Business Scenarios Research Articles

A SOFTWARE SOLUTION TO WORK WITH A DATABASE OF BUSINESS PROCESS MODELS AND ANALYZE THEIR STRUCTURAL MEASURES

Business process modeling is one of the main tools of the BPM (Business Process Management) concept. With the help of business process modeling, business scenarios can be presented in the form of graphical models that can be easily understood by both information technology (IT) professionals and non-IT professionals – business analysts, software customers, department heads, top managers, and other stakeholders interested in business process improvement. Business process improvement is usually done through the automation of activities, which were identified as “bottlenecks” after analysis. However, it is possible to analyze a business process model only if it is clear and correct in terms of compliance with both the notation used and the real business process it depicts. This paper considers the analysis of BPMN (Business Process Model and Notation) business process model structural measures. It is assumed that business process models, which by their structural features violate rules of business process modeling, are neither understandable nor suitable for further work with them, which also can lead to various errors occurring at the stage of business process analysis, as well as at the stage of its improvement and implementation of proposed changes, i.e., during development, testing and maintenance of distinct software components, information system modules or BPM-system scenarios that ensure business process execution. Therefore, in this paper, we propose to identify the main elements of BPMN business process models and their structural measures that affect models’ understandability and maintainability and could be sources of errors. Considering selected measures, it is proposed to calculate respective values for a large collection of BPMN business process models, and then study compliance with theoretical business process modeling guidelines on practice when real business process models are designed. In order to provide efficient storage and processing of a large collection of BPMN business process models data, there were developed a database, and a software component. Results of analysis of BPMN business process model structural measures obtained using developed database and software component are demonstrated and discussed. The conclusion is made, as well as future research directions in this field are formulated.

Enacting entrepreneurial hustle

Success as an entrepreneur requires boldness, creativity, and action in the face of uncertain opportunities and idiosyncratic setbacks. Our recent research elevated and defined the concept of entrepreneurial hustle: an entrepreneur’s urgent, unorthodox actions intended to be useful in addressing immediate challenges and opportunities under conditions of uncertainty. We argue this foundational construct is useful for explaining how successful entrepreneurs behave. Early scholarly research on entrepreneurial hustle has generated meaningful theoretical insights into the concept. In this article, we extend those insights into practical prescriptions for entrepreneurs, corporative innovators, and innovative changemakers, identifying what they might do and how they might use the hustle concept to effectively manage uncertain and ambiguous business scenarios. Furthermore, we examine the potential downsides of hustle and provide practical steps that can be taken to mitigate such risks.

Behavior Driven Development using Gauge Framework

Abstract: Behavior Driven Development (BDD) focuses on the behavior of the system or the business point of view and captures the business specific requirements. Many BDD frameworks implement a strict syntax like Gherkin, this study proposes a solution to remove this by using Gauge Framework. The BDD Gauge Framework will be analyzed and studied in-depth. The drawback of this study is that a big industry level testing isn’t feasible hence will need to be dependent on external research papers. The emerging opportunity here is that Gauge Framework can be considered as a BDD tool with its unique inbuilt capability of parallelization or scaling of tests, data driven testing, no strict restricted syntax and also enhances agile development. Key findings of this study will be how Gauge Framework improves testing with better defect detection while maintaining good method coverage for various business scenarios and also how it can be used as a BDD framework by reducing manual effort. This paper will also determine the performance with respect to other competitive frameworks in the market like Cucumber, RSpec, SpecFlow.

Modelling Cost of Quality for Defect Reduction

Purpose: This paper aims to develop the system dynamics model of managing quality costs using the perception maps prepared on the basis of the actual data of the organization. The model depicts the cost of quality and the associated defect percentage to represent the real-world data of the company under study. Model is validated using the different tests to build the confidence on the model. Underlying feedback structures and interactions among various variables make the model more robust and realistic.
 Design/Methodology/Approach: The simulation software STELLA is used for programming the model. Using the generic structures of the cost of quality, stock and flow diagram is developed to map the real-life business scenario.
 Findings: Cost of Quality is a forgotten dimension in many companies. Most of the companies are not measuring the cost of quality as a powerful indicator for quality measurement and for process improvement. Defect level is the function of prevention, appraisal and failures (PAF) costs associated with the PAF model. System Dynamics is computer-based simulation methodology that gains the insight of the social, economic, and business problems and acts as a powerful tool for policy design for better decision making.
 Implications/Originality/Value: Policy analysis clearly indicate that dynamics of cost of quality is quite complex and to identify the prioritized parameter for investment cannot be intuitively appreciated. System dynamics is a simulation-based methodology which can solve the complex interactions and different policy runs lead to the best appropriate mix of cost elements in order to reduce the failure costs (internal and external).

