Search results for: sales demand forecasting

Authors: Fatbardha Kadiu, Nulifer Caliskan

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The value added tax came as a necessity of substituting the old tax on sales. Based on the advantages of this new tax in our days it is used successfully in more than 140 countries around the world. The aim of the paper is to describe the nature of this tax with its advantages and disadvantages. Also it will describe the way how it functions in most of the European countries and the actual challenges of these countries on value added tax. It will be present the types of goods which are exempt from this tax, the reasons and the consequences of those exemptions. The paper will be based on secondary data taken from respective literature. An econometric model will be present in order to identify the dependence of value tax from other parameters. The analyzing most refers to the two main principles of harmonization and billing on the fiscal system and the ways how to restructures the system in order to minimize the fiscal evasion.

Keywords: value added tax, revenues, complexity, legal uncertainty

Procedia PDF Downloads 382

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Jeonghwan Jeon, Mintak Han, Youngjun Kim

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Due to the rapid development of information and communication technology (ICT), a substantial transformation is currently happening in the society. As the range of intelligent technologies and services is continuously expanding, ‘things’ are becoming capable of communicating one another and even with people. However, such “Internet of Things” has the technical weakness so that a great amount of such information transferred in real-time may be widely exposed to the threat of security. User’s personal data are a typical example which is faced with a serious security threat. The threats of security will be diversified and arose more frequently because next generation of unfamiliar technology develops. Moreover, as the society is becoming increasingly complex, security vulnerability will be increased as well. In the existing literature, a considerable number of private and public reports that forecast future society have been published as a precedent step of the selection of future technology and the establishment of strategies for competitiveness. Although there are previous studies that forecast security technology, they have focused only on technical issues and overlooked the interrelationships between security technology and social factors are. Therefore, investigations of security threats in the future and security technology that is able to protect people from various threats are required. In response, this study aims to derive potential security threats associated with the development of technology and to explore the security technology that can protect against them. To do this, first of all, private and public reports that forecast future and online documents from technology-related communities are collected. By analyzing the data, future issues are extracted and categorized in terms of STEEP (Society, Technology, Economy, Environment, and Politics), as well as security. Second, the components of potential security threats are developed based on classified future issues. Then, points that the security threats may occur –for example, mobile payment system based on a finger scan technology– are identified. Lastly, alternatives that prevent potential security threats are proposed by matching security threats with points and investigating related security technologies from patent data. Proposed approach can identify the ICT-related latent security menaces and provide the guidelines in the ‘problem – alternative’ form by linking the threat point with security technologies.

Keywords: future society, information and communication technology, security technology, technology forecasting

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Ítalo de Pontes Oliveira

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This paper presents a analysis of performance the Received Strength Signal Indicator (RSSI) to Wireless Sensor Networks, with a finality of investigate a behavior of ZigBee devices operating into real environments. The test of performance was realize using two Series 1 ZigBee Module and two modules of development Arduino Uno R3, evaluating in this form a measurements of RSSI into environments like places of sports, preservation forests and water reservoir.

Keywords: wireless sensor networks, RSSI, Arduino, environments

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Yuang Guo, Dewancker Bart

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The primary energy consumption of buildings throughout China was approximately 814 million tons of coal equivalents in 2014, which accounts for 19.12% of China's total primary energy consumption. Also, the energy consumption of public buildings takes a bigger share than urban residential buildings and rural residential buildings among the total energy consumption. To improve the level of energy demand, various design parameters were chosen. Meanwhile, a series of simulations by Energy Plus (EP-Launch) is performed using a base case model established in Open Studio. Through the results, 16%-23% of total energy demand reductions can be found in the severe cold zone of China, and it can also provide a reference for the architectural design of other similar climate zones.

Keywords: energy consumption, design parameters, indoor thermal comfort, simulation study, severe cold climate zone

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Authors: T. Yuri M. Zagloel, Inaki M. Hakim, Syarafi A. M.

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Manufacturing process has been considered as one of the most important activity in business process. It correlates with productivity and quality of the product so industries could fulfill customer’s demand. With the increasing demand from customer, industries must improve their manufacturing ability such as shorten lead time and reduce wastes on their process. Lean manufacturing has been considered as one of the tools to waste elimination in manufacturing or service industri. Workforce development is one practice in lean manufacturing that can reduce waste generated from operator such as waste of unnecessary motion. Anthropometric approach is proposed to determine the recommended measurement in operator’s work area. The method will get some dimensions from Indonesia people that related to piston workstation. The result from this research can be obtained new design for the workarea considering ergonomic aspect.

