Search results for: enterprise data warehouse

Authors: Mateusz Rak

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Objective: The paper aims to present various sources of competitive advantage which may occur when an enterprise strategically applies its concept of corporate philanthropy. Methodology: The review of the literature and available reports on the research regarding corporate philanthropy. Results: Strategic philanthropy is a positive phenomenon. Unfortunately, enterprises in Poland do not see all positive sides of such activities yet. Three kinds of corporate philanthropy may be described. They are to fulfil a social duty, improve the company reputation and gain a competitive edge. Practical implications: Showing enterprises the advantages of taking philanthropic actions, in particular, a large role of strategic philanthropy in gaining a competitive edge in the market as well as how to avoid negative consequences of corporate philanthropy. The paper presents corporate philanthropy on a few layers: as a CSR element, actions generating values in products, actions improving a corporate image in the market, altruist actions of employees.

Keywords: corporate philanthropy, corporate social responsibility, corporate foundations, CSR

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Authors: Aneeqa Suhail, Shabana Naveed

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The public sector (in both developed and developing countries) has gone through various waves of radical reforms in recent decades. In Pakistan, under the influence of New Public Management(NPM) Reforms; best practices of private sector are introduced in the public sector to modernize public organizations. Human Resource Information System (HRIS) has been popular in the private sector and proven to be a successful system, therefore it is being adopted in the public sector too. However, implementation of private business practices in public organizations us very challenging due to differences in context. This implementation gets further critical in Pakistan due to a centralizing tendency and lack of autonomy in public organizations. Adoption of HRIS by public organizations in Pakistan raises several questions: What challenges are faced by public organizations in implementation of HRIS? Are benefits of HRIS such as efficiency, process integration and cost reduction achieved? How is the previous system improved with this change and what are the impacts? Yet, it is an under-researched topic, especially in public enterprises. This study contributes to the existing body of knowledge by empirically exploring benefits and challenges of implementation of HRIS in public organizations. The research adopts a case study approach and uses qualitative data based on in-depth interviews conducted at various levels in the hierarchy including top management, departmental heads and employees. The unit of analysis is LESCO, the Lahore Electric Supply Company, a state-owned entity that generates, transmits and distributes electricity to 4 big cities in Punjab, Pakistan. The findings of the study show that LESCO has not achieved the benefits of HRIS as established in literature. The implementation process remained quite slow and costly. Various functions of HR are still in isolation and integration is a big challenge for the organization. Although the data is automated, the previous system of manually record maintenance and paperwork is still in work, resulting in the presence of parallel practices. The findings also identified resistance to change from top management and labor workforce, lack of commitment and technical knowledge, and costly vendors as major barriers that affect the effective implementation of HRIS. The paper suggests some potential actions to overcome these barriers and to enhance effective implementation of HR-technology. The findings are explained in light of an institutional logics perspective. HRIS’ new logic of automated and integrated HR system is in sharp contrast with the prevailing logic of process-oriented manual data maintenance, leading to resistance to change and deadlock.

Keywords: human resource information system, technological changes, state-owned enterprise, implementation challenges

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Melaku Tsehay

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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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Authors: Yao Wu

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In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.

Keywords: digital inclusive finance, high-quality development of export trade, fixed effects, binary marginal effects

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Authors: Memory Ranga, Phillip Pretorious

