Search results for: cost forecasting

Authors: S. Abdulkadir, I. Y. Moh’d, S. U. Kunya, U. Nuruddeen

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The basis of any contract formation between the client and contractor is the budgeted cost and the estimated duration of projects. These variables are paramount important to project's sponsor in a construction projects and in assessing the success or viability of construction projects. Despite the availability of various techniques of cost and time control, many projects failed to achieve their initial estimated cost and time. The paper evaluate the inhibiting factors of cost and time control in Nigerian construction practice and comparing the result with the United Kingdom practice as identified by one researcher. The populations of the study are construction professionals within Bauchi and Gombe state, Nigeria, a judgmental sampling employed in determining the size of respondents. Descriptive statistics used in analyzing the data in SPSS. Design change, project fraud and corruption, financing and payment of completed work found to be common among the top five inhibiting factors of cost and time control in the study area. Furthermore, the result had shown some comprising with slight contrast as in the case of United Kingdom practice. Study recommend the adaptation of mitigation measures developed in the UK prior to assessing its effectiveness and so also developing a mitigating measure for other top factors that are not within the one developed in United Kingdom practice. Also, it recommends a wider assessing comparison on the modify inhibiting factors of cost and time control as revealed by the study to cover almost all part of Nigeria.

Keywords: comparison, cost, inhibiting factor, United Kingdom, time

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Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

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We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

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Construction project cost are not only made up of production costs. This cost comprises of many other elements such as the preparation of a bidding document, cost estimations, drafting contractual agreements and monitoring that contractual obligations are met. Several studies have stressed the need for transaction costs (TC) to be defined in a way that covers all phases of a project and not only the pre-contract phase. Hence, this study aims to appraise transaction cost in South African (SA) construction projects by assessing what constitutes transaction cost, influencing factors and possible optimisation measures. A survey design was adopted. A total number of eighty (80) questionnaires were administered to quantity surveyors, procurement managers and project managers in Guateng Province, SA and seventy-two (72) were returned and found suitable for analysis. Collected data was analysed using percentage, mean item score, standard deviation, one-sample t-test. The findings show that external technical interaction, uncertainty, human factors are the most significant constituents of TC in SA, while technical competency, experience in similar project type and project characteristics are the leading influencing factors. Furthermore, understanding project characteristics, clear communication and technically competent project teams are most of the significant measures for optimising TC in SA construction projects. Therefore, this study recommends that a competent project team and a clear communication are fundamental to proper management of TC in SA construction projects.

Keywords: construction projects, project cost, South Africa, transaction cost

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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Authors: Chris Durden, Peter Lane

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Cost accounting information potentially plays an important role in price setting. According to prior research fixed and variable cost information often is a key influence on pricing decisions. The literature highlights the benefits of applying systematic costing systems for enhanced price setting processes. This paper explores how costing systems are used for pricing decisions in the tourism and hospitality industry relative to other sources of price setting information. Pricing based on full cost information was found to have relatively greater importance and short-term survival and customer oriented objectives were found to be the more important pricing objectives. This paper contributes to the literature by providing a recent analysis of accounting’s role in price setting within the tourism and hospitality industry.

Keywords: cost accounting systems, pricing decisions, cost-plus pricing, market pricing, tourism industry

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Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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Authors: Lai Ving Kam

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Many markets are maturing, consumer buying powers are weakening and customer preferences change rapidly. To survive, many adopt fast paced continuous cost reduction and competitive pricing to remain relevance. Marketers desire to push for more sales to increase revenues have intensified competitions at time cannibalize the product and market. The amazing technologies changes have created both hope and despair to the industries. The pressure to constantly reduce cost, on the one hand, create and market new products in cheaper prices and shorter life cycles, on the other has become a continuous endeavour. The twin trends appear irreconcilable. Can core strategic vision provides and adapts new directions in continuous cost reduction? This study investigates core strategic vision able to meet this need, for firms to survive and stay profitable. Under current uncertainty market, are firms falling back on their core strategic visions to take them out of the unfavourable positions?

