Hasil untuk "Production management. Operations management"

Bohdan Tsymbal

Мета роботи:  Метою роботи є зменшення та/або усунення ергономічних ризиків під час виконання аварійно-рятувальних робіт. / The goal of the work is to reduce or eliminate ergonomic risks during emergency and rescue operations. Метод : / Design/Method/Approach (only for empirical papers): З метою перевірки гіпотез, вирішення дослідницьких завдань була використана система прийомів та способів таких, як метод абстрагування, аналізу й синтезу, порівняння, спостереження та експертний метод оцінки ергономічних ризиків. Експериментальні дані були отримані за рахунок відеоматеріалів 16 реальних подій під час аварійно-рятувальних робіт після ворожого обстрілу. Результати дослідження: / Findings: Було встановлено, що найбільш вразливими частинами тіла рятувальників під час здійснення аварійно-рятувальних робіт є спина та шия. Максимальна оцінка ергономічного ризику за методикою REBA становить 7. Показники ергономічного ризику за методикою Soter: загальний ризик є високий. Були виявлені небезпеки: тривале згинання та незручне положення тіла під час роботи з уламками; підйом та робота на нестабільних поверхнях; повторювані рухи та перенапруження; тривале згинання шиї; незручні пози для лівої руки; повторювані завдання та сильні навантаження; повторювані нахили та підйоми в незручних позах; підйом та робота на нестабільних поверхнях та ін. / It was found that the most vulnerable parts of the body of rescuers during emergency rescue operations are the back and neck. The maximum ergonomic risk score according to the REBA method is 7. Ergonomic risk indicators according to the Soter method: the overall risk is high. The following hazards were identified: prolonged bending and awkward body positions when working with debris; lifting and working on unstable surfaces; repetitive movements and overexertion; prolonged neck bending; awkward postures for the left hand; repetitive tasks and heavy loads; repetitive bending and lifting in awkward postures; lifting and working on unstable surfaces, etc. Теоретична цінність дослідження: / Theoretical implications (if applicable): Теоретичні дослідження розширили теорію ризиків та доповнили її особливостями ергономічних ризиків в екстремальних умовах, у не виробничій сфері. / Theoretical studies have expanded the theory of risks and supplemented it with the features of ergonomic risks in extreme conditions, in the non-production sphere. Практична цінність дослідження: (якщо є) / Practical implications (if applicable): Практичні результати досліджень, а саме розроблені заходи для зменшення або усунення ергономічних ризиків дадуть можливість підвищити рівень безпеки рятувальників під час виконання аварійно-рятувальних робіт та будуть корисними для практичної діяльності органів та підрозділів ДСНС України. / The practical results of the research, namely the developed measures to reduce or eliminate ergonomic risks, will make it possible to increase the level of safety of rescuers during emergency rescue operations and will be useful for the practical activities of the bodies and units of the State Emergency Service of Ukraine. Оригінальність/Цінність дослідження: / Originality/Value: For the first time, artificial intelligence for risk management, safety and compliance with regulatory requirements SoterAI was used to study ergonomic risks during emergency and rescue operations. The research was conducted on video footage of real events, during emergency and rescue operations of rescuers after enemy shelling. The developed measures will be useful in the practical activities of employees of the State Emergency Service of Ukraine. Обмеження дослідження/Майбутні дослідження: / Research limitations/Future research: Під час проведення досліджень використовувалась тільки одна методика, що не надало можливість порівняти отримані результати. Проведені дослідження не виробничих ергономічних ризиків стали основою для удосконалення існуючої технології та адаптації до невиробничої та екстремальної сфери. / During the research, only one methodology was used, which did not allow comparing the results obtained. The conducted research on non-production ergonomic risks became the basis for improving the existing technology and adapting it to the non-production and extreme sphere. Тип статті: / Paper type: науково-практична. / scientific and practical.

