Forthcoming and Online First Articles

International Journal of Applied Decision Sciences

International Journal of Applied Decision Sciences (IJADS)

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International Journal of Applied Decision Sciences (32 papers in press)

Regular Issues

  • Business case the state-of-the-art   Order a copy of this article
    by José Santos, Leandro Pereira 
    Abstract: Nowadays the business case is a well-known and applied methodology in a multiple dimensionality of projects. This dimensionality of projects, where the business case is being implement, can range from the health sector, gender equality to digital transformation due to its transversality. This paper intends to provide a comprehensive overview of the literature review of the business case in terms of academic literature, searched keywords on the internet as well on the social network by providing a wide-ranging data analysis while providing a review in some of the research outcomes. Therefore, the present paper aims to provide a critically analysing occurrence and conjunction of the different data sources in a representative sample between 1977 to 2022, understand and integrate the current state of research on business cases in an attempt to provide a clear vision of the trends and future scenario of the business case.
    Keywords: business case; dimensionality; literature review; Google Trends; social networks; Scopus; digital transformation.
    DOI: 10.1504/IJADS.2023.10046008
     
  • Treatment Process Conformance Checking of Patients (with Sepsis and Septic Shock) in Compliance with SSC and WMA using Fuzzy Miner Algorithm in Fluxicon Disco   Order a copy of this article
    by Parham Porouhan 
    Abstract: This paper emphasises on presenting a process-centric approach to provide analytical processing of medical event-logs by means of the process mining tool: Fluxicon Disco. The event log contains the treatment procedures of the septic patients along with relevant medical testing and other services since admission (to the hospital) until final discharge. The main objectives of the study are: 1) to generate visual maps for septic cases/patients; 2) to check the hospitals medical guidelines; 3) to explore and control deviations of the medical requirements; 4) to simulate and visualise the bottleneck areas; 5) to optimise the hospitals efficiency; 6) to discover who is doing what; 7) to provide groundwork for applying fuzzy miner algorithm for further and future research in the field of medical process improvement. The study found a significant amount of medical malpractice associated with violation of SSC and WMA guidelines when treating the septic cases/patients.
    Keywords: process mining; Fluxicon Disco; fuzzy miner algorithm; medical data; hospital dataset; sepsis patients; Surviving Sepsis Campaign; SSC; World Medical Association; WMA.
    DOI: 10.1504/IJADS.2023.10046196
     
  • A Multistage sustainable inventory model with backorder, fuzzy parameters and decision variable for deteriorating items with imperfect production and reliability.   Order a copy of this article
    by S. V. Singh Padiyar, Naveen Bhagat, Neha Punetha 
    Abstract: As the environment of industry becomes more competitive, management of supply chain has become essential part of the industries. In this paper, a multi-echelon inventory model for deteriorating items with imperfect production and reliability under inflationary environment has been developed. In this study, single-producer and single-retailer are considered from the integrated point of view. Practically, it is observed that deterioration rate is almost uncertain in every supply chain therefore deterioration rate is taken as triangular fuzzy number. Shortage is allowed only in retailer’s part; imperfect production process is also considered but it is not reworkable in this supply chain. The main premise of this study is to get minimum cost by developing integrated model for deteriorating items. Signed distance method is used to defuzzify the total cost function with two different demands for producer and retailer. Finally, a numerical example and sensitivity analysis are employed to illustrate the model.
    Keywords: multi echelon; reliability; inflation; deteriorating items; signed distance method.
    DOI: 10.1504/IJADS.2023.10046452
     
  • Decision Biases in the Capacity Expansion Problems with Product Importance Perceptions   Order a copy of this article
    by Giteak Roh, Seongam Moon, Kyunghwan Choi 
    Abstract: Capacity expansion is one of the vital areas of decision-making in production management and its sustainability. Most quantitative studies on capacity expansion have been focused on computing the optimal times, sizes. In this paper, we investigate the effect of substantial and nominal importance on the capacity expansion decision-making through online experiments. We provide three results for capacity expansion decision-making. The first provides both substantial and nominal importance perceptions have an effect on capacity expansion decision-making. We further provide capacity expansion experiments also show the analogical results of Schweitzer and Cachon’s (2000) study, the pull-to-centre effect regardless of high or low margins. The third provides the nominal importance effect at low margins affects capacity expansion decision-making, but not at high margins. Our study gives implications that bounded rationality also occurs in capacity expansion decisions, so it must be analysed with mathematical models to ensure more reasonable results.
    Keywords: capacity expansion; product importance; decision-making; bias heuristics; behavioural operations management; BOM.
    DOI: 10.1504/IJADS.2023.10047350
     
