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The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

Emotions, understood as evolving mental states, are pivotal in shaping individuals“' decision-making, especially in ambiguous information evaluation, probability estimation of events, and causality analysis. Public–private partnership (PPP) projects represent a confluence of “economic–environmental–social” dimensions, wherein stakeholder behavior follows the sequential progression of “cognition–emotion–action.” Consequently, comprehending the effects of emotional shifts on stakeholder's decision-making processes is vital to fostering the sustainability of PPP projects.

The paper utilizes rank-dependent expected utility and evolutionary game theory to systematically examine the influence of emotional factors on stakeholders' behavior and decision-making processes within PPP projects. The paper integrates three emotional state functions—optimism, pessimism and rationality—into the PPP framework, highlighting the intricate interactions among the government, private sector, surrounding public and the media. Furthermore, the paper amalgamates the evolutionary pathways of environmental rights incidents with the media's role. Through equilibrium analysis and numerical simulation, the paper delves into the diverse interplay of emotions across different phases of the environmental rights incident, assessing the impact of these emotions on the evolutionary game's equilibrium results.

Emotions significantly influence the microlevel decisions of PPP stakeholders, adapting continually based on event dynamics and media influences. When the private sector demonstrates optimism and the surrounding public leans toward rationality or pessimism, the likelihood of the private sector engaging in speculative behavior escalates, while the surrounding public refrains from adopting a supervisory strategy. Conversely, when the private sector is pessimistic and the public is optimistic, the system fails to evolve a stable strategy. However, when government regulation intensifies, the private sector opts for a nonspeculative strategy, and the surrounding public adopts a supervisory strategy. Under these conditions, the system attains a relatively optimal state of equilibrium.

The paper develops a game model to examine the evolutionary dynamics between the surrounding public and private sectors concerning environmental rights protection in waste incineration PPP projects. It illuminates the nature of the conflicting interests among project participants, delves into the impact of emotional factors on their decision-making processes and offers crucial perspectives for the governance of such partnerships. Furthermore, this paper provides substantive recommendations for emotional oversight to enhance governance efficacy.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

It is imperative for policymakers, financial institutions, and individual investors to comprehend the factors that impact stock market participation, given the growing significance of the stock market in terms of personal and national wealth. This study endeavours to explore the relationship between cognitive ability and participation in the stock market. We examine the relationship between cognitive abilities and stock market participation, and further explore the mechanism of their influence.

The data from the China Family Panel Studies is utilized, and Tobit and Probit regressions are employed. Additionally, an instrumental variable approach (IV-estimate) is implemented to address the endogeneity issue linked to cognitive ability, and the study’s findings are resilient.

The results reveal a significant positive relationship between cognitive ability and stock market participation. Additionally, the findings suggest that households with higher cognitive ability tend to aggregate more information, expand social networks, and take more risks. A likely explanation is that individuals with higher cognitive ability are more likely to process more external information and evaluate the subjective uncertainty of stock markets based on a well-defined probability distribution. Our findings indicate that the impact of cognitive ability on stock market participation varies among families with differing education levels, genders, marital statuses, and geographical locations.

Therefore, the roles of cognitive abilities in accelerating stock market participation should be fully considered. More information channels and sources that contain financial markets’ information (e.g. mobile applications and financial education) should be provided. Thus, the significance of cognitive ability in increasing stock market participation should be fully considered. Providing more information channels and sources, such as mobile applications and financial education, that contain financial markets’ information would be helpful. Our study contributes to promoting financial literacy and inclusion by highlighting the significant positive impact of cognitive ability, where institutions can tailor their outreach efforts and information channels to better serve individuals with different cognitive ability.

Mega construction projects (MCPs), which play an important role in the economy, society and environment of a country, have developed rapidly in recent years. However, due to frequent social conflicts caused by the negative social impact of MCPs, social risk control has become a major challenge. Exploring the relationship between social risk factors and social risk from the perspective of risk evolution and identifying key factors contribute to social risk control; but few studies have paid enough attention to this. Therefore, this study aims to systematically analyze the impact of social risk factors on social risk based on a social risk evolution path.

This study proposed a social risk evolution path for MCPs explaining how social risk occurs and develops with the impact of social risk factors. To further analyze the impact quantitatively, a social risk analysis model combining structural equation model (SEM) with Bayesian network (BN) was developed. SEM was used to verify the relationship in the social risk evolution path. BN was applied to identify key social risk factors and predict the probabilities of social risk, quantitatively. The feasibility of the proposed model was verified by the case of water conservancy projects.

The results show that negative impact on residents’ living standards, public opinion advantage and emergency management ability were key social risk factors through sensitivity analysis. Then, scenario analysis simulated the risk probability results with the impact of different states of these key factors to obtain management strategies.

This study creatively proposes a social risk evolution path describing the dynamic interaction of the social risk and first applies the hybrid SEM–BN method in the social risk analysis for MCPs to explore effective risk control strategies. This study can facilitate the understanding of social risk from the perspective of risk evolution and provide decision-making support for the government coping with social risk in the implementation of MCPs.

This paper aims to provide an elucidative and explanatory overview of decision-making theory that human resource management and development (HR) researchers and practitioners can use to explore the impact of heuristics and biases on organizational decisions, particularly within HR contexts.

This paper draws upon three theoretical resources anchored in decision-making research: the theory of bounded rationality, the heuristics and biases program, and cognitive-experiential self-theory (CEST). A selective narrative review approach was adopted to identify, translate, and contextualize research findings that provide immense applicability, connection, and significance to the field and study of HR.

