Technological Capabilities Research Articles

Strategic redesign of business processes in the digital age: A framework

Organizations constantly seek ways to improve their business processes by using digital technologies as enablers. However, simply substituting an existing technology with a new one has limited value compared to using the capabilities of digital technologies to redesign business processes. Therefore, process analysts try to understand how the capabilities of digital technologies can enable the redesign of business processes. In this paper, we conduct a systematic literature review and examine 40 case studies where digital technologies were used to redesign business processes. We identified that, within the context of business process improvement, capabilities of digitalization, communication, analytics, digital representation, and connectivity can enable business process redesign. Furthermore, we note that these capabilities enable applying nine redesign heuristics. Based on our review, we map how each capability can facilitate the implementation of specific redesign heuristics. Finally, we illustrate how such a capability-driven approach can be applied to Metaverse as an example of a digital technology. Our mapping and classification framework can aid analysts in identifying candidate redesigns that capitalize on the capabilities of digital technologies.

Large language models and their applications in bioinformatics

Recent advancements in Natural Language Processing (NLP) have been significantly driven by the development of Large Language Models (LLMs), representing a substantial leap in language-based technology capabilities. These models, built on sophisticated deep learning architectures, typically transformers, are characterized by billions of parameters and extensive training data, enabling them to achieve high accuracy across various tasks. The transformer architecture of LLMs allows them to effectively handle context and sequential information, which is crucial for understanding and generating human language. Beyond traditional NLP applications, LLMs have shown significant promise in bioinformatics, transforming the field by addressing challenges associated with large and complex biological datasets. In genomics, proteomics, and personalized medicine, LLMs facilitate identifying patterns, predicting protein structures, or understanding genetic variations. This capability is crucial, e.g., for advancing drug discovery, where accurate prediction of molecular interactions is essential. This review discusses the current trends in LLMs research and their potential to revolutionize the field of bioinformatics and accelerate novel discoveries in the life sciences.

Low Network Power Challenges in IoT-Based Applications in Smart Cities

The emergence of Internet of Things (IoT) technologies has led to the development of smart cities, potentially improving urban life through efficient and effective use of resources. The success of IoT-based applications in smart cities is contingent on several factors, including network power challenges. Deploying IoT-based applications in smart cities requires a reliable and efficient network infrastructure to ensure smooth and uninterrupted data communication. One of the significant challenges faced in this regard is low network power, which can significantly impact the performance of IoT devices and, consequently, the entire smart city system. This article addresses the issue of low network power in IoT-based applications in smart cities. It investigates the causes of this problem and the potential solutions that can be adopted to mitigate its impact. The article also highlights the importance of network power management in the context of IoT-based applications in smart cities. By implementing effective network power management techniques, it is possible to optimize the performance of IoT devices and extend their battery life, thus ensuring the overall efficiency and sustainability of the smart city system. The article concludes by emphasizing the need for continuous research and development to overcome the challenges of low network power and further enhance IoT technology's capabilities in smart cities.

An analytical approach for identifying trend-seasonal components and detecting unexpected behaviour in psychological time-series.

The recent advances in technological capabilities have led to a massive production of time-series data and remarkable progress in longitudinal designs and analyses within psychological research. However, implementing time-series analysis can be challenging due to the various characteristics and complexities involved, as well as the need for statistical expertise. This paper introduces a statistical pipeline on time-series analysis for studying the changes in a single process over time at either a population or individual level, both retrospectively and prospectively. This is achieved through systemization and extension of existing modelling and inference techniques. This analytical approach enables practitioners not only to track but also to model and evaluate emerging trends and apparent seasonality. It also allows for the detection of unexpected events, quantifying their deviations from baseline and forecasting future values. Given that other discernible population- and individual-level changes in psychological and behavioural processes have not yet emerged, continued surveillance is warranted. A near real-time monitoring tool of time-series data could guide community psychological responses across multiple ecological levels, making it a valuable resource for field practitioners and psychologists. An empirical study is conducted to illustrate the implementation of the introduced analytical pipeline in practice and to demonstrate its capabilities.

Tuning Nanochannel Microenvironments of a Thermoresponsive MXene Membrane for Mixed Molecule Gradient Separation.

