Enterprise Applications Research Articles

Agile Application Landscape Planning in Energy Sector – Architectural Experiences

The continuously changing and developing technology framework and IT infrastructure create novel approaches and possibilities all over the industry spectrum. Thus the energy and its IT supporting segment cannot be an exception either. Nowadays it is hard to imagine any kind of work process on energy generation, transmission, distribution or consumption filed without IT application solutions. To keep this portfolio transparent and effective a methodology is needed for developments and strategy planning. In this paper enterprise application landscape planning experiences and recommendations are introduced. The approach effectively combines the TOGAF (The Open Group Architecture Framework) and Agile methods. At the end of a five years ‘journey’, the evolution can be followed from a target architecture planning approach to a novel solution which is in use right now. To conclude this work a group of techniques and methods are suggested for the application of these solutions for a sustainable and forward-looking application portfolio at a reasonable cost level.

Preface to the special issue on “Enterprise and organizational applications of distributed ledger technologies”

Preface to the special issue on “Enterprise and organizational applications of distributed ledger technologies”

The effects of environmental regulations on the sustainable entrepreneurship from the perspective of dynamic capabilities: a study based on Chinese new energy enterprises

Environmental regulations play important roles in enterprises’ sustainable entrepreneurship, and their relationships are affected by enterprises’ dynamic capabilities. This paper analyzed the panel data of China’s new energy industry from 2011 to 2021, aiming to explore the impact of environmental regulations on sustainable entrepreneurship and the mechanism of dynamic capacities between them. The results include: There is an inverted U-shaped relationship between incentive environmental regulation and enterprises’ sustainable entrepreneurial performances, and there is a positive relationship between command environmental regulations and enterprises’ sustainable entrepreneurial performances; Both absorptive capacity and innovative capability of dynamic capacities negatively moderate the inverted U-shaped relationship between incentive environmental regulations and sustainable entrepreneurial performances, and negatively moderate the positive relationship between command environmental regulations and sustainable entrepreneurial performances. The results highlight the importance of dynamic capabilities for new energy enterprises, and provide a certain enlightening effect on the formulation of environmental regulation policies, as well as the application of enterprises’ dynamic capabilities.

Defining a theoretical model to assess transition from on-premises to Software-as-a-Service

Transitioning enterprise applications (EA) software from on-premises to Software-as-a-Service (SaaS) is a crucial question for IT adoption decisions. Grounded in the literature, this article suggests a research model to support enterprises assessing a transition strategy from on-premises to a SaaS model. The research model proposes eight hypotheses to be tested and analysed with data collected from a questionnaire among firms that have EA software. This paper goes beyond the software functionality and usage to address the strategic challenges of selection in a new landscape of the enterprise software industry, also considering the industry’s software deployment chain, business model, and the moderating factor of firm’s business process sophistication. We aim to provide new and significant guidelines for enterprise’s and software vendor´s decision-making.

Current state and approaches to automation of central heating stations at industrial enterprises

The paper examines the problems of forming technical requirements for the automation of central heating points of fuel and energy complex enterprises. The main technological schemes that are subject to automation are considered, the basic requirements for the installation of technical automation equipment are shown, the basic requirements are identified based on modern concepts for constructing automated control systems, and the main adjustable and controlled parameters of the central heating station for the main application in State Unitary Enterprise “Fuel and Energy Complex” are clarified.

Innovation and Practical Exploration of Industrial Economic Models Driven by Emerging Technologies

Abstract Science and technology innovation is the key driving force to support and lead industrial transformation and upgrading. This topic explores the relationship between digital technology application and industrial economic model innovation in the context of emerging technology development. Taking the annual report text of an enterprise as a research sample, the improved LDA theme model is applied to extract the themes of the annual report text and analyze the characteristics and trends of the digital technology application of the sample enterprise. After measuring the degree of digitization of the enterprise, the conceptual model of its relationship with industrial economic model innovation is constructed, relevant hypotheses are put forward, and correlation and regression analyses are applied to validate the role of the application of digital technology in promoting the innovation of the industrial economic model. The use of digital technology in the sample enterprises during the research interval has increased by about 18 times, dominated by the use of artificial intelligence technology. The application of digital technology has a significant positive effect on the industrial economic model’s innovation (p < 0.01), with a regression coefficient value of 0.508. The analysis demonstrates that enterprises can use emerging technologies to connect all links from production to sales, revolutionize the logic of value creation in the existing business model, and promote the innovation of the industrial economic model.