  • K-means analysis of construction projects in port waterfronts   Order a copy of this article
    by Iñigo L. Ansorena 
    Abstract: Choosing the best construction project on the city’s waterfront is a difficult decision since the view of the waterfront is one of the main attractions for tourism in many cities. In a competition context, it is essential for port authorities to choose the project that best meets not only the needs of the port-city but also the expectations of the citizens and visitors. The present study explained and explored the citizens’ opinion about a construction project competition. A structured and un-disguised questionnaire was developed and used to collect the primary data from 535 respondents. Conceptual model was investigated by k-means clustering method. Study delivered detailed insight on various elements used for analysis and revealed the alternatives that attracted more interest. The general framework presented in this article can help decision-makers to find the best construction projects.
    Keywords: decision making; alternatives; similarity search; dataset; port-city; cluster analysis; k-means; waterfront; emblematic projects; decision analysis.
    DOI: 10.1504/IJADS.2023.10047423
     
  • Performance measurement of Taiwan hotels with a hierarchical Network DEA With Shared Inputs   Order a copy of this article
    by Huaping Lin, Weiwei Zhu, Yu Yu, Mojtaba Ghiyasi 
    Abstract: The structure of a hotel and its operational departments (e.g., catering department and occupancy department) is appropriate in a hierarchical organisation. However, the previous DEA research only focuses on the network process of internal structures for the hotel systems. Therefore, this paper develops a hierarchical network DEA to evaluate the hotels’ operational performance with the hierarchical network production systems. Moreover, the shared inputs of hotels could be allocated vertically along the hierarchical structure. An empirical analysis using data from 70 Taiwan’s international tourist hotels in 2014 was conducted. The results show that the overall operational efficiency of 70 hotels is low, attributing to a shortage of the transformation from service capability to earning capability. Meanwhile, although all hotels allocate a large proportion of shared inputs to the catering department, the operational efficiency of the catering department is mostly lower than the occupancy department. The proposed model also can be used for the production systems which include a hierarchical network structure and some shared inputs.
    Keywords: hierarchical network DEA; hierarchical network systems; shared inputs; Taiwan’s international tourist hotels; Taiwan.
    DOI: 10.1504/IJADS.2023.10048276
     
  • Artificial Intelligence Based on MCDM for the Board Game of the Royal Game of Ur   Order a copy of this article
    by Tomas G. Roskovec, Petr Chladek, Daniel Hejplik, Stepan Mudra, Marek Sulista 
    Abstract: The Royal Game of Ur is an ancient board game with random elements and strategies. We introduce two methods of designing simple but effective artificial intelligence (AI) that performs well in this game against both human players and chosen AI available online. We present both the description of the development of AI and the performance results. The advantage and originality of the method is easy evaluation of player’s move based in a way such that simple program or human player may follow the strategy as a guideline. The multiple-criteria decision-making methods in use are the lexicographic semi-order method and the weighted sum method. The weights and ordering of criteria are set by automatic testing software based on an evolutionary algorithm for searching the optimum.
    Keywords: artificial intelligence; AI; board games; multiple-criteria decision-making; MCDM; weighted sum method; WSM; lexicographic semi-order method; LSM.
    DOI: 10.1504/IJADS.2023.10048377
     
  • An Intelligent Financial Management System for optimal resource allocation in an organization   Order a copy of this article
    by Juan Vanegas, Jose Aguilar, Elizabeth Suescun, José Alejandro Román, Alejandra Cardenas, Mateo Flórez, Laura Sanchez 
    Abstract: Today, companies require many decision-making tools to maximise their efficiency. This task can be facilitated by the possibility of developing intelligent decision-making systems based on data. In this way, the objective of this paper is to develop a tool to optimise free cash flow that assists in making decisions concerning the allocation of financial resources, so that the profitability can be improved without disproportionately increasing risk. This paper defines a smart system to study the financial performance of a company, and additionally, it prescribes changes in the approach to the allocation of financial resources that management may adopt. The smart system is based on an autonomous cycle of data analysis tasks, which consists of an optimisation process to define the financial resource allocation changes needed towards the accomplishment of the best risk-reward possible that uses a prescriptive model to evaluate the expected behaviour of the company’s future free cash flows.
    Keywords: data analytics; machine learning; financial forecasting; cash flow forecasting; financial analysis; risk asymmetry analysis.
    DOI: 10.1504/IJADS.2023.10048577
     
