Template-Type: ReDIF-Article 1.0 Author-Name: Srishti Maheshwari Author-X-Name-First: Srishti Author-X-Name-Last: Maheshwari Author-Name: Shubhangi Aggarwal Author-X-Name-First: Shubhangi Author-X-Name-Last: Aggarwal Author-Name: Rishabh Kaushal Author-X-Name-First: Rishabh Author-X-Name-Last: Kaushal Title: A novel SMS spam dataset and bi-directional transformer based short-text representations for SMS spam detection Abstract: Short message service (SMS) is a form of exchanging short messages over mobile phones without the internet. Unfortunately, the SMS service's popularity is exploited to send irrelevant and malicious messages to entrap users into scams and frauds. In this work, we investigate the performance of state-of-the-art bi-directional encoder representations from transformers for short-text messages in SMS data. For evaluation, we curate a novel augmented SMS spam dataset by extending a classical SMS spam dataset to further categorise spam SMS messages into four fine-grained categories, namely, indecent, malicious, promotional, and updates. We perform experiments on the standard benchmark SMS dataset of spam and non-spam and on our curated multi-class SMS spam dataset. We find that BERT based short-text representations outperform the baseline traditional approach of using handcrafted text-based features by 15%-30% for different machine learning algorithms in terms of accuracy on multi-class SMS spam dataset. Journal: Int. J. of Information and Decision Sciences Pages: 341-359 Issue: 4 Volume: 16 Year: 2024 Keywords: spam classification; machine learning; word embedding; representation learning; short message service; SMS. File-URL: http://www.inderscience.com/link.php?id=142636 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:4:p:341-359 Template-Type: ReDIF-Article 1.0 Author-Name: Muhammad Ihsan Author-X-Name-First: Muhammad Author-X-Name-Last: Ihsan Author-Name: Muhammad Saeed Author-X-Name-First: Muhammad Author-X-Name-Last: Saeed Author-Name: Atiqe Ur Rahman Author-X-Name-First: Atiqe Ur Author-X-Name-Last: Rahman Title: Multi-attribute decision-making application based on Pythagorean fuzzy soft expert set Abstract: The Pythagorean fuzzy soft expert set (<i>ƤƑЅƐ</i>-set) is a parameterised family and one of the appropriate extensions of the Pythagorean fuzzy sets. It is also a generalisation of intuitionistic fuzzy soft expert set, used to accurately assess deficiencies, uncertainties, and anxiety in evaluation. Its main advantage over the existing models is that the Pythagorean fuzzy soft expert set is considered a parametric tool. The <i>ƤƑЅƐ</i>-set can accommodate more uncertainty comparative to the intuitionistic fuzzy soft expert set, this is the most important strategy to explain fuzzy information in the decision-making process. The main objective of the present research is to establish the new structure of <i>ƤƑЅƐ</i>-set along with its corresponding fundamental properties in a Pythagorean fuzzy soft expert environment. In this article, we introduce Pythagorean fuzzy soft expert set and discuss its desirable characteristics (i.e., subset, not set and equal set), results (i.e., commutative, associative, distributive and De Morgan's laws) and set-theoretic operations (i.e., complement, union intersection AND and OR) are explained. An algorithm is proposed to solve decision-making problem. A comparative analysis with the advantages, effectiveness, flexibility, and numerous existing studies demonstrates the effectiveness of this model. Journal: Int. J. of Information and Decision Sciences Pages: 383-408 Issue: 4 Volume: 16 Year: 2024 Keywords: soft expert set; Pythagorean fuzzy soft set; Pythagorean fuzzy soft expert set; PFSE-set. File-URL: http://www.inderscience.com/link.php?id=142637 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:4:p:383-408 Template-Type: ReDIF-Article 1.0 Author-Name: Atieh Namazi Author-X-Name-First: Atieh Author-X-Name-Last: Namazi Author-Name: Mohammad Khodabakhshi Author-X-Name-First: Mohammad Author-X-Name-Last: Khodabakhshi Author-Name: Vahid Reza Salamat Author-X-Name-First: Vahid Reza Author-X-Name-Last: Salamat Title: A game theoretic approach on the investment in economic sectors by multiplier analysis: case study of Iran's economy Abstract: There is a debate on how the amount of capital should be invested in economic sectors to achieve the most prosperity in the economy. According to the balanced growth theory, some economists believe that large investment in different economic sectors increases productivity and