The Latest Trends and Challenges in Enterprise Application Development with Java

The Latest Trends and Challenges in Enterprise Application Development with Java

A Comprehensive Microservice Extraction Approach Integrating Business Functions and Database Entities

Cloud application practitioners are building large-scale enterprise applications as microservices, to leverage scalability, performance, and availability. Microservices architecture allows a large monolithic application to be split into small, loosely coupled services. A service communicates with other services using lightweight protocols such as RESTful APIs. Extracting microservices from the monolith is a challenging task and is mostly performed manually by system architects based on their skills. This extraction involves both: 1) Partitioning of business logic, 2) Partitioning of database. For partitioning of business logic, the existing research studies focus on decomposition by considering the dependencies in the application at the class-level. However, with the passage of time, monolith application classes outgrow their size defying the Single Responsibility Principle (SRP). So, there is a need to consider the code within the classes when identifying microservices. Current studies also lack the partitioning of database and ignore the mapping of Database Entities (DE) to the microservices. In this paper, we present a Comprehensive Microservice Extraction Approach (CMEA) that considers: 1) Both classes and their methods to define and refine microservices, 2) Associate the DE to microservices using newly devised eight guiding rules handling ownership conflicts. This approach has been applied to three benchmark web applications implemented in Java and one in-house application implemented in both Java and Python. Our results demonstrate better or similar software quality attributes in comparison to the existing related studies. CMEA improves software quality attributes by 22%. System architects can easily identify microservices along with their DE using our approach. The CMEA is generic and language-independent so it can be used for any application

Evaluate Canary Deployment Techniques using Kubernetes, Istio and Liquibase for Cloud Native Enterprise Applications to Achieve Zero Downtime for Continuous Deployments

Evaluate Canary Deployment Techniques using Kubernetes, Istio and Liquibase for Cloud Native Enterprise Applications to Achieve Zero Downtime for Continuous Deployments

Managing business using emerging technologies: an examination of firms' performance through big data and enterprise applications capabilities

Managing business using emerging technologies: an examination of firms' performance through big data and enterprise applications capabilities

Construction of Financial Performance Evaluation System based on Principal Component Analysis Algorithm and Its Application in Digital Transformation Enterprises

In the context of a strong national push toward the growth of the ""digital economy"", traditional manufacturing companies are increasingly turning to new digital technologies for their digital transformation. This paper aims to investigate the suitability of using a financial performance evaluation system for assessing the success of digital transformation strategies employed by these enterprises. The application of principal component analysis in digital transformation enterprises involves repeatedly selecting the main indicators in the financial performance evaluation index system of manufacturing enterprises. Finally, a financial performance evaluation index system suitable for analyzing digital transformation enterprises is constructed. The differences in financial performance before and after transformation are analyzed, and a comprehensive evaluation and comparative analysis are conducted on the financial performance of digital transformation enterprises and non-digital transformation enterprises. The experimental results show that the average growth rate of total assets of enterprises is 7.07%. The average growth rate of operating revenue is 20.99%. The standard deviations are 17.42% and 235.9%. There is a significant difference between the maximum and minimum values of these two indicators, indicating that the average dispersion of these two indicators is relatively high. In the initial phases of digital transformation implementation, enterprises that adopt digital technology experience a certain level of profitability improvement, as shown by the results. Compared to businesses that have not undergone a digital transformation, digitally transformed enterprises possess greater advantages and flexibility in digital operations. Digital transformation has important theoretical and practical value in improving the financial management level of digital transformation enterprises.

Epidemiological data of suicidal behaviour – how to inform and not to disinform?

Introduction and objective: Suicide is a significant global public health concern. Media reporting greatly influences suicide prevention efforts, with the Internet and social media playing a major role. Inappropriate reporting can undermine prevention, while responsible reporting can have a preventive effect. The World Health Organization and the International Association for Suicide Prevention have issued a set of guidelines for journalists, which are also available in the Polish language. This article is a preliminary report on suicide behaviour epidemiology reporting in the Polish media. Materials and methods: The study used data from the National Police Headquarters to analyse suicide attempts and deaths in Poland between 2017 and 2022. Population size data was obtained from the Statistics Poland website. News analysis was conducted using the BuzzSumo Enterprise Application to assess social media shares and engagements for the top 100 popular web pages with the keyword “suicide” in the Polish language news between 2017 and 2022. Results: The study found that media articles often omitted standardised indicators when reporting suicide statistics. The media focus on growing suicide mortality among children and adolescents was evident, while a similar trend among older adults received only limited attention. Additionally, some articles failed to distinguish between suicide attempts and deaths, used sensational language in the headlines, and did not consider changes in reporting methodologies, leading to potential misinterpretations of suicide-related data. Conclusions: Responsible reporting is crucial to prevent negative effects on public health. Understanding the association between suicide and misinformation can lead to targeted interventions and strategies to safeguard well-being.

