Search results for: business data processing

Authors: Veepaul Kaur Mann Balwinder Singh

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The COVID-19 had an intense impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole selling process because of the relevant issues that emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital expertise that may ensure connections and, thus, help business activities run smoothly. This could be true, especially with the occurrence of strong limitations on physical interactions during the COVID-19 pandemic. The catastrophe changes life publically and economically. People are living alone for following the social distancing norms. In that set-up, Digital Marketing is playing an important role in civilization. Anyone can buy any item, pay bills, transfer money and compare items through Digital Marketing without physical interactions. After COVID-19, people will be more aware of health safety and trust. So, through Digital Marketing, organizations can approach customers and provide good service environments. In such a situation, the online network becomes the most important encouraging for online customers to get in contact with the firm and carry out online selling and purchasing activities around the world.

Keywords: COVID-19, business, digital marketing, online customer

Procedia PDF Downloads 53

Authors: Thuan Nguyen

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In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

Procedia PDF Downloads 245

Authors: K. Marciniak, M. Owoc

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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

Procedia PDF Downloads 512

Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

Procedia PDF Downloads 191

Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

Procedia PDF Downloads 374

Authors: Samuel Faboyede, Obiamaka Nwobu, Samuel Fakile, Dickson Mukoro

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In the present dynamic business environment of corporate governance and regulations, financial reporting is an inevitable and extremely significant process for every business enterprise. Several financial elements such as Annual Reports, Quarterly Reports, ad-hoc filing, and other statutory/regulatory reports provide vital information to the investors and regulators, and establish trust and rapport between the internal and external stakeholders of an organization. Investors today are very demanding, and emphasize greatly on authenticity, accuracy, and reliability of financial data. For many companies, the Internet plays a key role in communicating business information, internally to management and externally to stakeholders. Despite high prominence being attached to external reporting, it is disconnected in most companies, who generate their external financial documents manually, resulting in high degree of errors and prolonged cycle times. Chief Executive Officers and Chief Financial Officers are increasingly susceptible to endorsing error-laden reports, late filing of reports, and non-compliance with regulatory acts. There is a lack of common platform to manage the sensitive information – internally and externally – in financial reports. The Internet financial reporting language known as eXtensible Business Reporting Language (XBRL) continues to develop in the face of challenges and has now reached the point where much of its promised benefits are available. This paper looks at the emergence of this revolutionary twenty-first century language of digital reporting. It posits that today, the world is on the brink of an Internet revolution that will redefine the ‘business reporting’ paradigm. The new Internet technology, eXtensible Business Reporting Language (XBRL), is already being deployed and used across the world. It finds that XBRL is an eXtensible Markup Language (XML) based information format that places self-describing tags around discrete pieces of business information. Once tags are assigned, it is possible to extract only desired information, rather than having to download or print an entire document. XBRL is platform-independent and it will work on any current or recent-year operating system, or any computer and interface with virtually any software. The paper concludes that corporate stakeholders and the government cannot afford to ignore the XBRL. It therefore recommends that all must act locally and think globally now via the adoption of XBRL that is changing the face of worldwide business reporting.

Keywords: XBRL, financial reporting, internet, internal and external reports

Procedia PDF Downloads 286

Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

Procedia PDF Downloads 94

Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

Procedia PDF Downloads 451

Authors: Y. Boulaksil, J. C. Fransoo, E.E. Blanco, S. Koubida

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In this paper, we study the small traditional retailers that are located in the neighborhoods of big cities in emerging markets. Although modern retailing has grown in the last two decades in these markets, the number of small retailers is still increasing and serving a substantial part of the daily demand for many basic products, such as bread, milk, and cooking oil. We conduct an empirical study to understand the business environment of these small traditional retailers in emerging markets by collecting data from 333 small retailers, spread over 8 large cities in Morocco. We analyze the data and describe their business environment with a focus on the informal credits they offer to their customers. We find that smaller small retailers that are funded from personal savings and managed by the owner himself offer relatively the most credits. Our study also provides interesting insights about these small retailers that will help FMCG manufacturers that are (planning to be) active in Morocco and other emerging markets. We also discuss a number opportunities to improve the efficiency of the supply chains that serve them.

