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For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

The restoration and strengthening of QT600 is an industry bottleneck challenge. The Co-12 cladding layer has great wear and corrosion resistance. The purpose of this paper is to quantitatively reveal the transient evolution law of the corrosion process of Co-12 cladding layer on QT600 surface.

In this paper, a three-dimensional numerical model of the corrosion process of Co-12 cladding layer by QT600 laser cladding is established. The interaction between pitting pits and corrosion medium is considered to reveal the transient evolution of ion concentration, electrode potential, pH and corrosion rate at different locations.

The calculation shows that the ion concentration in pitting pit changes Cl⁻>Co²⁺>Na⁺, pH value decreases from top to bottom and corrosion rate at bottom is greater than that at top. The electrochemical corrosion test of Co-12 cladding layer was carried out. It is shown that the current density of QT600 increases by an order of magnitude compared to the Co-12 cladding layer, and the corrosion rate is 4.862 times higher than that of the cladding layer.

The results show that Co-12 cladding layer has great corrosion resistance, which provides an effective way for QT600 protection.

Notwithstanding the Geographical Information System (GIS) being a fast-emerging green area of a digital revolution, the available studies focus on different subject areas of application in the construction industry, with no study that clarifies its knowledge strands. Hence, this systematic review analyses GIS core area of application, its system integration patterns, challenges and future directions in the construction industry.

A systematic review approach was employed, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. A total of 60 articles published between 2011 and 2022 were identified, thoroughly reviewed and analysed using thematic analysis.

The analysis revealed spatial planning and design, construction-task tracking, defect detection and safety monitoring as its four main application-based areas. The findings showed that the adoption of GIS technology is rapidly expanding and being utilised more in building projects to visual-track construction activities. The review discovered an integrated pattern involving data flow from a device and window-form application to GIS, the pathways to data exchange between platforms to platforms, where ArcGIS is the most used software. Furthermore, the study highlighted the lack of interoperability between heterogeneous systems as the crux impediment to adopting GIS in the built environment.

The research provides a deep insight into possible areas where GIS is adopted in the construction industry, identifying areas of extensive and limited application coverage over a decade. Besides, it demystifies possible pathways for future integration opportunities of GIS with other emerging technologies within the construction industry.

Incipient detection of pavement deterioration (such as crack identification) is critical to optimizing road maintenance because it enables preventative steps to be implemented to mitigate damage and possible failure. Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing. Therefore, there is a need to develop automated tools to detect and classify cracks.

The literature review is employed to evaluate existing attempts to use Hough transform algorithm and highlight issues that should be improved. Then, developing a simple low-cost crack detection method based on the Hough transform algorithm for pavement crack detection and classification.

Analysis results reveal that model accuracy reaches 92.14% for vertical cracks, 93.03% for diagonal cracks and 95.61% for horizontal cracks. The time lapse for detecting the crack type for one image is circa 0.98 s for vertical cracks, 0.79 s for horizontal cracks and 0.83 s for diagonal cracks. Ensuing discourse serves to illustrate the inherent potential of a simple low-cost image processing method in automated pavement crack detection. Moreover, this method provides direct guidance for long-term pavement optimal maintenance decisions.

The outcome of this research can help highway agencies to detect and classify cracks accurately for a very long highway without a need for manual inspection, which can significantly minimize cost.

Hough transform algorithm was tested in terms of detect and classify a large dataset of highway images, and the accuracy reaches 92.14%, which can be considered as a very accurate percentage regarding automated cracks and distresses classification.

The purpose of the contemporary research study is to develop and empirically investigate antecedents of innovative work behavior (IWB) in organizations by applying the broaden-and-build theory, associating both personal and contextual factors in encouraging employees' IWB.

A conceptual model has been developed, examining the influence of proactive personality and psychological capital (PsyCap) on innovative performance. Data were collected through an in-person administered questionnaire-based survey from the employees working in the software houses of Pakistan.

The analysis revealed that proactive personality and PsyCap have a significant impact on employee innovative performance, given that proactive personality and PsyCap are the critical antecedents of IWB.

This contemporary research study is original and will impart constructive contribution for a substantial number of reasons. First, this research study provides suggestions on proactive personality, which relate remarkably to innovative work behavior. Second, this research study observes the relationship between several organizational aspects and employees' creativity for the evaluation and advancement in the results of prior classic research studies conducted in the given field. This research study integrates both personal and organizational dynamics to evaluate the innovative and creative ability not only in the perspective of multinational, but also in the national corporations.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

As climate change has become a growing concern, sustainable development has become increasingly important. Emissions reduction is a key step for more efficient energy use. In the last few years, the residential building sector in Croatia has received financial support for multi-dwelling building energy efficiency retrofits (EERs). However, some of these projects encountered difficulties due to information asymmetry between the key participants. This study aims to address the problem from the perspective of the principal-agent theory, which is concerned with information asymmetry and the asymmetry's repercussions.

A social network analysis is conducted to reflect the operation and management (OM) details of Croatian multi-dwelling buildings. The key stakeholders of EER are mapped, along with the contractual and communication ties between them. Using the Gephi software, relationship data are visually represented and statistically evaluated.

The analysis indicated two different clusters or groups of stakeholders in EERs in Croatia and enabled the mapping of key relationships between stakeholders. The findings stress the importance of the key relationship between owner representatives (ORs) and property managers (PMs).

The contribution of this study is the development of framework for blockchain implementation in EERs, which can be adapted for use in different markets and/or projects. Blockchain is proposed for minimization of information asymmetry between different stakeholders. Blockchain enables communication and cooperation during project development and enhances trust among stakeholders.