Search results for: Competitive Intelligence

Authors: Fay A. Al-Khalifa, Fariel Khan, Anamika Jiwane

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Responding to some governmentally enforced building sustainability criteria is today becoming an unavoidable challenge to the real estate development industry and is no longer an extra that allows developers to gain competitive advantages. Previous studies suggested that using green technologies, if done under the right circumstances, could lead to positive incentives, tax breaks, higher rents, cost savings and higher property values in the long run. This is all in addition to the marketing benefits of the green label. There are, however, still countries, mostly in the developing world, that lack the implementation of such sustainability guidelines and assessment tools. This research aspires to investigate the market’s readiness to implement such criteria, its perception of sustainable architecture and building users motivation to use and/or invest in sustainable buildings. The study showed via a survey administered to 385 inhabitants and investors in commercial real estate in Bahrain that the respondents have a limited understanding of the benefits of green buildings and are unlikely to want to occupy or invest in a green building under the current social, economic and industrial conditions. Reliability of green technology, effectiveness, price and the questionable long-term financial benefits were among the major concerns. The study suggests that the promotion of sustainable architecture should respond to the current market concerns in a more direct way to trigger an interest in investors and users of commercial real estate project. This stimulated attention should consequently encourage developers to consider incorporating sustainability measures, apply for green building assessment programs and invest in green technologies, all of which need higher capitals that are nonetheless financially justifiable on the long run.

Keywords: investment, real estate, sustainability, clients perception, Bahrain

Procedia PDF Downloads 157

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

Procedia PDF Downloads 409

Authors: Sepinoud Hamedi

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The ponder points to observationally look at the impact of carbon-neutrality approaches on the key assets required for Industry 4.0 driven savvy fabricating and how these assets can give a economical competitive advantage. The hypothetical system is coordinates with the regulation hypothesis and the resource-based see (RBV). The observational strategy is utilized for collecting information through studies and assist covariance-based auxiliary condition modeling is utilized to test the theories. Discoveries demonstrate that carbon–neutral-based government arrangements have a more grounded impact on unmistakable assets and human aptitudes than intangible assets related to Industry 4.0 driven shrewd fabricating. Moment, carbon–neutral arrangement arrangement with the firm’s maintainability destinations plays a directing impact on the relationship between carbon–neutral-based government arrangements and assets (substantial, intangible assets and human abilities) for Industry 4.0 driven shrewd fabricating. Finally, the three assets (substantial, intangible assets and human abilities) for Industry 4.0 driven savvy fabricating play a basic part in creating firms’ carbon–neutral capability and assist improving operational execution. Administrative suggestions incorporate venture in progressed advanced innovations, creating a solid mentality among workers and supply chain partners, and planning preparing programs for upgrading shrewd fabricating execution to create carbon-neutrality capability. This think about proposes a crossover hypothesis within the setting of carbon nonpartisanship by coordination institutional theory and RBV. Typically the primary think about that looks at the impact of carbon neutrality-based government arrangements on crucial Industry 4.0-driven savvy fabricating assets and the circuitous impact on carbon nonpartisanship capability and operational execution.