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The South African Government has invested a lot of money in Information Technology Governance (ITG) within the Government departments. The ITG framework was spearheaded by the Department of Public Service and Administration (DPSA). This led to the development of a governing ITG DPSA framework and later the Government Wide Enterprise Architecture (GWEA) Framework for assisting the departments to implement ITG. In addition to this, the government departments have adopted the Information Systems Audit and Control Association (ISACA) Control Objectives for Information and Related Technology (COBIT) for ITG processes. Despite all these available frameworks, departments fail to fully capitalise and improve the ITG processes mainly as these are too generic and difficult to apply for specific governance needs. There has been less research done to evaluate the progress on ITG initiatives within the government departments. This paper aims to evaluate the existing ITG frameworks within selected government departments in South Africa. A quantitative research approach was used in this study. Data was collected through an online questionnaire targeting ICT Managers and Directors from government departments. The study is undertaken within a case study and only the Eastern Cape Province was selected for the research. Document review mainly on ITG framework and best practices was also used. Data was analysed using the Google Analytic tools and SPSS. A one–sample Chi-Squared Test was used to verity the evaluation findings. Findings show that there is evidence that the current guiding National governance framework (DPSA) is out dated and does not accommodate the new changes in other governance frameworks. The Eastern Cape Government Departments have spent huge amount of money on ITG but not yet able to identify the benefits of the ITG initiatives. The guiding framework is rigid and does to address some of the departmental needs making it difficult to be flexible and apply the DPSA framework. Furthermore, despite the large budget on ITG, the departments still find themselves with many challenges and unable to improve some of the processes and services. All the engaged Eastern Cape departments have adopted the COBIT framework, but none has been conducting COBIT maturity Assessment which is a functionality of COBIT. There is evidence of too many the ITG frameworks and underutilisation of these frameworks. The study provides a comprehensive evaluation of the ITG frameworks that have been adopted by the South African Government Departments in the Eastern Cape Province. The evaluation guides and recommends the government departments to rethink and adopt ITG frameworks that could be customised to accommodate their needs. The adoption and application of ITG by government departments should assist in better governance and service delivery to the citizens.

Keywords: information technology governance, COBIT, evaluate, framework, governance, DPSA framework

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

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Authors: Ying Guo, Miaochan Li, David Yang, Xiao-Yan Li

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This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies.

Keywords: accounting information, response time, value relevance, stock price

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Authors: H. M. Avanesyan

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Economists have been discussing the importance of intangible assets for the success of organization for many years. The term intellectual capital was popularized in the 1990s by Thomas Stewart. “Intellectual capital is the knowledge, applied experience, enterprise processes and technology customer relationship and professional skills which are valuable assets to an organization.” Human capital – includes employee brainpower, competence, skills, experience and knowledge. Customer capital – includes relations and networks with partners, suppliers, distributors, and customers. The objective of the article is to assess one of the key components of organizational culture – organizational values. The focus of the survey was on assessing how intellectual capital presented in these values of the organization. In the conclusion section the article refers to underestimation of intellectual capital by the organization management and the various possible negative effects of the latter.

Keywords: human capital, intellectual capital, organizational culture, management, social identity, organization

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Omar Bendjimaa, Karzabi Abdelatif

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Small and medium enterprises have witnessed several developments in recent years thanks to the policies and programs of support given by the state, and that is due to their importance in local and national development. Nevertheless, the success and development of these firms depends on a number of factors, especially the human element, for instance, the culture of the manager has its origin in the culture of the community and is of crucial influence in these firms. In fact, this culture is nothing more than a set of values, perceptions, beliefs, symbols and practices repeated, in addition to the knowledge it has received from the readings and the modern means of education. All these factors have an impact on the effectiveness of governance, its resolutions, instructions and performance of its function as a manager of a medium or small enterprise is inevitably affected by these cultural values, it is the driving force, the leader, and the observer at the same time.

Keywords: small and medium enterprises, the culture of the manager, the culture of the community, values, perceptions, beliefs, symbols, performance

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Danuta Szwajca

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Image is a very important intangible asset of a contemporary enterprise, especially, in case of a bank as a public trust institution. A positive, demanded image may effectively distinguish the bank among the competition and build the customer confidence and loyalty. PKO BP is the biggest and largest bank functioning on the Polish financial market. Within the years not a very nice image of the bank has been embedded in the customers’ minds as an old-fashioned, stagnant, resistant to changes institution, what result in the customer loss, and ageing. For this reason, in 2010, the bank launched a campaign of radical image change along with a strategy of branches modernization and improvement of the product offer. The objective of the article is to make an attempt of effectiveness assessment of the brand repositioning campaign that lasted three years. The foundations of the assessment are the results of the questionnaire research concerning the way of bank’s perception before and after the campaign.

