, it is still not clear if the most significant social movements of the region tend to choose rather the cooperative or the conflictual way as action strategy. This study differentiates between a national and a European action field, having different social orders. The actors of the two fields are the broadly understood civil society members, conceptualized as social movements. This research tries to answer the following questions: a) What are the norms that best characterize the CEE countries’ social order? b) What type of actors would prefer a change and in which areas? c) Is there a significant difference between the main actors active in the national versus the European field? The main hypotheses are that there are conflicting norms defining the national and the European action field, and there is a significant difference between the action strategies adopted by social movements acting in the two different fields. In mapping the social order, the study uses data provided by the European Social Survey. Big data of the Global Data on Events, Location and Tone (GDELT) database offers information regarding the main social movements and their preferred type of action. The unit of the analysis is the so called ‘Visegrad 4’ countries: Poland, Czech Republic, Slovakia and Hungary and the research uses data starting from 2005 (after the European accession of these four countries) until May, 2017. According to the data, the main hypotheses were confirmed.

Keywords: big data, Central and Eastern Europe, civil society, GDELT, social movements

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Authors: Teresa Wills, Geraldine Mccarthy, Nicola Cornally

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Background: Obesity is an emerging healthcare epidemic affecting virtually all age and socio-economic groups and is one of the most serious and prevalent diseases of the 21st century. It is a public health challenge because of its prevalence, associated costs and health effects. The increasing prevalence of obesity has created a social perception that overweight body sizes are healthy and normal. This normalization of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation thus impeding recognition of obesity. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. It is widely accepted that the causes of obesity are complex and multi-factorial. Engagement of individuals in weight management programmes is difficult if they do not perceive they have a problem with their weight. Recognition of the problem is a key component of obesity management and identifying the main predictors of behaviour is key to designing health behaviour interventions. Aim: The aim of the research was to determine factors relating to motivation to change behaviours in individuals who perceive themselves to be overweight. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. A sample of 202 men and women who perceived themselves to be overweight participated in the research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Findings: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p = < 0.019) and environmental barriers to physical activity (p= < 0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p < 0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. These findings have important implications for health professionals to help inform their practice and for the development of intervention programmes to prevent and control obesity.

Keywords: motivation to change behaviours, obesity, predictors of behavior, interventions, overweight

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Authors: Sayan Munshi, Subrajit Banerjee, Indrani Chakraborty

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Tourism is a prime sector in the economic development of many countries in particular the Indian sub-continent. Tourism is considered an integral pillar in the Make in India Program under the Government of India. The statistics of tourism in India had evolved from a past with the formation of History. The sector had shown dynamic changes in the statistics since 1980. With the evolving tourism along with destinations, this sector has been converted into the prime industry, as it not only impacts the destination but on the other hand supports the periphery of the destination. Tourism boost revenue and creates varied economic possibilities for the residents. Due to the influx of tourism in the cities, a load on the infrastructure and services can be observed, specifically in the Physical Infrastructure sectors. Due to the floating population in the designated tourism core of the Urban / Peri-Urban area, issues pertaining to Solid waste management and Transportation are highly observed. Thus, a need for capacity building arises for the infrastructure impacted by tourism, which may result in the upgradation of the lifestyle of the city and its permanent users. As tourism of a region has a dependency on the infrastructure, the paper here focuses on the relationship between tourism potential of a region and the infrastructural determinants of the city or region and hence to derive a structural equation supporting the relationship, further determine a coefficient and suggest the domain of in need of upgradation or retrofitting possibilities. The outcome of the paper is to suggest possible recommendations towards the formation of policies on an urban level to support the tourism potential of the region.

