Template-Type: ReDIF-Article 1.0
Author-Name: Ahmet Talha Yigit
Author-X-Name-First: Ahmet Talha
Author-X-Name-Last: Yigit
Author-Name: Tolga Kaya
Author-X-Name-First: Tolga
Author-X-Name-Last: Kaya
Author-Name: Utku Dogruak
Author-X-Name-First: Utku
Author-X-Name-Last: Dogruak
Title: An unsupervised learning approach to basket type definition in FMCG sector based on household panel data
Abstract:
The purpose of this study is to propose a clustering-based modelling approach to define the main groups of baskets in Turkish fast-moving consumer goods (FMCG) industry regarding the sectoral decomposition, the total value and the size of the baskets. To do this, based on the information regarding nearly three million basket purchases made in 2018 by more than 14,000 households, alternative unsupervised learning methods such as K-means, and Gaussian mixtures are implemented to obtain and define the basket patterns in Turkey. Additionally, a supervised ensemble learning approach based on XGBoost method is also selected among fully connected neural networks and random forest models to assign the new baskets into the existing clusters. Results show that, 'SaveTheDay', 'CareTrip', 'Breakfast', 'SuperMain' and 'MeatWalk' are among the most important basket types in Turkish FMCG sector.
Journal: Int. J. of Information and Decision Sciences
Pages: 243-259
Issue: 3
Volume: 14
Year: 2022
Keywords: basket analysis; cluster analysis; K-means; fast-moving consumer goods; FMCG; supervised learning; consumer panel; ensemble learning; deep learning.
File-URL: http://www.inderscience.com/link.php?id=125187
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:3:p:243-259
Template-Type: ReDIF-Article 1.0
Author-Name: E.P. Ephzibah
Author-X-Name-First: E.P.
Author-X-Name-Last: Ephzibah
Author-Name: R. Sujatha
Author-X-Name-First: R.
Author-X-Name-Last: Sujatha
Author-Name: Jyotir Moy Chatterjee
Author-X-Name-First: Jyotir Moy
Author-X-Name-Last: Chatterjee
Title: An adaptive neuro-fuzzy inference for blockchain-based smart job recommendation system
Abstract:
Blockchain is a technology that supports secured transaction in a public distributed database. It maintains a peer-to-peer network where a transaction cannot be modified or tampered by unauthenticated users. It provides a safe message transfer from a sender to a receiver. Job recommendation is an online system that provides a mapping between the job seeker and the employer. This paper proposes a public blockchain of job recommendations based on incremental hashing. The examinations show that this blockchain job recommendation provides process integrity, traceability, security, high levels of transparency, drastic reduction in operational cost and high standard and systematic. The system has two stages. Firstly, using blockchain technology, the authenticated data is fetched. Secondly, a classification model using adaptive neuro-fuzzy inference system is built for mapping the job seeker to the recruiter. This approach proves to be authenticated as well as a smart job recommendation system.
Journal: Int. J. of Information and Decision Sciences
Pages: 1-14
Issue: 1
Volume: 14
Year: 2022
Keywords: blockchain; distributed database; peer to peer network; job recommendation system; unsecured message transmission; unauthenticated data; time-consuming search; incremental hashing; classification model; adaptive neuro-fuzzy inference system; ANFIS.
File-URL: http://www.inderscience.com/link.php?id=122719
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:1:p:1-14
Template-Type: ReDIF-Article 1.0
Author-Name: Moumita Poddar
Author-X-Name-First: Moumita
Author-X-Name-Last: Poddar
Author-Name: Tanmoyee Banerjee
Author-X-Name-First: Tanmoyee
Author-X-Name-Last: Banerjee
Author-Name: Ajitava Raychaudhuri
Author-X-Name-First: Ajitava
Author-X-Name-Last: Raychaudhuri
Title: What determines the household decision to borrow for investment or repayment of old debt? The Indian story
Abstract:
Borrowing for investment in either physical or human capital promotes growth while that for consumption or debt repayment may lead to so called 'debt-trap' for the households. The present paper probes deeper into the decision-making process of the households regarding choice between these alternative borrowing. The data comes from All India Debt and Investment Survey (NSS 70th round). These methods used are Cragg's Box-Cox double hurdle model and instrumental variable (IV) probit model. Our study shows the decision to borrow for investment purposes depends on such factors as gender, religion, location, education, asset position as well as on the status of financial inclusion of households. The decision to borrow for repayment of existing debt is most prevalent among urban educated households in addition to land-owning rural borrowers.
