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This study aims to improve a construction company's overall project delivery by utilising lean six sigma (LSS) methods combined with building information modelling (BIM) to design, modularise and manufacture various building elements in a controlled factory environment off-site.

A case study in a construction company utilised lean six sigma (LSS) methodology and BIM to identify non-value add waste in the construction process and improve sustainability.

An Irish-based construction company manufacturing modular pipe racks for the pharmaceutical industry utilised LSS to optimise and standardise their off-site manufacturing (OSM) partners process and leverage BIM to design skids which could be manufactured offsite and transported easily with minimal on-site installation and rework required. Productivity was improved, waste was reduced, less energy was consumed, defects were reduced and the project schedule for completion was reduced.

The case study was carried out on one construction company and one construction product type. Further case studies would ensure more generalisability. However, the implementation was tested on a modular construction company, and the methods used indicate that the generic framework could be applied and customized to any offsite company.

This is one of the few studies on implementing offsite manufacturing (OSM) utilising LSS and BIM in an Irish construction company. The detailed quantitative benefits and cost savings calculations presented as well as the use of the LSM methods and BIM in designing an OSM process can be leveraged by other construction organisations to understand the benefits of OSM. This study can help demonstrate how LSS and BIM can aid the construction industry to be more environmentally friendly.

This chapter reviews Internet of Things (IoT) as a concept with bibliometric analysis using data selected from the Scopus database. The cited references included two clusters. Also, co-occurrence keyword analysis found four groups. The first cluster shows IoT adoption in agriculture, manufacturing, logistics, and supply chain management. The second cluster includes behavioral models of IoT technology acceptance. The third cluster refers to the adoption of IoT and automation technology in intelligent buildings, smart homes, smart cities, and health care. Finally, the fourth cluster contains information management.

A more accurate comprehension of data elements and the exploration of new laws governing contemporary data in both theoretical and practical domains constitute a significant research topic.

Based on the perspective of evolutionary economics, this paper re-examines economic history and existing literature to study the following: changes in the “connotation of production factors” in economics caused by the evolution of production factors; the economic paradoxes formed by data in the context of social production processes and business models, which traditional theoretical frameworks fail to solve; the disruptive innovation of classical theory of value by multiple theories of value determination and the conflicts between the data market monopoly as well as the resulting distribution of value and the real economic society. The research indicates that contemporary advancements in data have catalyzed transformative innovation within the field of economics.

The research indicates that contemporary advancements in data have catalyzed disruptive innovation in the field of economics.

This paper, grounded in academic research, identifies four novel issues arising from contemporary data that cannot be adequately addressed within the confines of the classical economic theoretical framework.

The purpose is to understand the factors affecting Chinese diet selections and propose strategies for revolutionizing Chinese diets toward healthy ones.

This study implemented an online discrete choice experiment to identify the factors affecting diet selections among urban Chinese consumers. Four different diet patterns were used to label each of the product alternatives in the experiment, which varied in taste and cost. Specifically, implying the healthiness and sustainability of a diet, the diet alternatives included the average diet, the Chinese Food Guide Pagoda diet, the EAT-Lancet diet and the Flexitarian diet. Using consumer data from six provincial capital cities, we used random parameter logit models to estimate their preferences.

Diet type and diet cost were found to be more important in urban Chinese consumers' diet selections than the ability to customize taste. The average diet, although not healthy and sustainable, was preferred most by respondents, signaling the challenges of shifting the consumer diet in China. Increasing the cost of the average diet can significantly promote sustainable healthy diet choices among urban Chinese residents. In other words, improving the affordability of sustainable healthy diets would have the potential to fuel the diet revolution in China.

Instead of choices of a single food item, this paper focused on the individual selection of a diet, where different food products can act as substitutes or as complements for one another. We also proposed a way to assess individual preferences and valuations for several different diets.