Keywords: urban planning, tourism planning, infrastructure, transportation, solid waste management

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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Over the past decade, the non-elective admissions in the UK have increased significantly. Taking into account limited resources (i.e. beds), the related service managers are obliged to manage their resources effectively due to the non-elective admissions which are mostly admitted to inpatient specialities via A&E departments. Geriatric medicine is one of specialities that have long length of stay for the non-elective admissions. This study aims to develop a discrete event simulation model to understand how possible increases on non-elective demand over the next 12 months affect the bed occupancy rate and to determine required number of beds in a geriatric medicine speciality in a UK hospital. In our validated simulation model, we take into account observed frequency distributions which are derived from a big data covering the period April, 2009 to January, 2013, for the non-elective admission and the length of stay. An experimental analysis, which consists of 16 experiments, is carried out to better understand possible effects of case studies and scenarios related to increase on demand and number of bed. As a result, the speciality does not achieve the target level in the base model although the bed occupancy rate decreases from 125.94% to 96.41% by increasing the number of beds by 30%. In addition, the number of required beds is more than the number of beds considered in the scenario analysis in order to meet the bed requirement. This paper sheds light on bed management for service managers in geriatric medicine specialities.

Keywords: bed management, bed occupancy rate, discrete event simulation, geriatric medicine, non-elective admission

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Yael Livneh, Shay Tzafrir, Ilan Meshoulam

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Technological startup companies have been recognized as bearing tremendous potential for business and economic success. However, many entrepreneurs who produce promising innovative ideas fail to implement them as successful businesses. A key argument for such failure is the entrepreneurs' lack of competence in adaptation of the relevant level of formality of human resource management (HRM). The purpose of the present research was to examine multiple antecedents and consequences of HRM formality in growing startup companies. A review of the research literature identified two central components of HRM formality: HR control and professionalism. The effect of three contextual predictors was examined. The first was an intra-organizational factor: the development level of the organization. We based on a differentiation between knowledge exploration and knowledge exploitation. At a given time, the organization chooses to focus on a specific mix of these orientations, a choice which requires an appropriate level of HRM formality, in order to efficiently overcome the challenges. It was hypothesized that the mix of orientations of knowledge exploration and knowledge exploitation would predict HRM formality. The second predictor was the personal characteristics the organization's leader. According the idea of blueprint effect of CEO's on HRM, it was hypothesized that the CEO's cognitive style would predict HRM formality. The third contextual predictor was an external organizational factor: the level of investor involvement. By using the agency theory, and based on Transaction Cost Economy, it was hypothesized that the level of investor involvement in general management and HRM would be positively related to the HRM formality. The effect of formality on trust was examined directly and indirectly by the mediation role of procedural justice. The research method included a time-lagged field study. In the first study, data was obtained using three questionnaires, each directed to a different source: CEO, HR position-holder and employees. 43 companies participated in this study. The second study was conducted approximately a year later. Data was recollected using three questionnaires by reapplying the same sample. 41 companies participated in the second study. The organizations samples included technological startup companies. Both studies included 884 respondents. The results indicated consistency between the two studies. HRM formality was predicted by the intra-organizational factor as well as the personal characteristics of the CEO, but not at all by the external organizational context. Specifically, the organizational orientations was the greatest contributor to both components of HRM formality. The cognitive style predicted formality to a lesser extent. The investor's involvement was found not to have any predictive effect on the HRM formality. The results indicated a positive contribution to trust in HRM, mainly via the mediation of procedural justice. This study contributed a new concept for technological startup company development by a mixture of organizational orientation. Practical implications indicated that the level of HRM formality should be matched to that of the company's development. This match should be challenged and adjusted periodically by referring to the organization orientation, relevant HR practices, and HR function characteristics. A relevant matching could enhance further trust and business success.

Keywords: control, formality, human resource management, organizational development, professionalism, technological startup company