  • Big Data Analytical Capability and Firm Performance: Moderating effect of Analytics Capability Business Strategy Alignment   Order a copy of this article
    by Amal Sindarov, Ali Vafaei-Zadeh, Syafrizal Syafrizal, Razib Chandra Chanda 
    Abstract: This research investigates the impact of big data analytical capability (BDAC) on decision-making performance, comparative advantage, and firm performance considering the moderating effect of analytical capability business strategy alignment among manufacturing companies. To test the research framework, a survey questionnaire was distributed to Malaysian manufacturing companies. The results indicate that customer orientation, entrepreneurial orientation, and technology orientation positively and significantly affect BDAC. Besides, BDAC has a positive and significant effect on decision making performance, comparative advantage, and firm performance. The results of this study highlighted that BDAC is an important enabler of organisational performance and their competitive advantage. However, DBAC is more strongly related to competitive advantage than to firm performance.
    Keywords: big data analytics; decision making performance; firm performance; competitive advantage; technology orientation; Malaysia; big data analytical capability; BDAC.
    DOI: 10.1504/IJADS.2023.10048606
     
  • Research on financing availability of small and micro logistics enterprises in China   Order a copy of this article
    by Yubin Yang, Lili Xu, Xuejian Chu, Ruiqi Pang, Zunli Zhang 
    Abstract: This study explores the financing availability of small and micro logistics enterprises (SMLEs) in digital supply chain finance (DSCF). Drawing upon the signalling view and the logic of signalling-financing availability: this study constructs a theoretical model that affects the financing availability of SMLEs in five dimensions, including supervision behaviour, transaction credit, financial credit, policy environment, and financial environment. By applying partial least squares structural equation modelling, the study asserts that supervision behaviour, transaction credit, and financial credit all have a direct and significant positive impact on the financing availability of SMLEs. Moreover, financial credit has a mediation effect on supervision behaviour and transaction credit in the mediation model. Furthermore, the results confirm that policy and financial environments positively moderate effects. The results reveal that both supervision behaviour and transaction credit can impact financial credit, to achieve the purpose of credit enhancement, thereby improving the financing availability of SMLEs.
    Keywords: digital supply chain finance; small and micro logistics enterprises; financing availability; partial least squares structural equation modelling; signalling.
    DOI: 10.1504/IJADS.2023.10048741
     
  • Factors predicting customer satisfaction in online hotel booking using machine learning technique. Evidence from developing countries.   Order a copy of this article
    by Mehnaz Mehnaz, Jianhua Jin, Wasim Ahmad, Azhar Hussain 
    Abstract: This paper predicts and documents the determinants of customer satisfaction in online hotel booking for the foreign tourists in developing countries. The data was taken from the customer web-based reviews and comments. The study forecasts customer satisfaction by comparing logistic model with artificial neural network (ANN) in terms of prediction accuracy. In case of both datasets, i.e., training and testing, ANN outperformed the logistic regression model in terms of prediction. In other words, ANN is more robust in terms of prediction as compared to logistic regression model. Furthermore, empirical results depict that rental price, staff performance, location, services quality, and rating are the significant tools to maximise customer satisfaction. Hotel authorities in developing countries need to focus on these factors where customer feedback may play a significant role implementing the best services of hotels. These incentives will help to increase the booking incentives and ensure sufficient revenues for hotel industry of developing nations.
    Keywords: online hotel booking; customer satisfaction; location; price; service quality; artificial neural network; ANN.
    DOI: 10.1504/IJADS.2023.10049278
     
  • An integrated fuzzy multi-criteria decision-making approach for prioritizing strategies to drive the sustainable Roll-on/ Roll-off port development: A case study of Thailand   Order a copy of this article
    by Detcharat Sumrit, Ratima Jaidee 
    Abstract: This study proposes a framework for prioritizing strategies to drive sustainable Roll-on/Roll-off (RO/RO) port development by combining fuzzy multi-criteria decision-making approach The application of the proposed framework uses one of the largest RO/RO ports in Thailand as a case study First, the measuring perspectives/criteria and driving strategies for sustainable port are identified through the extensive literature review along with port development plan The fuzzy Delphi method is applied to select the suitable criteria and driving strategies for sustainable development of RO/RO port Next, the Fuzzy Decision-Making Trail and Evaluation Laboratory (Fuzzy DEMATEL) is employed to analyze the interrelationship between perspective and criteria as well as their importance weights Finally, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is utilized to prioritize the driving strategies.
    Keywords: Multi-criteria decision-making (MCDM); Fuzzy Delphi; Fuzzy DEMATEL); Fuzzy TOPSIS; Roll-on/Roll-off; Sustainability.
    DOI: 10.1504/IJADS.2023.10049358
     
