Hasil untuk "Employee participation in management. Employee ownership. Industrial democracy. Works councils"

Les auteurs examinent les transitions vers l’emploi vert sur le marché du travail du Viet Nam ainsi que leur relation avec la protection sociale. À partir d’une approche fondée sur les tâches et des données d’une enquête longitudinale sur les forces de travail, ils constatent que les emplois verts restent limités et ne représentent que 15 pour cent de l’emploi total. Les taux de transition varient beaucoup en fonction des caractéristiques démographiques, les jeunes travailleurs et les femmes ayant plus de difficultés à accéder aux emplois verts. Le niveau d’éducation est aussi un facteur déterminant: les personnes ayant fait des études supérieures sont plus susceptibles d’accéder à des métiers verts. Quant à la couverture sociale, elle est positivement associée aux transitions d’un emploi brun ou neutre vers un emploi vert chez ceux qui ont fait des études supérieures, et négativement liée à la probabilité de passer d’un emploi vert à un emploi brun. En revanche, elle ne semble pas faciliter les transitions vers des professions vertes pour les travailleurs ayant un faible niveau d’éducation. Ces résultats soulignent la nécessité de mettre en place des cadres politiques intégrés combinant la protection sociale et l’éducation afin de promouvoir des transitions vertes inclusives dans les pays en développement.

Yiran Ma, Jerome Le Ny, Zhichao Chen et al.

In modern process industries, data-driven models are important tools for real-time monitoring when key performance indicators are difficult to measure directly. While accurate predictions are essential, reliable uncertainty quantification (UQ) is equally critical for safety, reliability, and decision-making, but remains a major challenge in current data-driven approaches. In this work, we introduce a diffusion-based posterior sampling framework that inherently produces well-calibrated predictive uncertainty via faithful posterior sampling, eliminating the need for post-hoc calibration. In extensive evaluations on synthetic distributions, the Raman-based phenylacetic acid soft sensor benchmark, and a real ammonia synthesis case study, our method achieves practical improvements over existing UQ techniques in both uncertainty calibration and predictive accuracy. These results highlight diffusion samplers as a principled and scalable paradigm for advancing uncertainty-aware modeling in industrial applications.

Claude DIDRY

Nils B. Weidmann, Mats Faulborn, David García

Current political developments worldwide illustrate that research on democratic backsliding is as important as ever. A recent exchange in Political Science & Politics (2/2024) has highlighted again a fundamental challenge in this literature: the measurement of democracy. With many democracy indicators consisting of subjective assessments rather than factual observations, trends in democracy over time could be due to human biases in the coding of these indicators rather than empirical facts. In this paper, we leverage two cutting-edge Large Language Models (LLMs) for the coding of democracy indicators from the V-Dem project. With access to a huge amount of information, these models may be able to rate the many "soft" characteristics of regimes without the cognitive biases that humans potentially possess. While LLM-generated codings largely align with expert coders for many countries, we show that when these models deviate from human assessments, they do so in different but consistent ways: Some LLMs are too pessimistic, while others consistently overestimate the democratic quality of these countries. While the combination of the two LLM codings can alleviate this concern, we conclude that it is difficult to replace human coders with LLMs, since the extent and direction of these attitudes is not known a priori.

Tong Nie, Jian Sun, Wei Ma

Networked urban systems facilitate the flow of people, resources, and services, and are essential for economic and social interactions. These systems often involve complex processes with unknown governing rules, observed by sensor-based time series. To aid decision-making in industrial and engineering contexts, data-driven predictive models are used to forecast spatiotemporal dynamics of urban systems. Current models such as graph neural networks have shown promise but face a trade-off between efficacy and efficiency due to computational demands. Hence, their applications in large-scale networks still require further efforts. This paper addresses this trade-off challenge by drawing inspiration from physical laws to inform essential model designs that align with fundamental principles and avoid architectural redundancy. By understanding both micro- and macro-processes, we present a principled interpretable neural diffusion scheme based on Transformer-like structures whose attention layers are induced by low-dimensional embeddings. The proposed scalable spatiotemporal Transformer (ScaleSTF), with linear complexity, is validated on large-scale urban systems including traffic flow, solar power, and smart meters, showing state-of-the-art performance and remarkable scalability. Our results constitute a fresh perspective on the dynamics prediction in large-scale urban networks.

