Search results for: forest management certification

Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan

Procedia PDF Downloads 109

Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

Procedia PDF Downloads 256

Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

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We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

Procedia PDF Downloads 459

Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

Procedia PDF Downloads 202

Authors: Lotsmart Fonjong

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The livelihood of rural communities in the West African state of Cameroon, which is largely dictated by natural forces (rainfall, temperatures, and soil), is today threatened by climate change and armed conflict. This paper investigates the extent to which rural communities are aware of climate change, how their perceptions of changes across different agro-ecological zones have impacted farming practices, output, and lifestyles, on the one hand, and the extent to which local armed conflicts are confounding their efforts and adaptation abilities. The paper is based on a survey conducted among small farmers in selected localities within the forest and savanna ecological zones of the conflict-ridden Northwest and Southwest Cameroon. Attention is paid to farmers’ gender, scale, and type of farming. Farmers’ perception of/and response to climate change are analysed alongside local rainfall and temperature data and mobilization for climate justice. Findings highlight the fact that farmers’ perception generally corroborates local climatic data. Climatic instability has negatively affected farmers’ output, food prices, standards of living, and food security. However, the vulnerability of the population varies across ecological zones, gender, and crop types. While these factors also account for differences in local response and adaptation to climate change, ongoing armed conflicts in these regions have further complicated opportunities for climate-driven agricultural innovations, inputs, and exchange of information among farmers. This situation underlines how poor communities, as victims, are forced into many complex problems outsider their making. It is therefore important to mainstream farmers’ perceptions and differences into policy strategies that consider both climate change and Anglophone conflict as national security concerns foe sustainable development in Cameroon.

Keywords: adaptation policies, climate change, conflict, small farmers, cameroon

Procedia PDF Downloads 140

Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 94

Authors: É. Kónya, E. Szabó, I. Bata-Vidács, T. Deák, M. Ottucsák, N. Adányi, A. Székács

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Spice paprika is a major spice commodity in the European Union (EU), produced locally and imported from non-EU countries, reported not only for chemical and microbiological contamination, but also for fraud. The effective interaction between producers’ quality management practices and government and EU activities is described on the example of spice paprika production and control in Hungary, a country of leading spice paprika producer and per capita consumer in Europe. To demonstrate the importance of various contamination factors in the Hungarian production and EU trade of spice paprika, several aspects concerning food safety of this commodity are presented. Alerts in the Rapid Alert System for Food and Feed (RASFF) of the EU between 2005 and 2013, as well as Hungarian state inspection results on spice paprika in 2004 are discussed, and quality non-compliance claims regarding spice paprika among EU member states are summarized in by means of network analysis. Quality assurance measures established along the spice paprika production technology chain at the leading Hungarian spice paprika manufacturer, Kalocsai Fűszerpaprika Zrt. are surveyed with main critical control points identified. The structure and operation of the Hungarian state food safety inspection system is described. Concerted performance of the latter two quality management systems illustrates the effective interaction between internal (manufacturer) and external (state) quality control measures.

Keywords: spice paprika, quality control, reporting mechanisms, RASFF, vulnerable points, HACCP

Procedia PDF Downloads 274

Authors: Serdar Öge, Alpay Karasoy, Özlem Kara

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Although women have merit in their jobs, they still are located very few in the top management in many sectors. There are many causes of such situation. Such a situation creates obstacles; especially invisible ones are called “glass ceiling syndrome”. Also, studies which handle this subject in academic community are very few. The aim of this research is to reach the results about glass ceiling obstacles in terms of female teaching staff (academics) working in higher education institutions. To this end, our study was performed on female academics working at Selcuk University, Konya / Turkey. Our study's main aim can be expressed as to determine whether there are glass ceiling obstacles for female academics working at the higher education institution in question, to measure their glass ceiling perceptions and, thus, to identify what the glass ceiling barrier components for them to promotion to senior management positions are.

