Template-Type: ReDIF-Article 1.0 Author-Name: Bagus Setya Rintyarna Author-X-Name-First: Bagus Setya Author-X-Name-Last: Rintyarna Author-Name: Riyanarto Sarno Author-X-Name-First: Riyanarto Author-X-Name-Last: Sarno Author-Name: Chastine Fatichah Author-X-Name-First: Chastine Author-X-Name-Last: Fatichah Title: Enhancing the performance of sentiment analysis task on product reviews by handling both local and global context Abstract: Commonly, product review analysis includes extracting sentiment from product documents. The contextual aspect contained in a review document has potential to improve results obtained by the sentiment analysis task. In this regard, this paper proposes an approach that takes into account both local and global context. The main contribution of this work is threefold. Firstly, local context is defined and the graph-based word sense disambiguation (WSD) method is extended to assign the correct sense of a word in the context of a sentence. Secondly, global context is defined for addressing contextual issues related to the specific domain of a review document by using an improved SentiCircle-based method. Thirdly, a weighted mean-based strategy to determine sentiment value at document level is presented. Several experiments were conducted to assess the proposed method. Overall, the proposed method outperformed the baseline method in the metrics of precision, recall, F-measure and accuracy. Journal: Int. J. of Information and Decision Sciences Pages: 75-101 Issue: 1 Volume: 12 Year: 2020 Keywords: sentiment analysis; local context; global context; word sense disambiguation; WSD; SentiCircle; decision sciences. File-URL: http://www.inderscience.com/link.php?id=104992 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:1:p:75-101 Template-Type: ReDIF-Article 1.0 Author-Name: Merouane Zoubeidi Author-X-Name-First: Merouane Author-X-Name-Last: Zoubeidi Author-Name: Okba Kazar Author-X-Name-First: Okba Author-X-Name-Last: Kazar Author-Name: Saber Benharzallah Author-X-Name-First: Saber Author-X-Name-Last: Benharzallah Author-Name: Nadjib Mesbahi Author-X-Name-First: Nadjib Author-X-Name-Last: Mesbahi Author-Name: Abdelhak Merizig Author-X-Name-First: Abdelhak Author-X-Name-Last: Merizig Author-Name: Djamil Rezki Author-X-Name-First: Djamil Author-X-Name-Last: Rezki Title: A new approach agent-based for distributing association rules by business to improve decision process in ERP systems Abstract: Nowadays, the distributed computing plays an important role in the data mining process. To make systems scalable it is important to develop mechanisms that distribute the workload among several sites in a flexible way. Moreover, the acronym ERP refers to the systems and software packages used by organisations to manage day-by-day business activities. ERP systems are designed for the defined schema that usually has a common database. In this paper, we present a collaborative multi-agent based system for association rules mining from distributed databases. In our proposed approach, we combine the multi-agent system with association rules as a data mining technique to build a model that can execute the association rules mining in a parallel and distributed way from the centralised ERP database. The autonomous agents used to provide a generic and scalable platform. This will help business decision-makers to take the right decisions and provide a perfect response time using multi-agent system. The platform has been compared with the classic association rules algorithms and has proved to be more efficient and more scalable. Journal: Int. J. of Information and Decision Sciences Pages: 1-35 Issue: 1 Volume: 12 Year: 2020 Keywords: enterprise resource planning; ERP; multi-agents system; MAS; data mining associate rules; JADE; WEKA. File-URL: http://www.inderscience.com/link.php?id=104993 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:1:p:1-35 Template-Type: ReDIF-Article 1.0 Author-Name: Yun-Ning Liu Author-X-Name-First: Yun-Ning Author-X-Name-Last: Liu Author-Name: Shiow-Yang Wu Author-X-Name-First: Shiow-Yang Author-X-Name-Last: Wu Title: A rule-based approach for dynamic analytic hierarchy process decision-making Abstract: The analytic hierarchy process (AHP) is widely used in many multi-criteria decision-making problems and has been successfully applied to many practical cases. However, the AHP is time-consuming and the decision model is not agile enough for fast changing environment. To overcome this weakness, we develop a rule-based approach for dynamic AHP decision-making in changing environment. We analyse critical factors in the AHP decision process under uncertainty and propose to encode expert knowledge for change handling using event-condition-action rules. We propose a theorem and associated method to determine the change in ordering of decision alternatives based on event-condition-action rule-induced weight updates. We demonstrate the effectiveness of our approach using a case study of the supplier