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The increasing demand for high-quality logistics services has forced container shipping firms to decrease logistics service failure to retain the customers. This study thus aims to apply organizational information processing theory (OIPT) to construct a maritime supply chain collaborative decision-making model and examine its impact on logistics service performance.

In total, 142 usable questionnaires were collected from questionnaire survey. A two-step structural equation modeling approach including confirmatory factor analysis was subsequently performed to test the hypotheses.

The results show that internal information integration positively impacts external information integration, that external information integration positively impacts collaborative decision-making, and that collaborative decision-making positively impacts logistics service performance for container shipping firms. However, a relationship between internal information integration and collaborative decision-making was not found in this study.

This study primarily examines collaborative decision-making from the view of container shipping firms. Future research including other supply chain members is needed to generalize the results and could also incorporate other factors such as relationship quality and culture, into the model to address this issue.

To decrease the occurrence of logistics failures and improve service quality in the maritime logistics process, it is suggested that container shipping firms apply information technology for acquiring and assimilating logistics information internally and externally across the supply chain to facilitate decision-making.

This study contributes to the knowledge about the antecedents and impacts of collaborative decision-making for container shipping firms in Taiwan. Particularly, in line with OITP, the findings indicate that container shipping firms can facilitate logistics decision-making and strategy formulation through information integration, which in turn enhances logistics service performance.

Agile principles have been widely used in software development team practice since the creation of the Agile Manifesto. Studies have examined variables related to agile principles without systematically considering the relationships among key team, agile methodology, and process variables underlying the agile principles and how these variables jointly influence the achievement of software development agility. In this study, the authors tested a team/methodology–process–agility model that links team variables (team autonomy and team competence) and methodological variable (iterative development) to process variables (communication and collaborative decision-making), which are in turn linked to software development agility (ability to sense, respond and learn).

Survey data from one hundred and sixty software development professionals were analyzed using structural equation modeling methods.

The results support the team/methodology–process–agility model. Process variables (communication and collaborative decision-making) mediated the effects of team (autonomy and competence) and methodological (iterative development) variables on software development agility. In addition, team, methodology and process variables had different effects on the three dimensions of software development agility.

The results contribute to the literature on organizational IT management by establishing a team/methodology–process–agility model that can serve as a basis for developing a core theoretical foundation underlying agile principles and practices. The results also have practical implications for organizations in understanding and managing holistically the different roles that agile methodological, team and process factors play in achieving software development agility.

Describes a study that exploits the potential of fuzzy systems in construction through the development of a decision support system which is capable of handling fuzziness in the collaborative decision‐making process. The proposed system is intended to provide an objective and rational framework within which collaborative decisions can be made by virtual construction project teams. Given the often linguistic nature of the weightings ascribed by individual disciplines to decision criteria, the proposed system will utilise fuzzy systems theory to rank criteria and recommend an optimal decision alternative. Presents an example to illustrate how the proposed tool works.

This study aims to examine how embeddedness influences consultants' information seeking when making decisions within a social network of relationships, and how these social networks evolve throughout the project delivery stages. The study is grounded in social network theory and examines embeddedness from three perspectives: structural (network cohesion), relational (tie strength in terms of friendship and knowledge awareness) and actor prominence.

A social network analysis (SNA) questionnaire was administered to a team of consultants working on a management consultancy project in Shanghai, China. The SNA measures of density, degree centrality and betweenness centrality were used to analyse relationship patterns among project team members, permitting comparison between the networks. Networks were also compared across the three project delivery stages of collect, consider and create.

Structural embeddedness was observed in the active information seeking behaviour among consultancy team members. The moderate network density of the self-organising information seeking networks across the project delivery stages ensures that the team remains connected but avoids information redundancy and overload. Relational embeddedness was evident through the multiplexity of ties among team members with overlapping friendship and information seeking relationships. The knowledge awareness network's sparseness indicates a team of autonomous knowledge workers with distributed expertise. Project managers were the most prominent actors across the three project delivery stages, underlining these actors' relational leadership role.

The study provides a deeper understanding of collaborative decision-making behaviours in dynamic-project environments. Limited attempts have been made to visualise and analyse the relationships involved in small consulting teams. The novelty of the network approach adopted stems from its ability to offer a structural view of the relationship among consultants, thus offering a distinctive and arguably more complete picture of consultancy team dynamics.

The study validates the social network theory of embeddedness in a real-world collaborative decision-making setting and provides a deeper understanding of information seeking behaviours for decision-making in dynamic-project environments. From a project management process viewpoint, the evolving nature of the information seeking network as it changes across the project stages with associated actors' roles was also visualised graphically, offering a distinctive and arguably more complete picture of consultancy team dynamics.