Keywords: career, career barriers, glass ceiling syndrome, academics

Procedia PDF Downloads 311

Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

Procedia PDF Downloads 231

Authors: Talha Khan, Surendhar Kumaran, Rajeev Nair

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The development of economical, efficient, and reliable next-generation thermal and water management systems to provide efficient cooling and water management technologies is being pursued application in compact and lightweight spacecraft. The elimination of liquid-vapor phase change-based thermal and water management systems is being done due to issues with the reliability and robustness of this technology. To achieve the motive of implementing the principle of using an innovative evaporator and condenser design utilizing bimodal wicks manufactured using a microsecond pulsed CO₂ laser has been proposed in this study. Cylin drical, multilayered capillary copper wicks with a substrate diameter of 39 mm are additively manufactured using a pulsed laser. The copper particles used for layer-by-layer addition on the substrate measure in a diameter range of 225 to 450 micrometers. The primary objective is to develop a novel, high-quality, fast turnaround, laser-based additive manufacturing process that will eliminate the current technical challenges involved with the traditional manufacturing processes for nano/micro-sized powders, like particle agglomeration. Raster-scanned, pulsed-laser sintering process has been developed to manufacture 3D wicks with controlled porosity and permeability.

Keywords: liquid-vapor phase change, bimodal wicks, multilayered, capillary, raster-scanned, porosity, permeability

Procedia PDF Downloads 175

Authors: Mohd Zamri Che Wanik

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This paper presents the management of the Fault Ride Through event within a Solar Farm during a grid fault. The modeling and simulation of a photovoltaic (PV) with battery energy storage connected to the power network will be described. The modeling approach and the study analysis performed are described. The model and operation scenarios are simulated using a digital simulator for different scenarios. The dynamic response of the system when subjected to sudden self-clearance temporary fault is presented. The capability of the PV system and battery storage riding through the power system fault and, at the same time, supporting the local grid by injecting fault current is demonstrated. For each case, the different control methods to achieve the objective of supporting the grid according to grid code requirements are presented and explained. The inverter modeling approach is presented and described.

Keywords: faut ride through, solar farm, grid code, power network

Procedia PDF Downloads 36

Authors: Arun Dhakal, Geoff Cockfield

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This paper examines the emission potential of different farming practices that the farmers have adopted in Dhanusha District of Nepal and scope of these practices in climate change mitigation. Which practice is more climate-smarter is the question that this aims to address through a life cycle assessment (LCA) of greenhouse gas (GHG) emissions. The LCA was performed to assess if there is difference in emission potential of broadly two farming systems (agroforestry–based and traditional agriculture) but specifically four farming systems. The required data for this was collected through household survey of randomly selected households of 200. The sources of emissions across the farming systems were paddy cultivation, livestock, chemical fertilizer, fossil fuels and biomass (fuel-wood and crop residue) burning. However, the amount of emission from these sources varied with farming system adopted. Emissions from biomass burning appeared to be the highest while the source ‘fossil fuel’ caused the lowest emission in all systems. The emissions decreased gradually from agriculture towards the highly integrated agroforestry-based farming system (HIS), indicating that integrating trees into farming system not only sequester more carbon but also help in reducing emissions from the system. The annual emissions for HIS, Medium integrated agroforestry-based farming system (MIS), LIS (less integrated agroforestry-based farming system and subsistence agricultural system (SAS) were 6.67 t ha-1, 8.62 t ha-1, 10.75 t ha-1 and 17.85 t ha-1 respectively. In one agroforestry cycle, the HIS, MIS and LIS released 64%, 52% and 40% less GHG emission than that of SAS. Within agroforestry-based farming systems, the HIS produced 25% and 50% less emissions than those of MIS and LIS respectively. Our finding suggests that a tree-based farming system is more climate-smarter than a traditional farming. If other two benefits (carbon sequestered within the farm and in the natural forest because of agroforestry) are to be considered, a considerable amount of emissions is reduced from a climate-smart farming. Some policy intervention is required to motivate farmers towards adopting such climate-friendly farming practices in developing countries.