selection decision-making task of the steel and iron industry in Taiwan. The study shows that our mechanism can effectively reach the same level of decision quality as expert decision maker(s). Journal: Int. J. of Information and Decision Sciences Pages: 36-74 Issue: 1 Volume: 12 Year: 2020 Keywords: dynamic rule-based AHP; two criteria analysis; steel and iron industry; comparison matrix. File-URL: http://www.inderscience.com/link.php?id=104994 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:1:p:36-74 Template-Type: ReDIF-Article 1.0 Author-Name: Aynalem Shita Author-X-Name-First: Aynalem Author-X-Name-Last: Shita Author-Name: Nand Kumar Author-X-Name-First: Nand Author-X-Name-Last: Kumar Author-Name: Seema Singh Author-X-Name-First: Seema Author-X-Name-Last: Singh Title: The impact of agricultural technology adoption on income inequality: a propensity score matching analysis for rural Ethiopia Abstract: This study analyses the impact of agricultural technology adoption on income inequality. Primary data has been collected from 400 sample households in Awi zone of Ethiopia through household survey during agricultural season of 2017/18. The collected data were analysed by using propensity score matching method. The estimated results revealed that adoption of agricultural technologies such as chemical fertiliser and improved seeds significantly increase total household income but worsen income distribution. After adoption of agricultural technologies, income inequality measured by Gini coefficient increased ranged from 0.047 to 0.087. Hence, the government and other concerned authorities should exert more efforts in order to enhance technology adoption status of the poor households by increasing their accessibility for extension and credit services. Journal: Int. J. of Information and Decision Sciences Pages: 102-114 Issue: 1 Volume: 12 Year: 2020 Keywords: technology adoption; income inequality; propensity score matching; Ethiopia. File-URL: http://www.inderscience.com/link.php?id=105013 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:1:p:102-114 Template-Type: ReDIF-Article 1.0 Author-Name: Shiksha Singh Author-X-Name-First: Shiksha Author-X-Name-Last: Singh Author-Name: Rohit Kumar Tiwari Author-X-Name-First: Rohit Kumar Author-X-Name-Last: Tiwari Title: Quality of service-based service selection in smart parking Abstract: Smartness in the existing environment is required for overall growth of any country. Government is putting tremendous effort and a huge sum of money for making cities smart to achieve smartness. A very first asset that needs to be made smart is smart parking system to avoid the traffic congestion. There are many service providers which are offering smart parking services, but there is no quality of service (QoS) framework available so far. So, for a customer point of view, it is very hard to select the best service provider and gain maximum satisfaction. So, in this paper, we have designed a QoS framework which consists of 33 metrics to evaluate a smart parking service. These parameters are identified from the user as well as vendors' perspective and help to select better service provider. We have also proposed multi criteria decision making (MCDM) approach technique for order preferences by similarity to ideal solution (TOPSIS) to select best smart parking service provider based on identified QoS. We have demonstrated our approach with the help of case studies. Journal: Int. J. of Information and Decision Sciences Pages: 154-175 Issue: 2 Volume: 12 Year: 2020 Keywords: quality of services; QoS; smart city; smart parking system; internet of things; IoT; multi criteria decision making; MCDM; TOPSIS. File-URL: http://www.inderscience.com/link.php?id=106722 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:2:p:154-175 Template-Type: ReDIF-Article 1.0 Author-Name: Salma Mouatassim Author-X-Name-First: Salma Author-X-Name-Last: Mouatassim Author-Name: Ahmed Haroun Sabry Author-X-Name-First: Ahmed Haroun Author-X-Name-Last: Sabry Author-Name: Mustapha Ahlaqqach Author-X-Name-First: Mustapha Author-X-Name-Last: Ahlaqqach Author-Name: Jamal Benhra Author-X-Name-First: Jamal Author-X-Name-Last: Benhra Title: A new framework using biform game for cost optimisation of distribution networks Abstract: The present work focuses on the demand decision making problem for regional distribution centres sharing the same product families. Each centre orders quantities to be distributed from production units. Our approach suggests a biform game to maximise the benefits of each centre and minimise the end of cycle market induced supply to demand deviations. We start by an independent demand forecasting under uncertainty. Once the demand is met, the centres enter a collaboration phase where coalitions are created and products are exchanged, in order to achieve the core stability of the actual game. If not met, we try to achieve the same objectives using individual rationality through an adapted approach based on