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External stakeholder risks (ESRs) caused by unfavorable behaviors hinder the success of project portfolios (PPs). However, due to complex project dependency and numerous risk causality in PPs, assessing ESRs is difficult. This research aims to solve this problem by developing an ESR-PP two-layer fuzzy Bayesian network (FBN) model.

A two-layer FBN model for evaluating ESRs with risk causality and project dependency is proposed. The directed acyclic graph (DAG) of an ESR-PP network is first constructed, and the conditional probability tables (CPTs) of the two-layer network are further presented. Next, based on the fuzzy Bayesian network, key variables and the impact of ESRs are assessed and analyzed by using GeNIe2.3. Finally, a numerical example is used to demonstrate and verify the application of the proposed model.

The proposed model is a useable and effective approach for ESR assessment while considering risk causality and project dependency in PPs. The impact of ESRs on PP can be calculated to determine whether to control risk, and the most critical and heavily contributing risks and project(s) in the developed model are identified based on this.

This study extends prior research on PP risk in terms of stakeholders. ESRs that have received limited attention in the past are explored from an interaction perspective in the PP domain. A new two-layer FBN model considering risk causality and project dependency is proposed, which can synthesize different dependencies between projects.

Selecting and scheduling optimal project portfolio simultaneously is a complex decision-making problem faced by organizations to realize the strategy. However, dynamic synergy relationships among projects complicate this problem. This study aims at constructing a project portfolio selection and scheduling (PPSS) model while quantifying the dynamic synergetic effects to provide decision support for managing PPSS problems.

This study develops a mathematical model for PPSS with the objective of maximal project portfolio benefits (PPBs). To make the results align with the strategy, comprehensive PPBs are divided into financial and non-financial aspects based on the balanced scorecard. Then, synergy benefits evolve dynamically in the time horizon, and system dynamics is employed to quantify them. Lastly, a case example is conducted to verify the applicability of the proposed model.

The proposed model is an applicable model for PPSS while incorporating dynamic synergy. It can help project managers obtain the results that which project should be selected and when it should start while achieving optimal PPBs.

This study complements prior PPSS research in two aspects. First, financial and non-financial PPBs are designed as new criteria for PPSS, making the results follow the strategy. Second, this study illuminates the dynamic characteristic of synergy and quantifies the synergetic effect. The proposed model provides insights into managing a PPSS effectively.

This paper is to contribute to addressing the knowledge gap on the roles of rural cooperatives in disaster risk reduction and management (DRRM).

This study adopts a mixed-methods approach highlighting indigenous strategies of community engagement – the pantatabtaval/tong tongan (brainstorming and dialogs), pan-iestorya/dad-at (storytelling session) and field observations with 50 village-level cooperatives in Benguet, Philippines to understand their contributions to local DRRM.

Rural cooperatives in Benguet have evolved on their context of service from mere rural development to now include DRRM donations and aid for disaster-affected families, credit and loans are the most common services of these rural cooperative extended to their members to deal with risks of disasters.

Most research on cooperatives focuses on their contribution to socio-economic development and only few dealt with DRRM. This paper explores the link of these rural organizations with DRRM drawing evidence from cooperatives in the rural communities of Benguet, Philippines.

This study aims to propose a model-free statistic that tests asymmetric correlations of stock returns, in which stocks move more often with the market when the market goes down than when it goes up, and then empirically analyze the asymmetric correlations of the China stock market and international stock markets, respectively.

Using empirical likelihood method, this study designs and conducts a model-free test, which converges to χ2 distribution under regulated conditions and performs well in the finite sample using bootstrap critical value method.

By analyzing the authors' model-free test, the authors find that compared with Hong et al.'s test that closely relates to the authors, both of the tests are under rejected using asymptotic critical value. However, using the bootstrap critical value method can greatly improve the performance of the two tests. Second, investigating the power of the two tests, the authors find that the proportion of rejections of the authors' test is roughly 10-20 percent larger than Hong et al.'s test in mixed copula model setting. The last finding is the authors find evidence of asymmetric for small-cap size portfolios, but no evidence for middle-cap and large-cap size portfolios in the China stock market. Besides, the authors test asymmetric correlations between the USA and Japan, France and the UK; the asymmetric phenomenon exists in international stock markets, which is similar to Longin and Solnik's findings, but they are not significant according to both the authors' test and Hong et al.'s test.

The findings in this study suggest that both the authors' test and Hong et al.'s test are under rejected using asymptotic critical value. When applying these statistics to test asymmetric correlations, the authors should take care with the choice of critical value.

The empirical analysis has a significant practical implication for asset allocation, asset pricing and risk management fields.

This study constructs a model-free statistic to test asymmetric correlations using empirical likelihood method for the first time and corrects the size performance by bootstrap method, which improves the performance of Hong et al.'s test. To the authors' knowledge, this is the first study to test the asymmetric correlations in the China stock market.

The purpose of the work is to provide a comprehensive review of the digital image correlation (DIC) technique for those who are interested in performing the DIC technique in the area of manufacturing.

No methodology was used because the paper is a review article.

no fundings.