Keywords: life cycle assessment, greenhouse gas, climate change, farming systems, Nepal

Procedia PDF Downloads 599

Authors: Pinzón Uribe Luis Felipe, Chávez Porras Álvaro, Ruge Castellanos Liliana Constanza

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According to global data, solid waste management of has low economic investment for its management in underdeveloped countries; being the main factor the advanced technologies acknowledge for proper operation and at the same time the technical development. Has been evidenced that communities have a distorted perception of the role and legalized final destinations for waste or "Landfill" places specific management; influenced primarily by their physical characteristics and the information that the media provide of these, as well as their wrong association with "open dumps". One of the major inconveniences in these landfills is the leachate sludge management from treatment plants; as this exhibit a composition highly contaminating (physical, chemical and biological) for the natural environment due to improper handling and disposal. This is the case Landfill Doña Juana (RSDJ), Bogotá, Colombia, considered among the largest in South America; where management problems have persisted for decades, since its creation being definitive on the concept that society has acquired about this form of waste disposal and improper leachate handling. Within this research process for treating phytoremediation alternatives were determined by using plants that are able to degrade heavy metals contained in these; allowing the resulting sludge to be used as a seal in the final landfill cover; within a restoration process, providing option to solve the landscape contamination problem, as well as in the communities perception and conflicts that generates landfill. For the project chemical assays were performed in sludge leachate that allowed the characterization of metals such as chromium (Cr), lead (Pb), arsenic (As) and mercury (Hg), in order to meet the amount in the biosolids regard to the provisions of the USEPA 40 CFR 503. The evaluations showed concentrations of 102.2 mg / kg of Cr, 0.49 mg / kg Pb, 0.390 mg / kg of As and 0.104 mg / kg of Hg; being lower than of the standards. A literature review on native plant species suitable for an alternative process of phytoremediation, these metals degradation capable was developed. Concluding that among them, Vetiveria zizanioides, Eichhornia crassipes and Limnobium laevigatum, for their hiperacumulativas in their leaves, stems and roots characteristics may allow these toxic elements reduction of in the environment, improving the outlook for disposal.

Keywords: health, filling slurry of leachate, heavy metals, phytoremediation

Procedia PDF Downloads 312

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 104

Authors: Shelley Harrington

Abstract:

As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

Procedia PDF Downloads 253

Authors: Qingqing Feng, S. Thomas Ng, Frank J. Xu, Jiduo Xing

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Faced with unprecedented challenges including aging assets, lack of maintenance budget, overtaxed and inefficient usage, and outcry for better service quality from the society, today’s infrastructure systems has become the main focus of many metropolises to pursue sustainable urban development and improve resilience. Digital twin, being one of the most innovative enabling technologies nowadays, may open up new ways for tackling various infrastructure asset management (IAM) problems. Digital twin application for IAM, as its name indicated, represents an evolving digital model of intended infrastructure that possesses functions including real-time monitoring; what-if events simulation; and scheduling, maintenance, and management optimization based on technologies like IoT, big data and AI. Up to now, there are already vast quantities of global initiatives of digital twin applications like 'Virtual Singapore' and 'Digital Built Britain'. With digital twin technology permeating the IAM field progressively, it is necessary to consider the maturity of the application and how those institutional or industrial digital twin application processes will evolve in future. In order to deal with the gap of lacking such kind of benchmark, a draft maturity model is developed for digital twin application in the IAM field. Firstly, an overview of current smart cities maturity models is given, based on which the draft Maturity Model of Digital Twin Application for Infrastructure Asset Management (MM-DTIAM) is developed for multi-stakeholders to evaluate and derive informed decision. The process of development follows a systematic approach with four major procedures, namely scoping, designing, populating and testing. Through in-depth literature review, interview and focus group meeting, the key domain areas are populated, defined and iteratively tuned. Finally, the case study of several digital twin projects is conducted for self-verification. The findings of the research reveal that: (i) the developed maturity model outlines five maturing levels leading to an optimised digital twin application from the aspects of strategic intent, data, technology, governance, and stakeholders’ engagement; (ii) based on the case study, levels 1 to 3 are already partially implemented in some initiatives while level 4 is on the way; and (iii) more practices are still needed to refine the draft to be mutually exclusive and collectively exhaustive in key domain areas.

