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The purpose of this paper is to examine the threshold effect of group size on customer's complaining intention under group service failures.

Based on two main laboratory experiments, through two 10×2 scenario simulation experiments, the authors examine the role of group size in customer's complaining intention.

Results show that: (1) the relationship between group size and customer's complaining intention follows an inverted “U” type trend; (2) evaluation apprehension mediates the relationship between group size and customer's complaining intention; (3) relational distance can change threshold values and (4) relational distance moderates the relationship between group size and customer's complaining intention.

Managers should judge the threshold of group size through experience so as to have a preliminary understanding of customer evaluation concerns and complaint intention. In the face of service failure groups smaller than the threshold range, managers should divided the group into several small groups. For service failure groups larger than the threshold range, the opinion leaders in the group should be given more attention, so as to control the whole group.

This paper is helpful to deeply understand the key role of group size in the process of customer complaints, and also provides decision-making basis for service enterprises to deal with group customer complaints.

There has been little research about the threshold effect of group size on customer's complaining intention. The previous studies on customer's complaining intention focus on its influences on group size, and draw a single common conclusion that the customer's intention to complain will increase with the growing number of groups increases. However, few studies are explored on the threshold of group size. Therefore, this paper will focus on the threshold effect of group size on customer's complaining intention to fill the gap.

This paper aims to explore the effects of mineral diesel fuel carbon soot (MCS) and biodiesel carbon soot (BCS) on the lubrication of polyalphaolefin (PAO) and diesel fuels.

Two styles of carbon soot were prepared from the natural combustion of mineral diesel fuel oil (MDO) and biodiesel oil (BDO). Tribological tests were conducted on a high-frequency reciprocating rig. Friction surfaces were characterized using three-dimensional laser scanning confocal microscopy and Raman spectroscopy.

The addition of MCS and BCS to PAO could reduce friction in most cases. MCS had a negligible effect on the wear for contents not exceeding 1.0 per cent. By contrast, BCS exhibited a considerable negative influence on the wear resistance even at low contents. For diesel fuels, MCS reduced both friction and wear, whereas BCS substantially deteriorated the lubrication of BDO. MCS formed a Fe₃O₄/C composite lubricating film on the friction surface. BCS also entered the contact region, but it did not form an effective Fe₃O₄/C composite lubricating film.

This work compared MDO and BDO from a different perspective, i.e. the effects of their combustion carbon soot on the lubrication of lubricating oil and fuel oil. The significant negative effect of BCS on the lubrication of lubricating oil and BDO is a problem that could occur in the industrial application of BDO.

Brand crowdfunding, launched through brands’ social media platforms, can provide a myriad of crowdfunding and branding benefits, such as strengthening brands’ social networks, validating product launches, generating mass exposure and enabling cocreation. Gamification positions brand crowdfunding as an exciting and joyful activity that more deeply engages prosumers. Anchored on resource-based theory, theory of planned behavior and service-dominant logic, this paper aims to develop a brand crowdfunding framework for established brands with insights from two emerging markets: China and India.

A deductive cross-sectional design is used to gather data from an established brand’s (e.g. Xiaomi) social media followers in China (n = 826) and India (n = 358), which is analyzed through PLSc-SEM.

The results reveal that social media brand engagement is an antecedent of brand crowdfunding participation, brand crowdfunding intention is a predictor of brand loyalty and gamification is a significant moderator in technology-oriented societies.

The paper develops a brand crowdfunding framework that provides insights on how established brands can leverage crowdfunding to enhance their new product development process. The results contribute to the social media brand engagement, crowdfunding, gamification and emerging markets literature.

Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.

In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.

Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.

These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.

Grounding the research in the stimulus-organism-resource (S-O-R) framework, this study aims to address the research gap of explaining and predicting the relationship between price discounts, interactivity and professionalism on college students’ purchasing intention in live-streaming shopping. It also attempts to understand if trust plays the role of mediator in the effect of these relationships.