Keywords: adjustable, anthropometric, ergonomic, waste

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Authors: Abdollah Kavousi Fard

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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

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Authors: Dalia Almaghaslah, A. Alsayari, R. Asiri, N. Albugami

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The aim of this study was to evaluate the pharmacy workforce in Saudi Arabia in terms of supply, geographical distribution, nationality and gender distribution, as well as to assess the employment rate. A retrospective cross-sectional approach was used to address these objectives. Relevant data was identified and retrieved from the latest version of the Health Statistical Yearbook— Kingdom of Saudi Arabia, 2016; Saudi Commission for Health Specialties publications, 2018; and national pharmacy organisation websites. In general, the exponential increase in the number of pharmacy schools has helped to produce more pharmacists in the rural areas of the country, but inequitable distribution of the workforce still exists. The reliance on non-indigenous pharmacists, especially in the private sector, is substantial. Male pharmacists outnumber females, mainly due to the cultural and social factors that limit the participation of women in community pharmacy, which is the largest employment sector. The employment rate shows limited opportunities for Saudi pharmacists at the Ministry of Health (MOH) as they have already Saudised almost all pharmacy positions at the MOH healthcare facilities. However, the private sector needs to assume responsibility for their share of the re-nationalisation of the profession in order to provide jobs for local pharmacists. Regular, more detailed profiling of the pharmacy workforce is an essential step to achieving effective pharmacy workforce planning. Currently, a large gap exists in our knowledge of the workforce in the country, especially regarding their supply and demand and employment prospects.

Keywords: employment prospects, pharmacy workforce, Saudi Arabia, supply and demand

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Authors: Sheikh Saeed Ahmad

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Electricity is vital for any state’s development that needs policy for planning the power network extension. This study is about simulation modeling for electricity in Balochistan province. Baseline data of electricity consumption was used of year 2004 and projected with the help of LEAP model up to subsequent 30 years. Three scenarios were created to run software. One scenario was baseline and other two were alternative or green scenarios i.e. solar and wind energy scenarios. Present study revealed that Balochistan has much greater potential for solar and wind energy for electricity production. By adopting these alternative energy forms, Balochistan can save energy in future nearly 23 and 48% by incorporating solar and wind power respectively. Thus, the study suggests to government planners, an aspect of integrating renewable sources in power system for ensuring sustainable development and growth.

Keywords: demand and supply, LEAP, solar energy, wind energy, households

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Authors: Mohammed Al Awadh

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In order for businesses to take advantage of the opportunities for expanded production and trade that have arisen as a result of globalization and increased levels of competition, productivity growth is required. The number of available sources is decreasing with each passing day, which results in an ever-increasing demand. In response to this, there will be an increased demand placed on firms to improve the efficiency with which they utilise their resources. As a scientific method, work and time research techniques have been employed in all manufacturing and service industries to raise the efficiency of use of the factors of production. These approaches focus on work and time. The goal of this research is to improve the productivity of a manufacturing industry's production system by looking at ways to measure work. The work cycles were broken down into more manageable and quantifiable components. On the observation sheet, these aspects were noted down. The operation has been properly analysed in order to identify value-added and non-value-added components, and observations have been recorded for each of the different trails.

Keywords: time study, work measurement, work study, efficiency

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: communication technology between appliances, demand response, load monitoring, smart appliances, smart grid

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Authors: A. S. Zgalei, B. T. Al-Mabrouk

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With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

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Authors: Samira Mohabbatdar, Abbas Ahmadi, Mohsen S. Sajadieh

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This paper deals with a two-level supply chain consisted of one manufacturer and one retailer for single-type product. The demand function of the customers depends on price. We consider an integrated production inventory system where the manufacturer processes raw materials in order to deliver finished product with imperfect quality to the retailer. Then retailer inspects the products and after that delivers perfect products to customers. The proposed model is based on the joint total profit of both the manufacturer and the retailer, and it determines the optimal ordering lot-size, number of shipment and selling price of the retailer. A numerical example is provided to analyse and illustrate the behaviour and application of the model. Finally, sensitivity analysis of the key parameters are presented to test feasibility of the model.

