Search results for: spot price volatility

Authors: Abdou Mahmoud Abdou Hussein

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We attempt, in this paper, to spot the light on the difference between the two concepts (diglossia and bilingualism). Thus, we will show the definition of these two concepts among various perspectives. On the other hand, we will emphasize and highlight 'diglossa' in The Arabic language historically. Furthermore, we will illustrate the factors of the diglossia, the impact of diglossia on the learners of Arabic (native and non native speakers) and finally the suggested solutions for this issue.

Keywords: Arabic linguistics, diglossia, bilingualism, native and non-native speakers

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Authors: Rudi Kurniawan Arief

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Manufacturing cost and setup time are the hot topics to improve in Metal Stamping industry because material and components price are always rising up while costumer requires to cut down the component price year by year. The Single Minute Exchange of Die (SMED) is one of many methods to reduce waste in stamping industry. The Japanese Quick Die Change (QDC) dies system is one of SMED systems that could reduce both of setup time and manufacturing cost. However, this system is rarely used in stamping industries. This paper will analyze how deep the QDC dies system could reduce setup time and the manufacturing cost. The research is conducted by direct observation, simulating and comparing of QDC dies system with conventional dies system. In this research, we found that the QDC dies system could save up to 35% of manufacturing cost and reduce 70% of setup times. This simulation proved that the QDC die system is effective for cost reduction but must be applied in several parallel production processes.

Keywords: press die, metal stamping, QDC system, single minute exchange die, manufacturing cost saving, SMED

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Authors: Badrane Nohayla, Bamousse Zineb

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Financial crises, exchange rate volatility, fluctuations in commodity prices, increased competitive pressures, and environmental issues are all threats that businesses face. In light of these diverse challenges, proactive, agile, and innovative cash management becomes an indispensable financial shield, allowing companies to thrive despite the adverse conditions of the global environment. In the same spirit, uncertainty, turbulence, volatility, and competitiveness continue to disrupt economic environments, compelling companies to swiftly master innovative breakthroughs that provide added value. In such a context, innovation emerges as a catalytic vector for performance, aiming to reduce costs, strengthen growth, and ultimately ensure the sustainability of Moroccan companies in the national arena. Moreover, innovation in treasury management promises to be one of the key pillars of financial stability, enabling companies to navigate the tumultuous waters of a globalized environment. Therefore, the objective of this study is to better understand the impact of innovative treasury management on cost optimization and, by extension, performance improvement. To elucidate this relationship, we conducted an exploratory qualitative study with 20 large Moroccan companies operating in the Casablanca-Settat region. The results highlight that innovation at the heart of treasury management is a guarantee of sustainability against the risks of failure and stands as a true pivot of the performance of Moroccan companies, an important parameter of their financial balance and a catalytic vector of their growth in the national economic landscape. In this regard, the present study aims to explore the extent to which innovation at the core of the treasury function serves as an indispensable tool for boosting performance while optimising costs in large Moroccan companies.

Keywords: innovative cash management, artificial intelligence, financial performance, risk management, cost savings

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Authors: Avinash Kishore, Suman Chakrabarti

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In September 2013, the parliament of India enacted the National Food Security Act (NFSA) which entitles two-thirds of India’s population to five kilograms of rice, wheat or coarse cereals per person per month at one to three rupees per kilogram. Five states in India—Andhra Pradesh, Chhattisgarh, Tamil Nadu, Odisha and West Bengal—had already implemented somewhat similar changes in the TPDS a few years earlier using their own budgetary resources. They made rice—coincidentally, all five states are predominantly rice-eating—available in fair price shops to a majority of their population at very low prices (less than Rs.3/kg). This paper tries to account for the changes in household consumption patterns associated with the change in TPDS policy in these states using data from household consumption surveys by the National Sample Survey Organization (NSSO). NSS data show improvement in the coverage of TPDS and average off-take of grains from fair price shops between 2004-05 and 2009-10 across all states of India. However, the increase in coverage and off-take was significantly higher in four out of these five states than in the rest of India. An average household in these states purchased three kilos more rice per month from fair price shops than its counterpart in non-treated states as a result of more generous TPDS policies backed by administrative reforms. The increase in consumption of PDS rice was the highest in Chhattisgarh, the poster state of PDS reforms. Households in Chhattisgarh used money saved on rice to spend more on pulses, edible oil, vegetables and sugar and other non-food items. We also find evidence that making TPDS more inclusive and more generous is not enough unless it is supported by administrative reforms to improve grain delivery and control diversion to open markets.