Multiple linear regression analysis for determining factors affecting the actual adoption of enterprise application architecture for supply chain management

Background: In this study, Multiple Linear Regression (MLR) is cast-off a statistical technique accustomed to propositions on determining the nexus between internal dynamic exasperations (IDEs) and external dynamic exasperations (EDEs), denoted as the independent variables (Xs), as well as perceived attitudes signified as the predictor variable for actual adoption (AA) of enterprise application architecture (EAA), presented as the dependent variable (Y). Objective: The objective of this paper was to ascertain the alternative hypotheses that IDEs, EDEs, and perceived attitudes (PAs) affect the AA of EAA for supply chain management (SCM) within small and medium enterprises (SMEs). Design/Methodology: The study used quantitative analysis chronicled in statistical package social science (SPSS) version 25 that encompassed diagnostic tests through Cronbach’s Alpha for reliability, and Double-Exponent Distribution for data validity. Data analysis is concerted through the model summary, graphical expression of MLR, regression analysis (algebra expression), along with Beta weight. Results/Findings: A stratified-random sampling of 310 data sets were used as SMEs’ owners and managers. The results were obtained from the main analysis of multiple regression that produced a model equation (Y) that determined the estimations of AA of EAA with 5xs; 19.49x6; 17.84x6; 18.23x6; 16.12x6; and 9.82x6; and response variable (Y); 25.8 x6: wherein Ԑi is residual error. Practical implications and conclusions: This exertion contributes to existing knowledge on AA of EAA for SCM by providing three main separable functions of multilinear regression (MLR). First, it broadens the understanding of the strength of relationships between Xs, PV and Y. Second, its expositions which predictors in the model are statistically significant and which are not. Third, it projects a confidence interval for each predicted regression coefficient.

Production costs and total completion time minimization for three-stage mixed-model assembly job shop scheduling with lot streaming and batch transfer

Assembly scheduling problems have broad applications in discrete manufacturing enterprises and hence gained extensive attention in academics. However, some important and actual factors including lot streaming, batch transfer of components and mixed-model assembly are yet not well studied. To adapt to actual production and enhance competitiveness, a three-stage mixed-model assembly job shop scheduling with lot streaming and batch transfer is investigated in this work. To tackle this problem, spatial-temporal links among three stages with differentiated production lot size are established and a novel mathematical model is formulated to minimize total completion time and production costs including setup costs, transport costs, and inventory costs. Besides, an improved multi-objective coevolutionary simulated annealing algorithm is developed. To promote the coevolution of processing, transfer, and assembly sub-problems, the multi-attribute combination rule, similarity rule, and consistency rule are respectively designed for each sub-problem. An adaptive execution strategy of sub-problems is trained by Q-learning to maximize the overall benefits. Experimental results show that both the discovered rule and the adaptive strategy are effective, and the proposed algorithm significantly outperforms seven competitive multi-objective algorithms in fixing the studied problem. More importantly, the developed production mode of “processing with lot streaming-batch transfer-mixed-model assembly considering pull production” has a better comprehensive performance than the other three actual production modes.

The use of Lean Manufacturing in Process Improvement: The Impacts of Lean Philosophy in a Medium Metallurgy Shipping

In the current economic scenario and post-pandemic business resumption, the companies are pressed to look for efficient alternatives that reduce costs and provide productive wins. The lean philosophy as well as its organizational improvement methodology is a powerful factor in improving processes, identifying waste, and increasing productivity and efficiency in the productive chain. The lean manufacturing has the purpose of identifying and eliminating waste and looking for perfection in the products, always focusing on the client's vision. This work was carried out in a metallurgical company and had as its main objective to analyze the impact of the lean philosophy in the company and identify the benefits provided by process improvement applications in a medium-sized enterprise. This work used the action research method, which collected information and processes analysis directly in the factory environment for the subsequent development of strategies and improvement plans. Through the application of lean and after the improvement's implementation, it was noted that the lean philosophy and the process improvement generated high productivity gains in the organization, in addition to savings, security, efficient management control, waste reduction, space optimization, process standardization, organization and quality assurance.