Journal: Int. J. of Information and Decision Sciences
Pages: 60-84
Issue: 1
Volume: 14
Year: 2022
Keywords: institutional borrowing; capital formation; financial inclusion; inequality; potential debt-trap.
File-URL: http://www.inderscience.com/link.php?id=122720
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:1:p:60-84
Template-Type: ReDIF-Article 1.0
Author-Name: Ernest Oseghale Amiens
Author-X-Name-First: Ernest Oseghale
Author-X-Name-Last: Amiens
Author-Name: Ifuero Osad Osamwonyi
Author-X-Name-First: Ifuero Osad
Author-X-Name-Last: Osamwonyi
Title: Stock price forecasting using hidden Markov model
Abstract:
We used hidden Markov model (HMM) with single observation to estimate stock prices of selected manufacturing companies from the Nigerian Stock Exchange. Data from 22 November 2013 to 6 July 2018 were partitioned into two datasets for training and testing. Subsequently, the data were differenced, trained, tested and used to forecast closing prices for 60 days for each equity. The HMM was implemented with Matlab. The research revealed closing price prediction accuracy ranging from 3.33% to 96.67% and trade signal precision ranging from 31.67% to 97.67%. Also, the MAE values range from 0.0013 to 34.2867 while the MAPE values are between 0.1498% and 6.0034%. The hypothesis tested revealed that the model is efficient. Similarly, the comparison test conducted revealed the performance of HMM is better than ARIMA and neural network (NN). The research proposes that hidden Markov model be adopted in the exercise of stock price forecasting.
Journal: Int. J. of Information and Decision Sciences
Pages: 39-59
Issue: 1
Volume: 14
Year: 2022
Keywords: stock forecasting; hidden Markov model; HMM; stock price; manufacturing firms; neural network; auto-regressive integrated moving average; ARIMA; mean absolute percentage error; MAPE; Nigerian Stock Exchange; NSE; forecast accuracy.
File-URL: http://www.inderscience.com/link.php?id=122721
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:1:p:39-59
Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Alizadeh Noughabi
Author-X-Name-First: Hadi Alizadeh
Author-X-Name-Last: Noughabi
Title: Testing the validity of Cauchy model based on the informational energy
Abstract:
In this article, a test statistic for testing the validity of the Cauchy model based on the informational energy is introduced. Consistency of our test is shown. Also, we show that the distribution of the test statistic does not depend on the location and scale parameters. Through a simulation study, we obtain the critical values of the test statistic and then the power of the test is computed by Monte Carlo method against different alternatives. The performance of the proposed test with some competing tests is compared. Our results show that our test is superior to the classical non-parametric tests and can apply to a testing problem in practice.
Journal: Int. J. of Information and Decision Sciences
Pages: 85-96
Issue: 1
Volume: 14
Year: 2022
Keywords: goodness of fit test; Cauchy distribution; informational energy; power of test; Monte Carlo simulation.
File-URL: http://www.inderscience.com/link.php?id=122722
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:1:p:85-96
Template-Type: ReDIF-Article 1.0
Author-Name: Nimisha Gupta
Author-X-Name-First: Nimisha
Author-X-Name-Last: Gupta
Author-Name: Mitul Kumar Ahirwal
Author-X-Name-First: Mitul Kumar
Author-X-Name-Last: Ahirwal
Author-Name: Mithilesh Atulkar
Author-X-Name-First: Mithilesh
Author-X-Name-Last: Atulkar
Title: Human decision making modelling for gambling task under uncertainty and risk
Abstract:
In this paper, modelling of human decision making process and comparison among various reinforcement learning (RL) techniques with utility functions has been performed. Iowa gambling task (IGT) is used to collect real time data to understand and model the decision making (DM) process involving uncertainty, risk or ambiguity. Performance of models is evaluated based on their mean square deviation (MSD) value. This helps to predict the probability of the next choice that lead to the selection of the advantageous deck as compared to disadvantageous one. Along with that, the deck selection pattern between male and female with the learning process of the participants were also analysed. By comparing the MSD value of various RL models, it is found that the MSD value of DM model consists of prospect utility (PU)-decay reinforcement learning (DRI) with trial dependent choice (TDC) rule is best.
