Search results for: stock price

Authors: L. E. Mphahama, A. Mushunje, A. Taruvinga

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Although broiler production does not generate any large incomes among the smallholder community, it represents the main source of livelihood and part of nutritional requirement. As a result, market for broiler meat is growing faster than that of any other meat products and is projected to continue growing in the coming decades. However, the implication is that a multitude of factors manipulates transformation of smallholder broiler farmers participating in the mainstream markets. From 217 smallholder broiler farmers, socio-economic and institutional factors in broiler farming were incorporated into Binary model to estimate the probability of broiler farmers’ participation in the mainstream markets within the Maseru district in Lesotho. Of the thirteen (13) predictor variables fitted into the model, six (6) variables (household size, number of years in broiler business, stock size, access to transport, access to extension services and access to market information) had significant coefficients while seven (7) variables (level of education, marital status, price of broilers, poultry association, access to contract, access to credit and access to storage) did not have a significant impact. It is recommended that smallholder broiler farmers organize themselves into cooperatives which will act as a vehicle through which they can access contracts and formal markets. These cooperatives will also enable easy training and workshops for broiler rearing and marketing/markets through extension visits.

Keywords: broiler chicken, mainstream market, Maseru district, participation, smallholder farmers

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

Procedia PDF Downloads 88

Authors: Sadik Yigit

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The energy consumed in the buildings constitutes a large portion of the total energy consumption in the world. In this study, it was aimed to measure the impact of climate change on the energy consumption of residential building stock by analyzing a typical mid-rise residential building in four different climate regions of Turkey. An integrated system was developed using the "Distribution Evolutionary Algorithms in Python" tool and Energy Plus. By using the developed integrated system, the energy performance of the typical residential building was analyzed under the effect of different climate change scenarios. The results indicated that predicted overheating will be experienced in the future, which will significantly increase the cooling energy loads of the buildings. In addition, design solutions to improve the future energy performance of the buildings were proposed, considering budget constraints. The results of the study will guide researchers studying in this area of research and designers in the sector in finding climate change resilient design solutions.

Keywords: energy_efficient, residential buildings, climate change, energyplus

Procedia PDF Downloads 77

Authors: Siti Rodliyah, Andrik Purwasito, Bani Sudardi, Abdullah Wakit

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This study employs sociological-ethnographic basic method and the cultural studies paradigm as the approach in understanding the habitus within the customary marriage of the East Nusa Tenggara society who require belis as a bride-price. The conceptual basis underlying the application of habitus theory and symbolic power in East Nusa Tenggara (NTT) society refers to the Bourdieu’s framework. This study is a result of participatory observation on habitus of a marital system using belis observed by the NTT society as a cognitive structure which connects individuals to the social activities of the customary marriage and makes it unquestionable habits. Knowledge of the social world under the pretext of prosperity for the recipients (family) of a bride-price can be a political instrument for the sustainability of power relations. The ritual-mythical system in the society has never been fully present as a neutral habit. The habitus reflected in the marital relationship among the NTT society enables the men to obtain and exercise their power relations. The sustainability of power relations can be seen from the representation of the social status of a girl and the properties attached to her. This is what gave birth to a symbolic rule, in which the social rules about bride-price or belis eventually will serve the interests of those who occupy a dominant position in the social structure, namely the rich men.

Keywords: belis, habitus, East Nusa Tenggara, marital system, power, symbolic

Procedia PDF Downloads 221

Authors: Maryam Ghoreishi, Christian Larsen

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In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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Authors: Rosie S. Abalos, John Patrick M. Dizon

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The operation of fish cages in mariculture parks for milkfish production remains a lucrative business for aquaculture operators. Three areas in the Philippines where mariculture parks are still in active operation were identified as study sites for this research. Financial analysis was used to estimate profitability of mariculture operations in the selected study sites. Based on the result of this research, milkfish production in mariculture parks remains profitable both in terms of net profit generation and the return on investment. To improve the profitability of aquaculture operations in mariculture parks, the relatively high price of operational inputs should be managed. As a recommendation, further studies should be conducted on the profitability of aquaculture operations in mariculture parks in the country to include other factors which may cause losses on the part of the operator and factors that may affect price of produce upon harvest.

