Hasil untuk "Management. Industrial management"

Oleksandr Korchyha

Trends in the development of the energy sector determine the dynamics of pricing policy in the energy market, the level of socio-economic stability and investment attractiveness of both the country as a whole and its individual regions. The study is devoted to the study of regional features of the potential of alternative energy in Ukraine and their impact on economic development. The methodological basis of the article is formed by a number of general theoretical principles, techniques and interdisciplinary methods of scientific research. The article considers the main regional aspects of the impact of the development of renewable energy sources on the socio-economic state of communities: decentralization of energy supply and growth of energy independence, creation of new jobs in the regions and stimulation of local business development, attraction of investments, improvement of environmental safety indicators and decarbonization. Potential challenges for regional economic development caused by the destruction of energy infrastructure during a full-scale war are noted, as well as other problematic aspects, including the need to modernize and expand electricity networks, large losses in electricity networks, problems with resource supply that may limit the development of certain types of alternative energy (for example, bioenergy). The study substantiates the need for the transfer of new technologies and the promotion of "green" initiatives within regional economic development strategies. The main regional advantages and limitations of energy production from various types of renewable energy sources (solar, wind, hydro- and bioenergy, tidal, geothermal energy) are highlighted. Optimization measures are proposed, including diversification of supplies, modernization of the energy system, and updating of legislation. It has been proven that stimulating the regional development of alternative energy in Ukraine will accelerate the overall economic growth of the state, promote investment, stimulate further regional decentralization of energy supply and the introduction of climate-neutral energy capacities.

Oana Panazan, Catalin Gheorghe, Aamir Aijaz Syed et al.

This study examines the dynamic interactions between precious metals, cryptocurrencies, stablecoins, safe-haven currencies, and two key macroeconomic indicators, the 5-year breakeven inflation expectation (T5YIE) and the 10-year minus 3-month Treasury yield spread (T10Y3M), over January 2016–July 2025. To capture nonlinear and multi-scale dependencies, the study applies Quantile-on-Quantile Regression (QQR) in combination with wavelet coherence (WCO) and wavelet transform coherence (WTC). The results indicate that major cryptocurrencies such as Bitcoin and Ethereum do not display robust or systematic links with inflation expectations or recession risk, limiting their role as macro-financial hedges. By contrast, the Japanese yen and Swiss franc show pronounced tail sensitivities, reaffirming their safe-haven status, while gold and its tokenized counterparts (DGX, PAXG) exhibit persistent long-run coherence with inflation expectations. Stablecoins demonstrate unstable short-term linkages shaped by liquidity shocks and market frictions. The research provides new evidence on the heterogeneous roles of digital and traditional assets in shaping macroeconomic expectations. The findings carry implications for investors, who should continue to rely on gold and safe-haven currencies for crisis hedging, and for regulators concerned with the systemic stability of emerging digital instruments.

Suleman Bawa, Xie Yongping, Ibn Wahab Benin

This study investigates the influence of knowledge management (KM) and merger and acquisition (M&A) networks on the effectiveness of innovation networks within mature entrepreneurial firms. By focusing on a sample of 4139 firms listed on the Chinese stock market and analyzing 8563 M&A transactions from the mid-2000s to 2023, the research aims to explore how these strategic networks shape entrepreneurial innovation, with particular attention to the moderating role of absorptive capacity (AC) and the impact of entrepreneurial uncertainty. A mixed-method approach, combining structural equation modelling (SEM) and qualitative interviews, was employed to evaluate the relationships between KM, M&A, and innovation networks. SEM facilitated the assessment of hypothesized connections and mediation effects, while interviews with key stakeholders provided qualitative insights into the practical nuances of network interactions and strategies in mature firms. The study finds that KM practices, such as effective planning and knowledge acquisition, alongside M&A networks, collectively enhance the effectiveness of innovation networks. While KM promotes operational and strategic alignment, M&A networks support stakeholder decision-making, thus reinforcing firm operations. Absorptive capacity (AC) significantly mediates the relationship between KM, M&A networks, and innovation network effectiveness. However, entrepreneurial uncertainty diminishes the effectiveness of KM and M&A networks but simultaneously enhances innovation networks' outcomes, underscoring mature firms' adaptability in uncertain environments. This research deepens the understanding of innovation networks in mature entrepreneurial firms by applying the Knowledge-Based View (KBV) framework, highlighting the strategic role of KM and M&A networks. It offers new insights into how mature firms in emerging economies can leverage knowledge assets for sustained innovation and competitive advantage. The findings provide implications for practice and policy, suggesting that mature firms strategically manage KM and M&A activities to enhance innovation networks, even under varying levels of entrepreneurial uncertainty.

