International Journal of Applied Decision Sciences (35 papers in press)
Strategic Intentions Guided by Individual Values: Evidence from Business Owners
by Pavel Prokushenkov, Mike Wahl
Abstract: This paper aims to research the relationship between business owners strategic intentions underlined by attitudes and their basic human values in the form of motivational types. The study focused on business owners attitudes towards gaining power opposed to revenue generation, profit withdrawal time horizon, investment in research and development, adherence to ethical standards, and filling a role in society. Unfolding the association between strategically significant attitudes of business owners and their personal values is crucial. This is a cross-sectional survey study using Spearmans rank correlation analysis. Purposive sampling was conducted to collect data based on the authors personal network over a period of five years through a questionnaire among 682 business owners from 39 countries. The results showed that business owners strategically significant attitudes related to their intentions can be not only value-expressive and value-ambivalent as found in previous studies, but also value-unmanifested and value-quasi-manifested. The theoretical and practical implication of the paper is that studying the relationship between strategic intentions and individual values applying a normative approach weakens the validity of the findings.
Keywords: business owners; strategic intentions; attitudes; basic human values; image theory; portrait value questionnaire; PVQ; strategy formation.
Decision Support System for Feasibility Investment of Virgin Coconut Oil Agroindustry
by Meilizar Meilizar, Ridha Luthvina, Nurike Oktavia, Putranesia Putranesia
Abstract: Agroindustry investment issue arises when the natural dataset and economics analysis is not involved in decision making. Similarly, investment in processing coconut yields into virgin coconut oil (VCO) provides a promising future by applying agriculture 4.0. This paper presents decision support system which provides investment decision toward new VCO agroindustries. The contribution lies in the improvement management system with observed several aspects before the investment is carried out. The approach combines nature dataset and economics analysis. The methods cover spatial analysis, location quotient, capacity production planning, and financial analysis. The result presents four study case of VCO investment in Pariaman districts in West Sumatera Indonesia, which decision about feasibility investment of VCO agroindustry in selected potential area. This DSS application permits the investor to be facilitated with an accurate and fast decision. Although, the DSS requires futures improvement with a fully online application without an overlay process.
Keywords: decision support system; feasible investment; virgin coconut oil; agroindustry; capacity production planning.
Performance of Max-HEWMAMS Control Chart for Simultaneous Monitoring of Process Mean and Variability in the Presence of Measurement Errors
by Maziar Saemian, Mohammad Reza Maleki, Ali Salmasnia
Abstract: In recent years, the simultaneous monitoring of the process mean and variability has received increasing attention in statistical process monitoring (SPM). Most of control charts in this context have been carried out under the assumption of no measurement errors. This paper develops the Max-HEWMAMS chart for simultaneous detection of mean and variance shifts when the measurements are imprecise due to the gauge inaccuracy. Multiple measurements approach is employed to reduce the impact of measurement errors on detecting ability of Max-HEWMAMS chart. Extensive simulations are conducted to explore the impact of measurement errors on run length properties of Max-HEWMAMS chart. The results indicate under different out-of-control scenarios including mean, variance, and joint shifts, the measurement error has an undesired impact on detecting efficiency of the Max-HEWMAMS chart. It is also confirmed that taking multiple measurements per item improves the performance of Max-HEWMAMS chart when the observations are contaminated with measurement errors. Finally, the adverse impact of gauge imprecision on sensitivity of the Max-HEWMAMS chart is probed by a real-life data example.
Keywords: Max-HEWMAMS control chart; measurement errors; multiple measurements approach; simultaneous monitoring; run length.
The Strategic Impact of Information Systems in Organizations: An Empirical Study
by Renato Lopes Da Costa, Ana Cunha, Rui Gonçalves, Leandro Ferreira Pereira, Álvaro Dias, Rui Vinhas Da Silva
Abstract: In a volatility, uncertainty, complexity, and ambiguity world, having up-to-date information with a high of quality is one of the main assets that organisations can have, enabling them to choose the best strategies that will grant competitive advantage, resilience and consequently drive to success. The present research aims to understand the contribution of information systems (IS) for strategy, what are the benefits that organisations can achieved through the effective implementation of IS and in which resources organisations should invest, as way to maximise those benefits and to mitigate the risks associated with IS implementation. The methodology uses data gathered through a questionnaire and analysis is done using structure equation modelling. The results obtained show that the IS have a positive impact in organisations strategy and that the investments made by organisations in IS implementation are influenced by the benefits and risks perceived by using IS.
Keywords: information systems; organisational strategy; benefits of IS; risks of IS; investments in IS.
