Management Technology Research Articles

Light and Shadow of the Digital Factory: Response to the Comments

Abstract This response to the comments on The Digital Factory discusses why and how the concepts of the digital factory and digital Taylorism have been applied in the book, as well as the question of the relationship between digital control and workers' resistance to algorithmic management technologies. While agreeing with the comments that point to the limitations of the concepts used, this response argues that these can be productive precisely by drawing our attention to aspects that are otherwise difficult to bring to light. In terms of the potential for workers' resistance, many collective and individual forms of such resistance remain possible in labour regimes under algorithmic management, as well as in other coexisting labour regimes.

Digital Tools in Language Learning: Optimizing Memory and Attention for College Students

College English teaching often encounters challenges related to students’ memory and attention in the educational process. This study aims to investigate the effectiveness of integrating memory and attention management technologies supported by the digital environment in college English teaching. To achieve this goal, the author use an action research method with testing as well as descriptive and statistical analysis. The experimental group studied using Quizlet and Busuu for one academic semester. The findings showed that the overall average scores of the experimental and control groups on the Sustained Attention test were 23.3 and 22.5, respectively. Additionally, an Automated Working Memory Assessment showed that the experimental group performed better on working memory tasks than the control group. These results highlighted the potential benefits of incorporating technology-integrated learning tools into language learning including improvements in language skills, attentional resource allocation, and working memory abilities. The novelty of this study lies in the combination of memory and attention management techniques, which are usually studied separately.

The Impact of the 2022 Electoral Reform on the Credibility of the 2023 General Elections in Nigeria

Over the years, Nigeria has faced serious election fraud, leading many Nigerians to lose confidence in the electoral process. In 2022, the new Electoral Act was introduced, creating more opportunities for the integration of technologies like BVAS and IREV to improve voter accreditation, result transmission, and real-time election viewership for all stakeholders. This development was welcomed by many Nigerians who hoped the Act would restore voter confidence in the country. However, the outcome of the elections, particularly the presidential elections, indicated that the Act failed to meet the expectations of Nigerians. This study therefore examined the Electoral Act 2022 and the election credibility of the 2023 elections. It explored why the Act failed to mitigate insecurity and ensure effective transmission and viewing of election results, which are key to free and fair elections. Using a mixed research approach to data collection and analysis, the study drew on direct responses from voters and stakeholders, scholarly literature, media reports, and findings from election observer groups. The results indicate that while the Act provides a legal framework for stronger elections in Nigeria, it has not sufficiently ensured a free and fair election in the presidential polls. The study concludes that the Act alone cannot guarantee transparent elections due to poor implementation by stakeholders and certain grey areas in the Act that were exploited for election manipulation. The researcher recommends revisiting or strengthening these grey areas to prevent manipulation by elites and ensuring effective implementation by all stakeholders. Specifically, the study suggests the integration of technological advancements, such as blockchain for secure voting, electronic voting systems to enhance accessibility, geospatial technology for better logistics management, and secure mobile applications for real-time results transmission, to further bolster election credibility and transparency in Nigeria.

UNRAVELING THE GENETIC AND BIOLOGICAL INTRICACIES OF ANESTHESIA FOR CHRONIC PAIN: A COMPREHENSIVE REVIEW OF COMT GENE VARIATIONS AND THEIR IMPACT ON TREATMENT EFFICACY ACROSS ETHNICITIES

Chronic pain management remains a significant challenge, with individual responses to anesthesia and analgesics varying widely due to genetic and biological factors. This review explores the influence of the catechol-O-methyltransferase (COMT) gene, particularly the Val158Met polymorphism, on pain sensitivity and opioid efficacy across different ethnicities. COMT variations play a crucial role in modulating pain perception and analgesic response, with Met allele carriers generally exhibiting higher pain sensitivity and lower opioid requirements. Ethnic differences in COMT gene frequencies further impact anesthesia efficacy, underscoring the importance of personalized pain management strategies. The review also discusses the potential of pharmacogenetic approaches, a beacon of hope for improving treatment outcomes. It highlights emerging technologies in genetic-based pain management, such as epigenetic modulation and gene editing.

The Difficult Airway in Patients with Cancer.