WANG Xiaofei, CHEN Ling

[Objective] In the context of the “dual carbon” goals, digitalization is the key approach for manufacturing enterprises to achieve energy-saving and carbon-reducing operations. Building upon an in-depth interpretation of the connotations of digitalization, this study tries to deconstruct the mechanism of how digital transformation drives energy saving and carbon reduction. In doing so, this study aims to enrich micro-level research perspectives and provide new insights for the research on the new integration of digitization and greening in enterprises. [Methods] Using questionnaire survey data collected from 704 manufacturing enterprises in China, Germany, and Brazil, this study employed an ordered Probit model and a mediation effect model to systematically evaluate the energy-saving and carbon-reducing effects, heterogeneous characteristics, and influencing pathways of digital transformation. [Results] (1) The digital transformation of enterprises had a significantly positive effect on energy saving and carbon reduction. (2) Digital transformation achieved energy saving and carbon reduction by improving enterprises' energy utilization efficiency, technological R&D capabilities, coordinated collaboration, and supply-demand matching capabilities. (3) The positive effect of digitization on energy saving and carbon reduction was more pronounced for enterprises closer to upstream sectors in the industry chain and with higher industry technology levels. Digital transformation in Chinese and German manufacturing enterprises greatly promoted energy saving and carbon reduction, whereas this effect was not significant in Brazilian manufacturing enterprises. [Conclusion] This study confirms the energy-saving and carbon-reducing effects of digital transformation, which is realized through two influence paths: the production process and the management process. In production processes, these effects manifest as improved energy utilization and R&D capabilities driven by technological progress. In management processes, they are reflected in strengthened coordinated collaboration and supply-demand matching capabilities resulting from reduced information asymmetry.

Pu Tingqian, Zulkafli Abdul Hadi

Background: In the contemporary business environment, corporate research and development (R&D) expenditure is pivotal for fostering technological innovation and advancing technological progress. While much research has focused on the influence of boards of directors on corporate innovation, the role of foreign directors in shaping corporate R&D expenditure, particularly in developing countries, remains underexplored. Purpose: The aim of this paper is to investigate the pivotal role of foreign directors in corporate R&D expenditure within Chinese listed manufacturing firms. It also provides micro-level evidence of the economic consequences of foreign directors, considering heterogeneity across property rights, industry, regional dimensions, and board positions. Study design/methodology/approach: This study utilizes the largest and most detailed dataset of Chinese listed manufacturing firms in the CSMAR database, offering comprehensive proxy variables. The sample encompasses 18,273 observations from 2008 to 2021. Multivariate regression models, employing static two-way fixed effects models with clustered robust standard errors and dynamic generalized method of moment (GMM) models, were established to investigate the relationship between foreign directors and corporate R&D expenditure. Sensitivity tests involve the substitution of dependent and core explanatory variables. Moreover, heterogeneity test and situational analysis are conducted. Findings/conclusions: The results confirmed a significant augmentation in corporate R&D expenditure attributable to foreign directors. Heterogeneity analysis reveals that the positive impact of foreign directors on R&D expenditure is more pronounced in private-owned enterprises, high-tech industries, and economically developed regions of China. Situational analysis further confirms that foreign independent directors are the main driving force behind this effect. Limitations/future research: This research is confined to a single-country and single-industry sample, without a comprehensive consideration of the individual traits of foreign directors. Future research avenues could involve cross-national comparisons and a more nuanced categorization of foreign directors.

Prof. Dr. Sri Setyo Iriani, Nuswantara Dian Anita, Pribadi Farid et al.

Purpose – This research analyzes the competitive advantage of tourist villages influenced by VRIN and non-VRIN resources on the performance of tourist village businesses. The sporadic nature of village tourism development and the difficulty of getting out of the pioneer level are the problems raised in this study. Design/methodology/approach –This research collected primary data on respondents who were workers from tourist villages, according to the established criteria. A total of 383 research respondents were obtained from distributing questionnaires. Using a quantitative approach, this study analyzed the relationship between VRIN resource and non-VRIN resource variables on competitive advantage, which then affects business performance Findings – The research of the study shows that VRIN resources significantly influence competitive advantage, which then affects business performance. The results of the study also show that non-VRIN resources do not affect competitive advantage. This shows how VRIN resources play a role in forming the unique value of tourist villages as well as traditional resources that are no longer relevant in forming the competitive advantages of tourist villages. Research limitations/implications – This research has limitations in generalizing the research results, where the research context was only conducted in Indonesia, precisely in East Java. Further research can develop the research by adding the geographical scope of the research sample. Practical implications – This research underlines the importance of strategic development of tourist villages based on a resource-based view approach. Development based on intangible assets, integration, and collaboration with other parties can be done by tourist villages. Originality/value – The use of the resource-based view approach in analyzing the competitive advantage of tourist villages is still not widely used, which then becomes the unique value of this research.