Keywords: public distribution system, social safety-net, national food security act, diet quality, Chhattisgarh

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Authors: Muna Jalal Ali, Essam A. Makky, Mashitah M. Yusoff

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Objectives: The aim of this study to evaluate the antimicrobial susceptibility of combined toothpaste with medicinal plants and the relations between the commercial toothpaste to its price and the patient age as well. Materials and Methods: Oral isolates of different patients aged 3 to 60 years were obtained, purified, and tested against four different ethnomedicinal plant extracts for antimicrobial activity. A total of 10 different commercial toothpastes (different brands and prices) were collected from the market, and the combined action of the medicinal plants and toothpaste was studied. Results: We found a higher bacterial population in the age group of 3–40 years than the group of 40–60 years, with approximately 44% and 32%, respectively. The combined action of ethanolic extract (alone) against oral isolates showed a synergistic effect, with 32.20, 30.50, and 25.42% for combinations A (Ci/Ca), B (Ci/Ca/P), and C (Ci/Ca/P/N), respectively. By contrast, the combined action of ethnomedicinal plants with 10 different toothpastes improved the antimicrobial sensitivity by 60, 100, and 0% for combinations A, B, and C respectively. Clinical relevance: The ethanolic extract of only combinations A and B with commercial toothpaste showed high antibacterial activity against oral isolates and the effectiveness of toothpaste is not related to the price.

Keywords: microbial evolution, oral isolates, ethnomedicinal plants, antimicrobial activity, toothpaste

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Authors: Mengna Hu

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This paper examines the impact of an anti-speculation tax policy on the trading activities and home price movements in the housing market in Hong Kong. The study focuses on the secondary residential property market where transactions dominate. The policy intervention substantially raised the transaction cost to speculators as well as genuine homeowners who dispose their homes within a certain period. Through the demonstration of structural breaks, our empirical results show that the rise in transaction cost effectively reduced speculative trading activities. However, it accelerated price increase in the small-sized segment by vastly demotivating existing homeowners from trading up to better homes, causing congestion in the lower-end market where the demand from first-time buyers is still strong. Apart from that, by employing regime switching approach, we further show that the unintended consequences are likely to be persistent due to this policy together with other strengthened cooling measures.

Keywords: transaction costs, housing market, structural breaks, regime switching

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Authors: Xiaobin Liang, Wei Liang, Laibin Zhang, Xiaoyan Guo

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Pipelines pass through coal mined gobs inevitably in the mining area, the stability of which has great influence on the safety of pipelines. After extensive literature study and field research, it was found that there are a few risk assessment methods for coal mined gob pipelines, and there is a lack of data on the gob sites. Therefore, the fuzzy comprehensive evaluation method is widely used based on expert opinions. However, the subjective opinions or lack of experience of individual experts may lead to inaccurate evaluation results. Hence the accuracy of the results needs to be further improved. This paper presents a comprehensive approach to achieve this purpose by combining bow-tie model and cloud inference. The specific evaluation process is as follows: First, a bow-tie model composed of a fault tree and an event tree is established to graphically illustrate the probability and consequence indicators of pipeline failure. Second, the interval estimation method can be scored in the form of intervals to improve the accuracy of the results, and the censored mean algorithm is used to remove the maximum and minimum values of the score to improve the stability of the results. The golden section method is used to determine the weight of the indicators and reduce the subjectivity of index weights. Third, the failure probability and failure consequence scores of the pipeline are converted into three numerical features by using cloud inference. The cloud inference can better describe the ambiguity and volatility of the results which can better describe the volatility of the risk level. Finally, the cloud drop graphs of failure probability and failure consequences can be expressed, which intuitively and accurately illustrate the ambiguity and randomness of the results. A case study of a coal mine gob pipeline carrying natural gas has been investigated to validate the utility of the proposed method. The evaluation results of this case show that the probability of failure of the pipeline is very low, the consequences of failure are more serious, which is consistent with the reality.

