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Fixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between pixels in the photoelectric conversion process belong to fixed mode noise. This study aims to improve the image sensor imaging quality by processing the fixed mode noise.

Through an iterative training of an ergoable long- and short-term memory recurrent neural network model, the authors obtain a neural network model able to compensate for image noise crosstalk. To overcome the lack of differences in the same color pixels on each template of the image sensor under flat-field light, the data before and after compensation were used as a new data set to further train the neural network iteratively.

The comparison of the images compensated by the two sets of neural network models shows that the gray value distribution is more concentrated and uniform. The middle and high frequency components in the spatial spectrum are all increased, indicating that the compensated image edges change faster and are more detailed (Hinton and Salakhutdinov, 2006; LeCun et al., 1998; Mohanty et al., 2016; Zang et al., 2023).

In this paper, the authors use the iterative learning color image pixel crosstalk compensation method to effectively alleviate the incomplete color mixing problem caused by the insufficient filter rate and the electric crosstalk problem caused by the lateral diffusion of the optical charge caused by the adjacent pixel potential trap.

Stakeholder interests are complex, sensitive and highly uncertain and may influence the development of net zero carbon building (NZCB). However, this study aims to conduct a systematic literature review to explore the stakeholder interests towards achieving NZCB.

A total of 62 articles were identified from the Scopus database and thoroughly reviewed to extract relevant information on stakeholders' interest towards achieving NZCB.

A total of 28 stakeholder interests influencing the development of NZCB were identified from the literature and were classified into six major groups according to their uniqueness (economic, social, environmental, technological, political, regulatory and legal).

The findings of this study provide insight into the specific stakeholder interests towards achieving NZCB. Thus, the findings of this study could serve as a guide for future research, policy formulation and implementation to expedite the practice of building towards net zero carbon (NZC). Empirical studies are suggested in future studies to test and consolidate the theoretical claims of this study.

This paper undertakes a comprehensive systematic review of studies on stakeholder interests towards achieving NZCB, which is the least investigated in the literature.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

Optimal clean-up procedures lie at the heart of the closeout phase of construction projects under contract law. However, due to its complexity involving multiple issues, potentially unfulfilled contractual obligations, performance claims and counter-claims, combined with consequently deteriorating stakeholder relationships, the management of closeouts is fraught with difficulties leading to suboptimal outcomes. This is particularly true where general contractor (GC) organizations do not have a claims management office (CMO) dedicated to improving such suboptimal clean-up outcomes. Thus, this study aims to develop a model by which CMOs’ may effectively manage the clean-up phase in an environment of closeout claims.

X-inefficiency theory was utilized as the theoretical lens guiding this study. The theory helps identify closeout strategies implemented by a GC, which manages completion claims through a CMO. Data were received and analyzed from a large GC, which served as the firm case study. In this case, managing the closeout completion claims was the main function of the CMO.

The average delay of closeout completion was four times greater than construction phase delays. The GC results highlighted the “economic destruction tsunami of projects,” as a root cause for these completion delays. Wrap-up activities under contract law are identified, including within the domains of statements of completion, project handover and debt settlement. Behavior strategies are also defined, including relational and contractual approaches. Moreover, a process for improving closeout claim performance is described, comprising project closeout identification, rational intra-firm behavior, closeout completion and program closeout practice.

Findings from this work can significantly contribute in X-inefficiency theory in relation to how a decrease of X-inefficiency will lead to better closeout claim performance. It also offers practical insights into how best to minimize delayed closeout completion while providing valuable lessons for stakeholders in complex infrastructure projects. Further, a model is developed that may be utilized by owners, consultancies, designers and other contractor organizations in an effort to improve closeout claim performance.

This article explores how the social media usage affect team creative performance via transactive memory system, knowledge interaction and expertise coordination.

The study is based on the perspective of transaction memory system and expertise coordination theory. A research model was constructed and tested, involving 289 individuals from 67 distributed agile software development teams.

The results indicate that social media usage is positively correlated with transactive memory system, and social media usage and transactive memory system have positive relations to knowledge interaction and expertise coordination. Moreover, this analysis shows that knowledge interaction has a positive relationship with expertise coordination, and expertise coordination positively affects team creative performance. However, knowledge interaction has no direct relationship on team creative performance, and its indirect impact on team creative performance was fully mediated by expertise coordination. This research shows that social media usage by distributed agile software development teams can support the development of transactive memory system and promote expertise coordination. In addition, knowledge interaction alone is not enough, and expertise coordination must be achieved to increase team creative performance.

First, this paper explores the mechanism of transactive memory system in distributed Agile Software Development teams from the perspective of social media, which is different from the previous information processing theory framework that confined transactive memory system to the cognitive aspects of knowledge coding, storage and retrieval. Second, this research focuses on the knowledge interaction and expertise coordination formed by team members in the process of communication in the context of social media usage, which confirms the crucial roles of social media usage and transactive memory system in team knowledge management and team creative performance. Then, this research also shows that the development of transactive memory system in the team is indeed an important factor to promote knowledge interaction and professional expertise coordination.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

In today’s digital era, talent recruitment can help address the growing shortage of skilled labor in the construction industry and promote sustainable growth. While existing research has explored the association between talent acquisition and local labor productivity or economic progress, the impact on construction growth deserves further study. This study aims to (1) explore the influence of talent recruitment on the growth of the construction industry and (2) analyze whether different regional characteristics shape the differential impact of talent acquisition on construction growth.

