Hasil untuk "Management. Industrial management"

John C. Anderson, M. Rungtusanatham, R. Schroeder

E. Kossek, Brenda A. Lautsch, S. Eaton

Vladimirovich Khachaturyan Mikhail, Valeryenva Klicheva Evgeniia

In contemporary circumstances, it is evident that the activities of industrial enterprises, particularly in the Russian economic system, have a substantial and detrimental impact on the environment. Consequently, it is imperative to transform the management systems of Russian manufacturing companies by integrating sustainability management mechanisms into their structures, encompassing both environmental and economic dimensions, has become increasingly pressing. This article analyzes the distinctive features and characteristics of sustainable development tools as a potential direction for transforming the management mechanisms of contemporary Russian manufacturing companies. The primary objective of this article is to analyse and synthesize the concepts related to the development and implementation of these mechanisms within the management systems of Russian manufacturing companies. The central section presents an analysis of the fundamental characteristics involved in constructing modern Russian production from the perspective of addressing the challenges of sustainable development. Definitions and concepts formulated by Russian and foreign researchers regarding the establishment of mechanisms for the sustainable development of manufacturing companies are scrutinized. The fundamental principles of sustainable development and their potential application within the management systems of Russian manufacturing companies are succinctly analysed. In conclusion, the authors present their interpretations of how management functions (planning, organization, motivation and control) can be transformed in the context of establishing economically and environmentally sustainable production.

Alireza Ghahtarani, Ahmed Saif, Alireza Ghasemi

Asset Liability Management (ALM) represents a fundamental challenge for financial institutions, particularly pension funds, which must navigate the tension between generating competitive investment returns and ensuring the solvency of long-term obligations. To address the limitations of traditional frameworks under uncertainty, this paper implements Distributionally Robust Optimization (DRO), an emergent paradigm that accounts for a broad spectrum of potential probability distributions. We propose and evaluate three distinct DRO formulations: mixture ambiguity sets with discrete scenarios, box ambiguity sets of discrete distribution functions, and Wasserstein metric ambiguity sets. Utilizing empirical data from the Canada Pension Plan (CPP), we conduct a comparative analysis of these models against traditional stochastic programming approaches. Our results demonstrate that DRO formulations, specifically those utilizing Wasserstein and box ambiguity sets, consistently outperform both mixture-based DRO and stochastic programming in terms of funding ratios and overall fund returns. These findings suggest that incorporating distributional robustness significantly enhances the resilience and performance of pension fund management strategies.

Erum Iftikhar, Wei Wei, John Cartlidge

Blockchain-based decentralised lending is a rapidly growing and evolving alternative to traditional lending, but it poses new risks. To mitigate these risks, lending protocols have integrated automated risk management tools into their smart contracts. However, the effectiveness of the latest risk management features introduced in the most recent versions of these lending protocols is understudied. To close this gap, we use a panel regression fixed effects model to empirically analyse the cross-version (v2 and v3) and cross-chain (L1 and L2) effectiveness of liquidation mechanisms, measured through TVL and total revenue as proxies for performance of the two most popular lending protocols, Aave and Compound, during the period Jan 2021 to Dec 2024. Our analysis reveals that liquidation events in v3 of both protocols lead to an increase in total value locked and total revenue, with stronger impact on the L2 blockchain compared to L1. In contrast, liquidations in v2 have an insignificant impact, which indicates that the most recent v3 protocols have better risk management than the earlier v2 protocols. We also show that L1 blockchains are the preferred choice among large investors for their robust liquidity and ecosystem depth, while L2 blockchains are more popular among retail investors for their lower fees and faster execution.

Zinuo You, John Cartlidge, Karen Elliott et al.

Existing black-box portfolio management systems are prevalent in the financial industry due to commercial and safety constraints, though their performance can fluctuate dramatically with changing market regimes. Evaluating these non-transparent systems is computationally expensive, as fixed budgets limit the number of possible observations. Therefore, achieving stable and sample-efficient optimization for these systems has become a critical challenge. This work presents a novel Bayesian optimization framework (TPE-AS) that improves search stability and efficiency for black-box portfolio models under these limited observation budgets. Standard Bayesian optimization, which solely maximizes expected return, can yield erratic search trajectories and misalign the surrogate model with the true objective, thereby wasting the limited evaluation budget. To mitigate these issues, we propose a weighted Lagrangian estimator that leverages an adaptive schedule and importance sampling. This estimator dynamically balances exploration and exploitation by incorporating both the maximization of model performance and the minimization of the variance of model observations. It guides the search from broad, performance-seeking exploration towards stable and desirable regions as the optimization progresses. Extensive experiments and ablation studies, which establish our proposed method as the primary approach and other configurations as baselines, demonstrate its effectiveness across four backtest settings with three distinct black-box portfolio management models.