The goal of this review is to provide an overview of difficult airway management in the cancer population. Difficult airways can be unanticipated; however, several anatomical and physiological features may predict difficult airway management, with several specific for the cancer patient population. New technologies and techniques for airway management, including non-invasive oxygenation, and even the utilization of ECMO, have led to better outcomes and decreased morbidity. Furthermore, the incorporation of multidisciplinary airway teams has helped reduce morbidity associated with predicted and known difficult airways. Cancer patients may exhibit or develop anatomic and physiologic features that may predispose them to difficulty with airway management. As our technologies for airway management continue to advance, as well as further commitment to more interdisciplinary collaboration, difficult airway management in the cancer population will continue to become safer.

Economic development through sustainable energy transition: the impact of machine learning-driven energy efficiency in industrial sectors

The transition to sustainable energy systems is a critical component in addressing global environmental challenges and fostering economic development. Industrial sectors, which are major consumers of energy and contributors to greenhouse gas emissions, play a pivotal role in this transition. Machine learning (ML) technologies have emerged as transformative tools for enhancing energy efficiency in these sectors, offering significant potential for economic and environmental benefits. This review explores the impact of ML-driven energy efficiency on economic development, focusing on its application within various industrial contexts. The integration of machine learning into energy management systems allows for advanced predictive analytics, real-time monitoring, and process optimization. ML algorithms can analyze large datasets to forecast energy demand, detect inefficiencies, and optimize operational processes, leading to substantial cost savings and energy reductions. For example, in manufacturing industries, ML-driven solutions have been employed to enhance predictive maintenance, optimize production processes, and reduce energy consumption, resulting in lower operational costs and increased productivity. Similarly, in industrial facilities such as chemical plants and data centers, ML has been used to streamline energy management and minimize waste, demonstrating its versatility and effectiveness across diverse industrial applications. The economic impacts of ML-driven energy efficiency are profound. By reducing energy costs and improving operational performance, industries can achieve significant financial savings, which in turn can be reinvested into further innovations and growth. Additionally, the adoption of ML technologies fosters job creation and skill development in the tech and energy sectors, contributing to broader economic growth. Industries that leverage ML for energy efficiency gain a competitive advantage, positioning themselves favorably in the market and tapping into new opportunities for innovation and expansion. However, the transition to ML-driven energy efficiency is not without challenges. Issues related to data availability and quality, high implementation costs, and industry-specific constraints must be addressed to fully realize the benefits. Policymakers play a crucial role in facilitating this transition by developing supportive policies and regulations that encourage the adoption of ML technologies in energy management. Machine learning offers a transformative approach to achieving energy efficiency in industrial sectors, with significant implications for economic development. By addressing the challenges and leveraging emerging opportunities, industries and policymakers can drive sustainable energy transitions that benefit both the environment and the economy. This review provides a comprehensive analysis of these impacts and offers strategic recommendations for advancing ML-driven energy efficiency in the industrial sector. Keywords: Economic Development, Sustainable Energy, Machine Learning, Industrial Sectors.

Application of 5G network technology in agricultural production and information management

Establishing a management information system that adapts to the continuous development of agricultural production management today, adopting advanced 5G technology and means, and comprehensively managing the entire agricultural production is an inevitable trend in the development of agricultural production management. In order to improve the effect of agricultural production informatization management, this paper combines 5G (fifth-generation) network technology to construct agricultural production and informatization management models. In view of the massive dynamic agricultural production management data, this paper studies the efficient multi-copy management strategy, which can consider the two aspects of load balancing and energy efficiency at the same time, so as to achieve efficient data access and energy efficiency. Moreover, this paper introduces a time series-based file access heat calculation model. In terms of determining the number of copies of files, this paper proposes a copy factor allocation algorithm centered on the ranking of file access popularity, and gives a characteristic function. Through cluster analysis, it can be seen that the agricultural production informatization management model based on 5G technology proposed in this paper can effectively improve the efficiency of agricultural information management.

Expanding the Areas of Attraction of Solutions to Singularly Perturbed Equations

The article analyzes the state and development prospects of the transport and logistics system of automobile transport in the Kyrgyz Republic. The authors consider the key features of the functioning of the automobile sector in the context of the country’s transition economy. The work assesses the current state of automobile transportation of goods and passengers, examines the main problems hindering the increase in the efficiency of the transport and logistics system. These include low technical equipment of the vehicle fleet, insufficient development of the logistics infrastructure, imperfection of legal regulation, personnel shortage. The authors propose a set of measures aimed at modernizing and optimizing the functioning of automobile transport in Kyrgyzstan. Among the key areas are the renewal of the vehicle fleet, the development of a network of logistics centers and multimodal transportation, the introduction of information technologies in transportation management, and the improvement of state regulation of the industry. According to the authors, the implementation of the proposed measures will contribute to increasing the competitiveness and customer focus of automobile transport in the Kyrgyz Republic, which in turn will have a positive impact on the development of the national economy.