Julian Golak, Alexander Grigoriev, Freija van Lent et al.

In inland waterways, the efficient management of water lock operations impacts the level of congestion and the resulting uncertainty in inland waterway transportation. To achieve reliable and efficient traffic, schedules should be easy to understand and implement, reducing the likelihood of errors. The simplest schedules follow periodic patterns, reducing complexity and facilitating predictable management. Since vessels do not arrive in perfectly regular intervals, periodic schedules may lead to more wait time. The aim of this research is to estimate this cost by evaluating how effective these periodic schedules manage vessel traffic at water locks. The first objective is to estimate a periodic arrival pattern that closely matches a dataset of irregular vessel arrivals at a specific lock. We develop an algorithm that, given a fixed number of vessel streams, solves the problem in polynomial time. The solution then serves as input for the subsequent part, where we consider algorithms that compute operational schedules by formulating an optimisation problem with periodic arrival patterns as input, and the goal is to determine a periodic schedule that minimises the long-run average waiting time of vessels. We present a polynomial-time algorithm for the two-stream case and a pseudo-polynomial-time algorithm for the general case, along with incremental polynomial-time approximation schemes. In our numerical experiments, use AIS data to construct a periodic arrival pattern closely matching the observed data. Our experiments demonstrate that when evaluated against actual data, intuitive and straightforward policies often outperform optimal policies specifically trained on the periodic arrival pattern.

Li Yang, Mirna El Rajab, Abdallah Shami et al.

Zero-Touch Networks (ZTNs) represent a state-of-the-art paradigm shift towards fully automated and intelligent network management, enabling the automation and intelligence required to manage the complexity, scale, and dynamic nature of next-generation (6G) networks. ZTNs leverage Artificial Intelligence (AI) and Machine Learning (ML) to enhance operational efficiency, support intelligent decision-making, and ensure effective resource allocation. However, the implementation of ZTNs is subject to security challenges that need to be resolved to achieve their full potential. In particular, two critical challenges arise: the need for human expertise in developing AI/ML-based security mechanisms, and the threat of adversarial attacks targeting AI/ML models. In this survey paper, we provide a comprehensive review of current security issues in ZTNs, emphasizing the need for advanced AI/ML-based security mechanisms that require minimal human intervention and protect AI/ML models themselves. Furthermore, we explore the potential of Automated ML (AutoML) technologies in developing robust security solutions for ZTNs. Through case studies, we illustrate practical approaches to securing ZTNs against both conventional and AI/ML-specific threats, including the development of autonomous intrusion detection systems and strategies to combat Adversarial ML (AML) attacks. The paper concludes with a discussion of the future research directions for the development of ZTN security approaches.

Moslem Uddin, Huadong Mo, Daoyi Dong

This study presents an integrated energy management strategy for cost optimization in multi-energy community microgrids (MGs). The proposed approach combines storage-based peak shaving, economic dispatch of diesel generators, and efficient utilization of renewable energy sources to enhance energy management in community MGs. The efficacy of the energy management system (EMS) was validated through a simulation case study for a rural Australian community. The results demonstrate that the proposed EMS effectively reduces the peak energy demand by up to 43%, lowers operational costs by 84.63% (from $189,939/year to $29,188/year), and achieves a renewable energy utilization of 92.3%, up from 47.8% in the base system. Furthermore, the levelized cost of energy was reduced by 14.21% to $0.163/kWh. The strategy ensures an uninterrupted power supply during grid outages by utilizing DGs and battery energy storage systems. The environmental benefits included a 196.4% reduction in CO2 emissions and 100% reductions in CO, unburned hydrocarbons, and particulate matter. These findings validate the feasibility of the proposed EMS in achieving cost-effective, reliable, and sustainable energy management in community MGs. These findings contribute to the field by introducing a novel approach and demonstrating the practical feasibility of multi-energy MGs.