Keywords: small retailers, big cities, emerging markets, empirical study, supply chain management, Morocco

Procedia PDF Downloads 580

Authors: Sucihatiningsih Dian Wisika Prajanti, Himawan Arif Susanto

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Fruits are perishable products and have relatively low price, especially at harvest time. Generally, farmers only sell the products shortly after the harvest time without any processing. Farmers also only play role as price takers leading them to have less power to set the price. Sometimes, farmers are manipulated by middlemen, especially during abundant harvest. Therefore, it requires an effort to cultivate fruits and create innovation to make them more durable and have higher economic value. The purpose of this research is how to increase the added- value of fruits that have high economic value. The research involved 60 farmers of Salak fruit as the sample. Then, descriptive analysis was used to analyze the data in this study. The results showed the selling price of Salak fruit is very low. Hence, to increase the added-value of the fruits, fruit processing is carried out by freezing - frying which can cause the fruits last longer. In addition to increase these added-value, the products can be accommodated for further processed without worrying about their crops rotted or unsold.

Keywords: fruits processing, Salak fruit, freezing frying, farmer’s welfare, Sleman, Yogyakarta

Procedia PDF Downloads 347

Authors: Ahmed Shaik

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Estimates are very critical in accounting and Financial Reporting cannot be complete without these estimates. There is a long list of accounting estimates that are required to be made to compute Net Income and to determine the value of assets and liabilities. To name a few, valuation of inventory, depreciation, valuation of goodwill, provision for bad debts and estimated warranties, etc. require the use of different valuation models and forecasts. Different business entities under the same industry may use different approaches to measure the value of financial items being reported in Income Statement and Balance Sheet. The disclosure notes do not provide enough details of the approach used by a business entity to arrive at the value of a financial item. Lack of details in the disclosure notes makes it difficult to compare the financial performance of one business entity with the other in the same industry. This paper is an attempt to identify the lack of enough information about accounting estimates in disclosure notes, the impact of the absence of details of accounting estimates on the comparability of financial data and financial analysis. An attempt is made to suggest the detailed disclosure while taking care of the cost and benefit of making such disclosure.

Keywords: accounting estimates, disclosure notes, financial reporting, transparency

Procedia PDF Downloads 200

Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

Procedia PDF Downloads 200

Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

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The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

Procedia PDF Downloads 113

Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

Procedia PDF Downloads 338

Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

Procedia PDF Downloads 445

Authors: Elena Antonova Unlu, Cigdem Sagin Simsek

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The research presents two studies examining the impact of formal interpreting training (FIT) on Working Memory Capacity (WMC) of student-interpreters. In Study 1, the storage and processing capacities of the working memory (WM) of last-year student-interpreters were compared with those of last-year Foreign Language Education (FLE) students. In Study 2, the impact of FIT on the WMC of student-interpreters was examined via comparing their results on WM tasks at the beginning and the end of their FIT. In both studies, Digit Span Task (DST) and Reading Span Task (RST) were utilized for testing storage and processing capacities of WM. The results of Study 1 revealed that the last-year student-interpreters outperformed the control groups on the RST but not on the DST. The findings of Study 2 were consistent with Study 1 showing that after FIT, the student-interpreters performed better on the RST but not on the DST. Our findings can be considered as evidence supporting the view that FIT has a beneficial effect not only on the interpreting skills of student-interpreters but also on the central executive and processing capacity of their WM.

