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This study aims to understand independence in internal auditing by investigating how internal auditor independence is constructed when analysed in its corporate governance context.

A critical discourse analysis (CDA) of the corporate governance reports of Swedish large stock market listed non-financial companies, for three consecutive years, is undertaken, using a theoretical lens of organisational embeddedness and operational coupling to understand independence as a situated practice.

The study develops four archetypes of internal auditor independence – autarchic, instrumental, symbiotic and subservient – and discusses each archetype's implications for independence, related to tripartite relations with management and the audit committee, regarding who has the mandate to direct work and how the work is done. It finds that internal auditors always have a capacity to be independent. Although they are not independent in relation to agents in the subservient archetype, they are independent of those down the organisational chain of command, suggesting independence is both situational and relational.

The analysis contributes a novel approach to the literature and develops a conception of independence using the dimensions of embeddedness and coupling. The archetypes offer an analytical framework for future studies on independence.

Internal auditors may understand their practice differently through the archetypes that result from this study.

Internal auditors' power relations within corporate governance further an understanding of the pressures on internal auditors and their role.

This study contributes new knowledge on the situatedness of independence by showing how internal auditors are embedded and coupled helps build their independence.

Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.

In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.

We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.

A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.

By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

The purpose of this paper is to examine the nuanced effects of downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. Intelligent manufacturing is considered to clarify their boundary conditions.

The ordinary least squares regression was conducted, based on the data collected from 136 high-tech firms in China.

Horizontal downstream complexity has a positive effect on supply chain resilience significantly, while the negative impact of vertical downstream complexity on supply chain resilience is not significant. Contingently, intelligent manufacturing plays a negative moderating role in the relationship between horizontal downstream complexity and supply chain resilience, while it positively moderates the relationship between vertical downstream complexity and supply chain resilience.

This study disentangles the nuanced effects of both horizontal and vertical downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. It also clarifies their boundary conditions by considering the focal firm's intelligent manufacturing level as the contingent factor.

In this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.

The presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.

The authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

To be able to continuously provide affordable services to consumers, managers of critical infrastructure (CI) maintenance supply networks have to balance investments in resilience with costs. At the same time, CI providers need to consider factors that influence resilience such as the geographical spread or the location of the network. This study aims to contextualize supply chain resilience knowledge by exploring how maintenance resource configurations impact resilience and costs in CI supply networks.

An in-depth longitudinal single case study of a representative CI provider that has centralized its maintenance supply network is used. Data were collected before and after the change to evaluate the effect of the changes on the maintenance supply network.

This study shows that in this specific CI maintenance context, structural resource choices such as the quantity or location of spare parts and tools, the creation and exploitation of tacit knowledge and staff motivation impact both resilience and costs due to geographical spread, network location and other network properties.

This study extends general supply chain resilience knowledge to a new setting (i.e. CI) and shows how existing insights apply in this context. More specifically, it is shown that even in engineered supply networks there is a need to consider the effect of human agency on resilience as the creation and exploitation of tacit knowledge are of immense importance in managing the network. In addition, the relationship between normal accidents theory and high reliability theory (HRT) is revisited as findings indicate that HRT is also important after a disruption has taken place.

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.

In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.

Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.

In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.

This study aims to demonstrate how governmental authorities can take interorganizational network responses to address unexpected situations developed by the breakdown of critical infrastructure, such as communication failure in a hyperconnected society.

This study uses social network analysis to investigate the performance of interorganizational response networks regarding the 2018 KT network blackout, a failure of telecommunication facility, compared to the planned network.

The national fire agency was the most prominent actor in the actual interorganizational network, while the actor was not significant in the planned network in addressing unexpected needs. Moreover, top government authorities were involved in the actual response network because of the national attention on the breakdown of the infrastructure as a focusing event.

Unexpected conditions in the actual response to a technological disaster, such as a critical infrastructure (CI) breakdown, require the involvement of emerging or non-significant actors in accordance with the findings related to other types of disasters. Particularly, communication failure in a hyperconnected society may involve prominent government authorities in the actual interorganizational response because of the event's broad and severe impact on the functions of society.

This study aims to extend ambidexterity theory from the perspective of organisational learning and examine how process ambidexterity, which comprises operational flexibility and operational routine, responds to environmental uncertainty and ultimately reduces organisational risks.

This study tests the hypotheses by analysing 464 annual reports of 115 listed companies in the Chinese agricultural and food industry using content and secondary data analyses. Four case studies are also provided.

The results show that (1) environmental uncertainty has a positive effect on either operational flexibility or operational routine; (2) both operational flexibility and operational routine have negative effects on organisational risks, supporting the view that process ambidexterity mediates the relationship between environmental uncertainty and organisational risks; and (3) organisational slack plays the role of “double-edged sword” by negatively moderating the effect of environmental uncertainty on operational flexibility and positively moderating the effect of environmental uncertainty on operational routine.

In an uncertain environment, companies are exposed to greater risk. This study contributes to risk management in three ways: first, it extends ambidexterity theory to process management and proposes how process ambidexterity balances operational flexibility and routines. Second, it distinguishes between the different conditions under which flexibility or routines are superior. Third, it explains the mechanisms related to how organisations can resolve environmental uncertainty into risk through process ambidexterity.

Economy-wide crises create major challenges for small and medium enterprises (SMEs). Existing studies emphasize the crucial role of contrasting behavioral strategies, effectuation and causation in SMEs' adaptation to crisis conditions. Yet, prior literature concentrated predominantly on exploring the impact of effectuation and causation on firm performance rather than survival. The authors present and empirically test a theoretical model explaining how behavioral strategies affect SME survival during an economy-wide crisis under different levels of environmental dynamism.

The authors propose a theoretical framework based on the combination of the effectuation literature and the emerging variance-based perspective on entrepreneurial actions. The theoretical model is then tested using a sample of Russian SMEs during a period of economic adversity and recovery (2015–2019).

The empirical results reveal that causation reduces the probability of firm survival in dynamic environments, while effectuation increases the chance of survival irrespective of the state of the environment. In a nutshell, the study provides evidence that the effectuation logic serves a viable way for SMEs to increase the chances of survival through the economic shock and subsequent recovery period.

For the first time in the literature, the authors demonstrate the role of behavioral strategy (effectual and causal) as a crucial antecedent of SME survival in the short and medium term, particularly during an economy-wide downturn. Furthermore, the study demonstrates the power of variability-based theorizing for explaining and predicting the survival/failure implications of entrepreneurial actions.