Keywords: advertising campaign, brand repositioning, image of the bank, repositioning

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Christopher Muhawe, Masooda Bashir

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With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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Authors: S. Łęgowik-Świącik

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This article is a contribution to the research into the determinants of value creation via digital platforms in variable operating conditions. The dynamics of the market environment caused by the COVID-19 pandemic have made enterprises built on digital platforms financially successful. While many classic companies are struggling with the uncertainty of conducting a business and difficulties in the process of value creation, digital platforms create value by modifying the existing business model to meet the changing needs of customers. Therefore, the objective of this publication is to understand and explain the relationship between value creation and the conversion of the business model built on digital platforms under pandemic conditions. The considerations relating to the conceptual framework and determining the research objective allowed for adopting the hypothesis, assuming that the processes of value creation are evolving, and the measurement of these processes allows for the protection of value created and enables its growth in changing circumstances. The research methods, such as critical literature analysis and case study, were applied to accomplish the objective pursued and verify the hypothesis formulated. The empirical research was carried out based on the data from enterprises listed on the Nasdaq Stock Exchange: Amazon, Alibaba, and Facebook. The research period was the years 2018-2021. The surveyed enterprises were chosen based on the targeted selection. The problem discussed is important and current since the lack of in-depth theoretical research results in few attempts to identify the determinants of value creation via digital platforms. The above arguments led to an attempt at theoretical analysis and empirical research to fill in the gap perceived by deepening the understanding of the process of value creation through network effects via digital platforms under pandemic conditions.

Keywords: business model, digital platforms, enterprise management, pandemic conditions, value creation process

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Authors: Jun-Lun Jiang, Bing-Sheng Yu

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Processing of flat-panel displays generates huge amount of wasted glass polishing powder, with high concentration of cerium and other elements such as lanthanum. According to the current statistics, consumption of polishing powder was approximately ten thousand tons per year in the world. Nevertheless, wasted polishing powder was usually buried or burned. If the lanthanum and cerium compounds in the wasted polishing powder could be recycled, that will greatly reduce enterprise cost and implement waste circulation. Cathodes of SOFCs are the principal consisting of rare earth elements such as lanthanum and cerium. In this study, we recycled the lanthanum and cerium from wasted glass polishing powder by acid-solution method, and synthesized La0.8Sr0.05Ca0.15Fe0.8Co0.8O3-δ and Gd0.1Ce0.9O2 (LSCCF-GDC) composite cathode material for SOFCs by glycinenitrate combustion (GNP) method. The results show that the recovery rates of lanthanum and cerium could accomplish up to 80% and 100% under 10N nitric acid solution within one hour. Comparing with the XRD data of the commercial LSCCF-GDC powder and the LSCCF-GDC product synthesized with chemicals, we find that the LSCCF-GDC was successfully synthesized with the recycled La & Ce solution by GNP method. The effect of adding ammonia to the product was also discussed, the grain size is finer and recovery rate of the product is higher without the addition of ammonia to the solution.

Keywords: glass polishing powder, acid solution, recycling, composite cathodes of solid oxide fuel, cell (SOFC), perovskite, glycine-nitrate combustion(GNP) method

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Belaynesh Tsegay Beyene, Teklay Gebrecherkos, Atsebaha Gebrekidan Kahsay, Mahmud Abdulkader

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Background: Hepatitis B and C viruses are of important health and socioeconomic problem of the globe with remarkable diseases and deaths in Sub-Saharan African countries. The burden of hepatitis is unknown in the prison settings of Tigrai. Therefore, we aimed to describe the seroprevalence and associated factors of hepatitis B and C viruses among prisoners of Tigrai, Ethiopia. Methods: A cross-sectional study was carried out from February 2020 to May 2020 at the prison facilities of Tigrai. Demographics and associated factors were collected from 315 prisoners prospectively. Five milliliter of blood was collected and tested using rapid tests kits of HBsAg (Zhejiang orient Gene Biotech Co., Ltd., China) and HCV antibodies (Volkan Kozmetik Sanayi Ve Ticaret Ltd. STI, Turkey). Positive samples were confirmed using enzyme-linked immunosorbent assay (ELISA) (Beijing Wantai Biological Pharmacy Enterprise Co. Ltd). Data were analyzed using Statistical Package for Social Sciences (SPSS) version 20 and p < 0.05 was considered statistically significant. Results: The overall seroprevalence of HBV and HCV were 25 (7.9%) and 1(0.3%), respectively. The majority of hepatitis B viral infections were identified from the age groups of 18-25 years (10.7%) and unmarried prisoners (11.8%). Prisoners greater than 100 per cell [AOR =3.95, 95% CI= (1.15, 13.6, p =0.029)] and having history of alcohol consumption [AOR =3.01, 95% CI= (1.17, 7.74, p =0.022)] were significantly associated with HBV infections. Conclusions: The seroprevalence of HBV among prisoners was nearly high or borderline (7.9%) with a very low HCV prevalence (0.3%). HBV was most prevalent among young adults, large number of prisoners per cell and those who had history of alcohol consumption. This study recommends that there should be prison-focused intervention including regular health education by emphasis on the mode of transmission and introducing HBV screening policy for prisoners especially when they enter to the prison.

