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Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.

We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.

The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.

This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.

Drawing on Suchman’s conception of cognitive legitimacy and Boswell’s account of the political functions of expert knowledge, this paper aims to study the due process followed by the International Integrated Reporting Council (IIRC) prior to the publication of the first version of the International Integrated Reporting Framework (IIRF). Specifically, the author analyses the lobbying strategies used in the comment letters sent by a subset of lobbyists, “the experts”, represented by accounting bodies and firms, regulators and academics.

From both a form- and meaning-oriented analysis, this paper focuses on how the experts resorted to the functions of knowledge when they took part in the IIRF’s public consultation. The author first carries out a quantitative content analysis of the responses to the 2013 Consultation Draft submitted by those constituents considered as accounting expert lobbyists. Then, the author analyse how these actors framed their comments under expert knowledge to legitimise the IIRC, the IIRF and the accounting profession itself.

The findings suggest that the expert groups welcomed the opportunity, not simply to legitimise the IIRC through their democratic support, but to provide a technocratic settlement that ensures the due process is based on the mobilisation of expert knowledge as a legitimate source. By drawing on the cognitive legitimacy of expert lobbyists, the IIRC drew on the political functions of expert knowledge to reduce uncertainty and gain stability.

Analysis of the lobbying strategies used by the accounting experts whose position could make a difference and receive more attention from the IIRC makes this contribution of particular interest, especially since the first version of the IIRF sought to guide disclosure and sustainable business practices around the world.

Experts as political actors play a legitimising role since they are capable of producing relevant knowledge that, due to its nature and scope, certainly affects policymaking and sustainable development.

This research provides a sociopolitical perspective to comprehend how some lobbying strategies, in this case, of expert actors, contribute to legitimising a standard-setter body and its endeavours in the context of voluntary standards.

The “experience is the best teacher” model assumes that acquiring expertise in a given domain reduces biases. Research in expert knowledge in investment decisions has shown better ability to produce improved results in asset selection or portfolio returns. Universities created student-managed investment funds (SMIFs) to train students in portfolio management as fiduciaries. However, analyses of the effectiveness of the SMIF as a medium for expert knowledge transfer have not been done.

The authors’ analyze an SMIF's structure against established models of expert knowledge transfer, using the voting patterns of the trustees of the fund from the recorded minutes of the fund's meetings to show the fund's structure and outcomes demonstrate effective knowledge transfer. Voter consensus between faculty and student trustees is one proxy the authors use for knowledge transfer.

Consensus between faculty and students was uniformly high across all recommendations. Chi-square tests were employed to test for independence between approval of recommendation and level of consensus, showing dependence in most cases. Analysis of sale returns over the 12-year sample period showed significantly better performance of asset sales over relevant benchmarks for both equity and fixed income portfolios.

Most analyses of SMIF structure concentrate on well-known issues with things like student turnover, summers or other structural issues. Performance is evaluated based on returns. This study looks at the SMIF as an expert knowledge transfer medium and examines expert/novice decision approval in terms of knowledge transfer.

Credit risk evaluation is a crucial task for banks and non-bank financial institutions to support decision-making on granting loans. Most of the current credit risk methods rely solely on expert knowledge or large amounts of data, which causes some problems like variable interactions hard to be identified, models lack interpretability, etc. To address these issues, the authors propose a new approach.

First, the authors improve interpretive structural model (ISM) to better capture and utilize expert knowledge, then combine expert knowledge with big data and the proposed fuzzy interpretive structural model (FISM) and K2 are used for expert knowledge acquisition and big data learning, respectively. The Bayesian network (BN) obtained is used for forward inference and backward inference. Data from Lending Club demonstrates the effectiveness of the proposed model.

Compared with the mainstream risk evaluation methods, the authors’ approach not only has higher accuracy and better presents the interaction between risk variables but also provide decision-makers with the best possible interventions in advance to avoid defaults in the financial field. The credit risk assessment framework based on the proposed method can serve as an effective tool for relevant policymakers.

The authors propose a novel credit risk evaluation approach, namely FISM-K2. It is a decision support method that can improve the ability of decision makers to predict risks and intervene in advance. As an attempt to combine expert knowledge and big data, the authors’ work enriches the research on financial risk.

Indigenous knowledge is an essential element for unveiling the evolutionary journey of socio-culture phenomena. One of the key challenges in foresight exercises is to incorporate social-culture issues such as culture, lifestyle and behavior (referred as indigenous knowledge) into the study. However, the statistical trends of those factors tend to be either not available or limited unlike the population or economic related factors. The purpose of this study is to present the use of valuable data from indigenous knowledge to enhance the foresight exercise through the better understanding of social dynamics and changes.

The fragmented form of indigenous knowledge is analyzed and converted into a structured data format and then interpreted to unveil the evolutionary journey of socio-cultural phenomena. This study applies a scenario development method to visualize the results of foresight by comparing before and after the integration of indigenous knowledge. Finally, an assessment was conducted to reflect the value enhancement resulting from the integration of indigenous knowledge into the foresight process.

With the proposed approach, the foresight study on the future development of Thai food was demonstrated. The findings of this study show that the use of indigenous knowledge on eating behavior, cooking style and food flavor helps improve the alternative scenarios for the future development of Thai foods.

