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The purpose of this paper is to investigate the influence of key parameters on the bond strength and failure modes of laminated structures made of different aluminum alloys (i.e. Al 2024 and Al 7075) via the ultrasonic consolidation (UC) process.

The UC is used to fabricate laminated structures with various parameters. The push-pin tests were performed on the specimens of different materials and parameters, and the force and displacement were recorded during the tests. The peak punch force was used to represent the bond quality of the laminated structure, and the curves of force versus displacement were used to study the failure modes of the structures.

It is found that the lower normal force, the larger vibration amplitude and the lower travel speed can result in stronger bonding. Three different failure modes are observed in the tests, due to the different relations between the toughness of interface and raw materials. The process parameters have influence on the interface toughness of a laminated structure, which further leads to different failure modes.

The overall mechanical properties of a laminated structure highly depend on the bond quality between laminated layers. The push-pin test can easily and effectively evaluate the bond quality of the laminated structure. This paper not only focuses on the bond strength evaluation, but also analyzes the different failure modes of laminated structures made of different aluminum alloys, which can give an opportunity to optimize the parameters for different materials.

Project knowledge in the construction context needs to be disseminated within organisations to improve organisations’ performance and learning. Much of project knowledge is tacit, residing in social interactions in team relationships, and likely to be disseminated through social networks and processes within organisations. Social capital comprises both the network of strong personal relationships and the knowledge resources that may be mobilised through that network. The purpose of this paper is to explore the role of “networks” in disseminating project knowledge within the construction organisations in Sri Lanka.

The case study research method was used to investigate the research problem. The principal data collection technique used was semi-structured interviews. Content analysis, tables and cognitive maps were used to analyse data.

The findings revealed that strong network ties created with equal interaction of project and head office (H/O) individuals, frequent connectivity and much closer relationships enhance the flexibility of sharing project knowledge. The available invisible informal social networks within project and H/O individuals play a key role in disseminating project knowledge compared to business networks.

This research offers useful implications for construction organisation, in particular, to pay careful attention to nurture networks within their organisations in order to benefit from disseminating project knowledge widely within the organisations for effective re-use in future.

The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

The purpose of this paper is to assess the water resources vulnerability (WRV) rationally in Haihe River Basin (HRB) using set pair analysis (SPA) theory.

An improved intelligent set pair analysis (IISPA) model is established, in which intelligent SPA theory is introduced and the weights are determined by use of the maximum entropy principle and the improved analytic hierarchy process method. The index systems and criteria of WRV assessment in terms of water cycle, socio-economy, and ecological environment are established based on the analysis of sensibility and adaptability.

The authors apply IISPA to the WRV assessment of seven administrative divisions in HRB. Results show IISPA can fully take advantage of certain and uncertain information compared with fuzzy assessment and topsis assessment models. For present situation, Shanxi, Shandong, Tianjing, Inner Mongolia, Hebei are higher, Henan and Beijing are the middle vulnerability. But Henan will become worse under climate change scenario II and IV.

The analysis results may be affected by the limited climate change data.

It is helpful for further research to the complexity analysis of water resources system.

This paper will have an important impact on water resources sustainable utilization.

This is the first time to utilize IISPA method to analyze the WRV of seven administrative divisions in HRB. This paper provides an important theoretical support for water resources management.

Proactive career behavior (PCB) is an effective form of career self-management that has positive impacts on individual career development and career success, and therefore, the purpose of this paper is to explore the driving factors of PCB.

Drawing on the interactionist perspective and situational strength theory, this study examined the independent and joint effects of role commitment and pay-for-performance (PFP) on employees' PCB based on data collected from 298 Chinese private enterprise employees at two time points.

The authors found that occupational role commitment (ORC), parental role commitment (PRC) and PFP were positively related to PCB. Furthermore, PFP moderated the relationship between ORC/PRC and PCB, such that the two relationships were stronger when PFP was low.

Drawing on the interactionist perspective, the authors contribute to the literature on PCB by revealing novel antecedents of PCB: ORC, PRC and PFP. The authors also contribute to the situational strength theory by examining how role commitment and PFP may interact to impact employees' PCB. Finally, the authors are among the first to consider the effects of role commitment on individual career behaviors, thus extending the nomological network of role commitment.

The purpose of this paper is to investigate and uncover key determinants that could explain partners' commitment to risk management in public‐private partnership projects so that partners' risk management commitment is taken into the consideration of optimal risk allocation strategies.

Based on an extensive literature review and an examination of the purchasing power parity (PPP) market, an industry‐wide questionnaire survey was conducted to collect the data for a confirmatory factor analysis. Necessary statistical tests are conducted to ensure the validity of the analysis results.

The factor analysis results show that the procedure of confirmatory factor analysis is statistically appropriate and satisfactory. As a result, partners' organizational commitment to risk management in public‐private partnerships can now be determined by a set of components, namely general attitude to a risk, perceived one's own ability to manage a risk, and the perceived reward for bearing a risk.

It is recommended, based on the empirical results shown in this paper, that, in addition to partners' risk management capability, decision‐makers, both from public and private sectors, should also seriously consider partners' risk management commitment. Both factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects. Future research may therefore explore how to form optimal risk allocation strategies by integrating organizational capability and commitment, the determinants and measurement of which have been established in this study.

