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Purpose: In this chapter of this book, the role and contributions of blockchain in Industry 5.0 are examined. Especially, the advantages offered by blockchain in mass customization, hyper-personalization, human–robot collaboration and cognitive systems, which constitute the main theme of Industry 5.0, are mentioned.

Need for the study: With developing technology, revolutions are taking place in the industry. While these revolutions are occurring, various technologies serve as enablers. In this chapter, one of these technologies, blockchain, is examined.

Methodology: Industrial revolutions represent important technological developments for societies. In this chapter, Industry 5.0, one of these revolutions, is discussed. In the first section, the main themes of Industry 5.0 were examined. Afterward, the transition from Industry 4.0 to Industry 5.0 was analyzed. Then, the opportunities offered by Industry 5.0 were reviewed. Subsequently, the contributions of blockchain to Industry 5.0 were examined. Finally, the role of blockchain in Industry 5.0 is summarized.

Findings: The main themes of Industry 5.0 enable customized processes and smart production approaches. Blockchain makes significant contributions to these processes with its security and traceability features. In addition, smart contracts can increase transparency, traceability and security among stakeholders in the production process with their distributed ledger structure and immutability features. In blockchain networks, each transaction is carried out and approved by consensus. This consensus, provided by smart contracts, also secures transactions by reducing administrative costs. With these contributions, blockchain meets the security and smart management requirements of Industry 5.0.

This study investigates the relationship between digitalization and agricultural carbon intensity from 2006 to 2021.

Utilizing panel data from 30 provinces in China from 2006 to 2021, this study employs a threshold and a spatial Durbin model to investigate the relationship between digitalization and agricultural carbon intensity. In addition, a heterogeneity analysis was conducted to understand variations across regions.

The study used threshold models and spatial Durbin models to reveal that in agricultural production, digitalization can significantly reduce the carbon emission intensity of planting and livestock production. Through the threshold effect, it was found that the effectiveness of digitization in curbing emissions varies by region and is influenced by the level of urbanization, with the inhibitory effect being: western > central > eastern. In addition, through spatial analysis, it was found that the impact of digitalization on carbon emission intensity has significant spatial effects, presenting a “high-high” and “low-low” clustering pattern. Moreover, through the Durbin model, digitization exhibits a significant negative spatial impact on the planting industry, and the development of the local digitalization can significantly reduce the carbon emission intensity of the planting industry in neighboring areas. There is a significant positive spatial effect on livestock production, and the development of local digitalization will, to some extent, increase the carbon emission intensity of livestock production in neighboring areas. This study underscores the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This study shows the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This paper pioneers the investigation of the spatial impact of digitalization on agricultural carbon emissions using provincial-level panel data and classifies agriculture into planting and livestock production. This study contributes to the literature by filling the research gap and enhancing our understanding of the relationship between digitalization and environmental sustainability in rural areas.

Open innovation platform has become an effective field through which enterprises can acquire valuable knowledge for incremental and breakthrough innovation. However, as more entities join the innovation platform, the knowledge activities in the platform ecosystem are now facing higher complexity and vulnerability due to the differences in the knowledge demands as well as conflicting interest claims of participants. The lack of mature governance mechanisms has caused opportunistic behaviors like knowledge infringement, leakage and hiding, which seriously hinder the in-depth knowledge sharing and effective utilization. What’s more, the enthusiasm for collaborative innovation also reduced among multi-subjects. Therefore, the purpose of this study is to improve platform participants’ innovation ambidexterity under the guidance of scientific design of platform knowledge governance mechanisms through improved knowledge transformation processes.

Therefore, based on knowledge governance theory and knowledge transformation model (SECI, socialization-externalization-combination-internalization), the study explored the influence of relationship and contractual knowledge governance on the innovation ambidexterity of platform participants through the mediation effect of knowledge transformation. To better analyze complex causal relationships among variables and the chain multiple mediation effect, structural equation modeling is used, coupled with bootstrap analysis verification.

Platform contractual governance and relationship governance can positively influence the innovation ambidexterity of participants through knowledge trading and reuse, as well as through knowledge sharing and creation. The findings not only contribute to optimizing the effectiveness of knowledge activities on digital platforms but also provide empirical evidence and practical insights to support enterprises’ incremental and breakthrough innovation according to their own knowledge bases.

The findings offer valuable insights for providing decision-making guidance not only for platform-leading enterprises but also for individual and enterprise users on effectively using open innovation platforms to conduct knowledge seeking, trading or sharing and knowledge reuse or creation to enlarge the incremental innovation value and to trigger breakthrough innovation value in their product and technology developments.

