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Algorithmic monitoring has been widely applied to the practice of platform economy as a management means. Despite its benefits, negative effects of algorithmic monitoring are gradually emerging.

Based on moral disengagement theory, this research aims to investigate how algorithmic monitoring might affect gig workers’ attitudes and behaviors. Specifically, we explored the effect of algorithmic monitoring on gig workers’ unethical behavior. A three-wave survey was conducted online, and the sample consisted of 318 responses from Chinese gig workers.

The results revealed that algorithmic monitoring positively affected unethical behavior through displacement of responsibility, and the individualistic orientation of gig workers moderated this relationship. However, the relationship between moral justification and algorithmic monitoring was not significant.

This research contributes to the algorithmic monitoring literature and examines its impact on gig workers’ unethical behavior. By revealing the underlying mechanism and boundary conditions, this research furthers our understanding of the negative influences of algorithmic monitoring and provides practical implications.

This article aims to answer two research questions that remain controversial in the accounting and corporate governance literature: (1) how corporate disclosure is related to board monitoring and (2) how this link is affected by the institutional environment and firm-level governance.

The study is based on S&P data on corporate disclosure by Russian companies collected over 2002–2010 and supplemented by information from the SKRIN database. The dataset covers 125 non-financial companies, with 559 observations in total. We use three indicators of board monitoring: the percentage of non-executive directors, a dummy for two-tier boards, and a dummy for an audit committee. The firm’s governance is proxied by a dummy for single class stock, while the institutional environment is proxied by a dummy for ADRs/GDRs. We apply conventional methods of panel data analysis with several robustness checks, including the random- and fixed-effects models, 2SLS that addresses the potential endogeneity of board composition, alternative definitions of the dependent variable, and an extended list of controls.

We find a positive (complementary) relationship between the amount of disclosure and the proxies for board monitoring employed. This complementary relationship turns out to be the strongest among companies that have better internal governance but face a weaker institutional environment. There is little evidence of such complementarity under strong institutions.

The findings may be of interest to investors and policymakers. As to the former, the results warn of firms that provide limited disclosure in the presence of strong corporate governance arrangements, such as independent boards, as these factors are not substitutes for each other. As to the latter, the results support comprehensive policies aimed at simultaneous improvements in both board governance and corporate disclosure in weak institutional settings.

This paper uses a unique setting and rich, partly proprietary data to extend the existing literature on the relationship between corporate disclosure and board monitoring, with an emphasis on the moderating role of the institutional environment and firm-level governance. It is also one of the very few studies of corporate disclosure in Russia, an important emerging economy of the early 2000s.

The purpose of the paper is to propose a novel approach, based on grey clustering decision, to fill in an omission of quantitative monitoring parameter selection methods.

The basic monitoring parameter selection criteria and the corresponding calculation methods are presented. Then, the grey clustering decision model for monitoring parameter optimization selection is constructed, and an integrated weight determination method based on analytic hierarchy process (AHP) and information entropy is provided.

Basic principle for monitoring parameter selection is proposed and quantitative description is carried out for selection principle in engineering application. Grey clustering decision‐making model for monitoring parameter optimization selection is established. Comprehensive weight ascertainment method based on AHP and information entropy is provided to make the index weight more scientific.

At system design stage, it is of significance to carry out selection and optimization of monitoring parameters. After the optimization of monitoring parameters is confirmed, measurability analysis and design in parallel are carried out for convenience of timely information feedback and system design revision. Therefore, the system integration efficiency is improved and the cost of research and manufacturing is reduced.

Monitoring parameter optimization selection process based on grey clustering decision‐making model is described and the analysis result shows that the proposed method has certain degree of effectiveness, rationality and universality.

The purpose of this article is to suggest that Fraby‐Perot optic sensor is a practical measurement gage to monitor the strain of great structures such as railway bridges.

A remote strain monitoring system based on F‐P optic fiber and virtual instrument is designed to monitor the strains of a railway bridge.