Keywords: supply chain, pricing policy, defective quality, joint economic lot sizing

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Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Sameh S. Namnqani, Yaqoob Y. Abobakar, Ahmed M. Alsewehri, Khaled M. AlQethami

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The main objective of this research is to know the impact of the application of the electronic supply system on the performance of the supply department of health organizations. To reach this goal, the study adopted independent variables to measure the dependent variable (performance of the supply department), namely: integration with suppliers, integration with intermediaries and distributors and knowledge of supply size, inventory, and demand. The study used the descriptive method and was aided by the questionnaire tool that was distributed to a sample of workers in the Supply Chain Management Department of King Abdullah Medical City. After the statistical analysis, the results showed that: The 70 sample members strongly agree with the (electronic integration with suppliers) axis with a p-value of 0.001, especially with regard to the following: Opening formal and informal communication channels between management and suppliers (Mean 4.59) and exchanging information with suppliers with transparency and clarity (Mean 4.50). It also clarified that the sample members agree on the axis of (electronic integration with brokers and distributors) with a p-value of 0.001 and this is represented in the following elements: Exchange of information between management, brokers and distributors with transparency, clarity (Mean 4.18) , and finding a close cooperation relationship between management, brokers and distributors (Mean 4.13). The results also indicated that the respondents agreed to some extent on the axis (knowledge of the size of supply, stock, and demand) with a p-value of 0.001. It also indicated that the respondents strongly agree with the existence of a relationship between electronic procurement and (the performance of the procurement department in health organizations) with a p-value of 0.001, which is represented in the following: transparency and clarity in dealing with suppliers and intermediaries to prevent fraud and manipulation (Mean 4.50) and reduce the costs of supplying the needs of the health organization (Mean 4.50). From the results, the study recommended several recommendations, the most important of which are: that health organizations work to increase the level of information sharing between them and suppliers in order to achieve the implementation of electronic procurement in the supply management of health organizations. Attention to using electronic data interchange methods and using modern programs that make supply management able to exchange information with brokers and distributors to find out the volume of supply, inventory, and demand. To know the volume of supply, inventory, and demand, it recommended the application of scientific methods of supply for storage. Take advantage of information technology, for example, electronic data exchange techniques and documents, where it can help in contact with suppliers, brokers, and distributors, and know the volume of supply, inventory, and demand, which contributes to improving the performance of the supply department in health organizations.

Keywords: healthcare supply chain, performance, electronic system, ERP

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Authors: Swadhin Mondal

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While safe drinking water is an effective defense against the infection of water borne diseases, a large number of populations suffering from these diseases do not have access to safe drinking water due inadequacy of supply. Private entrepreneurs entered this sector and made bottled drinking water available by supplying various kinds of bottled water. In this study we found that the bottled drinking water industry has experienced a spectacular growth over the past two decades and it has a huge growth potential because of rising demand for safe drinking. High profit margin (217 %) is the main attraction to the entrepreneur to invest in this industry. Health awareness, lack of safe drinking water facilities, rising income, urbanization, migration and rising trend in tourism industries are the major influencing factors of demand for bottled drinking water (BDW). This industry also partially fulfills the demand for drinking water. More than 2 percent of household’s demands were met by this industry and many more households (additional 4 percent) coping with BDW during water crisis. Poor households spend around 4 percent of their total monthly household’s consumption expenditure on BDW which may have an adverse impact on household because households could have spent this for purchasing other goods. Like other developed counties, a large section of Indian households are shifting from their traditional sources of water to BDW. However, there are some concerns about the quality of BDW. Many cases, BDW contains chemical toxins at more than permissible level that can be harmful for health. Hence, there is an urgent need for appropriate intervention to regulate price, reduce potential harm and improve the quality of water provided by this industry.

Keywords: drinking water, public health public failure, privatization, development, public policy

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Authors: B. Sudhakara Reddy

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The transition to a clean and green energy system is an economic and social transformation that is exciting as well as challenging. The world today faces a formidable challenge in transforming its economy from being driven primarily by fossil fuels, which are non-renewable and a major source of global pollution, to becoming an economy that can function effectively using renewable energy sources and by achieving high energy efficiency levels. In the present study, a green economy scenario is developed for India using a bottom-up approach. The results show that the penetration rate of renewable energy resources will reduce the total primary energy demand by 23% under GE. Improvements in energy efficiency (e.g. households, industrial and commercial sectors) will result in reduced demand to the tune of 318 MTOE. The volume of energy-related CO2 emissions decline to 2,218 Mt in 2030 from 3,440 under the BAU scenario and the per capita emissions will reduce by about 35% (from 2.22 to 1.45) under the GE scenario. The reduction in fossil fuel demand and focus on clean energy will reduce the energy intensity to 0.21 (TOE/US$ of GDP) and carbon intensity to 0.42 (ton/US$ of GDP) under the GE scenario. total import bill (coal and oil) will amount to US$ 334 billion by 2030 (at 2010/11 prices), but as per the GE scenario, it would be US$ 194.2 billion, a saving of about US$ 140 billion. The building of a green energy economy can also serve another purpose: to develop new ‘pathways out of poverty’ by creating more than 10 million jobs and thus raise the standard of living of low-income people. The differences between the baseline and green energy scenarios are not so much the consequence of the diffusion of various technologies. It is the result of the active roles of different actors and the drivers that become dominant.