Keywords: carbon, industry 4.0, neutrality, RBV, nonpartisanship

Procedia PDF Downloads 75

Authors: Jayshree Patnaik, Bhaskar Bhowmick

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The economic growth of any nation is steered and dependent on innovation in technology. It can be preferably argued that technology has enhanced the quality of life. Technology is linked both with an economic and a social structure. But there are some parts of the world or communities which are yet to reap the benefits of technological innovation. Business and organizations are now well equipped with cutting-edge innovations that improve the firm performance and provide them with a competitive edge, but rarely does it have a positive impact on any community which is weak and marginalized. In recent times, it is observed that communities are actively handling social or ecological issues with the help of indigenous technologies. Thus, "Appropriate Technology" comes into the discussion, which is quite prevalent in the rural third world. Appropriate technology grew as a movement in the mid-1970s during the energy crisis, but it lost its stance in the following years when people started it to describe it as an inferior technology or dead technology. Basically, there is no such technology which is inferior or sophisticated for a particular region. The relevance of appropriate technology lies in penetrating technology into a larger and weaker section of community where the “Bottom of the pyramid” can pay for technology if they find the price is affordable. This is a theoretical paper which primarily revolves around how appropriate technology has faded and again evolved in both developed and developing countries. The paper will try to focus on the various concepts, history and challenges faced by the appropriate technology over the years. Appropriate technology follows a documented approach but lags in overall design and diffusion. Diffusion of technology into the poorer sections of community remains unanswered until the present time. Appropriate technology is multi-disciplinary in nature; therefore, this openness allows having a varied working model for different problems. Appropriate technology is a friendly technology that seeks to improve the lives of people in a constraint environment by providing an affordable and sustainable solution. Appropriate technology needs to be defined in the era of modern technological advancement for sustainability.

Keywords: appropriate technology, community, developing country, sustainability

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Authors: Jing-Ma

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Digital transformation (DT) is an important way for manufacturing enterprises to shape new competitive advantages, and how to choose an effective DT strategy is crucial for enterprise growth and sustainable development. Rooted in strategic change theory, this paper incorporates the dimensions of managers' digital cognition, organizational conditions, and external environment into the same strategic analysis framework and integrates the dynamic QCA method and PSM method to study the antecedent grouping of the DT strategy mode of manufacturing enterprises and its impact on corporate profitability based on the data of listed manufacturing companies in China from 2015 to 2019. We find that the synergistic linkage of different dimensional elements can form six equivalent paths of high-level DT, which can be summarized as the proactive change mode of resource-capability dominated as well as adaptive response mode such as industry-guided resource replenishment. Capacity building under complex environments, market-industry synergy-driven, forced adaptation under peer pressure, and the managers' digital cognition play a non-essential but crucial role in this process. Except for individual differences in the market industry collaborative driving mode, other modes are more stable in terms of individual and temporal changes. However, it is worth noting that not all paths that result in high levels of DT can contribute to enterprise profitability, but only high levels of DT that result from matching the optimization of internal conditions with the external environment, such as industry technology and macro policies, can have a significant positive impact on corporate profitability.

Keywords: digital transformation, strategy mode, enterprise profitability, dynamic QCA, PSM approach

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Authors: Pedro G. Rodrigues, Maria J. Bárrios, Sara A. Ambrósio

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The digitalisation of health is a profoundly transformative economic, political, and social process. As is often the case, such processes need to be carefully managed if misunderstandings, policy misalignments, or outright conflicts between the government and a wide gamut of stakeholders with competing interests are to be avoided. Thus, ensuring open lines of communication where all parties know what each other’s concerns are is key to good governance, as well as efficient and effective policymaking. This project aims to make a small but still significant contribution in this regard in that we seek to determine the extent to which health managers’ perceptions of what is a priority for digital health in Portugal are aligned with official policy perspectives. By applying state-of-the-art artificial intelligence technology first to the indexed literature on digital health and then to a set of official policy documents on the same topic, followed by a survey directed at health managers working in public and private hospitals in Portugal, we obtain two priority rankings that, when compared, will allow us to produce a synthesis and toolkit on digital health policy in Portugal, with a view to identifying areas of policy convergence and divergence. This project is also particularly peculiar in the sense that sophisticated digital methods related to text analytics are employed to study good governance aspects of digitalisation applied to health care.