  • Impact of Covid-19 on Systemic Risk for Indian Financial Institutions   Order a copy of this article
    by Subhash Karmakar, Gautam Bandyopadhyay, Dragan Pamucar, J.N. Mukhopadhyay, Sanjib Biswas 
    Abstract: This paper studies differential impact of COVID-19 on systemic risk during different phases of lockdown on the financial institutions in India. We use SRISK as a measure of systemic risk and study three categories of financial institutions viz., public sector banks (PSBs), private sector banks and non-banking financial companies (NBFCs). We use Kruskal-Wallis test for examining the difference in the SRISK parameter for the three categories of financial institutions considered in this paper and observe significant difference. We have also estimated the Spearman correlations between the Indian volatility index (VIX) and SRISK across the three categories of financial institutions. The PSBs are foremost in risk contribution compared to private banks and NBFCs but they are not affected by market volatility index as compared to their counterparts, on the other hand medium and small sized PSBs have performed well as compared to large PSBs. Based on the result it is inferred that the month of April 2020 to June 2020 (lockdown period) had the most significant increase in systemic risk.
    Keywords: systemic risk; SRISK; COVID-19; NBFC; banks; financial institutions; volatility index; VIX.
    DOI: 10.1504/IJADS.2023.10049402
     
  • FE-TAC: An Effective Document Classification Method Combining Feature Extraction and Feature Selection   Order a copy of this article
    by Kshetrimayum Nareshkumar Singh, Haobam Mamata Devi, Anjana Kakoti Mahanta, A. Dorendro 
    Abstract: An effective classification method requires the most informative and relevant set of features. In this paper, we discuss an enhanced text classification method combining feature extraction (FE) and feature selection. First, we used the FE method to extract features from text data and then apply the feature selection method to select the most relevant features out of those extracted features. During feature selection, we introduce a new measure called term affinity to the class (TAC) to estimate the degree of retaining capability of the term as a member of the particular class. TAC is computed based on the combination of normalise document frequency and summing up the occurrence frequency of the term to the specific class. Experimental results on three existing datasets BBC, Classic4, 20 Newsgroup, and our own dataset called Sangai show that the proposed method outperforms the other competent methods in terms of accuracy.
    Keywords: bag of words; BoW; document representation; term weights; text classification; word vectors.
    DOI: 10.1504/IJADS.2023.10049403
     
  • A TWO PHASE APPROACH BASED ON MULTI OBJECTIVE PROGRAMMING AND SIMULATION FOR PHYSICIAN SCHEDULING IN EMERGENCY ROOMS   Order a copy of this article
    by Ozgur Yanmaz, Ozgur Kabak 
    Abstract: Scheduling hospital staff is a complex problem because of the wide fluctuations in demand and staffing needs. Physician scheduling in an emergency room (ER) is the one that is most complex and crucial since it requires not only economic and patient perspectives but also the social needs of physicians. Thus, the working conditions and preferences of physicians should be considered in planning their schedules. This study aims to develop an approach for scheduling physicians in an ER to provide better conditions for physicians and, a qualified and reachable healthcare service to the patients. A multi-objective mathematical model is developed to ensure Pareto optimal solutions considering not only economic aspects but also social aspects including the physician preferences and balancing the workload. A Monte Carlo simulation is used to determine the best schedule among Pareto optimal solutions obtained from the mathematical model and deal with the fluctuations in demand. The approach is applied with real world data.
    Keywords: physician scheduling; emergency rooms; multiple objective programming; Monte Carlo simulation; the augmented ?-constraint.
    DOI: 10.1504/IJADS.2023.10049933
     
  • Comparative Analysis of Novel Fuzzy Multi-Criteria Decision Making Methods for Selecting Forth-Party Logistics Service Providers: A Case Study in Plastic Resin Industry.   Order a copy of this article
    by Detcharat Sumrit, Kamolchanok Jiamanukulkij 
    Abstract: This paper proposes a systematic framework to select the best 4PLs by incorporating several MCDM methods. The aim of this paper is to conduct a comparative study to examine how different MCDM methods compare when apply for 4PLs selecting problem. First, 14 criteria of 4PLs selection are identified through literature and input from industrial experts. Second, the objective weights of criteria are derived through interval Shannon’s entropy based on α-level sets. Afterward, the 4PL candidates are ranked comparatively using five novel MCDM methods reported in literature including CoCoSo, MARCOS, EDAS, MAIRCA, and CODAS. Finally, the sensitivity analysis is performed to test the robustness and reliability of the proposed framework. A case of plastic resin industry in Thailand is used to demonstrate the application of the proposed framework. The practitioners and academicians can utilise the proposed framework to select the best 4PLs.
    Keywords: multi-criterion decision making; fuzzy set theory; FST; forth-party logistics providers.
    DOI: 10.1504/IJADS.2024.10050867
     