Keywords: digital twin, infrastructure asset management, maturity model, smart city

Procedia PDF Downloads 142

Authors: Ahuva Even-Zohar

Abstract:

Context: Families living in poverty often struggle with poor financial management and accumulating debts. Social workers play a crucial role in assisting these families, but they typically receive no formal training in financial management. Research Aim: The aim of this study was to assess the impact of a voluntary organization called Paamonim on social work students' attitudes toward providing material support and assistance in financial management to families living in poverty. Additionally, the study aimed to evaluate the students' perception of the workshop's contribution and their actual use of the tools acquired during the training. Methodology: The study involved 134 social work students, with 55 in a regular program and 79 in a retraining program. The first stage of the study involved the students receiving an explanation of the research, ensuring confidentiality, and signing informed consent. The students completed two questionnaires: The Student Attitudes Questionnaire and a sociodemographic questionnaire. In the second stage, three months after the workshop, the students completed the questionnaires again, along with a feedback questionnaire. Findings: The study found that there were no significant differences in the students' attitudes toward providing material support and proper financial management to families living in poverty before and after the workshop. However, their attitudes remained positive, at a medium level or higher. The students reported that the workshop provided them with tools to assist families in poverty, and they used these tools to some extent in their practical training. They found the workshop interesting and acknowledged its importance in raising awareness about budget management and enriching their knowledge of money management. The students acknowledged the workshop's effectiveness but mentioned that it was too short. Theoretical Importance: This study highlights the importance of developing programs to help families living in poverty manage their household finances. The workshop enriched the students' knowledge and skills, which are vital for their role as social workers working with families in poverty to rehabilitate their financial situations. Data Collection and Analysis Procedures: The students completed self-report questionnaires before and after the workshop, providing insights into their attitudes and perception about the role of social workers in providing material support for families living in poverty and helping them manage their household finances. Statistical analysis was conducted to compare the students' attitudes pre and post-workshop, and a feedback questionnaire assessed the students' perception of the contribution of the workshop. Question Addressed: This study addressed the question of whether a workshop on financial management can positively impact social work students' attitudes and skills in assisting families living in poverty with their household finances. Conclusion: Despite being short and consisting of only one session, the workshop proved to be valuable in enriching the students' knowledge and providing them with important tools for their role as social workers. The students reported positive attitudes toward providing material support and financial assistance to families in need. The practical recommendation is to continue offering such workshops as part of the social work curriculum to further enhance students' abilities to help families manage their finances effectively.

Keywords: financial literacy, poverty, social work students, workshop

Procedia PDF Downloads 52

Authors: María Jesús Luengo-Valderrey, Mónica Moso-Díez

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In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Keywords: high and medium technology sector, innovation, knowledge management, Spanish companies

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Authors: Shau-Ping Shiu, Shu-Ling Lin

