Search results

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

A crucial issue in educational management refers to helping teachers reach their full potential and manage their talents. Although managing talent is advised as an essential resource for organizational transformation to maximize performance and to promote a school’s knowledge capital increase, Teachers’ talent management (TTM) is not an agreed-upon concept in the literature. The aim of this study is threefold: (1) to propose a theoretical and operational TTM definition, (2) to develop a test to measure TTM and (3) to discuss the value of TTM implementation in educational settings.

A psychometric validation design according to international standards for test development is implemented. A cross-sectional intentional sampling with 200 schools is used for obtaining reliability and validity evidence. We operationalized TTM using 9 factors (10 items per factor, 6-point Likert scale): attraction, selection, development, retention, succession, climate, culture, evaluation and knowledge management.

Results show adequate evidence of reliability and validity, focusing on items' content and latent structure. The combined use of structural equation models (SEM) and psychometric networks (PN) detects a six-factor model with a test reduced version including 61 items, getting 64.28% of the total explained variance and adequate reliability indices and factor loadings.

The Teachers' Talent Management Assessment Test (TTMAT) can contribute educational institutions to create a culture of excellence and deliver the best possible education to their students. Educational transformation will only happen if teachers are professionalized, trained, motivated and supported to inspire and to guide their learners to reach their objectives and well-being.

This paper argues for the need to use multiple sources and methods that respond to research challenges presented by new forms of war. There are methodological constraints and contention on the superiority given to positivist and interpretivist research designs when doing fieldwork in war situations, hence there is a need to use integrated data generation techniques. The combined effect of severe limitations of movement for both the researcher and researched fragmented data because of polarized views about the causes of the war and unpredictable events that make information hard to come by militate against systematic, organised and robust data generation. The purpose of this paper, therefore, is to make fieldwork researchers understand significant research problems unique to war zones.

This research was guided by the postmodernist mode of thought which challenges standardised research traditions. Fieldwork experiences in Cabo suggest the need to use the composite strategies that rely on the theoretical foundation of integrative and creative collection of data when doing research in violent settings.

The fieldwork experiences showed that the standardised, conventional and valorised positivist and ethnographic research strategies may not sufficiently facilitate understanding of the dynamics of war. There should not be firm rules, guidelines or regulations governing the actions of the researcher in conflict. As such, doing research in violent settings require reflexivity, flexibility and creativity in research strategies that respond to rapid changes. Research experiences in Mozambique show the need to use blended methods that include even less structured methodologies.

Fieldwork experiences in Cabo challenges researchers who cling to standardised research traditions which often hamper awareness of new postmodernist mode of thought applicable to war settings. It is essential to study the nature of African armed conflicts by combining creativity and flexibility in the selection of research strategies.

This study aims to apply for the first time in literature a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm and test the sensors' configuration found in a delamination identification case study.

This work aims to study the damage identification in an aircraft wing using the Lichtenberg and multi-objective Lichtenberg algorithms. The former is used to identify damages, while the last is associated with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time.

The proposed method was not only able to find a sensor configuration for each sensor number and modal metric but also found one that had full accuracy in identifying delamination location and severity considering triaxial modal displacements and minimal sensor number for all wing sections.

This study demonstrates for the first time in the literature how the most used modal metrics vary with the sensor number for an aircraft wing using a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm.

The purpose of this paper is to discuss the issues in studying hard-to-reach or dispersed populations, with particular focus on methodologies used to collect data and to investigate dispersed migrant entrepreneurs, illustrating shortcomings, pitfalls and potentials of accessing and disseminating research to hard-to-reach populations of migrant entrepreneurs.

A mixed methodology is proposed to access hard-to-reach or dispersed populations, and this paper explores these using a sample of Brazilian migrants settled in different countries of the world.

This paper explores empirical challenges, illustrating shortcomings, pitfalls and potentials of accessing and disseminating research to hard-to-reach populations of migrant entrepreneurs. It provides insights by reporting research experiences developed over time by this group of researchers, reflecting a “mixing” of methods for accessing respondents, contrasting to a more rigid, a-priori, mixed methods approach.