Shapley value analysis for each possible coalition. Journal: Int. J. of Information and Decision Sciences Pages: 115-135 Issue: 2 Volume: 12 Year: 2020 Keywords: game theory; forecasting; Shapley value; collaboration; biform game; cost allocation; coalitions; core stability. File-URL: http://www.inderscience.com/link.php?id=106727 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:2:p:115-135 Template-Type: ReDIF-Article 1.0 Author-Name: Mohd Zabid Mohd Faeid Author-X-Name-First: Mohd Zabid Mohd Author-X-Name-Last: Faeid Author-Name: Norhaslinda Zainal Abidin Author-X-Name-First: Norhaslinda Zainal Author-X-Name-Last: Abidin Author-Name: Shri Dewi Applanaidu Author-X-Name-First: Shri Dewi Author-X-Name-Last: Applanaidu Title: Determining optimal replanting rate in palm oil industry, Malaysia: a system dynamics approach optimal policy search in oil palm plantation feedback loops using system dynamics optimisation Abstract: One of the important factors that contribute to the stagnant growth of Malaysia's crude palm oil production is the accumulation of ageing oil palm plantation area. Given the scarcity of new plantation area in Malaysia, it is very important that an optimal replanting rate has to be determined to decrease the accumulation of ageing area. The objective of this study is to determine an optimal replanting rate for oil palm industry in Malaysia. This study compared the trend results of fresh fruit bunches (FFB) yield using base run system dynamics (SD) and SD with optimisation analysis. Findings indicate that the proposed optimal replanting rate based on SD revealed the maximum production of the FFB yield by year 2050 compared to base run analysis. Findings from this study proposed the appropriate planting strategy to ensure the continuous supply of palm oil without significant disruption if high replanting rate has been implemented. Journal: Int. J. of Information and Decision Sciences Pages: 136-153 Issue: 2 Volume: 12 Year: 2020 Keywords: fresh fruit bunches yield; oil palm plantation; system dynamics optimisation; optimal replanting rate; Malaysia. File-URL: http://www.inderscience.com/link.php?id=106728 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:2:p:136-153 Template-Type: ReDIF-Article 1.0 Author-Name: Bolanle Adefowoke Ojokoh Author-X-Name-First: Bolanle Adefowoke Author-X-Name-Last: Ojokoh Author-Name: Idorenyin Akwaowo Amaunam Author-X-Name-First: Idorenyin Akwaowo Author-X-Name-Last: Amaunam Title: A switching hybrid mobile recommender system for tourists Abstract: This paper proposes a switching feature-based model that leverages the needs of both new and existing users for recommendation of tourist locations. In an attempt to solve the cold-start problem, recommendations to new users are implemented with Bayesian algorithm on supplied demographic data. For existing users, the system switches to the collaborative filtering subsystem, where recommendation results are produced using Pearson correlation computation and offered based on the items in the database. The model was validated with discounted cumulative gain, precision, and recall. A comparative analysis with some existing systems showed lower mean absolute error. Experimental results obtained from the survey of different categories of users showed the effectiveness of the proposed techniques. Journal: Int. J. of Information and Decision Sciences Pages: 176-194 Issue: 2 Volume: 12 Year: 2020 Keywords: Bayesian algorithm; conditional probability table; CPT; cold-start; mobile app; recommender system; decision; tourists. File-URL: http://www.inderscience.com/link.php?id=106735 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:2:p:176-194 Template-Type: ReDIF-Article 1.0 Author-Name: Sukanta Chandra Swain Author-X-Name-First: Sukanta Chandra Author-X-Name-Last: Swain Title: Impact of farmers' ownership of seeds on well-being of farmers: study of a village in Odisha Abstract: After India's green revolution, the use of seed bio-technologies in agriculture, in which the ownership of seeds lies with organised private parties, have been in question. But prior to that, Indian farmers were going by using their harvested corps as seeds in future. As time passed, farmers in front-line got acclimatised to the seed bio-technology. Small and marginal farmers had also to follow the foot-print of the front-line farmers for two reasons: 1) seeing the prosperity of the latter, the former got motivated to follow suit; 2) good harvest with HYVs seeds by front-line farmers, leading to reduced average cost, drove the traditional seed users away from the market on pricing ground. It is pertinent to unfold whether this paradigm shift has affected the well-being of the small farmers in rural Odisha. Thus, this paper highlights the impact of ownership of seeds on small farmers' well-being. Journal: Int. J. of Information and Decision Sciences Pages: 195-209 Issue: 2 Volume: 12 Year: 2020 Keywords: seed ownership; seed bio-technology; small