  • Verification of neural network models for forecasting the volatility of the WIG20 index rates of return during COVID-19 pandemic   Order a copy of this article
    by Emilia Fraszka-Sobczyk, Aleksandra Zakrzewska 
    Abstract: The paper investigates the issue of the volatility of stock index returns on the Warsaw Stock Exchange (the WIG20 index returns volatility). The purposes of this review are to present an alternative neural network and to examine it to predict the stock index returns according to the historical data. Finally, these predictions got from the new neural network are compared with predictions based on a standard neural network MLP. In this article, as the measurements for the best forecasting performance of neural networks are taken common used forecast error measurements: mean error (ME), mean percentage error (MPE), mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), R (the correlation coefficient). The results show that the introduced neural network has good accuracy in measuring effectively the WIG20 index returns volatility.
    Keywords: stock index returns; volatility forecasting; stock index prediction; neural network; machine learning.
    DOI: 10.1504/IJADS.2024.10051016
     
  • Human Rights Disclosure and Sustainable Banking: Evidence from Europe and Implications for Policy   Order a copy of this article
    by Loris Di Nallo, Alberto Manzari, Raffaele Trequattrini 
    Abstract: This paper investigates the nature and quality of human rights reporting and disclosure in sustainable banking and its practices in providing information to stakeholders and assuring sustainability and sustainable development. Thus, this paper aims at analysing what are human rights information reported and disclosed by the banking industry to assure transparency and sustainable practices, drafting corporate transparency, sustainability and responsibility. We used the quantitative methodology based on the statistical analysis to represent the role of human rights disclosure in the sustainable banking. Using frameworks by corporate disclosure theories, we built our sample of all banks included in the EUROStoxx 600. We developed the regression analysis establishing the relationship between sustainability disclosure and human rights. Our results show achievements in the sustainability reporting and disclosure in representing human rights information by sustainable banking and practices. The positioning of human rights information is directed to increase corporate transparency, corporate responsibility and responsible investments decisions as well as sustainability and sustainable development.
    Keywords: sustainability; human rights disclosure; sustainable banking; responsible investment decisions; sustainable strategy; sustainable finance; sustainable development; metrics.
    DOI: 10.1504/IJADS.2024.10051089
     
  • Applying customer intelligence in marketing: a holistic approach   Order a copy of this article
    by Nguyen Anh Khoa Dam, Thang Le Dinh, William Menvielle 
    Abstract: Enterprises have started to adopt and apply customer intelligence, which is acquired through the support of business analytics to capitalise on big data, to optimise marketing decisions. However, little research focuses on holistically applying customer intelligence from defining and acquiring the right type of customer intelligence to applying and evaluating it for optimal outcomes. This paper presents a comprehensive approach to value creation from customer intelligence in marketing. Adapted from Bloom’s taxonomy, the proposed approach significantly contributes to identifying the six levels of applying customer intelligence in marketing, including defining relevant types of customer intelligence, building appropriate strategies, identifying customer data, understanding customer analytics, setting key performance indicators for the evaluation purpose, and creating value through business questions and the interactive dashboard.
    Keywords: customer intelligence; marketing decisions; holistic approach; big data; interactive dashboard.
    DOI: 10.1504/IJADS.2024.10051592
     
  • A Robust and Resourceful Automobile Insurance Fraud Detection with Multi-Stacked LSTM Network and Adaptive Synthetic Oversampling   Order a copy of this article
    by Isaac Kofi Nti, Kwabena Adu, Peter Nimbe, OWUSU NYARKO-BOATENG, Adebayo Felix Adekoya, Peter Appiahene 
    Abstract: Insurance companies worldwide are concerned about financial losses due to false claims. Automobile insurance fraud (AIF) has become more sophisticated, causing the yearly loss of trillions of dollars. AIF is tough to establish, and acquiring a thorough knowledge of the problem is complex. Also, AIF investigators have relied on manual claims inspection, proving costly, inefficient, and time-consuming. This paper proposed a robust and resourceful approach to AIF detection with multi-stacked LSTM (MSLSTM) reinforced with the adaptive synthetic (ADASYN) sampling algorithm for imbalanced learning. We experiment with the proposed model with a publicly available AIF dataset from Kaggle. Using accuracy, recall, precision, F1-score, and AUC, we compared the performance of our proposed MSLSTM model with well-known machine learning algorithms and previous AIF detection works. Our results showed a fair performance (accuracy = 95%, precision = 94%, AUC = 97% and F1-score = 92%) of the MSLSTM model than other algorithms and works.
    Keywords: automobile insurance fraud; AIF; car fraud detection; stacked LSTM network; adaptive synthetic oversampling.
    DOI: 10.1504/IJADS.2024.10051767
     