the production size. However, other economists cling to the belief that limiting investment in key economic sectors results in increasing production and accordingly household income will increase by dispersion of production through the economy. In this article, the game theory approach is utilised by using multiplier analysis and the matrix derived from the input-output table. This method is the middle ground between the balanced and unbalanced growth theories and benefits from them. The results obtained from applying the new approach in the economy of Iran indicate that it is more profitable to invest in different economic sectors; however, the investment should be in accordance with the contribution of the economic sectors in the production process, each of which is in accord with the balanced and unbalanced growth theories, respectively. In conclusion, applying the game theory approach in the economy of Iran increases the scale of economic production and prosperity. Journal: Int. J. of Information and Decision Sciences Pages: 440-453 Issue: 4 Volume: 16 Year: 2024 Keywords: game theory; multi-criteria analysis; data envelopment analysis; input-output analysis. File-URL: http://www.inderscience.com/link.php?id=142638 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:4:p:440-453 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Hossein Azadi Author-X-Name-First: Mohammad Hossein Author-X-Name-Last: Azadi Author-Name: Mohammad Hakkak Author-X-Name-First: Mohammad Author-X-Name-Last: Hakkak Author-Name: Reza Sepahvand Author-X-Name-First: Reza Author-X-Name-Last: Sepahvand Author-Name: Seyed Najmodin Mousavi Author-X-Name-First: Seyed Najmodin Author-X-Name-Last: Mousavi Title: The importance-performance analysis of lean human resource management themes Abstract: Applying lean management to human resources (HR) talks about a technique that makes different organisation departments, particularly the human resources management (HRM), adhere to a set of executive policies and processes. This descriptive research of applied type was conducted on a statistical population including 23 senior managers working at the Social Security Organization (SSO) in Fars Province, Iran. In the qualitative phase of the study, semi-structured interviews were employed to collect the data, whose validity and reliability were endorsed using content validity ratio (CVR) and Cohen's kappa coefficient (κ), respectively. To analyse the qualitative findings, thematic analysis was also exercised. Upon examining the existing literature and the expert opinions, seven global themes, as well as 27 and 85 organising and basic themes were respectively identified. In the quantitative phase, a questionnaire was administered to collect the data. Afterwards, the themes obtained were investigated using the importance-performance analysis (IPA). Journal: Int. J. of Information and Decision Sciences Pages: 360-382 Issue: 4 Volume: 16 Year: 2024 Keywords: human resource management; HRM; importance-performance analysis; IPA; fuzzy numbers; lean human resources; thematic analysis. File-URL: http://www.inderscience.com/link.php?id=142639 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:4:p:360-382 Template-Type: ReDIF-Article 1.0 Author-Name: Lely Herlina Author-X-Name-First: Lely Author-X-Name-Last: Herlina Author-Name: Machfud Author-X-Name-First: Author-X-Name-Last: Machfud Author-Name: Elisa Anggraeni Author-X-Name-First: Elisa Author-X-Name-Last: Anggraeni Author-Name: Sukardi Author-X-Name-First: Author-X-Name-Last: Sukardi Title: Designing a decision support system for integrated production and distribution planning in shrimp agro-industry Abstract: The integration of production and distribution planning is essential for the efficiency and responsiveness of the shrimp agro-industry. Due to the large number of actors involved in the supply chain and intense competition from similar industries, integration is needed. Besides, uncertainties in the supply of perishable raw materials, annual growth and harvest, various sizes and yields, and voluminous are challenges for the shrimp agro-industry. To overcome this, the integration production and distribution planning needed a decision support system (DSS). This study aims to develop a prototype of a decision support system that integrates production and distribution planning in a shrimp agro-industry. To test the designed system using a multi-objective evolutionary algorithm (MOEA) framework. DSS-shrimp can provide a validated mechanism for decision-making in an