Search results for: pricing decisions

Authors: Pablo Reyes, Vanessa Riveros Fiallo, Cesar Acevedo, Camila Castellanos, Catalina Moncaleano, Maria F. Parra, Laura Colmenares

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Social emotions are physiological, cognitive and behavioral phenomenon that intervene in the mechanisms of adaptation of individuals and their context. These are mediated by interpersonal relationship and language. Such emotions are subdivided into moral and comparison. The present research emphasizes two comparative emotions: Envy and Schadenfreude. Envy arises when a person lack of quality, possessions or achievements and these are superior in someone else. The Schadenfreude (SC) expresses the pleasure that someone experienced by the misfortune of the other. The relationship between both emotions has been questioned before. Hence there are reports showing that envy increases and modulates SC response. Other documents suggest that envy causes SC response. However, the methodological approach of the topic has been made through self-reports, as well as the hypothetical scenarios. Given this problematic, the neuroscience social framework provides an alternative and demonstrates that social emotions have neurophysiological correlates that can be measured. This is relevant when studying social emotions that are reprehensible like envy or SC are. When tested, the individuals tend to report low ratings due to social desirability. In this study, it was drawn up a proposal in research's protocol and the progress on its own piloting. The aim is to evaluate the effect of feeling envy and Schadenfreude has on the decision-making process, as well as the cooperative behavior in an economic game. To such a degree, it was proposed an experimental model that will provoke to feel envious by performing games against an unknown opponent. The game consists of asking general knowledge questions. The difficulty level in questions and the strangers' facial response have been manipulated in order to generate an ecological comparison framework and be able to arise both envy and SC emotions. During the game, an electromyography registry will be made for two facial muscles that have been associated with the expressiveness of envy and SC emotions. One of the innovations of the current proposal is the measurement of the effect that emotions have on a specific behavior. To that extent, it was evaluated the effect of each condition on the dictators' economic game. The main intention is to evaluate if a social emotion can modulate actions that have been associated with social norms, in the literacy. The result of the evaluation of a pilot model (without electromyography record and self-report) have shown an association between envy and SC, in a way that as the individuals report a greater sense of envy, the greater the chance to experience SC. The results of the economic game show a slight tendency towards profit maximization decisions. It is expected that at the time of using real cash this behavior will be strengthened and also to correlate with the responses of electromyography.

Keywords: envy, schadenfreude, electromyography, economic games

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Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle

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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.

Keywords: electric vehicles, fleets, path dependencies, transition pathways

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Ahmad Dahlan Salleh, Nik Abdul Rahim Nik Abdul Ghani, Muhamad Firdaus M. Hatta

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Risk management has implications on pricing, governance arrangements, business practices and strategy. Nowadays, home financing contract offers more in the risk transfer form to increase bank profit. This is parallel with Islamic jurisprudence method al-Kharaj bi al-thaman (gain accompanies liability for loss) and al-ghurm bil ghunm (gain is justified with risk) that determine the matching between risk transfer and returns. Malaysian financing trend is to buy house. Besides, exists transparency lacking risk transfer issues to the clients because of not been informed clearly. Terms and conditions of each financing also do not reflect clearly that the risk has been transferred to the client, justifying a determination price been made. The assumption on risk occurrence is also inaccurate as each risk is different with the type of financing contract. This makes the Islamic Financial Services Act 2013 in providing standards that transparent and consistent can be used by Islamic financial institution less effective. This study examines how far the level of the risk and obligation incurred by bank and client under various Islamic home financing contract. This research is qualitative by using two methods, document analysis, and semi-structured interviews. Document analysis from literature review to identify profile, themes and risk transfer element in home financing from Islamic jurisprudence perspective. This study finds that need to create a risk transfer parameter by banks which are consistent with risk transfer theory according to Islamic jurisprudence. This study has potential to assist the authority in Islamic finance such as The Central Bank of Malaysia (Bank Negara Malaysia) in regulating Islamic banking industry so that the risk transfer valuation in home financing contract based on home financing good practice and determined risk limits.