This research employs a quantitative approach, focusing on 35 major cities in China. A panel data regression model is utilized to analyze annual data from 2013 to 2018, considering variables like the construction talent recruitment index, value added in construction, gross regional product per capita and others. The study also examines regional heterogeneity and conducts robustness tests to validate the findings.

The results reveal a positive and significant correlation between talent recruitment and construction industry growth. This correlation is more pronounced in economically advanced and infrastructure-rich regions. The study also finds that factors like capital investment, educational attainment and housing prices significantly contribute to industry growth. Talent recruitment not only transforms local labor market dynamics but also drives demand for construction services, promoting industry growth through economies of scale.

This research constructs a new measurement for talent recruitment and provides new insights into the pivotal role of talent recruitment in the sustainable growth of the construction industry. It underscores the need for construction firms to tailor talent acquisition policies to their specific circumstances and regional developmental conditions. The findings offer practical guidance for driving regional growth within the sector, emphasizing the importance of talent recruitment as a key yet previously underappreciated factor in industry development.

The purpose of the article is to identify the factors of the success of the change management process in IT programs.

The article presents the results of quantitative research conducted among 221 managers involved in the process of IT program management. In addition, to achieve the assumed goal, a factor analysis and cluster analysis were carried out on the basis of which a model of the relationship between success determinants and the change management process in the IT program was built.

Nine factors significant for the change management of IT programs have been identified. What is more, they illustrate 78.23% of all significant variables that may occur and significantly affect the success of the IT change program. In addition, it was indicated which factors have a significant impact on achieving the success of the program in individual sub-processes of the course of change.

The article identified 38 variables determining the success of an IT program as a result of a literature review. Secondly, the article responds to the call of Teubner (2018) for IT programs and Vuorinen and Martinsuo (2018) for programs of change.

The article complements the current theory with identified factors of success in the change management process in IT programs. In addition, the article presents recommendations for managers regarding the importance of the identified factors and their impact on the success of the program.

To help decision-makers choose appropriate infrastructure project delivery systems (IPDS) and keep up with the construction industry’s rapid growth, this study aims to develop a goal optimization technique.This looks into team integration, large production and optimum sustainability. The suggested approach for meeting several infrastructure project objectives is flexible and expandable. This research overcomes the significant discrepancy between the construction industry’s progress and the rate at which project delivery methods evolve.

This study examined pertinent literature to choose an appropriate project delivery method and gave information on several elements that affect that decision. After optimization using a genetic algorithm (GA), a Pareto front of solutions has been found. The three construction goals of sustainability, mass production and team integration are all met by the chosen best solution. The four most popular possibilities for studying the suggested approach are five primary categories, each of which has 22 variables, and the weight of each variable was established using Simo’s procedure. This is optimized, demonstrating the accuracy of the optimization model.

Sustainability, mass production and team integration are the major goals of selecting the finest IPDS. The Pareto-optimal solutions discovered through analysis demonstrated that the created GA is reliable and generates solid outcomes. In fact, it enables decisions that were based on a single criterion to be overturned. The process has therefore demonstrated its efficacy in identifying the ideal answer. First integrated project delivery (IPD), second design-build (DB), third design-bid-build (DBB) and last construction manager at risk (CMR) are the best options. The weight of the aims function has found these rankings to be satisfactory.

The findings demonstrate that the suggested strategy can lead to optimization, providing the government with a wide range of options for attaining certain project objectives. The ability of this study to evaluate the combined effects of three objectives in choosing the best IPDS, the production of optimal selection solutions (IPDS), which can help with better decision-making when many objectives are present, and the flexibility and extendibility of the suggested approach for achieving priorities in infrastructure projects are what make it unique. This approach was able to select IPDS to meet developments in the construction project.

To confirm the validity of the GA, the factor of error was calculated, which is equal to 1.7599e-08.

This paper studies the determinants for the desirability of the public-private partnership (PPP) mode in infrastructure development.

The author manually collects data on over 12,000 PPP projects in China, and regard the successful transition and abnormal termination as signals for the mode’s desirability and undesirability, respectively. Then, guided by relevant theories in the literature, the author investigates the impact of various project characteristics on the projects’ successful transition and abnormal termination.

First, execution-stage projects in industries where government support is indispensable, or where quality improvement is more important than cost reduction, face higher likelihood of abnormal termination. But such negative effects are mitigated if state-owned enterprises (SOEs) participate in the social party. Second, the structure of social party matters. The participation by private firms in the social party increases the termination likelihood, while the decentralization of the social party decreases it. Third, pre-execution projects with government payment or subsidies are more likely to enter into the execution stage.

Regulations on participation by SOEs in PPPs, such as policy [2023 No. 115] announced by State Council, should take industrial heterogeneity into consideration.

Using a large sample, the author empirically tests the seminal PPP-related theories in the literature. The author also uncovers some unique stylized facts about PPPs in China, especially the impact of SOE participation in the social party on PPP survival.