Keywords: mariculture parks, milkfish production, aquaculture, profitability

Procedia PDF Downloads 127

Authors: Ketsada Sutthiumporn, Sittichot Thongkaw, Malee Santikunaporn

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In Thailand, biodiesel has been utilized as an attractive substitute of petroleum diesel and the government imposes a mandatory biodiesel blending requirement in transport sector to improve energy security, support agricultural sector and reduce emissions. Though biodiesel blend has many advantages over diesel fuel such as improved lubricity, low sulfur content and higher flash point, there are still some technical problems such as oxidative stability, poor cold- flow properties and impurity. Such problems were related to the fatty acid composition in feedstock. Moreover, Thailand has announced the use of low sulfur diesel as a base diesel and will be continually upgrading to EURO 5 in 2023. With ultra low sulfur content, it may affect the diesel fuel properties especially lubricity as well. Therefore, in this study, the physical and chemical properties of palm oil-based biodiesel in low sulfur diesel blends from different producers will be investigated by standard methods per ASTM and EN. Also, its economic benefits based on diesel price structure in Thailand will be highlighted. The appropriate biodiesel blend ratio can affect the physico-chemical properties and reasonable price in the country. Properties of biodiesel, including specific gravity, kinematic viscosity, FAME composition, flash point, sulfur, water, oxidation stability and lubricity were measured by standard methods of ASTM and EN. The results show that the FAME composition of biodiesel has the fatty acid of C12:0 to C20:1, mostly in C16:0, C18:0, C18:1, and C18:2, which were main characteristic compositions of palm biodiesel. The physical and chemical properties of biodiesel blended diesel was found to be increases with an increasing amount of biodiesel such as specific gravity, flash point and kinematic viscosity while sulfur value was decreased. Moreover, in this study, the various properties of each biodiesel blends were plotted to determine the appropriate proportional range of biodiesel-blended diesel with an optimum fuel price.It can be seen that the amount of B100 can be filled from 1% up to 7% in which the quality was in accordance with Notification of the department of Energy business.The understanding of relation between physico-chemical properties of palm oil-based biodiesel and pricing is beneficial to guide the better development of desired feedstock in Thailand and to implement biodiesel blends with comparative price and diesel engine performance.

Keywords: fatty acid methyl ester, biodiesel, fuel price structure, palm oil in Thailand

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Authors: O. Benabdeljelil, A. Karioun, S. Amami, R. Rouger, M. Hamidine

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A model for preventing the risks related to climate conditions in the agricultural sector is presented. It will determine the yearly optimum premium to be paid by a producer in order to reach his required turnover. The model is based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, the main ones of which are daily average sunlight, rainfall and temperature. By simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is determined from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. The model also requires accurate pricing of commodity at N+1. Therefore, a pricing model is developed using 3 state variables, namely the spot price, the difference between the mean-term and the long-term forward price, and the long-term structure of the model. The use of historical data enables to calibrate the parameters of state variables, and allows the pricing of commodity. Application to beet sugar underlines pricer precision. Indeed, the percentage of accuracy between computed result and real world is 99,5%. Optimal premium is then deduced and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect its harvest. The application to beet production in French Oise department illustrates the reliability of present model with as low as 6% difference between predicted and real data. The model can be adapted to almost any agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, production model, optimal price, meteorological factors, 3-factor model, parameter calibration, forward price

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Authors: Abisola Akinola, Akinsulere Femi

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The stock market has continually been a source of economic development in most developing countries. This study examined the relationship between investors’ ratio analysis and profitability of quoted companies in Nigeria using secondary data obtained from the annual reports of forty-two (42) companies. The study employed the multiple regression technique to analyze the relationship between investors’ ratio analysis (measured by dividend per share and earning per share) and profitability (measured by the return on equity). The results from the analysis show that investors’ ratio analysis, when measured by earnings per share, have a positive and significant impact on profitability. However, the study noted that investors’ ratio analysis, when measured by dividend per share, tend to have a positive impact on profitability but it is statistically insignificant. By implication, investors and other stakeholders that are interested in investing in stocks can predict the earning capacity of listed firms in the stock market.