Keywords: bow-tie model, natural gas pipeline, coal mine gob, cloud inference

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Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

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Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

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Authors: Velly Anatasia

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The worldwide annual expenditure for cosmetics is estimated at U.S. $18 billion and many players in the field are competing aggressively to capture more and more markets. Players in the cosmetics industry strive to be the foremost by establish customer loyalty. Furthermore, customer loyalty is portrayed by brand loyalty. Therefore, brand loyalty is the key determine of winning the competition in tight market. This study examines the influence of brand loyalty on cosmetics buying behavior of female consumers in Jakarta as capital of Indonesia. The seven factors of brand loyalty are brand name, Product quality, price, design, promotion, servicesquality and store environment. The paper adopted descriptive analysis, factor loading and multiple regression approach to test the hypotheses. The data has been collected by using questionnaires which were distributed and self-administered to 125female respondents accustomed using cosmetics. The findings of this study indicated that promotion has shown strong correlation with brand loyalty. The research results showed that there is positive and significant relationship between factors of brand loyalty (brand name, product quality, price, design, promotion, services quality and store environment) with cosmetics brand loyalty.

Keywords: brand loyalty, brand name, product quality, service quality, promotion

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Pisit Potjanajaruwit

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The objectives of the study were to determine the marketing mix factors that influencing tourist’s destination decision making for cultural tourism in the Chonburi province. Both quantitative and qualitative data were applied in this study. The samples of 400 cases for quantitative analysis were tourists (both Thai and foreign) who were interested in cultural tourism in the Chonburi province, and traveled to cultural sites in Chonburi and 14 representatives from provincial tourism committee of Chonburi and local tourism experts. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The study found that Thai and foreign tourists are influenced by different important marketing mix factors. The important factors for Thai respondents were physical evidence, price, people, and place at high importance level. For foreign respondents, physical evidence, price, people, and process were high importance level, whereas, product, place, and promotion were moderate importance level.

Keywords: Chonburi Province, decision making, cultural tourism, marketing mixed

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Authors: Elisa Menicucci, Guido Paolucci

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Purpose: The aim of this paper is to investigate the factors influencing profitability in the Italian hospitality industry during the period 2008-2016. Design/methodology/approach: This study examines the profitability and its determinants using a sample of 2366 Italian hotel firms. First, we use a multidimensional measure of profitability including attributes as return on equity, return on assets and occupancy rate. Second, we examine variables that are potentially related with performance and we sort these into five categories: market variables, business model, ownership structure, management education and control variables. Findings: The results show that financial crisis, business model and ownership structure influence profitability of hotel firms. Specific factors such as the internationalization, location, firm’s declaring accommodation as their primary activity and chain affiliation are associated positively with profitability. We also find that larger hotel firms have higher performance rankings, while hotels with higher operating cash flow volatility, greater sales volatility and a higher occurrence of losses have lower profitability. Research limitations/implications: Findings suggest the importance of considering firm specific factors to evaluate the profitability of a hotel firm. Results also provide evidence for academics to critically evaluate factors that would ensure profitability of hotels in developed countries such as Italy. Practical implications: This investigation offers valuable information and strategic implications for government, tourism policymakers, tourist hotel owners, hoteliers and tourism managers in their decision-making. Originality/value: This paper provides interesting insights into the characteristics and practices of profitable hotels in Italy. Few econometric studies empirically explored the determinants of performance in the European hospitality field so far. Therefore, this paper tries to close an important gap in the existing literature improving the understanding of profitability in the Italian hospitality industry.

Keywords: hotel firms, profitability, determinants, Italian hospitality industry

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Authors: Murad A. Bein

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This paper empirically examines the time-varying relationship and spillover effects between the international crude oil price and ten emerging equity markets, namely three oil-exporting countries (Brazil, Mexico, and Russia) and seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, and Slovakia). The results revealed that there are spillover effects from oil markets into almost all emerging equity markets save Slovakia. Besides, the oil supply glut had a homogenous effect on the emerging markets, both net oil-exporting, and oil-importing countries (CEE). Further, the time variance drastically increased during financial turmoil. Indeed, the time variance remained high from 2009 to 2012 in response to aggregate demand shocks (global financial crisis and Eurozone debt crisis) and quantitative easing measures. Interestingly, the time variance was slightly higher for the oil-exporting countries than for some of the CEE countries. Decision-makers in emerging economies should therefore seek policy coordination when dealing with financial turmoil.

