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This paper examines the relationship between transport connectivity and regional economic development in China. It develops measurements appropriate for transport connectivity based on a set of evaluation models. This model is used to analyze the logistic connectivity of China’s 31 provinces by focusing on 11 variables, including some new factors (Density of road network, Density of railway network, Number of Internet Users) not used in previous studies, over the 13-year period from 2002 to 2014. Using panel data regression analysis, the empirical results show a statistically significant and positive impact of transport connectivity (factors like Density of road network, Density of railway network and Number of Internet Users) on economic development in China. In particular, the Number of internet users is a key factor reflecting information connectivity in all the variables. Comparative analysis regarding economic development is conducted to benchmark between coastal provinces and interior provinces. Like most previous research, this study yields the same finding of higher impact of transport connectivity on economic development in eastern provinces than in western provinces. This study suggests that decentralized decision-making will be significantly more efficient for analyzing regional infrastructure development. It also shows that the influence of transport connectivity on economic development is dependent on a certain developmental stage. This suggests that an economic region should adopt different development strategies for transport connectivity during different stages of development.

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 reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

With the accelerated technological advancement, innovation has become a critical factor, which affects the core competitiveness of a company. However, studies about the relationship between internal stock option mechanisms and innovation productivity remain limited. Therefore, this paper aims to examine the impact of stock options and their elements design on innovation output from an internal mechanism perspective.

Using a sample of 302 stock option incentive plans announced and implemented between 2006 and 2016, this study uses the propensity score matching and difference-in-difference model to find out whether the implementation of stock options improves the innovation outputs of enterprises.

Based on the statistical analysis, it is concluded that: stock options can stimulate corporate innovation; a stock option may drive innovation outputs through two ways, performance-based incentives and risk-taking incentives, with the latter one playing a more dominant role and the risk-taking incentives of stock options, could be optimised when the non-executives granting proportion is larger, the granting range is limited, the incentive period is longer, the exercisable proportion is increasing, the price-to-strike ratio is lower and relatively loose performance assessment criteria are applied.

The conclusion reached in the study may provide valuable information to listed firms in designing and implementing the stock option plans.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.

This paper aims to investigate the effect of voluntary non-financial reporting on the evaluation of audit risk from the auditors’ viewpoint in a post-crisis period. Furthermore, this paper analyses whether auditors perceive that voluntary non-financial reporting impacts audit risk differently for old clients as compared with new clients.

This study is conducted on a sample of Italian audit firms through a paper-based questionnaire. Both Big4 and non-Big4 audit firms have been included in the sample.

Results show that integrated reporting is perceived to be the most relevant reporting method and intellectual capital statement the least relevant. Surprisingly, empirical findings over the sample period show that auditors do not perceive statistically significant differences between old and new clients.

Auditors can identify opportunities to adapt their assessment model to include voluntary non-financial report information. Moreover, they can use different assessment models regarding the research variables in the case of new and old clients.

Empirical findings highlight the growing role of voluntary non-financial reporting in the auditors’ perception of their client’s audit risk. All the observed voluntary non-financial reporting forms, except for intellectual capital, are considered as relevant by auditors in the evaluation of their client’s audit risk when compared to an indifference point. In addition, findings reveal that female auditors perceive a reduced gap in the relevance between integrated reports and intellectual capital reports compared to their counterparts.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

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.