Journal: Int. J. of Information and Decision Sciences
Pages: 15-38
Issue: 1
Volume: 14
Year: 2022
Keywords: human decision making; Iowa gambling task; IGT; reinforcement learning model; utility functions.
File-URL: http://www.inderscience.com/link.php?id=122723
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:1:p:15-38
Template-Type: ReDIF-Article 1.0
Author-Name: Hartrisari Hardjomidjojo
Author-X-Name-First: Hartrisari
Author-X-Name-Last: Hardjomidjojo
Author-Name: Marimin Marimin
Author-X-Name-First: Marimin
Author-X-Name-Last: Marimin
Author-Name: Suprihatin Suprihatin
Author-X-Name-First: Suprihatin
Author-X-Name-Last: Suprihatin
Author-Name: Rindra Yusianto
Author-X-Name-First: Rindra
Author-X-Name-Last: Yusianto
Title: A synergy of spatial perspective based non-numeric ME-MCDM and modified Dijkstra algorithm for optimal distribution route selection
Abstract:
The contribution of this paper is a new method synergising advanced non-numeric multi-expert multi-criteria decision-making (ME-MCDM) and modified Dijkstra algorithm with spatial perspectives. The selected route was determined by multiplying distance (D) in the classical Dijkstra algorithm with alternative values (AV) from non-numeric ME-MCDM using spatial perspective (S). In this new method, we provided the ratio values (R) for each spatial variable. The most optimal route (Rs) was determined by calculating the total alternative value (TAV) that was considered conflicting multi-criteria. The smallest TAV value is selected as the most optimal route. The results showed the new method provides a more reasonable and meaningful solution compared with the classical Dijkstra algorithm results. So, this new method can be used to determine the optimal distribution route selection which is more suitable for the agro-industrial sector. For further research, this method can be applied to optimise the supply and demand balance.
Journal: Int. J. of Information and Decision Sciences
Pages: 371-398
Issue: 4
Volume: 14
Year: 2022
Keywords: distribution route selection; non-numeric ME-MCDM; modified Dijkstra algorithm; spatial perspectives.
File-URL: http://www.inderscience.com/link.php?id=127456
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:371-398
Template-Type: ReDIF-Article 1.0
Author-Name: S. Ankitha
Author-X-Name-First: S.
Author-X-Name-Last: Ankitha
Author-Name: H.S. Sanjay
Author-X-Name-First: H.S.
Author-X-Name-Last: Sanjay
Title: Data mining-based analysis of the human activity in healthy subjects using smart phones
Abstract:
Human-activity-recognition (HAR) ascertains the nature of interaction with the surrounding environment. The present work quantifies the activities such as those of walking (WA), walking-upstairs (WU), walking-downstairs (WD), sitting (SI), standing (ST) and laying (LA) of 30 healthy subjects of age 19-48 years using accelerometer and gyroscope sensors embedded in Samsung Galaxy-S2 smartphone using data mining methods. Support vector machine (SVM), multiple layer perceptron (MLP), decision tree (DT), extra tree (ET), K-nearest neighbour (KNN), random forest (RF) and gradient boosting machine (GBM) techniques are used with and without linear discriminant analysis (LDA) for dimension reduction. The accuracy is seen to be higher with LDA. SVM (with C = 10, gamma = 0.001 with RBF kernel) provided the highest accuracy for both cases (SVM without LDA = SVM with LDA = 96%). However, the highest variation based on LDA was seen in DT (DT without LDA = 85% and DT with LDA = 95%). Such approaches can be extended in rehabilitative applications and virtual reality in the near future.