farmers; well-being; agriculture; decision; information lag; impact; Kasarda; Odisha. File-URL: http://www.inderscience.com/link.php?id=106738 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:2:p:195-209 Template-Type: ReDIF-Article 1.0 Author-Name: Amir Imran Zainoddin Author-X-Name-First: Amir Imran Author-X-Name-Last: Zainoddin Author-Name: Azlan Amran Author-X-Name-First: Azlan Author-X-Name-Last: Amran Author-Name: Mohd. Rizaimy Shaharudin Author-X-Name-First: Mohd. Rizaimy Author-X-Name-Last: Shaharudin Title: The effect of social capital on the effectiveness of community development programmes in Malaysia Abstract: This study aims to determine the influence of social capital on the effectiveness of the farmer's development programme established by a MNC in Malaysia for business-community relations as part of the company's CSR endeavours. The sampling technique employed in this study was census sampling with all of the 400 respondents being included in the study. The results unveiled that the relational and cognitive dimensions were positively and significantly related to the effectiveness of the community development programme. Nevertheless, the structural dimension failed to follow similar inclinations. The finding has contributed to the social capital theory by supporting the relational and cognitive dimensions as the factors that influence the success of the community development programmes. Future study is suggested to measure the effectiveness of community development programmes using financial or non-financial aspects, utilise the stakeholder theory perspectives, as well as validate the inconsistencies in the outcomes of the past studies. Journal: Int. J. of Information and Decision Sciences Pages: 227-245 Issue: 3 Volume: 12 Year: 2020 Keywords: corporate social responsibility; social capital; effectiveness; community development programmes; farmers. File-URL: http://www.inderscience.com/link.php?id=108139 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:3:p:227-245 Template-Type: ReDIF-Article 1.0 Author-Name: Vishal A. Bhosale Author-X-Name-First: Vishal A. Author-X-Name-Last: Bhosale Author-Name: Ravi Kant Author-X-Name-First: Ravi Author-X-Name-Last: Kant Author-Name: Mark Goh Author-X-Name-First: Mark Author-X-Name-Last: Goh Title: Impact of knowledge flows on supply chain performance: an experiment on four Indian luggage manufacturing firms Abstract: This paper seeks to investigate the role and impact of supply chain knowledge flow enablers (SCKFEs) in improving the supply chain performance of four luggage manufacturing firms. The paper applies fuzzy analytic hierarchy process (AHP) to obtain the weights of the SCKFEs, and fuzzy multi-objective optimisation by the ratio analysis (MOORA) to rank the firms practicing knowledge flows. A case study of four Indian luggage manufacturers suggests that the better the implementation of the SCKFEs, the better the knowledge flows and hence better supply chain performance. This study reveals how firms practicing knowledge flows influence their supply chain performance. Journal: Int. J. of Information and Decision Sciences Pages: 270-298 Issue: 3 Volume: 12 Year: 2020 Keywords: knowledge flow; supply chain performance; multi-criteria decision making; MCDM; analytic hierarchy process; AHP; MOORA. File-URL: http://www.inderscience.com/link.php?id=108140 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:3:p:270-298 Template-Type: ReDIF-Article 1.0 Author-Name: Priyanka Author-X-Name-First: Author-X-Name-Last: Priyanka Author-Name: Dharmender Kumar Author-X-Name-First: Dharmender Author-X-Name-Last: Kumar Title: Decision tree classifier: a detailed survey Abstract: Decision tree classifier (DTC) is one of the well-known methods for data classification. The most significant feature of DTC is its ability to change the complicated decision making problems into simple processes, thus finding a solution which is understandable and easier to interpret. This paper provides a brief review on various algorithms developed in literature for constructing and representing decision trees, splitting criteria for selecting best attribute and pruning methods. The readers will be able to understand why decision trees are more popular among all other methods of classification, what are their uses, limitations and applications in different diverse areas. They will also come to know about a decision tree induction algorithms, splitting criteria, pruning methods, concepts of ensemble methods, fuzzy decision trees, hybridisation of DTCs, etc. These enhancements are found very helpful in solving complex datasets with less computation in very short time period while achieving high accuracy. Journal: Int. J. of Information and Decision Sciences Pages: 246-269 Issue: 3 Volume: 12 Year: 2020 Keywords: decision tree hybridisation; classification; iterative dichotomiser 3; ID3; CART; ensembles; splitting criteria; pruning methods. File-URL: http://www.inderscience.com/link.php?id=108141 