This paper makes an original contribution to the general body of knowledge on risk allocation in large‐scale infrastructure projects in Australia adopting the procurement method of public‐private partnership. In particular, this paper has innovatively established a measurement model of organisational commitment to risk management, which is crucial to determining optimal risk allocation strategies and in turn achieving project success. The score coefficients of all obtained components can be used to construct components by linear combination so that commitment to risk management can be measured. Previous research has barely focused on this topic.

The purpose of this paper is to examine how signals of uncertainty in the media affect retail investor decisions and initial public offering (IPO) underpricing through theoretical and empirical methods.

The authors construct a theoretical model of the influence of media signals on IPO pricing, which describes the micro process in which uncertain signals in media influence retail investors’ decisions and IPO underpricing. Besides, the authors take 516 small and medium-size enterprises (SMEs) listed in A-share from July 2009 to December 2012 as samples for empirical tests and establish an in-depth learning model for text analysis with Java programming to measure Chinese media tone. Finally, the results of the model analysis are verified by empirical results.

The results show that authoritative media with high credibility can reduce the uncertainty of information sources attract more investors’ attention and improve the valuation and demand of retail investors. The higher the media credibility is the higher the IPO underpricing rate is. The uncertain tone of the media will increase the decision-making cost of investors reduce the valuation expectation and demand of the secondary market and lead to a lower IPO underpricing rate.

The authors study the influence of the uncertainty of media source and media content on the degree of IPO underpricing of SMEs. This is a useful supplement to the Chinese media tone research system that is still in the exploration stage. The research has reference value for government regulation and investor decision-making.

The purpose of this paper is to accurately simulate and predict the daily extreme temperature in Beijing Reservoir and the monthly extreme temperature in Tianjin Reservoir using wavelet refined rank set pair analysis (WRRSPA).

The new method, called WRRSPA, which combines wavelet analysis and refined rank set pair analysis (RRSPA), was proposed for use in this study because of the non-linear and multi-time scale characteristics of the temperature series. The model includes the advantages of the multi-resolution feature of wavelet analysis and the non-parametric data-driven prediction from refined rank set air analysis.

Based on the daily extreme temperature of Beijing Reservoir, the predictions of the last 18 days reveal that WRRSPA is more appropriate because the percentage of the relative errors that are smaller than 10 percent increased from 78 percent by Back Propagation (BP) and 78 percent by RRSPA to 100 percent by WRRSPA in Beijing Reservoir. In addition, WRRSPA has lower values of root mean squared error (RMSE) and mean absolute error (MAE) and a higher coefficient of efficiency (modified coefficient of efficiency (MCE)). The last 12 monthly extreme temperature predictions of Tianjin Reservoir demonstrate that WRRSPA produces prediction results: the percentage of relative errors that are smaller than 10 percent are improved from 34 percent by BP and 58 percent by RRSPA to 67 percent by WRRSPA. In addition, WRRSPA also has lower values of RMSE and MAE and a higher coefficient of efficiency (MCE).

The analysis results ignore the physical processes and may be affected by the limited observation data. In addition, the WRRSPA method is still in its early stages of application and must be further tested.

The results of the study are helpful for the study of the complex features and accurate prediction of temperature series.

This paper contributes to further the process of research of climate change.

This study represents the first use of the WRRSPA method to analyze the multi-scale characteristics and forecast the future values of the extreme temperature series from Beijing Reservoir and Tianjin Reservoir. This paper provides an important theoretical support for extreme temperature prediction.

This case study examines the application of a known leadership theory, Transformational Leadership, within the student organization at a large U.S. university, during a time period when the organization was undergoing significant leadership turnover and impending dissolution of the club. By applying principles of Transformational Leadership, the organization’s President was able to foster a cohesive team of organization officers, to grow the organization membership population, and to achieve organization goals. As this phenomenon under study is highly context-dependent, the case study approach will better demonstrate the theory’s effects within these specific circumstances than will an esoteric, quantitative research approach. Let the findings from this case be an example for other student organizations and leadership teams to generate results with a leadership theory.

Barge-type offshore floating wind turbine (OFWT) commonly exhibits an under-actuated phenomenon in an offshore environment, which leads to a potential vibration-damping hazard. This article aims to provide a new robust output feedback anti-vibrational control scheme for the novel translational oscillator with rotational actuator (TORA) based five-degrees of freedom (5-DOF) barge-type OFWT in the presence of unwanted disturbances and modeling uncertainties.

In this paper, an active control technique called TORA has been used to design a 5-DOF barge-type OFWT model, where the mathematical model of the proposed system is derived by using Euler–Lagrange's equations. The robust hierarchical backstepping integral nonsingular terminal sliding mode control (HBINTSMC) with an adaptive gain is used in conjunction with extended order high gain observer (EHGO) to achieve system stabilization in the presence of unwanted disturbances and modeling uncertainties. The numerical simulations based on MATLAB/SIMULINK have been performed to demonstrate the feasibility and effectiveness of the proposed model and control law.

The numerical simulation results affirm the accuracy and efficiency of the proposed control law for the TORA based OFWT system. The results demonstrate that the proposed control law is robust against unwanted disturbances and uncertainties. The unknown states are accurately estimated by EHGO which enables the controller to exhibit improved stabilization performance.

A new mathematical model of the 5-DOF barge-type OFWT system based on TORA is the major contribution of this research paper. Furthermore, it provides a new adaptive anti-vibration control scheme by incorporating the EHGO for the proposed model.