The authors extract key insights from the theoretical resources surveyed and illustrate the linkages between HR and decision-making research, presenting a theoretical framework to guide future research endeavors.

Decades of decision-making research have been distilled into a digestible and accessible framework that offers both theoretical and practical implications.

Heuristics are mental shortcuts that facilitate quick decisions by simplifying complexity and reducing effort needed to solve problems. Heuristic strategies can yield favorable outcomes, especially amid time and information constraints. However, heuristics can also introduce systematic judgment errors known as biases. Biases are pervasive within organizational settings and can lead to disastrous decisions. This paper provides HR scholars and professionals with a balanced, nuanced, and integrative framework to better understand heuristics and biases and explore their organizational impact. To that end, a forward-looking and direction-setting research agenda is presented.

This paper argues that through information and communication technology (ICT) adoption, the youth will be engaged in all nodes of the agricultural value chains, thereby improving the level of employment and reducing post-harvest losses. The study examines the determinants of ICT adoption among the youth. In addition, it estimates the impact of ICT adoption on youth employment in agriculture towards the actualisation of the Sustainable Development Goals (SDGs), particularly SDG-8, to promote inclusive and sustainable economic growth, productive employment and decent work for all.

The study engages data from Wave 4 (2018/2019) of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The logit regression, the propensity score matching and the inverse probability weighted regression adjustment are used as the estimation techniques.

The study underscores that educational level, access to electricity, location, age and income are significant determinants of ICT adoption among the youth. The findings also show that the youth's average weekly engagement in agricultural activities is about 24 h. In addition, the result reveals that ICT adoption can increase youth agricultural employment by approximately 21%. The mean difference indicates that those with access to ICT participate in agricultural activities more than their counterparts without ICT access by 29.46%.

One of the limitations of the study is that some of the variables such as insecurity, social protection/safety nets, that may have a significant influence on youth agricultural participation where not included in the model due to data constraint. As a recommendation for further studies, given data availability, such variables should be considered when examining youth-agricultural employment nexus.

Since ICT adoption has a significant impact on agricultural employment, this study proposes improved infrastructure facilities such as reliable power supply, lowering the cost of mobile and data subscriptions and better education facilities should be prioritised at all localities. This will enable the youth to embrace agriculture and help improve their socioeconomic welfare and livelihood.

Using Wave 4 of the LSMS-ISA, logit regression, propensity score matching and the inverse probability weighted regression adjustment, makes this study one of the very few to examine the impact of ICT adoption on agricultural employment among the youth in Nigeria. It implies that this study has provided empirical evidence and expanded the frontiers of knowledge on the extent to which ICT adoption influences youth agricultural employment in Nigeria.

The board structure (BS) is pivotal in modern corporate governance (CG). This study aims to investigate BS variables (BSIZE, BIND and chief executive officer [CEO] duality) and their correlation with risk-taking behavior indicators, enriching the understanding of how CG shapes financial institutions’ (FIs) decision-making in Pakistan.

By scrutinizing data from 67 financial entities listed on the Stock Exchange of Pakistan spanning from 2011 to 2022 through panel data regression techniques, the research emphasizes that BS holds a substantial influence over the risk tendencies exhibited by these firms.

Key findings suggest that board size has a positive influence, aligned with previous CG research. Smaller boards perform better and avoid excessive risk-taking, contrasting some negative relationship claims. More independent directors are recommended to curtail risk and financial disruption. Holding both CEO and chair roles reduces risk exposure, resonating with reputational and employment risk theory. It is essential to recognize that BS’s impact on risk-taking is nuanced and context-dependent.

Policymakers, scholars, practitioners and investors working in the market for financial companies might greatly benefit from the empirical findings of this study. Imposing mandates on FIs to uphold adequate capital reserves functions as a safeguard against unforeseen losses, thereby diminishing the probability of unwarranted risk-taking.

Prior studies in this domain predominantly focus on nonfinancial sectors. In addition, existing research often explores the relationship between BS and firm risk-taking solely within the banking sector, overlooking other FIs. This study contributes by using a comprehensive data set encompassing all types of FIs, thus extending the existing literature.

Brief introduction on the importance and the need for plastic analysis methods were presented in the beginning section of this review. The plastic method for analysis was considered to be the more advanced method of analysis because of its ability to represent the true behaviour of the steel structures. Then in the following section, a literature analysis has been carried out on the previous investigations done on steel plates, steel beams and steel frames by other authors. The behaviour of them under different types of loading were presented and are under the investigation of innovative new analysis methods.

Structure member connections also have the potential for plastic failure. In this study, the authors have highlighted a few topics to be discussed. The three topics in this study are T-end plate connections to a square hollow section, semi-rigid connections and cold-formed steel storage racks with spine bracings using speed-lock connections. Connection is one of the important parts of a structure that ensures the integrity of the structure. Finally, in this technical paper, the authors introduce some topics related to seismic action. Application of the Theory of Plastic Mechanism Control in seismic design is studied in the beginning. At the end, its in-depth application for moment resisting frames-eccentrically braced frames dual systems is investigated.

When this study involves the design of a plastic structure, the design criteria must involve the ultimate load rather than the yield stress. As the steel behaves in the plastic range, it means the capacity of the steel has reached the ultimate load. Ultimate load design and load factor design are the methods in the range of plastic analysis. After the steel capacity has reached beyond the yield stress, it fulfills the requirement in this method. The plastic analysis method offers a consistent and logical approach to structural analysis. It provides an economical solution in terms of steel weight, as the sections designed using this method are smaller compared with elastic design methods.

The plastic method is the primary approach used in the analysis and design of statically indeterminate frame structures.