Drawing inspiration from dynamic biological ion channels, researchers have developed various artificial membranes featuring responsive nanochannels. Typically, these membranes modify mass transport behaviors by manipulating the responsive layer on the inner surfaces of the intrinsic layer. In this study, we build two-dimensional lamellar membranes composed of titanium carbide MXene and poly(N-isopropylacrylamide), endowed with dual-level regulatable nanochannels, achieved through adjustments of nanochannel microenvironments. The size of these two-dimensional nanochannels can be altered by both the thermoresponsive polymer layer and the intrinsic MXene layer that could undergo spontaneous oxidation. The multilevel regulation strategy substantially enhances the molecular selectivity of MXene separation membranes, which is further applied for precise gradient separation toward multiple molecules. This advancement showcases the versatility and transformative capabilities of responsive nanochannel technology, setting the stage for innovative developments in diverse fields.

The impact of agile supply chain strategy on manufacturers’ ambidextrous innovation—the role of relational governance and information technology capability

The impact of agile supply chain strategy on manufacturers’ ambidextrous innovation—the role of relational governance and information technology capability

A-257 Revolutionizing Fungal Infection Diagnosis: A Sensitive, Cost-Effective, and Time-Efficient Solution

Abstract Background Fungal infection detection is essential for optimizing therapeutic strategies, preventing complications, enhancing overall health, and alleviating the financial burden, and preventing transmission. According to the CDC, fungal illness resulted in 75,000 hospital admissions and 9 million outpatient visits annually, with 7,199 deaths predicted in the United States in 2021. The rising prevalence of fungal infections, influenced by factors such as population expansion and evolving treatment strategies poses a growing challenge to achieving an early and accurate diagnosis. There is the crucial need for improved detection methods to promptly identify various fungal infections, including Candida species, spanning from skin issues to potentially fatal systemic diseases, ultimately reducing associated morbidity and mortality. Severe and profound infections with life-threatening potential are common in individuals with compromised immune systems and those who are hospitalized. This risk is notably elevated among patients with organ transplants, immunosuppressive treatments, diabetes, recent broad-spectrum antibiotic usage, catheter utilization, and extended hospitalization periods. Our advancement seeks to introduce innovative methods leveraging carbon-based nanomaterials for the detection of fungal infections, offering distinct advantages including cost-effectiveness, ease of operation, and time efficiency compared to conventional techniques. Methods Our technology utilizes carbon-based nano materials, a promising advancement in nanotechnology to detect fungal infections, especially Candida manifestations. The samples are brought into contact with pre-probed carbon-based nano materials sensors maintained at a specific annealing temperature, facilitating nucleic acid hybridization. Subsequently, alterations in the carbon nanotube's electrical signal are observed, indicating a change in conductivity. This change can allow for the measurement of a voltage difference across a continuous flow of electricity, correlating with the concentration of targets present in the sample, thereby enabling the detection of specific microorganisms. No change was noticed in electrical properties of carbon-based nano material when negative experiments were conducted. Results The initial findings showed the presence of specific microorganisms within the sample in less than 15 minutes with carbon-based nano materials sensors. Comparative analysis of the electrical signal magnitude values obtained from carbon nanotube measurements against the corresponding CT values from quantitative PCR (qPCR) provides insights into the correlation between the electrical readouts and molecular quantification, offering a comprehensive evaluation of the nanotube-based detection system's performance in diagnostics procedure. Conclusions Unlike conventional blood culture and qPCR, our technology, delivers outcomes with heightened sensitivity, cost-effectiveness, and time efficiency. Our team's uncomplicated sample collection method notably reduces the intricacies of sample preparation, enabling the proper disposal of both the sample container and sensor part without requiring disassembly. Enhanced sensitivity, coupled with the economical and rapid detection capabilities of advanced technologies like carbon-based nano materials, is a promising alternative for the accurate and efficient diagnosis of fungal infections. Consequently, the implementation of such technology not only enhances diagnostic efficiency but also contributes to better patient outcomes through prompt and targeted therapeutic interventions.

