Search results for: polyacryl company

Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: distributed generation photovoltaic (DG PV), optimal location, penetration level, sub–transmission network

Procedia PDF Downloads 347

Authors: Lizinis Cassendra Frederick Dony, Jirom Jeremy Frederick Dony, Cyril Supain Christopher

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The purpose of this paper is to improve the devotion to leadership through HR practices implementation at the PETRONAS stations. This emphasize the importance of personal grooming and Customer Care hospitality training for their front line working individuals and teams’ at PETRONAS stations in Sabah. Based on Thomas Edison, International Leadership Journal, theory, research, education and development practice and application to all organizational phenomena may affect or be affected by leadership. FINDINGS – PETRONAS in short called Petroliam Nasional Berhad is a Malaysian oil and gas company that was founded on August 17, 1974. Wholly owned by the Government of Malaysia, the corporation is vested with the entire oil and gas resources in Malaysia and is entrusted with the responsibility of developing and adding value to these resources. Fortune ranks PETRONAS as the 68th largest company in the world in 2012. It also ranks PETRONAS as the 12th most profitable company in the world and the most profitable in Asia. As of the end of March 2005, the PETRONAS Group comprised 103 wholly owned subsidiaries, 19 partly owned outfits and 57 associated companies. The group is engaged in a wide spectrum of petroleum activities, including upstream exploration and production of oil and gas to downstream oil refining, marketing and distribution of petroleum products, trading, gas processing and liquefaction, gas transmission pipeline network operations, marketing of liquefied natural gas; petrochemical manufacturing and marketing; shipping; automotive engineering and property investment. PETRONAS has growing their marketing channel in a competitive market. They have combined their resources to pursue common goals. PETRONAS provides opportunity to carry out Industrial Training Job Placement to the University students in Malaysia for 6-8 months. The effects of the Industrial Training have exposed them to the real working environment experience acting representing on behalf of General Manager for almost one year. Thus, the management education and reward incentives schemes have aspire the working teams transformed to gain their good leadership. Furthermore, knowledge and experiences are very important in the human capital development transformation. SPSS extends the accurate analysis PETRONAS achievement through 280 questionnaires and 81 questionnaires through excel calculation distributed to interview face to face with the customers, PETRONAS dealers and front desk staffs stations in the 17 stations in Kota Kinabalu, Sabah. Hence, this research study will improve its service quality innovation and business sustainability performance optimization. ORIGINALITY / VALUE – The impact of Transformational Leadership practices have influenced the working team’s behaviour as a Brand Ambassadors of PETRONAS. Finally, the findings correlation indicated that PETRONAS stations needs more HR resources practices to deploy more customer care retention resources in mitigating the business challenges in oil and gas industry. Therefore, as the business established at stiff competition globally (Cooper, 2006; Marques and Simon, 2006), it is crucial for the team management should be capable to minimize noises risk, financial risk and mitigating any other risks as a whole at the optimum level. CONCLUSION- As to conclude this research found that both transformational and transactional contingent reward leadership4 were positively correlated with ratings of platoon potency and ratings of leadership for the platoon leader and sergeant were moderately inter correlated. Due to this identification, we recommended that PETRONAS management should offers quality team management in PETRONAS stations in a broader variety of leadership training specialization in the operation efficiency at the front desk Customer Care hospitality. By having the reliability and validity of job experiences, it leverages diversity teamwork and cross collaboration. Other than leveraging factor, PETRONAS also will strengthen the interpersonal front liners effectiveness and enhance quality of interaction through effective communication. Finally, through numerous CSR correlation studies regression PETRONAS performance on Corporate Social Performance and several control variables.1 CSR model activities can be mis-specified if it is not controllable under R & D which evident in various feedbacks collected from the local communities and younger generation is inclined to higher financial expectation from PETRONAS. But, however, it created a huge impact on the nation building as part of its social adaptability overreaching their business stakeholders’ satisfaction in Sabah.

