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Limited geometric accuracy is one of the major challenges that hinder the wider application of additive manufacturing (AM). This paper aims to predict in-plane shape deviation for online inspection and compensation to prevent error accumulation and improve shape fidelity in AM.

A sequence-to-sequence model with an attention mechanism (Seq2Seq+Attention) is proposed and implemented to predict subsequent layers or the occluded toolpath deviations after the multiresolution alignment. A shape compensation plan can be performed for the large deviation predicted.

The proposed Seq2Seq+Attention model is able to provide consistent prediction accuracy. The compensation plan proposed based on the predicted deviation can significantly improve the printing fidelity for those layers detected with large deviations.

Based on the experiments conducted on the knee joint samples, the proposed method outperforms the other three machine learning methods for both subsequent layer and occluded toolpath deviation prediction.

This work fills a research gap for predicting in-plane deviation not only for subsequent layers but also for occluded paths due to the missing scanning measurements. It is also combined with the multiresolution alignment and change point detection to determine the necessity of a compensation plan with updated G-code.

The purpose of this paper is to examine the implications of the COVID-19 pandemic on internal auditing as the pandemic forced individual internal auditors and audit teams to conduct the work remotely.

Five in-depth semi-structured interviews of internal audit experts that work in German retail and manufacturing industry were conducted between February and April 2021.

The authors find that the importance of audit technologies did not change significantly due to the pandemic, as audit technologies were already an integral part of internal audits. Interestingly, the transition to remote audits occurred with remarkable speed and efficiency. The presence of well-functioning information and communication technologies emerges as a critical facilitator for effective remote communication, collaboration and data exchange. However, audit technologies can only partially replace physical on-site examinations and human interaction. The main challenges of remote audits are related to the auditing of non-digitalized processes and the inherent limitations of auditee interviews and interactions.

The authors' interview approach does not allow to cover variations between industries and between countries. While internal audit experts provided notably consistent responses during the interviews, acknowledging that the sample size is very small is important.

The COVID-19 pandemic serves as a catalyst for increased digitalization and technology adoption within the realm of internal auditing. A hybrid approach combining the benefits of on-site and remote audits is expected to prevail in the future.

The paper is among the first to document the effects of the COVID-19 pandemic on the work of internal auditing using field-based research methods.

From the signaling theory perspective, the current study explores various drivers of brand transparency and its effect on users' interactions with food delivery apps.

First, a set of precursors of brand transparency of food delivery apps from focus group discussions was identified. Next, an integrated model tests the impact of brand transparency, perceived risk and brand trust on users' ordering frequency. Data collected from 522 users were analyzed using the partial least squares structural equation modeling method.

The outcomes showed the effectiveness of brand communications as the strongest indicator of brand transparency. Moreover, brand transparency favorably influences users' brand trust and ordering intention and negatively influences perceived risk. Hygiene rating attenuates the adverse effects of perceived risk.

The current study is a pioneering attempt that offers ways for online food delivery providers to build brand transparency, lessen users' risk perceptions and foster greater use of apps in the post-pandemic scenario.

We challenge the conventional approach to distinguish between professional and non-professional Airbnb hosts by solely using the number of managed listings.

We leverage the recently released platform policy that categorizes hosts' professionalism by their self-declared status. Our multinomial modeling approach predicts true host status, factoring in the number of managed listings and controlling for listing and host traits. We employ data from five major European cities collected through scraping the Airbnb webpage.

Our research reveals that relying solely on the number of listings managed falls short of accurately predicting the host type, leading to difficulties in evaluating the platform's impact on the local housing market and reducing the effectiveness of policy intervention. Moreover, we advocate using more fine-grained measures to differentiate further between semi-professional and professional hosts who exhibit heterogeneous economic behaviors.

Reliable professionalism metrics are essential to curb unethical practices, promote market transparency and ensure a level playing field for all market participants.

This work pioneers the revelation of the inadequacy of a commonly used measure for predicting host professionalism accurately.

In this paper, the authors take the central environmental protection inspection (CEPI) as an exogenous shock to study the reaction of the stock market in China. Using the event study method, the authors check how the first round of the first batch of CEPI supervision affects the cumulative abnormal return (CAR) of the listed firms on the Shenzhen or Shanghai stock exchange. This paper aims to discuss the aforementioned objective.