Keywords: digital health, health informatics, text analytics, governance, natural language understanding

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Authors: Prakash Singh

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The focus of this exploratory study is on whether teachers demonstrate emphatic concern for their learners in planning, implementing and assessing learning outcomes in their regular classrooms. Empathy must be shown to all learners equally and not only for high-risk learners at the expense of other ability learners. Empathy demonstrated by teachers allows them to build a stronger bond with all their learners. This bond based on trust leads to positive outcomes for learners to be able to excel in their work. Empathic teachers must make every effort to simplify the subject matter for high risk learners so that these learners not only enjoy their learning activities but are also successful like their more able peers. A total of 87.5% of the participants agreed that empathy allows teachers to demonstrate humanistic values in their choice of learning materials for learners of different abilities. It is therefore important for teachers to select content and instructional materials that will contribute to the learners’ success in the mainstream of education. It is also imperative for teachers to demonstrate empathic skills and consequently, to be attuned to the emotions and emotional needs of their learners. Schools need to be reformed, not by simply lengthening the school day or by simply adding more content in the curriculum, but by making school more satisfying to learners. This must be consistent with their diverse learning needs and interests so that they gain a sense of power, fulfillment, and importance in their regular classrooms. Hence, teacher - pupil relationships based on empathic concern for the latter’s educational needs lays the foundation for quality education to be offered.

Keywords: emotional intelligence, empathy, learners’ emotional needs, teachers’ empathic skills

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Kalpeshkumar L. Gupta, Shivali Rathore

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India is home to over 30 crore rural poor, aware of the criticality of the situation that has made to come with an innovative business idea. Entrepreneurship in India is on the verge of explosive growth and which is actually need of an hour for employment generation, poverty elevation at grass root through developmental intervention. India economic progress has started from the development of its small and medium scale enterprises to ensure that the sectors continues to stay competitive and achieve sustained growth in the era of global economy many incubators centers has been established with the mission to give the encouragement to many innovative ideas. If we define an Incubator, it is simply an enclosed apparatus in which premature small babies are placed and which provides a controlled and protective environment for their care this gives them a chance to adjust to outside environment, and grow stronger before they face the outside world. In a similar way the startup entrepreneur’s business idea is incubated in the incubation centers. Entrepreneurship has been conventionally rated as risky career, to break the myth and to augment the supply of new entrepreneurs through education; research training the incubation centers has been established, their goal is to help create and grow young businesses by providing them with necessary support and financial and technical services. The startup companies spend on an average two years in a business incubator during which numerous benefits like funding, office space, equipment’s etc. is provided by the incubators to the startup business. Present paper will study the background, role, objectives of different incubators set up in Indian Institute of Management (IIMs) and Indian Institute of Technology (IITs) for our study.

Keywords: incubation centres, entrepreneurship, Indian Institute of Management, Indian Institute of Technology

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Authors: Daniel J. Glauber

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Knowledge transfer between personnel could benefit an organization’s improved competitive advantage in the marketplace from a strategic approach to knowledge management. The lack of information sharing between personnel could create knowledge transfer gaps while restricting the decision-making processes. Knowledge transfer between personnel can potentially improve information sharing based on an implemented knowledge management strategy. An organization’s capacity to gain more knowledge is aligned with the organization’s prior or existing captured knowledge. This case study attempted to understand the overall influence of a KMS within the corporate environment and knowledge exchange between personnel. The significance of this study was to help understand how organizations can improve the Return on Investment (ROI) of a knowledge management strategy within a knowledge-centric organization. A qualitative descriptive case study was the research design selected for this study. The lack of information sharing between personnel may create knowledge transfer gaps while restricting the decision-making processes. Developing a knowledge management strategy acceptable at all levels of the organization requires cooperation in support of a common organizational goal. Working with management and executive members to develop a protocol where knowledge transfer becomes a standard practice in multiple tiers of the organization. The knowledge transfer process could be measurable when focusing on specific elements of the organizational process, including personnel transition to help reduce time required understanding the job. The organization studied in this research acknowledged the need for improved knowledge management activities within the organization to help organize, retain, and distribute information throughout the workforce. Data produced from the study indicate three main themes including information management, organizational culture, and knowledge sharing within the workforce by the participants. These themes indicate a possible connection between an organizations KMS, the organizations culture, knowledge sharing, and knowledge transfer.

