International Journal of Applied Decision Sciences (32 papers in press)
An empirical study on Internet-based false news stories: experiences, problem awareness, and responsibilities
by Sven Grüner
Abstract: The Internet has significantly reduced the marginal costs of generating and disseminating information. The human information portfolio includes correct and incorrect information. False news stories constitute a challenge for our democracy. Therefore, scientists are increasingly interested in redesigning the information ecosystem. This paper addresses the problem awareness of university students in the realm of false news stories. With the help of a questionnaire, we seek for interesting correlations to generate hypotheses that can be analysed in further studies with new data (i.e., exploratory study).
Keywords: Study type: exploratory; information economics; false news stories; information ecosystem; social net-work; institutional economics.
A method for partner selection of product development teams using the synergy requirements of product architecture
by Zhongfeng Hu, Minglun Ren
Abstract: Developers with better synergy is important for the formation of cross-functional product development teams. While extant research focuses on the coordination qualification of candidates, the synergy requirements of product architecture is overlooked. As a solution to this problem, a novel approach reinforced by the product architecture is proposed, where ideal synergic matrix (ISM) is derived from the product architecture to express its synergy requirements, real synergic matrix (RSM) is extracted from the collaborative relationships among different candidates, coordination deficit is proposed to characterise the satisfaction degree of the synergy requirements according to the matching level between ISM and RSM. To solve the model, a hybrid GA-PSO algorithm is developed. The experiment results show that our method can guarantee satisfactory and high quality partner selection for the actual product development scenario.
Keywords: product architecture; partner selection; product development; synergic effect; coordination deficit.
Sustainable Performance Evaluation: A Practical Approach based on Fuzzy Best-Worst Method and Fuzzy Inference System
by Abdolreza Azadmanesh, Mohammad Reza Maleki
Abstract: Taking into account sustainability perspective, this paper proposes a practical integrated approach based on fuzzy best-worst method (BWM) and fuzzy inference system (FIS) for performance evaluation. In the proposed approach, the criteria are determined based on three aspects, namely economic, social, and environmental ones; and the corresponding weights are calculated using fuzzy BWM. Moreover, the performance of the company under study is evaluated for each of the sustainability aspects. Finally, an FIS is developed based on the knowledge of experts and the final score of the intended company is accordingly calculated. A real-world example using the knowledge of eight experts of Parsian Gas Refinery Company in Iran indicates the efficiency and effectiveness of the proposed approach.
Keywords: sustainable performance evaluation; best-worst method; fuzzy inference system; FIS; fuzzy theory; sustainability.
Supply Chain Value Co-creation and Flexibility Management Decisions Taking Supply Risk into Account
by Min Yang
Abstract: Value co-creation provides an effective way to prevent and control risks in supply chain enterprises. By building a three-stage supply chain game decision model under risk conditions, rational derivation is made on the dynamic relationship between supply chain flexibility management costs, flexible benefits, unit product costs, and supply chain value creation to investigate conditions required to achieve supply chain value co-creation and optimal flexibility management. Some useful conclusions were finding that the functional relationship between flexibility management cost and supply chain value co-creation is represented as the envelope curve of optimal supply chain value creation and supply chain risks, flexible benefit, and unit product cost exert a significant impact on supply chain flexibility management effect. This article proposes that under certain supply chain risks, companies should maximise the marginal benefits of supply chain flexibility management inputs, so that supply chain flexibility management inputs show positive benefits rather than cost effects.
Keywords: supply chain risk; supply chain flexibility; value creation.
Ranking Risk Attitudes Using an Integrated AHP-TOPSIS Approach
by Lubna Obaid, Haneen Abu Zaid, Doraid Dalalah, Salhah Alhassani, Fouzeya Albastaki, Tania El Khalil
Abstract: Due to the ambiguity between risk attitudes, this study aims at ranking the different risk attitudes considering the factors that affect the behaviour of the decision-makers. Both the technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) are employed to address the characteristics of risk attitudes aiming to highlight the criteria significance and finally to rank the most impactful risk attitude. It was found that regret aversion and risk aversion attitudes have higher impact in real life decision-making problems. In contrast, the maximin and maximax risk attitudes have the lowest importance. Risk seeking and regret aversion attitudes demonstrated the highest importance using TOPSIS of equal-weights while the importance of loss aversion and regret aversion have the highest for the AHP-TOPSIS approach. The results of this study can be beneficial for decision-makers who encounter a variety of risk attitudes in their decision problems.
