Search results for: financial market prediction

Authors: Fatemeh Rouhi, Hadi Nassiri

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Earning forecast is a key element in economic decisions but there are some situations, such as conflicts of interest in financial reporting, complexity and lack of direct access to information has led to the phenomenon of information asymmetry among individuals within the organization and external investors and creditors that appear. The adverse selection and moral hazard in the investor's decision and allows direct assessment of the difficulties associated with data by users makes. In this regard, the role of trustees in corporate governance disclosure is crystallized that includes controls and procedures to ensure the lack of movement in the interests of the company's management and move in the direction of maximizing shareholder and company value. Therefore, the earning forecast of companies in the capital market and the need to identify factors influencing this study was an attempt to make relationship between moral hazard and corporate governance with earning forecast quality companies operating in the capital market and its impact on Earnings Forecasts quality by the company to be established. Getting inspiring from the theoretical basis of research, two main hypotheses and sub-hypotheses are presented in this study, which have been examined on the basis of available models, and with the use of Panel-Data method, and at the end, the conclusion has been made at the assurance level of 95% according to the meaningfulness of the model and each independent variable. In examining the models, firstly, Chow Test was used to specify either Panel Data method should be used or Pooled method. Following that Housman Test was applied to make use of Random Effects or Fixed Effects. Findings of the study show because most of the variables are positively associated with moral hazard with earnings forecasts quality, with increasing moral hazard, earning forecast quality companies listed on the Tehran Stock Exchange is increasing. Among the variables related to corporate governance, board independence variables have a significant relationship with earnings forecast accuracy and earnings forecast bias but the relationship between board size and earnings forecast quality is not statistically significant.

Keywords: corporate governance, earning forecast quality, moral hazard, financial sciences

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Authors: Muhammad Shehu Garba

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The financial statements of the firms between the periods of 2013 and 2022 were collected using the secondary method of data collection, and the study aims to investigate the effect of ownership structure on the financial performance of listed industrial goods companies in Nigeria. 10 firms were used as the study's sample size. The study used panel data variables of the study. The ownership structure is measured with managerial ownership, institutional ownership and foreign ownership, while financial performance is measured with return on asset and return on equity; the study made use of control variables leverage and firm size. The result shows a multivariate relationship that exists between variables of the study, which shows ROA has a positive correlation with ROE (0.4053), MO (0.2001), and FS (0.3048). It has a negative correlation with FO (-0.1933), IO (-0.0919), and LEV (-0.3367). ROE has a positive correlation with ROA (0.4053), MO (0.2001), and FS (0.2640). It has a negative correlation with FO (-0.1864), IO (-0.1847), and LEV (-0.0319). It is recommended that firms should focus on increasing their ROA. Firms should also consider increasing their MO, as this can help to align the interests of managers and shareholders. Firms should also be aware of the potential impact of FO and IO on their ROA.

Keywords: firm size, ownership structure, financial performance, leaverage

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Authors: Xiao Zhou, Jianlin Cheng

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A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

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Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar

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Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.

Keywords: machine learning, hydro-gravimetry, ground water level, predictive model

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Authors: Elham Fakhrpoor, Daryush Mohammadi Zanjirani, Maziyar Nojaba

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Business process reengineering is one of the most important strategies in banks in recent years that not only it increases customers’ satisfaction, but also it increases performance of banks. The purpose of elementary (initial) business process reengineering is reinforcing banks abilities to obtain new customers and making long-term relationships with existed customers and increasing customers’ satisfaction among service quality in global level. Banks specially the private ones are the main streams of state, because cash flow is necessary to survive a state. What guarantees survival and permanency of financial institutes’ activities is providing favorite, certain, and proper services. Capital market being small and state financial system being bank-oriented needs optimum usage from banks. According to this fact and role and importance of developing banking system, the present study tried to offer a constructed model using Lisrel and also spss software to evaluate effects of business process reengineering on performance of private banks. We have one min hypothesis and four sub-hypotheses. The main hypothesis says reengineering factors have positive effects on bank performances (balanced- scores card aspects). These hypotheses were tested by structural equations modeling.