Assessing the prospects and constraints of blockchain technology for intellectual property management

AbstractThis study aims to assess the prospects and constraints of blockchain technology (BCT) for intellectual property management (IPM). It uses a qualitative method using existing literature related to BCT and IPM. Findings suggest that BCT has huge potential to transform IPM using BCT. The BCT can provide better transparency, security, and efficiency. BCT can be useful for increased transparency, trust, better licensing management, collaboration, innovation, and digital rights management. However, BCT has challenges in terms of standardization, interoperability, data privacy, security, accessibility, inclusivity, and integration with legacy systems. This paper will be useful for policymakers to implement the use of BCT in IPM.

A framework for modeling and simulating blockchain-based supply chain traceability systems

Traceability improves supply chain operations transparency, benefiting the overall performance and the end customer perception. Blockchain technology is a promising alternative to create robust traceability systems, as it promotes trust and supports information sharing based on data immutability. Despite the hype surrounding blockchain technology and the vast literature in the field, the effectiveness and efficiency of blockchain-based supply chain traceability systems remain uncertain across multiple industry sectors, due to the lack of empirical evidence. Considering its characteristics, simulation is a valuable tool to evaluate the performance of supply chain management processes and technology alternatives. However, a structured guide to support the building process of simulation models regarding blockchain in the supply chain is still missing, making it hard for modelers to create realistic simulation models. Thus, this work proposes a novel methodological framework with guidelines to develop HS models regarding supply chain traceability capable of integrating the main blockchain concepts for managerial purposes. Scenarios with different granularity levels may be designed through the combination of both discrete-event and agent-based simulation paradigms. The proposed approach integrates concepts and terminologies from foundational references, including the Supply Chain Operations Reference (SCOR) model and the Global Traceability Standard (GTS). In addition, it is anchored on the ADACOR holonic architecture for the agentification process. Following the Design Science Research methodology, a proof-of-concept application is presented, based on a real-scale industrial case of a lobster supply chain from Canada. Results obtained reflect the framework's versatility to assist the development of a hybrid simulation model, as traceability is explored through the perspectives of time to react, item separation, temporal screening, and blockchain participation rate.

Paraffin/graphite/boron nitride composite as a novel phase change material for rapid heat absorption in battery thermal management technology

Phase change material (PCM) cooling is widely employed in the thermal management of compact battery packs. Thermal protection triggered by rapid temperature rise shortens the effective discharge time in high-rate discharge, making it essential to prepare PCM that rapidly absorbs heat at high temperatures. However, research on the thermal absorption performance and insulating properties of PCM at high-rate discharge remains limited. Herein, we innovatively propose a thermally conductive and insulating PCM with a wide phase transition temperature to address the overheating issue in batteries at 7 C, 8 C and 9 C discharge rates. The C236 consists of paraffin (PA236), graphite and boron nitride with a ratio of 6: 2: 2, which achieves outstanding thermal performance with a latent heat of up to 138.0 J/g and a high-volume resistivity of 1.6 × 108 Ω·m. It is found that at a discharge rate of 7 C, the C236 with a thickness of 3 mm effectively maintains the temperature below 80 °C. At discharge rates of 8 C and 9 C, the PCM significantly reduces the battery temperature by 26.9 % and 32.5 %, respectively, highlighting the rapid heat absorption capability at high temperatures. Furthermore, after four cycles at a 9 C discharge rate, the temperature differential of the battery remains below 5 °C. The low-cost PCM provides a new experimental reference for battery thermal management in high-rate discharge, with broad application prospects.

Advanced Technologies for Sustainable Water Management: A Comprehensive Review

This review paper provides a comprehensive analysis of the latest advancements in water management technology, focusing on the integration of Internet of Things (IoT), machine learning, blockchain, and other emerging technologies. The study examines 19 key research papers, exploring various methodologies, key outcomes, and the challenges associated with these technologies. While significant progress has been made in improving water resource management through real-time monitoring, predictive analytics, and decentralized data management, several challenges persist, including high implementation costs, integration complexities, and the need for standardized protocols. The review identifies opportunities for future research, particularly in developing cost-effective solutions, enhancing interoperability, and advancing artificial intelligence applications in water management. Additionally, the paper highlights the importance of evolving regulatory frameworks and increasing public awareness to ensure the successful adoption of these technologies. The findings of this review contribute to the ongoing efforts to create more sustainable and efficient water management systems capable of addressing the growing global water demand.

Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management.

The Internet of Things (IoT) base has grown to over 20 billion devices currently operational worldwide. As they greatly extend the applicability and use of biosensors, IoT developments are transformative. Recent studies show that IoT, coupled with advanced communication frameworks, such as machine-to-machine (M2M) interactions, can lead to (1) improved efficiency in data exchange, (2) accurate and timely health monitoring, and (3) enhanced user engagement and compliance through advancements in human-computer interaction. This systematic review of the 19 most relevant studies examines the potential of IoT in health and lifestyle management by conducting detailed analyses and quality assessments of each study. Findings indicate that IoT-based systems effectively monitor various health parameters using biosensors, facilitate real-time feedback, and support personalized health recommendations. Key limitations include small sample sizes, insufficient security measures, practical issues with wearable sensors, and reliance on internet connectivity in areas with poor network infrastructure. The reviewed studies demonstrated innovative applications of IoT, focusing on M2M interactions, edge devices, multimodality health monitoring, intelligent decision-making, and automated health management systems. These insights offer valuable recommendations for optimizing IoT technologies in health and wellness management.

Revenue effects of Denuvo digital rights management on PC video games

In the personal computer video game market, a digital rights management (DRM) technology called Denuvo has been used since 2014 to restrict software usage to legitimate buyers, thereby preventing piracy. Sometimes Denuvo DRM is bypassed or “cracked”, after which the video game can be pirated. I exploit the randomness with which Denuvo is cracked to estimate the effect Denuvo has on protecting revenue from piracy displacement. When Denuvo is cracked very early on, piracy leads to an estimated 20 percent fall in total revenue on average relative to an uncracked counterfactual, but that effect is weaker the longer it takes for Denuvo to be cracked. When Denuvo survives for at least 12 weeks, piracy leads to nearly zero total revenue loss on average. The results suggest that Denuvo does protect legitimate sales to an estimated mean of 15 percent of total revenue and median of 20 percent, but there is little justification to employ Denuvo long-term (i.e. for more than three months), especially given that Denuvo can have negative technical side effects and is generally disliked by users.

Unlocking potential for a circular bioeconomy transition through digital innovation, lean manufacturing and green practices: a review

PurposeToday’s businesses are looking for a circular bioeconomy (CBE) to develop a sustainable manufacturing process as industrial operations result in significant amounts of waste materials and the depletion of natural sources. The industry commonly applies techniques such as lean manufacturing (LM), digital innovations (DI) and green practices (GP) for operational and quality improvement. However, publications explaining how these technologies enable the CBE transition are scarce. This study examines CBE components, common practices of each technology facilitating the CBE transition, problems of solitary technology deployment as well as coupling technologies for the CBE transition.Design/methodology/approachA scoping review was conducted to analyse previous studies in this new field. The data collection is in a quantitative manner, but the data synthesis process follows a similar method of synthesising data in the grounded theory method, which includes familiarisation with the data, open-coding and finalisation of the themes.FindingsCritical components of CBE were identified as biobased goods, industry symbiosis, material resource efficiency, renewable energy, product lifecycle and sharing economy. GP is the most prominent in moderating the CBE transition. We identify each technology has coupled relationships (Lean-4.0, Green-Lean and Green-4.0) technologies facilitated by the circularity concept, which form the core pillars of enablers and advance the CBE paradigm.Research limitations/implicationsThis study demonstrates that combining lean principles with green technology and digital technologies can effectively decrease waste and resource usage in biobased manufacturing processes, therefore endorsing the concept of resource efficiency in circular bioeconomy models.Practical implicationsThe results allow entrepreneurs to strategically incorporate different existing technologies to meet CBE fundamental objectives by initiating it with dual technologies and facilitate industry professionals and regulators to support the improvement of environmental sustainability performance in the manufacturing industry. The management will be able to focus on the common practices across the technologies, which have a dual benefit for both operational and environmental performance.Originality/valueThe paper makes the first attempt to present the synergic impact of the three quality management technologies on a new concept of sustainability, CBE.