Keywords: knowledge transfer, management, knowledge management strategies, organizational learning, codification

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 190

Authors: Chiung-Hui Chen

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With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity

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Authors: Sresha Yadav, Ishwar Kumar

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Second language learning is an important area of research in the language and linguistic domains. Literature suggests that several factors impact second language learning, including age, motivation, objectives, teacher, instructional material, classroom interaction, intelligence and previous background, previous linguistic experience, other student characteristics. Previous researchers have also highlighted that classroom atmospherics has a significant impact on learning as well as on the performance of students. However, the impact of classroom atmospherics on second language learning is still not known in the existing literature. Therefore, the purpose of the present study is to explore whether classroom atmospherics has an impact on second language learning or not? And if it does, it would be worthwhile to explore the nature of such relationship. The present study aims to explore the impact of classroom atmospherics on second language learning by dwelling into the existing literature to explore factors which impact second language learning, classroom atmospherics which impact language learning and the metrics through which such learning impacts could be measured. Based on the findings of literature review, the researchers have adopted a clustering approach for categorization and positioning of various measures of second language learning. Based on the clustering approach, the researchers have approach for measuring the impact of classroom atmospherics on second language learning by drawing a student sample consisting of 80 respondents. The results of the study uncover various basic premises of second language learning, especially with regard to classroom atmospherics. The present study is important not only from the point of view of language learning but implications could be drawn with regard to the design of classroom atmospherics, environmental psychology, anthropometrics, etc as well.

Keywords: classroom atmospherics, cluster analysis, linguistics, second language learning

Procedia PDF Downloads 457

Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

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Authors: Aamir Hasan, Subhash Mishra

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The purpose of the study was to determine the key drivers which influence the shopping behavior of the customers in the retail store. In today‟s competitive world with increasing number of retail stores, the retailers need to be more customer oriented. Retail has changed and expanded in all lines of business, be it apparel,jewelry, footwear, groceries etc. The modern consumer is posing a challenging task for the Indian retailer. More aware, more confident and much more demanding, therefore the retailers are looking for ways to deliver better consumer value and to increase consumer purchase intention. Retailers tend to differentiate themselves by making their service easier to consumers. The study aims to study the key drivers that can influence shopping behavior in retail store. A survey (store intercept) method was employed to elicit primary information from 300 shoppers in different retail stores of Lucknow. The findings reveal the factors that play a greater role in influencing the shopping behavior of customers in retail store. As such, a survey of retail store customers‟ attitude towards reduced price, sales promotion, quality of the products, proximity to the home, customer service, store atmospherics were analyzed to identify the key drivers influencing shopping behavior in retail store. A questionnaire based on a five-item Likert scale, as well as random sampling, was employed for data collection. Data analysis was accomplished using SPSS software. The paper has found shopping experience, store image and value for money as three important variable out of which shopping experience emerged as a dominant factor which influences the consumer's shopping behavior in the retail store. Since the research has established empirical evidences in determining the key drivers which influences the shopping behavior of the customers in the retail store, it serves as a foundation for a deeper probe into the shopping behavior of the customers in the retail store research domain in the Indian context.

Keywords: retail, shopping, customers, questionnaire

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Authors: Leila Najeh Bel'Kiry

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Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels.

Keywords: artificial language model, attitudes, foreign language learning, ChatGPT, linguistic capabilities, Tunisian English language learners

