Artificial Intelligence Based Commercial Risk Management Framework for SMEs

Žigienė, Gerda; Rybakovas, Egidijus; Alzbutas, Robertas

doi:10.3390/su11164501

Cited by 43 publications

(7 citation statements)

References 57 publications

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“…In terms of the impact of Fintech sector development on SME businesses, the range of Fintech services is expanding to include not only mobile payments but crowd financing (Kim & De Moor, 2017;Serwaah, 2021), artificial intelligence solutions for more accurate SME credit assessments (Bughin et al, 2017(Bughin et al, , 2019Rybakovas & Žigienė, 2021;Taylor, 2018;Westermann, 2018;Zhang et al, 2018;Žigienė et al, 2019), the impact of platform economies (Langley & Leyshon, 2021) on financing, and more. The application of individual technologies helps SMEs to overcome the barrier of access to finance for business development, thus the potential of increasing business financial inclusion.…”

Section: Relevant Literature Reviewmentioning

confidence: 99%

Financial Innovation for Financial Inclusion: Mapping Potential Access to Finance

Rybakovas

Žigienė

2022

ECIE

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The importance of access to finance as a significant problem for business development is considered one of the measures representing the level of financial inclusion. Developing financial innovations, such as crowdfunding, mobile payments, AI-based credit scoring systems, and even blockchain technologies has an immense potential to increase financial inclusion, increase access to finance for individuals and businesses, enabling the unscored or unbanked population to become active members of financial markets. Studies have shown the positive impact of financial technology on individuals' financial inclusion and access to finance, but the development of the Fintech phenomenon does not itself imply improved access to finance for businesses. The spread and adoption of Fintech are taken as evidence of financial innovation This research aims to explore the expected interaction between financial innovation and financial inclusion in selected European countries. The data from the Global Fintech Ranking and Survey on the access to finance of enterprises (SAFE) is used in this study, examining them by comparing countries by their Fintech rankings and respective rank position obtained by measuring the importance of access to finance as a problem in business development. The analysis of 29 European countries indicates that theoretically defined expectations are met in most cases: access to finance is not an important problem for the companies from the countries that are ranked higher in the Fintech rating report. But part of the sampled countries deviates from this trend. These findings indicate that besides financial innovation other factors also may determine the financial inclusion of the companies.

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Section: Relevant Literature Reviewmentioning

confidence: 99%

Financial Innovation for Financial Inclusion: Mapping Potential Access to Finance

Rybakovas

Žigienė

2022

ECIE

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“…Technology allows entrepreneurs to make decisions about the opportunity exploitation during the COVID-19 pandemic. It makes decision making more versatile and easier to determine sooner (Ranjan 2009 ; Žigienė et al 2019 ; Samiei and Habibi, 2020 ) amid a global epidemic. In general, the exploration of opportunities is a crucial phase in the creation of an effective business in an entrepreneurial marketing process.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Technology and Entrepreneurial Marketing Decisions During COVID-19

Polas

Raju

2021

Glob J Flex Syst Manag

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The prime concern of this study is to explore how technology influences entrepreneurial marketing decisions during the world pandemic (COVID-19). The study uses a sample of 127 SMEs from Bangladesh. Data were collected by sending out questionnaires electronically and by mail. Smart PLS (SEM) 3.0 was used to analyse the data following the quantitative method. The study reveals positive and significant relationships between entrepreneurial opportunity recognition, opportunity development and opportunity exploitation with their entrepreneurial marketing decisions. It also claims that entrepreneurial passion mediates the relationship between entrepreneurial opportunity recognition and opportunity development with their entrepreneurial marketing decisions. However, entrepreneurial passion does not mediate the relationship between entrepreneurial opportunity exploitation and entrepreneurial marketing decisions. The study offers researchers a broader and more wide-ranging view of the importance of artificial intelligence in small firms. Researchers, educators and practitioners will benefit from the findings. The analyses are more complex and varied than the methodologies used in most of the limited previous research.

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“…Subsequent researches could focus on how to use the fuzzy logic tool to determine the sustainable marketing communication channel most relevant to the customers. Zigiene et al (2019) presented artificial intelligence based risk management framework for SMEs for risk prevention in SMEs as large scale external and internal data are generated. The research strongly considers the integration of artificial intelligence and machine learning to process large scale unstructured data with its attendant incompleteness and uncertainty in order to improve risk management.…”

Section: Literature Reviewmentioning

confidence: 99%

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

2021

EJBM

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The aim of this research is to apply an intelligent technique to predict optimal inventory quantity in small and medium-scale enterprise. This is in view of the fact that the conventional models such as the EOQ model use only deterministic while some decision variables are non-deterministic in nature. Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in the first hidden layer and four neurons in the second hidden layer. Two feed-forward training algorithms of quasi-newton and quick propagation were employed in the training with the results of fuzzy logic technology found in the literature as the target output. Results obtained show that the quasi-newton algorithm covaries stronger with the fuzzy logic results than the quick propagation results. The objective and subjective feelings of the inventory manager were also captured to optimise the results of the training.The study is at a framework stage and will proceed to implementation level when more datasets are collected. Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. The inclusion of nondeterministic circumstances such as emotional and objective feelings of the inventory manager to predict inventory is novel considering the fact that studies in the available intelligent inventory prediction have not employed such variables in their predictions.

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Artificial Intelligence Based Commercial Risk Management Framework for SMEs

Cited by 43 publications

References 57 publications

Financial Innovation for Financial Inclusion: Mapping Potential Access to Finance

Financial Innovation for Financial Inclusion: Mapping Potential Access to Finance

Technology and Entrepreneurial Marketing Decisions During COVID-19

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

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