The main contribution of this paper is to showcase experiences from, and suitability of, remote data collection, especially for projects that cannot accommodate the physical participation of researchers, either because of time or cost constraints. It reports on researching migrant entrepreneurship overseas. Remote digital tools and online data collection are highly relevant due to time- and cost-efficiency, but also represent solutions for researching dispersed populations. These approaches presented allow for overcoming several barriers to data collection and present instrumental characteristics for migrant research.

This paper aims to examine the conditions under which small and medium enterprises (SMEs) invest in security services when they migrate their e-commerce applications to the cloud environment. Using a risk management perspective, the paper assesses the impact of security service pricing, security incident prevalence and virulence to estimate SME security spending at the market level and draw out implications for SMEs and security service providers.

Security risks are inherently characterized by uncertainty. This study uses a Monte Carlo approach to understand the role of uncertainty in the decision to adopt security services. A model relating key security constructs is assembled based on key constructs from the domain. By manipulating security service costs and security incident types, the model estimates the market-level adoption of services, security incidents and damages incurred, along with measures of their relative dispersion.

Three key findings emerge from this study. First, adoption of services and protection is higher when tiered security services are provided, indicating that SMEs prefer to choose their security services rather than accept uniformly priced products. Second, SMEs are considered price-sensitive, resulting in a maximum level of spending in the market. Third, results indicate that security incidents and damages can be much higher than the mean in some cases, and this should serve as a cautionary note to SMEs.

Security spending has been modeled at the firm level. Adopting a market-level perspective represents a novel contribution. Additionally, the Monte Carlo approach provides managers with tangible measures of uncertainty, affording additional information and insight when making security service adoption decisions.

The study hypothesized that the impact of board diversity on financial distress (FD) is not direct but rather mediated by the firm’s corporate social responsibility (CSR) activities. Consequently, the purpose of this study is to examine the impact of CSR as a mediator in the board diversity–FD relationship.

The study examined six board diversity dimensions – age, gender, nationality, education and tenure in 81 nonfinancial Pakistan Stock Exchange (PSX)-listed firms from 2010 to 2021. The CSR engagement of the sample firms is evaluated using a multidimensional financial approach and the likelihood of FD is computed using Altman’s Z-score. The system-generalized method of moments estimator is used to meet the study objectives. In addition, several tests are run to determine the robustness of the study’s findings.

Based on the procedure for mediation analysis outlined by Baron and Kenny (1986), the authors found that CSR is significantly inversely associated with the likelihood of FD. Second, board diversity variables age, gender and national diversity were positively associated with CSR. Third, board age, gender and national diversity are significantly inversely related to FD. Finally, it was found that there is partial mediation between board age diversity and FD, whereas full mediation is shown between board age diversity and FD and between board nationality diversity and FD.

This study provides practical insights into PSX’s board diversity for companies, regulators and policymakers.

This research studies the connection between board diversity and FD. In addition, the current study extended the analysis by testing for the first time the mediating role of CSR in the diversity–distress relationship, particularly in the context of an emerging economy.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

The purpose of this paper is to propose a consensus method for multi-attribute group decision-making (MAGDM) problems based on preference-approval structure and regret theory, which can improve the efficiency of decision-making and promote the consensus level among individuals.

First, a new method to obtain the reference points based on regret theory and expert weighting method is proposed. Second, a consensus reaching method based on preference-approval structure is proposed. Then, an adjustment mechanism to further improve the consensus level between individuals is designed. Finally, an example of the assessment of elderly care institutions is used to illustrate the feasibility and effectiveness of the proposed method.

The feasibility and validity of the proposed method are verified by comparing with the advanced two-stage minimum adjustment method. The compared results show that the proposed method is more consistent with the actual situation.

This paper presents a consensus reaching method for MAGDM based on preference-approval structure, which considers the avoidance behaviors of individuals and reference points. Decision makers (DMs) can use this approach to rank and categorize alternatives while further increasing the level of consensus among them. This can further help determine the optimal alternative more efficiently.

A new MAGDM problem based on the combination of regret theory and individual reference points is proposed. Besides, a new method of obtaining experts' weights and a consensus reaching method for MAGDM based on preference-approval structure are designed.