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This study examines the relationship between goal properties, both at the employee and organizational-level, and the perceived fairness of the performance appraisal system by federal employees.

We describe the theoretical framework regarding goals and employee perceptions of performance appraisal fairness. We then develop and test four hypotheses, exploring the relationships among variables using five years of the FEVS data. To strengthen the research design, we created an agency-level dataset, by calculating agency-level averages for all the covariates. Instead of examining 500,000 federal employees each year, we are examining 80 federal agencies. Creating a panel dataset at the agency level allows us to make stronger statements about causality than using cross-sectional data.

This study finds a significant positive relationship between goal setting factors and employees' perceived fairness of performance appraisals: perceived employee-level goal difficulty and perceived organizational-level goal specificity at the agency level. The study results show that certain control variables, such as intrinsic motivation, play important roles in predicting public employees' perceived fairness of performance appraisals. Federal employees who have a higher level of intrinsic motivation show a more positive perception toward performance appraisal fairness. The appropriate use of extrinsic rewards and intrinsic motivation, combined with effective goal setting strategies in public organizations, may enhance public employees' perceived fairness of performance appraisal systems.

This study used the FEVS, necessitating the reduction of the sample size to agency level averages to create a panel dataset. Also, this study was limited to federal agencies in the United States, so research results may lack generalizability.

This paper fulfills an identified need to avoid cross-sectional research design and leverage longitudinal panel data.

The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift.

A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population.

Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies.

Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management.

The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.

Environmental issues have become an important concern in modern supply chain management. The structure of closed-loop supply chain (CLSC) networks, which considers both forward and reverse logistics, can greatly improve the utilization of materials and enhance the performance of the supply chain in coping with environmental impacts and cost control.

A biobjective mixed-integer programming model is developed to achieve the balance between environmental impact control and operational cost reduction. Various factors regarding the capacity level and the environmental level of facilities are incorporated in this study. The scenario-based method and the Epsilon method are employed to solve the stochastic programming model under uncertain demand.

The proposed stochastic mixed-integer programming (MIP) model is an effective way of formulating and solving the CLSC network design problem. The reliability and precision of the Epsilon method are verified based on the numerical experiments. Conversion efficiency calculation can achieve the trade-off between cost control and CO₂ emissions. Managers should pay more attention to activities about facility operation. These nodes might be the main factors of costs and environmental impacts in the CLSC network. Both costs and CO₂ emissions are influenced by return rate especially costs. Managers should be discreet in coping with cost control for CO₂ emissions barely affected by return rate. It is advisable to convert the double target into a single target by the idea of “Efficiency of CO₂ Emissions Control Reduction.” It can provide managers with a way to double-target conversion.

We proposed a biobjective optimization problem in the CLSC network considering environmental impact control and operational cost reduction. The scenario-based method and the Epsilon method are employed to solve the mixed-integer programming model under uncertain demand.

The study seeks to analyze concepts of “career grades” and “job grading,” to highlight their importance and objectives for the efficiency of administrative systems. In addition, it identifies the international standards that can be used to draw grading systems. It explores the most important types of grade structures. It also clarifies grading systems in the Egyptian administrative system. It indicates some methods that can be considered a form of career progression.

The study employs descriptive, analytical, as well as, legal approaches; it analyzes the information given in the study in terms of relevant legal texts.

The study identifies precise definitions of both career grades and job grading, referring to these concepts in the Egyptian administrative system. It also suggests that there is no ideal hierarchy to be applied in all administrative systems. Therefore, the study provides some criteria that help to form the appropriate grade structure for each system.

The study analyses some literature on “job grading,” its objectives, its criteria and its main types, presenting an integrated framework that can be used to develop career-structure systems. Finally, the study identifies some methods that can be considered as a means of grading.

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

The purpose of this paper is to offer a critical examination of industrial relations in Denmark.

The approach is based upon available data and a mixture of Marxist theory and systems theory. The theoretical position is discussed in relation to the academic discourses on the main characteristics of Danish industrial relations and provides a review of the foundation and historical development of the Danish system.

From this basis, it is analysed how the stagnation or decline has taken place in recent years regarding representation of workers’ interest as well as the ability of the Danish system to maintain its key importance when challenged by decentralisation, decreasing union affiliation rates, cuts in unemployment insurance and social dumping due to labour migration.

It is an original paper which offers a critical analysis of the institutional decline and increasing inequality that are the result of the liberalist political-economic hegemony.

