A Comprehensive Star Rating Approach for Cruise Ships Based on Interactive Group Decision Making with Personalized Individual Semantics

This article proposes a comprehensive star rating approach for cruise ships by the combination of subject and objective evaluation. To do that, it firstly established a index system of star rating for cruise ships. Then, the modified TOPSIS is adopted to tackle objective data for obtaining star ratings for basic cruise indicators and service capabilities of cruise ships. Thus, the concept of distributed linguistic star rating function (DLSRF) is defined to analyze the subjective evaluation from experts and users. Hence, a novel weight calculation method with interactive group decision making is presented to assign the importance of the main indicators. Particularly, in order to enable decision makers to effectively deal with the uncertainty in this star rating process, it adopts the personalized individual semantics (PIS) model. Finally, data of nine cruise ships is collected to obtain their final star rating results and some suggestions for improving cruise service capabilities and star indicators were put forward.National Natural Science Foundation of China (NSFC) 71971135,72001134,72071056 China Scholarship Council 202108310183 Innovative Talent Training Project of Graduate Students in Shanghai Maritime University of China 2021YBR00

An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour in consensus reaching process under social network group decision making is proposed, which is based on a theoretically sound optimal feedback model. The manipulation behaviour classification is twofold: (1) ‘individual manipulation’ where each expert manipulates his/her own behaviour to achieve higher importance degree (weight); and (2) ‘group manipulation’ where a group of experts force inconsistent experts to adopt specific recommendation advices obtained via the use of fixed feedback parameter. To counteract ‘individual manipulation’, a behavioural weights assignment method modelling sequential attitude ranging from ‘dictatorship’ to ‘democracy’ is developed, and then a reasonable policy for group minimum adjustment cost is established to assign appropriate weights to experts. To prevent ‘group manipulation’, an optimal feedback model with objective function the individual adjustments cost and constraints related to the threshold of group consensus is investigated. This approach allows the inconsistent experts to balance group consensus and adjustment cost, which enhances their willingness to adopt the recommendation advices and consequently the group reaching consensus on the decision making problem at hand. A numerical example is presented to illustrate and verify the proposed optimal feedback model

A personalized consensus feedback mechanism based on maximum harmony degree

This work was sponsored by National Natural Science Foundation of China (NSFC) (No.71971135,71571166), EU project H2020-MSCA-IF-2016-DeciTrustNET-746398 and FEDER funds provided in the National Spanish project TIN2016-75850-R.This article proposes a framework of personalized feedback mechanism to help multiple inconsistent experts to reach consensus in group decision making by allowing to select different feedback parameters according to individual consensus degree. The general harmony degree (GHD) is defined to determine the before/after feedback difference between the original and revised opinions. It is proved that the GHD index is monotonically decreasing with respect to the feedback parameter, which means that higher parameters values will result in higher changes of opinions. An optimisation model is built with the GHD as the objective function and the consensus thresholds as constraints, with solution being personalized feedback advices to the inconsistent experts that keep a balance between consensus (group aim) and independence (individual aim). This approach is, therefore, more reasonable than the unpersonalized feedback mechanisms in which the inconsistent experts are forced to adopt feedback generated with only consensus target without considering the extent of the changes acceptable by individual experts. Furthermore, the following interesting theoretical results are also proved: (1) the personalized feedback mechanism guarantees that the increase of consensus level after feedback advices are implemented; (2) the GHD by the personalized feedback mechanism is higher than that of the unpersonalized one; and (3) the personalized feedback mechanism generalises the unpersonalized one as it is proved the latter is a particular type of the former. Finally, a numerical example is provided to model the feedback process and to corroborates these results when comparing both feedback mechanism approaches.National Natural Science Foundation of China (NSFC) 71971135 71571166European Commission H2020-MSCA-IF-2016-DeciTrustNET-746398 TIN2016-75850-

A bidirectional feedback mechanism for balancing group consensus and individual harmony in group decision making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This article proposes a bidirectional feedback mechanism for consensus in group decision making (GDM) driven by the behavior of decision makers (DMs), which is discriminated with a flexible harmony degree as one of three possible states: (1) ‘tolerance behavior’; (2) ‘rationalist behavior’; and (3) ‘conflict behavior’. The first two states are possible to be resolved in the consensus reaching process with one round of feedback recommendations to the discordant DMs. However, in the conflict state, which implies the lack of harmony between the group aim of ‘consensus’ and the individual benefit, it is unreasonable to be resolved with only discordant DMs’ feedback recommendations, and concordant DMs are also expected to make concessions at some degree. To address this not so unusual research problem, a theoretical bidirectional feedback mechanism framework for consensus is developed. Firstly, a maximum consensus driven feedback model is proposed to resolve ‘conflict behavior’ between the concordant and discordant DMs. Secondly, a maximum harmony driven feedback model is activated to support the discordant DMs to reach the threshold values of group consensus. A numerical example is provided to illustrate and verify the proposed mechanism usefulness and how it compares against other existent feedback mechanisms in terms of the extent up to which DMs’ preferences are changed for reaching consensus

Rapid Detection of Malathion, Phoxim and Thiram on Orange Surfaces Using Ag Nanoparticle Modified PDMS as Surface-Enhanced Raman Spectroscopy Substrate