Zhaoxuan Lu, Lyuchao Liao, Xingang Xie et al.

In recent years, climate change and marine pollution have significantly degraded coral reefs, highlighting the urgent need for automated coral detection to monitor marine ecosystems. However, underwater coral detection presents unique challenges, including low image contrast, complex coral structures, and dense coral growth, which limit the effectiveness of general object detection algorithms. To address these challenges, we propose SCoralDet, a soft coral detection model based on the YOLO architecture. First, we introduce a Multi-Path Fusion Block (MPFB) to capture coral features across multiple scales, enhancing the model’s robustness to uneven lighting and image blurring. We further improve inference efficiency by applying reparameterization. Second, we integrate lightweight components such as GSConv and VoV-GSCSP to reduce computational overhead without sacrificing performance. Additionally, we develop an Adaptive Power Transformation label assignment strategy, which dynamically adjusts anchor alignment metrics. By incorporating soft labels and soft central region loss, our model is guided to prioritize high-quality, well-aligned predictions. We evaluate SCoralDet on the Soft-Coral dataset, achieving an inference latency of 9.52 ms and an mAP50 of 81.9. This surpasses the performance of YOLOv5 (79.9), YOLOv6 (79.4), YOLOv8 (79.5), YOLOv9 (78.3), and YOLOv10 (79.5). These results demonstrate the effectiveness and practicality of SCoralDet in underwater coral detection tasks.

Liu Yuxin

With the advent of the Transformer, the attention mechanism has been applied to Large Language Model (LLM), evolving from initial single- modal large models to today's multi-modal large models. This has greatly propelled the development of Artificial Intelligence (AI) and ushered humans into the era of large models. Single-modal large models can be broadly categorized into three types based on their application domains: Text LLM for Natural Language Processing (NLP), Image LLM for Computer Vision (CV), and Audio LLM for speech interaction. Multi-modal large models, on the other hand, can leverage multiple data sources simultaneously to optimize the model. This article also introduces the training process of the GPT series. Large models have also had a significant impact on industry and society, bringing with them a number of unresolved problems. The purpose of this article is to assist researchers in comprehending the various forms of LLM, as well as its development, pre- training architecture, difficulties, and future objectives.

P. Buckley, C. Pass, Kate Prescott

José Manuel Porras, Juan Alfonso Lara, Cristóbal Romero et al.

Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own data. However, that approach is not always feasible or advisable and may depend on the availability of data, local infrastructure, and resources. In those cases, there are various machine learning approaches for sharing data and/or models between educational entities, using a classical centralized machine learning approach or other more advanced approaches such as transfer learning or federated learning. In this paper, we used data from three different LMS Moodle servers representing homogeneous different-sized educational entities. We tested the performance of the different machine learning approaches for the problem of predicting student dropout with multiple educational entities involved. We used a deep learning algorithm as a predictive classifier method. Our preliminary findings provide useful information on the benefits and drawbacks of each approach, as well as suggestions for enhancing performance when there are multiple institutions. In our case, repurposed transfer learning, stacked transfer learning, and centralized approaches produced similar or better results than the locally trained models for most of the entities.

Naifeng Wen, Guanqun Liu, Jie Zhang et al.

Abstract Molecular property prediction (MPP) is vital in drug discovery and drug reposition. Deep learning-based MPP models capture molecular property-related features from various molecule representations. In this paper, we propose a molecule sequence embedding and prediction model facing with MPP task. We pre-trained a bi-directional encoder representations from Transformers (BERT) encoder to obtain the semantic representation of compound fingerprints, called Fingerprints-BERT (FP-BERT), in a self-supervised learning manner. Then, the encoded molecular representation by the FP-BERT is input to the convolutional neural network (CNN) to extract higher-level abstract features, and the predicted properties of the molecule are finally obtained through fully connected layer for distinct classification or regression MPP tasks. Comparison with the baselines shows that the proposed model achieves high prediction performance on all of the classification tasks and regression tasks.

Olívia Prado Schiavon, Márcia Ramos May, Andréa Torres Barros Batinga de Mendonça

Purpose – The study aims to understand how dynamic capabilities (DCs) contribute to business model innovation (BMI) in sustainable family farming. The agrifood sector has been seeking solutions for the development of agroecological markets. Thus, the authors have analyzed the challenges imposed to innovation and sustainability strategic management and the value proposition to sustain the business over the years. Design/methodology/approach – Considering the complexity of organizations and through an exploratory multiple case study of initiatives identified in the Organic Fair of Curitiba’s Passeio Público, it was possible to analyze the evolution of the business models (BMs) and the fair itself. Furthermore, it was possible to identify the DCs within the influence of agroecosystem elements on the innovation development. Findings – Analyzing each case individually, the authors understood the different dimensions of the evolution of BMs considering the organizational complexity. The authors conclude that the balance between organizational practices and changes in the environment, engagement and learning plays a significant role in the developing competitive advantage. The same applies to the patterns that precede the development of DCs and BMs. Originality/value – The article investigates innovation in agroecological BMs from a dynamic capability perspective. The agroecological BM is a subject that is still little discussed in the literature. In addition, the authors chose a context that includes socioenvironmental aspects and a few specificities of family farming in Brazil.