Keywords: working memory capacity, formal interpreting training, student-interpreters, cross-sectional and longitudinal data

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Authors: Titilayo Shodeinde, Bukola Dawodu

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Aquaculture practice in Nigeria is an industry that includes fish development in a controlled situation. It has developed through various stages and stages with its latent capacity yet to be completely tapped. To avow this potential in adding to human advancement, nourishment security and improved way of life, the aquaculture business requires new approaches. Subsequently, this seminar paper reviews the impact of aquaculture on sustainable development in Nigeria. The examination received on subjective research strategy. The segments and the frameworks of business fish cultivating were completely talked about. Additionally, imperatives to business fish cultivating in the area were explained. The systems for advancing business aquaculture, for example, increment in consciousness of aquaculture items, financing of aquaculture data sources, preparing and labor improvement, government support, arrangement of fish ranchers agreeable social orders, access to advances and credit offices, advancement of research exercises, viable fisheries approaches, great institutional structure, and decreasing the degrees of defilement and instability in the district, were plainly brought up as a veritable devices, for changing the current situation with aquaculture in Niger Delta, through arranged, engaged and composed compelling administration procedures, by singular ranchers, government organizations and applicable foundations for economical advancement of the locale specifically and the nation by and large.

Keywords: aquaculture, sustainability, Nigeria, research

Procedia PDF Downloads 219

Authors: Nilay Balkan

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Introductory statement: The purpose of this study is to understand how small business owners develop social media marketing competency, the challenges they encounter in doing so, and establish the social media training needs of such businesses. These challenges impact the extent to which small business owners build effective social media knowledge and, in turn, impact their ability to implement effective social media marketing into their business practices. This means small businesses are not fully able to benefit from social media, such as benefits to customer relationship management or increasing brand image, which would support the overall business operations for these businesses. This research is part one of a two-phased study. The first phase aims to establish the challenges small business owners face in building social media marketing competency and their specific training needs. Phase two will then focus in more depth on the barriers and challenges emerging from phase one. Summary of Methodology: Interviews with ten small business owners were conducted from various sectors, including fitness, tourism, food, and drinks. These businesses were located in the central belt of Scotland, which is an area with the highest population and business density in Scotland. These interviews were in-depth and semi-structured, with the purpose of being investigative and understanding the phenomena from the lived experience of the small business owners. A purposive sampling was used, where small business owners fulfilling certain criteria were approached to take part in the interviews. Key findings: The study found four ways in which small business owners develop their social media competency (informal methods, formal methods, learning through a network, and experimenting) and the various challenges they face with these methods. Further, the study established four barriers impacting the development of social media marketing competency among the interviewed small business owners. In doing so, preliminary support needs have also emerged. Concluding statement: The contribution of this study is to understand the challenges small business owners face when learning how to use social media for business purposes and identifying their training needs. This understanding can help the development of specific and tailored support. In addition, specific and tailored training can support small businesses in building competency. This supports small businesses to progress to the next stage of their development, which could be to further their digital transformation or grow their business. The insights from this study can be used to support business competitiveness and support small businesses to become more resilient. Moreover, small businesses and entrepreneurs share some similar characteristics, such as limited resources and conflicting priorities, and the findings of this study may be able to support entrepreneurs in their social media marketing strategies as well.

Keywords: small business, marketing theory and applications, social media marketing, strategic management, digital competency, digitalisation, marketing research and strategy, entrepreneurship

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Ana L. Martins, Rita S. Saraiva, João C. Ferreira

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Much effort has been placed on the assessment of perceived service quality. Several models can be found in literature, but these are mainly focused on business-to-consumer (B2C) relationships. Literature on how to assess perceived quality in business-to-business (B2B) contexts is scarce both conceptually and in terms of its application. This research aims at filling this gap in literature by applying INDSERV to a case study situation. Under this scope, this research aims at analyzing the adequacy of the proposed assessment tool to other context besides the one where it was developed and by doing so analyzing the perceive quality of the advertisement service provided by a specific television network to its B2B customers. The INDSERV scale was adopted and applied to a sample of 33 clients, via questionnaires adapted to interviews. Data was collected in person or phone. Both quantitative and qualitative data collection was performed. Qualitative data analysis followed content analysis protocol. Quantitative analysis used hypotheses testing. Findings allowed to conclude that the perceived quality of the television service provided by television network is very positive, being the Soft Process Quality the parameter that reveals the highest perceived quality of the service as opposed to Potential Quality. To this end, some comments and suggestions were made by the clients regarding each one of these service quality parameters. Based on the hypotheses testing, it was noticed that only advertisement clients that maintain a connection to the television network from 5 to 10 years do show a significant different perception of the TV advertisement service provided by the company in what the Hard Process Quality parameter is concerned. Through the collected data content analysis, it was possible to obtain the percentage of clients which share the same opinions and suggestions for improvement. Finally, based on one of the four service quality parameter in a B2B context, managerial suggestions were developed aiming at improving the television network advertisement perceived quality service.

