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The purpose of this paper is to explore whether the databases from a certain library are Pareto-compliant or not? If so, to what extent is the Pareto principle performance evident among these databases? The other purpose is to determine the differences in Pareto principle performance according to time change and database type.

Data on full-text downloads from six e-resources – Elsevier ScienceDirect (SD), Wiley Blackwell, Springer Journal, EBSCO Business Source Premier (BSP), American Chemical Society and American Institute of Physics (AIP) – for the period 2007-2013 were analysed; 42 samples were collected from these databases. The proportion of frequently downloaded journals from databases was selected as an indicator to determine differences in Pareto principle performance according to time change. The difference between the proportion of frequently downloaded journals and the classic proportion of 20 per cent was used as indicator to determine difference in Pareto principle performance related to database type.

There are 33 samples (78.57 per cent) which exhibited the Pareto principle. Four databases – Elsevier SD, Wiley Blackwell, EBSCO BSP and AIP – constantly exhibited the Pareto principle. The differences were not significant according to time change. The two multi-discipline databases – Elsevier SD and Wiley Blackwell – fluctuated more moderately than the two single-discipline databases – EBSCO BSP and AIP. Multi-discipline and single-discipline databases showed some differences in Pareto principle performance; however, these differences were not remarkable.

The Pareto principle confirmed that there were frequent and infrequent downloads of e-journals from e-journal databases. It was of great importance to analyse these to improve digital resources acquisition and user service.

The purpose of this paper is to address the urgent need for transformation and upgrading in the construction industry amid the accelerating industrialization process. The focus is on understanding how value-added for construction enterprises can be achieved through servitization.

Grounded in the perspective of added value of construction enterprises, this paper uses a multicase analysis method, selecting four internationally renowned construction enterprises as the research subjects. The analysis investigates how these case study enterprises transition toward servitization and explores the trends in servitization in construction.

The research results indicate that servitization manifests in two aspects: contractor transition to servitization, and the shift of the construction industry toward integrated delivery. Furthermore, servitization in construction can achieve value-adding through three pathways: increasing product value, creating market demand and providing customized services.

This study contributes by providing insights into the manifestations of servitization and pathways for value-added. It provides a reference for the overall direction and basic strategy of servitization in construction.

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.

Trust has emerged as a crucial research topic in the sharing economy. However, scholarship on trust in sharing accommodation remains limited. By using stakeholder theory, this study aims to provide a systematic framework for integrating trust among multiple stakeholders and identify potential knowledge gaps and future research directions for trust in sharing accommodation.

The authors select papers using a combination of multiple keywords from EBSCOhost and Web of Science. The analysis includes 172 journal papers published between 2011 and 2021. The authors conduct a systematic review through thematic content analysis, and each paper is analyzed using manual coding.

The analysis shows that key stakeholders for trust building in sharing accommodation include consumers, hosts, platforms, residents and governments, with most studies focusing on the consumer perspective. The study integrates various trust antecedents and outcomes from the above multistakeholder. Second, this study summarizes the most commonly used theories, and more diversified theories could be applied to future research. Third, this study finds that most studies use quantitative methods, and researchers should introduce more integrated methodologies such as machine learning on a large scale. Furthermore, the current research disciplinary paradigm should be extended to multidisciplinary and interdisciplinary approaches to promote innovation in trust research. Finally, the COVID-19 pandemic has brought both challenges and opportunities to industry as well as researchers, and more institutional rather than commercial perspectives need to be addressed.

The study contributes to the trust and the sharing economy literature by providing a systematic framework for integrating trust from multistakeholder perspectives. The study also points out several future research directions by combining micro and macro multistakeholder perspectives, identifying more diversified theories and methodologies and specifying multidisciplinary and interdisciplinary approaches.

The study advances knowledge by providing a systematic framework for integrating trust among multiple stakeholders and proposing future research directions for trust in sharing accommodation.

Safety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.

Based on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.

The research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.

Considering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.

This research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.

This research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

The purpose of this work is to construct a grey entropy comprehensive evaluation model to measure the regional green innovation vitality (GIV) of 31 provinces in China.

The traditional grey relational proximity and grey relational similarity degree are integrated into the novel comprehensive grey evaluation framework. The evaluation system of regional green innovation vitality is constructed from three dimensions: economic development vitality, innovative transformation power and environmental protection efficacy. The weights of each indicator are obtained by the entropy weight method. The GIV of 31 provinces in China is measured based on provincial panel data from 2016 to 2020. The ward clustering and K-nearest-neighbor (KNN) algorithms are utilized to explore the regional green innovation discrepancies and promotion paths.

The novel grey evaluation method exhibits stronger ability to capture intrinsic patterns compared with two separate traditional grey relational models. Green innovation vitality shows obvious regional discrepancies. The Matthew effect of China's regional GIV is obvious, showing a basic trend of strong in the eastern but weak in the western areas. The comprehensive innovation vitality of economically developed provinces exhibits steady increasing trend year by year, while the innovation vitality of less developed regions shows an overall steady state of no fluctuation.

The grey entropy comprehensive relational model in this study is applied for the measurement and evaluation of regional GIV, which improves the one-sidedness of traditional grey relational analysis on the proximity or similarity among sequences. In addition, a three-dimensional evaluation system of regional GIV is constructed, which provides the practical guidance for the research of regional development strategic planning as well as promotion paths.

A comprehensive grey entropy relational model based on traditional grey incidence analysis (GIA) in terms of proximity and similarity is proposed. The three-dimensional evaluation system of China's regional GIV is constructed, which provides a new research perspective for regional innovation evaluation and expands the application scope of grey system theory.

This study aims to probe the applicability of 2-mercaptobenzothiazole (MBT) functionalized ionic liquids (ILs) as additives in lithium complex grease (LCG) by researching the corrosion inhibiting, rheological and tribological performances.

Electrochemical tests such as electrochemical impedance spectroscopy and potentiodynamic polarization curves were used on Gamry electrochemical workstation to research the corrosion inhibition properties of ILs in 1.0 M HCl corrosive solution. The rheological properties of different grease samples were tested on a rheometer. The tribological properties were investigated on SRV-V oscillating reciprocating friction and wear tester. Scanning electron microscope, X-ray spectrometer and X-ray photoelectron spectrometer were used to characterize the lubricating mechanism.

The 2-MBT functionalized ILs have excellent corrosion inhibition properties. When used as additives in LCG, they both exhibited enhancing effects on thermostability, colloid stability and structural recoverability, and furthermore, outstanding friction-reducing and antiwear properties were also obtained. Surface analysis indicated that the superior lubricating performances of 2-MBT functionalized ILs were mainly ascribed to the formation of tribochemical products on wear tracks, including organic compounds with C–O bond, Fe₂O₃ and FeS₂.

The 2-MBT-based ILs synthesized in this study were multifunctional additives with excellent corrosion inhibiting and tribological properties, which would have a very broad application prospect in lubricating grease industry.

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.

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.