Malathion, phoxim, and thiram are organophosphates and organosulfur pesticides widely used in agricultural products. The residues of these pesticides present a direct threat to human health. Rapid and on-site detection is critical for minimizing such risks. In this work, a simple approach was introduced using a flexible surface-enhanced Raman spectroscopy (SERS) substrate. The prepared Ag nanoparticles-polydimethylsiloxane (AgNPs-PDMS) substrate showed high SERS activity, good precision (relative standard deviation = 5.33%), and stability (30 days) after optimization. For target pesticides, the linear relationship between characteristic SERS bands and concentrations were achieved in the range of 10~1000, 100~5000, and 50~5000 μg L−1 with LODs down to 3.62, 41.46, and 15.69 μg L−1 for thiram, malathion, and phoxim, respectively. Moreover, SERS spectra of mixed samples indicated that three pesticides can be identified simultaneously, with recovery rates between 96.5 ± 3.3% and 118.9 ± 2.4%, thus providing an ideal platform for detecting more than one target. Pesticide residues on orange surfaces can be simply determined through swabbing with the flexible substrate before acquiring the SERS signal. This study demonstrated that the prepared substrate can be used for the rapid detection of pesticides on real samples. Overall, this method greatly simplified the pre-treatment procedure, thus serving as a promising analytical tool for rapid and nondestructive screening of malathion, phoxim, and thiram on various agricultural products

A Calibrated Individual Semantic Based Failure Mode and Effect Analysis and Its Application in Industrial Internet Platform

This article proposes a calibrated individual semantic (CIS)-based failure mode and effect analysis (FMEA) to deal with the risk evaluation of industrial internet platforms (IIP) from four perspectives: network security, data processing capability, equipment performance, and openness. The novelty of the CIS model is based on the deviation between linguistic terms and numerical values to calibrate linguistic scales of decision-makers (DMs). Not only can it handle situations in which different DMs have different understandings of the same term, but it is also suitable for multiple attributes decision-making with uncertainty. In addition, this new FMEA framework considers the consensus-reaching process as a way to eliminate the disagreement among DMs from different departments. Finally, a comparison between the proposed and traditional method is presented to illustrate the advantages of new method

A Calibrated Individual Semantic Based Failure Mode and Effect Analysis and Its Application in Industrial Internet Platform

This article proposes a calibrated individual semantic (CIS)-based failure mode and effect analysis (FMEA) to deal with the risk evaluation of industrial internet platforms (IIP) from four perspectives: network security, data processing capability, equipment performance, and openness. The novelty of the CIS model is based on the deviation between linguistic terms and numerical values to calibrate linguistic scales of decision-makers (DMs). Not only can it handle situations in which different DMs have different understandings of the same term, but it is also suitable for multiple attributes decision-making with uncertainty. In addition, this new FMEA framework considers the consensus-reaching process as a way to eliminate the disagreement among DMs from different departments. Finally, a comparison between the proposed and traditional method is presented to illustrate the advantages of new method

Application of Group Decision Making in Shipping Industry 4.0: Bibliometric Analysis, Trends, and Future Directions

With the development of Internet technologies, the shipping industry has also entered the Industry 4.0 era, which is the era of using information technology to promote industrial change. Group decision making (GDM), as one of the key methods in decision science, can be used to obtain optimal solutions by aggregating the opinions of experts on several alternatives, and it has been applied to many fields to optimize the decision-making process. This paper provides an overview and analysis of the specific applications of GDM methods in Shipping Industry 4.0, and discusses future developments and research directions. First, the existing relevant literature is analyzed using bibliometrics. Then, the general procedure of GDM is investigated: opinion/preference representation, consensus measure, feedback mechanism, and the selection of alternatives. Next, the specific applications of GDM methods in Shipping Industry 4.0 are summarized. Lastly, possible future directions are discussed to advance this area of research

A Comprehensive Star Rating Approach for Cruise Ships Based on Interactive Group Decision Making with Personalized Individual Semantics

This article proposes a comprehensive star rating approach for cruise ships by the combination of subject and objective evaluation. To do that, it firstly established a index system of star rating for cruise ships. Then, the modified TOPSIS is adopted to tackle objective data for obtaining star ratings for basic cruise indicators and service capabilities of cruise ships. Thus, the concept of distributed linguistic star rating function (DLSRF) is defined to analyze the subjective evaluation from experts and users. Hence, a novel weight calculation method with interactive group decision making is presented to assign the importance of the main indicators. Particularly, in order to enable decision makers to effectively deal with the uncertainty in this star rating process, it adopts the personalized individual semantics (PIS) model. Finally, data of nine cruise ships is collected to obtain their final star rating results and some suggestions for improving cruise service capabilities and star indicators were put forward

Consensus-trust driven bidirectional feedback mechanism in social network group decision making.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper proposes a consensus-trust driven framework of bidirectional interaction for social network large-group decision making. Firstly, the concepts of interaction consensus threshold and interaction trust threshold are defined, which are used to discriminate the interaction modes between subgroups into four categories. Corresponding hybrid feedback strategies are designed in which the consensus level and trust level of subgroups are regarded as reliable resources to facilitate the achievement of group consensus. Secondly, a minimum adjustment bidirectional feedback model considering cohesion is developed to help the interacting subgroups reach mutual consensus with minimum opinion modification. Finally, the proposed consensus framework is applied to a blockchain platform selection problem in supply chain to demonstrate the effectiveness and applicability of the model