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Pregnancy lead a process of changing in the endocrine system. Either pregnancy itself or the surrounding affect such as the attitude of family to the pregnant lady can bring lots of stress. Sever stress may lead pregnant women display serious mental problem such as mood swings, impulsivity, and abnormal behavior. A method of self management of stress(SMS) has been proved that help patient of cancer in release their stress. This study were going to use SMS to help pregnant women. Methods: In this study, 42 ladies in the first to third months of pregnancy process applied to join SMS of program have divided into 21 participants in both control and experimental group by draw. 24 sessions of Yoga program were conducted once a week for 6 months for experimental group. Verbatim used to gather more feedbacks from the interview followed by each Yoga sessions. Brief symptom Rating scale also conducted pre and post experiment for 42 participations. Results: Overall score of Brief Symptom Rating Scale reduced 17.82 points and suicide drop 9 points in experimental group, compared to the control group increasing 10.24 point of overall score and suicide add 7 points. Feedback from interviews showed participations improved in emotion, physical health and stress management. They indicated having more positive emotion daily, having better gastrointestinal peristalsis movement, releasing back tention, well weight control, reducing stress and changing the quality of interpersonal relationships. Conclusion: SMS of Yoga program in this study included four key training directions which were stimulation, relaxation, awareness and pranayama lead a great improvment of stress management for pregnant lady. Throughout this Yoga program, women learned to ignite eustress, remove distress, create calmness and breath slows down. As the result, Yoga program has helped women in experiment group lower their tension, and bring the extra benifits in emotion and relationships. It support women to overcome their pregnancy. Suggestion: An unexpected result of this study showed all participants had no morning sickness since they engaged in SMS program, and no one absent from course due to the benefits of it. We strongly suggest that SMS of Yoga program can be a add of medication for women in pregnancy, however, the position of Forward in the SMS sequence has been point out pressing participant’s stomach, which can be replace to Bridge position to comfort participants.

Keywords: self-management of stress(SMS), yoga program, pregnant women, early pregnancy

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Authors: Vidya Badrinarayanan, Appa Iyer Sivakumar

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The coronavirus pandemic has sent an important message that future project teams need to be trained to work under virtual conditions, which has already become the new norm in organizations across the world. As organizations increasingly rely on virtual teams to achieve project objectives, it is essential to comprehend how leadership functions in virtual project teams. The purpose of this research is to analyze the leadership behaviors exhibited by project managers for building trust and managing conflicts effectively in virtual project teams. This convergent parallel mixed method research was conducted by surveying 185 virtual leaders and conducting a semi-structured interview with 13 senior virtual leaders involved in managing projects across the industry sectors. The research findings indicate that establishing trust and managing conflicts were ranked as significant challenges in leading virtual project teams in the post-pandemic era. In contrast to earlier findings, our research findings suggest that productivity was not ranked as a significant challenge in leading virtual project teams. This indeed is a positive finding for organizations to consider adopting virtual project teams in the long run. Additionally, the research findings recommend that virtual leaders need to strive to build a high-trust environment and develop effective conflict resolution skills to improve the effectiveness of virtual project teams. As the project management profession struggles with low project success rates, mixed-method research aims to contribute to the knowledge in the growing research area of virtual project leadership. This research contributes to the knowledge by offering first-person accounts from senior virtual leaders on the innovative strategies they had implemented for building trust and resolving conflicts effectively in the virtual project when there were limited opportunities for face-to-face interaction on account of the pandemic. In addition, the leadership framework created as a part of this research for trust development and conflict management in virtual project teams will guide project managers to improve virtual project team effectiveness.

Keywords: conflict management, trust building, virtual leadership, virtual teams

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Authors: Rubijesmin Abdul Latif, Norshakirah Abdul Aziz, Mohd Taufik Abdul Jalil

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This paper focuses on the impact of online games among Malaysian undergraduate students. The purpose of this study is to investigate whether online games (especially MMOGs) impacted students positively or vice versa; focusing on three elements (time management, social life, and emotion). A total of 83 respondents comprised from 14 Malaysia universities, randomly selected undergraduate students who play MMOGs (casual and hardcore gamers i.e. addiction to MMOGs) were involved in this study. The results showed that MMOGs have only negative impact on students capabilities in time management, meanwhile as for the elements social life and emotion, MMOGs do not affect them negatively.