The application results show that the Fraby‐Perot optical fiber sensors can accurately measure strain and they are suitable for the long‐term and automatic monitoring. In addition, the system has several advantages over conventional structural instruments including fast response, ability of both static and dynamic monitoring, absolute measurement, immunity to interferences such as lightning strikes, electromagnetic noise and radio frequency, low attenuation of light signals in long fiber optic cables.

Health monitoring of structures is getting more and more recognition all over the world because it can minimize the cost of reparation and maintenance and ensure the safety of structures. A strain monitoring system based on F‐P optic fiber sensor was developed according to the health monitoring requirements of Wuhu Yangtze River Railway Bridge, which is the first cable‐stayed bridge with a maximum span of 312 m carrying both railway and highway traffic in China. It has run stably in the monitoring field more than two years and fulfilled the monitoring requirement very well. Now the system has been transplanted successfully to the Zhengzhou Yellow Railway Bridge for strain monitoring. So the work can be referenced by other similar health monitoring projects.

Long‐term, real‐time monitoring of strain using FP fiber optic sensors in railway bridge is an innovation. A remote strain data acquisition and real‐time processing are another character of the system. The work studied can be referenced by other structures monitoring, such as tunnel, concrete bridges, concrete and earth dams.

Corrosion monitoring techniques fall broadly into two categories: those which provide simple numeric data for control purposes, and those which offer a spectrum of information for diagnostic purposes. Corrosion monitoring can be carried out directly at locations susceptible to corrosion, or indirectly under conditions simulating susceptible but inaccessible points. The interpretation of the data can reflect the purpose of monitoring at the particular location. A consistent form of presentation, and comparative tabulation including statistical analysis can greatly facilitate correlation and trend spotting. Broad spectrum techniques may give an early indication of new problems. An effective internal corrosion monitoring programme can make a major contribution towards the control of plant operating costs.

The purpose of this paper is to review the recent advancements in the development of wearable sensors which can continuously monitor critical medical, assess athletic activity, watch babies and serve industrial applications.

The paper presents an in-depth review of a number of developments in wearable sensing and monitoring technologies for medical, athletic and industrial applications. Researchers and companies around the world were contacted to discuss their direction and progress in this field of medical condition and industrial monitoring, as well as discussions with medical personnel on the perceived benefits of such technology.

Dramatic progress is being made in continuous monitoring of many important body functions that indicate critical medical conditions that can be life-threatening, contribute to blindness or access activity. In the industrial arena, wearable devices bring remote monitoring to a new level.

Doctors will be able to replace one-off tests with continuous monitoring that provides a much better continuous real-time “view” into the patient’s conditions. Wearable monitors will help provide much better medical care in the future. Industrial managers and others will be able to monitor and supervise remotely.

An expert insight into advancements in medical condition monitoring that replaces the one-time “finger prick” type testing only performed in the doctor’s office. It is also a look at how wearable monitoring is greatly improved and serving athletics, the industry and parents.

This study aims to analyze the dynamic monitoring of deformation damage of steel structure buildings in long-term use. Although the steel structure building has the advantage of high structural strength, it will be deformed after being affected by factors such as corrosion and impact during long-term use, and which will affect building safety, especially the public building facilities. The dynamic monitoring of its security is an indispensable means.

This paper briefly introduced the principle of building information modeling (BIM)-based steel structure building information monitoring and the dynamic information monitoring system based on this principle. Then the monitoring system was used to analyze an operational steel structure suspension bridge in Xinxiang City, Henan Province, China, and compared it with the monitoring system based on back propagation (BP) neural network.

The results showed that the fitting degree of the dynamic deformation displacement data processed by BIM-based monitoring system was higher than that processed by BP-based monitoring system. Based on the comprehensive comparison of the dynamic data of all monitoring points, the BIM-based monitoring system had higher accuracy of deformation displacement monitoring and reliability of structural safety evaluation.

In summary, the BIM-based steel structure building monitoring system can effectively monitor the dynamic information of steel structure information.