Keywords: core strategy vision, continuous cost reduction, fashionable products industry, competitive pricing

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Authors: S. P. Koko, K. Kusakana, H. J. Vermaak

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Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)

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Authors: Hninn Thiri Naing

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In Myanmar, there are many regions that are far away from the national grid. For these areas, isolated regional micro-grids are one of the solutions. The study area in this paper is also operating in such way. The main difficulty in such regions is the high cost of electrical energy. This paper will be approached to cost-effective or cost-optimization by energy planning with renewable energy resources and natural gas. Micro-grid will be set up for performance in the Dawei region since it is economic zone in lower Myanmar and so far from national grids. The required metrological and geographical data collections are done. Currently, the status is electric unit rate is higher than the other. For microgrid planning and optimization, Homer Pro-software is employed in this research.

Keywords: energy planning, renewable energy, homer pro, cost of energy

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Authors: L. Totladze

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The role of financial sector in supporting economic growth and development is well acknowledged. The term spread (the difference between the yields on long-term and short-term Treasury securities) has been found useful for predicting economic variables as output growth, inflation, industrial production, consumption. The temp spread is one of the leading economic indicators according to NBER methodology. Leading economic indicators are widely used in forecasting of economic activity. Many empirical studies find that the term spread predicts future economic activity. The article shortly explains how the term spread might predict future economic activity. This paper analyses the dynamics of the spread between short and long-term interest rates in countries with transition economies. The research paper analyses term spread dynamics in Georgia and compare it with post-communist countries and transition economies spread dynamics. In Georgia, the banking sector plays an important and dominant role in the financial sector, especially with respect to the mobilization of savings and provision of credit and may impact on economic activity. For this purpose, we study the impact of the term spread on economic growth in Georgia.

Keywords: forecasting, leading economic indicators, term spread, transition economies

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Zainab Khalifah, Wong Chiet Bing, Noor Hazarina Hashim

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The evolution of customer behavior in purchasing products or services through the Internet leads to airline companies engaging in the e-ticketing process in order to maintain their business. A well-designed website is vitally significant for the airline companies to provide effective communication, support, and competitive advantage. This study was conducted to identify the dimensions of website quality for low cost airline and to investigate the relationship between the website quality and customer e-satisfaction at low cost airline. A total of 381 responses were conveniently collected among local passengers at Low Cost Carrier Terminal, Kuala Lumpur via questionnaire distribution. This study found that the five determinant factors of website quality for AirAsia were Information Content, Navigation, Responsiveness, Personalization, and Security and Privacy. The results of this study revealed that there is a positive relationship between the five dimensions of website quality and customer e-satisfaction, and also information content was the most significant contributor to customer e-satisfaction.

Keywords: website quality, customer e-satisfaction, low cost airline, e-ticketing

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: cold-start learning, expectation propagation, multi-armed bandits, Thompson Sampling, variational inference

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Nouha Ben Salah, Mohamed Ali Omri

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This paper treats the association between disclosure level and the cost of equity capital in Tunisian’slisted firms. This relation is tested by using two models. The first is used for testing this relation directly by regressing firm specific estimates of cost of equity capital on market beta, firm size and a measure of disclosure level. The second model is used for testing this relation by introducing information asymmetry as mediator variable. This model is suggested by Baron and Kenny (1986) to demonstrate the role of mediator variable in general. Based on a sample of 21 non-financial Tunisian’s listed firms over a period from 2000 to 2004, the results prove that greater disclosure is associated with a lower cost of equity capital. However, the results of indirect relationship indicate a significant positive association between the level of voluntary disclosure and information asymmetry and a significant negative association between information asymmetry and cost of equity capital in contradiction with our previsions. Perhaps this result is due to the biases of measure of information asymmetry.

Keywords: cost of equity capital, voluntary disclosure, information asymmetry, and Tunisian’s listed non-financial firms

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Authors: Yu Zhang, Kohei Inoue, Kiichi Urahama

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We propose a simplified bilateral filter with binarized coefficients for accelerating it. Its computational cost is further decreased by sampling pixels. This computationally low cost filter is useful for smoothing or denoising images by using mobile devices with limited computational power.