Tomi Suomi, Petri Ihantola, Tommi Mikkonen et al.

Agile software development relies on self-organized teams, underlining the importance of individual responsibility. How developers take responsibility and build ownership are influenced by external factors such as architecture and development methods. This paper examines the existing literature on ownership in software engineering and in psychology, and argues that a more comprehensive view of ownership in software engineering has a great potential in improving software team's work. Initial positions on the issue are offered for discussion and to lay foundations for further research.

seyed Ali Marashi, Elham Saei, kioumars Beshlideh et al.

Abstract                   Purpose: The purpose of the present study was to investigate the effects of leadership styles on employees' deviant behavior with the mediating role of perceived politicization and the moderating role of social support among employees working in Abadan Oil Refining Company. In the proposed research model, leadership style was the independent variable and workplace deviance functioned as the dependent variable; besides, perceived organizational politicization played the role of mediating variable. Methodology: The method of the current research was correlational. The statistical sample consisted of 480 individuals whom we selected from among the employees of Abadan Oil Refinery Company using a multi-stage random sampling method. Using structural equation modeling, we evaluated the conceptual research model. Findings: The results show that all the direct paths are significant, except for the transactional leadership style regarding perceived politicization. Also, the mediating effect of perceived politicization between ethical and transformational leadership styles and deviant behaviors in the workplace is significant. However, the moderating role of social support between perceived politicization and workplace deviance is not significant. Originality: For the first time in Iran, the present research has investigated the impact of organizational leadership styles on creating a politicizing atmosphere in the organization and its ability to control this phenomenon.

Shohreh Nasri, Mercedeh Pahlavanian, Mojtaba Sharanjani,

Purpose: Considering the importance of evaluating the performance of student affairs departments in providing favorable educational facilities for students, this research intended to identify relevant indicators for Iranian universities through a comparative study as well as validated performance evaluation criteria. Methodology: To collect the data, desk research, together with international experience were used; besides, questionnaires were administered to validate the indicators regarding the performance evaluation of student services. Also, we applied the intervention logic model and performance evaluation cycle to provide a performance evaluation framework for student affairs division. Findings: The results of the research indicate that the functions related to the management of student affairs, according to the international experiences, are as follow: providing suitable food, providing housing services, providing suitable welfare facilities, maintaining and promoting physical and mental health and vitality, empowerment and development of students, discipline and education, providing additional educational services to students with disabilities, international student services, providing security and comfort, providing free legal advice, providing cultural and social services and providing suitable physical environment. Finally, based on the conceptual framework of the research we are presenting a set of indicators and measures are under each of the mentioned functions, which all together conform the three components of inputs, outputs, and results. Originality: Applying a systematic and process-oriented approach, we have presented for the first time a framework for evaluating the student affairs divisions of universities based on international practice. Implications: The suggested framework of this study can serve as a basis for appropriate policymaking for evaluating universities, allocating budgets, classifying students, and classifying services.

Domenico Mario Nuti

Yousef Vakili, Akbar Hassanpoor, Saeed Jafarinia et al.

Purpose: Mentern is a strategy that can help organizations in the field of generational differences. Therefore, for this purpose, the end of this study is to design a model of Mentern in public organizations. Methodology: This research was conducted using the Glacerian Grounded theory. Semi-structured interview was used to collect data, and after interviewing 19 experts, theoretical saturation was obtained. The data using actual coding (open and selective coding) and theoretical coding were analyzed. Finding: The findings showed that mentoring as a core category, supportive management system, empowering human resource management, dynamic organizational structure, learning culture, suitable individual characteristics and personality of mentoring, interpersonal skills, supportive culture of society as a context and the formation of a positive attitude towards the organization, development of professional and leadership abilities, improvement of job performance, formation of cooperative climate and improvement of organizational performance were identified as outcomes. Originality/ Value: The present research has been able to provide a comprehensive model for the implementation of the mentern in public organizations by examining the characteristics of different working generations and the concepts of coaching and mentoring. Recommendations: According to the proposed model, managers are advised to distance themselves from hierarchical structures, and to use suitable people and train them to provide opportunities for the implementation of mentern in order to reduce the generation gap in public organizations.