Keywords: risk transfer, home financing contract, Sharia compliant, Malaysia

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Olga Biedova, Victoria Steblovskaya, Kai Wallbaum

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In the current capital market environment, investors constantly face the challenge of finding a successful and stable investment mechanism. Highly volatile equity markets and extremely low bond returns bring about the demand for sophisticated yet reliable risk management strategies. Investors are looking for risk management solutions to efficiently protect their investments. This study compares a classic Constant Proportion Portfolio Insurance (CPPI) strategy to a Volatility Target portfolio insurance (VTPI). VTPI is an extension of the well-known Option Based Portfolio Insurance (OBPI) to the case where an embedded option is linked not to a pure risky asset such as e.g., S&P 500, but to a Volatility Target (VolTarget) portfolio. VolTarget strategy is a recently emerged rule-based dynamic asset allocation mechanism where the portfolio’s volatility is kept under control. As a result, a typical VTPI strategy allows higher participation rates in the market due to reduced embedded option prices. In addition, controlled volatility levels eliminate the volatility spread in option pricing, one of the frequently cited reasons for OBPI strategy fall behind CPPI. The strategies are compared within the framework of the stochastic dominance theory based on numerical simulations, rather than on the restrictive assumption of the Black-Scholes type dynamics of the underlying asset. An extended comparative quantitative analysis of performances of the above investment strategies in various market scenarios and within a range of input parameter values is presented.

Keywords: CPPI, portfolio insurance, stochastic dominance, volatility target

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Authors: Ritsuko Kawasaki, Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: M. Osipova

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Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.

Keywords: human resources management, salary expectations, statistics, turnover

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Authors: John Hardy

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A range of future-oriented intelligence techniques is commonly used by states to assess their national security and develop strategies to detect and manage threats, to develop and sustain capabilities, and to recover from attacks and disasters. Although homeland security organizations use future's intelligence tools to generate scenarios and simulations which inform their planning, there have been relatively few studies of the methods available or their applications for homeland security purposes. This study presents an assessment of one category of strategic intelligence techniques, termed Multi-Path Futures Analyses (MPFA), and how it can be applied to three distinct tasks for the purpose of analyzing homeland security issues. Within this study, MPFA are categorized as a suite of analytic techniques which can include effects-based operations principles, general morphological analysis, multi-path mapping, and multi-criteria decision analysis techniques. These techniques generate multiple pathways to potential futures and thereby generate insight into the relative influence of individual drivers of change, the desirability of particular combinations of pathways, and the kinds of capabilities which may be required to influence or mitigate certain outcomes. The study assessed eighteen uses of MPFA for homeland security purposes and found that there are five key applications of MPFA which add significant value to analysis. The first application is generating measures of success and associated progress indicators for strategic planning. The second application is identifying homeland security vulnerabilities and relationships between individual drivers of vulnerability which may amplify or dampen their effects. The third application is selecting appropriate resources and methods of action to influence individual drivers. The fourth application is prioritizing and optimizing path selection preferences and decisions. The fifth application is informing capability development and procurement decisions to build and sustain homeland security organizations. Each of these applications provides a unique perspective of a homeland security issue by comparing a range of potential future outcomes at a set number of intervals and by contrasting the relative resource requirements, opportunity costs, and effectiveness measures of alternative courses of action. These findings indicate that MPFA enhances analysts’ ability to generate tangible measures of success, identify vulnerabilities, select effective courses of action, prioritize future pathway preferences, and contribute to ongoing capability development in homeland security assessments.

Keywords: homeland security, intelligence, national security, operational design, strategic intelligence, strategic planning

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Authors: Seyedeh Sajedeh Salehi

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The Regulation No. 1215/2012/EC also known as the Brussels I Regulation (Recast) deals with jurisdictional disputes in civil and commercial matters. The main aim of the Recast (as in-line with its predecessor Regulation) is to bring a reform in procuring more simplified and faster circulation of civil and commercial judgments within the EU. Hence it is significant to take a closer look at the function of this regulatory tool. Therefore, the main objective of this paper is to analyze a clear understanding of the post-Recast situation on e-commerce relevant jurisdictional matters. The e-consumer protection and the choice-of-court agreements along with the position of the Court of Justice of the European Union in its decisions within the Recast Regulation will be also taken into consideration throughout this paper.

Keywords: choice-of-court agreements, consumer protection, e-commerce, jurisdiction, Recast Brussels I Regulation

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Mazyar Taghavi

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This research examines middle-level managers’ involvement in strategy process in 15 manufacturing and service companies in Iran. We considered two dominant theoretical arguments for expecting a positive association. According to the first direction involvement improves organizational performance by improving the quality of strategic decisions. According to the second track, middle managers contribute to increased levels of performance through strategic consensus among them. Results indicate that involvement in the strategy is related to organizational performance. Involvement is associated with consensus (i.e. strategic understanding and commitment) among middle-level managers. However, findings indicate that consensus is not related to the organizational performance.