integrated production-distribution planning in the shrimp agro-industry. Journal: Int. J. of Information and Decision Sciences Pages: 191-213 Issue: 2 Volume: 16 Year: 2024 Keywords: decision support system; DSS; production planning; distribution; supply chain; agro-industry; multi-objective evolutionary algorithm; MOEA; integrated; prototype. File-URL: http://www.inderscience.com/link.php?id=139824 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:191-213 Template-Type: ReDIF-Article 1.0 Author-Name: Zhe Chyuan Yeap Author-X-Name-First: Zhe Chyuan Author-X-Name-Last: Yeap Author-Name: Pantea Keikhosrokiani Author-X-Name-First: Pantea Author-X-Name-Last: Keikhosrokiani Author-Name: Moussa Pourya Asl Author-X-Name-First: Moussa Pourya Author-X-Name-Last: Asl Title: Social media and decision making: a data science lifecycle for opinion mining of public reactions to the 2020 International Booker Prize in Twitter Abstract: The emergence of social media platforms has altered patterns of interaction between individuals and decision-makers. To explore the impact of such changes, this study conducts an opinion mining of public reactions in Twitter to the 2020 International Booker Prize shortlist. Over 13,000 tweets were collected and analysed to examine whether public's emotions and responses to a list of nominees are akin to or influence the judges' decisions about the winning novelist. A data science lifecycle for sentiment analysis and topic modelling is proposed to classify tweet sentiments and identify the dominant topics in relation to the six shortlisted literary works both before and after the announcement of the winner. The findings show a marked discrepancy between readers' preference and the judges' decision as the prize was granted to one of the least heeded nominees. This difference reinforces the suspicion that the literary prizes are filtered through judges' personal views. The proposed digital model in this study can assist critics, book club judges, literary prize-givers, and publishing industries in better decision making. Journal: Int. J. of Information and Decision Sciences Pages: 409-439 Issue: 4 Volume: 16 Year: 2024 Keywords: decision making; opinion mining; natural language processing; NLP; sentiment analysis; topic modelling; International Booker Prize. File-URL: http://www.inderscience.com/link.php?id=142640 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:4:p:409-439 Template-Type: ReDIF-Article 1.0 Author-Name: Theodore Tarnanidis Author-X-Name-First: Theodore Author-X-Name-Last: Tarnanidis Author-Name: Jason Papathanasiou Author-X-Name-First: Jason Author-X-Name-Last: Papathanasiou Author-Name: Kofi Osei-Frimpong Author-X-Name-First: Kofi Author-X-Name-Last: Osei-Frimpong Author-Name: Nana Owusu-Frimpong Author-X-Name-First: Nana Author-X-Name-Last: Owusu-Frimpong Title: How young consumers are influenced by the valence of positive and negative frames: a cross-cultural perspective Abstract: This study contributes to the examination of the literatures on framing effects between two diverse contexts, i.e., Greece and Ghana. The first one has a strong democratic culture over the last 2.500 years, whereas the other is characterised by long periods of military rule. To that extent, data was collected from 590 young consumers. The results suggest that in the attribute framing examinations, gain-framed messages make people to focus on the positive outcomes, whereas loss-framed messages have negative evaluations. In the goal framing case, the majority of the subjects from both countries preferred the positive condition. And when decisions involve a risky option, Greeks in the positively framed condition were split between risk avoid and risk seeking behaviour, whereas Ghanaians have only a risk-seeking behaviour. In contrast, in the negatively framed condition all study subjects showed a risk seeking attitude. The findings provide unique technical insights into the consumer framing arena. Journal: Int. J. of Information and Decision Sciences Pages: 109-133 Issue: 2 Volume: 16 Year: 2024 Keywords: decision framing; framing effects; cognition; prospect theory; Greece; Ghana. File-URL: http://www.inderscience.com/link.php?id=139825 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:109-133 Template-Type: ReDIF-Article 1.0 Author-Name: Muhammad Asrol Author-X-Name-First: Muhammad Author-X-Name-Last: Asrol Author-Name: M. Marimin Author-X-Name-First: M. Author-X-Name-Last: Marimin Author-Name: M. Machfud Author-X-Name-First: M. Author-X-Name-Last: Machfud