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Unbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.

The identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.

The proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.

The data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

Trust is the glue that holds cooperative relationships together and often exists in an asymmetric manner. The purpose of this study is to explore how to mitigate the issue of losses or increased transaction costs caused by opportunistic behavior in a soft environment where trust asymmetry is quite common and difficult to avoid.

This study focuses on examining asymmetric trust between the government and the private sector in public-private partnership (PPP) projects. Drawing upon both project realities and relevant literature, the primary conditional variables influencing asymmetric trust are identified. These variables encompass power perception asymmetry, information asymmetry, interaction behavior, risk perception differences and government-side control. Subsequently, through the use of a survey questionnaire, binary-matched data from both the government and the private sector are collected. The study employs fuzzy-set qualitative comparative analysis (fsQCA) to conduct a configurational analysis, aiming to investigate the causal pathways that trigger asymmetric trust.

No single conditional variable is a necessary condition for the emergence of trust asymmetry. The pathways leading to a high degree of trust asymmetry can be categorized into two types: those dominated by power perception and those involving a combination of multiple factors. Differences in power perception play a crucial role in the occurrence of high trust asymmetry, yet the influence of other conditional variables in triggering trust asymmetry should not be overlooked.

The findings can contribute to advancing the study of trust relationships in the field of Chinese PPP projects. Furthermore, they hold practical value in facilitating the enhancement of trust relationships between the government and the private sector.

The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.

In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.

The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.

The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.

The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.

To achieve sustainability for a construction project requires the achievement of economic, environmental and social sustainability at the same time. The economic sustainability of a project should be built into the stipulated cost. The unbalanced bidding always contribute cost overrun for a construction project. The purpose of this paper is to develop a method for identifying unbalanced bidding.

The problem of identifying unbalanced bidding is a comprehensive evaluation problem. All line items and bidders in bills of quantities are evaluation factors and evaluation objects, respectively, and the engineer’s estimated prices are considered as the evaluation benchmarks. The weights of these factors are determined through integrating the entropy weight method and the analytic hierarchy model, which consider subjective and objective factors in the weighting process.

The proposed model can be used to quantitatively evaluate unbalanced bids. The identification process can be analyzed within a short period, specifically with the aid of Microsoft Excel, reducing delays in awarding contracts. The results show that the model will support owners as they efficiently and effectively identify unbalanced bids in the bid evaluation stage to mitigate the negative consequences of unbalanced bidding.

A case study is given to verify the feasibility and practicability of the proposed method, which not only assists owners in efficiently and effectively identifying unbalanced bidding, but also promotes the economic sustainability of construction projects.

The fuzzy comprehensive evaluation method is used to detect unbalanced bidding, allowing owners to be objective as they identify and reduce unbalanced bidding at the procurement stage.

This paper aims to propose a new model and examine how night market entrepreneurs have achieved a competitive advantage in strongly competitive markets.

Two statistics methods, multiple regression analysis and structural equation models (SEM), were used to test the hypotheses for a sample of 346 vendor cases.

The results indicate that competitive aggressiveness and being proactive are positively related to risk-taking among night market vendors, which, in turn, has a positive effect on innovativeness. Further, the findings also indicate that risk-taking positively influences innovativeness and, in a mediating role, also affects competitive advantages through innovativeness.

Results of this study suggest that if night market entrepreneurs demonstrate innovativeness, positively develop new products and new services and attract customers to buy them, then they will have unique and attractiveness in the night markets, thus giving themselves relative competitive advantage.

This research is the first comprehensive examination of entrepreneurship among night market entrepreneurs to study the competitive advantages of different facets, which may provide a benchmark for future studies.

As the market competition becomes increasingly intensive and the profit from traditional voice services margins gradually decline, 3G telecom operators must provide various value‐added services to enhance the ARPU (average revenue per user). The purpose of this paper is to recognize the factors infecting the adoption of 3G value‐added services.

The TAM (technology acceptance model) was used as the foundation to further understand consumer's behavioral intention to use 3G value‐added services. Structural equation modelling (SEM) was used to develop a conceptual model of customer adoption and nine important factors were proposed. The authors conducted a questionnaire investigation, using a large sample, in the Chinese 3G value‐added service market. SPSS and AMOS were applied to analyze the survey data.

The empirical findings are: security and social influence are two of the most important factors in 3G market; 3G value‐added services must be perceived as enjoyment and useful; using context should be friendly and compatible; and in a whole view, the influence from gender, ease of use and need for unique to adoption intention is not significant, but to separate as two models, the difference is huge – the female group considers more about price and usefulness, while the male group thinks about enjoyment and compatibility.