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Authors: Yonosuke Murayama

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We have developed and studied a metastable beta Ti alloy, which shows super-elasticity and low Young’s modulus according to the phase stability of its beta phase. The super-elasticity and low Young’s modulus are required in a wide range of applications in various industrial fields. For example, the metallic implant with low Young’s modulus and non-toxicity is desirable because the large difference of Young’s modulus between the human bone and the implant material may cause a stress-shielding phenomenon. We have investigated the role of Sn and Al in metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys. The metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys form during quenching from the beta field at high temperature. While Cr and V act as beta stabilizers, Sn and Al are considered as elements to suppress the athermal omega phase produced during quenching. The athermal omega phase degrades the properties of super-elasticity and Young’s modulus. Although Al and Sn as single elements are considered as an alpha stabilizer and neutral, respectively, Sn and Al acted also as beta stabilizers when added simultaneously with beta stabilized element of Cr or V in this experiment. The quenched microstructure of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys shifts from martensitic structure to beta single-phase structure with increasing Cr or V. The Young’s modulus of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys decreased and then increased with increasing Cr or V, each showing its own minimum value of Young's modulus respectively. The composition of the alloy with the minimum Young’s modulus is a near border composition where the quenched microstructure shifts from martensite to beta. The border composition of Ti-Cr-Sn and Ti-V-Sn alloys required only less amount of each beta stabilizer, Cr or V, than Ti-Cr-Al and Ti-V-Al alloys. This indicates that the effect of Sn as a beta stabilizer is stronger than Al. Sn and Al influenced the competitive relation between stress-induced martensitic transformation and slip deformation. Thus, super-elastic properties of metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys varied depending on the alloyed element, Sn or Al.

Keywords: metastable beta Ti alloy, super-elasticity, low Young’s modulus, stress-induced martensitic transformation, beta stabilized element

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Authors: Gabriel Woldu, Maria Sassi

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Coffee performs a pivotal role in Ethiopia's GDP, revenue, employment, domestic demand, and export earnings. Ethiopia's coffee production and exports show high variability in the amount of production and export earnings. Despite being the continent's fifth-largest coffee producer, Ethiopia has not developed its ability to shine as a major exporter in the globe's green coffee exports. Ethiopian coffee exports were not stable and had high volume and earnings fluctuations. The main aim of this study was to analyze the dynamics of the export of coffee variation to different importing nations using a first-order Markov Chain model. 14 years of time-series data has been used to examine the direction and structural change in the export of coffee. A compound annual growth rate (CAGR) was used to determine the annual growth rate in the coffee export quantity, value, and per-unit price over the study period. The major export markets for Ethiopian coffee were Germany, Japan, and the USA, which were more stable, while countries such as France, Italy, Belgium, and Saudi Arabia were less stable and had low retention rates for Ethiopian coffee. The study, therefore, recommends that Ethiopia should again revitalize its market to France, Italy, Belgium, and Saudi Arabia, as these countries are the major coffee-consuming countries in the world to boost its export stake to the global coffee markets in the future. In order to further enhance export stability, the Ethiopian Government and other stakeholders in the coffee sector should have to work on reducing the volatility of coffee output and exports in order to improve production and quality efficiency, so that stabilize markets as well as to make the product attractive and price competitive in the importing countries.

Keywords: coffee, CAGR, Markov chain, direction of trade, Ethiopia

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Authors: Arijit Saha, Hassan Kassem, Leo Hoening

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Ongoing climate change demands the increasing use of renewable energies. Wind energy plays an important role in this context since it can be applied almost everywhere in the world. To reduce the costs of wind turbines and to make them more competitive, simulations are very important since experiments are often too costly if at all possible. The wind turbine on a vast open area experiences the turbulence generated due to the atmosphere, so it was of utmost interest from this research point of view to generate the turbulence through various Inlet Turbulence Generation methods like Precursor cyclic and Kaimal Spectrum Exponential Coherence (KSEC) in the computational simulation domain. To be able to validate computational fluid dynamic simulations of wind turbines with the experimental data, it is crucial to set up the conditions in the simulation as close to reality as possible. This present work, therefore, aims at investigating the turbulent inflow strategy and boundary conditions of KSEC and providing a comparative analysis alongside the Precursor cyclic method for Large Eddy Simulation within the context of wind energy applications. For the generation of the turbulent box through KSEC method, firstly, the constrained data were collected from an auxiliary channel flow, and later processing was performed with the open-source tool PyconTurb, whereas for the precursor cyclic, only the data from the auxiliary channel were sufficient. The functionality of these methods was studied through various statistical properties such as variance, turbulent intensity, etc with respect to different Bulk Reynolds numbers, and a conclusion was drawn on the feasibility of KSEC method. Furthermore, it was found necessary to verify the obtained data with DNS case setup for its applicability to use it as a real field CFD simulation.