Keywords: human resources practices implementation (hrpi), source of competitive advantage in people’s development (socaipd), corporate social responsibility (csr), service quality at front desk stations (sqafd), impacts of petronas leadership (iopl)

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Authors: Hüseyin Altubaş, Hasret Aktaş, A. Mücahid Zengin

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Children determine the direction of the power of consumption. They affect the decisions of their parents but they also reached to a significant purchasing power themselves. Children, who are turning interactive behavior to normal behavior are becoming the decision makers in a company’s survival. Companies that analyze this effective target audience can communicate successfully with children. Children, who are interactive individuals, are closer to advertising. They are almost talking better with advertising. They are not afraid to express their likings, as well as their dislikes. Children have an interactive lifestyle and they were exposed to the vast changes in technology after year 2000. They do not know a life without internet, they spend mobile life in internet. This Z generation is the new determinants of brands. Z generation finds it appropriate to be brand ambassadors and they completely changed traditional media and traditional consumer behavior. These children live social reality with virtual reality and they feed brands differently. Brands that interact with Z generation are affected by this feeding positively, while brands that keep interaction in traditional levels are affected negatively. In this research we examine the communication, advertising and brand behaviors of Z generation. We especially analyze this generation’s interaction with social media brands and their interactive attitudes.

Keywords: social media, Z generation, children, advertising, brand choice

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Authors: Yared Yitagesu Tilahun

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Every nation, developed or developing, relies on transportation, but Addis Abeba City's transportation service is impacted by a number of variables. The current study's objectives are to determine the factors that influence transportation and gauge consumer satisfaction with such services in Addis Abeba. Customers and employees of Addis Ababa's transportation service authority would be the study's target group. 40 workers of the authority would be counted as part of the 310 000 clients that make up the population of the searcher service. Using a straightforward random selection technique, the researcher only chose 99 customers and 28 staff from this enormous group due to the considerable cost and time involved. Data gathering and analysis options included both quantitative and qualitative approaches. The results of this poll show that young people between the ages of 18 and 25 make up the majority of respondents (51.6%). The majority of employees and customers indicated that they are not satisfied with Addis Ababa's overall transportation system. The Addis Abeba Transportation Authority prioritizes client happiness by providing fair service. The company should have a system in place for managing time, resources, and people effectively. It should also provide employees the opportunity to contribute to client handling policies.

Keywords: transportation, customer satisfaction, services, determinants

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Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: Shanshan Zhou, Massimo Battaglia

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Identity plays a critical role when an organization faces disasters. Individuals reflect on their working identities and identify themselves with the group and the organization, which facilitate collective sensemaking under crisis situations and enable coordinated actions to respond to and recover from disasters. In addition, an organization’s identity links it to its regional community, which fosters the mobilization of resources and contributes to rapid recovery. However, identity is also problematic for disaster prevention because of its persistence. An organization’s ego-defenses system prohibits the rethink of its identity and a rigid identity obstructs disaster prevention. This research aims to tackle the ‘problem’ of identity by study in-depth a case of an Italian multi–utility which experienced the 2012 Northern Italy earthquakes. Collecting data from 11 interviews with top managers and key players in the local community and archived materials, we find that the earthquakes triggered the rethink of the organization’s identity, which got reinforced afterward. This research highlighted the importance of identity in disaster response and recovery. More importantly, it explored the solution of overcoming the barrier of ego-defense that is to transform the organization into a learning organization which constantly rethinks its identity.

Keywords: community identity, disaster, identity, organizational learning

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Authors: Farah Kanani

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Blue Tide Environmental is a company focused on developing a network of used motor oil recycling facilities across the U.S. They initiated the redesign of its recycling plant in Texas, and aimed to establish an updated carbon footprint of re-refined used motor oils compared to an equivalent product derived from virgin stock that is not re-refined. The aim was to quantify emissions savings of a circular alternative to conventional end-of-life combustion of used motor oil (UMO). To do so, they mandated an ISO-compliant carbon footprint, utilizing complex models requiring geographical and temporal accuracy to accommodate the U.S. refinery market. The quantification of linear and circular flows, proxies for fuel substitution and system expansion for multi-product outputs were all critical methodological choices and were tested through sensitivity analyses. The re-refined system consisted of continuous recycling of UMO and thus, end-of-life is considered non-existent. The unique perspective to this topic will be from a life cycle i.e. holistic one and essentially demonstrate using this example of how a cradle-to-cradle model can be used to quantify a comparative carbon footprint. The intended audience is lubricant manufacturers as the consumers, motor oil industry professionals and other industry members interested in performing a cradle-to-cradle modeling.