Keywords: effect, business, reengineering, private bank

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Authors: K. Roushanger, A. Soleymanzadeh

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Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

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Authors: Xue Junwei

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In the global economy, multinational corporations face challenges due to cultural differences impacting consumer behavior. Understanding these influences is vital for effective business decisions in the Chinese market. This study aims to analyze how cultural differences affect consumer behavior when multinational corporations enter the Chinese market, using cultural dimensions theory to derive marketing mix strategies. The study employs statistical analysis of cultural dimensions to investigate the impact on consumer behavior and derive marketing strategies for multinational corporations entering the Chinese market. Furthermore, this study enhances the study by incorporating qualitative data to complement the statistical analysis, providing a more comprehensive understanding of cultural impacts on consumer behavior. The study reveals significant implications of cultural differences on consumer behavior and provides insights into tailored marketing mix strategies for multinational corporations in the Chinese market. This research contributes to the theoretical understanding of how cultural dimensions influence consumer behavior and provides practical implications for multinational corporations entering the Chinese market. Data on cultural dimensions are collected and analyzed statistically and qualitatively to understand their impact on consumer behavior and derive effective marketing strategies. This study concludes that cultural differences have a profound impact on consumer behavior in the Chinese market, and understanding these nuances is crucial for the success of multinational corporations. Tailored marketing strategies are essential for navigating these cultural challenges.

Keywords: marketing, multinational company, globalization, cultural differences

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Authors: Disha Batra

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With the advent of economic reforms in India in 1992, economic journalism in India has undergone a sea change along with the rise in the Indian economy. Squeezing out of economic news stories (economy-in-general) over business (individual corporate stories) and financial (financial and equity markets) news stories have been done and are still underway. The objective of the study is to explore how economic journalism – news stories about macroeconomic issues or economy-in-general has changed over the past three decades with the emergence of LPG (Liberalisation, Privatisation, and Globalisation) policies in India. The purpose of the study is to examine to what extent business and financial news are constricting economic news which is done by analysing news stories and content of business papers. The study is based on the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017. The parametric analysis of the different parameters (source of information, sub-topic, a dominant source in economic news, layout and framing, etc.) has been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. The study revealed that stories concerning broader issues about the economy which are likely to be of public concern had been dropped. The paper further indicates an upward trend for the stories concerning individual corporate, equity, and financial markets. Findings of the study raise concern over the indicated disparity between economic and business news stories which may further limit the information that people need in order to make well-versed decisions.

Keywords: business-papers, business news, economic news, financial news

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Authors: Ofuan James Ilaboya, Okhae J. Ibhadode

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The objective of this paper is to theoretically examine the truism of the “true and fair view” in the context of financial reporting. The paper examines the concepts such as true, fair, true and fair view, problems of true and fair view, the origin/history of true and fair view, review of attributes and key issues relating to true and fair view. The methodological approach adopted in this paper is library-based research, focusing on the review of relevant and related extant literature. The findings based on the review of relevant and related literature is suggestive of the fact that the true and fair concept in financial reporting environment is contentious. The study concludes that given the circumstances as chronicled on this paper, it is evident that the truism of the true and fair view of the auditor’s opinion is under serious threat. The way forward may be for the auditor to certify the accuracy and the correctness of the financial statement. While this position being canvassed here may help to substantially bridge the age-long expectation gap, it may as well require an upward review of the current audit fee structure in order to be able to operationalize the onerous task of certifying the accuracy and correctness of the financial statement. This position is contentious and will require a robust consideration which is not within the purview of the present review.

Keywords: fiduciary duty, financial statement, true and correct, true and fair

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Authors: Sunday Odunaiya

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The statistics of banks in operation in this current dispensation compared to some decades ago has brought about a lot of changes on the face of the financial system. The demand of customers, technological advancement, and government policies among others has therefore generated a lot of heat for financial sector’s growth, sustenance and survival. This paper discusses mergers and acquisitions (M&A) in banking sector using West Africa as a yardstick of evaluation. It explains rigorously the conditions that warrant mergers and acquisitions in the banking sector, its effect, and how to ensure mergers and acquisitions effectiveness in the banking sector. The conceptual and empirical review of the relevant literature were done systematically while value-increasing and value-decreasing theories were used to substantiate the discourse. Findings of this paper show that mergers and acquisitions is a practical and conscious activity in Nigeria, Ghana and Ivory Coast from earliest time till date with tremendous turnaround in the financial sector. It was found out that M&A is consensually arrived at by the targets and the acquirer on a value-based account. In other words, merger and acquisition is a deliberate decision reached by the management of such bank for a ‘just cause’.