Takashi Nakayama, Yusuke Matsushita, Ken Sakayori et al.

Automated verification of functional correctness of imperative programs with references (a.k.a. pointers) is challenging because of reference aliasing. Ownership types have recently been applied to address this issue, but the existing approaches were limited in that they are effective only for a class of programs whose reference usage follows a certain style. To relax the limitation, we combine the approaches of ConSORT (based on fractional ownership) and RustHorn (based on borrowable ownership), two recent approaches to automated program verification based on ownership types, and propose the notion of borrowable fractional ownership types. We formalize a new type system based on the borrowable fractional ownership types and show how we can use it to automatically reduce the program verification problem for imperative programs with references to that for functional programs without references. We also show the soundness of our type system and the translation, and conduct experiments to confirm the effectiveness of our approach.

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammed Atiquzzaman

The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent healthcare systems, and various real-world applications have resulted in the generation of vast amounts of data, often analyzed using different Machine Learning (ML) models. Federated learning (FL) has been acknowledged as a privacy-preserving machine learning technology, where multiple parties cooperatively train ML models without exchanging raw data. However, the current FL architecture does not allow for an audit of the training process due to the various data-protection policies implemented by each FL participant. Furthermore, there is no global model verifiability available in the current architecture. This paper proposes a smart contract-based policy control for securing the Federated Learning (FL) management system. First, we develop and deploy a smart contract-based local training policy control on the FL participants' side. This policy control is used to verify the training process, ensuring that the evaluation process follows the same rules for all FL participants. We then enforce a smart contract-based aggregation policy to manage the global model aggregation process. Upon completion, the aggregated model and policy are stored on blockchain-based storage. Subsequently, we distribute the aggregated global model and the smart contract to all FL participants. Our proposed method uses smart policy control to manage access and verify the integrity of machine learning models. We conducted multiple experiments with various machine learning architectures and datasets to evaluate our proposed framework, such as MNIST and CIFAR-10.

Vahid reza Halvaeiha

Background & Purpose: Perception of justice arises from the social actions in the form of perceptual-behavioral cycles between social actors over time. In organizations, this cycles between superiors and subordinates affect the perceptions and consequently the behaviors of both sides of the relationship. Considering the small number of superiors and their placement in the center of organizational interactions, the best point of intervention to manage these cycles is the perceptions of superiors. In this research, our goal is to identify personality traits that influence the perception of justice of leaders and their continued behavior. Methodology: This research is fundamental in terms of results, is exploratory regarding purpose, and is qualitative concerning method, the data were collected by library research and based on thematic analysis of the Nahj-Ol-Balagha Text. To do so, Nahj-Ol-Balagha Text was read many times and coding was accomplished after selecting the related parts. Then, the codes were revised, summarized, and then categorized in different steps. The results were validated using expert panel and Holsti’s coefficient of reliability (92%). Finally, Delfi Method was used to reach agreement in categorizing the codes. Findings: Two sets of codes were found in this study: the 25-code set refers to the relationship between personal traits as well as behavior with the values and believes. The second set consists of 505 basic recorded codes that categorized in the form of two main organizing themes of magnanimity and dignity, and steadfastness and fortitude.  Magnanimity and dignity cover three sub-organizing themes including: respect for others, kindness and generosity, and the main organizing theme of steadfastness and fortitude, and includes three sub-organizing themes of self-control, insight, and personal stability. These findings signify a specific style of leading that is balanced through these two sets of Magnanimity and dignity, and steadfastness and fortitude. Conclusion: The results suggest that the leaders who possess the characteristics mentioned in this research, will perceive less injustice, and after the perception of injustice, the possibility of extreme behavior in them is less probable. Thus, it is expected that the perception of justice in the subordinates of such leaders will be more and the atmosphere of justice in the organization will be more positive as well.