  • An exact solution method for seru scheduling problems considering past-sequence-dependent setup time and adjustment activities   Order a copy of this article
    by Ru Zhang, Zhe Zhang, Xiaoling Song, Yong Yin 
    Abstract: This paper concerns production scheduling problems with past-sequence-dependent (p-s-d) setup time and adjustment activities considerations in seru production system (SPS), in which the setup time is proportionate to the sum of processing times of jobs scheduled already, and the adjustment activities are also considered due to the deteriorating positional processing time. Some common scheduling criteria are concerned for five seru scheduling problems, and an exact assignment matrix approach is formulated to prove that these seru scheduling problems can be transformed into assignment problems. The polynomial computation time is also confirmed. Computational experiments are made finally, and it is shown that the proposed approach is effective for resolving seru scheduling problems through reformulation.
    Keywords: seru scheduling; setup time; adjustment activities; exact assignment matrix.
    DOI: 10.1504/IJADS.2024.10051772
     
  • Measuring Source, Affiliation, and Permission Likelihood of Consumer Confusion in Trademark Infringement Litigation   Order a copy of this article
    by Robert Peterson, Isabella Cunningham, Jeffrey A. Peterson 
    Abstract: This boundary-spanning article addresses the measurement of 'likelihood of confusion' in trademark infringement litigation. Likelihood of confusion is the sine qua non of trademark infringement litigation and is typically measured by means of consumer surveys. After brief discussions of consumer confusion and the Lanham Act, the three traditional types of likelihood of confusion recognised under the Lanham Act source confusion, affiliation confusion, and permission confusion are described, and two prominent survey approaches for measuring likelihood of confusion, 'Ever-ready' and 'Squirt, ' reviewed. Through a quantitative evaluation of existing likelihood of confusion surveys and an empirical experiment, various measurement issues are examined, and their implications considered. We document how existing measurement procedures can influence likelihood of confusion survey results, and especially how the attention accorded source confusion may inherently or unintentionally produce estimates of likelihood of confusion that understate overall confusion due to affiliation and/or permission likelihood of confusion. Suggestions for future research are discussed and an approach for measuring likelihood of confusion in trademark infringement litigation offered.
    Keywords: Lanham Act; trademark infringement; likelihood of confusion.
    DOI: 10.1504/IJADS.2024.10051848
     
  • Extended Fuzzy AHP for Decision under the DeLone McLean Model   Order a copy of this article
    by Frantisek Zapletal, Radek Nemec 
    Abstract: Fuzzy analytic hierarchy process (F-AHP) has been introduced in many variations requiring different conditions and assumptions. In this paper, we deal with a problem when the uncertainty is not primarily implied by a linguistic evaluation scale, but by the hesitance of decision-makers. This assumption is essential in our case study of the project success factor evaluation under the DeLone and McLean model because the evaluators have different skills, knowledge, and even competences. To get the level of hesitance of each decision-maker, we introduce the so-called hesitance degree, which defines the shape of fuzzy evaluations. To derive the fuzzy weights of criteria, we use the linear goal programming priority method introduced by Wang and Chin (2008), and the possibility and necessity measures to interpret the results. We also provide a novel diagram visualising the results. The presented F-AHP approach is used to evaluate the success factors of information system implementation.
    Keywords: hesitance; fuzzy; analytic hierarchy process; AHP; DeLone and McLean model.
    DOI: 10.1504/IJADS.2024.10052829
     