Keywords: Inlet Turbulence Generation, CFD, precursor cyclic, KSEC, large Eddy simulation, PyconTurb

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Authors: Mahshid Asadollahi, Mohammad Akbari Asl

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The restaurant industry is highly competitive, and restaurants are constantly looking for ways to attract new customers and retain their existing ones. Nonverbal communication is an important factor in creating a positive customer experience and can play a significant role in attracting customers to restaurants. Nonverbal communication can include body language, facial expressions, tone of voice, and physical proximity, among other things. The present study aimed to investigate the impact of nonverbal communication between restaurant employees and customers on attracting customers in food courts in Tehran. The research method was descriptive-correlational, and the statistical population of this study included all customers of food court restaurants in Tehran, which was about 30 restaurants. The research sample was selected through probability sampling, and 440 customers completed emotional response, customer satisfaction, and nonverbal communication questionnaires in person. The data obtained were analyzed using multiple regression analysis. The results showed that vocal language, employee proximity, physical appearance, and speech movements, as components of nonverbal communication of restaurant employees, had an impact on attracting customers. Additionally, positive and negative emotions of customers have a significant relationship with customer attraction in Food Court restaurants. The study shows that various nonverbal communication factors can play a significant role in attracting customers, and that positive and negative customer emotions can affect customer satisfaction. Therefore, restaurant owners and managers should pay attention to nonverbal communication and train their employees accordingly to create a positive and welcoming atmosphere for customers.

Keywords: verbal language, proximity of employees, physical appearance, speech gestures, nonverbal communication, customer emotions, customer attraction

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Authors: Dimpy Shah

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The global economy has substantially changed in last three decades. Now almost all markets are transparent and visible for global customers. The corporates are now no more reliant on local markets for trade. The information technology revolution has changed business dynamics and marketing practices of corporate. The markets are divided into two different formats: traditional and virtual. In very short span of time, many e-commerce portals have captured global market. This strategy is well supported by global delivery system of multinational logistic companies. Now the markets are dealing with global supply chain networks, which are more demand driven and customer oriented. The corporate have realized importance of supply chain integration and marketing in this competitive environment. The Indian markets are also significantly affected with all these changes. In terms of population, India is in second place after China. In terms of demography, almost half of the population is of youth. It has been observed that the Indian youth are more inclined towards e-commerce and prefer to buy goods from web portal. Initially, this trend was observed in Indian service sector, textile and electronic goods and now further extended in other product categories. The FMCG companies have also recognized this change and started integration of their supply chain with e-commerce platform. This paper attempts to understand contemporary marketing practices of corporate in e-commerce business in Indian food and beverages segment and also tries to identify innovative marketing practices for proper execution of their strategies. The findings are mainly focused on supply chain re-integration and brand building strategies with proper utilization of social media.

Keywords: FMCG (Fast Moving Consumer Goods), ISCM (Integrated supply chain management), RFID (Radio Frequency Identification), traditional and virtual formats

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Sadia Bibi, Karim Ullah

Abstract:

Islamic banks have excess liquidity, which needs proper management to earn a high rate of return on them to remain competitive. However, they lack assets-backed avenues and rely on a few sukuks, which led them to liquidity management issues. Financial engineering comes forward to innovate and develop instruments for the requisite financial problem. Still, they face many challenges, explored in the context of liquidity management in Islamic banks. The rigorous literature review shows that Shariah compliance, competition from the conventional banks, lack of sufficient instruments, derivatives are still not accepted as legitimate products, the inter-bank market being less developed, and no possibility of lender of last resort is the six significant constraints to financial engineering for liquidity management of Islamic banks. To further explore the problem, a multiple case study strategy is used to extend and develop the theory with the philosophical stance of social constructivism. Narrative in-depth interviews over the telephone are conducted with key personnel at treasury departments of selected banks. Data is segregated and displayed using NVivo 11 software, and the thematic analysis approach identifies themes related to the constraints. The exploration of further constraints to financial engineering for liquidity management of Islamic banks achieves the research aim. The theory is further developed by the addition of three more constraints to the theoretical framework, which are i) lack of skilled human resources, ii) lack of unified vision, and iii) lack of government support to the Islamic banks. These study findings are fruitful for the use of the government, regulatory authorities of the banking sector, the State Bank of Pakistan (Central Bank), and the product design & development division of Islamic banks to make the financial engineering process feasible and resolve liquidity management issues of Islamic banks.