Keywords: crude oil, spillover effects, emerging equity, time-varying, aggregate demand shock

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Authors: Maria Evnevich

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In modern conditions, in most markets, price competition is becoming less effective. On the one hand, there is a gradual decrease in the level of marginality in main traditional sectors of the economy, so further price reduction becomes too ‘expensive’ for the company. On the other hand, the effect of price reduction is leveled, and the reason for this phenomenon is likely to be informational. As a result, it turns out that even if the company reduces prices, making its products more accessible to the buyer, there is a high probability that this will not lead to increase in sales unless additional large-scale advertising and information campaigns are conducted. Similarly, a large-scale information and advertising campaign have a much greater effect itself than price reductions. At the same time, the cost of mass informing is growing every year, especially when using the main information channels. The article presents generalization, systematization and development of theoretical approaches and best practices in the field of customer focus approach to business management and in the field of relationship marketing in the modern digital economy. The research methodology is based on the synthesis and content-analysis of sociological and marketing research and on the study of the systems of working with consumer appeals and loyalty programs in the 50 largest client-oriented companies in Russia. Also, the analysis of internal documentation on customers’ purchases in one of the largest retail companies in Russia allowed to identify if buyers prefer to buy goods for complex purchases in one retail store with the best price image for them. The cost of attracting a new client is now quite high and continues to grow, so it becomes more important to keep him and increase the involvement through marketing tools. A huge role is played by modern digital technologies used both in advertising (e-mailing, SEO, contextual advertising, banner advertising, SMM, etc.) and in service. To implement the above-described client-oriented omnichannel service, it is necessary to identify the client and work with personal data provided when filling in the loyalty program application form. The analysis of loyalty programs of 50 companies identified the following types of cards: discount cards, bonus cards, mixed cards, coalition loyalty cards, bank loyalty programs, aviation loyalty programs, hybrid loyalty cards, situational loyalty cards. The use of loyalty cards allows not only to stimulate the customer to purchase ‘untargeted’, but also to provide individualized offers, as well as to produce more targeted information. The development of digital technologies and modern means of communication has significantly changed not only the sphere of marketing and promotion, but also the economic landscape as a whole. Factors of competitiveness are the digital opportunities of companies in the field of customer orientation: personalization of service, customization of advertising offers, optimization of marketing activity and improvement of logistics.

Keywords: customer focus, digital economy, loyalty program, relationship marketing

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Authors: Tamar Trop, Michal Roffeh

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One of the emerging trends in construction is installing an exterior “green wall” (GW). GW is an overarching and most common term for various techniques of incorporating greenery into buildings’ vertical elements, mainly facades. This green infrastructure yields numerous benefits for the urban environment, the public, and the buildings’ tenants and users, such as enhancing air quality and biodiversity, managing stormwater runoff, mitigating urban heat island and climate change, improving urban aesthetics and mental wellbeing, improving indoor comfort conditions, and saving energy. Yet, the penetration rate of GWs into the construction market, especially into the housing sector, is still very slow. Furthermore, the research regarding prospective homebuyers’ willingness to purchase and pay a price premium for GW apartments is scarce and does not refer to newly built buildings and specific GW types. This research aims to narrow these knowledge gaps by exploring the willingness of prospective homebuyers in Israel to purchase a newly built apartment with a hydroponic living wall, the size of the PP that they would be willing to pay for it, and the various factors ̶ knowledge-related, concern, economic, and personal ̶ that influence these motivations. A nationwide online survey was conducted among a sample of 514 adults using a structured questionnaire. Findings show that despite low familiarity with GWs and strong concerns about various kinds of nuisance, technical issues, and maintenance costs, potential homebuyers express a relatively high willingness to purchase and pay a significant price premium for such an apartment. The main motivations behind this willingness were found to be potential energy savings and governmental incentives. Study findings can contribute to a better understanding of the maturity of the housing market in Israel to adopt GWs and to better tailor intervention tools for increasing GWs’ uptake among potential homebuyers.