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Authors: Tingting Song

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Wetlands are significant ecosystems that provide a variety of ecosystem services for humans, such as, providing water and food resources, purifying water quality, regulating climate, protecting biodiversity, and providing cultural, recreational, and educational resources. Wetlands also provide benefits, such as reduction of flood, storm damage, and soil erosion. The flood protection ecosystem services of wetlands are often ignored. Due to climate change, the flood caused by extreme weather in recent years occur frequently. Flood has a great impact on people's production and life with more and more economic losses. This study area is in the Tone river basin in the Kanto area, Japan. It is the second-longest river with the largest basin area in Japan, and it is still suffering heavy economic losses from floods. Tone river basin is one of the rivers that provide water for Tokyo and has an important impact on economic activities in Japan. The purpose of this study was to investigate land-use changes of wetlands in the Tone River Basin, and whether there are spatial differences in the value of wetland functions in mitigating economic losses caused by floods. This study analyzed the land-use change of wetland in Tone River, based on the Landsat data from 1980 to 2020. Combined with flood economic loss, wetland area, GDP, population density, and other social-economic data, a geospatial weighted regression model was constructed to analyze the spatial difference of wetland ecosystem service value. Now, flood protection mainly relies on such a hard project of dam and reservoir, but excessive dependence on hard engineering will cause the government huge financial pressure and have a big impact on the ecological environment. However, natural wetlands can also play a role in flood management, at the same time they can also provide diverse ecosystem services. Moreover, the construction and maintenance cost of natural wetlands is lower than that of hard engineering. Although it is not easy to say which is more effective in terms of flood management. When the marginal value of a wetland is greater than the economic loss caused by flood per unit area, it may be considered to rely on the flood storage capacity of the wetland to reduce the impact of the flood. It can promote the sustainable development of wetlands ecosystem. On the other hand, spatial analysis of wetland values can provide a more effective strategy for flood management in the Tone river basin.

Keywords: wetland, geospatial weighted regression, ecosystem services, environment valuation

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Oluibukun G. Ajayi, Joseph O. Odumosu, Oladimeji T. Babafemi, Azeez Z. Opeyemi, Asaleye O. Samuel

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The need for the complete automation of every procedure of surveying and most especially, its engineering applications cannot be overemphasized due to the many demerits of the conventional manual or analogue approach. This paper presents the summarized details of the development of a Route Information Management (RIM) software. The software, codenamed ‘AutoROUTE’, was encoded using Microsoft visual studio-visual basic package, and it offers complete automation of the computational procedures and plan production involved in route surveying. It was experimented using a route survey data (longitudinal profile and cross sections) of a 2.7 km road which stretches from Dama to Lunko village in Minna, Niger State, acquired with the aid of a Hi-Target DGPS receiver. The developed software (AutoROUTE) is capable of computing the various simple curve parameters, horizontal curve, and vertical curve, and it can also plot road alignment, longitudinal profile, and cross-section with a capability to store this on the SQL incorporated into the Microsoft visual basic software. The plotted plans with AutoROUTE were compared with the plans produced with the conventional AutoCAD Civil 3D software, and AutoROUTE proved to be more user-friendly and accurate because it plots in three decimal places whereas AutoCAD plots in two decimal places. Also, it was discovered that AutoROUTE software is faster in plotting and the stages involved is less cumbersome compared to AutoCAD Civil 3D software.

Keywords: automated systems, cross sections, curves, engineering construction, longitudinal profile, route surveying

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Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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Authors: Sang Ho Lee, Yountaik Leem

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This paper reviews Korean cases of smart cities through the analysis framework of strategic foci, characteristics and effects. Firstly, national strategies including c(cyber), e(electronic), u(ubiquitous) and s(smart) Korea strategies were considered from strategic angles. Secondly, the characteristics of smart cities in Korea were looked through the smart cities examples such as Seoul, Busan, Songdo and Sejong cities etc. from the views on the by STIM (Service, Technology, Infrastructure and Management) analysis. Finally, the effects of smart cities on socio-economies were investigated from industrial perspective using the input-output model and structural path analysis. Korean smart city strategies revealed that there were different kinds of strategic foci. c-Korea strategy focused on information and communications network building and user IT literacy. e-Korea strategy encouraged e-government and e-business through utilizing high-speed information and communications network. u-Korea strategy made ubiquitous service as well as integrated information and communication operations center. s-Korea strategy is propelling 4th industrial platform. Smart cities in Korea showed their own features and trends such as eco-intelligence, high efficiency and low cost oriented IoT, citizen sensored city, big data city. Smart city progress made new production chains fostering ICTs (Information Communication Technologies) and knowledge intermediate inputs to industries.