This study collected data using a questionnaire protocol adapted and refined from the original scales in existing studies. The partial least squares structural equation modeling was used to analyze data collected from 258 college students in China. Other than assessing the path model’s explanatory power, this study examined the model’s predictive power toward predicting new cases using PLS predict.

Results indicated that all three predictors have a positive significant relationship with trust, while only price discounts demonstrate a significant relationship with purchase intention. Simultaneously, the mediation results provide support to the S-O-R framework demonstrating that external factors (professionalism, interactivity and price discounts) can arouse organism (trust), which in return, generate a behavioral outcome (purchase intention).

This study is the first few studies that focus on college students’ behavioral responses in an online shopping environment. At the same time, this is the first study supplement the explanatory perspective with a predictive focus, which is of particular importance in making sound recommendations on managerial decision-making.

Prediction models for the unsaturated permeability proposed in the literature are numerous. However, a model may give a good result for a sample of a given soil when it may give a bad result for another sample belonging to the same type of soil. This showed that the choice of a model to complete the permeability curve in the unsaturated state is complex. To facilitate such studies, this paper aims to present a help system capable of defining the mathematical model to the user that best represents the permeability of the soil.

The authors have detailed the difficulties in determining the correct value of kuns from a thorough bibliographic study. To develop this idea, the authors took real examples, to which they applied mathematical models and then compared their results with those of the bibliographic study. Knowledge structuring in the form of classes, rules and functions. Implementation of the data in generator of help system Kappa-pc. validation of results.

An aid tool was developed for the evaluation of unsaturated soils permeability using Brooks and Corey (1964) and Leong and Rahardjo (1997) models, which are known for their effectiveness and ease of application. This system will also evaluate these two methods using estimation models of saturated permeability [Dane and Pocket (1992), Terzaghi (1981) and laboratory data]. This system allows the evaluation of unsaturated permeability by the aforementioned two models, makes comparison between these two models, classifies them and proposes the model presenting the best result.

This aid system is able to compare results of different models of prediction of the hydraulic conductivity of unsaturated soils according to several criteria (suction, degree of saturation, plasticity index, models of estimation of the permeability to the soil, saturated state, particle size, etc.). It can also deduce the model that best adapts to a given soil. This aid system will be of great use for geotechnical engineers and researchers in the field.

The purpose of this paper is to introduce an expressive query language, called relational XML query language (RXQL), capable of dealing with heterogeneous Extensible Markup Language (XML) documents in data‐centric applications. In RXQL, data harmonization (i.e. the removal of heterogeneous factors from XML data) is integrated with typical data‐centric features (e.g. grouping, ordering, and aggregation).

RXQL is based on the XML relation representation, developed in the authors' previous work. This is a novel approach to unambiguously represent semistructured data relationally, which makes it possible in RXQL to manipulate XML data in a tuple‐oriented way, while XML data are typically manipulated in a path‐oriented way.

The user is able to describe the result of an RXQL query straightforwardly based on non‐XML syntax. The analysis of this description, through the mechanism developed in this paper, affords the automatic construction of the query result. This feature increases significantly the declarativeness of RXQL compared to the path‐oriented XML languages where the user needs to control the construction of the result extensively.

The authors' formal specification of the construction of the query result can be considered as an abstract implementation of RXQL.

RXQL is a declarative query language capable of integrating data harmonization seamlessly with other data‐centric features in the manipulation of heterogeneous XML data. So far, these kinds of XML query languages have been missing. Obviously, the expressive power of RXQL can be achieved by computationally complete XML languages, such as XQuery. However, these are not actual query languages, and the query formulation in them usually presupposes programming skills that are beyond the ordinary end‐user.

Reasonable risk sharing is the key to the smooth implementation of infrastructure public-private partnership (PPP) projects and the optimization of benefit distribution among the participants. This study aims to explore the risk redistribution ratio between the government and the private sector under different degree of fairness concern.