Proposed Study on the Existing Body of Literature on Innovation Performance in China’s High-Tech SMEs

This study investigates the intricate relationship between top management capability, relational capability, technological capability, learning capability, innovation strategy, and innovation performance within the context of high-technology Small and Medium Enterprises (SMEs) in China. Through a synthesis of the Resource-Based View and Dynamic Capability Theory, this research delves into how these diverse capabilities intersect to shape innovation outcomes in a rapidly evolving market landscape. Drawing upon empirical data collected from a comprehensive sample of high-tech SMEs operating across various industries in China, this study examines how top management capability influences the firm's strategic direction and innovation agenda. Furthermore, the research explores the role of relational capability in fostering collaborative relationships with stakeholders, such as customers, suppliers, and partners, to access valuable resources and knowledge for innovation initiatives. Moreover, the study investigates how technological capability enables firms to harness advanced technologies and expertise to drive innovation, while learning capability facilitates the absorption, assimilation, and application of new knowledge and insights to fuel continuous innovation efforts. Through an analysis of innovation strategies adopted by high-tech SMEs and their alignment with dynamic capabilities, this research elucidates the mechanisms through which firms leverage their diverse capabilities to formulate and execute effective innovation strategies, ultimately impacting innovation performance. The findings contribute to both theoretical understanding and practical implications, providing insights for high-tech SMEs in China on how to develop and leverage dynamic capabilities across multiple dimensions to enhance innovation performance and achieve sustainable competitive advantage in today's dynamic business environment.

Coming Home in the Age of Industry 4.0? The Effects of Offshoring and Backshoring on Manufacturing Companies’ Success

This study explores the effects of offshoring and backshoring on value creation per employee within the manufacturing sector by investigating the difference between firms that did and those that did not engage in corresponding relocation activities. Historically, offshoring has been a strategy to reduce costs and increase efficiency. However, the rise of advanced digital technologies and changing market dynamics have sparked a countertrend toward backshoring. Using data from the European Manufacturing Survey, this research examines how these strategies impact value creation, also taking into account the roles of sales growth and export intensity as potential moderators. The results of hierarchical regression analysis indicate that neither firms that have engaged in offshoring of production nor firms that have engaged in offshoring of R&D have significantly higher or lower value creation per employee than those that did not. In contrast, firms that have engaged in backshoring of production realize higher value creation when coupled with high sales growth. Firms that have engaged in backshoring of R&D, on the other hand, realize higher value creation when combined with high export intensity. These findings highlight the importance of aligning strategic decisions with both technological capabilities and market conditions to enhance productivity. The study suggests that a balanced and holistic approach, integrating both offshoring and backshoring strategies tailored to specific business contexts, can optimize value creation and maintain competitiveness in a rapidly evolving global landscape.

The Lives of Lewis Thomas

What researching a biography of the celebrated mid-century physician-humanist reveals about technological capability and human frailty.

A Formalism for Scalable Maritime Traffic Monitoring and Explainable Anomaly Detection and Resolution at Vessel Traffic Services

Abstract Vessel traffic service (VTS) centres around the globe monitor and manage the ship traffic in their areas of responsibility and respond to arising unsafe or inefficient situations. Decision support tools (DST) help vessel traffic service operators (VTSO) to enhance their situational awareness and decision-making process, thus to recognise and assess dangerous situations. However, current DST have unsophisticated features and require manual configuration by the operator. Firstly, triggers for alerts are mostly based on the creation of geographical polygons for spatial-dependent assignment of rules, thresholds, ranges and limits for specific features. Secondly, calculations for the detection of safety-critical situations rely on measurements based on the closest point of approach (CPA) without taking contextual information into account. Thirdly, trajectory predictions are performed considering a constant velocity model (CVM) which does not depict reality. Due to these and other peculiarities, current DST are prone to false alerts. This results into a high workload where unsafe situations may be overlooked. In this paper, we propose a hierarchical formalism as foundation for an anomaly detection and resolution which generates less false alerts. The formalism consists of three hierarchical layers which represent, objects, measurements and situations. The formalism ensures adaptability and extensibility to various VTS areas and traffic patterns. Moreover, due to the given structure, the presented formalism is easily implementable, adaptable and scalable taking the currently available technological capabilities at VTS centres into account. We demonstrate the feasibility of this formalism by implementing a proof-of-concept and assessing it with realistic scenarios. Our implementation utilizes a rule-based system as central framework and it is configured through statistical methods, e.g. machine learning. Given this hybrid approach, the implementation provides reasonable and explainable results. This enables comprehensibility and verifiability by authorities and operators which is crucial for acceptance.

TECHNOLOGY FOR OBTAINING BIOCOMPONENT YARN FROM NATURAL SILK WASTE

The paper presents the results of a study on the development of technological parameters for the preparation of blended yarn from cotton fibers and secondary waste of natural silk. A new technological chain for the production of mixed yarns in modern cotton spinning equipment is given, taking into account their technological capabilities, as well as physical, mechanical and technological indicators of the resulting new mixed yarn. Also, the indicators of filling the loom, which received the fabric, are given. In conclusion, the physical and mechanical indicators and the results obtained in the certification laboratory of the institute are given.