Keywords: bilateral filter, binarized-weight bilateral filter, image smoothing, image denoising, pixel sampling

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Authors: Qiuxiao Chen, Yan Hou, Ning Wu

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As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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Authors: Yu-Yao Wang, Xiao-Meng Hu, Joanne Yeung, Xiao-Yan Li

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The high private cost and unquantified external cost limit the development of reclaimed water. In this study, an integrated framework comprising life cycle assessment (LCA), quantitative microbial risk assessment (QMRA), and life cycle costing (LCC) was developed to evaluate both costs of reclaimed water supply in water systems of various scales. LCA assesses the environmental impacts, and QMRA estimates the associated pathogenic impacts. These impacts are monetized as external costs and analyzed with the private cost by LCC to count the total life cycle cost. The framework evaluated the Hong Kong urban water system in the baseline scenario (BS) and five wastewater reuse scenarios (RS). They are RSI: substituting freshwater for toilet flushing only, RSII: substituting both freshwater and seawater for toilet flushing, RSIII: using reclaimed water for all non-potable uses, RSIV: using reclaimed water for all non-potable uses and indirect potable uses, and RSV: non-potable use and indirect potable use by conveying 100% reclaimed water to recharge the reservoirs. The results show that substituting freshwater and seawater for toilet flushing has the least total life cycle cost, exhibiting that it is the most cost-effective option for Hong Kong. Meanwhile, the evaluation results show that the external cost of each scenario is comparable to the corresponding private cost, indicating the importance of the inclusion of comprehensive external cost evaluation in private cost assessment of water systems with reclaimed water supply.

Keywords: life cycle assessment, life cycle costing, quantitative microbial risk assessment, water reclamation, reclaimed water, alternative water resources

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Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

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Authors: Lo Kar Yin, Law Ka Mei

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Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its discipline. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC Engineering and Construction Contract (ECC) Options A and C.

Keywords: building information modeling, cost estimation, quantity take-off, modeling techniques

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Authors: Ali Heidari

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This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

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Authors: S. Aditya, K. T. Nideesh, N. Guruprasad

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Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost.

Keywords: NW method, optimum utilization, transportation problem, Vogel’s approximation method

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: Rohit Kapoor

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In this paper, an attempt is made to formulate 3-echelon repairable parts inventory system under (S-1, S) policy. This analytical model is the extension of an exact formulation of two - echelon repairable parts inventory system, already reported in the established literature. In the present paper, we try to formulate the total cost expression consisting of two components, viz., system investment cost and expected backorder cost.

Keywords: (S-1, S) inventory policy, multi-echelon inventory system, repairable parts

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Authors: Tzu-Ching Weng, Hsin-Yi Chi

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This study examines the effect of family succession on the cost of bank loans and non-price contractual terms. We use a unique dataset from China and find that lending banks are likely to charge high-interest rates and offer tight contractual terms, such as loan maturity and collateral requirement, for family succession firms. These findings indicate that information and default risks may arise after subsequent family successions. We also find that family succession firms can reduce the cost of bank loans by hiring top-tier auditors to enhance financial reporting credibility. This finding suggests that professional and high-quality auditors can provide extremely valuable services to family succession firms.

Keywords: family succession, cost of bank loans, loan contract terms, top-tier auditor

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Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Pirom Thangchitpianpol, Suttipong Jumroonrut

Abstract:

This research investigates the distribution of food demand for animal food and the optimum amount of that food production at minimum cost. The data consist of customer purchase orders for the food of laying hens, price of food for laying hens, cost per unit for the food inventory, cost related to food of laying hens in which the food is out of stock, such as fine, overtime, urgent purchase for material. They were collected from January, 1990 to December, 2013 from a factory in Nakhonratchasima province. The collected data are analyzed in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results are used in a stochastic linear programming model for aggregate planning in which the optimum production or minimum cost could be obtained. Programming algorithms in MATLAB and tools in Linprog software are used to get the solution. The distribution of the food demand for laying hens and the random numbers are used in the model. The study shows that the distribution of monthly food demand for laying has a normal distribution, the monthly average amount (unit: 30 kg) of production from January to December. The minimum total cost average for 12 months is Baht 62,329,181.77. Therefore, the production planning can reduce the cost by 14.64% from real cost.

Keywords: animal food, stochastic linear programming, aggregate planning, production planning, demand uncertainty

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