Keywords: Korean smart cities, Korean smart city strategies, STIM, smart service, infrastructure, technologies, management, effect of smart city

Procedia PDF Downloads 367

Authors: Kenneth Harper

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The rapid growth of data-driven decision-making across various industries necessitates advanced solutions to ensure data integrity, scalability, and security. This study introduces a decentralized data platform built on blockchain technology to improve data management processes in high-volume environments such as healthcare and financial services. The platform integrates blockchain networks using Cosmos SDK and Polkadot Substrate alongside decentralized storage solutions like IPFS and Filecoin, and coupled with decentralized computing infrastructure built on top of Avalanche. By leveraging advanced consensus mechanisms, we create a scalable, tamper-proof architecture that supports both structured and unstructured data. Key features include secure data ingestion, cryptographic hashing for robust data lineage, and Zero-Knowledge Proof mechanisms that enhance privacy while ensuring compliance with regulatory standards. Additionally, we implement performance optimizations through Layer 2 scaling solutions, including ZK-Rollups, which provide low-latency data access and trustless data verification across a distributed ledger. The findings from this exercise demonstrate significant improvements in data accessibility, reduced operational costs, and enhanced data integrity when tested in real-world scenarios. This platform reference architecture offers a decentralized alternative to traditional centralized data storage models, providing scalability, security, and operational efficiency.

Keywords: blockchain, cosmos SDK, decentralized data platform, IPFS, ZK-Rollups

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Authors: Esra Polat

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Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists a classical Partial Least Squares Regression (PLSR) in which the dependent variable is a categorical one expressing the class membership of each observation. PLSDA can be applied in many cases when classical discriminant analysis cannot be applied. For example, when the number of observations is low and when the number of independent variables is high. When there are missing values, PLSDA can be applied on the data that is available. Finally, it is adapted when multicollinearity between independent variables is high. The aim of this study is to determine the economic and/or demographic indicators, which are effective in grouping the 28 European Union (EU) member countries and 7 candidate countries (including potential candidates Bosnia and Herzegovina (BiH) and Kosova) by using the data set obtained from database of the World Bank for 2014. Leaving the political issues aside, the analysis is only concerned with the economic and demographic variables that have the potential influence on country’s eligibility for EU entrance. Hence, in this study, both the performance of PLSDA method in classifying the countries correctly to their pre-defined groups (candidate or member) and the differences between the EU countries and candidate countries in terms of these indicators are analyzed. As a result of the PLSDA, the value of percentage correctness of 100 % indicates that overall of the 35 countries is classified correctly. Moreover, the most important variables that determine the statuses of member and candidate countries in terms of economic indicators are identified as 'external balance on goods and services (% GDP)', 'gross domestic savings (% GDP)' and 'gross national expenditure (% GDP)' that means for the 2014 economical structure of countries is the most important determinant of EU membership. Subsequently, the model validated to prove the predictive ability by using the data set for 2015. For prediction sample, %97,14 of the countries are correctly classified. An interesting result is obtained for only BiH, which is still a potential candidate for EU, predicted as a member of EU by using the indicators data set for 2015 as a prediction sample. Although BiH has made a significant transformation from a war-torn country to a semi-functional state, ethnic tensions, nationalistic rhetoric and political disagreements are still evident, which inhibit Bosnian progress towards the EU.

Keywords: classification, demographic indicators, economic indicators, European Union, partial least squares discriminant analysis

