期刊,Group decision and negotiation 2025年34卷3期_国家学术搜索

Leveraging Group Decision Aiding with Decision Conferencing: A Systematic Review and a Roadmap for Future Research

Edgar MascarenhasMónica D. Oliveira

405-433页

查看更多>>摘要：Abstract Framed within facilitated modelling approaches and grounded on multi-criteria decision aiding concepts, Decision Conferencing (DCing) combines group facilitation, preference modelling and decision analytical software to help groups tackle problems characterized by high complexity, uncertainty, and diverse, conflicting perspectives. Despite its widespread application over the past decades, scholarly knowledge on DCing remains under-systematized and poorly explored. This study addresses this gap through a systematic literature review (SLR) and selected bibliometric analyses of DCing literature, and by identifying major challenges and promising research directions to advance DCing practice. The SLR adhered to the PRISMA guidelines, with structured searches applied to Web of Science, Scopus, EBSCO, ScienceDirect and Google Scholar. Seventy-one studies met the pre-defined criteria and were categorised by year, publication source, country, and type of DCing study. Information on analytical methods/frameworks/tools, software used, and evidence of effectiveness was extracted from DCing case studies. Selected bibliometric analyses included co-authorship and keyword co-occurrence network maps and were conducted to gain further insights into the DCing scientific landscape. Results show that DCing has been applied in multiple contexts and that there is diversity in facilitation practices and methods used; few studies have formally evaluated DCing effectiveness or reported its use in virtual settings. Based on the review findings and on literature from adjacent areas, we propose a roadmap for advancing DCing practice, highlighting the need for research on DCing effectiveness, for comparative studies on methods/software, for investigating biases in DCing settings, for developing empirical research on virtual DCing, and for sharing of best facilitation practices.

原文链接:

NETL
NSTL
Springer Nature

Leveraging Group Decision Aiding with Decision Conferencing: A Systematic Review and a Roadmap for Future Research

Edgar MascarenhasMónica D. Oliveira

405-433页

查看更多>>摘要：Abstract Framed within facilitated modelling approaches and grounded on multi-criteria decision aiding concepts, Decision Conferencing (DCing) combines group facilitation, preference modelling and decision analytical software to help groups tackle problems characterized by high complexity, uncertainty, and diverse, conflicting perspectives. Despite its widespread application over the past decades, scholarly knowledge on DCing remains under-systematized and poorly explored. This study addresses this gap through a systematic literature review (SLR) and selected bibliometric analyses of DCing literature, and by identifying major challenges and promising research directions to advance DCing practice. The SLR adhered to the PRISMA guidelines, with structured searches applied to Web of Science, Scopus, EBSCO, ScienceDirect and Google Scholar. Seventy-one studies met the pre-defined criteria and were categorised by year, publication source, country, and type of DCing study. Information on analytical methods/frameworks/tools, software used, and evidence of effectiveness was extracted from DCing case studies. Selected bibliometric analyses included co-authorship and keyword co-occurrence network maps and were conducted to gain further insights into the DCing scientific landscape. Results show that DCing has been applied in multiple contexts and that there is diversity in facilitation practices and methods used; few studies have formally evaluated DCing effectiveness or reported its use in virtual settings. Based on the review findings and on literature from adjacent areas, we propose a roadmap for advancing DCing practice, highlighting the need for research on DCing effectiveness, for comparative studies on methods/software, for investigating biases in DCing settings, for developing empirical research on virtual DCing, and for sharing of best facilitation practices.

原文链接:

NETL
NSTL
Springer Nature

Correction to: Leveraging Group Decision Aiding with Decision Conferencing: A Systematic Review and a Roadmap for Future Research

Edgar MascarenhasMónica D. Oliveira

435-438页

原文链接:

NETL
NSTL
Springer Nature

Correction to: Leveraging Group Decision Aiding with Decision Conferencing: A Systematic Review and a Roadmap for Future Research

Edgar MascarenhasMónica D. Oliveira

435-438页

原文链接:

NETL
NSTL
Springer Nature

Ethical Conflict and Team Innovation: A Categorization– Elaboration Model Approach

Erica Wen ChenCathy Yang GuoZhechen YinMelvyn R.W. Hamstra...