Keywords: green façade, green wall, living wall, willingness to pay

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Sara Sousa

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The environmental goods and services have often been neglected in crucial decisions affecting the environment mainly because the difficulty in estimating their economic value, since we are dealing with non-market goods and, thus, without a price associated. Nevertheless, the inexistence of prices does not necessarily mean these goods have no value. The environment is a key element in today's society that seeks to be as sustainable as possible, where the environmental assets have both use and non-use values. To estimate the use value, researchers may apply the revealed preference methods. This paper provides a theoretical review of the main concepts and methodologies on the economic valuation of the environment, with particular emphasis on the revealed preference techniques. Based on a detailed literature review, this study concludes that, despite some inherent limitations, the revealed preference methodologies – travel cost, hedonic price, and averting behaviour – represent essential tools for the researchers who accept the challenge to estimate the use value of environmental goods and services based on the actual individuals` behaviour. The main purpose of this study is to contribute to an increased theoretical information on the economic valuation of environmental assets, allowing researchers and policymakers to improve future decisions regarding the environment.

Keywords: economic valuation, environmental goods, revealed preference methods, total economic value

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Authors: Phutthiwat Waiyawuththanapoom, Pimploi Tirastittam, Manop Tirastittam

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Thailand is the agriculture country which mainly exports the agriculture product to the other countries in so many ways which are fresh vegetable, chilled vegetable or frozen vegetable. The gross export for Thailand’s vegetable is 30-40 billion baht per year, and the growth rate is about 15-20 percent per year. Ginger is one of the main vegetable product that Thailand export to Japan because Thailand’s Ginger has a good quality and be able to supply Japan’s demand with a reasonable price. This research paper is aimed to study the factors which affect the efficiency of the supply chain process of Thailand’s ginger to Japan. There are 5 factors which related to the exporting Thailand’s ginger to Japan which are quality, price, equipment and supply standard, custom process and distribution pattern. The result of the research showed that the factor which reached the 'very good' significant level is quality of Thailand’s ginger with the score of 4.86. The other 5 factors are in the 'good' significant level. So the most important factor for Thai ginger farmer to concern is the quality of the product.

Keywords: critical success factor, export, ginger, supply chain

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Authors: Waheed Akhtar

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Bears in Asia facing multiple threats and challenges such as hunting, illegal trading, habitat loss, and human conflicts. According to IUCN Red List, the Asiatic black bear (Ursus thibetanus) is listed as Vulnerable since 1990, population declining by 49% during the last 30 years. The present study was conducted in Manglawar (DwaSaro Mountain) from April-August 2021, to collect all the information on Asiatic black bear observation, illegal hunting, and cub poaching. According to the response of the local community, very intensive illegal hunting and cub poaching were observed. Hunters usually installed many traps in the routes of black bears and when they move in the winter season the cubs get trapped and they collect them and kept in a specialized wooden box that is mainly helpful for further transportation. These cubs are then brought to the concerned Market where they sell them to many dealers. One of the potential observers of the illegal trading responds towards the Market price of the cubs, “The average price of the black bear cub is ranging from 45000-50000 Pakistani Rupees”. Apart from cubs' poaching, the black bear is also hunted for its skin, claws, and teeth.

Keywords: first report, illegal hunting, cub poaching, parts trading, Ursus thibetanus

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Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

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Authors: Modupeoluwa Solawon, Folusho Oluwole

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The resource curse hypothesis is a widely discussed topic that suggests despite expectations of boosting economic development and improving the well-being of citizens, natural resource wealth in a country can lead to negative outcomes. The study focused on crude oil price, crude oil production, the pump price of petrol, agricultural production, and natural resources rent in Nigeria to determine the possible curse of these resources. The study also looked into the well-being of the citizens by employing gross domestic product per capita. The data used for the study were drawn from the World Bank Data Indicators in 2022, limited to annual data from 1981 to 2022, using the autoregressive distributed lag (ARDL) as the main estimation technique. The findings of the study revealed that natural resource rent influenced the GDP per capita detrimentally, indicating that natural resource rent has not led to better welfare for Nigerians. This effect could likely be a result of corruption in the system, causing the inability of the rents to promote better welfare in Nigeria. In conclusion, the study recommends reducing the cost of living in Nigeria and making productive use of revenues generated from its natural resources.