Journal: Int. J. of Information and Decision Sciences
Pages: 417-427
Issue: 4
Volume: 14
Year: 2022
Keywords: human activity recognition; accelerometer; gyroscope; linear discriminant analysis; LDA; rehabilitative engineering.
File-URL: http://www.inderscience.com/link.php?id=127457
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:417-427
Template-Type: ReDIF-Article 1.0
Author-Name: Ezzatollah Asgharizadeh
Author-X-Name-First: Ezzatollah
Author-X-Name-Last: Asgharizadeh
Author-Name: Ehsan Yadegari
Author-X-Name-First: Ehsan
Author-X-Name-Last: Yadegari
Author-Name: Fariba Salahi
Author-X-Name-First: Fariba
Author-X-Name-Last: Salahi
Author-Name: Mahdi Homayounfar
Author-X-Name-First: Mahdi
Author-X-Name-Last: Homayounfar
Author-Name: Amir Daneshvar
Author-X-Name-First: Amir
Author-X-Name-Last: Daneshvar
Title: Multiple criteria ABC classification: an accelerated hybrid ELECTRE-PSO method
Abstract:
ABC classification analysis categorises inventory items into predefined classes namely A, B and C. The limitation of the ABC system is that only one criterion is considered, however, as emphasised in the literature, the inventory classification is multi-criteria problem. So, this paper proposed a multiple criteria ABC inventory classification (MCIC) method integrating ELECTRE TRI with particle swarm optimisation (PSO) algorithm. Since, the application of ELECTRE TRI method requires to determine the preferences of decision makers (DMs) as parameter values, the solution process is very complex and time-consuming especially in large-scale problems. Tackling these difficulties, all ELECTRE TRI parameters are inferred from training data through a procedure using hybrid PSO algorithm, for accelerating the PSO, the variable position (VP) model is also proposed as an exploitation and variable exploration. Finally, the model applied to six inventory datasets and the results revealed high applicability of the proposed model to inventory classification problems.
Journal: Int. J. of Information and Decision Sciences
Pages: 325-344
Issue: 4
Volume: 14
Year: 2022
Keywords: inventory classification outranking relations; particle swarm optimisation; PSO; ELECTRE TRI.
File-URL: http://www.inderscience.com/link.php?id=127458
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:325-344
Template-Type: ReDIF-Article 1.0
Author-Name: Nita H. Shah
Author-X-Name-First: Nita H.
Author-X-Name-Last: Shah
Author-Name: Milan B. Patel
Author-X-Name-First: Milan B.
Author-X-Name-Last: Patel
Author-Name: Pratik H. Shah
Author-X-Name-First: Pratik H.
Author-X-Name-Last: Shah
Title: Inventory policies under fuzzy and cloud fuzzy environment
Abstract:
This article is an attempt to extend the classical economic order quantity (EOQ) model for deteriorating items under fuzzy and cloud fuzzy environment. Inventory parameters such as holding cost, purchase cost, ordering cost, demand rate and deterioration rate are considered as triangular fuzzy numbers as well as cloud triangular fuzzy numbers to develop fuzzy and cloud fuzzy models respectively. Yager's ranking method and De and Beg's ranking methods are used for defuzzification. A comparative study reveals the superiority of cloud fuzzy model over crisp and fuzzy model. Further, numerical example, graphical illustrations and sensitivity analysis are carried out for better understanding of the application of cloud fuzzy approach to inventory optimisation problem.
Journal: Int. J. of Information and Decision Sciences
Pages: 356-370
Issue: 4
Volume: 14
Year: 2022
Keywords: inventory; economic order quantity; EOQ; deterioration; cloud fuzzy number.