Genevieve Smith, Natalia Luka, Merrick Osborne et al.

Since 2022, generative AI (genAI) has rapidly become integrated into workplaces. Though organizations have made commitments to use this technology "responsibly", how organizations and their employees prioritize responsibility in their decision-making remains absent from extant management theorizing. In this paper, we examine how product managers - who often serve as gatekeepers in decision-making processes - implement responsible practices in their day-to-day work when using genAI. Using Institutional Theory, we illuminate the factors that constrain or support proactive responsible development and usage of genAI technologies. We employ a mixed methods research design, drawing on 25 interviews with product managers and a global survey of 300 respondents in product management-related roles. The majority of our respondents report (1) widespread uncertainty regarding what "responsibility" means or looks like, (2) diffused responsibility given assumed ethical actions by other teams, (3) lack of clear incentives and guidance within organizations, and (4) the importance of leadership buy-in and principles for navigating tensions between ethical commitments and profit motives. However, our study finds that even in highly uncertain environments, absent guidance from leadership, product managers can "recouple" ethical commitments and practices by finding responsibility "micro-moments". Product managers seek out low-risk, small-scale actions they can take without explicit buy-in from higher-level managers, such as individual or team-wide checks and reviews and safeguarding standards for data. Our research highlights how genAI poses unique challenges to organizations trying to couple ethical principles and daily practices and the role that middle-level management can play in recoupling the two.

I Made Sukresna, Jesca Edward Mikina

Environmental concerns have led to increased environmentally conscious practices and the production of green products. However, in an emerging country like Tanzania, young Tanzanian consumers have shown less responsiveness, necessitating an exploration of the factors influencing their purchase behaviour. This study investigates the factors influencing young Tanzanian consumers' decision to buy green products. A quantitative approach was conducted using structured online questionnaires to collect data from 161 individuals aged 18 to 35. The data is analysed using Partial Least Squares-Structural Equation Modeling. Results reveal that environmental consciousness and price perception positively influence green product awareness, while green advertising does not. Environmental consciousness exhibits a more significant influence over price perception. Subsequently, green product awareness positively influences green-product buying decisions. These findings indicate that young Tanzanian consumers know about green issues and are ready to pay more for green products. Businesses and policymakers can develop more effective strategies to promote sustainable behaviours and facilitate the transition to a greener economy. This study provides valuable insights into the critical factors driving the purchasing behaviour of green products among young consumers, emphasising the need for targeted efforts to encourage sustainable consumption in emerging economies.

Rita Ambarwati, Dedy, Rohman Dijaya et al.

This research aims to identify and investigate human resource and operational risk control activities to support power plant productivity after the pandemic. In various facets of business operations, including financial, operational, and reputational impacts, the bow-tie approach and Business Impact Analysis (BIA) are employed to assess consequences and identify risks. The study involved informants who met specific criteria, including permanent employees with a minimum of five years of service, a comprehensive understanding of their field's work processes, holding a minimum supervisory level position, or being a member of the COVID-19 task force. The BIA risk analysis revealed three primary priority areas characterized by the highest level of risk: operation-2 (maintenance activities), environment-1 (environmental and occupational health and safety concerns), and finance (financial considerations). These priorities were determined based on Risk to Production (RTP) values and Mean Time to Production Downtime (MTPD). Analysis of Focus Group Discussions (FGD) results identified four high-risk areas interrelated with the three objectives identified by the Business Impact Analysis (BIA) assessment. These high-risk areas include the workshop, warehouse, administration building, and CHCB. The Bow-Tie analysis was subsequently implemented. The results of Corrective and Preventive Actions (CAPA) from Bow-Tie analysis serve as a reference for the development of Standard Operating Procedures (SOPs), Implementation Guidelines, and Work Instructions (WIs) related to labor mitigation operations in the context of post-pandemic prevention efforts. The proposed strategy encompasses effective risk management measures to ensure uninterrupted business operations, enhancing clarity in risk communication and a comprehensive understanding of potential ramifications.