Multi-Dimensional Classification of Wind Turbine Spare Parts in a Multi-Echelon Inventory System
by Bin Yan, Yifan Zhou, Zhaojun Li, Chaoqun Huang, Jingjing Liu
Abstract: Optimising inventory management of spare parts is important for wind power companies to reduce operation and maintenance (O&M) costs. We summarise the indicators for wind turbine spare parts classification by analysing O&M management characteristics of the wind power industry. Spare parts of wind turbines are classified based on three dimensions: value, demand, and importance. The existing multi-dimensional spare parts classification methods discretise the indicator on each dimension. However, we use the K-means algorithm to classify spare parts based on normalised indicators. The proposed classification method significantly decreases the reliance on expertise and information loss caused by indicator discretisation. The proposed multi-dimensional classification method is validated using a practical case study of wind turbine spare parts classification, demonstrating that the proposed method can obtain reasonable classification that simultaneously stabilises the service level and reduces inventory costs.
Keywords: multi-echelon inventory; wind turbine spare parts; normalisation; multi-dimensional classification.
Multi-intervals robust mean-Conditional Value-at-Risk portfolio optimization with conditional scenario reduction technique
by Tahereh Khodamoradi, Maziar Salahi, Ali Reza Najafi
Abstract: In this paper, we study mean-conditional value at risk (mean-CVaR) portfolio optimisation with cardinality constraints and short selling under uncertainty. To reduce the level of conservatism, instead of single uncertainty interval, multi-intervals uncertainty sets are considered that are obtained by an efficient scenario reduction technique. It is proved that the proposed robust mean-CVaR model with cardinality constraints and short selling is equivalent to a mixed integer linear programming problem. Finally, using historical data on the S&P index for 2018, we evaluate the efficiency of the proposed models using CVX software in MATLAB. The results show that robust model has relatively low conservatism under multi-intervals uncertainties.
Keywords: conditional value-at-risk; scenario reduction; robust optimisation.
Evaluation of cloud computing risks using an integrated fuzzy-ANP and FMEA approaches
by Ataallah Yazdani, Abbas Keramati, Ozgur Turetken, Yazwand Palanichamy
Abstract: Despite the considerable benefits of cloud-based services and their effect on the reduction of total investments in information technology (IT) infrastructures, there still exist a plethora of concerns regarding the potential risk of this relatively new method of resource outsourcing. Due to the diversity of activities in the risk management process, it is essential to develop an innovative framework for controlling and streamlining relevant processes. Such processes include the identification, ranking, and determination of relevant exposure strategies and risk responsiveness strategies. The proposed framework developed in this study was based on the risk management process phase of the PMBOK model to analyse the collected data via fuzzy analytical network processing and failure mode effective analysis methods. A survey was then drafted with participating IT experts. Results demonstrate that the three most important risks are data confidentiality, data integrity and reliability. Furthermore, 117 risk-responsiveness solutions such as auditing the scope of access to information, using relevant techniques to control data integrity, and implementing appropriate training programs for the support team within the organisation were recognised and ranked to suggest the most appropriate remedial strategies that extensively mitigate against identified risks.
Keywords: cloud computing; risk management framework; failure mode effective analysis; project management body of knowledge.
Measurement and determinants of innovation efficiency and its impact on asset prices
by Kailin Zeng, Fangyan Li, Ebenezer Fiifi Emire Atta Mills
Abstract: This study adopts a dynamic slack-based DEA framework to estimate the innovation efficiency of the exchange-listed companies that are at the centre of Chinas innovation network. On average, these companies have low efficiency scores, signalling an over-investment in fixed assets, R&D, and excessive subsidies received from the government, along with a shortage of patent output. A Tobit-based analysis indicates that market share of sales, overvaluation, and profitability are positively linked to innovation efficiency, while excess analyst coverage can impede corporate innovation. Moreover, innovation efficiency is positively associated with stock returns from both cross-sectional regression tests and portfolio strategies.
Keywords: DEA model; dynamic SBM model; innovation efficiency; determinants; Tobit regression; Fama-MacBeth cross-sectional test; stock returns; portfolio strategies; China.
The Internet-of-Things and Human Sustainability between theory and practice. Is it time to bridge the gap
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.
Business case the state-of-the-art
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.
An efficient constructive heuristic for the cutting stock problem applied in a foam mattress industry
by Mariem Baazaoui, Souhir Elleuch, Hihem 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.
Treatment Process Conformance Checking of Patients (with Sepsis and Septic Shock) in Compliance with SSC and WMA using Fuzzy Miner Algorithm in Fluxicon Disco
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.