Keywords: dividend per share, earnings per share, profitability, return on equity

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Authors: Mawardati Mawardati

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This research was carried out on the traditional milkfish and shrimp culture cultivation from March to May 2018 in East Aceh District. This study aims to to analyze the differences between traditional milkfish cultivation and shrimp farming in East Aceh District, Aceh Province. The analytical method used is acquisition analysis and Independent Sample T test analysis. The results showed a significant difference between milkfish farming and shrimp farming in East Aceh District, Aceh Province. Based on the results of the analysis, the average profit from shrimp farming is higher than that of milkfish farming. This demand exceeds market demand for exports. Thus the price of shrimp is still far higher than the price of milk fish.

Keywords: comparative, profit, shrimp, milkfish

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Authors: Jagbir Singh Kadyan

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This research paper critically analyse the performance of those Indian Automobile Companies which are listed and traded on the National Stock Exchange (NSE) of India and which are also included in the NSE nifty auto Index. In India, CSR–Corporate Social Responsibility is mandatory for certain qualifying companies under the Indian Companies Act 2013, which replaces the erstwhile Companies Act 1956. There has been a significant shift in the focus and approaches of the Indian Corporates towards their CSR obligations with the insertion of section 135, revision of section 198 and introduction of schedule VII of the Indian Companies Act 2013. Every such qualifying companies are required to mandatorily spend at least 2% of their annual average net profit of the immediately preceding three financial years on such CSR activities as specified under schedule VII of the Companies act 2013. This research paper analyzes the CSR performance of such Indian companies. This research work is originally based on the secondary data. The annual reports of the selected Indian automobile companies have been extensively used and considered for this research work.

Keywords: board of directors, corporate social responsibility, CSR committees, Indian automobile companies, Indian companies act 2013, national stock exchange

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

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First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

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In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: amelioration, deterioration, small sized poultry farmers, optimal price

Procedia PDF Downloads 189

Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Pricing strategy is a vital component in achieving the balance between customer value and business profitability. The aim of this study is to provide insights into the factors, techniques, and approaches involved in pricing decisions. The study utilizes a descriptive approach to discuss various aspects of pricing strategy in marketing, drawing on concepts from market research, consumer psychology, competitive analysis, and adaptability. This approach presents a comprehensive view of pricing decisions. The result of this exploration is a framework that highlights key factors influencing pricing decisions. The study examines how factors such as market positioning, product differentiation, and brand image shape pricing strategies. Additionally, it emphasizes the role of consumer psychology in understanding price elasticity, perceived value, and price-quality associations that influence consumer behavior. Various pricing techniques, including charm pricing, prestige pricing, and bundle pricing, are mentioned as methods to enhance sales by influencing consumer perceptions. The study also underscores the importance of adaptability in responding to market dynamics through regular price monitoring, dynamic pricing, and promotional strategies. It recognizes the role of digital platforms in enabling personalized pricing and dynamic pricing models. In conclusion, the study emphasizes that effective pricing strategies strike a balance between customer value and business profitability, ultimately driving sales, enhancing brand perception, and fostering lasting customer relationships.

Keywords: business, customer benefits, marketing, pricing

Procedia PDF Downloads 47

Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

Procedia PDF Downloads 1445

Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Nariman O. Kandil, Ehab K. Abou-Elkheir, Amr M. Kotb

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Effective IT governance guarantees the strategic alignment of IT and business goals, risk mitigation control, and better IT and business performance. This study seeks to examine empirically the extent of IT governance implementation within the firms listed on the Egyptian stock exchange (EGX30) and its determinants. Accordingly, 18 semi-structured interviews face to face, phone, and video-conferencing interviews using various tools (e.g., WebEx, Zoom, and Microsoft Teams) were undertaken at the interviewees’ offices in Egypt between the end of November 2019 and the end of August 2020. Results suggest that there are variances in the extent of IT Governance (ITG) implementation within the firms listed on the Egyptian stock exchange (EGX30), mainly caused by the industry type and internal and external triggers. The results also suggest that the organization size, the type of auditor, the criticality of the industry, the effective processes & KPIs, and the information intensity expertise of the CIO have a significant impact on IT governance implementation within the firms.