Xudong Wang, Lei Feng, Ruichen Zhang et al.

The Industrial Internet of Things (IIoT) requires networks that deliver ultra-low latency, high reliability, and cost efficiency, which traditional optimization methods and deep reinforcement learning (DRL)-based approaches struggle to provide under dynamic and heterogeneous workloads. To address this gap, large language model (LLM)-empowered agentic AI has emerged as a promising paradigm, integrating reasoning, planning, and adaptation to enable QoE-aware network management. In this paper, we explore the integration of agentic AI into QoE-aware network slicing for IIoT. We first review the network slicing management architecture, QoE metrics for IIoT applications, and the challenges of dynamically managing heterogeneous network slices, while highlighting the motivations and advantages of adopting agentic AI. We then present the workflow of agentic AI-based slicing management, illustrating the full lifecycle of AI agents from processing slice requests to constructing slice instances and performing dynamic adjustments. Furthermore, we propose an LLM-empowered agentic AI approach for slicing management, which integrates a retrieval-augmented generation (RAG) module for semantic intent inference, a DRL-based orchestrator for slicing configuration, and an incremental memory mechanism for continual learning and adaptation. Through a case study on heterogeneous slice management, we demonstrate that the proposed approach significantly outperforms other baselines in balancing latency, reliability, and cost, and achieves up to a 19% improvement in slice availability ratio.

Kristi Topollai, Tolga Dimlioglu, Anna Choromanska et al.

Contract management involves reviewing and negotiating provisions, individual clauses that define rights, obligations, and terms of agreement. During this process, revisions to provisions are proposed and iteratively refined, some of which may be problematic or unacceptable. Automating this workflow is challenging due to the scarcity of labeled data and the abundance of unstructured legacy contracts. In this paper, we present a modular framework designed to streamline contract management through a retrieval-augmented generation (RAG) pipeline. Our system integrates synthetic data generation, semantic clause retrieval, acceptability classification, and reward-based alignment to flag problematic revisions and generate improved alternatives. Developed and evaluated in collaboration with an industry partner, our system achieves over 80% accuracy in both identifying and optimizing problematic revisions, demonstrating strong performance under real-world, low-resource conditions and offering a practical means of accelerating contract revision workflows.

Zhongxuan Liu, Jiayou Shi, Jingyi Xu

Scientific scandals are catalysts for the evolution process of legal governance. The 2018 CRISPR-babies Incident has essentially triggered China's legal reforms of ethics governance in science and technology. This paper explores the institutional deficiency that led to such a scandal, analyzes its long-term implications for legal governance, and presents China's recent legal progress in response to such an issue. The rapid legislative response to the CRISPR-babies Incident is a double-edged sword, while promoting the improvement of the legal system, it can also cause issues like fragmentation of governance, contradictory rules, and conflict of interest. China should integrate departmental norms and upgrade its level of effectiveness. Strengthening legislation is the implementation path, and improving ethical review, supervision and scientific research integrity systems are the crucial means. In addition, it is necessary to bring the coordinating function of the Central Science and Technology Commission into full play and pay more attention to public engagement and international cooperation.

Kostiantyn Fuks

The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysis, web analytics and technology partnerships for success in the digital marketplace. It also examines modern organisational strategies to help IT companies effectively implement marketing initiatives and adapt quickly to changing business landscapes. Methodology. This article is based on a theoretical and methodological review of the existing scientific literature on digital technologies, the marketing of digital products and services, and an overview of current technological and organisational solutions in the digital field. In addition, it includes a survey of marketing managers from renowned IT companies with the aim of delineating the typology of organisational structures within marketing departments. Results. Information delivery, data analytics, monitoring tools and web analytics are critical to digital marketing in IT organisations, facilitating the collection and analysis of data from multiple sources such as websites, social media and CRM systems. By leveraging big data and machine learning algorithms, it is possible to identify complex dependencies and predict consumer behaviour. Technological partnerships and collaborations with startups are becoming increasingly important for IT companies' marketing efforts, providing access to fresh ideas, technologies and a competitive edge. Organisational structures in the marketing departments of IT companies emphasise agility and cross-functional teamwork, often using agile methodologies. This promotes adaptability to market changes. Marketing structures typically include inbound approaches, flexible growth-oriented setups, and streamlined hierarchies. Practical implications. These marketing tools and organisational methods are recommended for implementation in the marketing departments of IT companies. The correlation between informational and organisational capabilities contributes to the achievement of marketing goals and the competitive advantage of IT companies in the marketplace. Scrum and Kanban, widely used agile frameworks, are not limited to technology companies but are also common in financial services and retail. Value / Оriginality. In the context of the ongoing military conflict, successful operation of Ukrainian IT companies in the modern world requires not only technological superiority, but also effective marketing and a well-organised internal structure. To accelerate the recovery of the Ukrainian IT sector and improve existing practices, the following recommendations have been made.

