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Drawing on the international business and game theory literature, this study assesses foreign firm treatment in the early stages of regulatory enforcement.

Treating regulation intensity as an exposure variable, negative binomial regression models were applied to firm-level data from 32 emerging markets (n = 15,331) to identify the determinants of inspection interactions. Robustness checks also were performed via variable substitutions for several predictors and an alternative form of statistical testing (i.e. Tobit regression, since it arguably better addresses dependent variables with corner solution responses).

Controlling for multiple organizational, regulatory and national characteristics, the findings are consistent with a foreign privilege, manifesting in reduced vulnerability to multiple encounters with labor inspection officials. Moreover, inward FDI stock was negatively related to the general probability of repeat interactions regardless of locus of ownership, an effect that was not moderated by stage of development or the regulatory influence of host interest groups. This collectively suggests that foreign firms not only are favored in compliance monitoring but also work post-entry to influence agencies to generally benefit business.

More comprehensive assessments were precluded given the lack of information on reasons for contact, citations and fines, and inspectorate reactions to company responses. Second, enforcement-risk management was measured indirectly since investors' internal dealings and actions toward officials are unavailable in secondary sources.

These findings have important implications for social responsibility, suggesting CSR stakeholders need to track enforcement more closely and exert pressure where needed so rights are not sacrificed for economic development.

This study provides the most rigorous assessment to date of the role that firm, government and economic factors play in national inspection targeting. It also examined whether foreign owners pool and leverage their political influence to impact general inspection activity, a previously untested prospect.

The authors compare perspectives on external evaluation of health service provision between Norway and the USA. External inspection and accreditation are examples of internationally wide-spread external evaluation methods used to assess the quality of care given to patients. Different countries have different national policy strategies and arrangements set up to do these evaluations. Although there is growing attention to the impact and effects on quality and safety from external evaluation, there is still a gap in knowledge to how structures and processes influence these outcomes. Accordingly, the purpose of this article is to describe the structures and processes in external evaluation designed to promote quality improvement in Norway and the USA with attention to comparison of enablers and barriers in external evaluation systems.

Data collection consisted of documentary evidence retrieved from governmental policies, and reviews of the Joint Commission (the US), international guidelines, recommendations and reports from the International Society for Quality in Health Care, and the World Health Organization, and policies and regulations related to Norwegian governmental bodies such as the Ministry of Health and Care Services, the Norwegian Directorate of Health, and the Norwegian Board of Health Supervision . Data were analyzed inspired by a deductive, direct content analytical framework.

The authors found that both accreditation and inspection are strategies put in place to ensure that healthcare providers have adequate quality systems as well as contributing to the wider risk and safety enhancing management and implementation processes in the organizations subjected to evaluation. The US and the Norwegian external regulatory landscapes are complex and include several policymaking and governing institutions. The Norwegian regulatory framework for inspection has replaced an individual blame logic with a model which “blames” the system for inadequate quality and patient harm. This contrasts with the US accreditation system, which focuses on accreditation visits. Although findings indicate an ongoing turning point in accreditation, findings also demonstrate that involving patients and next of kin directly in adverse event inspections is a bigger part of a change in external inspection culture and methods than in processes of accreditation.

The message of this paper is important for policymakers, and bodies of inspection and accreditation because knowledge retrieved from the comparative document study may contribute to better understanding of the implications from the different system designs and in turn contribute to improving external evaluations.

Although there is a growing attention to the impact and effects on quality and safety from external evaluation, the implications of different regulatory strategies and arrangements for evaluation on quality and safety remain unclear.

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 reviews the literature on maintenance strategies for energy efficiency as a potential maintenance approach. The purpose of this paper is to identify the main concept and common principle for each maintenance strategy for energy efficiency.

A literature review has been carried out on maintenance and energy efficiency. The paper systematically classified the literature into three maintenance strategies (e.g. inspection-based maintenance [IBM], time-based maintenance [TBM] and condition-based maintenance [CBM]). The concept and principle of each maintenance strategy are identified, compared and discussed.

Each maintenance strategy's main concept and principle are identified based on the following criteria: data required and collection, data analysis/modeling and decision-making. IBM relies on human senses and common senses to detect energy faults. Any detected energy losses are quantified to energy cost. A payback period analysis is commonly used to justify corrective actions. On the other hand, CBM monitors relevant parameters that indicate energy performance indicators (EnPIs). Data analysis or deterioration modeling is needed to identify energy degradation. For the diagnostics approach, the energy degradation is compared with the threshold to justify corrective maintenance. The prognostics approach estimates when energy degradation reaches its threshold; therefore, proper maintenance tasks can be planned. On the other hand, TBM uses historical data from energy monitoring. Data analysis or deterioration modeling is required to identify degradation. Further analysis is performed to find the optimal time to perform a maintenance task. The comparison between housekeeping, IBM and CBM is also discussed and presented.

The literature on the classification of maintenance strategies for energy efficiency has been limited. On the other hand, the ISO 50001 energy management systems standard shows the importance of maintenance for energy efficiency (MFEE). Therefore, to bridge the gap between research and industry, the proposed concept and principle of maintenance strategies will be helpful for practitioners to apply maintenance strategies as energy conservation measures in implementing ISO 50001 standard.

The novelty of this paper is in-depth discussion on the concept and principle of each maintenance strategy (e.g. housekeeping or IBM, TBM and CBM) for energy efficiency. The relevant literature for each maintenance strategy was also summarized. In addition, basic rules for maintenance strategy selection are also proposed.