Keywords: effective IT governance, Egyptian market, information security, risk controls

Procedia PDF Downloads 135

Authors: Badr A. Al-Jehani

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Nowadays, contractor selection is a critical activity of the project owner. Selecting the right contractor is essential to the project manager for the success of the project, and this cab happens by using the proper selecting method. Traditionally, the contractor is being selected based on his offered bid price. This approach focuses only on the price factor and forgetting other essential factors for the success of the project. In this research paper, the Analytic Network Process (ANP) method is used as a decision tool model to select the most appropriate contractor. This decision-making method can help the clients who work in the construction industry to identify contractors who are capable of delivering satisfactory outcomes. Moreover, this research paper provides a case study of selecting the proper contractor among three contractors by using ANP method. The case study identifies and computes the relative weight of the eight criteria and eleven sub-criteria using a questionnaire.

Keywords: contractor selection, project management, decision-making, bidding

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Authors: Shanti Swaroop Gupta, Bibekananda Mohapatra, S. K. Chaturvedi, Anand Bohra

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For sustainable development in India, there is an urgent need to follow the principles of industrial symbiosis in the industrial processes, under which the scraps, wastes, or by‐products of one industry can become the raw materials for another. This will not only help in reducing the dependence on natural resources but also help in gaining economic advantage to the industry. Gypsum is one such area in India, where the linear economy model of by-product gypsum utilization has resulted in unutilized legacy phosphogypsum stock of 64.65 million tonnes (mt) at phosphoric acid plants in 2020-21. In the future, this unutilized gypsum stock will increase further due to the expected generation of Flue Gas Desulphurization (FGD) gypsum in huge quantities from thermal power plants. Therefore, it is essential to transit from the linear to circular economy in Gypsum in India, which will result in huge environmental as well as ecological benefits. Gypsum is required in many sectors like Construction (Cement industry, gypsum boards, glass fiber reinforced gypsum panels, gypsum plaster, fly ash lime bricks, floor screeds, road construction), agriculture, in the manufacture of Plaster of Paris, pottery, ceramic industry, water treatment processes, manufacture of ammonium sulphate, paints, textiles, etc. The challenges faced in areas of quality, policy, logistics, lack of infrastructure, promotion, etc., for complete utilization of by-product gypsum have been discussed. The untapped potential of by-product gypsum utilization in various sectors like the use of gypsum in agriculture for sodic soil reclamation, utilization of legacy stock in cement industry on mission mode, improvement in quality of by-product gypsum by standardization and usage in building materials industry has been identified. Based on the measures required to tackle the various challenges and utilization of the untapped potential of gypsum, a comprehensive action plan for the transition from linear to the circular economy in gypsum in India has been formulated. The strategies and policy measures required to implement the action plan to achieve a circular economy in Gypsum have been recommended for various government departments. It is estimated that the focused implementation of the proposed action plan would result in a significant decrease in unutilized gypsum legacy stock in the next five years and it would cease to exist by 2027-28 if the proposed action plan is effectively implemented.

Keywords: circular economy, FGD gypsum, India, phosphogypsum

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Authors: Prateep Wajeetongratana

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This study investigates the management accountant’s roles that link with the creation of corporate shared value to enable more effective decision-making and improve the information needs of stakeholders. Mixed method is employed to collect using triangulation for credibility. A quantitative approach is employed to conduct a survey of 200 Thai companies providing annual reports in the Stock Exchange of Thailand. The results of the study reveal that environmental and social data incorporated in a corporate social responsibility (CSR) disclosure are based on the indicators of the Global Reporting Initiatives (GRI) at a statistically significant level of 0.01. Environmental and social indicators in CSR are associated with environmental and social data disclosed in the annual report to support stakeholders’ and the public’s interests that are addressed and show that a significant relationship between environmental and social in CSR disclosures and the information in annual reports is statistically significant at the 0.01 level.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Sultan Haji Shube

