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Property developers identify the vital role of social media brand engagement (SMBE) in sustaining their businesses in competitive marketplaces, but it remains underexplored. This paper examines how SMBE mediates the effects of firm-generated content (FGC) and user-generated content (UGC) on brand trust, considering the moderating effects of social media influencer endorsement (SMIE) and self-image congruence (SIC) for luxury residential properties (LRPs).

Around 516 high-income homebuyers in Vietnam who shared information about LRP on social media were targeted to test the research model empirically. The primary data collected from paper-based surveys were analysed using SPSS 26 and AMOS 24.

Results indicate that FGC and UGC positively impact SMBE and consequently significantly affect brand trust. Further, results confirm the moderating roles of SMIE and SIC in the effects of FGC and UGC on SMBE.

Data and sample size were limited to meet the generalisation from different nations and cross cultures.

The authors' findings suggest that marketers should apply the authors' integrated SMBE model to strengthen brand–consumer interactions and increase their sales revenue.

This study is the first in its application of the uses and gratifications theory and self-congruence theory to investigate how SMBE mediates the relationship between FGC and brand trust as well as between UGC and brand trust. Noticeably, this study makes a novel contribution as the first to quantitatively explore the moderating effects of SMIE and SIC in the authors' research model.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market. The purpose of this paper is to examine the evolving efficiency and dual long memory in the GEM. This paper also explores the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

State-space GARCH-M model, Kalman filter estimation, factor-adjustment techniques and fractionally integrated models: ARFIMA–FIGARCH, ARFIMA–FIAPARCH and ARFIMA–HYGARCH are adopted for the empirical analysis.

The results indicate that the GEM is still weak-form inefficient but shows a tendency towards efficiency over time except during the global financial crisis. There also exists a stationary long-memory property in the market return and volatility; however, these long-memory properties weaken in magnitude and/or statistical significance when the joint impacts of the three aforementioned factors were taken into account.

A forecasts of the hedging model that capture dual long memory could provide investors further insights into risk management of investments in the GEM.

The findings of this study are relevant to market authorities in improving the GEM market efficiency and investors in modelling hedging strategies for the GEM.

This study is the first to investigate the evolving efficiency and dual long memory in an SME stock market, and the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

The consolidation behavior of prefabricated vertical drain (PVD)-installed soft deposits mainly depends on the PVD performance. The purpose of this study is to propose a numerical solution for the consolidation of PVD-installed soft soil using the large-strain theory, in which the reduction of discharge capacity of PVD according to depth and time is simultaneously considered.

The proposed solution also takes into account the general constitute relationship of soft soil. Subsequently, the proposed solution is applied to analyze and compare with the monitoring data of two cases, one is the experimental test and another is the test embankment in Saga airport.

The results show that the reduction of PVD discharge capacity according to depth and time increased the duration required to achieve a certain degree of consolidation. The consolidation rate is more sensitive to the reduction of PVD discharge capacity according to time than that according to the depth. The effects of the reduction of PVD discharge capacity according to depth are more evident when PVD discharge capacity decreases. The predicted results using the proposed numerical solution were validated well with the monitoring data for both cases in verification.

In this study, the variation of PVD discharge capacity is only considered in one-dimensional consolidation. However, it is challenging to implement a general expression for discharge capacity variation according to time in the two-dimensional numerical solution (two-dimensional plane strain model). This is the motivation for further study.

A geotechnical engineer could use the proposed numerical solution to predict the consolidation behavior of the drainage-improved soft deposit considering the PVD discharge capacity variation.

The large-strain consolidation of PVD-installed soft deposits could be predicted well by using the proposed numerical solution considering the PVD discharge capacity variations according to depth and time.

The net-present-value (NPV) method is well-known for its drawbacks. To overcome some of these NPV weaknesses this paper aims to provide a methodology to determine an optimal concession period that treats risk and time separately. The purpose of this paper is to apply the notion of risk-adjusted decoupled net present value (risk-adjusted DNPV) to determine a conception period taken into consideration synthetic insurance premiums as compensation for risks.

This paper conducts theoretical and empirical analysis and provides an integrated model for deriving concession periods of any PPP projects. The model is able to capture several contractual issues such risks costing and other contractual scenarios. Methodologically, the paper addressees both the issues of risk-based cost–benefit analysis and cash flow analysis bearing an emphasis of risk-adjusted DNPV to compute an optimum concession period.

The results show that using DNPV will produce a shorter concession period comparatively to NPV. The consequence of this is that the public sector will gain financially from an earlier transfer of the concession.

This paper contributes to the PPP literature by combing DNPV and risk to determine the PPP concession period for the mutual benefits both the private and public sectors. The decoupling of risk from traditional NPV computation will allow for risk pricing and tradability through insurance and allocation.

The attempt to decouple time and risk in the computation of NPV is the added value to the body of knowledge.