439-461页

查看更多>>摘要：Abstract Conflict is an inherent aspect of group decision-making and interpersonal negotiations, but how ethical conflict (e.g., disagreement over moral values and ethical principles) shapes group dynamics remains an uncharted area. Drawing on the Categorization–Elaboration Model (CEM), we intend to examine whether and when team ethical conflict influences team innovation in the present study. Specifically, we predict that information elaboration serves as a mediator, as high levels of ethical conflict generate biased judgments among teammates and hinder the exchange of task-relevant information. Also, we predict that process conflict (e.g., disagreement over role allocation and task distribution) serves as the moderator, as low levels of process conflict ensure clear role distribution, efficient task allocation, and consensus on workflows, which can mitigate the negative effect of ethical conflict. We test our hypotheses and find empirical support using a sample of 289 individual responses nested within 90 research and development (R&D) teams. This research advances our understanding of the emerging and important construct of ethical conflict, extends the CEM by emphasizing the pivotal role of information elaboration in group decision-making, and offers new insights into the ongoing debate on conflict, innovation, and the interaction of different conflict types.

原文链接:

NETL
NSTL
Springer Nature

Ethical Conflict and Team Innovation: A Categorization– Elaboration Model Approach

Erica Wen ChenCathy Yang GuoZhechen YinMelvyn R.W. Hamstra...

439-461页

查看更多>>摘要：Abstract Conflict is an inherent aspect of group decision-making and interpersonal negotiations, but how ethical conflict (e.g., disagreement over moral values and ethical principles) shapes group dynamics remains an uncharted area. Drawing on the Categorization–Elaboration Model (CEM), we intend to examine whether and when team ethical conflict influences team innovation in the present study. Specifically, we predict that information elaboration serves as a mediator, as high levels of ethical conflict generate biased judgments among teammates and hinder the exchange of task-relevant information. Also, we predict that process conflict (e.g., disagreement over role allocation and task distribution) serves as the moderator, as low levels of process conflict ensure clear role distribution, efficient task allocation, and consensus on workflows, which can mitigate the negative effect of ethical conflict. We test our hypotheses and find empirical support using a sample of 289 individual responses nested within 90 research and development (R&D) teams. This research advances our understanding of the emerging and important construct of ethical conflict, extends the CEM by emphasizing the pivotal role of information elaboration in group decision-making, and offers new insights into the ongoing debate on conflict, innovation, and the interaction of different conflict types.

原文链接:

NETL
NSTL
Springer Nature

New Group Decision Making Model for Occupational Health and Safety Risk Assessment with Heterogeneous Linguistic Information

Yu-Ting TanHu-Chen LiuQi-Zhen ZhangWen Chen...

463-485页

查看更多>>摘要：Abstract Occupational health and safety risk assessment (OHSRA) is a systematic and multidisciplinary activity for identifying, evaluating, and reducing the risks of occupational hazards at workplaces to protect employees from accidents. In practical OHSRA problems, domain experts tend to use linguistic terms to evaluate the risk of occupational hazards and the risk assessment information obtained is usually in heterogeneous forms due to their personalized and diversified expression habits. To address this challenge, this paper aims to propose a new OHSRA model based on the projection ranking by similarity to referencing vector (PRSRV) approach for the risk evaluation and prioritization of occupational hazards in a heterogeneous linguistic environment. To do so, the fuzzy linguistic approach, the hesitant fuzzy linguistic term set, and the probabilistic linguistic term set are used to represent experts’ heterogeneous risk assessment information. The PRSRV approach is utilized for the risk prioritization of occupational hazards based on their vectors and relative aggregate scores. In addition, the fuzzy-weighted with zero-inconsistency (FWZIC) method is extended and applied to obtain the importance weights of risk criteria. Finally, an example application of the proposed OHSRA model is presented to validate its effectiveness and advantages. The results show that the proposed OHSRA model can not only model the personalized heterogeneous linguistic risk evaluation information but also provide a reasonable risk ranking result of occupational hazards based on their relationships.