Herein, the historical development, main strengths and measurement setup of DIC are introduced. Subsequently, the basic principles of the DIC technique are outlined in detail. The analysis of measurement accuracy associated with experimental factors and correlation algorithms is discussed and some useful recommendations for reducing measurement errors are also offered. Then, the utilization of DIC in different manufacturing fields (e.g. cutting, welding, forming and additive manufacturing) is summarized. Finally, the current challenges and prospects of DIC in intelligent manufacturing are discussed.

This study investigates the influence of e-marketing risks on a Corporation’s Reputation (CR) resulting from its online marketing of products and services.

A comprehensive analysis was conducted to enhance the company’s e-marketing strategies and bolster its reputation in the market. This involved an investigation into key factors of e-marketing risks, such as customer confidence, product quality, marketing fraud, credibility and customer knowledge and proficiency in using online platforms. These factors have directly impacted the company’s reputation, including aspects such as product/service quality, attractiveness, performance and commitment to social responsibility.

Its finding indicates that customers' lack of confidence in e-marketing has a strong impact on CR, followed by product quality and credibility. The absence of consumer awareness about e-marketing websites and e-fraud frequently negatively affects the organizational reputation.

To enhance the corporation’s reputation, it is recommended that companies provide educational resources on online shopping, including guidance on using the company’s website, comparing prices and other services that facilitate online purchases. This will help to support the credibility of e-marketing and enhance customer trust.

This research is an exploration of how e-marketing has affected a Corporation’s Reputation. It provides modern knowledge about the dynamic interplay between digital strategies and brand perception. Investigating this relationship provides valuable insights into the evolving landscape of consumer trust in the digital age. By analysing the various ways in which e-marketing influences a company’s reputation, innovative approaches can be developed to enhance its online presence and build lasting customer trust.

This paper aims to investigate an identification strategy for the nonlinear state-space model (SSM) in the presence of an unknown output time-delay. The equations to estimate the unknown model parameters and output time-delay are derived simultaneously in the proposed strategy.

The unknown integer-valued time-delay is processed as a latent variable which is uniformly distributed in a priori known range. The estimations of the unknown time-delay and model parameters are both realized using the Expectation-Maximization (EM) algorithm, which has a good performance in dealing with latent variable issues. Moreover, the particle filter (PF) with an unknown time-delay is introduced to calculated the Q-function of the EM algorithm.

Although amounts of effective approaches for nonlinear SSM identification have been developed in the literature, the problem of time-delay is not considered in most of them. The time-delay is commonly existed in industrial scenario and it could cause extra difficulties for industrial process modeling. The problem of unknown output time-delay is considered in this paper, and the validity of the proposed approach is demonstrated through the numerical example and a two-link manipulator system.

The novel approach to identify the nonlinear SSM in the presence of an unknown output time-delay with EM algorithm is put forward in this work.

While the concept of cultural competence has emerged as a major contribution to improving migrants' and minority ethnic (MME) health, what constitutes culturally competent health promotion is less well understood. This paper explores the tension between the concept of cultural competence and community empowerment through an analysis of the author's recent experience of a participatory video project in which four ethnic/language groups were involved in the production of a breast‐screening video. It illustrates the engagement of migrants and minority ethnic communities in different stages of the video production process, and critically reflects on how this experience could be understood. It concludes that culturally competent health promotion requires us to go beyond language and cultural sensitivity to engage critically with communities to participate in health promotion activities. Participatory video has the potential not only to promote health messages in the communities, but also to strengthen capacity and cultural identities.

This paper aims to propose a new knowledge creation model called Grey SECI (G-SECI), study the knowledge creation mechanism and the relationship between knowledge creation models and innovation performance during complex product systems (CoPSs) development. Research and development of CoPSs relies heavily on knowledge creation. However, most scholars have studied CoPS innovation stages from the view of design process of system products, focussing on functional management and project management during the R&D process for CoPS. Attention is lacking with regards to the key and essence of creating a complex technology: the creation of knowledge.

Modified from the classic SECI model’s spiral process of knowledge creation, a grey-SECI (G-SECI) knowledge creation model is here proposed vis-à-vis three knowledge categories: explicit knowledge, grey knowledge and tacit knowledge. Then, this paper further analyzes the effects of knowledge creation from the perspective of individual and the view of organization. Besides, an empirical study is conducted.

Statistical analysis indicates that there are three main paths of knowledge creation: individual experience knowledge acquisition, individual communication and reflection and organizational knowledge learning. Results further suggest that knowledge internalization by practice (KIP) is the key mode of knowledge creation, as well as the most important step for high-quality CoPS performance. Moreover, individual innovation performance is influenced by knowledge internalization by reflection and KIP; and organization innovation performance is influenced by knowledge combination and knowledge systematization.

The coverage of geographical distribution is limited. Therefore, there are no data from foreign enterprises. The impact of different geographical cultures on CoPS knowledge creation model could be further investigated; in addition, the statistical analysis results of this study need to be further verified in other industries.

This paper provides a series of insights for CoPS project leaders. The results may also provide practical guidance for the related management personnel in the fields of human resource training, project planning, project quality and technology R&D in CoPS R&D management.

The paper’s main contribution is to modify classic SECI knowledge conversion model by introducing grey knowledge and build a new G-SECI knowledge creation model. Besides, the paper adds empirical evidence on the knowledge creation paths in CoPS and reveals that internalization by practice is the key mode of knowledge creation.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.