Procedia PDF Downloads 281

Authors: Ardak Myrzabekova

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Sentinel epidemiological surveillance (SES) of severe acute respiratory infections (SARI) was introduced in the Republic of Kazakhstan in 2008. The purpose of this study was to analyze SES of flu among SARI patients in the Republic of Kazakhstan during last two flu seasons. Comparative analysis was conducted of SARI morbidity during 40 – 23 weeks of 2014/2015 (season 2014) and 2015/2016 (season 2015) in online base (http:\\ses.dec.kz). In the database during season 2014 were 1,398 SARI patients and 1,985 patients during season 2015. Individual data (clinical, epidemiological and laboratory) of SARI cases were collected based on the questionnaire and were put into the flu electronic system. The studied population was residents of the Republic of Kazakhstan who addressed for medical help in 24 sentinel in-patient clinics in 9 sentinel regions of the country. Swabs from nose and throat were taken for laboratory testing from SARI patients who met the standard case definition. The samples were examined in virology labs of sentinel regions using PCR and 'AmpliSens' test systems made in Russia. The first positive results for flu during season 2014 were obtained on 48 week, during season 2015 – on 46 week. The increase of the number of hospitalized SARI patients was observed during 42 week of 2015 – 01 week of 2016, and during 03 - 06 weeks of 2016, with fluctuating SARI incidence rate from 171 to 444 per 1,000 hospitalized. The highest SARI incidence rate during season 2014 were observed during 01 - 03 weeks of 2015: from 389 to 466 per 1,000 hospitalized. Patients admitted to the ICU during season 2015 were 3.0% (60) SARI patients, compared to 2.7% (38) in 2014 (p=0.3), obtaining oxygen therapy 1.0% (21) compared to 0.3% (5), accordingly, (р=0.009); with shortness of breath 74.8% (1,486) compared to 72.6% (1,015), (р=0.07); with impairment of consciousness 1.0% (21) compared to 0.6% (9), (р=0.11); with muscle pain 19.3% (384) compared to 13.6% (191), (р < 0.001); with joint pain 13.3% (265) compared to 9.3% (131), (p < 0.001). During season 2015 the prevailing subtype of flu А was А/Н1N1-09, it was observed mainly in the age group 30-64: 32.5% (169/520). During season 2014 flu А/Н3N2 was observed mainly in the age group 15-29: 43.6% (106/243). Among children under 14 flu А/Н1N1-09 during season 2015 was 37.3% (194/520), during season 2014 flu А/Н3N2 – 34.9% (85/243). Earlier beginning of the flu season was noted in 2015-2016 and a longer period of hospitalization of SARI patients, with high SARI morbidity rates, unlike season 2014-2015. Season 2015-2016 was characterized by prevailing circulation of virus of flu А/Н1N1-09, mainly in the age group 30-64, and also among children under 14. During season 2014-2015 the virus circulating in the country was А/Н3N2, which was observed mainly in the age group 15-29 and among children under 14.

Keywords: flu, electronic system, sentinel epidemiological surveillance, severe acute respiratory infections

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Authors: Mohammed Ali Ahmed, Vaughan Coffey, Bo Xia

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Quality management systems (QMSs) in the construction industry are often implemented to ensure that sufficient effort is made by companies to achieve the required levels of quality for clients. Attainment of these quality levels can result in greater customer satisfaction, which is fundamental to ensure long-term competitiveness for construction companies. However, the construction sector is still lagging behind other industries in terms of its successful adoption of QMSs, due to the relative lack of acceptance of the benefits of these systems among industry stakeholders, as well as from other barriers related to implementing them. Thus, there is a critical need to undertake a detailed and comprehensive exploration of adoption of QMSs in the construction sector. This paper comprehensively investigates in the construction sector setting, the impacts of all the salient factors surrounding successful implementation of QMSs in building organizations, especially those of external factors. This study is part of an ongoing PhD project, which aims to develop a new framework that integrates both internal and external factors affecting QMS implementation. To achieve the paper aim and objectives, interviews will be conducted to define the external factors influencing the adoption of QMSs, and to obtain holistic critical success factors (CSFs) for implementing these systems. In the next stage of data collection, a questionnaire survey will be developed to investigate the prime barriers facing the adoption of QMSs, the CSFs for their implementation, and the external factors affecting the adoption of these systems. Following the survey, case studies will be undertaken to validate and explain in greater detail the real effects of these factors on QMSs adoption. Specifically, this paper evaluates the effects of the external factors in terms of their impact on implementation success within the selected case studies. Using findings drawn from analyzing the data obtained from these various approaches, specific recommendations for the successful implementation of QMSs will be presented, and an operational framework will be developed. Finally, through a focus group, the findings of the study and the new developed framework will be validated. Ultimately, this framework will be made available to the construction industry to facilitate the greater adoption and implementation of QMSs. In addition, deployment of the applicable recommendations suggested by the study will be shared with the construction industry to more effectively help construction companies to implement QMSs, and overcome the barriers experienced by businesses, thus promoting the achievement of higher levels of quality and customer satisfaction.