Chutian Ma, Paul Smith

We consider a simplified model for optimizing a single-asset portfolio in the presence of transaction costs given a signal with a certain autocorrelation and cross-correlation structure. In our setup, the portfolio manager is given two one-parameter controls to influence the construction of the portfolio. The first is a linear filtering parameter that may increase or decrease the level of autocorrelation in the signal. The second is a numerical threshold that determines a symmetric "no-trade" zone. Portfolio positions are constrained to a single unit long or a single unit short. These constraints allow us to focus on the interplay between the signal filtering mechanism and the hysteresis introduced by the "no-trade" zone. We then formulate an optimization problem where we aim to minimize the frequency of trades subject to a fixed return level of the portfolio. We show that maintaining a no-trade zone while removing autocorrelation entirely from the signal yields a locally optimal solution. For any given "no-trade" zone threshold, this locally optimal solution also achieves the maximum attainable return level, and we derive a quantitative lower bound for the amount of improvement in terms of the given threshold and the amount of autocorrelation removed.

Roman Lukyanenko

In an era dominated by information technology, the critical discipline of data management remains undervalued compared to the innovations it enables, such as artificial intelligence and social media. The ambiguity surrounding what constitutes data management and its associated activities complicates efforts to explain its importance and ensure data are collected, stored and used in a way that maximizes value and avoids failures. This paper aims to address these shortcomings by presenting a simple framework for understanding data management, referred to as MAGIC. MAGIC encompasses five key activities: Modeling, Acquisition, Governance, Infrastructuring, and Consumption support tasks. By delineating these components, the MAGIC framework provides a clear, accessible approach to data management that can be used for teaching, research and practice.

Star Dawood Mirkhan, Skala Kamaran Omer, Hussein Mohammed Ali et al.

Delegation and leadership are critical components of software management, as they play a crucial role in determining the success of the software development process. This study examined the relationship between delegation and leadership in software management and the impact of these factors on project outcomes. Results showed that effective delegation and transformational leadership styles can improve workflow, enhance team motivation and productivity, and ultimately lead to successful software development projects. The findings of this study have important implications for software management practices, as they suggest that organizations and software managers should prioritize the development of effective delegation and leadership practices to ensure the success of their software development initiatives. Further research is needed to explore the complex interplay between delegation and leadership in software management and to identify best practices for improving these processes.

Rachel E. Mason, Nicholas R. Vaughn, Gregory P. Asner

We describe the production of maps of buildings on Hawai’i Island, based on complementary information contained in two different types of remote sensing data. The maps cover 3200 km² over a highly varied set of landscape types and building densities. A convolutional neural network was first trained to identify building candidates in LiDAR data. To better differentiate between true buildings and false positives, the CNN-based building probability map was then used, together with 400–2400 nm imaging spectroscopy, as input to a gradient boosting model. Simple vector operations were then employed to further refine the final maps. This stepwise approach resulted in detection of 84%, 100%, and 97% of manually labeled buildings, at the 0.25, 0.5, and 0.75 percentiles of true building size, respectively, with very few false positives. The median absolute error in modeled building areas was 15%. This novel integration of deep learning, machine learning, and multi-modal remote sensing data was thus effective in detecting buildings over large scales and diverse landscapes, with potential applications in urban planning, resource management, and disaster response. The adaptable method presented here expands the range of techniques available for object detection in multi-modal remote sensing data and can be tailored to various kinds of input data, landscape types, and mapping goals.