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:3:p:246-269 Template-Type: ReDIF-Article 1.0 Author-Name: Hrishikesh Kulkarni Author-X-Name-First: Hrishikesh Author-X-Name-Last: Kulkarni Author-Name: Manisha Marathe Author-X-Name-First: Manisha Author-X-Name-Last: Marathe Title: Context vector convergence of computational behaviour and cultural traits for team selection Abstract: Selection of team for match, mission or project is always challenging since every mission is different and every match brings new uncertainties. Your best resource may not be the right choice for the given task. It is the context of task, behaviours of individuals and above all constitution of the team in that scenario contribute to the outcome. The context vector convergence (CVC) of behavioural vectors helps in deriving the actual effect of two vectors in overall team performance. The personality vector is used to derive behavioural context while mission vector is used to derive the scenario context. These two vectors are graphically associated in convergence to identify and recommend the best team combinations. While formulating the vector, cultural aspects and behaviours are captured through expressions and interactions. Top three combinations are compared to validate hypotheses. The promising results reinforce the premise to establish further research directions. Journal: Int. J. of Information and Decision Sciences Pages: 211-226 Issue: 3 Volume: 12 Year: 2020 Keywords: behavioural psychology; machine learning; artificial intelligence; cognitive sciences; computational psychology; context; cultural computing; computational social sciences; mission vector; personality vector; context vector. File-URL: http://www.inderscience.com/link.php?id=108143 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:3:p:211-226 Template-Type: ReDIF-Article 1.0 Author-Name: José Cristiano Pereira Author-X-Name-First: José Cristiano Author-X-Name-Last: Pereira Author-Name: Geane Cristina Fayer Author-X-Name-First: Geane Cristina Author-X-Name-Last: Fayer Title: Strategic decision making to maximise the efficiency of water usage in steel manufacturing process via AHP and BBN: a case study Abstract: This study proposes a method for strategic decision making, considering the identification and prioritisation of the potential risks that could stop production in the steel production processes in a water crisis scenario. This method combines AHP and BBN to assess risks arising from the water crisis scenario in steel manufacturing industries. As a methodological approach experts and professionals from a group of steel manufacturing companies were interviewed do identify risk factors considering a water crisis scenario and the risk probabilities were elicited accordingly. No previous work dealing with risk analysis to prioritise risks arising from the water crisis scenario in steel manufacturing processes could be found. As a result of this study, a global risk matrix is proposed. The study provides a method to be used by professionals, engineers and decision makers in the identification of risk factors that could impact the operation of steel manufacturing companies. Journal: Int. J. of Information and Decision Sciences Pages: 328-347 Issue: 4 Volume: 12 Year: 2020 Keywords: risk analysis; water shortage; analytic hierarchy process; AHP; Bayesian belief network; BBN; steel industry. File-URL: http://www.inderscience.com/link.php?id=110446 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:4:p:328-347 Template-Type: ReDIF-Article 1.0 Author-Name: Ameni Sassi Author-X-Name-First: Ameni Author-X-Name-Last: Sassi Author-Name: Wael Ouarda Author-X-Name-First: Wael Author-X-Name-Last: Ouarda Author-Name: Chokri Ben Amar Author-X-Name-First: Chokri Ben Author-X-Name-Last: Amar Author-Name: Serge Miguet Author-X-Name-First: Serge Author-X-Name-Last: Miguet Title: Hierarchical two-pathway autoencoders neural networks for skyline context conceptualisation Abstract: In this paper, we proposed a novel hierarchical two-pathway autoencoders architecture to transform a local information based on skyline scene representation, into nonlinear space. The first pathway is intended for the transformation of the geometric features extracted from the horizon line. The second pathway is applied after the first one to joint the colour information under the skyline to the transformed geometric features, and to get the landscape context conceptualisation. To evaluate our suggested system, we constructed the SKYLINEScene database containing 2,000 images of rural and urban landscapes, with a high degree of diversity. In order to investigate the performance of our HTANN-Skyline, many experiments were carried out using this new database. Our approach shows its robustness in skyline context conceptualisation and enhances the classification rates by 1% compared to the AlexNet architecture; and by more than 10% compared to the hand-crafted approaches based on global and local features. Journal: Int. J. of