Keywords: seroprevalence, HBV, HCV, prisoners, Tigrai

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Authors: Chuping Lo

Abstract:

This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: M. Verde, G. Falzarano

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The paper examines the connection between corporate social responsibility (CSR), capability approach and poverty reduction; in particular, the local employment development (LED) by way of CSR initiatives. The joint action of LED/CSR results in a win-win situation, not only for the enterprises but also for all the stakeholders involved; in this regard, subsidiarity and coordination between national and regional/local authorities are central to a socially-oriented market economy. In the first section, the CSR is analysed on the basis of its social function in the fight against poverty, as a 'capabilities deprivation'. In the central part, the attention is focused on the relationship between CSR and LED; ergo, on the role of the enterprises in fostering capabilities development (the employment). Besides, all the potential solutions are presented, stressing the possible combinations, in the last part. The benchmark is the enterprise as an economic and a social institution: the business should not be combined with profit merely, paying more attention to its sustainable impact and social contribution. In which way could it be possible? The answer is the CSR. The impact of CSR on poverty reduction is still little explored. The companies help to reduce poverty through economic contribution, human rights and social inclusion; hence, the business becomes an 'agent of development' in order to fight against 'inequality'. The starting point is the pyramid of social responsibility, where ethic and philanthropic responsibilities involve programmes and actions aimed at personal development of the individuals, improving human standard of living in all forms, including poverty, when people do not have a choice between different 'life options', ranging from level of education to employment. At this point, CSR comes into play and works on two dimensions: poverty reduction and poverty prevention, by means of a series of initiatives: first of all, job creation and precarious work reduction. Empowerment of the local actors, financial support and combination of top down and bottom up initiatives are some of CSR areas of activity. Several positive effects occur on individual levels of educations, access to capital, individual health status, empowerment of youth and woman, access to social networks and it was observed that these effects depend on the type of CSR strategy. Indeed, CSR programmes should take into account fundamental criteria, such as the transparency, the information about benefits, a coordination unit among institutions and more clear guidelines. In this way, the advantages to the corporate reputation and to the community translate into a better job matching on the labour market, inter alia. It is important to underline that the success depends on the specific measures of the areas in question, by adapting them to the local needs, in light of general principles and index; therefore, the concrete commitment of the all stakeholders involved is decisive in order to achieve the goals. The enterprise would represent a concrete contribution for the pursuit of sustainable development and for the dissemination of a social and well being awareness.

Keywords: capability approach, local employment development, poverty, social inclusion

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: Suzhou Wei, Isobel Cunningham, Laura Bradley McCauley