Keywords: internet game addiction, online games, MMOGs, impact, undergraduate students

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Authors: Fahad Suleiman

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Agriculture has been the mainstay of the nation’s economy in Nigeria. It provides food for the ever rapidly increasing population and raw materials for the industries. People especially the rural dwellers are gainfully employed on their crop farms and small-scale livestock farms for income earning. In farming, availability of funds and time management are one of the major factors that influence the system of farming in Nigeria in which mathematical science knowledge was highly required in order for farms to be managed effectively. Farmers often applied mathematics, almost every day for a variety of tasks, ranging from measuring and weighing, to land marking. This paper, therefore, explores some of the ways math is used in farming. For instance, farmers use arithmetic variety of farm activities such as seed planting, harvesting crop, cultivation and mulching. It is also important in helping farmers to know how much their livestock weighs, how much milk their cows produce and crop yield per acres, among others.

Keywords: agriculture, application, economic, farming, mathematics

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Authors: Chen Xiatong

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The study aims to explore the interrelationship between corporate governance factors and firm performance in Mainland China using a mixed-method approach. To clarify the current effectiveness of corporate governance, uncover the complex interrelationships between governance factors and firm performance, and enhance understanding of corporate governance strategies in Mainland China. The research involves quantitative methods like statistical analysis of governance factors and firm performance data, as well as qualitative approaches including policy research, case studies, and interviews with staff members. The study aims to reveal the current effectiveness of corporate governance in Mainland China, identify complex interrelationships between governance factors and firm performance, and provide suggestions for companies to enhance their governance practices. The research contributes to enriching the literature on corporate governance by providing insights into the effectiveness of governance practices in Mainland China and offering suggestions for improvement. Quantitative data will be gathered through surveys and sampling methods, focusing on governance factors and firm performance indicators. Qualitative data will be collected through policy research, case studies, and interviews with staff members. Quantitative data will be analyzed using statistical, mathematical, and computational techniques. Qualitative data will be analyzed through thematic analysis and interpretation of policy documents, case study findings, and interview responses. The study addresses the effectiveness of corporate governance in Mainland China, the interrelationship between governance factors and firm performance, and staff members' perceptions of corporate governance strategies. The research aims to enhance understanding of corporate governance effectiveness, enrich the literature on governance practices, and contribute to the field of business management and human resources management in Mainland China.

Keywords: corporate governance, business management, human resources management, board of directors

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Authors: Nahid Hassanshahi, Ayoub Karimi-Jashni, Nasser Talebbeydokhti

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Due to the economic and environmental benefits of producing less waste, the US Environmental Protection Agency (EPA) introduces source reduction as one of the most important means to deal with the problems caused by increased landfills and pollution. Waste reduction involves all waste management methods, including source reduction, recycling, and composting, which reduce waste flow to landfills or other disposal facilities. Source reduction of waste can be studied from two perspectives: avoiding waste production, or reducing per capita waste production, and waste deviation that indicates the reduction of waste transfer to landfills. The present paper has investigated home composting as a managerial solution for reduction of waste transfer to landfills. Home composting has many benefits. The use of household waste for the production of compost will result in a much smaller amount of waste being sent to landfills, which in turn will reduce the costs of waste collection, transportation and burial. Reducing the volume of waste for disposal and using them for the production of compost and plant fertilizer might help to recycle the material in a shorter time and to use them effectively in order to preserve the environment and reduce contamination. Producing compost in a home-based manner requires very small piece of land for preparation and recycling compared with other methods. The final product of home-made compost is valuable and helps to grow crops and garden plants. It is also used for modifying the soil structure and maintaining its moisture. The food that is transferred to landfills will spoil and produce leachate after a while. It will also release methane and greenhouse gases. But, composting these materials at home is the best way to manage degradable materials, use them efficiently and reduce environmental pollution. Studies have shown that the benefits of the sale of produced compost and the reduced costs of collecting, transporting, and burying waste can well be responsive to the costs of purchasing home compost machine and the cost of related trainings. Moreover, the process of producing home compost may be profitable within 4 to 5 years and as a result, it will have a major role in reducing waste management.