To ensure product quality within a manufacturing process, inspection processes are indispensable. One task of inspection planning is the selection of inspection characteristics. For optimization of costs and benefits, key characteristics can be defined by which the product quality can be checked with sufficient accuracy. The manual selection of key characteristics requires substantial planning effort and becomes uneconomic if many product variants prevail. This paper, therefore, aims to show a method for the efficient determination of key characteristics.

The authors present a novel Algorithm for the Selection of Key Characteristics (ASKC) based on an auto-encoder and a risk analysis. Given historical measurement data and tolerances, the algorithm clusters characteristics with redundant information and selects key characteristics based on a risk assessment. The authors compare ASKC with the algorithm Principal Feature Analysis (PFA) using artificial and historical measurement data.

The authors find that ASKC delivers superior results than PFA. Findings show that the algorithms enable the cost-efficient selection of key characteristics while maintaining the informative value of the inspection concerning the quality.

This paper fills an identified gap for simplified inspection planning with the method for the efficient selection of key features via ASKC.

The purpose of this paper is to propose an improved multi-objective optimization model for the condition-based maintenance (CBM) of single-component systems which considers periodic imperfect maintenance and ecological factors.

Based on the application of non-periodic preventive CBM, two recursion models are built for the system: hazard rate and the environmental degradation factor. This paper also established an optimal multi-objective model with a normalization process. The multiple-attribute value theory is used to obtain the optimal preventive maintenance (PM) interval. The simulation and sensitivity analyses are applied to obtain further rules.

An increase in the number of the occurrences could shorten the duration of a maintenance cycle. The maintenance techniques and maintenance efficiency could be improved by increasing system availability, reducing cost rate and improving degraded condition.

In reality, a variety of environmental situations may occur subsequent to the operations of an advanced manufacturing system. This model could be applied in real cases to help the manufacturers better discover the optimal maintenance cycle with minimized cost and degraded condition of the environment, helping the corporations better fulfill their CSR as well.

Previous research on single-component condition-based predictive maintenance usually focused on the maintenance costs and availability of a system, while ignoring the possible pollution from system operations. This paper proposed a modified multi-objective optimization model considering environment influence which could more comprehensively analyze the factors affecting PM interval.

Comfort foods consumption and linkages to stress coping strategies have received little attention in the business research on food products and services. This paper aims to explore comfort foods consumption among older Americans and how stress-coping strategies are related to their consumption frequency and variety of comfort foods.

Older Americans aged 50–99 years (N = 1,428) in the Health and Retirement Study were surveyed on their frequency and variety of comfort foods consumption and their consumption coping strategies. Data were analyzed and regression models were estimated.

Demographically, baby boomer, male, and non-Hispanic whites reported higher frequency and variety of comfort foods consumption. Comfort foods consumption in frequency and variety was significantly higher (lower) when “eat more” (“use alcohol”) was the endorsed coping strategy.

Research findings furthered research on the consumption of comfort foods among older American adults and added new insights into their coping behavior, both of which may help businesses be more targeted in serving comfort foods to the mature market and the public sector to tailor their services to older adults.

The chemical plant (CP) maintenance industry has been under increasing pressure by process designers to demonstrate its evaluation and information management of model checking (MC) on the durability’s performance and design of plant control instrument. This main problem has been termed as imperfect maintenance actions (IMAs) level. Although IMAs have been explored in interdisciplinary maintenance environments, less is known about what imperfect maintenance problems currently exist and what their causes are, such as the recent explosion in the Beirut city (4 August 2020, about 181 fatalities). The aim of this paper is to identify how CP maintenance environments could integrate MC within their processes.

To achieve this aim, a comprehensive literature review of the existing conceptualisation of MC practices is reviewed and the main features of information and communication technology tools and techniques currently being employed on such IMA projects are carried out and synthesised into a conceptual framework for integrating MC in the automation system process.

The literature reveals that various CP designers conceptualise MC in different ways. MC is commonly shaped by long-term compliance to fulfil the requirement for maintaining a comfortable durability risk on imperfect maintenance schemes of CP projects. Also, there is a lack of common approaches for integrating the delivery process of MC. The conceptual framework demonstrates the importance of early integration of MC in the design phase to identify alternative methods to cogenerate, monitor and optimise MC.

Thus far, this study advances the knowledge about how CP maintenance environments can ensure MC delivery. This paper highlights the need for further research to integrate MC in CP maintenance environments. A future study could validate the framework across the design phase with different CP project designers.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

Operation and maintenance (O&M) processes projects such as identification, assessment, planning and execution, embody a variety of standards such as technical (method of statement), environmental, economic (campus development) and social (health and wellbeing). Because these standards have proven to be challenging to integrate, local governments are increasingly experimenting with social innovation (SI) as a bottom-up form of standard integration. This study aims to apply the concept of SI to the O&M processes of facilities management at polytechnics in Malaysia to identify problems with conventional working practices in this area and to recommend potential solutions.

The paper reviews evidence that conventional working methods generate significant problems related to paper-based forms, improper database management and flawed decision-making processes. Because of the lack knowledge about different ways of how standard integration is achieved, the comparison of three polytechnic institutions which are Rensselaer Polytechnic Institute (RPI) and Southern Polytechnic College of Engineering and Engineering Technology (SPCEET) in USA as well as Seberang Perai Polytechnic, Pulau Pinang (PSP) in Malaysia shares the ambition to realise standard integration of O&M through SI.

The findings reveal that SI leads to four ways of standard integration: computerised maintenance management system, online customer complaint, electronic form and relational database. Application of the concept of SI reveals the need for more sophisticated management solutions in the O&M processes of facilities management.

These standard integration arrangements unfortunately seem to mainly contribute to greater alignment between standard rather than true standard integration. The concept of SI will guide future improvements and developments in maintenance management systems to fulfil requirements in this area.