Keywords: acquisitions, merger, management, financial sector

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Authors: Baeza S. Roberto

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The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

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Authors: Yasmin Umar Assegaf, Falikhatun, Salamah Wahyuni

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This study aims to provide empirical evidence about the influence of Islamic Corporate Social Responsibility Disclosures of the financial performance of Islamic banking with the characteristics of the company, as a control variable in Islamic banking in Indonesia. ICSR disclosures are an independent variable, while the Financial Performance is the dependent variable (proxied by Return on Assets (ROA), Return on Equity (ROE), Income Expense Ratio (IER), and Non-net Interest Margin (NIM). The control variables used are firm size, firm age and the type of audit. The population of the study was all Islamic Banks (BUS) operate in Indonesia. The research sample is Islamic Commercial Bank which has existed in Indonesia since 2002 and publishes financial statements between the years of 2007-2011. The sample of the study were include 31 Annual Report published. The results of this study concluded that there are significant influences between the ICSR Disclosures and financial performance. The disclosure is partially effect on ROA, IER and NIM, whereas there is no influence on ROE. Further result shows that all control variables (Firm Size, Age, and Type of Audit Companies) does not have any influence on ICSR Disclosures in Indonesia. This research gives a suggestion for further research to compare these ICSR disclosures in Indonesia with ICSR disclosures in other countries that have Islamic banking, by using other measure variables of financial performance, to get more comprehensive model and real picture.

Keywords: ROA, ROE, IER, NIM, company size, age of the company, audit type, Islamic banking

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Authors: Antoine F. Dedewanou, Eric N. Ekpinda

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We investigate whether and how deposit insurance program affects savings decisions in the Economic Community of Central African States (ECCAS). Specifically, using the World Bank’s 2014 and 2011 Global Financial Inclusion (Global Findex) databases, we apply special regressor approach. We find that the deposit insurance program increases significantly, everything else equal, the probability that people save their money at a financial institution by 11 percentage points in Gabon, by 22.2 percentage points in DR Congo and by 15.1 percentage points in Chad. These effects are matched with positive effects of age and education level. But in Cameroon, the effect of deposit insurance is not significant. The policies aimed at fostering financial inclusion will be more effective if there is a deposit insurance scheme in place, along with awareness among young people, and education programs. JEL Classification: G21, O12, O16

Keywords: deposit insurance, savings, special regressor, ECCAS countries

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Kennedy Efosa Ehimwenma, Sujatha Krishnamoorthy, Safiya Al‑Sharji

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The probability computation of events is in the interval of [0, 1], which are values that are determined by the number of outcomes of events in a sample space S. The probability Pr(A) that an event A will never occur is 0. The probability Pr(B) that event B will certainly occur is 1. This makes both events A and B a certainty. Furthermore, the sum of probabilities Pr(E₁) + Pr(E₂) + … + Pr(Eₙ) of a finite set of events in a given sample space S equals 1. Conversely, the difference of the sum of two probabilities that will certainly occur is 0. This paper first discusses Bayes, the complement of probability, and the difference of probability for occurrences of learning-events before applying them in the prediction of learning objects in student learning. Given the sum of 1; to make a recommendation for student learning, this paper proposes that the difference of argMaxPr(S) and the probability of student-performance quantifies the weight of learning objects for students. Using a dataset of skill-set, the computational procedure demonstrates i) the probability of skill-set events that have occurred that would lead to higher-level learning; ii) the probability of the events that have not occurred that requires subject-matter relearning; iii) accuracy of the decision tree in the prediction of student performance into class labels and iv) information entropy about skill-set data and its implication on student cognitive performance and recommendation of learning.

Keywords: complement of probability, Bayes’ rule, prediction, pre-assessments, computational education, information theory

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Authors: Muhadam Labolo, Afdal R. Anwar, Sucia Miranti Sipisang

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Electronic Local Finance Management Information System (ELFMIS) is integrated application that was used as a tool for local governments to improve the effectiveness of the implementation of the various areas of financial management regulations. Appropriate With Exceptions Opinion (WDP) of Indonesia Audit Agency (BPK) for local governments Mempawah is a financial management problem that must be improved to avoid mistakes in decision-making. The use of Electronic Local Finance Management Information System (ELFMIS) by Mempawah authority has not yet performed maximally. These problems became the basis for research in measuring the effectiveness LFMIS in Mempawah regency. This research uses an indicator variable for measuring information systems effectiveness proposed by Bodnar. This research made use descriptive with inductive approach. Data collection techniques were mixed from qualitative and quantitative techniques, used questionnaires, interviews and documentation. The obstacles in Local Finance Board (LFB) for the application of ELFMIS such as connection, the quality and quantity of human resources, realization of financial resources, absence of maintenance and another facilities of ELFMIS and verification for financial information.