Indigenous knowledge can be applied to develop plausible scenarios and future images in foresight exercises. However, by nature, indigenous knowledge is not well-structured and, therefore, needs to be analyzed and turned into structured data so that it can be interpreted before integrating into the foresight process.

This study is one of few studies addressing the opportunities for integrating indigenous knowledge into foresight process. Indigenous knowledge can unveil the evolution of socio-cultural changes to improve the results of foresight study, especially the cases where statistical data and trends may not be sufficient to foresee future development.

The purpose of this paper is to study the implications of managing human resource (HR) flexibility and absorptive capacity (AC) of knowledge for the implementation of agile innovation methods in the new product development (NPD) process of manufacturing firms.

To achieve this, the authors have carried out a meta-analysis by defining first a research question that determines the design of bibliometric data and compilation. The study question is: How firms can support agile initiatives in innovation considering their HR flexibility and AC? The Web of Science Collection has been consulted in three steps with several search strings. The analysis of 161 references without duplicities in the period 1997–2021 provides the foundations for exploring the research question.

The authors propose research hypotheses to analyze the interrelationship between HR flexibility, AC and agile innovation according to the literature-based discussion. The authors have identified and develop metrics to pilot the transition to agile that have been also adapted to specific innovation departures points before the transition. The authors also propose and discuss some organizational changes and practical guidelines to pilot transitions to agile that should be useful to the firm’s strategic decision of implementing the most adequate type of agile innovation.

Even though flexibility and innovation are very important needs for many firms, agile schemes are still under-studied topics in the NPD of manufacturing firms. There are no specific studies in the literature that analyze the interrelationship between HR flexibility, AC and agile innovation, identifying common aspects and different approaches. Thus, this study is of original nature and the developed managerial tools, composed of metrics and organizational changes, will be useful to managers and permitted the authors to achieve the proposed goal.

In traditional Bayesian belief networks (BBNs), a large amount of data are required to complete network parameters, which makes it impractical. In addition, no systematic method has been used to create the structure of the BBN. The aims of this study are to: (1) decrease the number of questions and time and effort required for completing the parameters of the BBN and (2) present a simple and apprehensible method for creating the BBN structure based on the expert knowledge.

In this study, by combining the decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modeling (ISM) and BBN, a model is introduced that can form the project risk network and analyze the impact of risk factors on project cost quantitatively based on the expert knowledge. The ranked node method (RNM) is then used to complete the parametric part of the BBN using the same data obtained from the experts to analyze DEMATEL.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively. The obtained results are based on a single case study project and may not be readily generalizable.

The presented framework makes the BBN more practical for quantitatively assessing the impact of risk on project costs. This helps to manage financial issues, which is one of the main reasons for project bankruptcy.

Drawing on open innovation and knowledge-based view, this study was initiated by investigating the fact that despite the growing literature on external knowledge being important for bridging the knowledge gap across the new product development (NPD) processes, gaps exist to explore as to what are the potential knowledge sources and their contribution for the Fuzzy-Front end (FFE-) (i.e. idea-generation) phase of the NPD process?

Thirty-seven open-ended interviews with the NPD managers in large firms from the Chemicals and Electronic industries have been conducted to collect the data following thematic analysis into NVIvo 12.

The findings reveal customers, suppliers and external research organizations are the potential knowledge sources. Each of the sources delivers distinct knowledge for FFE of the NPD process. The empirical analysis of this study demonstrates that each of the potential knowledge sources though bridges the knowledge gap that innovative firms seek for the FFE of the NPD process, however collaboration with such sources incurs significant costs, risks, resources, capabilities and management practices which differs noticeably among different kinds of knowledge sources.

Managers must need assessing not just the gains but also the pains associated with each of the knowledge source before deciding to make additional investments in terms of resources and capabilities dedicated to learning from them while considering any of these for the FFE.

This new conceptualization of FFE offers a better theoretical and practical rationale for how and what types of different sources of knowledge can bridge the knowledge gaps for the FFE of NPD processes provided that innovative firms have necessary resources to entail a successful collaboration.

Small and medium-sized enterprises (SMEs) are a major source of employment and revenue growth in developing nations like India, but they also face challenges from resource shortages, shifting consumer demand and heightened competition. This research aims to discover the aspects that enhance SMEs' competitiveness and performance.

By analyzing literature and consulting experts, 10 factors that boost a firm's competitiveness were identified. The total interpretive structural modeling (TISM) method was then used to determine their interaction and structural hierarchy. Neutrosophic-MICMAC analysis was employed to assess the driving-dependence power of each factor.

The study discovered that the factor, namely “entrepreneurial orientation,” was found to be a significant one. “Manufacturing strategy” was found to be extremely dependent on the remaining competitive advantage factors.

This SME-focused framework can be adopted by large businesses to enhance organizational performance by focusing on critical factors. The study depends on experts' judgment, which might be biased. Findings will assist SMEs in identifying significant factors influencing competitive advantage and relationships, increasing awareness of factors contributing to competitive edge.

The results of the research may encourage SME sector managers and practitioners to prioritize the factors that contribute to a firm's competitive advantage.

The majority of research on SME competitive advantage focuses on individual aspects. To add to the body of knowledge on the subject, this study applies the TISM technique to Indian SMEs to identify the contextual interactions among factors that increase long-term competitiveness.