  • An Optimization model to design a maritime search and rescue system under uncertainty   Order a copy of this article
    by Donya Rahmani, Babak Ebrahimi, Hadi Kian 
    Abstract: Unfavourable weather conditions, disruptions in equipment, and human error are the factors that lead to maritime accidents. In such cases, delays in providing relief may lead to catastrophic events. Hence, this paper presents a bi-objective mixed-integer linear programming (MILP) model for marine search and rescue under uncertainty. The purpose of the proposed model is to minimise total costs and the completion time of operations, simultaneously. Helicopters and ships equipped with rescue and relief equipment are applied for maximum coverage. We use a stochastic scenario-based approach to cope the uncertain response time. A fuzzy solution approach is developed to deal with the uncertainty and solve the proposed bi-objective model. Finally, an algorithm is presented to generate data using probabilistic distribution functions, and the performance of the proposed model is evaluated by eight simulated problems. The results obtained for the simulated problems and the sensitivity analysis of the coefficients of the objective functions show the effectiveness of the proposed model.
    Keywords: maritime search and rescue; mathematical programming; location problem; fuzzy theory; stochastic programming.
    DOI: 10.1504/IJADS.2024.10053102
     
  • Development of open nutritional recipe software for obese children based on intelligent computing
    by Lifang Zhang, Zhou Liang 
    Abstract: In order to assist children and their parents to formulate nutrition prescriptions and improve the scientific level of children’s diet, this study developed a self-selected nutrition prescription expert decision-making system based on the principle of energy balance. The system has a built-in database of common daily foods, their nutrients and corresponding energy values, and calculates the daily total energy expenditure and distributes the three meals reasonably based on the basic personal information of children. Users can choose different foods from the food database to form their own nutrition recipes according to the total energy of each meal allocated by the system. After evaluated by the system, the self-selected personalised nutrition recipes can be further revised and form formal personalised nutrition prescriptions. Through the black box test, the system can effectively realise each function and provide a good user experience.
    Keywords: expert decision-making system; children; energy balance; nutritional recipe; self-selected.

  • Enhance personalized recommendations by exploring online social relations   Order a copy of this article
    by Xiaoyun He, Chuleeporn Changchit 
    Abstract: Personalized digital recommendations are widely used to improve customer experience and drive sales. Although recent research suggests that online social relations influence users' both product choices and ratings, few studies have examined them in the context of personalized recommendations. In this study, we aim to explore how online social relations can be leveraged to enhance personalized recommendations. The empirical results demonstrate that incorporating the ratings from a user’s social circle improves accuracy and coverage of personalized recommendations; In addition, differentiating these social ratings helps increase the recommendation diversity while limiting the loss of accuracy. The findings have important implications for the applicability of recommender systems in modern online business and social environment.
    Keywords: Social relations; recommendation accuracy; the diversity; online recommendation; personalized recommendation; online relations.
    DOI: 10.1504/IJADS.2024.10054181
     
  • Vulnerability to Poverty Due to Schooling: A discussion from the spatial perspective   Order a copy of this article
    by Rafael Freitas Souza, Julio Carneiro-da-Cunha, Luiz Corrêa, Cláudia Orsini Machado De Sousa 
    Abstract: Economic theories point out that regional poverty is more concentrated in regions far from urban centres. However, at Brazilian Midwest, wealth-generating localities are not concentrated in those centres and may create misunderstandings about the theoretical understanding of this phenomenon, and for policymakers who need predictive tools to address the fight against poverty. Thus, it was intended to predict poverty vulnerability from educational levels in a distinct phenomenon of decentralization. A geographically weighted regression was performed using UNDP data on Midwest municipalities. It was pointed out that education levels can predict vulnerability to poverty, confirming the theories existing in the main agricultural area in the world. As a contribution, public policies need to be thought individual and spatially, to consider actions beyond the institutional boundaries of municipalities, in an integrated and coordinated manner between neighbouring cities.
    Keywords: Poverty; Education; Public Policies; Brazilian Midwest; Poverty Vulnerability.
    DOI: 10.1504/IJADS.2024.10054467
     
  • Production policy for an integrated inventory system under cloudy fuzzy environment   Order a copy of this article
    by S.V. Singh Padiyar, Naveen Bhagat, S.R. Singh, Neha Punetha, Himani Dem 
    Abstract: This article highlights an optimal strategy for a supply chain model having a defective manufacturing process for deteriorating items with cloudy fuzzy inflation. The system considers two different consumption rates at different time periods for the supplier. The imperfection during production causes ambiguity for the total production schedule, which affects the total shipment delivered by the manufacturer to the supplier. To emphasise the co-ordination between supplier and producer, a percentage of the total transport expenditures of the supplier is provided by the producer which helps the supplier to deliver the shipment fast and safely. The model has been developed over every likely expense incurred for the supply chain system, i.e., fixed and variable transportation costs, labour cost, costs of scrapping imperfect objects, etc. The formulated model is also justified using numerical examples and sensitivity analysis of the important parameters to inspect the effect on the optimal total cost.
    Keywords: supply chain model; deteriorating item; imperfect production; two-warehouse; cloudy fuzzy numbers.
    DOI: 10.1504/IJADS.2023.10046704
     