Keywords: TOPSIS; regret aversion; analytical hierarchy process; AHP; risk attitudes; multi-criteria decision-making; MCDM.
Operational Values of Information Technology and Green Initiatives: The Stochastic Production Frontier Approach
by Chia-Ching Chou, Winston Lin, Chieh Lee, Zhuang Qian, Xinyuan Tao
Abstract: Previous studies regarding environmental issues in the field of information technology (IT) focused on the direct impact of IT on the environment and indicated a trade-off relationship between them. This study employs the resource-based view (RBV),theory of production, and stochastic production frontier (SPF) approach to empirically investigate the operational value creating power of IT and green initiatives at firm, industry, and sector level, providing evidence that the presence of IT and green initiatives can positively contribute to operational performance. Our findings suggest that the complementarity phenomenon exist between green initiatives and IT. Furthermore, this study shows detailed information on how IT and green initiatives contribute to operational performance in different ways, provides managers and decision makers a guideline for IT and green initiative investment decision-making, and develops a more realistic stochastic production frontier model for researchers to apply.
Keywords: information technology; green initiative; sustainability; stochastic production frontier: SPF: approach; theory of production.
Total Interpretive Structural Modelling of Machine learning Enablers in the Healthcare System
by Pooja Gupta, Ritika Mehra
Abstract: The primary objective of this research is to build a total interpretive structural model of different enablers, vital to implement machine learning in the healthcare system. This study begins by implementing the progressive methodology of TISM to investigate the mutual dependence among ML enablers in the healthcare system. Further, the classification of enablers has been done based upon the driving power and dependence. A structural model of ML enablers has also been developed using the TISM procedure. Ten enablers of ML implementation have been recognised from the literature and experts opinions. TISM is applied to develop a six-level hierarchical structural model. The proposed study encourages decision-makers to focus on the necessary steps to implement these enablers. Enablers at the bottom of the TISM hierarchy are the ones with reliable driving power and these the lowest level enablers need more consideration from top administration.
Keywords: machine learning; interpretive structural modelling; healthcare; MICMAC; total interpretive structural modelling; medical models; driving power; dependence; enablers.
An EOQ model for non-instantaneous deteriorating items with time dependent quadratic rate, linear holding cost and partial backlogging rate under trade credit policy
by Babangida Bature, Yakubu Mamman Baraya
Abstract: In this article, an EOQ model for non-instantaneous deteriorating items with two phase demand rates, time dependent linear holding cost and shortages under trade credit policy is developed. The demand rate before deterioration begins is assumed to be time dependent quadratic and that after deterioration begins is considered as a constant. Shortages are allowed and partially backlogged. The purpose of this work is to determine the optimal time with positive inventory, cycle length and economic order quantity simultaneously such that total variable cost has minimum value. The necessary and sufficient conditions for the existence and uniqueness of the optimal solutions are presented. Some numerical examples were given to illustrate the model developed. Sensitivity analysis is carried out to see the effect of changes in some model parameters on decision variables and suggestions toward minimising the total variable cost were also given.
Keywords: non-instantaneous deterioration; time dependent quadratic rate; trade credit policy; linear holding cost; partially backlogged shortages; economic order quantity; EOQ.
An Enhanced Parallel Processing Algorithm Based on TOP-K Decomposition of Hypercube Model
by Quanyou Zhang, Bao-hua Qiang, Yong Feng, Yaohui Li
Abstract: Parallel processing technology has been widely used in many fields. Usually we will discuss the technology of large-scale data parallel computing based on network. The parallel processing method based on hypercube model could divide large-scale data into a large number of sub-datasets, which will be distributed to each processing unit. But empty hypercube units existed because of uneven segmentation. To solve this question, an enhanced parallel processing algorithm based on TOP-K (it is equal to selecting the kth data from the ordered data) decomposition of hypercube model was proposed to evenly divide large-scale data in parallel processing. Experiment result shows that the proposed algorithm has some enhancement on time complexity, scalability and speedup in contrast with the parallel processing method based on hypercube model.
Keywords: parallel processing; TOP-K decomposition; hypercube model.
