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Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

This study investigates paradox-responding strategies and enabling mechanisms in humanitarian temporary supply networks (TSNs). Given the high stakes involved in life-saving supply networks, understanding how diverse, often under-resourced, organisations jointly tackle paradoxical tensions under time pressure is crucial.

A qualitative single case study approach is adopted and a TSN deployed to meet shelter needs following the 2015 Nepal earthquake is selected as the case. The authors use diverse secondary data sources to establish how the TSN responded to paradoxical tensions.

Results show that paradox-responding in humanitarian TSNs is ongoing, dynamic and a collective effort. Most strategies entail tackling the paradoxical tensions at the same time, using the same TSN structure, but there are differences in the treatment of the paradoxical elements. Additionally, the authors find that the execution of the responding strategies is enabled by the appropriate types of network-level mechanisms which can vary in novelty, complexity, depth and reach.

This study provides rich explanations of paradox-responding and develops insights into collective action within TSNs. However, further research is needed to extend and refine insights given the single-case setting design.

This study develops a framework of paradox-responding strategies and a corresponding mix of enabling mechanisms that can guide decision-makers in the humanitarian sector when deploying TSNs.

To the best of the authors' knowledge, this is the first study that investigates paradox-responding strategies in humanitarian TSNs in particular and enabling mechanisms in general.

A shared cognitive schema is the fundamental source of tacit understanding within a team. This study aims to address how such a shared cognitive schema emerges and evolves in an interdisciplinary research team.

This study uses an exploratory single case study to analyze the emergence and evolution of a shared cognitive schema in an interdisciplinary research team systematically. The authors spent more than two years collecting data from the IAM team via semistructured interviews, archival data and observation. Subsequently, a framework for the resulting mechanism model was developed by analyzing the data using a three-step process.

This study shows that as the interdisciplinary research team develops, the shared cognitive schema passes through three stages: overlapping cognitive schema, complementary cognitive schema and synergetic cognitive schema. The mechanisms of overlap, complement and synergy play important roles. The convergent roles of partner-based recruiting, knowledge categorization and following the existing institution facilitate the overlapping of knowledge structures. Complementary cognitive schema sharing is facilitated by interdisciplinary member selection, knowledge stock expansion and the effects of accomplished mentors. The synergetic behaviors of group voice, interactive cognition and adaptive learning facilitate synergetic cognitive schema sharing.

This study is the first to discuss the emergence and evolution of a shared cognitive schema at the microlevel of knowledge structure and belief structure. It offers a new theoretical perspective on the development rules of scientific research teams and provides practical enlightenment regarding the establishment and operation of interdisciplinary research teams.

The online health community's success depends on doctors' active participation, so it is essential to understand the factors that affect doctors' knowledge contribution behavior in the online health communities. From the perspective of peer effect, this paper discusses the influence of focal doctors' peers on focal doctors' knowledge contribution behavior and the mechanism behind it. This paper aims to solve these problems.

Empirical data of 1,938 doctors were collected from a Chinese online health community, and propensity score matching and ordinary least squares were employed to verify the proposed theoretical model.

The results show that the presence of focal doctors' peers in online health communities has a positive effect on the knowledge contribution behavior of focal doctors, and the economic returns and social returns of focal doctors' peers have a significant mediating effect.

This paper discusses focal doctors' knowledge contribution behavior from the perspective of peer effect. It enhances the understanding of focal doctors' behavior in the online health communities by exploring the mediating role of their peers' economic and social returns. The results of this paper extend the research in the field of peer effect and online health and provide management implications and suggestions for online health platforms and doctors.

This paper aims to shed light on the mechanisms that connect dynamic capabilities and organizational knowledge in the innovative process to offer a new theoretical and practical solution considering the microfoundations of knowledge management strategies.

This research has emerged from an in-depth case study of an effective innovation (from just ethanol and sugar-production to an effective biomass plant). The study represents an “inductive inquiry,” useful to understand specific “organizational mechanisms” of innovation, where the main data came from in-depth interviews with 18 key actors. It proved to help search the development of a specific biomass plant, designed and implemented between 2000 and 2007 in a Brazilian ethanol and sugar-production large company, referred to here as “Energyplant.”