Keywords: effectiveness, E-LFMIS, finance, local government, system

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Authors: Sasitorn Chetanont

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The objectives of this study are to find out the approaches to promote healthy recreation activities for elderly tourists and develop Bang Nam Phueng Floating Market to be a health tourism attraction. The research methodology was to analyze internal and external situations according to MP-MF and the MC-STEPS principles. As for the results of this study the researcher found that the healthy recreational activities for elderly tourists could be divided in 7 groups; travelling Bang Nam Phueng Floating Market activity, homestay relaxation, arts center platform activity, healthy massage activity, paying homage to a Buddha image activity, herbal joss-stick home activity, making local desserts and food activity.

Keywords: elderly tourists, recreation activities, Bang Nam Phueng Floating Market, health tourism

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: D. Tloczynski

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The main aim of this article is to present a balance of the decade of Polish air transport market in the European Union having taking into account selected entities of the aviation market. This article analyzes the functioning of the Polish air transport market after the Polish accession to the European Union. During the study two main areas were pointed: shipping activity and activity of the airports. The most important benefits of integration and the benefits of introducing of the open sky policy were indicated. The last part of the article presents the perspectives of development of air traffic.

Keywords: air transport, airports, development air transport, European Union, Poland

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Authors: Marine Segui, Ruxandra Mihaela Botez

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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: aerodynamic, coefficient, cruise, improving, longitudinal, openVSP, solver, time

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Authors: Tom Turner

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The recent financial crisis in 2008 and the growing inequality in developed industrial societies would appear to present significant challenges to capitalism and the free market. Yet there have been few substantial mainstream political or economic challenges to the dominant capitalist and market paradigm to-date. There is no dearth of critical and theoretical (academic) analyses regarding the prevailing systems failures. Yet despite the growing inequality in the developed industrial societies and the financial crisis in 2008 few commentators have advocated the comprehensive socialization or state ownership of the means of production to our knowledge – a core principle of radical Marxism in the 19th and early part of the 20th century. Undoubtedly the experience in the Soviet Union and satellite countries in the 20th century has cast a dark shadow over the notion of centrally controlled economies and state ownership of the means of production. In this paper, we explore the history of a doctrine advocating the socialization or state ownership of the means of production that was central to Marxism and socialism generally. Indeed this doctrine provoked an intense and often acrimonious debate especially for left-wing parties throughout the 20th century. The debate within the political economy tradition has historically tended to divide into a radical and a revisionist approach to changing or reforming capitalism. The radical perspective views the conflict of interest between capital and labor as a persistent and insoluble feature of a capitalist society and advocates the public or state ownership of the means of production. Alternatively, the revisionist perspective focuses on issues of distribution rather than production and emphasizes the possibility of compromise between capital and labor in capitalist societies. Over the 20th century, the radical perspective has faded and even the social democratic revisionist tradition has declined in recent years. We conclude with the major challenges that confront both the radical and revisionist perspectives in the development of viable policy agendas in mature developed democratic societies. Additionally, we consider whether state ownership of the means of production still has relevance in the 21st century and to what extent state ownership is off the agenda as a political issue in the political mainstream in developed industrial societies. A central argument in the paper is that state ownership of the means of production is unlikely to feature as either a practical or theoretical solution to the problems of capitalism post the financial crisis among mainstream political parties of the left. Although the focus here is solely on the shifting views of the radical and revisionist socialist perspectives in the western European tradition the analysis has relevance for the wider socialist movement.

Keywords: sate ownership, ownership means of production, radicals, revisionists

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Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

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Sea level rise threatens to increase the impact of future storms and hurricanes on coastal communities. Accurate sea level change prediction and supplement is an important task in determining constructions and human activities in coastal and oceanic areas. In this study, support vector machines (SVM) is proposed to predict daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal parameter values of kernel function are determined using a genetic algorithm. The SVM results are compared with the field data and with back propagation (BP). Among the models, the SVM is superior to BPNN and has better generalization performance.