The sample of this study is limited at the range of empirical data; the development of 3G technology has not yet been perfected in China and this study fails to include all of the 3G value‐added services, some of which are still in the exploratory phase of development. At the same time, the cities in this study cannot be said to represent the present stage of the whole of China.

The paper develops a conceptual structural equation model on the area of 3G value‐added services in China. The findings in the paper would help 3G providers to improve their services.

In this study the aim was to investigate under-deposit corrosion (UDC) behavior and the action effects of amino trimethylene phosphonic acid (ATMP) in the oxygen-contained solution.

Electrochemical methods and wire beam electrode techniques were used for the study of ATMP action effect for X65 steel under silica sand and CaCO₃ particle deposit. Electronic coupon technique was used for the study of galvanic effect caused by the deposits and the action effect of ATMP.

ATMP would cause localized corrosion for the silica sand-covered steel. However, it could inhibit the localized corrosion of the steel beneath CaCO₃ particle deposit. Galvanic effect test showed that the galvanic effect caused by the deposits was an important factor for the acceleration of UDC. ATMP had an obvious promotion effect for the galvanic current between bare coupon and silica sand covered coupon and different degrees of localized corrosion were observed beneath both deposits.

The authors believe that the paper may be of particular interest to the readers of the journal as the measurement methods for the UDC of X65 pipeline steel. The experiment they did in the laboratory found that the inhibitor ATMP has a good inhibition effect for bare steel, but it would accelerate the UDC. Different kinds of deposits would have different influences for the UDC behavior with inhibitor added.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The purpose of this paper is to describe a processing system for 3D dress geometry modelling and texture mapping.

Since the range image and its corresponding texture from one direction could be acquired by areal 3D scanner simultaneously, the texture can be integrated into the range image exactly. In the geometry modelling stage, the graph‐based algorithm is used for multi‐view registration. In order to enhance its robustness, a method for judging bad pairwise registration is proposed based on the computation of two views' overlapping percentage. In order to enrich its completeness, combined the graph analysis with the metaview method is used to deal with the measurement data for local details. In the texture mapping stage, based on grid search structure, the method of solving the Poisson equation for the colour field that best fits the colour gradients can produce a seamlessly textured surface quickly.

Results show that the processing system can provide a 3D textured dress geometry model with no seams and low distortion successfully.

The processing system can provide an accurate 3D dress geometry model, which can be used to modify the further design or virtual try.

A 3D dress geometry model with no seams and low distortion provides the fashion designer with not only the visual effects, but also accurate data used for design modification.

Over the past several decades, there has been an increasing trend towards inter-city cooperation, which is an efficient policy option to deal with the challenges from globalization, regionalization and the externalities resulting from urban entrepreneurialism. Specific to China, the city governments, which mainly refer to prefecture-level and county-level governments, have also made many attempts to cooperate with respect to their local economic development and public affairs. Nevertheless, the results of these initiations to cooperate vary to a great extent. Based on a review of regional pollution governance in the Xiaoqing River area, tourism cooperation initiatives at Weishan Lake and transport integration between Jinan and Laiwu. The findings demonstrate that China's idiosyncratic institutional background has a significant impact on the shaping of inter-city cooperation. For the most part, leading small groups (LSGs) and their leadership property tend to determine the effectiveness of inter-city cooperation.

To examine the effect of the LSGs, we categorize them into three types, groups with strong leadership, weak leadership and self-forming leadership. Through reviewing regional pollution governance in the Xiaoqing River area, tourism cooperation initiatives at Weishan Lake and transport integration between Jinan and Laiwu, we try to probe the role of leading groups in the settlement of cross-administrative border issues.

Based on these three cases, the conclusion can be drawn that the leadership type of the LSG can exert an important influence on the efficiency of inter-city cooperation. If there is a leader with a higher administrative rank or authority, the cooperation can be quite efficient. Otherwise, the cooperative ending might be very negative. In terms of the operation principle, we can infer that even though the cities are always self-development oriented, the leader with higher authority or a strong coordinating capacity can convince and persuade the city leaders to overcome their self-centered behavior template and boost the cooperation to March on smoothly. Also, it means that the LSG is constrained by its personalistic characteristic. Key command derives from the person who chairs the LSG other than specific rules and norms. If the lead of the LSG leaves his position, the cooperation might just become paralyzed. From this point of view, the lack of legal basis remains to be the LSGs' significant deficiency and the future reform should attach more importance to the legalization of the LSGs so the operation of LSGs can be more standard and stable.

Many scholars have proposed their own theoretical models to explain the reason some cities successfully and effectively form cooperative relations, while the other cities do not. However, their models do not consider the idiosyncratic context of China or, how and to which extent LSGs can promote cooperation. Therefore, this paper seeks to probe which path in the context of China cities usually follows in the formation of joint efforts, and what role LSGs play in enabling cities to cooperate.