Keywords: B2B, case study, INDSERV, perceived service quality

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Michelle Marquard

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The evidence for collaboration technologies (CTs) as a source of business productivity has never been stronger, and grows each day. At the same time, paradoxically, there is an increasingly greater concern about the challenge CTs present to the unity and well-being of the virtual workforce than ever before, but nowhere in the literature has an empirical understanding of these linkages been set out. This study attempted to address by using virtual distance as a measure of the efficacy of CTs to reduce the psychological distance among people. Data from 350 managers and 101 individual contributors across twelve functions in six major industries showed that business value is related to collaboration (r=.84, p < .01), which, in turn, is associated with full spectrum participation (r=.60, p < .01), a summative function of inclusion, integration, and we-intention. Further, virtual distance is negatively related to both collaboration (r=-.54, p < .01) and full spectrum participation (r=-.26, p < .01). Additionally, CIO-CDO relationship is a factor in the degree to which virtual distance is managed in the organization (r=-.26, p < .01). Overall, the results support the positive relationship between business value and collaboration. They also suggest that the extent to which collaboration can be fostered may depend on the degree of full spectrum participation or the level of inclusion, integration, and we-intention among members. Finally, the results indicate that CTs, when managed wisely to lower virtual distance, are a compelling concomitant to collaboration and full spectrum participation. A strategic outcome of this study is an instrumental blueprint of CTs and virtual distance in relation to full spectrum participation that should serve as a shared dashboard for CIOs, CHROs, and CDOs.

Keywords: business value, collaboration, inclusion, integration, we-intention, full spectrum participation, collaboration technologies, virtual distance

Procedia PDF Downloads 346

Authors: Nellija Titova

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Latvia, Lithuania, and Estonia, as Baltic Countries, have gone throughout transformational changes since 90s leading to the high level of economic development. As countries departing Soviet Union with industrialization policy moved to service economies, the issues of intangibles, human capital, structural capital, and innovation capital have gained impetus. Following the growing demand of practitioners and later academia, intellectual capital as a discipline, which appeared in 90s, became fundamental nowadays. Aim of the paper is to analyze the Baltic companies entering stock markets at Nasdaq Baltic from the perspective of Intellectual Capital. Methodology of the research is based on a longitudinal analysis of the companies using composite ratios of Intellectual Capital and Business performance in the period 2012-2019. Data for 2020 as COVID year) were excluded from the analysis. Findings allow concluding there is a pattern of influence and companies clearly experience the systemic impact of IC on business performance, identifying also time effect investing in intangibles.

Keywords: intellectual capital, impact analysis, longitudinal effect, composite ratios

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Authors: Wildan Maulana, Machfudz Sa'idi

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Yogyakarta is a city with the most students in Indonesia, more than 250 thousand students living in Yogyakarta and more than 140 universities in Yogyakarta. Therefore, Yogyakarta is a very strategic place for the culinary business. Food is a basic requirement of all living things, and the tasty food and cheap is the target of almost all students. The objective of this paper is to give an idea and the innovation of culinary business in Yogyakarta who apply the concept sociopreneur and technology as a tool to facilitate the course of this business. KedaiKampus is a startup that brings the food business operators such as food stalls, restaurants or angkringan (a traditional restaurant of Indonesia) and people who want to find the food with the best price and the best taste. The uniqueness of this business is offered weekly and monthly food packages for students in particular or for everyone who needs and will be delivered to their homes each every hour meal. KedaiKampus is also a marketspace for industrial and culinary houses, using technology based mobile application and website will allow the food industry to connect them with customers, but it also allows them to know the customer's desire for food trending in the market. The application to be developed is designed for ease of access to customers in finding their favorite foods and convenience for the culinary home to create amazing culinary innovation.