Bent Flyvbjerg

Behavioral science has witnessed an explosion in the number of biases identified by behavioral scientists, to more than 200 at present. This article identifies the 10 most important behavioral biases for project management. First, we argue it is a mistake to equate behavioral bias with cognitive bias, as is common. Cognitive bias is half the story; political bias the other half. Second, we list the top 10 behavioral biases in project management: (1) strategic misrepresentation, (2) optimism bias, (3) uniqueness bias, (4) the planning fallacy, (5) overconfidence bias, (6) hindsight bias, (7) availability bias, (8) the base rate fallacy, (9) anchoring, and (10) escalation of commitment. Each bias is defined, and its impacts on project management are explained, with examples. Third, base rate neglect is identified as a primary reason that projects underperform. This is supported by presentation of the most comprehensive set of base rates that exist in project management scholarship, from 2,062 projects. Finally, recent findings of power law outcomes in project performance are identified as a possible first stage in discovering a general theory of project management, with more fundamental and more scientific explanations of project outcomes than found in conventional theory.

Mir Ali Sayyed Naghavi, Mahboubeh Rashidi, Behrouz rezaeemanesh et al.

Background & Purpose: Human resources slack refers to more human resources than the organization needs, which can have different and even contradictory effects on organizational performance. The objective of the present study was to investigate the effect of this new concept in the field of human resources on the organization performance. Methodology: This study was qualitative and fundamental with a systematic review in case of purpose. Therefore, the systematic search was limited to two databases including Elsevier (Scopus) and scientific network information sciences institute (Thomson Reuters) to identify and extract the articles. CASP standard checklist was used to assess the study validity, and Cohen kappa index equal to 0.731 was applied in SPSS software to assess the study reliability which was confirmed. Findings: A model was suggested through investigating the existing articles in order to clearly state the manner of human resources slack effect on the organizations performance. Referring to the articles, the model introduces our types of human resources slack including Value-oriented, Knowledge-oriented, Surplus-oriented, Accumulation-oriented from two aspects of being relative or absolute, and also being knowledge-based or non-knowledge-based and considering short-term and long-term period. Conclusion. The model presented in the research can be the basis for future research in order to optimize Human resource slack in various human resource management measures such as training, rewarding, and compensating evaluation, etc. In the proposed pattern, value-oriented and knowledge-based human resources slack with positive effects and Surplus-oriented human resources slack and to some extent Accumulation-oriented human resources slack with negative effects were evaluated. However, having too many of each type can be detrimental to an organization's performance.

Armin Goli, Ali Gholipur Soleimani, Narges Delafrooz

This study adopts a mixed approach: qualitative-quantitative. The statistical population in the qualitative section was all the stories of Ramsar destinations in the social media. Using judgmental sampling, 62 stories were selected. The study used a narrative analysis strategy. Data collection method was online written stories which were analyzed through narrative analysis and content analysis. Next, the identified dimensions of social media storytelling power were presented first in the form of a thematic network and then in the framework of a conceptual model for this destination. In the quantitative phase, the research strategy was conducting a survey. The statistical population here included all tourists who had read the tourism stories of this destination on the social media. Nonprobability convenience sampling method was used and the sample size, given the unlimited statistical population, was estimated to be 450 people per destination based on Morgan's table. Data collection method was electronic questionnaires sent to the tourists. The results of structural equations modeling show that all aspects of Ramsar online social media storytelling power, including literary knowledge, attractiveness, dynamism, tourism, trust, reliability, cognition, emotion, and ethics significantly affect the development of this destination.

David Leslie, Christopher Burr, Mhairi Aitken et al.