Keywords: emissions, green energy, fossil fuels, green jobs, renewables, scenario

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Jagdeep Singh, Prem Singh

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Milk is considered as an essential and complete food. The present study was conducted at Milk Plant Mohali especially in reference to the procurement section where the cash inflow was maximum, with the objective to achieve higher productivity and reduce wastage of milk. In milk plant it was observed that during the month of Jan-2014 to March-2014 the average procurement of milk was Rs. 4, 19, 361 liter per month and cost of procurement of milk is Rs 35/- per liter. The total cost of procurement thereby equal to Rs. 1crore 46 lakh per month, but there was mismatch in procurement-production of milk, which leads to an average loss of Rs. 12, 94, 405 per month. To solve the procurement-production problem Quality Control Tools like brainstorming, Flow Chart, Cause effect diagram and Pareto analysis are applied wherever applicable. With the successful implementation of Quality Control tools an average saving of Rs. 4, 59, 445 per month is done.

Keywords: milk, procurement-demand, quality control tools,

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Authors: Mohamad Ghozali Hassan, Abdul Aziz Othman, Mohd Azril Ismail

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Adapting quickly to environmental dynamism is essential for an organization to develop outsourcing strategic and management in order to sustain competitive advantage. This research used the Partial Least Squares Structural Equation Modeling (PLS-SEM) tool to investigate the factors of environmental dynamism impact on the strategic outsourcing success among electrical and electronic manufacturing industries in outsourcing management. Statistical results confirm that the inclusion of customer demand, technological change, and competition level as a new combination concept of environmental dynamism, has positive effects on outsourcing success. Additionally, this research demonstrates the acceptability of PLS-SEM as a statistical analysis to furnish a better understanding of environmental dynamism in outsourcing management in Malaysia. A practical finding contributes to academics and practitioners in the field of outsourcing management.

Keywords: environmental dynamism, customer demand, technological change, competition level, outsourcing success

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Authors: Paolo Guzzini, Emad Samuel M. Ebeid

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Bridges and Railways are critical infrastructures. Ensuring safety for transports using such assets is a primary goal as it directly impacts the lives of people. By the way, improving safety could require increased investments in O&M, and therefore optimizing resource usage for asset maintenance becomes crucial. Drones4Safety (D4S), a European project funded under the H2020 Research and Innovation Action (RIA) program, aims to increase the safety of the European civil transport by building a system that relies on 3 main pillars: • Drones operating autonomously in swarm mode; • Drones able to recharge themselves using inductive phenomena produced by transmission lines in the nearby of bridges and railways assets to be inspected; • Data acquired that are analyzed with AI-empowered algorithms for defect detection This paper describes the business model behind this disruptive project. The Business Model is structured in 2 parts: • The first part is focused on the design of the business model Canvas, to explain the value provided by the Drone4safety project; • The second part aims at defining a detailed financial analysis, with the target of calculating the IRR (Internal Return rate) and the NPV (Net Present Value) of the investment in a 7 years plan (2 years to run the project + 5 years post-implementation). As to the financial analysis 2 different points of view are assumed: • Point of view of the Drones4safety company in charge of designing, producing, and selling the new system; • Point of view of the Utility company that will adopt the new system in its O&M practices; Assuming the point of view of the Drones4safety company 3 scenarios were considered: • Selling the drones > revenues will be produced by the drones’ sales; • Renting the drones > revenues will be produced by the rental of the drones (with a time-based model); • Selling the data acquisition service > revenues will be produced by the sales of pictures acquired by drones; Assuming the point of view of a utility adopting the D4S system, a 4th scenario was analyzed taking into account the decremental costs related to the change of operation and maintenance practices. The paper will show, for both companies, what are the key parameters affecting most of the business model and which are the sustainable scenarios.