Intelligent Digital Platform for Community-Based Rural Tourism—A Novel Concept Development in Peru

The COVID-19 pandemic has driven the rapid evolution and digitization of different tourism sectors through Industry 4.0. However, Community-based Rural Tourism (CRT) has not experienced the same technological advancement. Thus, considering tourism as a powerful socioeconomic driver, this research is based on the relevance of the CRT for the development of rural areas through job creation, preservation of historical-cultural and architectural heritage, and appreciation of the local market. Therefore, the objective of this paper is to present a concept development model of an intelligent digital platform (IDP), where tourism products and services are visualized, articulated, and integrated with the different actors of the CRT, offering a personalized tourist experience. The concept was developed based on Business Process Management and Business Model Canvas (BMC). Thus, through meetings and interviews, it was possible to extract essential information to obtain the necessary know-how for the development of the concept. It was concluded that the COVID-19 pandemic has established a new business scenario, intensifying and accelerating the use of digital tools and ICTs in several sectors, including tourism. However, the use of ICTs in CRT is still incipient. As Peru is a country where rural tourism has a strong tradition, but there are no specific platforms for CRT, which makes the broad dissemination of rural experiences difficult, a BMC template has been developed to integrate the expected objectives, and the application of the proposed framework serves as a guide for other platforms with different niches markets in the tourism sector.

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

PurposeThe purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals.Design/methodology/approachThis paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations; exploring benefits of big data combined with AI in modern businesses; and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses.FindingsAI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic.Research limitations/implicationsThere is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well.Social implicationsThis paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant.Originality/valueThis paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times.

Decision support using AI: the data exploitation at telecoms in practice

ABSTRACT AI is a technological advancement used nowadays extensively by telecoms to take decisions based on the vast amounts of data they own and to optimise their daily operations. Hence, a question being raised amongst experts in this industry is how AI can be applicable in the various functions of telecoms. This paper showcases how the telecommunication industry could adopt Artificial Intelligence mechanisms into daily tasks and operations, in order to better utilise available data and accelerate digital transformation. The scope of this paper is to analyse and explore the opportunities and the challenges that have risen in telecommunications organisations, but more precisely, describes experiences from the IT Innovation Center of OTE Group that investigates and validates AI-related technologies in real business scenarios, aiming to boost and even further the organisation’s digital transformation and engagement in future markets. However, as depicted in this paper, although the numerous opportunities, telecoms face many obstacles which they try to overcome in this AI journey.

The influence of learner characteristics, instructional design and work environment on the transfer of training

PurposeThis study aims to highlight the role of individual and instructional design factors on training transfer and explore and review focal training factors that influence the transfer of training.Design/methodology/approachA conceptual framework has been developed for this study to better present the prevalent factors that have been empirically validated.FindingsThe facets of transfer encompassed in this study have gathered enough evidence to demonstrate a positive association with the transfer. This review points out that all predictor variables (learner characteristics, instructional design and environmental factors) positively and significantly influence the transfer of training. A mix of variables is proposed, with further investigation recommended to develop a robust training transfer hypotheses.Research limitations/implicationsThis study contributes to the training transfer literature in three ways. First, the authors have shown the positive influence of pre-training factors on training transfer. This study is grounded in a robust theoretical framework, thus fulfilling the previous gaps. This conceptual study elaborates on the importance of factors to establish the training transfer hypothesis. Future studies should test the suggested framework and look for other things that could help learners be more effective and motivated so that training can be more effective and transferable.Practical implicationsThis study has significant findings for organizations operating in the current business scenario to enhance learning transfer, where the transfer is very low and a significant cause of concern for every organization. By making management aware of the success factors of training transfer, they can ensure a better training transfer. In this study, the transfer design considerations are discussed in detail, and their practical consequences are provided for training transfer in general and training professionals in particular.Originality/valueThe training transfer literature showcases two significant gaps; first, it lacks appropriate characteristics, and second, there is variability in the results. This study bridges the gaps and attempts to advance our understanding of training transfer grounded in the theoretical framework by focusing on learner characteristics, instructional design and work environment in training transfer, which predictor variables can improve training transfer. This study also contributes to the current training transfer literature by proposing a combination of factors that provide a theoretical foundation for developing a solid training transfer theory.