Keywords: circularity, used motor oil, re-refining, systems expansion

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: A. Porshnev, A. Zaporozhtchuk

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Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

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Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

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Authors: Wen-Hsiang Lai

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Except for the internal aspects of entrepreneurship (i.e. motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares the internal knowledge within industrial clusters. This study finds that when comparing to the companies which are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: entrepreneurship, industrial cluster, industrial district, economies of agglomerations, Taiwan Machinery Cluster (TMC)

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Authors: Ebrahim Sabermaash Eshghi, Donna Sandsmark

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In changing modern economic conditions of the world, one the most important issues facing managers of firms, is increasing the sales and profitability through sales of newly developed products. This is while purpose of decreasing unnecessary costs is one of the most essential programs of smart managers for more implementation with new conditions in current business. In modern life, condition of misgiving is dominant in all of the industries. Accordingly, in this research, influence of different aspects of presenting products to the market is investigated. This study is done through a Quantitative-Qualitative (Interviews and Questionnaire) approach. In sum, 103 of informed managers and experts of Pars-Khazar Company have been examined through census. Validity of measurement tools was approved through judgments of experts. Reliability of tools was gained through Cronbach's alpha coefficient in size of 0.930 and in sum, validity and reliability of tools were approved generally. Results of regression test revealed that the influence of all aspects of product introduction supported the performance of product, positively and significantly. In addition that influence of two new factors raised from the interview, namely Human Resource Management and Management of product’s pre-test on performance of products was approved.

Keywords: introducing products, performance, home appliances, price, advertisement, production

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Authors: Amirmehdi Dokhanchi, Babak Ziyae

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Studying and prioritizing effective factors on productivity of human resources through TOPSIS method is the main aim of the present research study. For this reason, while reviewing concepts existing in productivity, effective factors were studied. Managers, supervisors, staff and personnel of Tabriz Tractor Manufacturing Company are considered subject of this study. Of total individuals, 160 of them were selected through the application of random sampling method as 'subject'. Two questionnaires were used for collecting data in this study. The factors, which had the highest effect on productivity, were recognized through the application of software packages. TOPSIS method was used for prioritizing recognized factors. For this reason, the second questionnaire was put available to statistics sample for studying effect of each of factors towards predetermined indicators. Therefore, decision-making matrix was obtained. The result of prioritizing factors shows that existence of accurate organizational strategy, high level of occupational skill, application of partnership and contribution system, on-the-job-training services, high quality of occupational life, dissemination of appropriate organizational culture, encouraging to creativity and innovation, and environmental factors are prioritized respectively.

Keywords: productivity of human resources, productivity indicators, TOPSIS, prioritizing factors

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Authors: Mamoon Mousa Atout

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Projects managers in construction industry usually face a difficult organizational environment especially if the project is unique. The organization lacks the processes to practice construction management correctly, and the executive’s technical managers who have lack of experience in playing their role and responsibilities correctly. Project managers need to adopt best practices that allow them to do things effectively to make sure that the project can be delivered without any delay even though the executive’s technical managers should follow a certain process to avoid any factor might cause any delay during the project life cycle. The purpose of the paper is to examine the awareness level of projects managers about construction management processes, tools, techniques and implications to complete projects on time. The outcome and the results of the study are prepared based on the designed questionnaires and interviews conducted with many project managers. The method used in this paper is a quantitative study. A survey with a sample of 100 respondents was prepared and distributed in a construction company in Dubai, which includes nine questions to examine the level of their awareness. This research will also identify the necessary benefits of processes of construction management that has to be adopted by projects managers to mitigate the maximum potential problems which might cause any delay to the project life cycle.

Keywords: construction management, project objectives, resource planing and scheduling, project completion

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Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

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Authors: Jan-Philipp Schiele, Karsten Schlinkmeier

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Allocation of scarce resources is a core process of traditional project portfolio management. However, with the popularity of agile methodology, established concepts and methods of portfolio management are reaching their limits and need to be adapted. Consequently, the question arises of how the process of resource allocation can be managed appropriately in scaled agile environments. The prevailing framework SAFe offers Weightest Shortest Job First (WSJF) as a prioritization technique, butestablished companies are still looking for methodical adaptions to apply WSJF for prioritization in portfolios in a more goal-oriented way and aligned for their needs in practice. In this paper, the relevant problem of prioritization in portfolios is conceptualized from the perspective of coordination and related mechanisms to support resource allocation. Further, an Action Design Research (ADR) project with case studies in a finance company is outlined to develop a practically applicable yet scientifically sound prioritization method based on coordination theory. The ADR project will be flanked by consortium research with various practitioners from the financial and insurance industry. Preliminary design requirements indicate that the use of a feedback loop leads to better team and executive level coordination in the prioritization process.