Renegotiation is a mechanism to provide flexibility and make up for incompleteness of PPP contracts. However, the threshold value of risk redistribution ratio and negotiation cost are not explicitly considered in previous studies. In addition, these studies do not consider the influence of the fairness concern psychology on the negotiation process. To address these gaps, based on risk-income equilibrium analysis, this paper established the bargaining optimization model of PPP projects renegotiation considering the fairness concerns of the negotiating parties. Furthermore, this study analyzed the influence of fairness concern degree on negotiation thresholds, negotiation results, and negotiation incomes under three scenarios.

The results showed that excessive focus on the fairness of incomes may exclude the risk redistribution ratio that is most beneficial to project incomes from the negotiation threshold. Moreover, the increase in the fairness concerns of negotiating parties can reduce the negotiation success period, but the net income may not necessarily be improved.

The main contribution of this paper is to propose a new risk renegotiation methodology based on the risk-income equilibrium analysis, which is helpful to develop risk management strategies in the construction field. The research results can provide government with reference about renegotiation in decision making and provide theoretical support for the practice of PPP renegotiation.

This study aimed to review various existing methods for improving the quality of recycled concrete aggregates (RCAs) as a possible substitution for natural aggregates (NAs) in concrete. It is vital as the old paste attached to the RCA weakens its structure. It is due to the porous structure of the RCA with cracks, weakening the interfacial transition zone (ITZ) between the RCA and binding material, negatively impacting the concrete's properties. To this end, various methods for reinforcement of the RCA, cleaning the RCA's old paste and enhancing the quality of the RCA-based concrete without RCA modification are studied in terms of environmental effects, cost and technical matters. Furthermore, this research sought to identify gaps in knowledge and future research directions.

The review of the relevant journal papers revealed that various methods exist for improving the properties of RCAs and RCA-based concrete. A decision matrix was developed and implemented for ranking these techniques based on environmental, economic and technical criteria.

The identified methods for reinforcement of the RCA include accelerated carbonation, bio deposition, soaking in polymer emulsions, soaking in waterproofing admixture, soaking in sodium silicate, soaking in nanoparticles and coating with geopolymer slurry. Moreover, cleaning the RCA's old paste is possible using acid, water, heating, thermal and mechanical treatment, thermo-mechanical and electro-dynamic treatment. Added to these treatment techniques, using RCA in saturated surface dry (SSD) mixing approaches and adding fibres or pozzolana enhance the quality of the RCA-based concrete without RCA modification. The study ranked these techniques based on environmental, economic and technical criteria. Ultimately, adding fibres, pozzolana and coating RCA with geopolymer slurry were introduced as the best techniques based on the nominated criteria.

The study supported the need for better knowledge regarding the existing treatment techniques for RCA improvement. The outcomes of this research offer an understanding of each RCA enrichment technique's importance in environmental, economic and technical criteria.

The practicality of the RCA treatment techniques is based on economic, environmental and technical specifications for rating the existing treatment techniques.

The soil water retention curve (SWRC) and unsaturated hydraulic conductivity (UHC) are crucial indices to assess hydraulic properties of porous media that primarily depend on the particle and pore size distributions. This study aims to present a method based on the discrete element model (DEM) and the typical Arya and Paris model (AP model) to numerically predict SWRC and UHC.

First, the DEM (PFC^3D software) is used to construct the pore and particle size distributions in porous media. The number of particles is calculated according to the AP model, which can be applied to evaluate the relationship between the suction head and the moisture of porous media. Subsequently, combining critical path analysis (CPA) and fractal theory, the air entry value is applied to calculate the critical pore radius (CPR) and the critical volume fraction (CVF) for evaluating the unsaturated hydraulic conductivity.

This method is validated against the experimental results of 11 soils from the clay loam to the sand, and then the scaling parameter in the AP model and critical volume fraction value for many types of soils are presented for reference; subsequently, the gradation effect on hydraulic property of soils is analyzed. Furthermore, the calculation for unbound graded aggregate (UGA) material as a special case and a theoretical extension are provided.

The presented study provides an important insight into the relationship between the heterogeneous particle and hydraulic properties by the DEM and sheds light on the directions for future study of a method to investigate the hydraulic properties of porous media.