Keywords: financial engineering, liquidity management, Islamic banks, shariah compliance

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: K. Marciniak, M. Owoc

Abstract:

Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.

Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

Abstract:

In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: A. H. Nanher, N. P. Singh

Abstract:

In India, Agriculture is largely in rice- based cropping system. It has indicated decline in factor productivity along with emergence of multi - nutrient deficiency, buildup of soil pathogen and weed flora because it operates and removes nutrients from the same rooting depth. In designing alternative cropping systems, the common approaches are crop intensification, crop diversification and cultivar options. The intensification leads to the diversification of the cropping system. Intensification is achieved by introducing an additional component crop in a pre-dominant sequential system by desirable adjustments in cultivars of one or all the component crops. Invariably, this results in higher land use efficiency and productivity per unit time Crop Diversification through such crop and inclusion of fodder crops help to improve the economic situation of small and marginal farmers because of higher income. Inclusion of crops in sequential and intercropping systems reduces some obnoxious weeds through formation of canopies due to competitive planting pattern and thus provides an opportunity to utilize cropping systems as a tool of weed management with non-chemical means. Use of organic source not only acts as supplement for fertilizer (nitrogen) but also improve the physico-chemical properties of soils. Production and use of nitrogen rich biomass offer better prospect for supplementing chemical fertilizers on regular basis. Such biological diversity brings yield and economic stability because of its potential for compensation among components of the system. In a particular agro-climatic and resource condition, the identification of most suitable crop sequence is based on its productivity, stability, land use efficiency as well as production efficiency and its performance is chiefly judged in terms of productivity and net return.

Keywords: integrated farming systems, sustainable intensification, system of crop intensification, wheat

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

Abstract:

This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

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Authors: Arawati Agus, Rahmah Ismail

Abstract:

An effective training has been increasingly recognized as critical factors in enhancing the skills and knowledge of employee or personnel in the organization. More and more manufacturing companies in Malaysia are increasingly incorporating training as an important element in supply chain management (SCM) to improve their employee skills and knowledge and ultimately organizational performances. In order to understand the connection of training in SCM and the performance of an organization, this paper considers of many arguments from various research papers. This paper presents the findings of a research which examines the relationship between training in SCM, personnel differentiation and business performance of manufacturing companies in Malaysia. The study measures perception of senior management regarding the incorporation of training in SCM and the level of personnel differentiation and business performance measurements in their companies. The associations between training in SCM, personnel differentiation and business performance dimensions are analyzed through methods such as Pearson’s correlations and Smart partial least squares (smart PLS) using 126 respondents’ data. The correlation results demonstrate that training in SCM has significant correlations with personnel differentiation determinants (comprises of variables namely employee differentiation and service differentiation). The findings also suggest that training in SCM has significant correlations with business performance determinants (comprises of indicators, namely market share, profitability, ROA and ROS). Specifically, both personnel differentiation and business performance have high correlations with training in SCM, namely ‘Employee training on production skills’, ‘On the job production employee training’ and ‘Management training on supply chain effectiveness’ and ‘Employee training on supply chain technologies’. The smart PLS result also reveals that training in SCM exhibits significant impact on both personnel differentiation (directly) and business performance (indirectly mediated by personnel differentiation). The findings of the study provide a demonstration of the importance of training in SCM in enhancing competitive performances in Malaysian manufacturing companies.

Keywords: training in SCM, personnel differentiation, business performance, Pearson’s correlation, Smart PLS

Procedia PDF Downloads 324