In September 2019, the Council of Europe's Committee of Ministers adopted the terms of reference for the Ad Hoc Committee on Artificial Intelligence (CAHAI). The CAHAI is charged with examining the feasibility and potential elements of a legal framework for the design, development, and deployment of AI systems that accord with Council of Europe standards across the interrelated areas of human rights, democracy, and the rule of law. As a first and necessary step in carrying out this responsibility, the CAHAI's Feasibility Study, adopted by its plenary in December 2020, has explored options for an international legal response that fills existing gaps in legislation and tailors the use of binding and non-binding legal instruments to the specific risks and opportunities presented by AI systems. The Study examines how the fundamental rights and freedoms that are already codified in international human rights law can be used as the basis for such a legal framework. The purpose of this primer is to introduce the main concepts and principles presented in the CAHAI's Feasibility Study for a general, non-technical audience. It also aims to provide some background information on the areas of AI innovation, human rights law, technology policy, and compliance mechanisms covered therein. In keeping with the Council of Europe's commitment to broad multi-stakeholder consultations, outreach, and engagement, this primer has been designed to help facilitate the meaningful and informed participation of an inclusive group of stakeholders as the CAHAI seeks feedback and guidance regarding the essential issues raised by the Feasibility Study.

Yutian Tang, Haoyu Wang, Xian Zhan et al.

Being able to automatically detect the performance issues in apps can significantly improve apps' quality as well as having a positive influence on user satisfaction. Application Performance Management (APM) libraries are used to locate the apps' performance bottleneck, monitor their behaviors at runtime, and identify potential security risks. Although app developers have been exploiting application performance management (APM) tools to capture these potential performance issues, most of them do not fully understand the internals of these APM tools and the effect on their apps. To fill this gap, in this paper, we conduct the first systematic study on APMs for apps by scrutinizing 25 widely-used APMs for Android apps and develop a framework named APMHunter for exploring the usage of APMs in Android apps. Using APMHunter, we conduct a large-scale empirical study on 500,000 Android apps to explore the usage patterns of APMs and discover the potential misuses of APMs. We obtain two major findings: 1) some APMs still employ deprecated permissions and approaches, which makes APMs fail to perform as expected; 2) inappropriate use of APMs can cause privacy leaks. Thus, our study suggests that both APM vendors and developers should design and use APMs scrupulously.

Damian Kisiel, Denise Gorse

This work proposes a novel portfolio management technique, the Meta Portfolio Method (MPM), inspired by the successes of meta approaches in the field of bioinformatics and elsewhere. The MPM uses XGBoost to learn how to switch between two risk-based portfolio allocation strategies, the Hierarchical Risk Parity (HRP) and more classical Naïve Risk Parity (NRP). It is demonstrated that the MPM is able to successfully take advantage of the best characteristics of each strategy (the NRP's fast growth during market uptrends, and the HRP's protection against drawdowns during market turmoil). As a result, the MPM is shown to possess an excellent out-of-sample risk-reward profile, as measured by the Sharpe ratio, and in addition offers a high degree of interpretability of its asset allocation decisions.

Razieh Taghizadeh, Hamidreza Yazdani

The challenge and inability to effectively manage organizational resources such as financial capital, human resources, and management of intra- and inter-organizational conflict resolution is one of the issues non-governmental organizations are faced with. Therefore, the purpose of this study is to present an effective leadership model for environmental people-based organizations (PBSs/NGOs) in Iran. The present study was developmental in terms of purpose and descriptive-exploratory in terms of methodology. Grounded method, together with Strauss and Corbin approach, was applied to collect qualitative data. Alongside this, 12 experts from these organizations were selected and interviewed. The process of coding in the founded theory involved the process of continuous data analysis in open, central and selective stages. Results show: (a) participation, service rendering, transformation orientation and legal orientation are effective leadership dimensions, (b) capacity of grassroots organizations, governance networks and organizational capabilities are among the causal factors, (c) flexible organizational structure and organizational climate are effective contextual factors, (d) supportive policies and strategies (both internal and external) are intervening factors in the effective leadership model, (e) public participation and organizational performance are effective leadership outcomes.