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Woodland ecosystems of semiarid rift valley of Ethiopia play a significant role in climate change mitigation by sequestering and storing more carbon. This study was conducted in Gidabo river sub-basins southeastern rift-valley escarpment of Ethiopian. It aims to estimate biomass and carbon stocks of woodlands and its implications for climate change mitigation. A total of 44 sampling plots (900m²each) were systematically laid in the woodland for vegetation and environmental data collection. A composite soil sample was taken from five locations main plot. Both disturbed and undisturbed soil samples were taken at two depths using soil auger and core-ring sampler, respectively. Allometric equation was used to estimate aboveground biomass while root-to-shoot ratio method and Walkley-Black method were used for belowground biomass and SOC, respectively. Result revealed that the totals of the study site was 17.05t/ha, of which 14.21t/ha was belonging for AGB and 2.84t/ha was for BGB. Moreover, 2224.7t/ha total carbon stocks was accumulated with an equivalent carbon dioxide of 8164.65t/ha. This study also revealed that more carbon was accumulated in the soil than the biomass. Both aboveground and belowground carbon stocks were decreased with increase in altitude while SOC stocks were increased. The AGC and BGC stocks were higher in the lower slope classes. SOC stocks were higher in the higher slope classes than in the lower slopes. Higher carbon stock was obtained from woody plants that had a DBH measure of >16cm and situated at plots facing northwest. Overall, study results will add up information about carbon stock potential of the woodland that will serve as a base line scenario for further research, policy makers and land managers.

Keywords: allometric equation, climate change mitigation, soil organic carbon, woodland

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Ben Kwame Agyei-Mensah

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This study investigated the influence of firm-specific characteristics which include proportion of Non-Executive Directors, ownership concentration, firm size, profitability, debt equity ratio, liquidity and leverage on the extent and quality of financial ratios disclosed by firms listed on the Ghana Stock Exchange. The research was conducted through detailed analysis of the 2012 financial statements of the listed firms. Descriptive analysis was performed to provide the background statistics of the variables examined. This was followed by regression analysis which forms the main data analysis. The results of the extent of financial ratio disclosure level, mean of 62.78%, indicate that most of the firms listed on the Ghana Stock Exchange did not overwhelmingly disclose such ratios in their annual reports. The results of the low quality of financial ratio disclosure mean of 6.64% indicate that the disclosures failed woefully to meet the International Accounting Standards Board's qualitative characteristics of relevance, reliability, comparability and understandability. The results of the multiple regression analysis show that leverage (gearing ratio) and return on investment (dividend per share) are associated on a statistically significant level as far as the extent of financial ratio disclosure is concerned. Board ownership concentration and proportion of (independent) non-executive directors, on the other hand were found to be statistically associated with the quality of financial ratio disclosed. There is a significant negative relationship between ownership concentration and the quality of financial ratio disclosure. This means that under a higher level of ownership concentration less quality financial ratios are disclosed. The findings also show that there is a significant positive relationship between board composition (proportion of non-executive directors) and the quality of financial ratio disclosure.

Keywords: voluntary disclosure, firm-specific characteristics, financial reporting, financial ratio disclosure, Ghana stock exchange

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Authors: Peter Oyelere, Fernando Zanella

Abstract:

Corporate governance is one of the most discussed and researched issues in recent times in countries around the world, with different countries developing and adopting different governance structures, models and mechanisms. While the Codes of corporate governance have been weaved into the regulatory fabrics of most countries, it is equally critically important that their mechanisms, procedures and practices be transparent, and be transparently communicated to all stakeholders. The Internet can be a very useful and cost-effective tool for the timely and voluntary communication of corporate governance matters to stakeholders. The current paper details the results of an investigation on the extent of which companies listed in the UAE are using the Internet for communicating corporate governance issues, matters and procedures. We surveyed the websites of companies listed on the two UAE Stock Exchanges – the Abu Dhabi Stock Exchange (ADX) and the Dubai Financial Market (DFM) – to find out their level and nature of usage of the Internet for corporate governance disclosures. Regulatory and policy implications of the results of our investigation, as well as other areas for further studies, are also presented in the paper.

Keywords: corporate governance, internet financial reporting, regulation, transparency, United Arab Emirates

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Authors: Hina Munir Abbasi

Abstract:

The current paper examines the relationship and diversification ability of Islamic stock indices /conventional stocks indices and Real Estate Investment Trust (REITs).To represent conditional dependency between stocks and REITs in a more realistic way, new modeling technique, time-varying copula with switching dependence is used. It represents reliance structure more accurately and realistically than a single copula regime as dependence may alter between positive and negative correlation regimes with time. The fluctuating behavior of markets has significant impact on economic variables; especially the downward trend during crisis. Overall addition of Real Estate Investment Trust in stocks portfolio reduces risks and provide better diversification benefit. Results varied depending upon the circumstances of the country. REITs provides better diversification benefits for Islamic Stocks, when both markets are bearish and can provide hedging benefit for conventional stocks portfolio.