Through diverse knowledge governance mechanisms, platform-leading enterprises do not only act as “economic agents” with private attributes to reduce knowledge asymmetry in the public trading market, diffuse knowledge broadly and mitigate cooperation costs to increase economic value; they also serve as “social actors” for multilateral participants to increase the cohesion of knowledge sharing and creation to provide sustainable knowledge fuel for the higher level of breakthrough innovation. Overall, knowledge arrangement efficiency can be optimized, and breakthrough innovation value can be activated in a well-governed platform, gradually escaping the diminishing marginal benefits of exploitative innovation.

This study has extended the views of the knowledge transformation model under the platform context and proposed dualistic knowledge transformation pathways, named “tacit knowledge socialization” and “explicit knowledge combination,” respectively. Besides, it discovered that under the contractual and relationship knowledge governance mechanisms’ guiding, participants in open innovation platforms may choose different knowledge searching and exchange ways according to their knowledge needs and thus trigger the different knowledge transform process. Then, “tacit knowledge socialization” transformation can show larger positive impact on breakthrough innovation, while “explicit knowledge combination” transformation makes larger impact on incremental innovation.

Artificial Intelligence (AI) has become an integral part of every business organisation across the world. It is a system designed to mimic human attributes such as speech, learning and problem-solving. It promotes cognitive functioning and can supplement and replace human workers in social, intellectual and professional contexts. AI serves as a versatile toolbox encompassing a range of technologies, including machine learning (ML), natural language processing, expert systems, neural networks, deep learning, robots and automation. These tools transform the business and marketing landscapes and infuse entertainment with innovation to boost consumer engagement. The growth of AI has set a new standard for what customers expect from businesses. AI provides companies with powerful tools to comprehend and meet customer expectations effectively. AI has given rise to diverse technologies, including robots, avatars, virtual bots and narrowcasting. The advent of AI-driven chatbots is revolutionising customer service by delivering instant responses, efficiently addressing queries and slashing wait times. This blend of AI and a customer-centric approach establishes the foundation for sustainable growth and enduring customer loyalty. This chapter will shed light on the present state of awareness regarding AI and ML and their impact on consumer engagement. We aim to illustrate how AI is utilised and its effects on the marketing landscape.

While extensive research exists on how positive life circumstances and positive personality traits promote entrepreneurship, there is little research focusing on how negative personal circumstances may potentially breed entrepreneurship. This study aims to build upon the theory of underdog entrepreneurship to examine the effect of challenging life circumstances such as poverty on the development of entrepreneurial traits in underdog entrepreneurs. This research analyzed the effect of risk-taking (RT) on the entrepreneurial success (ES) of underdog entrepreneurs and the role of optimism (OPM) and persistence (P) as mediating variables and poverty as a moderator variable.

A cross-sectional survey was conducted to collect data from 400 micro-finance borrowers of Akhuwat Foundation Pakistan. Akhuwat provides interest-free small loans to the poor segment of society. Preliminary testing of the survey questionnaire with a sample of 35 borrowers of Akhuwat Foundation in Lahore city was conducted before data collection. Data was collected from four randomly selected branches in Lahore city.

The authors found that OPM and P significantly mediate the relationship between RT and ES. In addition, the authors analyzed the moderating effect of poverty on the relationship between OPM and ES and found a negative moderating effect. A strong positive moderating effect of poverty was found on the relationship between P and ES. The results of multi-group analysis show that successful and unsuccessful underdog entrepreneurs differ in their RT propensity, which is significantly mediated by OPM and P.

This study provides empirical evidence on entrepreneurial traits and success of poor entrepreneur in an emerging economy. This work is original and has not been submitted elsewhere.

This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

This research aims at investigating how business process management capabilities (BPMC) impact the effectiveness of sustainable digital transformation (ESDT). Furthermore, it delves into the mediation of dynamic decision-making (DDM) in the relationship between BPMC and ESDT.

This research employed the hypothetico-deductive technique. The statistical database was generated from sample of 712 respondents from small and medium companies (SMEs) in Vietnam, utilizing convenience and snowball sampling methods. The two-step process utilizing structural equation modeling, supported by SmartPLS version 4.1.0.9 and AMOS 28, was employed to assess the measurement model, while SmartPLS version 4.1.0.9 was used to evaluate the structural model.

The results of the analysis emphasize significant and positive correlations between the proposed constructs related to significance and effect size. The statistical results indicated that BPMC had a significant and beneficial effect on ESDT. This relationship was partially mediated by DMM.