Rapid construction method of equipment model for discrete manufacturing digital twin workshop system

A large-scale manufacturing workshop includes a wide variety and a large amount of equipment. When equipment is mapped as a digital twin (DT) model, the DT model has complex and implicit or non-hierarchical relationships, which makes the development of a DT workshop system (DTWS) for a manufacturing plant challenging. To address this problem, this paper proposes a rapid construction method of equipment model (RCMEM) for a discrete manufacturing DT workshop system, which can meet the requirements of complex manufacturing business scenarios, improve the efficiency and quality of the DT model construction at the equipment level, and form an efficient equipment model construction method. First, a DT object (DTO), which represents a basic unit of the DT model, is defined. The DTO is used to derive the DT model at the equipment level. The DTO collects and wraps generalization-capable functions from equipment into components, and geometric, functional, and communicative descriptions are combined into a single model. The DT model can increase the scalability, reusability, and modeling quality by reusing the DTO capabilities. Further, a general construction process of the DTO model of multi-axis computer numerical control (CNC) machines is presented. This process standardizes the common capabilities of the equipment models and minimizes the construction time of machines’ DT models. Furthermore, a rapid mounting and communication configuration mechanism (RMCCM) is proposed. This mechanism enables fast DTO network communication and improves interoperability in a multi-source data environment. This paper also proposes a DTWorks Software development kit, which can help developers to build digital factory standalone applications. The RCMEM is implemented into the DTWorks. Finally, a real DTWS case is used to examine the differences in equipment model building before and after the application of the RCMEM. The results demonstrate the good effectiveness of the RCMEM in complex business settings.

Ecommerce Website

Abstract: E-commerce could be a boom within the modern business, Ecommerce means electronic commerce. E-commerce involves buying and selling of products and services, or the transmitting of funds or data, over an system, predominantly the net, E-commerce could be a paradigm shift influencing both marketers and also the customers. Rather, e-commerce is quite just differently to spice up the prevailing business practices. It’s leading to a whole change in the traditional way of doing business. This significant change in business model is witnessing an amazing growth round the globe and India isn't an exception. A large internet penetration has added to growth of E-commerce and more particularly start-ups are increasingly using this selection as a differentiating business model. Moreover, E-Commerce has significant influences on the environment. Although the model is very employed in current business scenario but the choice has not been explored at its fullest. The present research and analyses had been undertaken to explain the condition of E-Commerce websites, analyze the trends of E-Commerce. Keywords: Ecommerce, HTML, Django, CSS, Javascript.

Research and Implementation of Distributed Computing Management System for College Students' Sports Health Based on Integrated Regional Collaborative Medical Care.

This paper constructs and applies a university student sports health management system through the theory of integrated regional collaborative medical care and distributed computing technology. Firstly, it analyzes the current situation and problems of cross-regional medical care, the root causes, and the corresponding business scenarios, reflecting the development trend of cross-regional medical care, in the light of the current practical needs of cross-regional medical care. In response to the strong demand for cross-regional medical care, this paper gives the overall design of the distributed computing system, for the deployment and architecture of the cross-regional platform; the registration of cross-regional patients, regional platforms, and health events and documents; and data exchange, service integration, and process integration, etc. The corresponding design is given. The research was conducted on several medical institutions to refine the functional requirements for the construction of the regional collaborative medical platform, and the requirements were analyzed to present the research results of the collaborative medical project. Based on this, requirements were made for the preparation of the project construction data center and medical institutions, and the remote consultation and two-way referral modules of the distributed collaborative medical platform were designed, which are processed and analyzed through a system composed of multiple servers. The results are returned to the user, and the design results were tested for functionality, compatibility, security, and other usability tests. The necessity and feasibility of the college physical health test data platform were analyzed. Students have various needs for physical test data management, the necessity of designing the college physical health test data platform, and the feasibility of the college physical health test data platform in terms of technical means, theoretical basis, and social environment.

Coastal and mangrove economic valuation associated fisheries and problems in Kwale County, Kenya