Keywords: scaled agility, portfolio management, prioritization, business-IT alignment

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Authors: Vesna Bosilj Vukšić, Darija Ivandić Vidović, Ljubica Milanović Glavan

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Information technology plays an irreplaceable role in introducing and improving business process orientation in a company. It enables implementation of the theoretical concept, measurement of results achieved and undertaking corrective measures aimed at improvements. Information technology is a key concept in the development and implementation of the business process management systems as it establishes a connection to business operations. Both in the literature and practice, insurance companies are often seen as highly process oriented due to the nature of their business and focus on customers. They are also considered leaders in using information technology for business process management. The research conducted aimed to investigate whether the perceived leadership status of insurance companies is well deserved, i.e. to establish the level of process orientation and explore the practice of information technology use in insurance companies in the region. The main instrument for primary data collection within this research was an electronic survey questionnaire sent to the management of insurance companies in the Republic of Croatia, Bosnia and Herzegovina, Slovenia, Serbia and Macedonia. The conducted research has shown that insurance companies have a satisfactory level of process orientation, but that there is also a huge potential for improvement, especially in the segment of information technology and its connection to business processes.

Keywords: business processes management, process orientation, information technology, insurance companies

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Authors: Katarzyna Niewiadomska

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Many technology startups fail to achieve a worthwhile return on investment for their funders, founders, and employees. Failures in product development, to-market strategy, sales, and delivery are commonly recognized. Founder failures are not as obvious and harder to identify. This paper explores six critical failure points that entrepreneurs and innovators are susceptible to and aims to link their emotional intelligence and behavioral profile to the points at which they experienced self-perceived failure. A model of six failure points from the perspective of the technology entrepreneur ranging from pre-startup to maturity is provided. By analyzing emotional and behavioral profile data from entrepreneurs and recording in-person accounts, certain key emotional and behavioral clusters contributing to each failure point are determined, and several underlying factors are defined and discussed. Recommendations that support entrepreneurs and innovators stalling at each failure point are given. This work can enable stakeholders to evaluate founder emotional and behavioral profiles and to take risk-mitigating action, either through coaching or through more robust team creation, to avoid founder-related company failure. The paper will be of interest to investors funding startups, executives leading them and mentors supporting them.

Keywords: behavior, emotional intelligence, entrepreneur, failure

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Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Lisandy A. Suryana, Lidia Mayangsari, Santi Novani

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Creative industry in Indonesia become an important aspect of the economy. One of the sectors of creative industry which give the highest contribution toward Indonesia’s GDP is fashion sector. In line with the target of Indonesia in 2020 to be the qibla’ of moeslem fashion of the world, all of the stakeholders of the business ecosystem should collaborate. Rather than focus on the internal aspects of producer, external aspects such as customers, government, community, etc. become important to be involved in the ecosystem to support the development and sustainability of those fashion sector. Unfortunately, although Indonesia has the biggest moeslem population, the number of hijab business penetration only 10%. Therefore, this research aims to analyze and develop the virtual co-creation platform for hijab creative industry as the strategy to achieve sustainability and increase the market share. This preliminary research describes the main stakeholders in the hijab creative industry based on business model approach. This business model is adapted by considering the service science context, and the data is collected by using the qualitative approach especially in-depth interview. This business model shows the relationship between resource integration, value co-creation, the value proposition of the company, and also the financial aspect of the business.

Keywords: value co-creation, Hijab Fashion Industry, creative industry, service business model, business model canvas

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Authors: Abeer Amayri, Akif A. Bulgak

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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Ved Kulkarni, Karthik Kini

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This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.

Keywords: data mining, language processing, artificial neural networks, sentiment analysis

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Authors: M. T. Darzi, M. Shirkhodaei, M. R. Haj Seyed Hadi

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The main objective of this study was to determine the effects of organic fertilizer and azotobacter and azospirillum bacteria on concentration and composition of essential oil in the coriander essential oil content, essential oil yield, linalool percent, alpha pinene percent and cymene percent in essential oil. The experiment was carried out as factorial experiment in the base of randomized complete blocks design with eight treatments and three replications at research field of Agriculture Company of Ran in Firouzkuh of iran in 2012. The factors were Vermicompost in four levels (0, 3, 6 and 9 ton/ha) and biofertilizer, mixture of Azotobacter chroococcum and Azospirillum lipoferum in two levels (non-inoculated and inoculated seeds). The present results have shown that vermicompost had significant effects on evaluated traits except linalool percent in essential oil, as the highest essential oil content, essential oil yield and alpha pinene percent in essential were obtained after applying 6 ton/ha vermicompost. The minimum cymene percent in essential oil were obtained after applying 6 ton/ha vermicompost. Biofertilizer also showed significant effects on essential oil yield only. The highest essential oil yield were obtained by using the biofertilizer (inoculated seeds).