Keywords: compost, home compost, reducing waste, waste management

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Authors: N. Anusree, P. Sughosh, G. L. Sivakumar Babu

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Municipalities throughout the world are marred with serious issues related to the Municipal Solid Waste (MSW) collection, treatment, and safe disposal. While the Waste Management sector contributes around 3-9 % of the overall anthropogenic methane emission, measures towards mitigating these emissions are rarely given attention in developing countries. In the case of Bangalore, India, around 5680 tons of MSW is generated in a day, and its collection and treatment efficiency are around 90-95 % and 26.4 %, respectively. About 33.4 % of the waste collected is directly landfilled without any treatment, further aggravating the situation. The potential of reducing the emissions emanating from the MSW of Bangalore city without any severe consequences on the current MSW management practices is evaluated in this study. Three emission scenarios consisting of the baseline condition (current practices – Case-1), the application of biocovers for methane oxidation in the dumpsites (case-2), and the diversion of Organic Fraction of MSW (OFMSW) along with the application of biocovers (case-3) are evaluated and compared with each other. The emissions are calculated based on the aerobic and anaerobic stochiometric relations for the three scenarios. Laboratory scale column studies are carried out to determine the methane oxidation potential of three different biocover material (digested MBT (mechanically biologically treated) waste, Fresh MBT waste, and charcoal amended with fresh MBT waste). The results shown that around 40 % and 83 % reduction in carbon emissions can be achieved in case 3 and 2 in comparison to the baseline condition. The study clearly shows that with minor changes in the waste management practices, substantial reductions in the carbon emissions can be attained in Bangalore City.

Keywords: MSW, biocover, composting, carbon emission

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Authors: Vinicius Marzall, Jussanã Milograna

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The urban drainwatering remains a major challenge for most of the Brazilian cities. Not so different of the most part, Goiania, a state capital located in Midwest of the country has few legislations about the subject matter and only one registered solution of compensative techniques for drainwater. This paper clam to show some solutions which are adopted in other Brazilian cities with consolidated legislation, suggesting technics about detention tanks in a building sit. This study analyzed and compared the legislation of Curitiba, Porto Alegre e Sao Paulo, with the actual legislation and politics of Goiania. After this, were created models with adopted data for dimensioning the size of detention tanks using the envelope curve method considering synthetic series for intense precipitations and building sits between 250 m² and 600 m², with an impermeabilization tax of 50%. The results showed great differences between the legislation of Goiania and the documentation of the others cities analyzed, like the number of techniques for drainwatering applied to the reality of the cities, educational actions to awareness the population about care the water courses and political management by having a specified funds for drainwater subjects, for example. Besides, the use of detention tank showed itself practicable, have seen that the occupation of the tank is minor than 3% of the building sit, whatever the size of the terrain, granting the exit flow to pre-occupational taxes in extreme rainfall events. Also, was developed a linear equation to measure the detention tank based in the size of the building sit in Goiania, making simpler the calculation and implementation for non-specialized people.

Keywords: clean technology, legislation, rainwater management, urban drainwater

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Authors: Rohit Khankhoje

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The rapid evolution of software development practices has given rise to an increasing demand for efficient and effective test automation. The paper titled "Mastering Test Automation: Bridging Gaps for Seamless QA" delves into the crucial aspects of test automation, addressing the obstacles faced by organizations in achieving flawless quality assurance. The paper highlights the importance of bridging knowledge gaps within organizations, emphasizing the necessity for management to acquire a deeper comprehension of test automation scenarios, coverage, report trends, and the importance of communication. To tackle these challenges, this paper introduces innovative solutions, including the development of an automation framework that seamlessly integrates with test cases and reporting tools like TestRail and Jira. This integration facilitates the automatic recording of bugs in Jira, enhancing bug reporting and communication between manual QA and automation teams as well as TestRail have all newly added automated testcases as soon as it is part of the automation suite. The paper demonstrates how this framework empowers management by providing clear insights into ongoing automation activities, bug origins, trend analysis, and test case specifics. "Mastering Test Automation" serves as a comprehensive guide for organizations aiming to enhance their quality assurance processes through effective test automation. It not only identifies the common pitfalls and challenges but also offers practical solutions to bridge the gaps, resulting in a more streamlined and efficient QA process.