Keywords: barriers, critical success factors, external factors, internal factors, quality management systems

Procedia PDF Downloads 187

Authors: Joselyne Rugema, Innocent Twagirayezu, Aimable Nkurunziza, Alice Nyirazigama, Vedaste Bagweneza, Belancilla Nikuze

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Introduction: Burn injuries among children are associated with major complications. Early health care seeking and appropriate management are crucial in saving lives and preventing complications. Objective: To assess home-based management practices and health seeking behaviors among caregivers of children admitted with burn injuries at selected hospitals in Rwanda. Methods: A cross-sectional descriptive study was conducted among caregivers of children admitted with burn injuries at three hospitals in Kigali. A semi-structured questionnaire was used to collect the data that were analyzed using SPSS version 25. Statistical software Results: Most of the children with burn injuries had median age of 36 months, and 89.9% had second-degree burns. 92.4% of burns happened at home and 63.3% were scalds. Only 18% of the caregivers seek care immediately after children’s burn injuries. About 2.5% reported not seeking any care after burn injuries and 3.8% sought care from traditional healers. 65.9% of the participants used wrong practices before seeking care such as applying honey, cooking oil and urine to the burn injuries. Transportation difficulties before consulting health facilities were the main reported faced barriers to success health care (86.1%). Conclusion: Immediate health seeking behavior was low. Wrong practices including application of harmful products to burn injuries are common in the community. There is a need for community based interventions to prevent burn injuries at home and to empower the community with appropriate actions to take after injuries.

Keywords: adolescent pregnancy, qualitative design, childbearing, teenage mothers

Procedia PDF Downloads 62

Authors: Audrius Dedele, Aukse Miskinyte

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Air pollution is a major problem, especially in large cities, causing a variety of environmental issues and a risk to human health effects. In order to observe air quality, to reduce and control air pollution in the city, municipalities are responsible for the creation of air quality management plans, air quality monitoring and emission inventories. Atmospheric dispersion modelling systems, along with monitoring, are powerful tools, which can be used not only for air quality management, but for the assessment of human exposure to air pollution. These models are widely used in epidemiological studies, which try to determine the associations between exposure to air pollution and the adverse health effects. The purpose of this study was to determine the concentration of particulate matter smaller than 10 μm (PM10) in different districts of Kaunas city during winter season. ADMS-Urban dispersion model was used for the simulation of PM10 pollution. The inputs of the model were the characteristics of stationary, traffic and domestic sources, emission data, meteorology and background concentrations were entered in the model. To assess the modelled concentrations of PM10 in Kaunas districts, geographic information system (GIS) was used. More detailed analysis was made using Spatial Analyst tools. The modelling results showed that the average concentration of PM10 during winter season in Kaunas city was 24.8 µg/m3. The highest PM10 levels were determined in Zaliakalnis and Aleksotas districts with are the highest number of individual residential properties, 32.0±5.2 and 28.7±8.2 µg/m3, respectively. The lowest pollution of PM10 was modelled in Petrasiunai district (18.4 µg/m3), which is characterized as commercial and industrial neighbourhood.

Keywords: air pollution, dispersion model, GIS, Particulate matter

Procedia PDF Downloads 269

Authors: Lorcelie B. Taclan, Jolly S. Balila, Maribel Balagtas, Eunice M. Aclan, Myrtle C. Orbon, Emson Y. Taclan, Irenea A. Centeno

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Okara (soy pulp), a by-product and waste from the production of soymilk, tufo and tokwa and soybean-based vegan food products is readily available in the university thrice a week. The Food Factory owned and managed by AUP produces these food products weekly. Generally the study was conducted to determine the drying kinetics of soya pulp using the MCHPD. Specifically, it aimed to establish the time of drying; moisture loss per hour and percent moisture content of soya pulp and to establish the dried okara as an ingredient to other foods. The MCHPD is drying equipment that has an ideal drying condition of 50.00C and 10.0% relative humidity. Fresh and wet soya pulp were weighed at 1.0 kg per tray (21 drying trays), laid on the trays lined with cheese cloth. The MCHPD was set to desired drying conditions. Weight loss was monitored every hour and calculated using standard formulas. Research results indicated that the drying time for soya pulp was 19.0 hours; the % moisture content was reduced from 87.6.0% to 9.7.0% at an average moisture loss of 3.0 g/hr. The nutritional values of okara were favorably maintained with enhanced color. The dried okara was added as an ingredient to other healthy bakery products produced by the AUP Food Factory. Making use of okara would add nutritional values to other food products and would also help waste management concerns inside the university.