Overlaying DAQ Systems on Existing Control Systems for Modernizing Power Plants to Realize Industry 4.0

In Industry 4.0, digital technologies are integrated with control systems to use enterprise applications and data analytics to improve the efficiency and productivity of industrial processes. However, power plants in Sri Lanka are yet to get such applications primarily due to lack of data acquisition capabilities, high cost of control systems supplied with data analytic applications and lack of awareness about the capabilities of such applications.Though data analytic applications can be developed locally, obtaining data from power plants cannot be done without changing the existing control systems. This paper proposes a model to overlay a Data Acquisition System (DAQ) on top of the existing plant control system without replacing it. The acquired data can be used for Industry 4.0 applications. Due to the loose coupling of the control systems, DAQ and data analytic applications, each can be updated independently preserving each system’s investment.To demonstrate the model, an implementation of DAQ in hydropower plants in Sri Lanka in the 2000s - at a time when data analytics was not considered a part of the power plant control systems and data communication was not readily available- is discussed. Many faults were detected by these DAQs. The local development saved about Rs. 30 million for the Ceylon Electricity Board (CEB). Early fault detection would have saved billions of rupees for the CEB and Sri Lanka. This development shows the ingenuity of the engineers of the CEB at a juncture where the services and the financial operation of the CEB are questioned.Due to the availability of Internet access and the advancement of cloud systems at present, data analytics and AI applications are within the reach of power plants in Sri Lanka. By implementing the proposed model to collect data from existing control systems, the Sri Lankan Power Utility (CEB) can consider implementing Industry 4.0 applications locally without spending an excessive amount of foreign currency.

Enterprise Resource Planning: Analysis and Utilization of Open Source Applications with the EAP Method

System automation is currently very much needed for the small and medium business industry to large-scale companies. The computerized systems concept is increasingly in demand due to the shift in the industrial era 4.0. Enterprise Resource Planning (ERP) is a multi-module application that puts forward the concept of an integrated computerized system that stores all company data in one easily accessed database. This study discusses open source ERP applications for Micro, Small, and Medium Enterprises by looking at the running business processes that will then adjust to the ERP application module facilitated by the developer. The Enterprise Architecture Planning method acts as an analysis stage and a tool used in business process analysis using the Unified Modeling Language to identify all actors involved and a matrix of relationships between data entities, business processes, and applications. This research provides recommendations modules that can use in open source ERP applications appropriate for the company.

Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries

With the expansion of modern database services, multi-user access has become a crucial feature in various practical application scenarios, including enterprise applications and e-commerce platforms. However, if multiple users submit queries within a short time frame, it can result in potential issues such as redundant computation and query concurrency. Unfortunately, most existing multi-query optimization methods, which aim to enhance query processing efficiency, have not adequately addressed these two problems, especially in the setting where multiple queries are being executed concurrently. To this end, we propose a novel method named Lemo for the multi-query optimization problem. Specifically, we propose a novel value network to predict latencies of concurrent queries as the foundation model for query plan generation. Furthermore, we introduce a shared buffer manager component to cache the intermediate results of sub-queries. The shared buffer manager applies a novel replacement policy to maintain the cached buffer with the objective of maximizing the opportunity for the reuse of the cached sub-queries. Based on the shared buffer, our proposed value network can incorporate the cached results into cost estimation to further guide Lemo in generating query plans, thus avoiding redundant computation. Lemo has been integrated into PostgreSQL and experiments conducted on real datasets with PostgreSQL show that it outperforms all the baselines in efficiency.

Textual vs Visual Representation- Role of Aesthetics in Human Cognition and Perception

Visual representation is better as compared to textual representation in every aspect, either for a code or for the design of a software product. Writing a code using different programming languages in textual form is quite difficult as compared to a visual representation of code. The current study proved this phenomenon by presenting different codes in three different representations. These representations include textual, algorithm,and flow graph. On the basis of observation and analysis of the current study, these three representations were examined. It was concluded that visual representation is the best way to present a code according to many parameters. These results are helpful in the recent switch towards low programming from high programming. Moreover, further research can be conducted on how large enterprise applications code can be created by using visual programming languages.

Evolution of Enterprise Applications through Emerging Technologies

Evolution of Enterprise Applications through Emerging Technologies