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Social enterprises play a significant role in resolving social issues in the modern world. In contrast to traditional commercial businesses, their main goal is to address social concerns rather than primarily maximize profits. This phenomenon in entrepreneurship is presenting new opportunities and different operating models and resulting in modified approaches to measure success beyond traditional market share and margins. This paper explores social enterprises to clarify their roles and approaches in addressing grand challenges related to social issues. In doing so, it analyses the key differences between traditional business and social enterprises, such as their operating model and value proposition, to understand their contributions to society. The research presented in this paper responds to calls for research to better understand social enterprises and entrepreneurship but also to explore the dynamics between profit-driven and socially-oriented entities to deliver mutual benefits. This paper, which examines the features of commercial business, suggests their primary focus is profit generation, economic growth and innovation. Beyond the chase of profit, it highlights the critical role of innovation typical of successful businesses. This, in turn, promotes economic growth, creates job opportunities and makes a major positive impact on people's lives. In contrast, the motivations upon which social enterprises are founded relate to a commitment to address social problems rather than maximizing profits. These entities combine entrepreneurial principles with commitments to deliver social impact and grand challenge changes, creating a distinctive category within the broader enterprise and entrepreneurship landscape. The motivations for establishing a social enterprise are diverse, such as encompassing personal fulfillment, a genuine desire to contribute to society and a focus on achieving impactful accomplishments. The paper also discusses the collaboration between commercial businesses and social enterprises, which is viewed as a strategic approach to addressing grand challenges more comprehensively and effectively. Finally, this paper highlights the evolving and diverse expectations placed on all businesses to actively contribute to society beyond profit-making. We conclude that there is an unrealized and underdeveloped potential for collaboration between commercial businesses and social enterprises to produce greater and long-lasting social impacts. Overall, the aim of this research is to encourage more investigation of the complex relationship between economic and social objectives and contributions through a better understanding of how and why businesses might address social issues. Ultimately, the paper positions itself as a tool for understanding the evolving landscape of business engagement with social issues and advocates for collaborative efforts to achieve sustainable and impactful outcomes.

Keywords: business, social enterprises, collaboration, social issues, motivations

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Authors: Mohammad Reza Ostad Ali Naghi Kashani, Esfanji Elia

Abstract:

Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing particularly in developing countries like Iran. ERP projects are expensive, time consuming, and complex, in addition the failure rate is high among these projects. It is important to know whether these projects could meet their goals or not. Furthermore, the area which should be improved should be identified. In this paper we made a framework to evaluate ERP projects success implementation. First, based on literature review we made a framework based on BSC model, financial, customer, processes, learning and knowledge, because of the importance of change management it was added to model. Then an organization was divided in three layers. We choose corporate, managerial, and operational levels. Then to find criteria to assess each aspect, we use Delphi method in two rounds. And for the second round we made a questionnaire and did some statistical tasks on them. Based on the statistical results some of them are accepted and others are rejected.

Keywords: ERP, BSC, ERP project evaluation, IT projects

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Authors: Fernando Doral

Abstract:

Family businesses are a key phenomenon within the business landscape. Nevertheless, it involves two terms (“family” and “business”) which are nowadays rapidly evolving. Consequently, it isn't easy to diagnose if a family business will be a growing or decreasing phenomenon, which is the objective of this study. For that purpose, a sample of 50 Spanish-established companies from various sectors was taken. Different factors were identified for each enterprise, related to the profile of the founders, such as age, the number of sons and daughters, or support received from the family at the moment to start it up. That information was taken as an input for a clustering method to identify groups, which could help define the founders' profiles. That characterization was carried as a base to identify three factors whose evolution should be analyzed: family structures, business landscape and entrepreneurs' motivations. The analysis of the evolution of these three factors seems to indicate a negative tendency of family businesses. Therefore the consequent diagnosis of this study is to consider family businesses as a declining phenomenon.

Keywords: business diagnose, business trends, family business, family business founders

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, Valencia Pérez, Héctor Fernando, Lamadrid A. Alberto, Vivanco V. Martín

Abstract:

Cosmology is a discipline commonly linked to philosophy. In this work, we show cosmology, from a perspective that can provide some proposals to help develop SMB in Mexico. We start from the belief that, in a complex world, the solutions to problems must nurture from different approaches. In order to be able to do this, we need to change our point of reference and use theoretical proposals and methodologies that came from other disciplines; in this case, we will try to show that between philosophy and administration exist dialogs that need to be incentivized. The work is structured in three parts. In the first one, we create a description of cosmology and how it could be applied to business. In the second, we show some of the most common problems that the SMB suffer from and in the third, we present a proposal of how cosmology can help improve the development. Finally, we concluded that better understanding of real needs, integration of knowledge at large scale and using information technologies within the cosmology framework presentment could make a difference.

Keywords: harmonic fusion, national sustainability, financial management, triple helix

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Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

Abstract:

Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

Procedia PDF Downloads 115