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As the complexity and uncertainty of megaprojects make it difficult for traditional management models to address the difficulties, this paper aims to design a performance incentive contract through IT applications, thereby promoting the formation of an information-based governance mechanism for megaprojects and facilitating the transformation and upgrading of the construction management model of megaprojects to informatisation.

This paper introduced IT applications into the performance assessment and used the proportion of IT applications replacing traditional manual management as a variable. It analysed different replacement ratios to obtain the optimal solution for the change of contractors behaviours and promote the optimal performance incentive for the informatisation in megaprojects.

The results show that under the condition of the optimal replacement ratio, achieving the optimal state of a mutual win-win situation is possible for the benefit of both sides. The counter-intuitive finding is that the greater the replacement ratio is not, the better, but those other constraints are also taken into account.

This study enriched the research of the performance configuration incentive from a practical perspective. It extended the research framework of IT incentive mechanisms in the governance of megaprojects from a management theory perspective. It clarified the role of IT applications in incentive mechanisms and the design process of optimal incentive contracts under different performance incentive states. The incentives made the contractors work harder to meet the owner's requirements, and it could improve the efficiency of megaprojects, thus better achieving megaproject objectives.

The current era is characterized by hyperturbulence, population growth, attention to food security, the need to identify sustainable strategies to reduce pollution and poverty, and the disparity between developed and undeveloped economies. These circumstances force a global paradigm shift based on sustainable practices and processes that put people and the environment at the core of each activity, contributing to sustainable, social, and economic development and promoting well-being in the community.

In this spirit, a strong impulse can derive from the practices of Green Technology, considered here as that set of processes aimed at eco-sustainability that acquire undisputed relevance, especially for emerging economies.

This chapter focuses on the role that Green technology practices exert in generating local well-being in the world's fifth-largest country: Brazil. Dynamic growth and effective social policies lifted millions of people out of poverty in the 2000s, even if socio-economic development varies widely across the country. Brazil is a leading global agricultural, minerals, and oil producer. The natural environment represents the primary source of Brazil's development that deserves to be protected and push firms and citizens to find new sustainable solutions based on green policies. Drawing inspiration from a Brazilian case study, this chapter proposes a set of building blocks that foster sustainable business practices in emerging countries.

The chapter is organized as follows: the first part introduces the concept of green technology practices; the second highlights the opportunities of green technologies; the third focuses on a single case study.

Promoting low-carbon in the construction industry is important for achieving the overall low-carbon goals. Public–private partnership is very popular in public infrastructure projects. However, different perceptions of low-carbon and behaviors of public and private sectors can hinder the realization of low-carbon in these projects. In order to analyze the willingness of each stakeholder to cooperate towards low-carbon goals, an evolutionary game model is constructed.

An evolutionary game model that considers the opportunistic behavior of the participants is developed. The evolutionary stable strategies (ESSs) under different scenarios are examined, and the factors that influence the willingness to cooperate between the government and private investors are investigated.

The results illustrate that a well-designed system of profit distribution and subsidies can enhance collaboration. Excessive subsidies have negative impact on cooperation between the two sides, because these two sides can weaken income distribution and lead to the free-riding behavior of the government. Under the situation of two ESSs, there is also an optimal revenue distribution coefficient that maximizes the probability of cooperation. With the introduction of supervision and punishment mechanism, the opportunistic behavior of private investors is effectively constrained.

An evolutionary game model is developed to explore the cooperation between the public sector and the private sector in the field of low-carbon construction. Based on the analysis of the model, this paper summarizes the conditions and strategies that can enable the two sectors to cooperate.

Three-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.

First, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.

To evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.

The proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.

This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.

Based on the finite element approach coupled with the improved beluga whale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the design of the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar were defined as random variables, and the torsion bar's mass and strength were investigated using finite elements. Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whale optimization (BWO) algorithm and run case studies.

The findings demonstrate that the IBWO has superior solution set distribution uniformity, convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimize the anti-roll torsion bar design. The error between the optimization and finite element simulation results was less than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress was reduced by 35% and the stiffness was increased by 1.9%.

The study provides a methodological reference for the simulation optimization process of the lateral anti-roll torsion bar.