Author-Name: Moh. Yani Author-X-Name-First: Moh. Author-X-Name-Last: Yani Title: An intelligent decision support system modelling for improving agroindustry's supply chain performance: a case study Abstract: Decision-making has an important role to improve agroindustry's business process performance. This paper proposed an intelligent decision support system (IDSS) which was organised by four main performance models to improve agroindustry's competitiveness. Supply chain performance modelling was organised by using supply chain operation reference (SCOR) framework, agroindustry's risks assessment by using fuzzy house of risk, green productivity evaluation by using green productivity index (GPI) and fuzzy inference system (FIS) while agroindustry's business promising and feasibility assessment was modelled with FIS. The overall supply chain performance was developed to realise the supply chain performance. The proposed IDSS was validated at a sugarcane agroindustry and simulated the performance. The overall supply chain performance validations showed that sugarcane agroindustry's performance - as a case study -was moderate. For further research, this paper requires experienced expert verification to formulate the supply chain performance improvement strategy and verify the IDSS model to be implemented for the real world. Journal: Int. J. of Information and Decision Sciences Pages: 134-168 Issue: 2 Volume: 16 Year: 2024 Keywords: agro-industry; fuzzy system; green productivity; intelligent decision support system; IDSS; risk management; supply chain; supply chain operation reference; SCOR; green productivity index; GPI; fuzzy inference system; FIS. File-URL: http://www.inderscience.com/link.php?id=139826 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:134-168 Template-Type: ReDIF-Article 1.0 Author-Name: Rohit Kenge Author-X-Name-First: Rohit Author-X-Name-Last: Kenge Author-Name: Zafar Khan Author-X-Name-First: Zafar Author-X-Name-Last: Khan Title: A case study to prepare the framework solution for operational excellence during the recession at manufacturing industry Abstract: Since December 2019, the world is facing COVID-19 pandemic and its impact on the economy. As the product demand is shrinking, the product supply with the pre-installed capacities is facing major issues like job cuts, high unsold material inventory, and the running of companies at lower capacities. To answer these operational issues, we prepared the research hypothesis framework integrating the 12 operational excellence factors into an operational excellence model consisting of people, process and flow approach. We evaluated this hypothesis through a set of 36 questionnaires for a survey based on the Likert scale and received 402 complete responses. We performed the analysis of survey response data by testing the reliability, correlation, validity, and structural equation modelling and found out that organisational performance has a significant positive impact on our proposed operational excellence model. Also, organisational performance has a significant positive impact on our proposed operational excellence model. Journal: Int. J. of Information and Decision Sciences Pages: 214-232 Issue: 2 Volume: 16 Year: 2024 Keywords: operational excellence; recession; organisational performance; COVID-19; demand-supply cycle. File-URL: http://www.inderscience.com/link.php?id=139827 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:214-232 Template-Type: ReDIF-Article 1.0 Author-Name: Brajesh Mishra Author-X-Name-First: Brajesh Author-X-Name-Last: Mishra Author-Name: Fateh Bahadur Singh Author-X-Name-First: Fateh Bahadur Author-X-Name-Last: Singh Title: Estimating regulatory governance gaps for adoption of augmented reality in automobile sector: the application of analytical hierarchy approach Abstract: This study aims to estimate regulatory gaps that AR applications may encounter in the automobile sector. The theoretical framework of this study is inspired by regulatory commons dynamics approach. The document analysis and thematic analysis of semi-structure interview transcript helped propose an estimation framework of regulatory gaps in the context of AR adoption in Indian automobile sector. Next, the importance of various regulatory gaps domains and sub-domains have been assessed using fuzzy analytical hierarchy process technique. The automobile market regulatory gaps emerged as the most important regulatory gap domains, while the violation liability, market distortion, smart road infrastructure, customer