The paper aims to assess the impact of weather-induced shocks on household food consumption in the rural Vietnamese Mekong Delta (VMD) through the case of Long An province and evaluate the effectiveness of widely used coping strategies in mitigating weather-related shock impacts.

The system generalized method of moments (GMM) estimation method is applied to explore information on shock incidence, recovery, and time occurrences. The paper uses a sample of 272 repeated farming households from 5-wave survey data from 2008 to 2016, resulting in 1,360 observations.

The paper confirms the robust negative effect of a natural shock on food consumption. Additionally, using savings proves to be the most potent measure to smooth food consumption. Other favorable coping strategies are “getting assistance from relatives, friends” or “getting assistance from the Government, and non-government organizations (NGOs).” The mitigating effects are also traced in the current analysis.

Using caution when generalizing the results from Long An to the whole VMD is reasonable. The rather limited observations of coping strategies do not allow the authors to analyze any specific strategy.

The proposed approach employs the GMM technique and controls for endogenous coping strategies and thus provides accurate estimates of the effects of weather-related shocks and the mitigation effectiveness in the rural VMD.

This paper aims to provide discussions of a numerical method for bubbly flows and the interaction between a vortex ring and a bubble plume.

Small bubbles are released into quiescent water from a cylinder tip. They rise under the buoyant force, forming a plume. A vortex ring is launched vertically upward into the bubble plume. The interactions between the vortex ring and the bubble plume are numerically simulated using a semi-Lagrangian–Lagrangian approach composed of a vortex-in-cell method for the fluid phase and a Lagrangian description of the gas phase.

A vortex ring can transport the bubbles surrounding it over a distance significantly depending on the correlative initial position between the bubbles and the core center. The motion of some bubbles is nearly periodic and gradually extinguishes with time. These bubble trajectories are similar to two-dimensional-helix shapes. The vortex is fragmented into multiple regions with high values of Q, the second invariant of velocity gradient tensor, settling at these regional centers. The entrained bubbles excite a growth rate of the vortex ring's azimuthal instability with a formation of the second- and third-harmonic oscillations of modes of 16 and 24, respectively.

A semi-Lagrangian–Lagrangian approach is applied to simulate the interactions between a vortex ring and a bubble plume. The simulations provide the detail features of the interactions.

This paper aims to analyze the impacts of institutional quality on trade flows of NAFTA with a panel data set of 105 countries spanning the period 2006–2017.

We applied the system generalized method of moment (GMM) estimator to investigate the impacts.

The results show that institutional quality is a positive and significant determinant of international trade flows of the NAFTA bloc and its trading partners. Our results also indicate that the impact of institutional quality depends on the level of economic development of NAFTA's trading partners. Specifically, the trade elasticity of institutional quality is the highest for NAFTA’s trade with middle-income countries and the lowest for NAFTA's trade with low-income countries. In the long run, the trade elasticity of institutional quality increased significantly, with the highest increase in the case of NAFTA's trade with medium-income countries and the lowest increase in the case of NAFTA's trade with low-income countries.

This study contributes to the existing literature in three different ways. First, we examine the differential impact of institutions on NAFTA's trade according to the level of economic development of NAFTA's trading partners. Second, we compare the differential trade elasticity of institutional quality in the long run. Finally, we support our findings through an improved research methodology by using the system GMM estimation. This method allows us to overcome the potential sample bias, omitted variable problems and endogeneity of explanatory variables.

Large collections of patent documents disclosing novel, non-obvious technologies are publicly available and beneficial to academia and industries. To maximally exploit its potential, searching these patent documents has increasingly become an important topic. Although much research has processed a large size of collections, a few studies have attempted to integrate both patent classifications and specifications for analyzing user queries. Consequently, the queries are often insufficiently analyzed for improving the accuracy of search results. This paper aims to address such limitation by exploiting semantic relationships between patent contents and their classification.

The contributions are fourfold. First, the authors enhance similarity measurement between two short sentences and make it 20 per cent more accurate. Second, the Graph-embedded Tree ontology is enriched by integrating both patent documents and classification scheme. Third, the ontology does not rely on rule-based method or text matching; instead, an heuristic meaning comparison to extract semantic relationships between concepts is applied. Finally, the patent search approach uses the ontology effectively with the results sorted based on their most common order.

The experiment on searching for 600 patent documents in the field of Logistics brings better 15 per cent in terms of F-Measure when compared with traditional approaches.

The research, however, still requires improvement in which the terms and phrases extracted by Noun and Noun phrases making less sense in some aspect and thus might not result in high accuracy. The large collection of extracted relationships could be further optimized for its conciseness. In addition, parallel processing such as Map-Reduce could be further used to improve the search processing performance.

The experimental results could be used for scientists and technologists to search for novel, non-obvious technologies in the patents.

High quality of patent search results will reduce the patent infringement.

The proposed ontology is semantically enriched by integrating both patent documents and their classification. This ontology facilitates the analysis of the user queries for enhancing the accuracy of the patent search results.