Keywords: a swarm of drones, AI, bridges, railways, drones4safety company, utility companies

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Authors: Gunnar Oskarsson, Gudjon Helgi Egilsson

Abstract:

Due to globalization, small and medium-sized enterprises (SME) increasingly offer their products and services in foreign markets. The main reasons are either to compensate for a decreased market share in their home market or to exploit opportunities in foreign markets, which are becoming less distant and better accessible than before. International markets are particularly important for companies located in a small economy and offering specialized products. Although more accessible, entering international markets is both expensive and difficult. In order to select the most appropriate markets, it is, therefore, important to gain an insight into the factors that have an impact on success, or potential failure. Although there has been a reasonable volume of research into the theory of internationalization, there is still a need to gain further understanding of the decision-making process of SMEs in small economies and the most important characteristics that distinguish between success and failure. The main objective of this research is to enhance knowledge on the internationalization of SMEs, including the drivers for the decision to internationalize, and the most important factors contributing to success in their internationalization activities. A qualitative approach was found to be most appropriate for this kind of research, with the objective of gaining a deeper understanding and discovering factors which impact a company’s decision-making and potential success. In-depth interviews were conducted with 14 companies in different industries located in Iceland, a country extensively dependent on export revenues. The interviews revealed several factors as drivers of internationalization and, not surprisingly, the most frequently mentioned source of motivation was that the local market is inadequate to maintain a sustainable operation. Good networking relationships were seen as a particular priority for potential success, searching for new markets was mainly carried out through the internet, although sales exhibitions and sales trips were also considered important. When it comes to the final decision as to whether a market should be considered for further analysis, economy, labor cost, legal environment, and cultural barriers were the most common factors to be weighted. The ultimate answer to successful internationalization, however, is largely dependent on a coordinated and experienced management team. The main contribution of this research is offering an insight into factors affecting decision-making in the internationalization process of SMEs, based on the opinion and experience of managers of SMEs in a small economy.

Keywords: internationalization, success factors, small and medium-sized enterprises (SMEs), drivers, decision making

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Authors: Rahul Malhotra

Abstract:

The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.

Keywords: routing protocol, MANET, AODV, On Demand Distance Vector Routing, DSR, Dynamic Source Routing

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Authors: Abimbola M. Enitan, Josiah Adeyemo, Sheena Kumari, Feroz M. Swalaha, Faizal Bux

Abstract:

With the competing demand on water resources and water reuse, discharge of industrial effluents into the aquatic environment has become an important issue. Much attention has been placed on the impact of industrial wastewater on water bodies worldwide due to the accumulation of organic and inorganic matter in the receiving water bodies. The scope of the present work is to assess the physic-chemical composition of the wastewater produced from one of the brewery industry in South Africa. This is to estimate the environmental impact of its discharge into the receiving water bodies or the municipal treatment plant. The parameters monitored for the quantitative analysis of brewery wastewater include biological oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids, volatile suspended solids, ammonia, total oxidized nitrogen, nitrate, nitrite, phosphorus, and alkalinity content. In average, the COD concentration of the brewery effluent was 5340.97 mg/l with average pH values of 4.0 to 6.7. The BOD and the solids content of the wastewater from the brewery industry were high. This means that the effluent is very rich in organic content and its discharge into the water bodies or the municipal treatment plant could cause environmental pollution or damage the treatment plant. In addition, there were variations in the wastewater composition throughout the monitoring period. This might be as a result of different activities that take place during the production process, as well as the effects of the peak period of beer production on the water usage.

Keywords: Brewery wastewater, environmental pollution, industrial effluents, physic-chemical composition

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Authors: Gaurav Gupta, Jitendra Mahakud

Abstract:

This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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Authors: P. Brinks, O. Kornadt, R. Oly

Abstract:

This research focuses on the optimization of glazed surfaces and the assessment of possible solar gains in industrial buildings. Existing window rating methods for single windows were evaluated and a new method for a simple analysis of energy gains and losses by single windows was introduced. Furthermore extensive transient building simulations were carried out to appraise the performance of low cost polycarbonate multi-cell sheets in interaction with typical buildings for industrial applications. Mainly, energy-saving potential was determined by optimizing the orientation and area of such glazing systems in dependency on their thermal qualities. Moreover the impact on critical aspects such as summer overheating and daylight illumination was considered to ensure the user comfort and avoid additional energy demand for lighting or cooling. Hereby the simulated heating demand could be reduced by up to 1/3 compared to traditional architecture of industrial halls using mainly skylights.

Keywords: solar architecture, Passive Solar Building Design, glazing, Low-Energy Buildings, industrial buildings

Procedia PDF Downloads 222