Cross-border to Taiwan but not China

2019 ◽  
Vol 15 (1) ◽  
pp. 21-36
Author(s):  
Wai Ching Choy ◽  
Pui Yan Flora Lau
Keyword(s):  
Decision Making ◽  
Undergraduate Students ◽  
Dynamic Decision Making ◽  
International Mobility ◽  
Snowball Sampling ◽  
Content Type ◽  
Cross Border ◽  
Depth Interview ◽  
Drastic Increase ◽  
Decision Making Model

Purpose This study aims to find out why some students from Hong Kong (HK) consider higher education in Taiwan, rather than in China or elsewhere. It also attempts to build a decision-making model to advance the conventional push-pull logic associated with this particular issue. Design/methodology/approach The authors interviewed 11 undergraduate students from HK via an in-depth interview. Interviewees were recruited by snowball sampling. To protect the privacy of the interviewees, all names of the informants in this paper are pseudonyms. Findings A dynamic decision-making mechanism, which includes three major layers, namely, the macro, meso and micro levels, has been developed to demonstrate that HK students made their decision based on a recursive fashion with bounded rationality, rather than on a linear fashion with complete rationality. Research limitations/implications Although the relatively small number of interviewees has limited the representativeness of the research, the authors suggest that rather than claiming representativeness, the study attempts to tease out the diversity of the decision-making process and mechanisms. Originality/value The drastic increase in the number of HK students in Taiwan proves the current research study, which is the first qualitative research on the phenomenon, as a timely one. In addition, the present study is one of the few examples of studying students’ international mobility from a more economically advanced region (HK) to a less economically advanced one (Taiwan).

Dynamic information aggregation decision-making methods based on variable precision rough set and grey clustering

2014 ◽  
Vol 4 (2) ◽  
pp. 347-361 ◽  
Author(s):  
Yong Liu ◽  
Huan-huan Zhao
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Information Aggregation ◽  
Dynamic Decision Making ◽  
Dynamic Information ◽  
Content Type ◽  
Variable Precision ◽  
Model Based ◽  
Variable Precision Rough Set ◽  
Decision Making Model

Purpose – The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set. Design/methodology/approach – To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model. Findings – The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules. Research limitations/implications – The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers. Originality/value – The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

scholarly journals A Methodology for Redesigning Networks by Using Markov Random Fields

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1389
Author(s):  
Julia García Cabello ◽  
Pedro A. Castillo ◽  
Maria-del-Carmen Aguilar-Luzon ◽  
Francisco Chiclana ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Random Fields ◽  
Markov Random Fields ◽  
Application Performance ◽  
Cross Border ◽  
Markov Random ◽  
User Groups ◽  
Universal Definition ◽  
Definition Of ◽  
Decision Making Model

Standard methodologies for redesigning physical networks rely on Geographic Information Systems (GIS), which strongly depend on local demographic specifications. The absence of a universal definition of demography makes its use for cross-border purposes much more difficult. This paper presents a Decision Making Model (DMM) for redesigning networks that works without geographical constraints. There are multiple advantages of this approach: on one hand, it can be used in any country of the world; on the other hand, the absence of geographical constraints widens the application scope of our approach, meaning that it can be successfully implemented either in physical (ATM networks) or non-physical networks such as in group decision making, social networks, e-commerce, e-governance and all fields in which user groups make decisions collectively. Case studies involving both types of situations are conducted in order to illustrate the methodology. The model has been designed under a data reduction strategy in order to improve application performance.

scholarly journals An evidence accumulation model of perceptual discrimination with naturalistic stimuli

2018 ◽  
Author(s):  
Hector Palada ◽  
Rachel A Searston ◽  
Annabel Persson ◽  
Timothy Ballard ◽  
Matthew B Thompson
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Decision Process ◽  
Dynamic Decision Making ◽  
Evidence Accumulation ◽  
Natural Stimuli ◽  
Perceptual Judgments ◽  
Linear Ballistic Accumulator ◽  
Decision Making Model ◽  
Speed Accuracy

Evidence accumulation models have been used to describe the cognitive processes underlying performance in tasks involving two-choice decisions about unidimensional stimuli, such as motion or orientation. Given the multidimensionality of natural stimuli, however, we might expect qualitatively different patterns of evidence accumulation in more applied perceptual tasks. One domain that relies heavily on human decisions about complex natural stimuli is fingerprint discrimination. We know little about the ability of evidence accumulation models to account for the dynamic decision process of a fingerprint examiner resolving if two different prints belong to the same finger or not. Here, we apply a dynamic decision-making model — the linear ballistic accumulator (LBA) — to fingerprint discrimination decisions in order to gain insight into the cognitive processes underlying these complex perceptual judgments. Across three experiments, we show that the LBA provides an accurate description of the fingerprint discrimination decision process with manipulations in visual noise, speed-accuracy emphasis, and training. Our results demonstrate that the LBA is a promising model for furthering our understanding of applied decision-making with naturally varying visual stimuli.