Transforming Creative Process: A Systematic Literature Review of Discourse on AI Image Generators

ABSTRACTAI image generator, also known as Text‐to‐image generation (TTIG) technology, allows users to generate images based on natural language input. With advancements in AI, debates related to its application in the creative field have flourished. A systematic literature review was conducted to examine discourse that addresses the perception of people in the creative industry towards AI image generators and the impact of AI image generators on these individuals. The analysis of discourse revealed four major categories: 1) Evaluation of product or outcome of AI; 2) Impact of AI on practitioners/artists; 3) Impact of AI on creative industry and society; 4) Capabilities of AI technology. These findings provide insights into the areas of interest within AI image generator discussions on creative activity.

5G-Cloud-based real-time robotic part repairing for advanced manufacturing via computer vision

In this paper, we delve into the transformative capabilities of 5G wireless communication technology within the realm of robotics, particularly in the context of advanced manufacturing. Leveraging the power of computer vision and cloud/edge computing, we unveil the boundless possibilities that this technology heralds. Leveraging the ultra-reliable low latency communication (uRLLC) of 5G, we establish a distributed system showcasing its potential to revolutionize industrial processes. Additionally, to validate our framework, we developed a testbed tailored for real-world applications, focusing on milling operations using an industrial robot. Through high-level lidar data processing, we identify defects and create toolpaths, seamlessly to execute milling tasks. This research highlights 5G’s potential to redefine industrial processes while elucidating operational requirements for achieving uRLLC. Empirical testing underscores the benefits of 5G-robotics integration, enhancing efficiency and innovation in advanced manufacturing.

Smart Farming for Sustainable Agriculture: A Case Study through Korean Public TVET

This study aims to present implications for sustainable education and training of the agricultural workforce. It introduces the case of a smart farm learning factory as an educational facility at Korea Polytechnics. Learning factory refers to the practical experience gained using the knowledge acquired in engineering education to solve problems in the actual work field. For this study, we analyzed the smart farm case of Hongseong Campus of Korea Polytechnics, a government-funded vocational education institution in Korea. The research questions are as follows. First, what is the purpose of establishing a smart farm education and training facility? Secondly, what is the performance of the facility? Thirdly, what are the implications of the Korean smart farm for sustainable TEVT? As a result of analyzing the case, the purpose of establishing the facility was to improve the practical capabilities of convergence technologies used in machinery, automation, industrial facilities, and electrical departments. Additionally, the performance has been found to serve as the foundation for project-based learning subjects that incorporate convergence education, and companies have been able to reduce training costs and contribute to sales profits by using this facility to train employees. Finally, the implication of sustainable TVET through smart farm cases is that it has provided a way to enhance the effectiveness of teaching and learning guidance at agricultural sites, create educational resources that can utilize advanced agricultural technologies for sustainable development, and actively cooperate and collaborate with educational institutions, governments, and local companies.

Enhancing localisation in public procurements: A framework for evaluating suppliers' capabilities

This study investigates a framework for assessing suppliers' capabilities in public procurements to bolster localisation objectives. The study utilises the Action Design Research (ADR) methodology, combining the strengths of Action Research and Design Science, to examine the 'Ten Products Group' initiative within Iran's oil industry (2014–2023). This approach allows for the investigation of an applied problem within its specific contextual framework. The research highlights the importance of a comprehensive capability evaluation framework that includes qualitative assessments of suppliers' organisational, technological, and manufacturing capabilities. The framework incorporates both self-reporting and independent outside evaluation, enabling the inclusion of competent participants in public procurements and aligning contractual duties with the objective of localisation.The study emphasises the need for a transparent and thorough capability evaluation framework, contributing to the development of local industries and economic growth in situations where suppliers lack necessary capabilities. It suggests that a well-designed capability evaluation framework can facilitate the growth of local industries through public procurements, enabling the inclusion of competent suppliers and supporting economic development. The study's limitations include its focus on the context of localisation in public procurement and the potential challenges associated with implementing the proposed capability evaluation framework in practice.