With recent advances in artificial intelligence, the hospitality industry has introduced the concept of unmanned smart hotels staffed by service robots instead of human employees. Research is needed to understand consumers’ receptivity to such an innovation. This paper examines factors associated with consumers’ potential resistance to using automated service hotels via two sequential studies. Given that younger generations of consumers are typically early adopters of advanced technology and innovative services, our sampling approach focused on this consumer group.

Two studies were conducted. Study 1 proposed and empirically tested a theoretical model. Results revealed that attitude, subjective norms and perceived behavioral control each positively influenced individuals’ intentions to use unmanned smart hotels. In Study 2, we further investigated aspects informing perceived security, a key variable in the use of unmanned smart hotels.

Findings showed how people’s beliefs about unmanned smart hotels and security control assurances led to perceived security. These perceptions were shaped by perceived physical risks, privacy concerns, website design and hotel reputation. Overall, this research provides theoretical and practical implications for various stakeholders associated with unmanned smart hotels.

Findings of this study suggested that managers of unmanned smart hotels should design user-friendly, secure processes and offer comprehensive support resources to enhance customer experience and usage.

The findings provide a holistic understanding of consumers’ receptivity to unmanned smart hotels.

The global COVID-19 epidemic has posed significant challenges to the development of innovation and entrepreneurship education in Chinese and foreign universities, and the application of artificial intelligence generated content (AIGC) technology has presented both opportunities and challenges to its development. The purpose of this study is to summarize advanced experiences and models of new engineering innovation and entrepreneurship education development in Chinese and foreign universities, as well as to analyze the influencing factors. Taking the sustainable development goals (SDGs) into account, this study qualitatively proposes enhancement paths and improvement suggestions based on the application of AIGC technology, providing a reference for promoting the sustainable development (SD) of innovation and entrepreneurship education in Chinese universities.

By using the qualitative comparative analysis (QCA), this paper studies the interaction mechanism between the influencing factors of innovation and entrepreneurship in universities under the background of SDGs. This paper selects 12 representative universities with different cultures and strengths. Meanwhile, this paper analyzes the content of 2,535 publications on innovation and entrepreneurship education and summarizes seven influencing factors as comparison criteria. Then, this paper codes, summarizes and uses configuration to assess the primary factors influencing the development of innovation and entrepreneurship in colleges and universities at home and abroad.

On the quality of new engineering innovation and entrepreneurship education, comprehensive, diverse influencing factors and upgrading paths are obtained. Furthermore, this research proposes that the SD of innovation and entrepreneurship education in universities should make effective use of “AI plus education” and actively construct practical and teaching platforms. Meanwhile, the ChatGPT is being used to strengthen the innovation and entrepreneurship curricular system and talent training mode. The research also makes recommendations for improving teachers’ ability to acquire intelligent tools and promotes three-way teaching modalities of “teacher-AI-student” by taking into account the influence of various aspects.

This research uses the QCA research method, which analyzes not only influencing factors on the SD of innovation and entrepreneurship education but also explores the interaction mechanisms among factors. Furthermore, the research incorporates SDGs and AIGC technology application scenarios into the field of domestic innovation and entrepreneurship education, which will be helpful in SDGs of innovation and entrepreneurship education on both theoretical and practical levels.

This paper aims to examine how bank stress tests affect bank tax planning.

The study uses US bank stress test bank size thresholds and a regression discontinuity design to investigate the effect of the Dodd-Frank Act and the instituted bank stress tests on bank tax planning. We use different measures of tax planning, including bank-specific measures and measures of tax avoidance, tax aggressiveness, and effective tax planning from recent literature. Our regression discontinuity and difference-in-differences regression analyses include bank and year fixed-effects and lagged bank characteristics to control for potential endogeneity.

This study finds that stress tests have the unintended consequences of intensifying tax planning and increasing tax avoidance. Stress-test banks increase tax avoidance by accelerating charge-offs, net interest, and non-interest expenses. However, this increase in tax planning is not optimally maximized, leading to lower effective tax planning compared to non-stress-test banks. Banks with a substantial increase in tax avoidance under the Dodd–Frank Act tend to increase their risk, investing in high-risk-weight assets and lending in riskier loan categories. These findings are consistent with tax minimization conditions under added regulatory attention and policy uncertainty.