interest, and safety have been globally ranked as the top five important regulatory gap sub-domains. Policymakers and regulators face a big challenge to match market dynamics created by rapidly advancing technologies. Market regulatory gaps and technical regulatory gaps need to be addressed separately for clarity and focus. Journal: Int. J. of Information and Decision Sciences Pages: 169-190 Issue: 2 Volume: 16 Year: 2024 Keywords: multiple criteria analysis; regulatory gaps; augmented reality; Indian automobile sector; fuzzy AHP; smart road infrastructure. File-URL: http://www.inderscience.com/link.php?id=139831 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:169-190 Template-Type: ReDIF-Article 1.0 Author-Name: R.P. Tripathi Author-X-Name-First: R.P. Author-X-Name-Last: Tripathi Title: EOQ model for time dependent demand with deterioration, inflation, shortages and trade credits Abstract: The inflation acts an important role for each area of life in the world. Inflation varies rapidly for high tech commodities with passing over time. This study develops an EOQ model with time sensitive demand rate for deteriorating products and shortages with inflation over a predetermined planning horizon. Mathematical formulations are prepared under two cases: 1) time for positive inventory (<i>T</i><SUB align="right"><SMALL>1</SMALL></SUB>) is greater than credit period <i>M</i>; 2) <i>T</i><SUB align="right"><SMALL>1</SMALL></SUB> is less than or equal to credit period <i>M</i>, to gain optimal number of replenishment and cycle time. An algorithm is presented to find the most favourable cycle time so that total annual relevant profit is maximised. We then demonstrate the total profit is concave with respect to number of replenishments. Numerical examples are offered to display the model. Sensitivity investigation for variation of a number of key parameters is also discussed. Mathematica 7.0 software is used to calculate numerical results and optimality conditions. Journal: Int. J. of Information and Decision Sciences Pages: 73-89 Issue: 1 Volume: 16 Year: 2024 Keywords: cash flow; inflation; non-increasing demand; credit period; shortages. File-URL: http://www.inderscience.com/link.php?id=136278 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:1:p:73-89 Template-Type: ReDIF-Article 1.0 Author-Name: Luciano Ferreira da Silva Author-X-Name-First: Luciano Ferreira da Author-X-Name-Last: Silva Author-Name: Paulo Sergio Gonçalves de Oliveira Author-X-Name-First: Paulo Sergio Gonçalves de Author-X-Name-Last: Oliveira Author-Name: Gustavo Grander Author-X-Name-First: Gustavo Author-X-Name-Last: Grander Author-Name: Renato Penha Author-X-Name-First: Renato Author-X-Name-Last: Penha Author-Name: Flavio Santino Bizarrias Author-X-Name-First: Flavio Santino Author-X-Name-Last: Bizarrias Title: Soft skills fuzzy TOPSIS ranked multi-criteria to select project manager Abstract: This study aims to use fuzzy logic to select a project manager based on soft skills. In the first phase, a focus group interview was applied to establish the weights according to the soft skills list selected. In the second phase, the fuzzy TOPSIS logic was applied. According to the concept of the fuzzy TOPSIS, a closeness coefficient is defined to determine the ranking order of all alternatives. The results allowed the construction of the framework here called fuzzy TOPSIS ranked multi-criteria for selecting the best candidate according to the profile and criteria adopted. The contribution of this study is to allow the attribution of values to soft skills that, in essence, are subjectivity. This framework is friendly, the investment required is low, and it is adaptable to different contexts. Journal: Int. J. of Information and Decision Sciences Pages: 19-45 Issue: 1 Volume: 16 Year: 2024 Keywords: fuzzy TOPSIS; multi-criteria decision; project manager selection; soft skill; human resources; competencies; competence; people management; project manager. File-URL: http://www.inderscience.com/link.php?id=136280 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:1:p:19-45 Template-Type: ReDIF-Article 1.0 Author-Name: M.W.R. Nuwanka Author-X-Name-First: M.W.R. Author-X-Name-Last: Nuwanka Author-Name: W.K.N.C. Withanage Author-X-Name-First: W.K.N.C. Author-X-Name-Last: Withanage Title: A GIS-based framework for flood hazard vulnerability evaluation in Thudawa area, Sri Lanka Abstract: The objectives of our research were identifying and classifying flood risk areas into different classes in Thudawa area, Sri Lanka, and