Keywords: conventional stocks, real estate investment trust, copula, diversification, risk spillover, safe heaven

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Authors: Abdulkarim Yusuf

Abstract:

Motivation: The Nigerian economy has seen significant macroeconomic instability, fuelled mostly by an overreliance on fluctuating oil revenues. The rising disparity between tax receipts and government spending in Nigeria necessitates government borrowing to fund the anticipated pace of economic growth. Rising public debt and fiscal sustainability are limiting the government's ability to invest in key infrastructure that promotes private investment and growth in Nigeria. Objective: This paper fills an empirical research vacuum by examining the impact of public debt on fiscal sustainability in Nigeria, given the significance of fiscal stability in decreasing poverty and the constraints that an unsustainable debt burden imposes on it. Data and method: Annual time series data covering the period 1980 to 2022 exposed to conventional and structural breaks stationarity tests and the Autoregressive Distributed Lag estimation approach were adopted for this study. Results: The results reveal that domestic debt stock, debt service payment, foreign reserve stock, exchange rate, and private investment all had a major adverse effect on fiscal stability in the long and short run, corroborating the debt overhang and crowding-out hypothesis. External debt stock, prime lending rate, and degree of trade openness, which boosted fiscal stability in the long run, had a major detrimental effect on fiscal stability in the short run, whereas foreign direct investment inflows had an important beneficial impact on fiscal stability in both the long and short run. Implications: The results indicate that fiscal measures that inspire domestic resource mobilization, sustainable debt management techniques, and dependence on external debt to boost deficit financing will improve fiscal stability and drive growth.

Keywords: ARDL co-integration, debt overhang, debt servicing, fiscal stability, public debt

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Authors: Zichun Guo

Abstract:

Guangzhou's housing prices have declined for a long time compared with the other three major cities. As Guangzhou's housing price ladder increases, the influencing factors of housing prices have gradually attracted attention. This article attempts to use housing price data and POI data and uses the Kriging spatial interpolation method and the geographically weighted regression model to explore the distribution of housing prices and the impact of factors. Caused, especially located in Huadu District and the city center. The response is mainly obvious in surrounding areas, which may be related to housing positioning. Economic POIs close to the city center have stronger responses. The factors affecting housing prices provide this method, which is conducive to the management and macro-control of relevant departments, better meets the demand for home purchases, and realizes financing-side reforms.

Keywords: housing prices, spatial heterogeneity, Guangzhou, POI

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Authors: Setya Winarno

Abstract:

Due to abundant Merapi volcanic sand in Yogyakarta City, many local people have utilized it for mass production of concrete blocks through mini plants although their products are low in quality. This paper presents a practice model for quality improvement in this situation in order to supply the current customer interest in good quality of construction material. The method of this research was to investigate a techno economic evaluation through laboratory test and interview. Samples of twenty existing concrete blocks made by local people had only 19.4 kg/cm2 in average compression strength which was lower than the minimum Indonesian standard of 25 kg/cm2. Through repeat testing in laboratory for fulfilling the standard, the concrete mix design of water cement ratio should not be more than 0.64 by weight basis. The proportion of sand as aggregate content should not be more than 9 parts to 1 part by volume of Portland cement. Considering the production cost, the basic price was Rp 1,820 for each concrete block, comparing to Rp 2,000 as a normal competitive market price. At last, the model describes (a) maximum water cement ratio is 0.64, (b) maximum proportion of sand and cement is 1:9, (c) the basic price is about Rp. 1,820.00 and (d) strategies to win the competitive market on mass production of concrete blocks are focus in quality, building relationships with consumer, rapid respond to customer need, continuous innovation by product diversification, promotion in social media, and strict financial management.

Keywords: concrete block, good quality, improvement model, diversification

Procedia PDF Downloads 494