File-URL: http://www.inderscience.com/link.php?id=127459
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:356-370
Template-Type: ReDIF-Article 1.0
Author-Name: Frederick Pobee
Author-X-Name-First: Frederick
Author-X-Name-Last: Pobee
Author-Name: Thuso Mphela
Author-X-Name-First: Thuso
Author-X-Name-Last: Mphela
Title: E-commerce research in developing countries: a systematic review of research themes, frameworks, methods and future lines of research
Abstract:
This paper presents a systematic review of e-commerce adoption research on developing countries with a focus on the classification of literature and their associated themes, frameworks, research methodology for ten years. A total of 151 articles from 35 peer-reviewed journals from 2010-2019 were retrieved and used in the analysis. The findings reveal that the issues of attitude towards e-commerce adoption and governance issues (legal and regulatory policies) have been comparatively neglected, whereas issues of trust and satisfaction have gained much attention. Though there has not been a constant increase in e-commerce research in developing countries over the past ten years, a significant number of published studies used the qualitative approach as a method of inquiry as compared to quantitative and mixed methodologies. Also, the majority of e-commerce studies on developing countries have not been supported by theoretical frameworks and models. As a contribution, this paper provides an in-depth analysis of e-commerce adoption in developing countries showing the trends of research themes, methodologies, and frameworks. Implications for future research were discussed.
Journal: Int. J. of Information and Decision Sciences
Pages: 399-416
Issue: 4
Volume: 14
Year: 2022
Keywords: e-commerce; developing countries; systematic review; business-to-customer; B2C; e-commerce adoption; research frameworks; research methodologies.
File-URL: http://www.inderscience.com/link.php?id=127460
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:399-416
Template-Type: ReDIF-Article 1.0
Author-Name: Pedram Memari
Author-X-Name-First: Pedram
Author-X-Name-Last: Memari
Author-Name: Seyedeh Samira Mohammadi
Author-X-Name-First: Seyedeh Samira
Author-X-Name-Last: Mohammadi
Title: A multi-criteria location selection model based on fuzzy ANP and Z-number VIKOR methods: a case study
Abstract:
Initial investment for construction of a power plant is an important issue which technologies and methods are moving forward to minimise the total costs. Therefore, a power plant should be established in a region which will increase the reliability and efficiency with minimum total cost. In this study, location of a solar power plant is optimised with considering a set of criteria including environmental, economic, social and strategic aspects in which energy resource usage will be maximised along with the least cost and the economic growth of country. For this purpose, fuzzy ANP and <i>Z</i>-number VIKOR approaches are used to rank the 20 candidate cities in Iran. The obtained results indicate the efficiency and reliability of this study.
Journal: Int. J. of Information and Decision Sciences
Pages: 133-148
Issue: 2
Volume: 14
Year: 2022
Keywords: location optimisation; solar energy; fuzzy ANP; Z-number VIKOR; data reliability; decision making; MCDM approaches.
File-URL: http://www.inderscience.com/link.php?id=123629
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:2:p:133-148
Template-Type: ReDIF-Article 1.0
Author-Name: Samson Gebresilasie Gebrerufael
Author-X-Name-First: Samson Gebresilasie
Author-X-Name-Last: Gebrerufael
Title: Technical efficiencies and technical change gaps in Africa: application of DEA on African sectors input-output frameworks
Abstract:
This paper presents the African sectors' technical efficiencies and the technical change gaps. The non-parametric data envelopment analysis (DEA) is employed using the standard input-oriented BCC model. The technical coefficients of 25 sectors are examined using the IO tables of 2005 and 2013 taken from the Eora MRIO database (2013). In 2005 and 2013, the benchmark sector is found to be 'the financial intermediation and business activities sector'. The actual technical efficiency changes are observed between 2005 and 2013 as the technical coefficients of 2013 are found to be relatively smaller than that of 2005. However, they are found to be lower than the potential technical coefficients and therefore lost input savings. Simply, the average potential input savings in 2005 had the sectors employed the 2013's lowest technical coefficients is found to be 93.9%. Hence, the African sectors have been performing 'weak' in avoiding the wastage of inputs.
Journal: Int. J. of Information and Decision Sciences
Pages: 164-203
Issue: 2
Volume: 14
Year: 2022
Keywords: technical efficiency; mix-inefficiency; actual technical change; potential technical change; technical change gap; TCG; BCC model; data envelopment analysis; DEA; Africa.