This paper aims to illustrate the main changes during martial law for conducting financial intelligence (monitoring), in particular, in the system of combating legalisation (laundering) of illegally gained income.

The research methodology includes general scientific methods of cognition. The authors used it to research the theoretical, organisational and legal aspects of financial intelligence (monitoring) in normal situations and during martial law. The authors also use the doctrinal legal research method to analyse and describe the legislation connected to the financial intelligence (monitoring) during martial laws.

This paper is an original work written by authors that discusses financial intelligence (monitoring) during martial law. The following changes in the conduction of financial intelligence (monitoring) were highlighted: suspension of scheduled and unscheduled on-site inspections; postponement of the entry into force of the provisions of some regulations on the submission of reports in electronic form; and the norms amending to remove administrative barriers in matters of financial intelligence (monitoring) in martial law. The authors also noted that certain rules for the functioning of the financial intelligence (monitoring) system were being clarified. Thus, the financial intelligence (monitoring) regime is being weakened to some extent.

In connection with the introduction of martial law in the territory of Ukraine on 24 February 2022, the most important changes that have taken place in the banking and financial sectors of the economy should be mentioned. In particular, this applies to the issues of the regulation on the statutory and regulatory levels. Certain vital points regarding the mechanism and procedures for conducting financial intelligence (monitoring) also needed to be changed, on a need-to-know basis to adapt to the needs of Ukrainian society during the military aggression of the Russian Federation. This paper is devoted to the study of financial intelligence (monitoring) during martial law. The authors identified the main changes in the procedure for conducting financial intelligence (monitoring) by both the National Bank of Ukraine (one of the main entities) and the legislator (by amending the current regulatory framework).

Distributed photovoltaic (DPV) projects generally have output risks, and the production effort of the supplier is often private information, so the buyer needs to design the optimal procurement contract to maximise its procurement utility.

Based on the principal-agent theory, we design optimal procurement contracts for DPV projects with fixed payments and incentive factors under three situations, i.e. symmetry information, asymmetry information without monitoring and asymmetry information with monitoring. We obtain the optimal production effort and expected utility of the supplier, the expected output and expected utility of the buyer and analyse the value of the information and monitoring.

The results show that under asymmetric information without monitoring, risk-averse suppliers need to take some risk due to output risk, which reduces the optimal production effort of the supplier and the expected output and expected utility of the buyer. Therefore, when the monitoring cost is below a certain threshold value, the buyer can introduce a procurement contract with monitoring to address the asymmetry information. In addition, under asymmetric information without monitoring, the buyer should choose a supplier with a low-risk aversion.

Considering the output risk of DPV projects, we study the optimal procurement contract design for the buyer under asymmetric information. The results provide some theoretical basis and management insights for the buyer to design optimal procurement contracts in different situations.

The purpose of this paper is to use the concept of boundary turbulence from Communication Privacy Management (CPM) theory to better understand how employee monitoring impacts employee engagement. This study is one of the first in corporate communication to combine the frameworks of CPM and employee engagement to better understand employee experiences.

To answer the research question, we conducted an online, open-ended survey that asked 633 participants to provide feedback regarding being monitored at work and how these experiences impacted their engagement with their employer.

This study sought to understand how boundary turbulence occurs in relation to employee engagement when employees are monitored at work. In total, four examples of boundary turbulence were illustrated in the data: employer monitoring creates distrust; employees find ways to resist being monitored; monitoring doesn’t accurately capture employee engagement; and monitoring leads to disengagement.

The findings from this study lead to important conclusions regarding what happens when employees experience boundary turbulence, and how it relates to employee engagement. This study illustrates how employee monitoring is interpreted as an attempt to control employees, which can lead to distrust and negatively impact employee engagement. Furthermore, boundary turbulence can threaten psychological safety and presence, which can cultivate employee disengagement. Therefore, employees may seek out ways to actively resist, which reiterates that internal publics are distinctive, active, and agentic audiences that cannot be forgotten or assumed.