Finn Klessascheck, Ingo Weber, Luise Pufahl

Given the continuous global degradation of the Earth's ecosystem due to unsustainable human activity, it is increasingly important for enterprises to evaluate the effects they have on the environment. Consequently, assessing the impact of business processes on sustainability is becoming an important consideration in the discipline of Business Process Management (BPM). However, existing practical approaches that aim at a sustainability-oriented analysis of business processes provide only a limited perspective on the environmental impact caused. Further, they provide no clear and practically applicable mechanism for sustainability-driven process analysis and re-design. Following a design science methodology, we here propose and study SOPA, a framework for sustainability-oriented process analysis and re-design. SOPA extends the BPM life cycle by use of Life Cycle Assessment (LCA) for sustainability analysis in combination with Activity-based Costing (ABC). We evaluate SOPA and its usefulness with a case study, by means of an implementation to support the approach, thereby also illustrating the practical applicability of this work.

Gianluigi Rozza, Oliver Schütze, Nicholas Fantuzzi

This Special Issue comprises the first collection of papers submitted by the Editorial Board Members (EBMs) of the journal <i>Mathematical and Computational Applications</i> (MCA), as well as outstanding scholars working in the core research fields of MCA [...]

Ju-Hong Lee, Bayartsetseg Kalina, KwangTek Na

Traditional risk-adjusted returns, such as the Treynor, Sharpe, Sortino, and Information ratios, have been pivotal in portfolio asset allocation, focusing on minimizing risk while maximizing profit. Nevertheless, these metrics often fail to account for the distinct characteristics of bull and bear markets, leading to sub-optimal investment decisions. This paper introduces a novel approach called the Market-adaptive Ratio, which was designed to adjust risk preferences dynamically in response to market conditions. By integrating the $ρ$ parameter, which differentiates between bull and bear markets, this new ratio enables a more adaptive portfolio management strategy. The $ρ$ parameter is derived from historical data and implemented within a reinforcement learning framework, allowing the method to learn and optimize portfolio allocations based on prevailing market trends. Empirical analysis showed that the Market-adaptive Ratio outperformed the Sharpe Ratio by providing more robust risk-adjusted returns tailored to the specific market environment. This advance enhances portfolio performance by aligning investment strategies with the inherent dynamics of bull and bear markets, optimizing risk and return outcomes.

Dinny Indrian, Kurniawan Kurniawan, Sindydevia Rahayu

Laporan WHO menyebutkan 372.441 orang meninggal setiap tahun disebabkan oleh tenggelam. Upaya kuratif untuk mengatasi tenggelam adalah dengan pengunaan pelampung. Korban yang nyaris tenggelam membutuhkan kecepatan penanganan. Oleh karena itu, pengembangan pelampung diarahkan pada peningkatan kecepatan gerak pelampung. Dalam penelitian dilakukan pencarian hubungan antara geometri penampang pelampung dengan kecepatan gerak optimum. Metodologi penyelesaian pada tugas akhir ini adalah studi literatur, identifikasi masalah (perhitungan volume pelampung), rancangan dan parameter desain pelampung, studi sensitivitas pelampung terhadap payload 100 kg, mengecek batas ergonomi, studi dinamika fluida komputasi (CFD) dan mengecek kecepatan alir fluida pada pelampung. Berdasarkan hasil penelitian yang dilakukan, masing – masing bentuk penampang memiliki karakterstik tersendiri. Sehingga beberapa penampang direkomendasikan untuk dikaji lebih lanjut untuk mencapai target dan efektifitas yang diinginkan.