Evaluation of the efficiency of regional ecological economic system based on the matrix network DEA model of the global framework
by Teng Ren, Zhongbao Zhou, Sidi Li, Shijian Wu, Binghua Song
Abstract: This paper proposes a matrix network DEA method based on the global DEA framework. This method avoids treating the decision-making unit as a black box, and the overall efficiency of the combined system and the efficiency of each subsystem can be obtained by it, and the convergence of the efficiency value is tested by convergence test, convergence test and club convergence test. Empirical results show that the whole, regional and provincial ecological economic efficiency levels are low. All subsystems of the ecological economic system in the eastern region are in a leading position. The economic and social efficiencies in the central region are higher than the western regions, but its ecological efficiency is lower than the western region. In addition, the results of efficiency convergence test show that the overall and social efficiencies have a divergence trend, while economic and ecological efficiencies keep steady.
Keywords: regional ecological economy; efficiency evaluation; matrix network DEA model.
The effects of aesthetics on consumer responses: the moderating effect of gender and perceived price
by Nguyen Ngoc Hien, Nguyen Ngoc Long, Nguyen Thi Nhu Mai
Abstract: This is a study that focuses on assessing how consumers perceive aesthetics, and determines the mechanism by which aesthetics influences consumer responses. To achieve this goal, two studies were conducted. In study 1, group discussions and direct surveys were conducted to develop an aesthetic measurement scale. The results show that the efficient aesthetic scale is a second order factor of 21 items and four components, including colour, design, style and overall appearance. In study 2, a direct interview with a sample of 384 automobile consumers and using partial least squares structural equation modelling techniques to test the hypotheses of this research were carried out. The results show that aesthetics affect brand image, brand evaluation and purchase intention. Furthermore, the relationship between aesthetics and purchase intention has been moderated by the gender. Important implications are proposed for business managers and marketers in developing brands and enhancing purchasing intention via aesthetics.
Keywords: aesthetics; brand image; brand evaluation; purchase intention; partial least square.
Optimal matching of urban emergency resources under major public health events by multi-expert decision model of Grey situations
by Haitao Li
Abstract: It is a difficult issue to optimal matching emergency resources among multiple epidemic areas and multiple emergency resources when information is poor, especially in early stage of a major public health event. This article tries to make full use of the experiences and wisdom of experts from various fields, build a multi-expert decision model combined with multi-objective grey situation method, and hope to improve the efficiency and the quality of emergency resources allocation. Firstly taking COVID-19 epidemic as an example to describe the modelling framework; then processing the three common types of uncertain decision information into the type of normalised utility value, putting forward a linear combination algorithm to determine aggregating weights of group decision information; finally giving the implementation steps of the proposed method and presents an application case to illustrate its practical feasibility and effectiveness. This article also contributes to the other public emergencies decision-making.
Keywords: major public health events; emergency resources matching; grey situation group decision; multiple uncertain preferences; COVID-19 epidemic.
Heterogeneity in the United States Gig Economy with a Focus on Gender
by Robert Peterson
Abstract: Most studies of workers in the gig economy have been limited to gig workers using online digital labour platforms or crowdsourcing platforms. However, by definition, gig workers are independent contractors engaged in a wide variety of mostly ad hoc or short-term activities and tasks, only some of which are linked to online digital platforms. The present research investigated the heterogeneity that exists among gig workers in the USA, with an emphasis on the moderating role of gender. Although motivations for entering the gig economy were relatively similar for males and females, the types of gigs engaged in differed somewhat between males and females. With few exceptions, female gig workers generally expected to earn less than male gig workers when entering the gig economy, and actually did earn less.
Keywords: gig workers; gig economy heterogeneity; gig worker gender.
Nash equilibrium in cooperative games as a tool for solving the Sustainable Business Development dilemma
by Juan Chica-Urzola, Vanessa Benavides-Miranda, Jesus Gabalan Coello
Abstract: The sustainable business development (SBD), as well as sustainable development in general, has been the subject of multiple conceptualisations, discussions and debates that have made this term become something abstract and difficult to implement in organisations. Even more so when one tries to do it from a multidimensional perspective that links the economic, social and environmental aspects; since many of the objectives of these dimensions are opposite or their effects, positive in one dimension, may be negative in another one, increasing complexity when making decisions framed in this model. Game theory and Nash equilibrium, for their part, propose tools to make an approximation that, taking considering this complexity, allows making the right decisions in terms of business sustainability.