In this paper, the authors take the first round of the first batch of CEPI supervision as a clean exogenous shock to study its effects on the capital market. The authors collect daily trading data from the China stock market and accounting research (CSMAR) database, with the sample containing 1,950 Chinese firms listed on either the Shenzhen or Shanghai stock exchanges. And detailed information on CEPI supervision is obtained from the official website of the Ministry of Ecology and Environment of the People's Republic of China. The event study method is adopted to analyze the reaction of the stock market under CEPI supervision. Specifically, the authors constructed the cumulative abnormal return of each firm around the event day of CEPI. To capture the deterrent effects of CEPI supervision, the authors examine the situation of polluting and non-polluting firms in the supervised provinces, adjacent provinces and provinces that are not supervised or close to the supervised provinces, respectively.

This paper throws light on the following: (1) the polluting firms in the supervised provinces were negatively impacted by CEPI within 20 trading days of the event day, and its effects spread to the polluting firms in the neighboring provinces; (2) CEPI had a favorable impact on the non-polluting businesses in the provinces that are neither supervised nor close to the supervised provinces. The authors contend that it is because the investment is being forced out of the polluting sector and into the non-polluting sector, which is more pronounced in the provinces not directly or indirectly targeted by CEPI; (3) by comparison, the “looking back monitoring of the first round” has had no discernible detrimental impact on the firms' CAR, indicating an important role of psychology anticipation of investors in the stock market performance; (4) although not physically located in the supervised provinces, the downstream enterprises of the polluting firms suffer significantly from CEPI shock; (5) the effectiveness of CEPI supervision in the supervised provinces depends on the level of local environmental regulation and the ownership structure of the company. Private firms in the provinces with stronger environmental regulations suffer more from the CEPI shock; (6) the multivariate analysis shows that while enterprises with high ROE and financial leverage may be at risk of CAR loss, older, larger firms are less likely to experience CEPI shock; (7) the study of persistent effect reveals that the strike of CEPI supervision can last for at least 10 months after the event day and deterrent effect can be spread within the whole polluting industry.

In this paper, the authors only concentrate on the market reaction within 20 trading days after the event day. An analysis of long-term effects should be valuable to get a deeper knowledge of the capital market reaction to the CEPI policy. In addition, the paper only focuses on the first round of the first batch of CEPI. Since CEPI has been built as a constant regulation of local environmental performance, further study may need to track both the reaction of listed firms and investment behavior in the capital market.

Policy implications of the paper are as follows: First, for the policymakers, it is important to construct a constant environmental regulation system instead of a campaign movement. Second, for investors, as environmental issues are receiving increasing attention from both the government and the public, investment decisions should take into account firms' environmental performance, which can help reduce the risk from environmental regulations. Third, the firms in the polluting industry should take more action to reduce pollutant releases and adopt green technology, which is essential for sustainable development under environmental protection.

This paper contributes to the existing literature in the following aspects. First, the authors provide new evidence on the effects of environmental regulations as a shock to the stock market, which has been wildly concentrated in the literature about environmental policies evaluation and capital market reaction. Second, the authors supplement the literature on green finance and sustainability transformation, which has got increasing attention in recent years. Theoretically, by guiding investment and affecting the stock market performance, environmental regulations are considered to be an efficient way to stimulate polluting firms to transform into green development. The results of the paper support this intuition by showing that the CAR of the non-polluting firms in non-supervised provinces in fact benefit from the CEPI supervision.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

This paper aims to realize an in-situ quality inspection system rapidly for new injection molding (IM) tasks via transfer learning (TL) approach and automation technology.

The proposed in-situ quality inspection system consists of an injection machine, USB camera, programmable logic controller and personal computer, interconnected via OPC or USB communication interfaces. This configuration enables seamless automation of the IM process, real-time quality inspection and automated decision-making. In addition, a MobileNet-based deep learning (DL) model is proposed for quality inspection of injection parts, fine-tuned using the TL approach.

Using the TL approach, the MobileNet-based DL model demonstrates exceptional performance, achieving validation accuracy of 99.1% with the utilization of merely 50 images per category. Its detection speed and accuracy surpass those of DenseNet121-based, VGG16-based, ResNet50-based and Xception-based convolutional neural networks. Further evaluation using a random data set of 120 images, as assessed through the confusion matrix, attests to an accuracy rate of 96.67%.