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H2) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO2) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO2 emissions in 2050. Achieving this net-zero CO2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $250 and $500 per ton CO2 when DACCS deployed as a backstop. The average CO2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO2/year, which implies a substantial upscaling of capacity to move and store CO2. Hydrogen sensitivity scenarios showed that H2 typically constituted a relatively small share of the overall U.S. energy system; however, H2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

Using Blockchain Technology for Sustainability and Secure Data Management in the Energy Industry: Implications and Future Research Directions

Using Blockchain Technology for Sustainability and Secure Data Management in the Energy Industry: Implications and Future Research Directions

Ethical Practices and Efficiency in the Internal Control of Peruvian Public Transport

The study aims to assess the impact of ethical practices on the effectiveness of internal control in public transport companies in Peru, to understand how these aspects influence corporate integrity, customer trust and corporate reputation; a quantitative, descriptive and explanatory methodology was used; data were collected through structured surveys applied to 50 employees of a transport company, covering various areas such as sales, administration and internal control; it is concluded that ethical practices significantly influence the effectiveness of internal control. Deficiencies in these areas lead to loss of customer confidence and financial and legal risks. The integration of sound ethical practices into business culture and processes improves management, customer confidence and business sustainability; highlights the need to improve integrity and operational efficiency in transport companies. It recommends implementing ethics training programmers and strengthening internal control systems adapted to the local context, as well as integrating advanced technologies for risk management and visualization.Corporate Governance

Challenges Facing the Use of Remote Sensing Technologies in the Construction Industry: A Review

Remote sensing is essential in construction management by providing valuable information and insights throughout the project lifecycle. Due to the rapid advancement of remote sensing technologies, their use has been increasingly adopted in the architecture, engineering, and construction industries. This review paper aims to advance the understanding, knowledge base, and practical implementation of remote sensing technologies in the construction industry. It may help support the development of robust methodologies, address challenges, and pave the way for the effective integration of remote sensing into construction management processes. This paper presents the results of a comprehensive literature review, focusing on the challenges faced in using remote sensing technologies in construction management. One hundred and seventeen papers were collected from eight relevant journals, indexed in Web of Science, and then categorized by challenge type. The results of 44 exemplary studies were reported in the three types of remote sensing platforms (satellite, airborne, and ground-based remote sensing). The paper provides construction professionals with a deeper understanding of remote sensing technologies and their applications in construction management. The challenges of using remote sensing in construction were collected and classified into eleven challenges. According to the number of collected documents, the critical challenges were shadow, spatial, and temporal resolution issues. The findings emphasize the use of unmanned airborne systems (UASs) and satellite remote sensing, which have become increasingly common and valuable for tasks such as preconstruction planning, progress tracking, safety monitoring, and environmental management. This knowledge allows for informed decision-making regarding integrating remote sensing into construction projects, leading to more efficient and practical project planning, design, and execution.

From pollution to resource: advancing swine waste treatment in the USA

Concentrated animal feeding operations (CAFOs) have led to environmental challenges, specifically waste management. Swine CAFOs generate large amounts of waste, requiring proper treatment to avoid air and water pollution. Conventional waste management technologies, such as lagoon and spray field systems, do not prevent air and water pollution impacts. Research for the past few decades led to recommendations for waste treatment technologies superior to lagoons and spray fields. Private environmental sustainability initiatives focused on reducing greenhouse gas emissions in the food supply chain have implemented biogas digester projects for capturing methane in covered swine lagoons to reduce greenhouse gas emissions. However, research indicates that methane capture alone does not solve the broader pollution issues associated with lagoon and spray field systems still in use at these CAFOs to dispose of digested effluents. The Environmentally Superior Technologies (EST) initiative in North Carolina set public standards to eliminate waste discharge, reduce atmospheric emissions, and control odors and pathogens. Research has confirmed that technologies coupling solids separation with water treatments to remove volatile organic carbon, pathogens, and reactive forms of nitrogen can meet EST standards. A designated EST—the Super Soil System—substantially reduced odor by 99.9%; pathogens by 99.99%, nutrients (phosphorus and nitrogen) by >90%, and heavy metals (cooper and zinc) by 99%. The ammonia emissions were reduced by 94.4% for the warm and 99.0% for the cool season with respect to a conventional lagoon system. Corresponding greenhouse gas emission reductions were 96.7%. Components of designated EST can be applied to retrofit covered lagoons and anaerobic digestion systems with significant environmental benefits. Recommendations are proposed, based on the collective experience with EST and current trends in animal production concentration, for environmentally safe technologies to handle excess manure produced in the USA.