Jiahua Xu, Yebo Feng

Yield farming represents an immensely popular asset management activity in decentralized finance (DeFi). It involves supplying, borrowing, or staking crypto assets to earn an income in forms of transaction fees, interest, or participation rewards at different DeFi marketplaces. In this systematic survey, we present yield farming protocols as an aggregation-layer constituent of the wider DeFi ecosystem that interact with primitive-layer protocols such as decentralized exchanges (DEXs) and protocols for loanable funds (PLFs). We examine the yield farming mechanism by first studying the operations encoded in the yield farming smart contracts, and then performing stylized, parameterized simulations on various yield farming strategies. We conduct a thorough literature review on related work, and establish a framework for yield farming protocols that takes into account pool structure, accepted token types, and implemented strategies. Using our framework, we characterize major yield aggregators in the market including Yearn Finance, Beefy, and Badger DAO. Moreover, we discuss anecdotal attacks against yield aggregators and generalize a number of risks associated with yield farming.

Marlon Dumas, Fabiana Fournier, Lior Limonad et al.

AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics.

Erica Weintraub Austin, Porismita Borah, Shawn Domgaard

Communities of color, suffering equity gaps and disproportionate COVID-19 effects, also must resist ongoing disinformation campaigns designed to impede their political influence. A representative, national survey (N=1264) of adults conducted June-July 2020 found that nonwhite respondents tended to report less COVID-19 knowledge, media literacy, and voting intent than white respondents, but more acceptance of COVID-19 disinformation and for risks associated with protesting for social justice. General media literacy skills are associated with COVID-19 knowledge and political engagement, while science media literacy is associated with less acceptance of COVID-19 disinformation. Media literacy skills appear important for empowering and informing communities of color.

Kirillova Elena, Uvarova Nataly

A modified system of indicators for assessing the innovation activities effectiveness in the region based on data on patent and licensing activities in the framework of scientific and industrial cooperation is described. Also in the article we presented a general mechanism for innovation process effectiveness managing of such cooperative interaction. They are intended to be used as tools to support decision-making, allowing one to coordinate the cooperative indicators management. The proposed system of indicators provides transfer and decomposition of goals for planning operational activities by levels and actors of the innovation process in the cooperative formation, as well as monitoring their achievement. Taking into account the peculiarities of the innovation environment, the proposed balanced indicators system (hereinafter referred to as the BSC) focuses on non-financial logistics performance indicators and patent’s information. The structure of the BSC assumes a pyramid-layer structure, the number of elements of each layer is determined by the structural decomposition of the cooperative interaction corresponding level. The article describes stages of forming such BSC-maps process. As a tool for improving the balance of strategic maps for generating management decisions, a transition to “horizontal dynamics” is proposed, according to which at each level of logistics management, among all goals there is the greatest deviation from the target values, i.e., from the target values achieved to the least extent. These goals are the “target limitations” of the enterprise effective operation and they take greatest importance for further analysis of critical situations. For this purpose, a procedure for managing innovation environment by deviations is proposed.

Zhao Xin, Ti Haowei, Ma Ding

It has been more than ten years since I started to study business management. There is no doubt that the modern management discipline originated with the West, and the West is the birthplace of modern management theories and methods. This kind of management theory and method, which originated from the industrial revolution in the West, took enterprises as the basic management unit, and relied on the two mechanisms of market economy and technological revolution. Western management concepts have been widely disseminated and applied around the world, deeply affecting the management practices of companies around the world. The strategic positioning of an enterprise is determined by the trend of the external environment and the destiny of the enterprise. The destiny of an enterprise is a management element that cannot be ignored, just like what Buddhism said: "Bodhisattva will also lose cause and effect."

Vicente Bagnoli

O objetivo do artigo é investigar a concorrência nos mercados digitais e o papel da política de concorrência nas economias em desenvolvimento para um crescimento inclusivo e prosperidade compartilhada com ferramentas inovadoras para uma melhor aplicação da lei. Sua metodologia analisa relatórios e pesquisas internacionais. As economias em desenvolvimento devem fortalecer sua capacidade de desenhar políticas de concorrência nos mercados digitais de acordo com suas particularidades sociais e econômicas de desenvolvimento, observando o que as economias desenvolvidas vêm fazendo em seu próprio mercado. A UE tem conduzido a política de concorrência nos mercados digitais, e o Digital Markets Act e o Digital Services Act são mais duas iniciativas capazes de facilitar as economias em desenvolvimento na concepção de sua própria regulamentação nos mercados digitais. O resultado do artigo indica que não existe um formato único e, como conclusão, a experiência e os bons padrões devem ser avaliados e ajustados.