Computational Efficiency in Sports Talent Identification - A Systematic Review
by Naveed Jeelani Khan, Gulfam Ahamad, Mohd Naseem, Shahab Saqib 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 to 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.
A Multistage sustainable inventory model with backorder, fuzzy parameters and decision variable for deteriorating items with imperfect production and reliability.
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 retailers 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.
Production policy for an integrated inventory system under cloudy fuzzy environment
by S. V. Singh Padiyar, Naveen Bhagat, S.R. Singh, Neha Punetha, Himani Dem
Abstract: This article highlights on optimal strategy for a supply chain model for defective manufacturing process for deteriorating items with cloudy fuzzy inflation. The system considers two different consumption rates at different time periods for supplier. The imperfection during production causes ambiguity for 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 as on a proposal which helps the supplier to deliver the shipment fast and safely. The model has been developed over every likely expense incurred for supply chain system, i.e., fixed and variable transportation costs, labour cost, cost to abolish 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.
Blockchain Applications and Challenges for Supply Chain and Industry 4.0: A Literature Review
by Kuanchin Chen, Damodar Y. Golhar, Snehamay Banerjee
Abstract: Application of blockchain technology to facilitate a flexible, reliable, and efficient supply chain is an emerging phenomenon. Motivated by its potential use, researchers have started investigating blockchains use for managing complex global supply chains. In addition to established supply chain performance criteria, Industry 4.0 requires a more data driven supply chain (SC), where data collection, transmission and processing capabilities are embedded in smart products. However, review articles of blockchain in SC primarily report descriptive statistics, but do not provide sufficient evidence on how topics are studied together. This article discusses the role of blockchain in SC and presents a methodology to study co-occurrence of blockchain topics in SC. Three most often researched topics identified are transparency/traceability, transaction related issues and tracking. Using a machine learning algorithm, we further examine trends of co-occurrence among various topics of interest and identify gaps in existing literature and point to future research directions.
Keywords: blockchain; Industry 4.0; Supply chain 4.0; supply chain management.
Human resource management at the enterprise during the development of new forms of employment
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.
Decision Biases in the Capacity Expansion Problems with Product Importance Perceptions
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 Cachons (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.
K-means analysis of construction projects in port waterfronts
by Iñigo L. Ansorena
Abstract: Choosing the best construction project on the citys 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.
Performance measurement of Taiwan hotels with a hierarchical Network DEA With Shared Inputs
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 Taiwans 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; Taiwans international tourist hotels; Taiwan.
Artificial Intelligence Based on MCDM for the Board Game of the Royal Game of Ur
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 players 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.
An Intelligent Financial Management System for optimal resource allocation in an organization
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 companys future free cash flows.
Keywords: data analytics; machine learning; financial forecasting; cash flow forecasting; financial analysis; risk asymmetry analysis.
Big Data Analytical Capability and Firm Performance: Moderating effect of Analytics Capability Business Strategy Alignment
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.
Research on financing availability of small and micro logistics enterprises in China
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.
Factors predicting customer satisfaction in online hotel booking using machine learning technique. Evidence from developing countries.
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.
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
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.
Impact of Covid-19 on Systemic Risk for Indian Financial Institutions
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.
FE-TAC: An Effective Document Classification Method Combining Feature Extraction and Feature Selection
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.
A TWO PHASE APPROACH BASED ON MULTI OBJECTIVE PROGRAMMING AND SIMULATION FOR PHYSICIAN SCHEDULING IN EMERGENCY ROOMS
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.
Investor behaviour in an environment of uncertainty: the impact of persuasion on investor decisions
by Cleber Broietti, Suliani Rover, Graça Maria Do Carmo Azevedo
Abstract: The objective of this study is to investigate the impact of investor persuasion in an environment of uncertainty. The experimental method was used, with 576 non-professional investors. The experiment used a 2 × 2 factorial, for these six different scenarios were elaborated with the manipulation of the following variables: environment of uncertainty, characterised by risk and ambiguity; and, the persuasive argument of authority. The analysis technique used was the binomial test. The results showed that the investors' choices are more persuasive in: 1) risky investments than in investments with ambiguity; 2) reports of analysts whose element of authority is present than in reports in which they do not present persuasive elements; 3) environments of uncertainty. The research contributed to the literature on investor behaviour when exposed to ambiguity and risk.
Keywords: investor behaviour; environment of uncertainty; investor decision; persuasion; ambiguity; risk; authority; binomial test.