Keywords: middle-level management, strategy process, organizational performance, strategy consensus

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Authors: Daniel Herrera Gonzalez, Maria Luisa Montas

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There are some factors affecting consumer decision-making regarding the use of the front of package labels in order to find benefits to the well-being of the human being. Currently, there are several labels that help influence or change the purchase decision for food products. These labels communicate the impact that food has on human health; therefore, consumers are more critical and intelligent when buying and consuming food products. The research explores the association between front-of-pack labeling and food choice; the association between label content and purchasing decisions is complex and influenced by different factors, including the packaging itself. The main objective of this study was to examine the perception of health labels and nutritional declarations and their influence on buying decisions in the non-alcoholic beverages sector. This comparative study of two developing countries will show how consumers take nutritional labels into account when deciding to buy certain foods. This research applied a quantitative methodology with correlational scope. This study has a correlational approach in order to analyze the degree of association between variables. Likewise, the confirmatory factor analysis (CFA) method and structural equation modeling (SEM) as a powerful multivariate technique was used as statistical technique to find the relationships between observable and unobservable variables. The main findings of this research were the obtaining of three large groups and their perception and effects on nutritional and wellness labels. The first group is characterized by taking an attitude of high interest on the issue of the imposition of the nutritional information label on products and would agree that all products should be packaged given its importance to preventing illnesses in the consumer. Likewise, they almost always care about the brand, the size, the list of ingredients, and nutritional information of the food, and also the effect of these on health. The second group stands out for presenting some interest in the importance of the label on products as a purchase decision, in addition to almost always taking into account the characteristics of size, money, components, etc. of the products to decide on their consumption and almost always They are never interested in the effect of these products on their health or nutrition, and in group 3, it differs from the others by being more neutral regarding the issue of nutritional information labels, and being less interested in the purchase decision and characteristics of the product and also on the influence of these on health and nutrition. This new knowledge is essential for different companies that manufacture and market food products because they will have information to adapt or anticipate the new laws of developing countries as well as the new needs of health-conscious consumers when they buy food products.

Keywords: healthy labels, consumer behavior, nutritional information, healthy products

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Authors: Roger-Claude Liwanga

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Over the last seven decades, there has been a proliferation of international tribunals. Yet, they have not received unanimous approval, raising a question about their legitimacy. A legitimate international tribunal is one whose authority to adjudicate international disputes is perceived as justified. Using the case study of the International Court of Justice (ICJ), this article highlights the three criteria that should be considered in assessing the legitimacy of an international tribunal, which include legal, sociological, and moral elements. It also contends that the ICJ cannot claim 'full' legitimacy if any of these components of legitimacy is missing in its decisions. The article further suggests that the legitimacy of the ICJ has a dynamic nature, as litigating parties may constantly change their perception of the court’s authority at any time before, during, or after the judicial process. The article equally describes other factors that can contribute to maintaining the international court’s legitimacy, including fairness and unbiasedness, sound interpretation of international legal norms, and transparency.

Keywords: international tribunals, legitimacy, human rights, international law

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Authors: Luay Jum'a

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Many challenges are facing third-party logistics (3PL) providers in the domestic and global markets which create a volatile decision making environment. All these challenges such as managing changes in consumer behaviour, demanding expectations from customers and time compressions have turned into complex problems for 3PL providers. Since the movement towards increased outsourcing outpaces movement towards insourcing, the need to achieve a competitive advantage over competitors in 3PL market increases. This trend continues to grow over the years and as a result, areas of strengths and improvements are highlighted through the analysis of the LSQ factors that lead to B2B customers’ satisfaction which become a priority for 3PL companies. Consequently, 3PL companies are increasingly focusing on the most important issues from the perspective of their customers and relying more on this value of information in making their managerial decisions. Therefore, this study is concerned with providing guidance for improving logistics service quality (LSQ) levels in the context of 3PL industry in Jordan. The study focused on the most important factors in LSQ and used a managerial tool that guides 3PL companies in making LSQ improvements based on a quadrant analysis of two main dimensions: LSQ declared importance and LSQ inferred importance. Although, a considerable amount of research has been conducted to investigate the relationship between logistics service quality (LSQ) and customer satisfaction, there remains a lack of developing managerial tools to aid in the process of LSQ improvement decision-making. Moreover, the main advantage for the companies to use 3PL service providers as a trend is due to the realised percentage of cost reduction on the total cost of logistics operations and the incremental improvement in customer service. In this regard, having a managerial tool that help 3PL service providers in managing the LSQ factors portfolio effectively and efficiently would be a great investment for service providers. One way of suggesting LSQ improvement actions for 3PL service providers is via the adoption of analysis tools that perform attribute categorisation such as Importance–Performance matrix. In mind of the above, it can be stated that the use of quadrant analysis will provide a valuable opportunity for 3PL service providers to identify improvement opportunities as customer service attributes or factors importance are identified in two different techniques that complete each other. Moreover, the data were collected through conducting a survey and 293 questionnaires were returned from business-to-business (B2B) customers of 3PL companies in Jordan. The results showed that the LSQ factors vary in their importance and 3PL companies should focus on some LSQ factors more than other factors. Moreover, ordering procedures, timeliness/responsiveness LSQ factors considered being crucial in 3PL businesses and therefore they need to have more focus and development by 3PL service providers in the Jordanian market.