  • Human resource management at the enterprise during the development of new forms of employment   Order a copy of this article
    by Islam O. Sulumov, Zulay K. Tavbulatova, Gulnaz F. Galieva, Gayane A. Kochyan, Anzaur A. Bzhasso 
    Abstract: The research is aimed at analysing and long-term forecasting of changes in the field of human resource management in the context of labour market transformation, as well as identifying adaptation tools at the enterprise management level. The article provides a forecast of structural and functional changes in organisations in terms of human resource management. The authors have formed a classification model of the functions and tasks performed in the organisation, which is necessary to optimise organisational activities and adapt to predicted changes. The authors used the analysis method to assess the current state of the global sphere of work and identify key patterns. The economic and mathematical method of trend extrapolation is used to forecast the macroeconomic dynamics of the freelance market in Russia. Synthesis as a method of studying the cumulative impact of the identified trends was used to make a holistic forecast of the transformation of intra-organisational activity.
    Keywords: labour market; transformation; employment; human resource management; freelance; adaptation tools.
    DOI: 10.1504/IJADS.2023.10047349
     
  • An efficient constructive heuristic for the cutting stock problem applied in a foam mattress industry   Order a copy of this article
    by Mariem Baazaoui, Souhir Elleuch, Hichem Kammoun 
    Abstract: The cutting and packing problem belongs to the combinatorial optimisation problems; it covers a wide range of practical cases in industries. The present paper investigates a new real world problem that needs to be solved through the daily operations of cutting foam blocks in an industrial company. The problem is considered as one of non-classical problems in the cutting and packing area. It represents a variant of the three dimensional cutting stock problem. The originality of the studied problem is indicated by a specific set of constraints related to the production process and the cutting ways. A constructive heuristic was developed to provide cutting patterns in advance. All possible combinations established from the ways of cutting right rectangular prisms from foam blocks define the cutting patterns. This heuristic performs well and shows promising results in reasonable computational times to provide efficient cutting plans in order to reduce the total material loss.
    Keywords: optimisation; three dimensional cutting stock problem; cutting patterns; guillotine cut; constructive heuristic.
    DOI: 10.1504/IJADS.2023.10046079
     
  • The internet of things and human sustainability between theory and practice: is it time to bridge the gap?   Order a copy of this article
    by Paola Paoloni, Maurizio Massaro, Francesca Dal Mas, Rosa Lombardi 
    Abstract: The internet of things (IoT) stands as a disruptive technology that offers unique opportunities for organisations to increase their competitive advantage. Still, several barriers in its implementation emerge, like privacy concerns. The paper aims at investigating how IoT can be used balancing the need to improve companies' performance safeguarding, at the same time, the sustainability of work conditions for employees. Thematic and content analysis is used to assess both practitioners' as well as scholars' works. Results demonstrate how IoT has the potential to enhance human sustainability by reducing stress and anxiety, facilitating some tasks, entailing a fairer performance assessment, and even contributing to work and life balance. A proactive role by organisations and policymakers is required to overcome barriers like the lack of privacy, by translating the benefits of the new technology to its users. A win-win strategy can boost the value for the organisation and its people.
    Keywords: internet of things; IoT; human sustainability; work-life-balance; technology; digital disruption; practitioners; scholars; practitioners-academics divide; strategy; organisations.
    DOI: 10.1504/IJADS.2023.10045855
     
  • Computational efficiency in sports talent identification - a systematic review   Order a copy of this article
    by Naveed Jeelani Khan, Gulfam Ahamad, Mohd. Naseem, Shahab Saquib Sohail 
    Abstract: The selection of talent for sports has always been of great concern. The research interest in the domain of computational decision-making for sports talent identification is on an increasing curve. The conventional approaches are being modelled into the scientific models using various analytical and mathematical computational techniques. This paper reviews some of the talent identification models and aims to project the current perspective of the computational techniques being employed in sports talent identification (TiD). Articles from a timeframe of 1995-2020 were systematically selected in accordance with the PRISMA guidelines. We remain focused on the computational methodology being employed in the TiD models. The review delivers the findings and highlights some of the inherent issues that are not being addressed by the existing TiD models.
    Keywords: sports talent identification; applied soft computing; multi-criteria decision making; MCDM; sports talent computation.
    DOI: 10.1504/IJADS.2023.10046451