The more valuable the knowledge, the more focused the enterprises: Intellectual property pledge financing and diversification in high-tech enterprises

This paper investigates the relationship between intellectual property pledge financing (IPPF) and enterprise diversification, utilizing data from a large sample of high-tech enterprises. The results demonstrate that IPPF reduces enterprise diversification, leading enterprises to be more focused on their core business. The potential mechanism through which IPPF reduces diversification involves alleviating financing constraints and enhancing firms’ capacity for risk-taking. Heterogeneity analysis reveals that in areas with a lower degree of marketization, IPPF exhibits a more pronounced effect in reducing corporate diversification. Similarly, for firms with lower technological innovation capabilities, the reduction in diversification is more pronounced.

OPTIMIZATION OF HEAT CONSUMPTION IN CENTRAL HEATING SYSTEMS AT COMMERCIAL FACILITIES

Rising energy prices and stricter environmental regulations are exacerbating the problem of inefficient heat consumption in the commercial sector. Central heating systems of office buildings, shopping malls, and industrial complexes are often characterized by excessive thermal energy consumption, which leads to significant economic losses and a negative impact on the natural environment. The purpose of the study is to study the directions and trends of optimization in the field under consideration (taking into account modern technological capabilities, and economic factors). There are disagreements in the professional community about the priority of measures to improve energy efficiency: some experts prefer improving the thermal insulation of buildings, others — the introduction of intelligent control systems, and others — the integration of renewable energy sources. The present study demonstrates that the greatest effect is achieved with a systematic approach combining various initiatives. The conclusion is formulated that in the current conditions and the future, a comprehensive application of modern thermal insulation materials, highly efficient heating equipment, intelligent management mechanisms, and alternative energy sources is required. The article is of interest to engineers-designers of heating systems, energy managers of commercial facilities, specialists in energy efficiency of buildings, and heads of companies interested in optimizing operating costs and improving the environmental friendliness of their real estate.

Разноуровневые стратегии развития: арктический нефтегазовый вектор

The balanced development of the hydrocarbon potential in the Arctic is currently a strategic priority for Russia. Given the present conditions of the global energy sector, alongside new geopolitical challenges and trends towards low-carbon and ecologically balanced development, there is a need for a system of coordinated strategies across the industry, regional, and corporate levels. To effectively develop Arctic oil and gas resources, it is necessary to ensure technological sovereignty, which involves equipping oil and gas companies with domestically produced equipment and software. Strategies should also focus on the development of industries that produce high value-added products, particularly in the petrochemical sector. Public administrators and corporate managers responsible for key decisions must have a clear, long-term vision for the development of the Arctic oil and gas sector and employ established methodological approaches in strategy design. The goal of this study is to substantiate the specific characteristics of multilevel strategies and assess the feasibility of using a matrix approach when designing strategic alternatives relevant to the current economic environment. The research methodology is based on the approaches, methods, and tools of strategic management and planning, with a particular focus on methods for designing strategic alternatives. The novelty of the research lies in the development of a system of criteria for comparing strategies and their target priorities at the industry, regional, and corporate levels. The study identifies current trends and challenges arising from the energy transition, stringent sanctions policies, and growing technological capabilities. It proposes an approach to designing alternative strategies of related and unrelated diversification for oil and gas companies. Developing a holistic concept of coordinated industry and corporate strategies is identified as a promising area for further research.

Exploring the antecedents of knowledge transfer among stakeholders in green building projects: From the configuration perspective

With the rapid development of green buildings around the world, knowledge transfer among stakeholders is of great significance in promoting the innovation and application of green building technologies. However, due to the complexity and specificity of green building projects, current studies have not fully established a comprehensive understanding of how elements from various dimensions (i.e., subject, relationship, context, and activity) collectively impact knowledge transfer among stakeholders in green building projects. Therefore, this study aims to explore the key factors that affect knowledge transfer among stakeholders in green building projects and how these factors work together to enhance the effectiveness of knowledge transfer (EKT). Firstly, the key factors influencing knowledge transfer were pinpointed: cognitive differences, connection strength, organizational climate, information technology capability, transmit willingness, receive willingness, perceived policy support, and richness of transfer channels. Then, an examination of the collected valid samples was conducted through configuration analysis utilizing the fuzzy set qualitative comparative analysis (fsQCA) method. The findings reveal five configurations, categorized as strong connection-driven, policy support-driven, and both-driven. Lastly, some combination strategies were outlined for different categories to assist green building companies in enhancing EKT. This study not only enhances the existing green building literature by developing a framework of factors that influence knowledge transfer among stakeholders, but also provides a reference for corporate executives to choose the best strategies to enhance EKT in green building projects.