Keywords: sustainable development; Nash equilibrium; multidimensional business development; cooperatives games; decision theory.
HDSS: A Healthcare Decision Support System on Combining Domain Knowledge and Data Analytics for Predicting Potential Risk of Mental Health
by Chun-Kit Ngan, Yok-Fong Paat, Rachel Green
Abstract: We develop HDSS to determine if a patient is at risk of mental health (MH) problems. This HDSS combines the strengths of both domain experts knowledge and data analytics techniques to conduct the risk identification for patients. Our contributions are three-fold: 1) develop a two-tier hybrid-based prediction process to construct a classification model to predict if a person suffers from a particular symptom; and then determine if that person is at risk of suffering from MH problems based upon the domain experts diagnostic criteria; 2) execute experiments to show that our approach is more effective and produces the results that are slightly less accurate than those of domain experts diagnostic criteria but superior to those of the data analytics approach; 3) develop a dashboard that delivers descriptive visuals from diverse perspectives to assist physicians in obtaining a more comprehensive view of patients MH status to provide them with better treatment and support.
Keywords: decision support; patient healthcare; mental health risk; predictive analytics; descriptive analytics; interactive dashboard.
Exploring the Impacts of Covid-19 Pandemic on Risks Faced by Infrastructure Projects in Pakistan
by Gohar Azeem, Mirpouya Mirmozaffari, Reza Yazdani, Rao Aamir Khan
Abstract: The current COVID-19 pandemic is making a huge impact on society. Most projects are either abandoned or halted due to this pandemic, especially in developing countries. We have conducted this study to evaluate the impact of COVID-19 pandemic on construction projects by using the concept of rework projects. Rework project is a class of projects that are initiated to achieve the intended objectives in the second attempt after failing to achieve the goals in the first attempt. People who were involved in the selected projects in different capacities were interviewed and analysis of the responses was performed. The unique challenges/risks such as time urgency, overburdened resources, and mobilisation of contractors, inappropriate documentation gaps, and technological changes were highly significant in rework projects. By having clear recognition to these highly significant risks, organisations will be well equipped in devising strategies to manage and complete the rework projects in the post-pandemic world.
Keywords: COVID-19; pandemic; project management; developing countries; risk management; rework projects; engineering projects; Pakistan.
The Influence of Emotional Intelligence on Technology Adoption and Decision-Making Process
by Emad Abu-Shanab, Amro AbuShanab
Abstract: Emotional intelligence is a vital measure of personality in psychology, where research indicated it has a direct influence on technology adoption. This study assumed that emotional intelligence dimensions would have an influence on personal self-efficacy, which makes it a driver of technology adoption domain. The proposed framework deployed a relational model of emotional intelligence dimensions, and connected it to technology adoption theories. A sample of 268 students filled the survey and used for analysis. Results indicated that self-awareness significantly influenced self-management, social management significantly influenced social skills, and both social management and self-management influenced social skills. In addition, social skills significantly influenced self-efficacy. All four dimensions of emotional intelligence explained 9% of the variance in self-efficacy. Self-efficacy and effort expectancy significantly influenced performance expectancy and explain 29.6% of its variance. Finally, performance expectancy significantly influenced the behavioural intention to use Excel for the decision-making process in the future, and explained 47.8% of its variance. Results supported the model and provided a fair explanation of power. Details, conclusions and future work are reported at the end.
Keywords: emotional intelligence; decision making; self-efficacy; UTAUT; behavioural intentions; Jordan.
Large-Scale Vehicle Routing Problem with Massive Precedence and Cluster Constraints
by Yongzhong Wu, Simin Huang, Yu Chen
Abstract: With the continuous development of the urban logistics industry, the vehicle routing problem (VRP) manifests in increasingly large-scale and complex scenarios. In this study, a realistic large-scale VRP with massive precedence and cluster constraints is studied. An artificial bee colony (ABC) algorithm is designed to solve the problem. A route repair procedure is devised to ensure the satisfaction of all the constraints in realistic-sized problems. The algorithms are used to solve a set of real instances for a courier company in China. For such large-scale problems, the improved ABC algorithm performs significantly better than the basic ABC algorithm without the route repair procedure. This study further analyses the sensitivity of the results to the values assigned to a series of weighting coefficients on the constraints and objectives. This provides the company with flexibility in its operations under different operating circumstances.