Literature on bank tax planning is limited. Most tax avoidance literature excludes financial institutions such as bank holding companies mainly due to differences in business practices and regulatory frameworks. This study is the first to investigate tax planning behavior among US banks. The current study thus extends the research field by examining the effect of bank transparency regulations, such as bank stress tests, on bank tax planning activities. Our findings have a direct bank policy implication. They show that stress testing has the unintended consequences of increasing tax planning activities and consequently increasing risk-taking on banks with high tax avoidance, which goes against the goals of stress testing regulations.

Considering both the current opportunities of the Internet of things (IoT) and aviation, as well as the potential opportunities they may offer for the future, it is understood that they are among the important issues that need to be examined in the literature. This study aims to provide an idea by conducting bibliometric and visualization analyses of the current trends and development opportunities of IoT and aviation.

In this study, descriptive and bibliometric analyses within the framework of co-author, co-citation, bibliographic coupling, and keyword co-occurrence analysis were carried out for publications found to be published between 2007 and 2023 in the Web of Science (WoS) database related to IoT and aviation. VOSviewer (ver. 1.6.18) program and the Biblioshiny application were used to create bibliometric networks and provide visualization.

As a result of some descriptive and visualization analyses, the current trend of publications on IoT and aviation and future publication opportunities has been revealed. It has been understood that the subject of IoT and aviation is one of the subjects whose number of publications has increased in recent years and has not yet fully matured in terms of the number of publications and has the potential to make new publications.

In this study, bibliometric analysis of IoT and aviation, which could not be found examined before in the literature, and the creation of existing bibliometric networks by visualizing were carried out.

The study aims to develop and test a supply chain wide green product development framework of focal firms and their major suppliers, in the context of the Chinese automotive industry.

An in-depth case studies approach is adopted for this study. Three automotive sector upstream supply chains involving 17 firms and 51 experts as respondents were interviewed on the importance and implementation effectiveness of 6Rs (reduce, redesign, recover, remanufacture, reuse and recycle) across the manufacturer and their respective tier 1 and tier 2 suppliers.

The results indicate that the Chinese automotive sector supply chains are mainly focused on “reduce” practices with immediate environmental and economic benefits. The investigated firms however had future implementation plans for “redesign” and “recovery” practices to become comprehensive in green product development (GPD).

The study facilitates automotive firms, industry policymakers and researchers the understanding of incorporating comprehensive GSCM practices across the upstream supply chain to achieve circularity. The study focused on upstream supply chain due to the concentration of major production practices in this section of the supply chain. However, the downstream supply chain equally deserve attention as well as the need to understand the mediating and moderating roles of the different Rs to tease out the pros and cons of achieving overall environmental sustainability.

There are very limited studies on comprehensive GPD for achieving optimal GSCM and sustainability. By simultaneous looking at a focal firm and its upstream supply chains GSCM practices, this study addresses a system-wide comprehensive GPD issues from implementation of 6Rs perspectives in the supply chain.

A section of in-service PE gas pipeline in Guocun, Beijing, was found to appear gas leaking at the electrofusion (EF) joint. This study is dedicated to reveal the material cause of EF joint failure to help with a more accurate prediction of service life of PE gas pipe and further normalize the construction of PE gas pipeline.

Defect detection was carried out on the leaking EF joint using ultrasonic phased array. The mechanical degradation and structural aging behavior was studied by tension test, FTIR technology, TG test and DSC test. The organic components in the soil surrounding the PE gas pipe failure area were qualitatively identified.

The results showed that the organic surfactants in the soil environment could accelerate the aging behavior of PE material, leading to a deterioration of mechanical properties and a serious reduction in the ability of the PE pipe and EF joint, especially at the welding defect, to resist external force.

A novel study was conducted to investigate the failure cause of the EF joint of in-service PE gas pipe, incorporating the analysis of environmental factors and structural deterioration.