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This study aims to investigate the optimal pricing decisions and shared channel strategy selection of battery manufacturers considering heterogeneous consumers' range anxiety.

Amidst the rapid growth of the electric vehicle sector, countries are promoting upgrades in the automotive industry. However, insufficient driving range causes consumer range anxiety. The study utilizes the Stackelberg game model to assess how range anxiety influences battery manufacturers' pricing and channel strategy decisions across three strategies.

We find that electric vehicle battery manufacturers' decisions to cooperate with third-party sharing platforms (TPSPs) are primarily influenced by fixed costs and consumer range anxiety levels. As range anxiety increases, the cost threshold for joining shared channels rises, reducing cooperation likelihood. However, considering diverse consumer needs, especially a higher proportion of leisure-oriented consumers, increases the likelihood of cooperation. Furthermore, higher battery quality makes direct participation in shared channels more probable.

In the electric vehicle industry, range anxiety is a significant concern. While existing literature focuses on its impact on consumer behavior and charging infrastructure, this study delves into battery manufacturers' strategic responses, offering insights into channel options and pricing strategies amidst diverse consumer segments.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

As technology aspect of agriculture becomes more and more important with the time to increase agricultural productivity in a sustainable and smart way, agriculture practices become more interdisciplinary. Furthermore, agricultural practices are affected by urban and rural planning enabling urban and rural farming. Architecture, engineering and construction (AEC) industry can support food security through the integration of agricultural practices and technologies into the built environment, its interior design, and greenhouses supporting urban and rural farming. Based on the literature review, this chapter aims to investigate ways for enhancing AEC industry’s and its professionals’ contribution to food security and sustainable agricultural practices. This chapter highlights roles of the AEC industry in enhancing food security and sustainable agricultural practices. This chapter emphasizes the importance of undergraduate and graduate curriculums of future AEC industry professionals (e.g., architects, interior architects, civil engineers) to equip them with the skills and knowledge of sustainable agricultural practices and technologies integrated greenhouses, built environment and indoor environment, and interior design. For this reason, agricultural policies need to cover food security-related interdisciplinary education and training (e.g., renewable energy-based agriculture integrated built environment) of AEC industry professionals. Agricultural policies need to be designed with the contribution of and considering AEC industry professionals as they are among the main stakeholders of food security and renewable energy-based agriculture-integrated built environment. Furthermore, this chapter highlights how AEC industry, in compliance with United Nations Sustainable Development Goals and countries sustainable and resilient development plans, can contribute to food security and sustainability. This chapter can be beneficial to all stakeholders of the sustainable agricultural practices.

Green and digital transitions (twin transition) help in achieving climate neutrality, cutting down the pollution level and reviving biodiversity. Organizations can mitigate their ecological footprint, improve their digital portfolio and fulfil their ethical responsibilities by fostering a sustainable global community and adhering to a well-defined plan. In such backdrop, this study aims to propose strategies by identifying the strengths, weaknesses, opportunities and threats of the twin transition and to categorize and evaluate the internal and external factors for achieving environmental sustainability.

Following a comprehensive review of the literature, 27 factors have been identified and analyzed using the strengths, weakness, opportunities and threat matrix (SWOT). Threats, opportunities, weakness, strength matrix analysis approach is used to limit risk, overcome weaknesses and take advantage of opportunities. Effective strategies are designed and implemented using strategic planning action and evaluation matrix (SPACE) and quantitative strategic planning (QSPM) approach.

The study found that aggressive strategies considering economic strength and global opportunities must be used to accomplish green growth objectives. Out of three strategies, the focus on green technological innovation by taking advantage of financial mechanisms at the international level is highly recommended to achieve environmental sustainability.

Through promoting green and digital transformation, the current study provides insightful policy recommendations for economic development. It may help to improve operational efficacy and to obtain a competitive edge by successfully limiting their adverse environmental effects in the global market through the implementation of twin transition. The process of developing a strategy aids stakeholders, including society, workers and other parties, in giving environmental sustainability a top priority while making financial decisions.

Strategy development helps society, employees and all the other stakeholders to prioritize their green and digital transition decisions for environmental sustainability.

The current study identifies the factors formulating strategies using SWOT, TOWS, SPACE and QSPM matrix analysis for achieving environmental sustainability in the pervasive twin transition.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

Purpose. This chapter discusses the challenges and different strategies to increase skill development for the future workforce.

Methodology. Multiple sources on the topic were studied and reviewed in this chapter. The idea of skill and its development is discussed in the literature review.

Findings. Different nations’ governments have promoted human capital development by providing up-skilling and retraining programs to balance supply and demand. Skills gaps need to be brought to the attention of stakeholders, such as governments, businesses, and the educational system. Teachers, employers, and other stakeholders need to develop strategies and action plans to ensure that the skills gaps are appropriately identified and adequately addressed. These initiatives must be developed with input from various stakeholders.