Keywords: multi-objective VRP; precedence and cluster constraints; artificial bee colony; ABC; route repair procedure; metaheuristic.
INVESTOR BEHAVIOR IN AN ENVIRONMENT OF UNCERTAINTY: THE IMPACT OF PERSUASION ON INVESTOR DECISIONS
by Cleber Broietti, Suliani Rover, Graça 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 this 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.
Capital structure and firm value nexus: The Ghanaian experience
by Ebenezer Fiifi Emire Atta Mills, Jema Jason Mwasambili
Abstract: This study examines the causal relationship between capital structure and firm value. It examines causality between variables using yearly series data from 2010 to 2017 using the financial statement of 38 companies listed on the Ghana Stock Exchange. Panel unit root tests, cointegration methods, panel FMOLS, DOLS, and Granger causality tests were applied. This study provides managers awareness of the cost that the company would incur by ignoring the power of capital structure selection. This study found that there is short-run bidirectional panel causality running between equity, long-term debt, short-term debt, and growth to firm value. For long-run causal relationships, the results indicate that estimated coefficients of lagged error correction term in variable equations are statistically significant, implying that these variables could play an important role in regulating processes. The findings of this study are important for decision-makers to optimize the capital structure to increase the firms value.
Keywords: capital structure; firm value; Ghana Stock Exchange; leverage; panel data.
Hotspot analysis of rural inclusive finance based on keyword co-occurrence clustering
by Mei Zhang, Huihui Su, Jinghua Wen
Abstract: It was analysed the hotspot about rural puhui finance in China that takes the literature of rural huipu finance in China National Knowledge Infrastructure (CNKI) as the research object. It uses a method of co-word analysis to construct a matrix, and it uses network knowledge maps, statistical product and service solutions (SPSS) cluster analysis and multi-dimensional scale analysis to study the connections and meanings between various keywords. By classifying and observing data information, we find: precise poverty alleviation and inclusive finance were combined; rural inclusive finance under digital technology is bound to become the current new trend in the development of financial services. It is suggested that rural inclusive finance should focus on the various businesses of rural financial service institutions in order to increase farmers income and promote sustainable economic development.
Keywords: rural inclusive finance; co-word analysis; knowledge map; cluster analysis; co-occurrence clustering; China National Knowledge Infrastructure; CNKI; statistical product and service solutions; SPSS.
Elucidating Cause-and-Effect Relationships of Components Affecting Talent Absorbing Organizations
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.
Extended Strategic Alignment Model (SAM) for Information Systems Governance
by Khaoula Benmoussa, Majida Laaziri, Mohammed Bennaser, Abdelrhani Bouayad, 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.
AOSR: An Agent Oriented Storage and Retrieval WMS planner for SMEs, associated with AOSF framework, under Industry 4.0
by Fareed Ud Din, David Paul, Frans Henskens, Mark Wallis, Muhammad Adnan Hashmi
Abstract: The concept of a smart factory, under Industry 4.0 relies heavily on cyber physical systems (CPS) and intra-enterprise-wide-networks (IWN). Cloud-based implementation is incumbent to accomplish the promises of enterprise integration, automation, seamless information exchange and intelligent self-organisation. Extensive research has been conducted in this domain, however, there is still much research to be done from the perspective of such frameworks in small to medium size enterprises (SMEs). In this context, the agent-oriented smart factory (AOSF) framework provides a generic end-to-end supply chain (SC) model, compliant with CPS and Industry 4.0 standards. In order to support the crucial side of warehouse management, this paper presents AOSFs recommended agent-oriented storage and retrieval (AOSR) warehouse planner with hybrid logic-based strategy, which yields a smart time-stamped plan to manage product placement and retrieval efficiently. The AOSF-associated AOSR-planner uses the hierarchical task network (HTN) AI planning to ensure different warehouse operations in a timely manner.
Keywords: smart factory; small to medium size enterprises; SMEs; agent-oriented storage and retrieval system; AOSR; agent-oriented smart factory; AOSF; warehouse management system; WMS.
Unrelated Parallel Dedicated Machine Scheduling with Sequence Dependent Set-Up 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.