This solution provides a new perspective based on the idea that dynamic capabilities are context-dependent and presents an original typological map that shows and materializes dynamic capabilities as teams of human-based resources. Managerial implications can be drawn from the capabilities typological map highlighting that, although identical dynamic capabilities are not required to change different firms, idiosyncratic dynamic capabilities perform universal knowledge functions that can be mapped, contributing to the planning of a specific innovation.

While the dynamic capabilities research has been seen as one of the most vibrant topics in strategic management, scholars have recently stressed that dynamic capabilities continue to be underrated because the knowledge mechanisms that lead to effective innovations have not been adequately explored. The visual mapping is then applied to solve the reviewed theoretical problems, being also suggested to firms interested in change and adapting their capabilities to the requirements of the business environment.

Project managers' competencies contribute toward project success in a considerable manner. The significance of technical competencies' (TCs) contribution toward success in Oil and Gas (O&G) projects is even higher due to the complexity and the technology-intensive nature of these projects. However, technical competencies have often been overlooked in favor of behavioral competencies or simply identified and listed in terms of their significance. Thus, there is currently very limited research-based knowledge concerning the contribution mechanisms of technical competencies toward project execution success. Hence, the aim of this study is to explore the contribution mechanisms of TCs toward success in O&G projects.

A case study was employed as the research strategy through which data was collected from project professionals in O&G projects in the Kingdom of Bahrain using semi-structured interviews. Transcripts of the interviews were then analyzed through thematic analysis method with the aid of NVIVO 12.

The findings reveal six mechanisms through which technical competencies of project managers contribute toward execution success in O&G projects. TCs not only act as a launch pad toward project success, but also help in optimizing engineering designs throughout the project life cycle.

Instead of simply identifying and listing TCs, the obtained results enhance our current understanding of their contribution mechanisms toward project success in O&G projects.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

This study aimed to identify a specific taxonomy of entry modes for international construction contractors and to develop a decision-making mechanism based on case-based reasoning (CBR) to facilitate the selection of the most suitable entry modes.

According to the experience orientation of the construction industry, a CBR entry mode decision model was established, and based on successful historical cases, a two-step refinement process was carried out to identify similar situations. Then the validity of the model is proved by case analysis.

This study identified an entry mode taxonomy for international construction contractors (ICCs) and explored their decision-making mechanisms. First, a two-dimension model of entry mode for ICCs was constructed from ownership and value chain dimensions; seven common ICC entry modes were identified and ranked according to market commitment. Secondly, this study reveals the impact mechanism of the ICC entry mode from two aspects: the external environment and enterprise characteristics. Accordingly, an entry mode decision model is established.

Firstly, sorting out the categories of entry mode in the construction field, which provide an entry mode list for ICCs to select. Secondly, revealing the impact mechanism of ICC entry mode, which proposes a systematic decision-making system for the selection of ICC entry mode. Thirdly, constructing a CBR entry mode decision-making model from an empirical perspective, which offers tool support and reduces transaction costs in the decision-making process.

The study on entry modes for ICCs is still in the preliminary exploratory stage. The authors investigate the entry mode categories and decision-making mechanisms for ICCs based on Uppsala internationalization process theory. It widens the applied scope of Uppsala and promotes cross-disciplinary integration. In addition, the authors creatively propose a two-stage retrieval mechanism in the CBR model, which considers the order of decision variables. It refines the influence path of the decision variables on ICCs' entry mode.

The purpose of the study was to examine the factors that are important for strengthening university–industry collaboration (UIC). This study also investigates the outcome of UIC in the light of creativity, skill, knowledge, and research work.

A survey method has been used to collect data for the study. This study applied a purposive judgmental sampling technique where particular types of respondents like university faculty members and the top officials of the organizations were selected who are knowledgeable and can provide the desired information. The current study used the structural equation modeling method to analyze the data. In the first stage, this research assessed the demographic factors of the respondent. Then this study conducts confirmatory factors analysis and convergent and discriminant validity and reliability test. Finally, the hypotheses are tested by using nonparametric.

This study finds that knowledge transfer mechanism, governmental factors, organizational design factors, technology transfer and the collaborative network has a significant impact on strengthening UIC, which ultimately facilitates creativity, knowledge creation, skills development and supply of graduate according to the requirement of the industry, good research work.

The current study identified some important determinant that has a substantial influence on strengthening UIC. According to the study organizational design, government, technology, collaborative network and mechanism for knowledge transfer play very crucial roles in strengthening collaboration that ultimately increases the creativity, skills, knowledge and research capability of graduates.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.