原文链接:

NETL
NSTL
Springer Nature

New Group Decision Making Model for Occupational Health and Safety Risk Assessment with Heterogeneous Linguistic Information

Yu-Ting TanHu-Chen LiuQi-Zhen ZhangWen Chen...

463-485页

查看更多>>摘要：Abstract Occupational health and safety risk assessment (OHSRA) is a systematic and multidisciplinary activity for identifying, evaluating, and reducing the risks of occupational hazards at workplaces to protect employees from accidents. In practical OHSRA problems, domain experts tend to use linguistic terms to evaluate the risk of occupational hazards and the risk assessment information obtained is usually in heterogeneous forms due to their personalized and diversified expression habits. To address this challenge, this paper aims to propose a new OHSRA model based on the projection ranking by similarity to referencing vector (PRSRV) approach for the risk evaluation and prioritization of occupational hazards in a heterogeneous linguistic environment. To do so, the fuzzy linguistic approach, the hesitant fuzzy linguistic term set, and the probabilistic linguistic term set are used to represent experts’ heterogeneous risk assessment information. The PRSRV approach is utilized for the risk prioritization of occupational hazards based on their vectors and relative aggregate scores. In addition, the fuzzy-weighted with zero-inconsistency (FWZIC) method is extended and applied to obtain the importance weights of risk criteria. Finally, an example application of the proposed OHSRA model is presented to validate its effectiveness and advantages. The results show that the proposed OHSRA model can not only model the personalized heterogeneous linguistic risk evaluation information but also provide a reasonable risk ranking result of occupational hazards based on their relationships.

原文链接:

NETL
NSTL
Springer Nature

The Impact of Information Load on Predicting Success in Electronic Negotiations

Muhammed-Fatih KayaMareike Schoop

487-521页

查看更多>>摘要：Abstract The exchange of information is an essential means for being able to conduct negotiations and to derive situational decisions. In electronic negotiations, information is transferred in the form of requests, offers, questions and clarifications consisting of communication and decisions. Taken together, such information makes or breaks the negotiation. Whilst information analysis has traditionally been conducted through human coding, machine learning techniques now enable automated analyses. One of the grand challenges of electronic negotiation research is the generation of predictions as to whether ongoing negotiations will success or fail at the end of the negotiation process by considering the previous negotiation course. With this goal in mind, the present research paper investigates the impact of information load on predicting success and failure in electronic negotiations and how predictive machine learning models react to the successive increase of negotiation data. Information in different data combinations is used for the evaluation of various classification techniques to simulate the progress in negotiation processes and to investigate the impact of increasing information load hidden in the utility and communication data. It will be shown that the more information the merrier the result does not always hold. Instead, data-driven ML model recommendations are presented as to when and based on which data density certain models should or should not be used for the prediction of success and failure of electronic negotiations.

原文链接:

NETL
NSTL
Springer Nature

The Impact of Information Load on Predicting Success in Electronic Negotiations

Muhammed-Fatih KayaMareike Schoop

487-521页

查看更多>>摘要：Abstract The exchange of information is an essential means for being able to conduct negotiations and to derive situational decisions. In electronic negotiations, information is transferred in the form of requests, offers, questions and clarifications consisting of communication and decisions. Taken together, such information makes or breaks the negotiation. Whilst information analysis has traditionally been conducted through human coding, machine learning techniques now enable automated analyses. One of the grand challenges of electronic negotiation research is the generation of predictions as to whether ongoing negotiations will success or fail at the end of the negotiation process by considering the previous negotiation course. With this goal in mind, the present research paper investigates the impact of information load on predicting success and failure in electronic negotiations and how predictive machine learning models react to the successive increase of negotiation data. Information in different data combinations is used for the evaluation of various classification techniques to simulate the progress in negotiation processes and to investigate the impact of increasing information load hidden in the utility and communication data. It will be shown that the more information the merrier the result does not always hold. Instead, data-driven ML model recommendations are presented as to when and based on which data density certain models should or should not be used for the prediction of success and failure of electronic negotiations.

原文链接:

NETL
NSTL
Springer Nature