Talking about smart cities also entails talking about new ways of mobility. Various concepts compete for reimagining future mobility, most prominently connected cars, robo taxis, and other forms of shared mobility. New digital technologies, changing customer requirements, but also new competitors are dynamically affecting previous market logics. To stay future-proof in this new world of mobility, the automotive sector, which is an important nucleus for developing such mobility solutions, is currently undergoing fundamental digital transformation processes. Established car manufacturers have to find their path to choose out of the many possibilities on the rise. Against this backdrop, they face the major challenge to find an answer to the question: Who are we and who do we want to be in the future? Therefore, we argue that organizations’ digital transformation is highly entangled with questions on organizational identity and discuss digital transformation as a potential identity threat for established organizations.

We begin this chapter by introducing the concept of organizational identity. Afterward, we will continue with applying it to the practical context of car manufacturers: After depicting the major trends of digitalization in the mobility and automotive sector, we will focus on the digital transformation processes of established automotive companies and discuss their impact on organizational identity. Empirical illustrations of the Volkswagen case depict our theoretical considerations.

We provide theoretical ideas for better understanding the impact of digital transformation on organizational identity, as well as suggestions for practitioners concerned with organizations’ digital transformation processes.

Coal is a critical global energy source, and fluctuations in its price significantly impact related enterprises' profitability. This study aims to develop a robust model for predicting the coal price index to enhance coal purchase strategies for coal-consuming enterprises and provide crucial information for global carbon emission reduction.

The proposed coal price forecasting system combines data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. It addresses the challenge of merging low-resolution and high-resolution data by adaptively combining both types of data and filling in missing gaps through interpolation for internal missing data and self-supervision for initiate/terminal missing data. The system employs self-supervised learning to complete the filling of complex missing data.

The ensemble model, which combines long short-term memory, XGBoost and support vector regression, demonstrated the best prediction performance among the tested models. It exhibited superior accuracy and stability across multiple indices in two datasets, namely the Bohai-Rim steam-coal price index and coal daily settlement price.

The proposed coal price forecasting system stands out as it integrates data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. Moreover, the system pioneers the use of self-supervised learning for filling in complex missing data, contributing to its originality and effectiveness.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Promoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.

This study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.

The results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.

This research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.

This study aims to examine the effects of industrialization, deindustrialization and financialization on Turkey’s energy insecurity by controlling the impacts of urbanization and alternative energy generation for the 1980–2018 period.

This study proposed an econometric model relying on the literature. Moreover, based on different financialization variables, this study estimated two specifications of this model using the augmented nonlinear autoregressive distributed lag approach.

The results are as follows: first, industrialization increased Turkey’s long-run energy insecurity, whereas deindustrialization did not affect Turkey’s energy security. Second, urbanization worsened Turkey’s energy insecurity. Third, financialization aggravated Turkey’s energy insecurity. Last, alternative energy generation improved Turkey’s energy security.

This study identifies the energy security’s drivers in Turkey with a focus on industrialization and financialization. Nonetheless, further research is needed on other emerging economies with high energy insecurity levels, and a disaggregated approach can be followed to examine how various industrial sectors impact energy security.

To combat energy insecurity, quantifiable, innovative and energy-efficient goals should be set for Turkey’s industry sector. Additionally, to achieve these goals, financial opportunities should be provided by reforming the financial sector. This reformative approach can also curb financialization’s negative effect on Turkey’s energy security.

Deindustrialization is not a solution to Turkey’s energy insecurity. Also, unless necessary actions are taken, industrialization, financialization and uncontrolled urbanization may continue to threaten Turkey’s energy security. Finally, promoting alternative energy generation seems to be a viable long-run solution to energy insecurity.

Although a significant number of studies investigated industrialization’s and financialization’s impacts on energy demand or environmental damage, only a few studies examined their impacts on energy insecurity. Similar to other developing nations, as Turkey is facing chronic energy security problems, the author believes that the analysis provides important policy insights regarding energy (in)security’s drivers. By differentiating the impacts of industrialization and deindustrialization, this study also shows that deindustrialization may not be a proper solution to deal with energy insecurity.