Keywords: okara, MCHPD, drying kinetics, nutritional values, waste management

Procedia PDF Downloads 396

Authors: Anderson Chidi Amadioha, Promise Chidi Kenkwo, A. A. Markson

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Cassava (Manihot esculenta Crantz) is an important food and cash crop that provide cheap source of carbohydrate for food, feed and raw material for industries hence a commodity for feature economic development of developing countries. Despite the importance, its production potentials is undermined by disease agents that greatly reduce yield and render it unfit for human consumption and industrial use. Pathogenicity tests on fungal isolates from infected cassava revealed Aspergillus flavus, Rhizopus stolonifer, Aspergillus niger, and Trichodderma viride as rot-causing organisms. Water and ethanol extracts of Piper guineense, Ocimum graticimum, Cassia alata, and Tagetes erecta at 50% concentration significantly inhibited the radial growth of the pathogens in vitro and their development and spread in vivo. Low cassava rot incidence and severity was recorded when the extracts were applied before than after spray inoculating with spore suspension (1x105 spores/ml of distilled water) of the pathogenic organisms. The plant materials are readily available, and their extracts are biodegradable and cost effective. The fungitoxic potentials of extracts of these plant materials could be exploited as potent biopesticides in the management of postharvest fungal deterioration of cassava especially in developing countries where synthetic fungicides are not only scarce but also expensive for resource poor farmers who produce over 95% of the food consumed.

Keywords: cassava, biopesticides, in vitro, in vivo, pathogens, plant extracts

Procedia PDF Downloads 180

Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Shaheeb Abdul Azeez, Siong-Choy Chong

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Background: Talent retention is increasingly becoming a major challenge for many industries due to the high turnover rate. Public higher learning institutions in the Maldives have a similar situation with the turnover of their employees'. This paper is to identify whether Human Resource Management (HRM) practices have any impact on employee retention in public higher learning institutions in the Maldives. Purpose: This paper aims to identify the influence of HRM practices on employee retention in public higher learning institutions in the Maldives. A total of 15 variables used in this study; 11 HRM practices as independent variables (leadership, rewards, salary, employee participation, compensation, training and development, career development, recognition, appraisal system and supervisor support); job satisfaction and motivation as mediating variables; demographic profile as moderating variable and employee retention as dependent variable. Design/Methodology/Approach: A structured self-administered questionnaire was used for data collection. A total of 300 respondents were selected as the study sample, representing the academic and administrative from public higher learning institutions using a stratified random sampling method. AMOS was used to test the hypotheses constructed. Findings: The results suggest that there is no direct effect between the independent variable and dependent variable. Also, the study concludes that no moderate effects of demographic profile between independent and dependent variables. However, the mediating effects of job satisfaction and motivation in the relationship between HRM practices and employee retention were significant. Salary had a significant influence on job satisfaction, whilst both compensation and recognition have significant influence on motivation. Job satisfaction and motivation were also found to significantly influence employee retention. Research Limitations: The study consists of many variables more time consuming for the respondents to answer the questionnaire. The study is focussed only on public higher learning institutions in the Maldives due to no participation from the private sector higher learning institutions. Therefore, the researcher is unable to identify the actual situation of the higher learning industry in the Maldives. Originality/Value: To our best knowledge, no study has been conducted using the same framework throughout the world. This study is the initial study conducted in the Maldives in this study area and can be used as a baseline for future researches. But there are few types of research conducted on the same subject throughout the world. Some of them concluded with positive findings while others with negative findings. Also, they have used 4 to 7 HRM practices as their study framework.

Keywords: human resource management practices, employee retention, motivation, job satisfaction

Procedia PDF Downloads 157