Keywords: logistics service quality, managerial decisions, quadrant analysis, third party logistics service provider

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Authors: Z. Ulukan, E. Demircioğlu,

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Facility location is a complex real-world problem which needs a strategic management decision. This paper provides a general review on studies, efforts and developments in Facility Location Problems which are classical optimization problems having a wide-spread applications in various areas such as transportation, distribution, production, supply chain decisions and telecommunication. Our goal is not to review all variants of different studies in FLPs or to describe very detailed computational techniques and solution approaches, but rather to provide a broad overview of major location problems that have been studied, indicating how they are formulated and what are proposed by researchers to tackle the problem. A brief, elucidative table based on a grouping according to “General Problem Type” and “Methods Proposed” used in the studies is also presented at the end of the work.

Keywords: discrete location problems, exact methods, heuristic algorithms, single source capacitated facility location problems

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Authors: Min Wang, Sergey Utev

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The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid.

Keywords: combinatorial construction, graphical representation, matroid, path calculation, share price, Tutte polynomial

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Authors: Amr Sultan, Sara Elgazzar, Breksal Elmiligy

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The airline industry nowadays is becoming a more growing industry facing a severe competition. It is an influential issue in this context to utilize revenue management (RM) concept and practice in order to develop the pricing strategy. There is an unfathomable necessity for RM to assist the airlines and their associates to disparage the cost and recuperate their revenue, which in turn will boost the airline industry performance. The complexity of RM imposes enormous challenges on the airline industry. Several studies have been proposed on the RM adaptation in airlines industry while there is a limited availability of implementing RM and its complexity in the developing countries such as Egypt. This research represents a research schema about the implementation of the RM to the Egyptian airline industry. The research aims at investigating and demonstrating the complexities face implementing RM in the airline industry, up on which the research provides a comprehensive understanding of how to overcome these complexities while adapting RM in the Egyptian airline industry. An empirical study was conducted on the Egyptian airline sector based on a sample of four airlines (Egyptair, Britishair, KLM, and Lufthansa). The empirical study was conducted using a mix of qualitative and quantitative approaches. First, in-depth interviews were carried out to analyze the Egyptian airline sector status and the main challenges faced by the airlines. Then, a structured survey on the three different parties of airline industry; airlines, airfreight forwarders, and passengers were conducted in order to investigate the main complexity factors from different parties' points of view. Finally, a focus group was conducted to develop a best practice framework to overcome the complexities faced the RM adaptation in the Egyptian airline industry. The research provides an original contribution to knowledge by creating a framework to overcome the complexities and challenges in adapting RM in the airline industry generally and the Egyptian airline industry particularly. The framework can be used as a RM tool to increase the effectiveness and efficiency of the Egyptian airline industry performance.

Keywords: revenue management, airline industry, revenue management complexity, Egyptian airline industry

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Authors: Lavinia B. Dulla

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The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data.

Keywords: fuzzy regression approach, minimum fuzziness criterion, interval regression, prediction interval

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

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Authors: Aynur Kazaz, Yusif Inusah

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In the bid to improve transparency and efficiency as well as to reduce the cost of the public procurement process, Ghana started implementing an electronic Government Procurement System, known as the Ghana Electronic Procurement System (GHANEPS) in November 2019. The implementation of e-tendering technology is new to the stakeholders. Therefore, this research is aimed to identify the critical barriers to e-tendering implementation in the Ghanaian construction industry. Examples of barriers to e-tendering implementation were first identified through a literature review, and questionnaires and interview questions were prepared to gather the data. This study contributes to the in-depth understanding of global e-tendering barriers in the Ghanaian construction industry. The findings could help researchers, practitioners, and governments make strategic investment decisions and overcome e-tendering challenges.