Information and Decision Sciences Pages: 299-327 Issue: 4 Volume: 12 Year: 2020 Keywords: deep neural network; autoencoder; scene categorisation; skyline; curvature scale space; features transformation; classification; horizon line; hierarchical; skyline context conceptualisation. File-URL: http://www.inderscience.com/link.php?id=110447 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:4:p:299-327 Template-Type: ReDIF-Article 1.0 Author-Name: Zahra Shekarchizade Author-X-Name-First: Zahra Author-X-Name-Last: Shekarchizade Author-Name: Bahram Ranjbarian Author-X-Name-First: Bahram Author-X-Name-Last: Ranjbarian Author-Name: Vahid Ghasemi Author-X-Name-First: Vahid Author-X-Name-Last: Ghasemi Title: Family members as an external source of travel information Abstract: The aim of this work is to investigate the effect of family structure, duration of family life and family members' acquaintance with travel destination on information search behaviour of heads of families to buy a package tour. A sample of 70 Isfahani heads of families who had bought an outbound package tour in January-September 2017 was selected. The results indicate that family structure and duration of family life have impacts on the perceived value of seeking information among family members. In families that have different value structures and in various stages of family life cycle, the perceived value of seeking information among family members is different; however, the perceived value was not significantly effective in the level of seeking information among family members. Indeed, family members' acquaintance with travel destination has a significant impact on the level of seeking information by using perceived value of seeking information among family members. Journal: Int. J. of Information and Decision Sciences Pages: 390-407 Issue: 4 Volume: 12 Year: 2020 Keywords: family members; travel information; family structure; duration offamily life; familiarity; information search behaviour; perceived value; familial factors; external source; decision making. File-URL: http://www.inderscience.com/link.php?id=110448 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:4:p:390-407 Template-Type: ReDIF-Article 1.0 Author-Name: Ankit Mehrotra Author-X-Name-First: Ankit Author-X-Name-Last: Mehrotra Author-Name: Reeti Agarwal Author-X-Name-First: Reeti Author-X-Name-Last: Agarwal Title: Credit cards in a developing economy: a data mining approach Abstract: Usage of credit cards has been witnessing an increase in recent years in India. The study was undertaken to comprehend the effect of the different demographic characteristics of the respondents on credit cards owned by them. Findings indicate that friends/family members are most influential in affecting customer's knowledge of credit card. It was seen that for pitching more than one credit card, the group of customers that should be targeted are those with low income and in the age group 46-60 years. Journal: Int. J. of Information and Decision Sciences Pages: 377-389 Issue: 4 Volume: 12 Year: 2020 Keywords: C%RT; credit cards; data mining; demographic variables; feature selection; gender; income; Indian customers; influencing medium; target group. File-URL: http://www.inderscience.com/link.php?id=110449 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:4:p:377-389 Template-Type: ReDIF-Article 1.0 Author-Name: Sana Hamdi Author-X-Name-First: Sana Author-X-Name-Last: Hamdi Author-Name: Emna Bouazizi Author-X-Name-First: Emna Author-X-Name-Last: Bouazizi Author-Name: Sami Faiz Author-X-Name-First: Sami Author-X-Name-Last: Faiz Title: Query optimisation in real-time spatial big data Abstract: Nowadays, real-time spatial applications have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of databases and data warehouses especially that users expect to receive the results of each query within a short time period without holding into account the load of the system. To solve this problem, several optimisation techniques are used. Thus, we propose, as a first contribution, a novel data partitioning approach for real-time spatial big data named vertical partitioning approach for real-time spatial big data (VPA-RTSBD). This contribution is an implementation of the matching algorithm for traditional vertical partitioning. Then, as a second contribution, we propose a new frequent itemset mining approach which relaxes the notion of window size and proposes a new algorithm named PrePost*-RTSBD. Thereafter, a simulation study is shown to prove that our contributions can achieve a significant performance improvement. Journal: Int. J. of Information and Decision Sciences Pages: 348-376 Issue: 4 Volume: 12 Year: 2020 Keywords: real-time spatial data; transaction; stream data; feedback control scheduling; quality of service; data partitioning; frequent itemset mining; simulation. File-URL: http://www.inderscience.com/link.php?id=110450 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijidsc:v:12:y:2020:i:4:p:348-376