developing a geographical information system (GIS) model to identify flood vulnerability areas accurately in Thudawa area. It was expected to propose preventive guidelines of flood hazard vulnerability using geo-informatics. The methodological procedure is extremely important in this type of research thus, the spatial multi-criteria decision analysis (MCDA) procedure was used. For this research, analytical hierarchy process (AHP) was used for the criterion weighting. AHP calculations run upon the results of experts' judgment as proposed by the Satty incorporating pair-wise comparison method. The results of this study attempt to analyse the existing flash flood risk levels using the GIS-based multi-criteria analysis technique which allowed ranking of risk areas since it is important in the decision-making process to mitigate the flood risk in the study area. Journal: Int. J. of Information and Decision Sciences Pages: 90-108 Issue: 1 Volume: 16 Year: 2024 Keywords: analytical hierarchy process; AHP; flood hazard; geographical information system; GIS; spatial multi-criteria decision analysis; MCDA; modelling; Sri Lanka. File-URL: http://www.inderscience.com/link.php?id=136281 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:1:p:90-108 Template-Type: ReDIF-Article 1.0 Author-Name: Bruno Moura Author-X-Name-First: Bruno Author-X-Name-Last: Moura Author-Name: Ivo Santos Author-X-Name-First: Ivo Author-X-Name-Last: Santos Author-Name: Nelson Barros Author-X-Name-First: Nelson Author-X-Name-Last: Barros Author-Name: Fernando Luis Almeida Author-X-Name-First: Fernando Luis Author-X-Name-Last: Almeida Title: D4SP - decision support system based on the use of the AHP method for science park selection Abstract: The literature reveals that science parks offer numerous benefits and support services to the activity of a technological startup. However, the decision of choosing the best science park for the startup tends to be an informal process, technically not very rigorous and planning, arising essentially by affinities with the research centre and university. In this study, a decision support system is presented to support entrepreneurs in the process of selecting a science park for the implementation of their startup. The AHP method is used to compare the importance of the criteria for selecting a science park, which includes factors such as location, activity sector, infrastructure, cost, and size. The findings reveal that the use of this decision support system helps entrepreneurs to find a science park that is suitable for the needs of their startup and allows them to comparatively identify the most relevant criteria when choosing a science park. Journal: Int. J. of Information and Decision Sciences Pages: 1-18 Issue: 1 Volume: 16 Year: 2024 Keywords: entrepreneurship; decision science; analytical hierarchy process; AHP; startups; new venture; science park. File-URL: http://www.inderscience.com/link.php?id=136282 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:1:p:1-18 Template-Type: ReDIF-Article 1.0 Author-Name: Juan Bernardo Quintero Author-X-Name-First: Juan Bernardo Author-X-Name-Last: Quintero Author-Name: David Villanueva-Valdes Author-X-Name-First: David Author-X-Name-Last: Villanueva-Valdes Author-Name: Bell Manrique-Losada Author-X-Name-First: Bell Author-X-Name-Last: Manrique-Losada Title: Artificial neural networks in the development of business analytics projects Abstract: The accelerated evolution of information and communication technologies, with an ever-growing increase in their access and availability, has become the foundation for the current big data age. Business analytics (BAs) has helped different organisations leverage the large volumes of information available today. In fact, artificial neural networks (ANNs) provide deep data mining facilities to organisations for identifying patterns, predict probable future states, and fully benefit from predictions/forecasts. This article describes three ANNs application scenarios for the development of BA projects, by using network learning for: 1) executing accounting processes; 2) time series forecasts; 3) regression-based predictions. We validate scenarios by implementing an application-case using actual data, thus demonstrating the full extent of the capabilities of this technique. The main findings exhibit the expressive power of the programming languages used in data analytics, the wide range of tools/techniques available, and the impact these factors may have on the BA development projects. Journal: Int. J. of