Keywords: ARDL, corruption, natural resources, resource curse hypothesis

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: Lidia Sanchis-Marco, Antonio Rubia, Pedro Serrano

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This paper studies the informational content of pricing errors in the term structure of sovereign CDS spreads. The residuals from a non-arbitrage model are employed to construct a Price discrepancy estimate, or noise measure. The noise estimate is understood as an indicator of market distress and reflects frictions such as illiquidity. Empirically, the noise measure is computed for an extensive panel of CDS spreads. Our results reveal an important fraction of systematic risk is not priced in default swap contracts. When projecting the noise measure onto a set of financial variables, the panel-data estimates show that greater price discrepancies are systematically related to a higher level of offsetting transactions of CDS contracts. This evidence suggests that arbitrage capital flows exit the marketplace during time of distress, and this consistent with a market segmentation among investors and arbitrageurs where professional arbitrageurs are particularly ineffective at bringing prices to their fundamental values during turbulent periods. Our empirical findings are robust for the most common CDS pricing models employed in the industry.

Keywords: credit default swaps, noise measure, illiquidity, capital arbitrage

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Authors: Nathenal Thomas

Abstract:

In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Ezgi Avci-Surucu, Doganbey Akgul

Abstract:

Turkey’s energy reforms has achieved energy security through a variety of interlinked measures including electricity, gas, renewable energy and energy efficiency legislation; the establishment of an energy sector regulatory authority; energy price reform; the creation of a functional electricity market; restructuring of state-owned energy enterprises; and private sector participation through privatization and new investment. However, current strategies, namely; “Electricity Sector Reform and Privatization Strategy” and “Electricity Market and Supply Security Strategy” has been criticized for various aspects. The present paper analyzes the implementation of the aforementioned strategies in the framework of generation scheduling, transmission constraints, bidding structure and general aspects; and argues the deficiencies of current strategies which decelerates power investments and creates uncertainties. We conclude by policy suggestions to eliminate these deficiencies in terms of price and risk management, infrastructure, customer focused regulations and systematic market development.

Keywords: electricity markets, risk management, regulations, balancing and settlement, bilateral trading, generation scheduling, bidding structure

Procedia PDF Downloads 553

Authors: Bundit Pungnirund, Boonyada Pahasing

Abstract:

The objective of this research is to study factors related to behaviors of Thai travelers traveling to Koh Kret Island, Nonthaburi Province. The subjects of this study included 400 Thai travelers coming to Koh Kred. Questionnaires were used to collect data which were analyzed by computer program to find mean and correlation coefficient by Pearson. The results showed that Thai travelers reported their opinions and attitudes in high level on the marketing service mix, product, price, place, promotion, personal, physical evidence, and process. They reported on travelling motivation factor, tourist attraction, and facility at high level. Moreover, marketing service mix, product, price, place, promotion, personal, physical, and process including travelling motivation factor, tourist attraction, and facility had positive relationship with the frequency in travelling at statistically significant level (0.01), though in a low relationship but in the same direction.

Keywords: factors, behaviors, Thai travelers, Koh Kled, Nonthaburi Province

Procedia PDF Downloads 226

Authors: Miroslav Čulík, Petr Gurný

Abstract:

This paper is aimed at the financial assessment of the hard coal mining in a given region by real option methodology application. Hard coal mining in this mine makes net loss for the owner during the last years due to the long-term unfavourable mining conditions and significant drop in the coal prices during the last years. Management is going to shut down the operation and abandon the project to reduce the loss of the company. The goal is to assess whether the shutting down the operation is the only and correct solution of the problem. Due to the uncertainty in the future hard coal price evolution, the production might be again restarted if the price raises enough to cover the cost of the production. For the assessment, real option methodology is applied, which captures two important aspect of the financial decision-making: risk and flexibility. The paper is structured as follows: first, current state is described and problem is analysed. Next, methodology of real options is described. At last, project is evaluated by applying real option methodology. The results are commented and recommendations are provided.

Keywords: real option, investment, option to abandon, option to shut down and restart, risk, flexibility

Procedia PDF Downloads 549

Authors: Valeria Bondarenko

Abstract:

In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.

Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model

Procedia PDF Downloads 377

Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 446

Authors: M. F. Wu, F. T. Cheng

Abstract:

Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Keywords: activity-based benefit assessment approach, input mixed, output rate, wet blue

Procedia PDF Downloads 376