Practical Implications. The research results would inform the curriculum, incorporating skill development processes tailored to various scenarios. These findings would aid business organisations in crafting skill development programs that address identified skill gaps. Challenges in skill development would be taken into account during course development, and relevant teaching–learning materials would be created. Key stakeholders, such as accrediting organisations, employers, and students, should exert more influence on academic institutions to prioritise societal demands for economic development.

Originality/Value. The uniqueness and significance of this chapter lie in its concise summary of the strategies to tackle the hurdles in skill development.

This paper studies the location-inventory problem (LIP) in pallet pooling systems to improve resource utilization and save logistics costs, which is a new extension of the classical LIP and also an application of the LIP in pallet pooling systems.

A mixed-integer linear programming is established, considering the location problem of pallet pooling centers (PPCs) with multi-level capacity, multi-period inventory management and bi-directional logistics. Owing to the computational complexity of the problem, a hybrid genetic algorithm (GA) is then proposed, where three local searching strategies are designed to improve the problem-solving efficiency. Lastly, numerical experiments are carried out to validate the feasibility of the established model and the efficiency of the proposed algorithm.

The results of numerical experiments show that (1) the proposed model can obtain the integrated optimal solution of the location problem and inventory management, which is better than the two-stage model and the model with single-level capacity; (2) the total cost and network structure are sensitive to the number of PPCs, the unit inventory cost, the proportion of repairable pallets and the fixed transportation cost and (3) the proposed hybrid GA shows good performance in terms of solution quality and computational time.

The established model extends the classical LIP by considering more practical factors, and the proposed algorithm provides support for solving large-scale problems. In addition, this study can also offer valuable decision support for managers in pallet pooling systems.

The aim of this study is to examine the relationships between taking charge, bootlegging innovation and innovative job performance, and to explore the moderating roles of felt responsibility for constructive change (FRCC) and creative self-efficacy (CSE).

Data for this research was collected from 503 employees working in a chain company. Through a longitudinal study design, a three-wave survey with 397 valid data provided support for the proposed theoretical model.

The results maintain a positive association between taking charge, bootlegging innovation and innovative job performance, indicating the mediating effect of bootlegging innovation. Additionally, both the FRCC and CSE facilitate the indirect effect of taking charge on innovative job performance through bootlegging innovation. Furthermore, the integrated moderated mediation model analysis suggested that FRCC is more vital in improving employees' innovative job performance.

This research aims to break the black box between taking charge and innovative job performance, which has been relatively unexplored. Drawing from self-determination theory (SDT) and the proactive motivation model, the authors verify the bridge-building role of bootlegging innovation and the dual-facilitating effects of FRCC and CSE while employees conduct taking charge. This study’s results provide new insight for managers to foster, encourage and support employees' proactive behavior.

On the premise of verifying whether the platformization organization of DEEs is born, this work aims to explore the evolutionary process of the organizational structure of digital entrepreneurial enterprises (DEEs) and to further reveal the drivers of organizational structure evolution from the perspective of data resources.

The authors use a longitudinal two-case approach to analyze rich archival and interview data from two DEEs in China.

The findings reveal that the organizational structure of DEEs evolves from hierarchy, network and flatlization to platformization, that the drivers of evolution include building data flow channels, removing barriers of data flow and forming data rules. Meanwhile, the coordination devices in this process have gradually evolved from hierarchy to standard operating procedures, shared culture, norms, etc. to achieve a balance between commercial and creative success.

This work develops a framework for the evolution of organizational structure of DEEs from organization design theory lens and provide some management insights into the development of DEEs.

In the prior literature, the motivation to adopt wearable fitness technology (WFT) has been linked with either intrinsic or extrinsic. However, how the subcategories of extrinsic motivations (identified, introjected and external) affect the consumers’ WFT adoption decision remains sparse. Furthermore, do regulatory focus (prevention vs promotion) and gender differences the effects of different motivations on WFT adoption is almost unknown in the health-care marketing literature. This study aims to fill the above-mentioned gap and to unfold the WFT adoption beyond the traditional motivation by incorporating the organismic integration theory (part of self-determined theory) and regulatory focus theory.

This study used a questionnaire-based survey. Using the “AMOS” survey, questionnaire responses of 641 respondents were analyzed and validated by using structural equation modeling. All the variables were adopted from the literature.

The results show that intrinsic, identified and external motivations have the greatest impact on consumers’ decisions, while introjected motivation was not significant directly. The moderation effects of regulatory focus are significant in such a way that prevention focus influences the introjected motivation and promotion focus affects the external motivation and WFT adoption decision. Furthermore, the findings on gender moderation suggest that women are more intrinsically motivated, and men are more externally motivated for WFT adoption.

The new insights and contributions of this study provide a better understanding of WFT adoption and help sellers develop more effective marketing strategies.

This study incorporates subcategories of extrinsic motivations to provide a deeper understanding of consumers’ behavior. Furthermore, this study applies a unique framework of organismic integration theory to consumers’ WFT adoption. It is also among very few research that investigate regulatory focus and gender impact on consumers’ WFT adoption.