Keywords: tides, prediction, support vector machines, genetic algorithm, back-propagation neural network, risk, hazards

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Authors: Paulette Henry

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If Caribbean Universities wish to remain sustainable in the global education market they must meet the new demands of the 21st Centuries learners. This means preparing the teaching and learning environment with the human and material and resources so that the University can blossom out into the entrepreneurial University. The entrepreneurial University prepares the learner to become a global citizen, one who is innovative and a critical thinker and has the competencies to create jobs. Entrepreneurship education provides more equitable access to university education building capacity for the local and global economy. The entrepreneurial thinking, the mindset, must therefore be among academic and support staff as well as students. In developing countries where resources are scarce, Universities are grappling with a myriad of financial and non-financial issues. These include increasing costs, Union demands for increased remuneration for staff and reduced subvention from governments which has become the norm. In addition, there is the political pressure against increasing tuition fees and the perceptions on the moral responsibilities of universities in national development. The question is how do small universities carve out their niche, meet both political and consumer demands for a high quality, low lost education, fulfil their development mandate and still remain not only viable but competitive. Themes which are central to this discourse on the transitions necessary for the entrepreneurial university are leadership, governance and staff well-being. This paper therefore presents a case study of a Caribbean University to show how transformational leadership and the change management framework propels change towards an entrepreneurial institution seeking to have a competitive advantage despite its low resourced context. Important to this discourse are the transformational approaches used by the University to prepare staff to move from their traditional psyche to embracing an entrepreneurial mindset whilst equipping students within the same mode to become work ready and creative global citizens. Using the mixed methods approach, opinions were garnered from both members of the University community as well as external stakeholder groups on their perception of the role of the University in the business arena and as a primary stakeholder in national development. One of the critical concepts emanating from the discourse was the need to change the mindset of the those in university governance as well as how national stakeholders engage the university. This paper shows how multiple non-financial factors can contribute to change. A combination of transformational and servant leadership, strengthened institutional structures and developing new ones, rebuilding institutional trust and pride have been among the strategies employed within the change management framework. The university is no longer limited by borders but through international linkages has transcended into a transnational stakeholder.

Keywords: competitiveness, context, entrepreneurial, leadership

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Authors: Fedil Jemal Ahmed

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This conference abstract paper presents a study that aimed to explore the impact of talent management and business skills on performance improvement in mini markets located in Johannesburg and Cape Town, South Africa. Mini markets are small retail stores that play a crucial role in providing essential goods and services to communities. However, due to their small size, they often face significant challenges in terms of resources and management. The study conducted interviews with mini market owners and managers in Johannesburg and Cape Town to understand their approach to talent management, business skills, and their impact on business performance. The results showed that effective talent management practices, including recruitment, training, and retention, along with strong business skills, had a significant positive impact on business performance in mini markets. Furthermore, the study found that the use of technology, such as point of sale systems and inventory management software, can also contribute to business performance improvement in mini markets. The results suggest that mini market owners and managers should prioritize talent management, business skills, and invest in technology to improve their business performance. Comparing the improvements made by mini markets in Johannesburg and Cape Town to those made by others, the study found that the adoption of effective talent management practices and strong business skills were key factors in driving performance improvement. Mini market owners and managers who invested in these areas were better equipped to manage their resources, enhance their customer service, and increase their profitability. When comparing the personal experiences of the fedil jemal who improved their business performance from a small market to a large one, they found that effective talent management practices and strong business skills were crucial in achieving success. Through the adoption of effective talent management practices, the fedil was able to attract and retain top talent, ensuring that the business was managed effectively. Furthermore, the fedil invested in improving their business skills, such as financial management, marketing, and customer service, which helped to increase their revenue and profitability. In terms of technology adoption, the author found that the use of point-of-sale systems and inventory management software were essential in managing their inventory and improving their customer service. By investing in technology, the fedil was able to streamline their operations and enhance their overall business performance. In conclusion, this study provides valuable insights into the importance of talent management, business skills, and technology adoption in improving business performance in mini markets. It highlights the need for mini market owners and managers to prioritize these areas and invest in them to enhance their business performance. The findings of this study have practical implications for mini market owners and managers who are looking to improve their business performance and compete in a highly competitive market. By adopting effective talent management practices, developing strong business skills, and investing in technology, mini market owners and managers can improve their operations and increase their profitability.