scholarly journals Music and Its Familiarity Affection on Audience Decision Making

2019 ◽  
Vol 11 (1A) ◽  
pp. 70
Author(s):  
Syazwani Mahsal Khan ◽  
Assoc. Prof. Dr. Norsiah Abdul Hamid ◽  
Dr. Sabrina Mohd Rashid
Keyword(s):  
Decision Making ◽  
Thematic Analysis ◽  
Elaboration Likelihood Model ◽  
Elaboration Likelihood ◽  
Snowball Sampling ◽  
Advertising Industry ◽  
Depth Interview ◽  
Musical Tone ◽  
Likelihood Model ◽  
Study Repetition

<p class="Default"><em>This article discuss a problem regarding the lack of using familiar music and its effect on audience decision making to buy advertised products or services. This study is to help the experts to maintain young audience focus while selling their products or services more effective using the familiar music in the advertisement content. The utilization method used for this study was in-depth interview, involved with ten informants which covered experts from academicians, advertising practitioners and musicians. It based on snowball sampling, because not all these experts have the knowledge on this issue. The Elaboration Likelihood Model was applied to show the process of decision making. Thematic analysis used to analyze two themes emerged from this study; Repetition of Musical Tone as Remembrance. This study may provide contribution in terms of ideas for music and advertising industry producing familiar catchy musical sound for their purpose.</em></p><p class="Default"> </p>

Grey assessment and prediction of the financial agglomeration degree in central five cities

2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu
Keyword(s):  
Decision Making ◽  
Scientific Development ◽  
Fuzzy Decision Making ◽  
Grey Prediction ◽  
Fuzzy Decision ◽  
Content Type ◽  
Multiple Dimension ◽  
The Government ◽  
Development Tendency ◽  
Decision Making Model

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.

scholarly journals Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Strategic Decision ◽  
Extensive Literature ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Selection For ◽  
Decision Making Model

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

Decision-making in a dynamic task: effects of goal orientation on stocks and flows performance

2020 ◽  
Vol 14 (3) ◽  
pp. 695-713
Author(s):  
Feifei Yang ◽  
Jiaqi Huang ◽  
Xiao Feng ◽  
Miles M. Yang
Keyword(s):  
Decision Making ◽  
Goal Orientation ◽  
Theoretical Perspective ◽  
Least Square ◽  
Dynamic Decision Making ◽  
Content Type ◽  
Dynamic Task ◽  
Learning Goal ◽  
Stocks And Flows ◽  
The Impact

Purpose This paper aims to investigate the effects of goal orientation on understanding the dynamics of stocks and flows (SF). Design/methodology/approach The authors use the well-established department store task as the experimental task to evaluate people’s understanding of SF and implement a survey to assess different goal orientation levels. Ordinary least square is used to test the effects of goal orientations on the SF performance. Findings The findings suggest that learning goal orientation is positively associated with SF performance. However, prove and avoid performance goal orientation are unrelated to SF performance. Originality/value The study has important theoretical and practical contributions. From a theoretical perspective, the authors examine the impact of goal orientation in dynamic decision-making to advance the knowledge on the role of goal orientation. Practically, the research demonstrates that learning-goal-oriented people perform better in stock and flow tasks, suggesting that goal orientation is an important trait for recruiting organizational members whose work involves SF decision-making tasks.

A risk-based integrated decision-making model for green supplier selection

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1229-1252 ◽  
Author(s):  
Morteza Yazdani ◽  
Prasenjit Chatterjee ◽  
Dragan Pamucar ◽  
Manuel Doval Abad
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supplier Selection ◽  
Potential Contribution ◽  
Effect Analysis ◽  
Content Type ◽  
Green Supplier Selection ◽  
Construction Company ◽  
Green Suppliers ◽  
Decision Making Model

Purpose Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk. Design/methodology/approach At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics. Findings A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model. Practical implications The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors. Originality/value A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

Stream processing data decision model for higher environmental performance and resilience in sustainable logistics infrastructure

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yasanur Kayikci
Keyword(s):  
Decision Making ◽  
Transport System ◽  
Environmental Performance ◽  
Stream Processing ◽  
Data Driven ◽  
Content Type ◽  
Sustainable Logistics ◽  
Processing Data ◽  
Decision Making Model ◽  
Resilience Capacity

PurposeAs the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.Design/methodology/approachA causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.FindingsThe result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.Originality/valueIn this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

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