Abstract. Ahmed HA, Mwaura F, Thenya T, Kairo JG. 2022. Coastal and mangrove economic valuation associated fisheries and problems in Kwale County, Kenya. Indo Pac J Ocean Life 6: 17-27. The coastal fisheries in Kenya are essential to the livelihoods of the coastal communities. They provide employment, income, and food and support other auxiliary industries. Despite the socio-economic importance of coastal fisheries, various anthropogenic and climate change impact threatened their existence. Fish habitats, including mangroves, coral reefs, and seagrasses, are threatened by human activities such as aquaculture, mangrove extraction, unplanned expansion of coastal cities, and marine pollution. Usually, coastal fisheries are also neglected in key policy-making agendas. That is attributed to inadequate information and a lack of data on the socio-economic contribution of coastal communities engaged in fisheries. This study aimed to estimate the economic value to provide crucial information for policy making of mangrove ecosystem-based coastal fisheries in Kwale County. The study also attempted to establish the coastal fishery production trend for the past decade, to estimate the economic value of mangrove ecosystems to fishery production, and the future of coastal fisheries projecting based on Climate Compatible Development (CCD) and Business As Usual (BAU) scenarios. Combining the primary data from interviews with 242 respondents with secondary data, including a decade of fish catch data, were analyzed, which exhibited a continuous increase from 1,908 tonnes in 2004 to 2,450 tonnes in 2013 coastal fisheries production. The coastal fisheries value was estimated to be Ksh.182 million (US$ 2.2) annually after deducting all fishing-related costs in 2013. This study also estimated that mangrove ecosystems could support the production of 160kg/ha/year, comprable to Ksh.11,610/ha/year (US$ 198/ha/year). Moreover, the estimated values could be much higher than the calculated ones because a considerable amount of fish caught is unrecorded. The future projections reveal that the scenario of Business As Usual (BAU) is not sustainable. Hence, the study demands a shift to the scenario of Climate Compatible Development (CCD), which incorporates mitigation measures, climate change adaptation, and investment in infrastructure. The study recommends reviewing the existing fishery policies regarding the unique characteristics of coastal fisheries to ensure sustainable exploitation and address the challenges. The research also recommends further economic studies on the coastal fisheries value chain.

Construction of Enterprise Financial Early Warning Model Based on Intelligent Mathematical Model

In order to improve the ability of enterprises to cope with financial risks, this paper analyzes the financial early warning of enterprises combined with intelligent mathematical models and builds an intelligent financial early warning model to assist in analyzing the financial status of enterprises. Moreover, this paper combines the existing information technology and expenditure business scenarios to construct an intelligent early warning frame for enterprise financial control based on an intelligent mathematical model. In addition, this paper combines the K-means clustering algorithm to design a financial approval process integrity control early warning method to warn the integrity of the financial approval process. Finally, this paper presents the early warning of financial standard compliance control based on the C4.5 decision tree algorithm. The experimental research shows that the enterprise financial early warning model based on the intelligent mathematical model proposed in this paper can play an important role in the enterprise financial management and effectively improve the ability of the enterprise to cope with financial risks.

Methodology for Developing an Adaptive Business Plan

Any firm has to adapt to a changing business environment to operate successfully. In the 21st century, they have to work actively on adaptive business plans and have some long-term plans, as the degree of uncertainty in the business environment increases steadily while the adaptive competencies help the firm to develop a competitive advantage over the environment. We can talk a lot to describe the business landscape of the last decade, however the only thing that can be said with certainty is that during this period there have never been certain, obvious radical changes. As business cycles and processes in the world become more rapidly accelerated, we can more strongly criticize the traditional strategic planning process, which offers small alternatives of business scenarios and focuses less on radical changes in market demand. Against this background, we want to focus on the importance of developing an adaptive business plan and discuss its development methodology for firms. Keywords: Adaptation, Business Plan, Adaptive Management, Adaptive Measures Complex, Competitive Advantage.

Systems Dynamics Model of SDGs: A Case Study of Iran

This paper investigates on the implementation Sustainable Development Goals (SDGs) in Iran. It generates a systems dynamics model for exploring possibilities for achieving four SDGs: SDG-1 (eradicating poverty), SDG-8 (economic growth and decent work), SDG-12 (sustainable production and consumption), and SDG-13 (climate action) in Iran. The model is used to generate four possible stories about the implementation of measures to achieve these SDGs in the future of the Iranian economy from 2020 to 2050: 1) the Scenario of Business as Usual continues current trends and projects them into the future, 2) the Scenario of Inclusive Growth is designed to simulate more income equality and faster economic growth, 3) the Scenario of a Steady State introduces measures to improve social, and environmental aspects while having zero economic growth, and 4) the Scenario of Well-being for People and Planet is designed to improve socio-economic and environmental aspects of the Iranian economy to achieve the four SDGs in Iran. The performance of the Iranian economy for progressing towards the SDGs is monitored through four SDG indexes which are measured based on the arithmetic mean of selected indicators for each SDG, and a Combined Index of SDGs which is measured based on the arithmetic mean of the four SDGs indexes. The results of the simulations of the SDGs model of Iran shows that the transformational scenarios ( Steady State , and Well-being for People and Planet ) provide better pathways in comparison to conventional scenarios ( Business as Usual and Inclusive Growth ) for achieving the SDGs. Moreover, this study find that transformational policy changes and extraordinary efforts are required for progress in achieving SDGs in Iran.