Information and Decision Sciences Pages: 46-72 Issue: 1 Volume: 16 Year: 2024 Keywords: artificial neural networks; ANNs; business analytics; data analytics; big data; deep data mining; network learning process; time series forecast; regression-based prediction; activity-based costing; supervised learning; decision making. File-URL: http://www.inderscience.com/link.php?id=136283 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:1:p:46-72 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Mirkazemi Mood Author-X-Name-First: Mohammad Mirkazemi Author-X-Name-Last: Mood Author-Name: Ali Mohaghar Author-X-Name-First: Ali Author-X-Name-Last: Mohaghar Author-Name: Yaser Nesari Author-X-Name-First: Yaser Author-X-Name-Last: Nesari Title: Designing a method to model the socio-technical systems Abstract: To capture the complexity and diversity of systems with both technical and social features, modelling methods are needed that similarly provide various tools and concepts. Study of developed methods shows that despite all of their advantages and strengths, there is a need for a method that with a holistic approach integrates perspectives, strengths and tools of the developed methods and models with different aspects of socio-technical systems. The main aim of the current study is to design a method for modelling complex socio-technical systems. To achieve this goal, it is necessary to design a method that is based on creativity and existing knowledge base. Therefore, design science research is used as a research strategy to design proposed method. For the first time, design science research in the field of operations research has been used to design a modelling method. This study also presents new tools and concepts for modelling socio-technical systems. Journal: Int. J. of Information and Decision Sciences Pages: 284-318 Issue: 3 Volume: 16 Year: 2024 Keywords: socio-technical approach; design science research; soft operations research; problem structuring methods; system thinking; meta-synthesis; modelling methods. File-URL: http://www.inderscience.com/link.php?id=140185 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:284-318 Template-Type: ReDIF-Article 1.0 Author-Name: José Ordóñez-Placencia Author-X-Name-First: José Author-X-Name-Last: Ordóñez-Placencia Author-Name: María Hallo Author-X-Name-First: María Author-X-Name-Last: Hallo Author-Name: Sergio Luján-Mora Author-X-Name-First: Sergio Author-X-Name-Last: Luján-Mora Title: A data mining model to predict the debts with risk of non-payment in tax administration Abstract: One of the main tasks in tax administration is debt management. The main goal of this function is tax due collection. Statements are processed in order to select strategies to use in the debt management process to optimise the debt collection process. This work proposes to carry out a data mining process to predict debts of taxpayers with high probability of non-payment. The data mining process identifies high-risk debts using a survival analysis on a dataset from a tax administration. Three groups of tax debtors with similar payment behaviour were identified and a success rate of up to 90% was reached in estimating the payment time of taxpayers. The concordance index (C-index) was used to determine the performance of the constructed model. The highest prediction rate reached was 90.37% corresponding to the third group. Journal: Int. J. of Information and Decision Sciences Pages: 319-339 Issue: 3 Volume: 16 Year: 2024 Keywords: data mining; debt management analysis; machine learning; taxpayer behaviour patterns; survival analysis. File-URL: http://www.inderscience.com/link.php?id=140186 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:319-339 Template-Type: ReDIF-Article 1.0 Author-Name: Fatemeh Gheitarani Author-X-Name-First: Fatemeh Author-X-Name-Last: Gheitarani Author-Name: Khaled Nawaser Author-X-Name-First: Khaled Author-X-Name-Last: Nawaser Author-Name: Haniruzila Hanifah Author-X-Name-First: Haniruzila Author-X-Name-Last: Hanifah Author-Name: Ali Vafaei-Zadeh Author-X-Name-First: Ali Author-X-Name-Last: Vafaei-Zadeh Title: Dimensions of anti-citizenship behaviours incidence in organisations: a meta-analysis Abstract: Research growth in organisational behaviour research, has increased the importance of paying attention to anti-citizenship behaviours. The current research with the aim of quantitative combination, has examined the results of research in effect of underlying factors of organisational anti-citizenship behaviours using meta-analysis