Keywords: marketplace, sociopreneur, culinary, meal

Procedia PDF Downloads 292

Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Janpen Srijan, Nahathai Tanmang, Thanit Purathanang, Anun Dowchern, Saksit Summart, Seangduan Kampimpa

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This paper presents the resistance reader program based on image processing by using MATLAB. The proposed program is divided into six parts; the first part is the web camera; the second part is a watt selection before shooting the resistor; the third part is a part of finding the position of the color on the mid-point of resistor; the fourth part is a part of identifying color code of the resistor; the fifth part is a part of taking the number of values for each color for resistance calculation and the last part is a part of displaying result of resistance value. The experimental result of the resistance reader program based on image processing was able to display the resistance value of resistor. The accuracy of proposed program is 85 percent for 1 watt resistor. It has 15 percent of reading error because a problem with the color code of some resistor was too bright.

Keywords: resistance reader program, image processing, resistor, MATLAB

Procedia PDF Downloads 388

Authors: Jamila Mohammed Makarfi, Yontem Sonmez

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Developing countries like Nigeria have recently been affected by conflicts characterized by violence, high levels of risk and insecurity, resulting in loss of lives, livelihoods, displacement of communities, degradation of health, educational and social infrastructure as well as economic underdevelopment. The Nigerian government’s response to most of these conflicts has mainly been reactionary in the form of military deployments, as against precautionary to prevent or address the root causes of the conflicts. Several studies have shown that at various points of a conflict, conflict regions can benefit from the resources and expertise available outside the government, mainly from the private sector through mechanisms such as corporate social responsibility (CSR) by businesses. The main aim of this study is to examine the role of businesses in peacebuilding in Northern Nigeria through CSR in the last decade. The expected contributions from this will answer research questions, such as the key business motivations to engage in peacebuilding, as well as the degree of influence exerted from various stakeholder groups on the business decision to engage. The methodology of the study adopts a multiple case study of over 120 businesses of various sizes, ranging from small, medium and large-scale. A mixed method enabled the collection of quantitative and qualitative primary data to augment the secondary data. The results indicated that the most important business motivations to engage in peacebuilding were the negative effects of the conflict on economic stability, as well as stakeholder-driven motives. On the other hand, out of the 12 identified stakeholders, micro-, small- and medium-scale enterprises (MSMEs) considered the chief executive officer’s interest to be the most important factor, while large companies rated the government and community pressure as the highest. Overall, the foreign stakeholders scored low on the influence chart for all business types.

Keywords: conflict, corporate social responsibility, peacebuilding, stakeholder

Procedia PDF Downloads 221

Authors: Gulnara Galeeva

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The Analytic Hierarchy Process is widely used in the economic and financial studies, including the formation of investment portfolios. In this study, a generalized method of obtaining a vector of priorities for the case with separate pairwise comparisons of the expert opinion being presented as a set of several equal evaluations on a ratio scale is examined. The author claims that this method allows solving an important and up-to-date problem of excluding vagueness and ambiguity of the expert opinion in the decision making theory. The study describes the authentic wide pairwise comparison matrix. Its application in the formation of the efficient investment portfolio of intangible assets of a small business enterprise with limited funding is considered. The proposed method has been successfully approbated on the practical example of a functioning dental clinic. The result of the study confirms that the wide pairwise comparison matrix can be used as a simple and reliable method for forming the enterprise investment policy. Moreover, a comparison between the method based on the wide pairwise comparison matrix and the classical analytic hierarchy process was conducted. The results of the comparative analysis confirm the correctness of the method based on the wide matrix. The application of a wide pairwise comparison matrix also allows to widely use the statistical methods of experimental data processing for obtaining the vector of priorities. A new method is available for simple users. Its application gives about the same accuracy result as that of the classical hierarchy process. Financial directors of small and medium business enterprises get an opportunity to solve the problem of companies’ investments without resorting to services of analytical agencies specializing in such studies.

Keywords: analytic hierarchy process, decision processes, investment portfolio, intangible assets

Procedia PDF Downloads 265