Keywords: talent management, business skills, technology adoption, mini markets

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Chaiwat Kongsom, Vitoon Panyakul

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The objective of this study was to assess the production and market of certified organic products in Thailand. A purposive sampling technique was used to identify a sample group of 154 organic entrepreneurs for the study. A survey and in-depth interview were employed for data collection. Also, secondary data from organic agriculture certification body and publications was collected. Then descriptive statistics and content analysis technique were used to describe about production and market of certified organic products in Thailand. Results showed that there were 9,218 farmers on 213,183.68 Rai (83,309.2 acre) of certified organic agriculture land (0.29% of national agriculture land). A total of 57.8% of certified organic agricultural lands were certified by the international certification body. Organic farmers produced around 71,847 tons/year and worth around THB 1,914 million (Euro 47.92 million). Excluding primary producers, 471 operators involved in the Thai organic supply chains, including processors, exporters, distributors, green shops, modern trade shops (supermarket shop), farmer’s markets and food establishments were included. Export market was the major market channel and most of organic products were exported to Europe and North America. The total Thai organic market in 2014 was estimated to be worth around THB 2,331.55 million (Euro 58.22 million), of which, 77.9% was for export and 22.06% was for the domestic market. The largest exports of certified organic products were processed foods (66.1% of total export value), followed by organic rice (30.4%). In the domestic market, modern trade was the largest sale channel, accounting for 59.48% of total domestic sales, followed by green shop (29.47%) and food establishment (5.85%). To become a center of organic farming and trading within ASEAN, the Thai organic sector needs to have more policy support in regard to agricultural chemicals, GMO, and community land title. In addition, appropriate strategies need to be developed.

Keywords: certified organic products, production, market, Thailand

Procedia PDF Downloads 322

Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

Abstract:

Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 171

Authors: Pallavi Kishore, Mariam Aslam

Abstract:

The sharp decline in oil prices that started in 2014 affected most economies in the world either positively or negatively. In some economies, particularly the oil exporting countries, the effects were felt immediately. The Gulf Cooperation Council’s (GCC henceforth) countries are oil and gas-dependent with the largest oil reserves in the world. UAE (United Arab Emirates) has been striving to diversify away from oil and expects higher non-oil growth in 2018. These two factors, falling oil prices and the economy strategizing away from oil dependence, make a compelling case to study the financial performance of various sectors in the economy. Among other sectors, the insurance sector is widely recognized as an important indicator of the health of the economy. An expanding population, surge in construction and infrastructure, increased life expectancy, greater expenditure on automobiles and other luxury goods translate to a booming insurance sector. A slow-down of the insurance sector, on the other hand, may indicate a general slow-down in the economy. Therefore, a study on the insurance sector will help understand the general nature of the current economy. This study involves calculations and comparisons of ratios pre and post the fall in oil prices in the insurance sector in the UAE. A sample of 33 companies listed on the official stock exchanges of UAE-Dubai Financial Market and Abu Dhabi Stock Exchange were collected and empirical analysis employed to study the financial performance pre and post fall in oil prices. Ratios were calculated in 5 categories: Profitability, Liquidity, Leverage, Efficiency, and Investment. The means pre- and post-fall are compared to conclude that the profitability ratios including ROSF (Return on Shareholder Funds), ROCE (Return on Capital Employed) and NPM (Net Profit Margin) have all taken a hit. Parametric tests, including paired t-test, concludes that while the fall in profitability ratios is statistically significant, the other ratios have been quite stable in the period. The efficiency, liquidity, gearing and investment ratios have not been severely affected by the fall in oil prices. This may be due to the implementation of stronger regulatory policies and is a testimony to the diversification into the non-oil economy. The regulatory authorities can use the findings of this study to ensure transparency in revealing financial information to the public and employ policies that will help further the health of the economy. The study will also help understand which areas within the sector could benefit from more regulations.

Keywords: UAE, insurance sector, ratio analysis, oil price, profitability, liquidity, gearing, investment, efficiency

Procedia PDF Downloads 245

Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

Procedia PDF Downloads 399