Saiqa Aleem, Luiz Fernando Capretz, Faheem Ahmed

Variability management (VM) in software product line engineering (SPLE) is introduced as an abstraction that enables the reuse and customization of assets. VM is a complex task involving the identification, representation, and instantiation of variability for specific products, as well as the evolution of variability itself. This work presents a comparison and contrast between existing VM approaches using qualitative meta-synthesis to determine the underlying perspectives, metaphors, and concepts of existing methods. A common frame of reference for the VM was proposed as the result of this analysis. Putting metaphors in the context of the dimensions in which variability occurs and identifying its key concepts provides a better understanding of its management and enables several analyses and evaluation opportunities. Finally, the proposed framework was evaluated using a qualitative study approach. The results of the evaluation phase suggest that the organizations in practice only focus on one dimension. The presented frame of reference will help the organization to cover this gap in practice.

Wentao Zhang, Yilei Zhao, Shuo Sun et al.

Portfolio management (PM) is a fundamental financial trading task, which explores the optimal periodical reallocation of capitals into different stocks to pursue long-term profits. Reinforcement learning (RL) has recently shown its potential to train profitable agents for PM through interacting with financial markets. However, existing work mostly focuses on fixed stock pools, which is inconsistent with investors' practical demand. Specifically, the target stock pool of different investors varies dramatically due to their discrepancy on market states and individual investors may temporally adjust stocks they desire to trade (e.g., adding one popular stocks), which lead to customizable stock pools (CSPs). Existing RL methods require to retrain RL agents even with a tiny change of the stock pool, which leads to high computational cost and unstable performance. To tackle this challenge, we propose EarnMore, a rEinforcement leARNing framework with Maskable stOck REpresentation to handle PM with CSPs through one-shot training in a global stock pool (GSP). Specifically, we first introduce a mechanism to mask out the representation of the stocks outside the target pool. Second, we learn meaningful stock representations through a self-supervised masking and reconstruction process. Third, a re-weighting mechanism is designed to make the portfolio concentrate on favorable stocks and neglect the stocks outside the target pool. Through extensive experiments on 8 subset stock pools of the US stock market, we demonstrate that EarnMore significantly outperforms 14 state-of-the-art baselines in terms of 6 popular financial metrics with over 40% improvement on profit.

Nuryakin, Fatmawati Indah, Siriyota Kumpanat

This study examined CRM’s effect on marketing performance and customer focus strategies. It also investigates the moderating role of environmental uncertainty in the relationship between CRM and customer focus on marketing performance. A quantitative research approach was used with a sample of the service industry in two countries, Indonesia and Thailand. The analysis unit was the manager responsible for customer relations. The number of examined surveys amounted to 406, with a distribution of 200 respondents from Thailand and 206 — from Indonesia. The purposive sampling approach was used. The study results indicated that CRM had a positive effect on marketing performance and customer focus. The latter positively affected marketing performance. The study also found that environmental uncertainty strengthened the relationship between CRM and the customer focus on marketing.

Radu Burlacu, Patrice Fontaine, Sonia Jimenez-Garcès

We use the Grossman \& Stiglitz (1980) framework to build a reference portfolio for uninformed investors and employ this portfolio to assess the performance of actively managed equity mutual funds. We propose an empirical methodology to construct this reference portfolio using the information on prices and supply. We show that mutual funds provide, on average, an insignificant alpha of 23 basis points per year when considering this portfolio as a reference. With the stock market index as a proxy for the market portfolio, the average fund alpha is negative and highly significant, --128 basis points per year. The results are robust when considering various subsets of funds based on their characteristics and their degree of selectivity. In line with rational expectations equilibrium models considering asymmetrically informed investors and partially revealing equilibrium prices, our study supports that active management adds value for uniformed investors.

Samira Hossein Ghorban, Bardyaa Hesaam

Product diversity is one of the prominent factors for customers' satisfaction, while from the firms' perspective, the additional engineering costs required for product diversity should not exceed the acquired profits from the increase in their market share. Thus, one of the critical decision-making tasks for companies is the selection of an optimal mix of products, namely product portfolio management (PPM). Traditional studies on PPM problem have paid relatively less attention to the actions of other competitors. In this paper, we study PPM problem in a competitive environment where each firm's objective is to maximize its expected shared surplus. We model the competition with an $n$-player game that optimal product portfolios are driven from its Nash equilibrium. Utility functions are determined by the expected value of the shared surplus. We analyze the strategic behavior of firms to determine their optimal product portfolios.