Keywords: barriers, challenges, construction industry, e-procurement, e-tendering

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Authors: Druzhinenko-Silhan Daria, Metz Claire

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In this paper, we introduce the findings of the "Conjugal violence: mothers' parenting and court decisions" (VIC-PADEJ) study, focusing on the motherhood experiences of domestic violence victims. Utilizing a longitudinal research protocol that encompassed clinical interviews, projective methods, and various questionnaires, we detail the outcomes derived from seven clinical interviews with mothers alongside a comprehensive analysis. The findings reveal a pronounced decline in security and an imperative need for structuring both social and internal realities. The convergence of these findings indicates that parenting, post-experiencing domestic violence, may become an unattainable task due to the deficiency of internal resources.

Keywords: domestic violence, parenthood, mothers victims, projective methods, longitudinal research, alceste analysis

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Authors: Carlos Escobar-del Pozo, César Ahumada-Monroy, Azael García-Rebolledo, Alberto Brambila-Solórzano, Gregorio Martínez-Sánchez, Luis Ortiz-Rincón

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Numerical simulations of flow in complex biological structures have gained considerable attention in the last years. However, the major issue is the validation of the results. The present work shows a Particle Image Velocimetry PIV flow visualization technique in complex biological structures, particularly in intracranial aneurysms. A methodology to reconstruct and generate a transparent model has been developed, as well as visualization and particle tracking techniques. The generated transparent models allow visualizing the flow patterns with a regular camera using the visualization techniques. The final goal is to use visualization as a tool to provide more information on the treatment and surgery decisions in aneurysms.

Keywords: aneurysms, PIV, flow visualization, particle tracking

Procedia PDF Downloads 85

Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

Abstract:

Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

Procedia PDF Downloads 170

Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

Abstract:

Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

Procedia PDF Downloads 365

Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

Procedia PDF Downloads 443

Authors: Andrew Kirabira

Abstract:

This study is an investigation into the effectiveness of climate-smart agriculture (CSA) technologies in improving productivity through managing biotic and abiotic stresses in the coffee agroecological zones of Uganda. The motive is to enhance farmer livelihoods. The study was initiated as a result of the decreasing productivity of the crop in Uganda caused by the increasing prevalence of pests, diseases and abiotic stresses. Despite 9 years of farmers’ application of CSA, productivity has stagnated between 700kg -800kg/ha/yr which is only 26% of the 3-5tn/ha/yr that CSA is capable of delivering if properly applied. This has negatively affected the incomes of the 10.6 million people along the crop value chain which has in essence affected the country’s national income. In 2019/20 FY for example, Uganda suffered a deficit of $40m out of singularly the increasing incidence of one pest; BCTB. The amalgamation of such trends cripples the realization of SDG #1 and #13 which are the eradication of poverty and mitigation of climate change, respectively. In probing CSA’s effectiveness in curbing such a trend, this study is guided by the objectives of; determining the existing farmers’ knowledge and perceptions of CSA amongst the coffee farmers in the diverse coffee agro-ecological zones of Uganda; examining the relationship between the use of CSA and prevalence of selected coffee pests, diseases and abiotic stresses; ascertaining the difference in the market organization and pricing between conventionally and CSA produced coffee; and analyzing the prevailing policy environment concerning the use of CSA in coffee production. The data collection research design is descriptive in nature; collecting data from farmers and agricultural extension workers in the districts of Ntungamo, Iganga and Luweero; each of these districts representing a distinct coffee agroecological zone. Policy custodian officers at district, cooperatives and at the crop’s overseeing national authority were also interviewed.

Keywords: climate change, food security, field stresses, Productivity

Procedia PDF Downloads 53

Authors: Vahid Bairami Rad

Abstract:

The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

Procedia PDF Downloads 51

Authors: M. El Mousadik, F. Elkandoussi

Abstract:

The concern for increased rigor in social management has led more and more Moroccan business leaders to question the value of applying social audit as an essential tool in the management of human resources. Hotel companies are not excluded; in fact, they are expected to implement such an audit to develop sound and credible human resources management (HRM) policies. The main objective of this paper is to establish the relationship between the practice of social audit as a tool, and its impact on the tourism sector, especially on hotels at one of the Morocco’s first and most popular city for tourism, Agadir. This exploratory study of properties in Agadir has revealed that hotel executives are aware of the importance of social auditing to hone their decisions in the field of HRM.

Keywords: social audit, hotel companies, human resources management, social piloting

Procedia PDF Downloads 275