Keywords: automation framework, API integration, test automation, test management tools

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Authors: Wongsim Manirath

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In order to implement AIS adoption successfully, it is important to consider the quality of information management and understand Information Quality (IQ) factors influencing AIS adoption. This research aims to explore ways of managing AIS adoption to investigate the adoption of accounting information systems within organisations. The study has led to the development of a framework for understanding the AIS adoption process in an organisation. This research used qualitative, interpretive evidence. This framework was developed from case studies and by collecting qualitative data (interviews). This research has conducted 10 case studies to study how IQ is managed through the accounting information system adoption process. A special focus is placed on determining how organisation size influences the information quality practices. The finding is especially useful to SMEs as many SMEs have the desire to grow bigger. By better dealing with IQ issues, there could be a successful future.

Keywords: data quality, information quality, accounting information system, information management

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Authors: Emmanuel Olasope Bamigboye, Ismail Oladeji Oladosu

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Local people of south-western Nigeria like in other climes, continue to be confronted with the vagaries of changing environments. Through the modification of existing practice and shifting resource base, their strategies for coping with change have enabled them to successfully negotiate the shifts in climate change and the environment. This article analyses indigenous adaptation strategies for climate change with a view to enhancing sustainable crop farming in south –western Nigeria. Multi-stage sampling procedure was used to select 340 respondents from the two major ecological zones (Forest and Derived Savannah) for good geographical spread. The article draws on mixed methods of qualitative research, literature review, field observations, informal interview and multinomial logit regression to capture choice probabilities across the various options of climate change adaptation options among arable crop farmers. The study revealed that most 85.0% of the arable crop farmers were males. It also showed that the use of local climate change adaptation strategies had no relationship with the educational level of the respondents as 77.3% had educational experiences at varying levels. Furthermore, the findings showed that seven local adaptation strategies were commonly utilized by arable crop farmers. Nonetheless, crop diversification, consultation with rainmakers and involvement in non-agricultural ventures were prioritized in the order of 1-3, respectively. Also, multinomial logit analysis result showed that at p ≤ 0.05 level of significance, household size (P<0.08), sex (p<0.06), access to loan(p<0.16), age(p<0.07), educational level (P<0.17) and functional extension contact (P<0.28) were all important in explaining the indigenous climate change adaptation utilized by the arable crops farmers in south-western Nigeria. The study concluded that all the identified local adaptation strategies need to be integrated into the development process for sustainable climate change adaptation.

Keywords: crop diversification, climate change, adaptation option, sustainable, small farmers

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Authors: Hafiz Haseeb Nisar, Maryam Bilal

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This qualitative study was conducted to investigate the underlying dynamics, key success factors and characteristics of Pakistani business leaders. The sample included 5 top businessmen from different business sectors. They were approached through the magazine “Manager Today” office in Lahore. Semi-structured interview technique was used to understand their experiences, attitudes, styles of management and key factors in their business success. Grounded theory was employed to analyze data. The following themes emerged as characteristics of business leaders: optimism, assertiveness, professionalism, effective management style, business knowledge/ excellence, supportive family and strong faith in God. It was noted that all these were interlinked, which leads the businessmen to become a successful business tycoon of this country. The importance of this study rests in its eastern contribution to the theoretical framework of the psychology of business leaders and particularly these findings will help to realize the basic key factors of success behind a business leader in Pakistan.

Keywords: business psychology, characteristics, key personality factors, leadership

Procedia PDF Downloads 130