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:2:p:164-203
Template-Type: ReDIF-Article 1.0
Author-Name: Cansu Ergun
Author-X-Name-First: Cansu
Author-X-Name-Last: Ergun
Author-Name: Sumeyra Elif Erdogan
Author-X-Name-First: Sumeyra Elif
Author-X-Name-Last: Erdogan
Author-Name: Gokhan Aldemir
Author-X-Name-First: Gokhan
Author-X-Name-Last: Aldemir
Author-Name: Ferhan Cebi
Author-X-Name-First: Ferhan
Author-X-Name-Last: Cebi
Title: Examination of gym centre design criteria using multi-criteria decision analysis methodologies
Abstract:
Designing a gym centre and selecting its atmospheric elements are time-consuming and difficult to change. Therefore, the aim of our study is to provide a beneficial and different perspective for operators who are considering designing a gym. Our study starts with a participatory observation in order to examine consumer behaviour in the natural state after the studies in the literature are examined. An interview and a survey study are conducted to define the crucial criteria for the consumer in the gym. A hierarchy is created, and a pairwise comparison is made to illustrate the importance levels. Accordingly, analytical hierarchy process (AHP) is applied and the criteria are sorted according to their importance. Different concepts are formed by giving different values to the criteria. The concepts with the highest score are determined by the concept selection matrix and their architectural designs are made by programs. The most optimal design is determined by the concept test.
Journal: Int. J. of Information and Decision Sciences
Pages: 345-355
Issue: 4
Volume: 14
Year: 2022
Keywords: multi-criteria decision making; gym centre design; analytical hierarchy process; AHP; consumer behaviour.
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:4:p:345-355
Template-Type: ReDIF-Article 1.0
Author-Name: Fernando Escobar
Author-X-Name-First: Fernando
Author-X-Name-Last: Escobar
Author-Name: João Varajão
Author-X-Name-First: João
Author-X-Name-Last: Varajão
Author-Name: Nilton Takagi
Author-X-Name-First: Nilton
Author-X-Name-Last: Takagi
Author-Name: Ulysses Almeida Neto
Author-X-Name-First: Ulysses Almeida
Author-X-Name-Last: Neto
Title: Multi-criteria model for selecting project managers in the public sector
Abstract:
To assure effectiveness in the management of projects, it is required that project managers have the right competencies, according to the context and characteristics of each project they are involved. Based on several competencies frameworks (including PMI's PMCDF, IPMA's ICB, APM's CF, and AIPM's PCSPM), this paper proposes a unified multi-criteria model to be used as a decision-making tool for selecting the most suitable managers and defining competencies pathways for public sector projects. A hierarchical structure comprising weighted elements related to behavioural, management, and contextual/organisational competencies is proposed. For researchers, the presented model of competencies enables a better understanding of the phenomenon and can be used to structure further research in other contexts than the public sector. It is also a valuable tool for practitioners and project management offices since it allows comparing the candidates for managing a project using an organised and rigorous process anchored on empirically well-grounded criteria.
Journal: Int. J. of Information and Decision Sciences
Pages: 205-242
Issue: 3
Volume: 14
Year: 2022
Keywords: project manager; project management; selection; decision; analytic hierarchical process; AHP; competencies; frameworks; public sector; Brazil.
File-URL: http://www.inderscience.com/link.php?id=125168
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:3:p:205-242
Template-Type: ReDIF-Article 1.0
Author-Name: R.P. Tripathi
Author-X-Name-First: R.P.
Author-X-Name-Last: Tripathi
Author-Name: Sachin Mishra
Author-X-Name-First: Sachin
Author-X-Name-Last: Mishra
Title: Development of optimal ordering strategy, with power demand and changeable deterioration under allowable delay in payments
Abstract:
In the present competitive trade world, each business would like to compose extra income by means of less investment. In view of an economic ordering quantity (EOQ) system by variable deterioration our objective is to learn the effect of fixed lifetime items under trade credits. At the present scenario, in any selling operation, a broker regularly offers the retailer a permissible delay phase. Some commodities like vegetables, fruits, liquids, pharmaceuticals, and volatile liquids, deteriorate continuously up to termination dates. This study considers an inventory model for power demand with deterioration at their highest life time. Two different cases are discussed, including a sub-case. Mathematical formulation is given for two unlike circumstances to demonstrate the proposed model. Condensed Taylor's series is applied in favour of exponential terms for judging blocked form explanation. Numerical designs and sensitivity investigation are made available to reveal the model.