Making distributed edge machine learning for resource-constrained communities and environments smarter: contexts and challenges

The maturity of machine learning (ML) development and the decreasing deployment cost of capable edge devices have proliferated the development and deployment of edge ML solutions for critical IoT-based business applications. The combination of edge computing and ML not only addresses the development cost barrier, but also solves the obstacles due to the lack of powerful cloud data centers. However, not only the edge ML research and development is still at an early stage and requires substantial skills normally missed in resource-constrained communities, but also various infrastructure constraints w.r.t. network reliability and computing power, and business contexts from the resource-constrained environments require different considerations to make edge ML applications context aware through smart and intelligent runtime strategies. In this paper, we analyze representative real-world business scenarios for edge ML solutions and their contexts in resource-constrained communities and environments. We identify and map the key distinguished contexts of distributed edge ML and discuss the impacts of these contexts on data and software components and deployment models. Finally, we present key research areas, how we should approach them, and possible tooling for making edge machine learning solutions smarter in resource-constrained communities and environments.

Surviving disruption: nature inspired solutions

PurposeDecision-makers in companies increasingly face unprecedented natural disasters. When business continuity is at risk, managers need a framework to imminently react.Design/methodology/approachA literature review and analysis of survival responses in nature and business case examples of company responses to the Covid-19 pandemic was the approach used.FindingsThere are direct parallels between the physiological stress response when a living individual perceives a threat to its survival, and the immediate reactions that occur when companies are faced with a disruptive event.Practical implicationsThis article is meant to be used by decision-makers in companies to better react to disruptive events.Originality/valueWhile nature-inspired methods have inspired inventions and algorithms, Hans Selye's general adaptation theory has not been used in parallel with business scenarios. We correlate fundamental organism survival mechanisms with a risk response framework to improve the probability of business survival during external threats.

Impact of COVID 19 on Small and Medium Enterprises

Purpose: The purpose of the study is to explore the SME business scenario in COVID 19 pandemic and to examine and discuss the effect of COVID 19 on small and medium enterprises. Design/Methodology/Approach: This study is based on a literature review of COVID-19 pandemic effect on small and medium firms. The researchers have collected secondary data from various sources like Research papers, websites, Reports, and newspapers. Findings: The study investigated that COVID 19 pandemic has severely impacted SMEs around the world. The lockdown has disrupted the supply chain and manufacturing of products, many jobs are at stake and a considerable amount of SMEs could not continue their businesses and unfortunately, they have closed the businesses. Governments around the world are trying to save the SME sector by formulating various schemes and policies.

Analysis of influencing factors on digital platform and its impact on buyers

In the context of post covid-19 dynamic markets, focus on Consumers to attain their attention becomes always prime objective for the sellers. From the available options, digital platforms where sellers exhibit the product features, promotional features, labellings, taggings of the products are become more increasing there by drawing their attention. The current paper analyzed based on the research data of the followers and leads generated on the digital platform representing capital goods in current business scenario where the challenges and competitiveness are coexisting. Capital goods include buildings, machinery, equipment, vehicles, and tools. Capital goods are not finished goods instead part of a system, but they are used to make finished goods or process systems. These are physical assets that a company uses in the different processes to produce products and provide services that consumers will later use. Inorder to improve in sales leads generation increasing the visibility through various factors on digital platforms been discussed and from the data acquired and thus proving the tile.

Data security mechanism of hyperledger fabric and its application in academic documents verification system

Blockchain technology ensures that data is tamper-proof, traceable, and trustworthy. This article introduces a well-known blockchain technology implementation—Hyperledger Fabric. The basic framework and privacy protection mechanisms of Hyperledger Fabric such as certificate authority, channel, Private Data Collection, etc. are described. As an example, a specific business scenario of an academic documents verification system m is figured out. And accordingly, some design details about how to apply these privacy protection mechanisms are described. The information of each enterprise in the blockchain needs to be shared, in this process, the privacy of ADVs needs to be protected, and we need an algorithm to protect privacy. Data sharing is not implemented in the traditional academic documents verification system. Therefore, the privacy protection requirements are different from those in the academic documents verification system based on blockchain. Therefore, the local database should also establish a corresponding hash value of the private transaction data and implement mapping with the private database on the chain to achieve traceability based on the same hash value.