The proposed MobileNet-based DL model achieves higher accuracy with less resource consumption using the TL approach. It is integrated with automation technologies to build the in-situ quality inspection system of injection parts, which improves the cost-efficiency by facilitating the acquisition and labeling of task-specific images, enabling automatic defect detection and decision-making online, thus holding profound significance for the IM industry and its pursuit of enhanced quality inspection measures.

This paper analyses the establishment and evolution of a public oversight body (POB) – the Egyptian Audit Oversight Unit (AOU) – and its implications for local auditing firms and practices.

Primary data were gathered from 34 semi-structured interviews (including follow-up ones) between 2014 and 2020. Secondary data was obtained through publicly available documents and internal memos. Drawing on Debord's (1967) Society of the Spectacle, the insights focus on the POB's conception, materialisation and evolution in a context characterised by weak regulatory structures.

Through a series of acts, the findings reveal how the AOU first accepted the image of “international best practice” oversight (the “metaphorical”), followed by the construction of the local structure and décor replicating a United States (US) style POB archetype (the “transformational”) by primarily relying on visible processes/procedures. Yet, these mechanisms emphasised the spectacular nature of oversight, with little improvement for practice and limiting itself to “cracking down” on smaller local firms. A final stage (the “performative”) reveals how the AOU seeks to expand its activities beyond its original mandate without challenging the image-driven nature of its oversight.

The paper offers two key contributions. First, it reveals how actors, through a combination of symbolic and tangible measures, create a new performative reality of public oversight. Second, it advocates Debord's “spectacle” to complement other theoretical lenses, with a view to illuminating the materialisation stages that bridge the gap between proclaimed oversight policies and actual practices (including conscious and unconscious omissions) within a given political economy context.

The 2008 Chinese melamine milk scandal resulted in six reported fatalities and affected around 300,000 children, of whom 54,000 were hospitalised. Previous studies have used linear approaches to examine the root causes of the melamine milk scandal.

In the present study, we applied a systems approach to the melamine milk scandal to identify the complex systems-level failures across the supply chain leading to the incident and why food fraud incidents such as this occurred in the dairy sector. Additionally, systemic failures associated with food fraud vulnerability factors were considered (i.e. opportunities, motivation and control measures).

48 contributory factors of influence were identified and grouped across six sociotechnical levels across the Chinese dairy system, from government to equipment and surroundings. Lack of vertical integration (processes and communication) contributed to the failure. When viewed from a broader perspective, the melamine milk scandal can be linked to a series of human errors and organisational issues associated with government bodies, the dairy supply chain, individual organisations and management decisions and individual actions of staff or processes.

This approach is of value to policymakers and the industry as it supports public health investigations of food fraud incidents and proactive food safety management.

To the best of our knowledge, this is the first study to analyse a food safety or fraud incident using the AcciMap approach and the food fraud vulnerability assessment (FFVA) technique. AcciMap analysis is applied to both unintentional and intentional aspects of the incident.

The construction of geographical indications agri-food (GIAF) brands play an important role in rural revitalization in China, this study aims to explore how to jointly promote brand building among multiple parties.

A tripartite game model of the producers, sales operating enterprises, and local governments is constructed to analyze the strategy choice of the parties in the complex system behavior evolution stability, and the simulation analysis of the influence factors of brand construction of GIAF and verify the game result.

(1) Increased government subsidies and supervision costs are beneficial to accelerating variety improvement and quality improvement of agri-food, but it is not conducive to the government, Therefore, it is necessary to ensure that the subsidy and supervision cost is kept within a reasonable range; (2) The dividend distributed to producers by sales operating enterprises play an important role in encouraging producers to improve the quality safety of agri-food, but it must be kept within a reasonable range to avoid discouraging the enthusiasm of sales operating enterprises; (3) Cost reduction, and revenue improvement are also effective ways to cooperate with all parties in brand co-construction.

This study does not consider consumers or logistics companies in the evolutionary game model.

This study proposes innovative policies and suggestions for improvement of the brand co-construction of all parties.

Based on the “Rural Revitalization” initiative, this study enriches research methods about brand value and provides a new perspective for brand value co-construction, and theoretical guidance, and empirical basis for formulating innovation policies and recommendations.