Journal: Int. J. of Information and Decision Sciences
Pages: 289-309
Issue: 3
Volume: 14
Year: 2022
Keywords: inventory; expiration; spoilage; trade credit; power demand.
File-URL: http://www.inderscience.com/link.php?id=125169
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:3:p:289-309
Template-Type: ReDIF-Article 1.0
Author-Name: Noor Saifurina Nana Khurizan
Author-X-Name-First: Noor Saifurina Nana
Author-X-Name-Last: Khurizan
Author-Name: Adli Mustafa
Author-X-Name-First: Adli
Author-X-Name-Last: Mustafa
Author-Name: Hamidah Abd. Hamid
Author-X-Name-First: Hamidah Abd.
Author-X-Name-Last: Hamid
Title: Three-level multi-criteria analysis for measuring the efficiency of grant awarded research projects
Abstract:
This paper is written for the purpose of demonstrating a new way of applying analytic hierarchy process (AHP) and data envelopment analysis (DEA) in examining the performance of university funded academic research projects. Three stages of multi-criteria analysis were employed in this study involving AHP, DEA and preferential voting. AHP methodology was employed to construct a four-level hierarchy system to group the evaluation criteria and generate the related priority score. Based on the priority score generated from AHP, a score for the output data was then calculated and standardised. The original DEA model was then used to find the efficiency score for each research grant by solving its multiple objective problems. Later, DEA analysis was conducted using different combinations of output to distinguish the research grant projects that fully utilised its input to consistently produce the output. Further, an alternative way of producing an overall ranking was explored by employing the methodology of preferential voting using DEA. A case study of Universiti Sains Malaysia (USM) funded research projects is presented to demonstrate the application with real life data.
Journal: Int. J. of Information and Decision Sciences
Pages: 115-132
Issue: 2
Volume: 14
Year: 2022
Keywords: data envelopment analysis; DEA; analytic hierarchy process; AHP; preferential voting; R%D; sponsored research; higher education; efficiency analysis.
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:2:p:115-132
Template-Type: ReDIF-Article 1.0
Author-Name: C.P. Waduge
Author-X-Name-First: C.P.
Author-X-Name-Last: Waduge
Author-Name: N.C. Ganegoda
Author-X-Name-First: N.C.
Author-X-Name-Last: Ganegoda
Author-Name: D.C. Wickramarachchi
Author-X-Name-First: D.C.
Author-X-Name-Last: Wickramarachchi
Author-Name: R.S. Lokupitiya
Author-X-Name-First: R.S.
Author-X-Name-Last: Lokupitiya
Author-Name: G.H.J. Lanel
Author-X-Name-First: G.H.J.
Author-X-Name-Last: Lanel
Title: A group of representative measures of a set of time series and its decision support: a trial for dengue incidence data of Sri Lanka
Abstract:
Partitioning a time series into a set of subseries is required in some temporal investigations. Here, a cross-sectional approach is implemented for such subseries to design representative series. The series containing point-wise arithmetic means (mean series) is somewhat the simplest choice, when such a representative is required. However, it may not acquire important temporal variations. In this paper, several alternatives are proposed based on a class of measures called ultimate tamed series (<i>UTS</i>). Here, an operation called <i>taming</i> is implemented upon time series and it is non-commutative and non-associative. The taming is carried out with the aid of discrete Haar wavelet, which is subscribed by both point-wise concern and local trend given by an adjacent point. We conducted a trial for this using a dataset of disease incidence. Better-informed decisions are possible via the proposed architecture of processing time series data.
Journal: Int. J. of Information and Decision Sciences
Pages: 260-288
Issue: 3
Volume: 14
Year: 2022
Keywords: time series; Haar wavelet; taming; representative series; decision support system; dengue incidence; Sri Lanka.
File-URL: http://www.inderscience.com/link.php?id=125170
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:3:p:260-288
Template-Type: ReDIF-Article 1.0
Author-Name: Firas AlOmari
Author-X-Name-First: Firas
Author-X-Name-Last: AlOmari
Title: Does a doctor's skill influence patient satisfaction, loyalty and compliance in low-medium income countries?