Keywords: coriander, vermicompost, biofertilizer, essential oil

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: J. Niemisto, A. Nissinen, S. Soimakallio

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Aviation causes carbon dioxide (CO2) emissions and other climate forcers which increase the contribution of aviation on climate change. Aviation industry and number of air travellers are constantly increasing. Aviation industry has an ambitious goal to strongly cut net CO2 emissions. Modern fleet, alternative jet fuels technologies and route optimisation are important technological tools in the emission reduction. Faster approaches are needed as well. Emission trade systems, voluntary carbon offset compensation schemes and taxation are already in operation. Global scenarios of aviation industry and its greenhouse gas emissions and other climate forcers are discussed in this review study based on literature and other published data. The focus is on the aviation in Nordic countries, but also European and global situation are considered. Different emission reduction technologies and compensation modes are examined. In addition, the role of aviation in a single passenger’s (a Finnish consumer) annual carbon footprint is analysed and a comparison of available emission calculators and carbon offset systems is performed. Long-haul fights have a significant role in a single consumer´s and company´s carbon footprint, but remarkable change in global emission level would need a huge change in attitudes towards flying.

Keywords: aviation, climate change, emissions, environment

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Göksel Şimşek

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Celebrities are admired, appreciated and imitated all over the world. As a natural result of this, today many brands choose to work with celebrities for their advertisements. It can be said that the more the brands include celebrities in their marketing communication strategies, the tougher the competition in this field becomes and they allocate a large portion of their marketing budget to this. Brands invest in celebrities who will represent them in order to build the image they want to create. This study aimed to bring under spotlight the perceptions of Turkish customers regarding the use of celebrities in advertisements and marketing communication and try to understand their possible effects on subsequent purchasing decisions. In addition, consumers’ reactions and perceptions were investigated in the context of the product-celebrity match, to what extent the celebrity conforms to the concept of the advertisement and the celebrity-target audience match. In order to achieve this purpose, a quantitative research was conducted as a case study concerning Mavi Jeans (textile company). Information was obtained through survey. The results from this case study are supported by relevant theories concerning the main subject. The most valuable result would be that instead of creating an advertisement around a celebrity in demand at the time, using a celebrity that fits the concept of the advertisement and feeds the concept rather than replaces it, that is celebrity endorsement, will lead to more striking and positive results.

Keywords: celebrity endorsement, product-celebrity match, advertising, social sciences

Procedia PDF Downloads 204

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 89

Authors: C. Okonkwo Ugochukwu, E. Sinebe Jude, N. Odoh Blessing, E. Okafor Christian

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In this paper, a modification on repair workshop queuing system using multi priority scheme was carried out. Chi square goodness of fit test was used to determine the random distribution of the inter arrival time and service time of crankshafts that come for maintenance in the workshop. The chi square values obtained for all the prioritized classes show that the distribution conforms to Poisson distribution. The mean waiting time in queue results of non-preemptive priority for 1st, 2nd and 3rd classes show 0.066, 0.09, and 0.224 day respectively, while preemptive priority show 0.007, 0.036 and 0.258 day. However, when non priority is used, which obviously has no class distinction it amounts to 0.17 days. From the results, one can observe that the preemptive priority system provides a very dramatic improvement over the non preemptive priority as it concerns arrivals that are of higher priority. However, the improvement has a detrimental effect on the low priority class. The trend of the results is similar to the mean waiting time in the system as a result of addition of the actual service time. Even though the mean waiting time for the queue and that of the system for no priority takes the least time when compared with the least priority, urgent and semi-urgent jobs will terribly suffer which will most likely result in reneging or balking of many urgent jobs. Hence, the adoption of priority scheme in this type of scenario will result in huge profit to the Company and more customer satisfaction.

Keywords: queue, priority class, preemptive, non-preemptive, mean waiting time

Procedia PDF Downloads 395