The weapon system of The Navy is the small quantity producing system on multiple kinds. It is consisted of various equipment and the subordinate parts of those which can repair the damaged part. The operating procedure concerning warship's repair parts managed under these systems is as follows. Firstly, if demand of repair parts occurs from warship which is the operating unit of weapon, then the Fleet(the repair & supply support battalion) is in charge of dealing with these requests. If certain request from warship is beyond the battalion's capability, it is delivered directly to the Logistic Command. In short, the repair and supply support system of repair parts can be described as the multi-level support system. The various theoretical researches on inventory management of Navy's repair parts and simulation study that reflects reality in detail have been carried out simultaneously. However, the majority of existing research has been conducted on aircraft and tank's repairable items, in that, the studies is woefully deficient in the area concerning Navy's inventory management. For that reason, this paper firstly constructs the model of consumable items that is frequently damaged reflecting characteristics of navy's repair parts inventory management using ARENA simulation. After that, this paper is trying to propose methodology to analyze optimal inventory level of each supply unit through OptQuest, the optimization program of ARENA simulation.

This paper aims to develop a geometry of moral systems. Existing social choice mechanisms predominantly employ simple structures, such as rankings. A mathematical metric among moral systems allows us to represent complex sets of views in a multidimensional geometry. Such a metric can serve to diagnose structural issues, test existing mechanisms of social choice or engender new mechanisms. It also may be used to replace active social choice mechanisms with information-based passive ones, shifting the operational burden.

Under reasonable assumptions, moral systems correspond to computational black boxes, which can be represented by conditional probability distributions of responses to situations. In the presence of a probability distribution over situations and a metric among responses, codifying our intuition, we can derive a sensible metric among moral systems.

Within the developed framework, the author offers a set of well-behaved candidate metrics that may be employed in real applications. The author also proposes a variety of practical applications to social choice, both diagnostic and generative.

The proffered framework, derived metrics and proposed applications to social choice represent a new paradigm and offer potential improvements and alternatives to existing social choice mechanisms. They also can serve as the staging point for research in a number of directions.

This paper aims to examine the state of research on environmental, social and governance (ESG) performance in the context of multinational business research. This paper discusses research progress as well as various issues and complexities associated with using ESG ratings in cross-country studies and for assessing the performance of multinational enterprises (MNE) and emerging market multinationals (EMNEs).

The paper identifies emerging literature that focuses on tracking the development and uptake of ESG ratings in the international context. It discusses three emerging research streams: Research examining the ESG-financial performance relationship in emerging markets, research tracking the ESG performance of multinationals in the various countries and regions they are operating, and frameworks for assessing ESG-related risks on a country level.

While the emerging body of work adds an important dimension to the identification and awareness of ESG issues globally, numerous unresolved issues become evident. ESG frameworks have been built to assess corporate sustainability as it relates to firms in their “home” countries (typically with a focus on developed countries), with limited applicability and transferability to emerging markets. International firm activities are often not captured in detail and not comprehensively mapped across firm subsidiaries and a firm’s corporate supply chain where ESG issues are prone to happen, and ESG scores do not comprehensively integrate views and voices from various local stakeholders that are impacted by firm activities, particularly indigenous communities.

Research on ESG ratings in the context of multinational business research is generally sparse and fragmented, thus creating opportunities for future research to expand on existing and emerging findings.

The paper creates awareness of issues to consider when using ESG ratings in cross-country studies and for assessing the ESG performance of MNEs and EMNEs: ESG scores can be subject to bias and are not weighted by materiality, which can be misleading for portfolio construction and performance measurement purposes. Managers need to be aware that ESG scores are often not capturing ESG issues occurring in supply chains and ESG issues affecting local communities.

This study enriches the understanding of ESG in the context of multinational business research practice.

This paper aims to examine the growth rates of small- and medium-sized enterprises (SMEs) over a three-year period, the relationship between firm size and firm growth in the context of SMEs, and the effect of marketing capability (MC) on firm growth and how it relates to firm size. The theoretical framework is based on the resource-based view and dynamic capabilities.

Data were gathered from Finnish SMEs (n = 214) and analyzed with Latent growth curve modeling (structural equation modeling). Respondents were chief executive officers or company owners.

Results show that firm size is unrelated to the rate of change, and MC has a significant effect on both the intercept and slope parameters. Smaller SMEs have less MC than larger SMEs.

While the overall human resources level of the SME is not linked to the rate of growth, MC is. This is an important point for small business growth studies, for it shows what type of personnel is called for during rapid growth. SMEs could advance significantly and rapidly if they invest in versatile human capital, especially in the marketing area.

Majority of the MC research involves larger corporations. This study brings new insights from SME perspective. In addition, this study suggests that it is imperative to consider different types of growth separately. This study contributes to this need by demonstrating the connection between employee growth rate and MC in SMEs.