Abstract:
The purpose of this research paper is to investigate the impact of doctor's skills on patient's satisfaction, loyalty and behavioural compliance in Syrian healthcare setting. Convenience sampling method was used to select 301 patients from six hospitals, in the Syrian capital Damascus, to complete the questionnaire. The validity and reliability of the proposed model had been confirmed. Doctor's skill is a multidimensional construct that consists of three dimensions: doctor's competence, listening skill and explanation skill. The statistical analysis indicated that doctor's skills construct has a significant positive direct effect on patient satisfaction, loyalty and compliance. In addition, patient satisfaction has a partial mediating effect between a doctor's skills and patient loyalty. However, a satisfied patient with the perceived clinical service does not secure medication compliance. In other words, patient satisfaction does not mediate the relationship between doctor skills and patient's compliance. This study introduces noticeable contributions to the healthcare marketing and management in Syria.
Journal: Int. J. of Information and Decision Sciences
Pages: 149-163
Issue: 2
Volume: 14
Year: 2022
Keywords: doctor's skills; patient satisfaction; patient loyalty; medication compliance; Syrian healthcare.
File-URL: http://www.inderscience.com/link.php?id=123635
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:2:p:149-163
Template-Type: ReDIF-Article 1.0
Author-Name: Koray Cirak
Author-X-Name-First: Koray
Author-X-Name-Last: Cirak
Author-Name: Hür Bersam Sidal Bolat
Author-X-Name-First: Hür Bersam Sidal
Author-X-Name-Last: Bolat
Title: Analysis of the relationship between sustainability and software performance
Abstract:
Sustainability problems are getting more and more critical and increasingly threatening human life day by day. Software, which is developing rapidly and entering into every aspect of our lives, is one of the most fundamental components of the technological society. The widespread use of software applications and limited natural resources has led researchers to focus on research that will ensure sustainability in the software development process. In this study, we conducted a questionnaire study concerning the sustainability factors that affect the software development process. Then the effect of these factors and the level of education, age, and experience of the people involved in the software development process on the software performance were investigated. As a result, it has been determined that the factors affecting the software development process in terms of sustainability and the descriptive attributes of the individual have an effect on software performance.
Journal: Int. J. of Information and Decision Sciences
Pages: 310-323
Issue: 3
Volume: 14
Year: 2022
Keywords: sustainability; software development process; software performance; path analysis.
File-URL: http://www.inderscience.com/link.php?id=125174
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:3:p:310-323
Template-Type: ReDIF-Article 1.0
Author-Name: Zahra Faraji
Author-X-Name-First: Zahra
Author-X-Name-Last: Faraji
Title: Investigate the causal effect of diversification strategy on risk-adjusted performance using Bayesian additive regression trees
Abstract:
This paper aims to develop a hybrid causal model based on the inverse probability weighting (IPW) and Bayesian additive regression trees (BART) as an advanced machine learning technique. IPW relies on parametric logistic regression model to estimate the propensity scores, however, the required assumptions and pre-specified relationships degrade its application for many real-world problems. We use BART to model the propensity scores to mitigate the limitations of standard IPW model. In addition, we apply Bayesian model to estimate the average treatment effect (ATE) in the pseudo-population instead of simple regression to provide posterior predictive distribution of ATE. Using a simulation study, we show that our model corrects the bias and RMSE introduced by the original IPW model and can recover the true ATE. Lastly, we apply the new IPW model to investigate the causal effect of diversification strategy on risk-adjusted performance for US public firms. The results show diversification can help firms to improve their performance even after considering the associated risk.
Journal: Int. J. of Information and Decision Sciences
Pages: 97-114
Issue: 2
Volume: 14
Year: 2022
Keywords: causal inference; diversification strategy; risk-adjusted performance; inverse probability weighting; machine learning; Bayesian additive regression trees; BART.
File-URL: http://www.inderscience.com/link.php?id=123642
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Handle: RePEc:ids:ijidsc:v:14:y:2022:i:2:p:97-114