The salient point emphasized that practitioners should prioritize enhancing focus on BPMC and DDM, as this would significantly facilitate more comprehensive solutions, enabling SMEs to achieve optimal success in sustainable digital transformation. Policymakers and government influencers are urged to concentrate on innovative attributes and ensure a conducive environment for the implementation of innovation by enacting regulations that promote the application of digital technology.

The findings of this study will broaden scholars’ understanding of the influence of BPMC on ESDT. The originality of the research is to provide research directions for advancing studies on the role of DDM in the context of sustainable digital transformation.

The traditional information phase of value engineering (VE) workshops often involves face-to-face meetings and physical site visits, which can be time-consuming, costly and impractical due to various constraints. This paper introduces a web-based platform integrating BIM and GIS to streamline this phase by systematically gathering, processing and visualizing multi-format information in a virtual environment.

A comprehensive literature review was conducted to analyze the potential of BIM and GIS integration in the VE context. A three-step information structure generation method was employed to outline the information gathering needs during the VE workshops, incorporating a review of multi-source references. A framework including information gathering, processing and visualization was proposed to streamline the information phase with BIM and GIS integration as the core. Subsequently, a web-based prototype platform was developed utilizing the three-layer architecture, with the case study to demonstrate its application. A comprehensive evaluation involving black box testing, user interface testing and focus group discussion was conducted to validate the functionality, usability, potential and limitations.

The platform can support the systematic collection, processing, organization and visualization of multi-format information during the information phase, enable virtual meetings and virtual site visits and facilitate VE participants’ review, understanding and analysis of such information and the documentation of their comments and suggestions. The black box testing validated its functionality, with necessity, effectiveness and convenience confirmed by VE practitioners. Its potential was approved due to clear information structure, web-based virtual review and logical multi-format information organization.

The generalized four-category information structure and proposed three-layer framework streamline the information phase of VE practices. The developed platform allows the VE team to review multi-format information virtually, simultaneously, freely and as many times as necessary.

This study aims to explore how the seal face structure affects the gas flow and film performance, focusing on compliant foil face gas seal with an upstream pumping spiral gap. The research is done to reveal the leakage control mechanism and obtain the optimal parameters of structure.

A gas-elastic coupling lubrication model for compliant foil face gas seal is developed using gas lubrication and elastic mechanics theories. The finite difference method is applied to calculate film pressure, deformation and flow rate variations under varying gap spiral angles. What’s more, the impacts of equilibrium film thickness, rotational speed and medium pressure on sealing performances are researched, and the flexibility coefficients α₁ (dynamic pressure area) and α₂ (sealing area) are optimized.

This design significantly reduces leakage rates while maintaining the adaptive operation capability of compliant foil face gas seals. When α₁ takes values from 0.10 to 0.15, α₂ takes values from 0.5 to 0.6 and φ (gap spiral angle) is equal to 30°, the comprehensive performance of sealing in steady and transient states is better.

Integrating the design concept of upstream pumping dry gas seals and the adaptive structure of compliant foil face gas seals, a novel foil face gas seal structure with upstream pumping function is proposed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0434/

When handling small-sized shafts and holes, achieving optimal safety, size compatibility and shape adaptability using rigid grippers presents significant problems. Recent advancements have introduced soft end-effectors that offer enhanced safety and adaptability for gripping parts. However, these soft end-effectors often struggle to maintain the necessary gripping positional accuracy. The purpose of this paper is to design a soft end-effector specifically engineered to address these problems, combining precise gripping capabilities with improved safety, positional accuracy and adaptability to the size and shape of fragile, small-sized components.

A soft finger with multilayer decreasing drive air chambers is designed to achieve the finger bending increasing from the root to the tip of the finger to improve the flexibility of the fingertip. Additionally, a three-finger self-centering configuration is employed, coupled with an expandable structure to increase the gripping range. Furthermore, a theoretical mathematical model of the finger is established. The physical prototype is manufactured and subjected to experimental testing, including gripping tests on small-sized, fragile shaft holes, to validate its operational performance.

The grasping experiments confirm that the designed end-effector can maintain coaxial positioning and meet adaptability requirements when handling fragile components with small-sized shaft holes. Furthermore, the addition of expanding palm structure increases the gripping attitude and enriches the application scene and gripping space.

The design of multilayer decreasing air chamber structure to solve the problem of poor gripping stability and low positional accuracy of soft manipulator; the expandable palm design is introduced to enhance gripping space; and solved the problem of gripping accuracy in the assembly of fragile parts with small-size shafts and holes.