This study was developed in response to the need to develop age-friendly smart living environments due to the complex demands placed on society by the ageing of the population. This study aims to analyse the potential that knowledge visualisation offers collaborative decision-making applied to the development of a multiple criteria framework supporting knowledge management (KM) through knowledge collaboration (KC) and knowledge sharing (KS) in the context of regional innovation systems (RIS).

Using a socio-technical approach, knowledgeable and experienced representatives of RIS innovation actors were brought together to develop a constructivist multiple criteria framework that integrates knowledge visualisation and collaborative decision-making techniques (i.e. cognitive mapping and system dynamics).

The study introduces a multiple criteria model supporting KM encompassing conditions and practices of RIS innovation actors facilitating and encouraging KC and KS. The potential for knowledge visualisation in collaborative decision-making is explored in great depth and illustrated in a case study setting.

The panel members who participated in this study consider our methodological proposal to be extremely versatile and see great potential for further applications in RIS contexts.

The combined use of cognitive mapping and system dynamics according to the strategic options development and analysis (SODA) approach offers a holistic and well-informed perspective on the issue in question. The literature reports no prior work of this methodological combination in the same research context.

This paper aims to report work regarding the design, development and evaluation of a surface computing application to support collaborative decision making. The domain-independent application, the so-called Ideas Mapping, builds on the principle of affinity diagramming to allow participants to analyze a problem and brainstorm around possible solutions, while they actively construct a consensus artifact – a taxonomy of their ideas.

Ideas Mapping was designed using a user-centred approach. During idea generation, Ideas Mapping replicates physical post-it notes on a multi-touch tabletop. Additional functionality supports student collaboration and interaction around the organization of ideas into thematic categories associated with the problem at hand. The tool was evaluated in two studies using quantitative and qualitative data.

The paper reports on the functionality and user experience while interacting with the application. The paper also reports initial findings regarding the affordances of surface computing for collaborative decision making.

The studies reported give insides regarding the affordances of multi-touch tabletops to support collaborative decision making. Information regarding the user experience in using such applications is reported.

To provide a concise briefing on the most topical issues and relevant implications from the top 400 management publications in the world.

This briefing is prepared by an independent writer who adds their own impartial comments and places the argument in context.

Feldman's detailed study reviews the decision‐making processes – and the influences which were brought to bear on those processes – in the years before the space shuttle Challenger exploded in 1986. He demonstrates – with a carefully‐constructed view of the culture of objectivity, of how decisions are made and what knowledge is brought to bear on those decisions – how misunderstandings of flight risk resulted. Robert F. Gratton analyses President Kennedy's style of leadership and decision making during the crucial days of the Cuban missile crisis in 1962. He reveals that Kennedy adopted a questioning, Socratic approach and concludes that the collective strategy process can not truly begin until a collective aim has been decided. In addition, the strategy process is best led by a facilitator than an authoritarian, and strategy formulation is an art, guided by whatever science can be brought to bear. Howard Hills demonstrates the benefits of collaborative decision making. He identifies symptoms of teams that fail to make collaborative decisions, and offers actions a team leader may take to enable effective collaborative decisions to be made. He asserts the value of mutual respect, learning from mistakes and welcoming feedback.

Provides implementable strategies and practical thinking that has influenced some of the world's leading organizations.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

In the construction sector, the knowledge-based process outgrows its emphasis on technological aspects. Yet, there is a lack of applied studies showing how a procurement system (PS) could be selected in the digital age. In particular, there is a radical need to establish an innovative process to visualise novel PS decision. Therefore, this paper aims to present a knowledge visualised framework for aiding construction PS decision-making.

This paper describes the construction of process innovation. The framework (process) is supported by four influential decision supporting methods (mean utility values, analytic hierarchy process, fuzzy set theory and Delphi method) and computer programming (Matlab).

There are four stages of this framework: (1) uniform rating for decision alternatives; (2) group decision for determining the decision attribute; (3) determining the final choice; (4) reporting the cognitive computing process. Supported by individual and groups decision dynamics, this framework emphasises how the dashboard aided innovative approach enables the induction of understanding, cognitive computing for decision-making and how the information would precisely be represented, which are vital requirements of modern construction.

The contribution of this paper presents two leverage points that support the modern PS decision. Firstly, this paper provides a holistic view of the decision supporting methods on the basis of how a suitable PS would be systematically sought. Based on the existing studies, this paper upgrades into a visualised knowledge decision supporting process. It helps the participants understand and improve their cognitive learning. Secondly, this framework allows the participants to have a view of the individual and group decisions. It sheds light on the development of the collaborative decision-making process.