Extended strategic alignment model for information systems governance
by Khaoula Benmoussa, Majida Laaziri, Abdelrhani Bouayad, Mohammed Bennaser, Ahmed Mouchtachi, Abir El Yamami
Abstract: The information systems (IS) of universities are at the heart of changes of various origins: the evolution of the processes they support and the evolution of information technologies (IT). Studies have shown great interest in strategic alignment to the private sector rather than to the public sector especially in universities. Moreover, through a review of the literature, it became apparent that there is no formal model of strategic alignment in universities. Therefore, this paper aims to take an exploratory approach to: 1) understand strategic alignment; 2) evaluate its implementation within universities; 3) adapt its mechanisms by proposing a new model of strategic alignment in universities based on the most widely used model (SAM). The result shows that the implementation of this proposed model can help universities achieve these goals and improve their competitiveness and effectiveness.
Keywords: strategic alignment model; SAM; IS governance; university strategic alignment; information system; SAM; information technology.
Elucidating cause-and-effect relationships of components affecting talent absorbing organisations
by Mohammad Hakkak, Mohammad Hossein Azadi, Khaled Nawaser, Haniruzila Hanifah, Ali Vafaei-Zadeh
Abstract: Organisations are required to identify, recruit, and foster talented individuals in order to optimise their own capacity in achieving business outcomes and build a competitive advantage in the future. The present study aimed at elucidating cause-and-effect relationships of talent absorption components using type-2 fuzzy set extension of the decision-making and trial evaluation (DEMATEL) method in the electronics industry. Following the review of the research literature and surveys of expert opinions, 22 main components in three 'strategic', 'retention-related', and 'organisational' dimensions were identified. After developing and distributing the study questionnaire among experts, the cause-and-effect relationships of these components were explained using type-2 fuzzy set extension of the DEMATEL method. The results revealed that the 'retention-related' dimension was the effective one and the 'strategic' and 'organisational' dimensions had been affected.
Keywords: talent; talent absorbing organisations; type-2 fuzzy DEMATEL method; electronics industry.
Unrelated parallel dedicated machine scheduling with sequence dependent setup times: an application in a textile company
by Yonca Erdem Demirtas
Abstract: This study deals with a real-life scheduling problem in a textile company that produces hygienic fibres. The addressed problem is a particular case of unrelated parallel dedicated machine scheduling problems with sequence-dependent setup times. The company has two unrelated production lines. Three different types of product families with due dates need to be scheduled onto the lines. The production planning problem is solved by minimising the total tardiness and total sequence-dependent setup costs. Permutation-based solution representation is used and an initial solution is generated via dispatching rules to start searching from a promising point. Powerful single solution-based local search algorithms such as 2-opt, swap, and insertion are used to improve the solution. Finally, the proposed solution technique is developed as a decision support system made available to the company for easy and efficient production planning.
Keywords: scheduling; unrelated parallel machines; sequence-dependent setup time; local search.
Preferential voting in the presence of undesirable voters
by Mehdi Soltanifar, Hamid Sharafi
Abstract: Multi-attribute decision-making (MADM) methods have always been considered by managers as a tool to support decision making. One of the best methods is to select based on expert opinions. In fact, providing models for aggregating the votes of voters in the group decision making is a subject that has always attracted researchers' attention. We aimed, in this paper, to present a model for aggregating the votes of voters who have been divided by the decision maker (DM) into two groups of desirable and undesirable ones. The proposed model has been explained by presenting its application while a numerical example and case study have also been provided.
Keywords: preferential voting; undesirable voter; data envelopment analysis; DEA; group decision making; multi-attribute decision making; MADM.
A novel data cluster algorithm based on linear regression and residual analysis for human resource management
by Hengxiaoyuan Wang
Abstract: Human resource management has become an important part of enterprise management. How to select high-quality talent and how to allocate corresponding talent to appropriate work has become an increasingly acute problem. Traditional data cluster methods cannot effectively solve the above problem due to the high-dimensional data. Therefore, we propose a novel data cluster algorithm based on linear regression and residual analysis for human resource management. Improved hybrid entropy weight attribute similarity is adopted for measuring the similarity between objects. The proposed local density calculation method based on k-nearest neighbour (KNN) and Parzen window is used to calculate the density of each object. Then, we utilise the linear regression and residual analysis to select the clustering centre points quickly and automatically, which can eliminate the subjectivity of artificial selection. A new clustering centre objective optimisation model is proposed to determine the real clustering centre. Through theoretical analysis and comparative experiments on artificial data sets and real data sets, it shows that the proposed cluster algorithm can overcome the defects of the original algorithms, and achieve better clustering effect and lower computation time than state-of-the-art methods.
Keywords: human resource management; data cluster; linear regression; residual analysis; clustering centre objective optimisation model.