Big Data, Artificial Intelligence and Epidemic Disasters. A primary Structured Literature Review
by Rosa Lombardi, Raffaele Trequattrini, Benedetta Cuozzo, Alberto Manzari
Abstract: This paper presents the structured literature review of the big data and artificial intelligence in relation to the epidemic disasters among which the current SAR-COV-2. Providing a deep understanding of the state of the art, the paper drafts implications and valuable insights to manage and prevent epidemic disasters by public and private organisations drafting the research agenda. Interestingly, a two-decade study of the connection between big data, artificial intelligence and pandemic or epidemic issues is undertaken for the first time. This paper adopted a longitudinal study of the literature from the relevant databases Scopus as a leading source to get access to the articles. The diffusion of epidemic disasters among which SARS-COV-2 needs to be managed investigating several aspects such as the prevention and tracking of the epidemia or pandemia. The role of smart technologies and particularly big data and artificial intelligence is useful in tracking, preventing and managing the emergency by organisations, institutions and policymakers. This study provides for the first time the connection among big data, artificial intelligence and epidemic disasters, providing valuable implications, insights and emerging issues among which the relevance of decision-making processes and risks definition and assessment.
Keywords: big data; artificial intelligence; epidemic disasters; SARS-COV-2; smart technologies; pandemia; decision-making process; prevention.
Flying Journey and the Contemporary Customers Combating Covid-19: The
by Riya Gupta, Rachna Agrawal, ARTI GUPTA
Abstract: The rising competition of every sector has evolved innovative thinking and application of a more developed version of strategies. However, the emergence of COVID-19 has further amplified the struggles. The intense competition and declining profits of the Indian aviation sector are the major concerns to be discussed. This study focuses on finding the needs and preferences of flyers of the selected well-known companies. Convenience sampling has been used and data is collected from 217 respondents with the help of a structured questionnaire. Exploratory factor analysis (EFA) is used to make 22 variables into six significant factors. These factors are further confirmed with help of confirmatory factor analysis (CFA). The novelty of this study is to propose the realistic ground to guide the struggling aviation sector to achieve the dazzling wave of customers.
Keywords: aviation industry; customers preference; customer expectations; exploratory factor analysis; EFA; confirmatory factor analysis; CFA.
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.
Optimal Portfolio Selection With Transaction Costs In Compound Binomial Model
by Fang Jin, Hui Ou
Abstract: Investors consider investing in an investment market including a risk-free asset plus a risky asset to get maximum profit. At the same time, the insurer has a proportional transaction cost every time they invest in risky assets in actual situation. In this paper a compound binomial model with investment costs as well as considering proportion investment costs was studied. We want to get the optimal investment strategy to maximise the expected utility of terminal wealth in the financial market. In order to solve this problem, we use the analytical method and construct the no-transaction region at time t to help us solve the problem. Finally, the expressions of the optimal investment strategy and the value function are derived, respectively. In addition, on the basis of this paper, we can consider introducing other influencing factors, such as: random time exit, Markovian environmental impact and so on.
Keywords: optimal portfolio; transaction costs; compound binomial model.
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.
The impact of corporate governance and political connections on the financial performance: The analysis of the financial distress of Lebanese banks
by Hani E.L. CHAARANI, Rosa Lombardi
Abstract: This paper aims to investigate the impact of corporate governance on the financial performance of Lebanese banks also analysing the impact of political connections to draft the financial crisis of the Lebanese banking sector in 20202021. Annual financial reports and the Orbis-BankFocus database are used to collect financial and non-financial information of Lebanese banks between 20162019. Descriptive statistics and multiple regressions are applied to explore the impact of corporate governance mechanisms and political net on the profitability, liquidity level and risk management of Lebanese banks. Results reveal that: 1) internal and external governance mechanisms of the Lebanese banking sector are considered weak and need improvements; 2) internal corporate governance mechanisms can improve the financial performance of Lebanese banks; 3) the presence of political connections seems to lead risky lending practices. This research provides information to support investors, bankers, regulators, and top managers in the Lebanese banking sector. Lebanese banks must improve their internal corporate governance mechanisms to sustain in the current legal protection environment.
Keywords: banks; corporate governance; political connection; performance; profitability; liquidity; financial risk.
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 talents and how to allocate corresponding talents to appropriate works have 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.