method and CMA2 software and 55 articles during the time period of 2000-2020. The results showed a positive significant link between underlying factors of organisational anti-citizenship behaviours and occurrence of these behaviours and this influence was 0.389, 0.338, 0514 and 0.498 (structural, organisational, managerial, employment and professional and socio-economic and cultural factors). The level of connection found relating to each four occurrences is '68 links, 49 links, 93 links and 71 links'. Findings indicate that minute attention has been paid to organisational anti-citizenship behaviours, especially to job and professional factors in research works. Research should be conducted to control and manage these behaviours more purposefully in organisations. Journal: Int. J. of Information and Decision Sciences Pages: 233-248 Issue: 3 Volume: 16 Year: 2024 Keywords: organisational behaviours; meta-analysis; organisational factor; anti-citizenship behaviours; personal factor. File-URL: http://www.inderscience.com/link.php?id=140187 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:233-248 Template-Type: ReDIF-Article 1.0 Author-Name: Siti Wardah Author-X-Name-First: Siti Author-X-Name-Last: Wardah Author-Name: Mohammad Yani Author-X-Name-First: Mohammad Author-X-Name-Last: Yani Author-Name: Taufik Djatna Author-X-Name-First: Taufik Author-X-Name-Last: Djatna Author-Name: Marimin Marimin Author-X-Name-First: Marimin Author-X-Name-Last: Marimin Title: Hybrid of machine learning-based multiple criteria decision making and mass balance analysis in the new coconut agro-industry product development Abstract: Product innovation has become a crucial part of the sustainability of the coconut agro-industry in Indonesia, covering upstream and downstream sides. To overcome this challenge, it is necessary to create several model stages using a hybrid method that combines machine learning based on multiple criteria decision making and mass balance analysis. The research case study was conducted in Tembilahan district, Riau province, Indonesia, one of the primary coconut producers in Indonesia. The analysis results showed that potential products for domestic customers included coconut milk, coconut cooking oil, coconut chips, coconut jelly, coconut sugar, and virgin coconut oil. Furthermore, considering the experts, the most potential product to be developed was coconut sugar with a weight of 0.26. Prediction of coconut sugar demand reached 13,996,607 tons/year, requiring coconut sap as a raw material up to 97,976,249. Journal: Int. J. of Information and Decision Sciences Pages: 264-283 Issue: 3 Volume: 16 Year: 2024 Keywords: coconut agro-industry; hybrid of machine learning; mass balance analysis; multiple criteria. File-URL: http://www.inderscience.com/link.php?id=140188 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:264-283 Template-Type: ReDIF-Article 1.0 Author-Name: Gurpreet Singh Matharou Author-X-Name-First: Gurpreet Singh Author-X-Name-Last: Matharou Author-Name: Simran Kaur Author-X-Name-First: Simran Author-X-Name-Last: Kaur Title: A novel approach of psychometric interaction and principal component for analysing factors affecting e-wallet usage Abstract: The Republic of India has witnessed an enormous leap in financial transactions after a sudden demonetisation in 2016. The study represents an in-depth analysis of the factors influencing e-wallets usage post-COVID situation covering the National Capital Region. The scientifically collected data were subjected to Pearson's correlation to recognise the correlation amongst the selected e-wallets. The usage of e-wallets is observed mainly during recharge, UPI payments, and utility payments. Through psychometric response and interaction analysis, six factors were selected and examined for data distribution and stable observation using standard deviation and variance coefficient. The coefficient of variance for six factors was observed ≤ 1. The weight of the factors noted to be secured way (0.184), to take advantage of cashback (0.182), low risk of theft (0.169), fast service (0.1689), ease to use (0.156), and saves time (0.139) using principal component eigenvectors analysis. Freecharge and Tez wallets reveal a maximum 99.2% correlation. Journal: Int. J. of Information and Decision Sciences Pages: 249-263 Issue: 3 Volume: 16 Year: 2024 Keywords: wallets; correlation; payment; p-value; technology. File-URL: http://www.inderscience.com/link.php?id=140189 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:249-263