Jamal Eddine Lazreg, Nadia Benkhettou, Mouffak Benchohra et al.

Abstract In this paper, we establish the existence and uniqueness of a solution for a class of initial value problems for implicit fractional differential equations with Caputo fractional derivative. The arguments are based upon the Banach contraction principle, the nonlinear alternative of Leray–Schauder type and Krasnoselskii fixed point theorem. As applications, two examples are included to show the applicability of our results.

Suely de Carvalho Roma, André Marques Cavalcanti, Auristela Maria da Silva

A economia da região semiárida do nordeste brasileiro historicamente sempre esteve ligada ao leite bovino. Este estudo tem por objetivo analisar se no modelo de gestão adotada no aglomerado da pequena indústria do leite há processo de inovação. Para atingir esse objetivo, foi realizada uma pesquisa de campo a partir de entrevista estruturada com base nos requisitos do modelo teórico de inovação aberta. Dentre os achados deste estudo, os pesquisados mostram-se limitados e passivos às técnicas que já existem e dominam, como também aos conceitos e ações que viabilizem a adoção de um perfil inovador. Propor um modelo de processo de inovação aberta como fator estratégico de desenvolvimento deste setor é uma possibilidade que está alinhada com a condição das empresas investigadas.

Gugus Wijonarko

Era digital secara konsep menuntut pemanfaatan teknologi pada seluruh aspek pekerjaan manusia, khususnya adanya sinergi dan hubungan antara teknologi dengan faktor manusia yang dianggap sebagai salah satu aset perusahaan. Tujuan penelitian ini adalah untuk mengukur dan mengetahui faktor-faktor yang membuat karyawan memutuskan untuk menggunakan aplikasi sistem informasi sumber daya manusia dalam rutinitas pekerjaan dengan melihat pada variabel penelitian manajemen SDM yaitu kinerja, disiplin, dan produktivitas kerja dalam mempengaruhi keputusan menggunakan aplikasi HRIS. Sampel penelitian ini adalah pengguna dari beberapa perusahaan di Surabaya yang menggunakan aplikasi HRIS dalam rutinitas operasional pekerjaan sehari-hari mereka. Pada penelitian ini ditemukan sampel penelitian sebanyak 55 responden dari berbagai perusahaan di Surabaya dan hasil tanggapan responden tersebut dilakukan pengolahan data menggunakan teknik analisis data regresi linear berganda dengan tingkat kepercayaan 95% dan pembuktian hipotesis menggunakan uji T dan uji F. Hasilnya adalah faktor kinerja karyawan dan faktor disiplin mempengaruhi secara signifikan keputusan pengguna menggunakan sistem informasi sumber daya manusia. Hal ini dikarenakan para responden merasa adanya urgensi terhadap proses pencatatan adminsitrasi yang lebih baik. Sedangkan untuk variabel produktivitas kerja tidak mempengaruhi keputusan penggunaan aplikasi SISDM dikarenakan aplikasi hanya dipandang sebagai alat penunjang operasional pekerjaan sehari hari.

R. Flin, N. Maran

K. Lins, H. Servaes

Richard E. Baldwin, Richard E. Baldwin, Richard E. Baldwin

The paper argues that East Asian regionalism is fragile since (i) each nation's industrial competitiveness depends on the smooth functioning of 'Factory Asia' - in particular on intra-regional trade; (ii) the unilateral tariff-cutting that created 'Factory Asia' is not subject to WTO discipline (bindings); (iii) there is no 'top-level management' to substitute for WTO discipline, i.e. to ensure that bilateral trade tensions - tensions that are inevitable in East Asia - do not spillover into region-wide problems due to lack of cooperation and communication. This paper argues that the window of opportunity for East Asian 'vision' was missed; what East Asia needs now is 'management' not vision. East Asia should launch a 'New East Asian Regional Management Effort' with a reinforced ASEAN+3 being the most likely candidate for the job. The first priority should be to bind the region's unilateral tariff cuts in the WTO.

L. Donaldson

Victor Aredo, Jhan Carranza Cabrera, Raúl Siche

El objetivo de este estudio fue realizar un inventario de especies vegetales nativas encontradas hasta la actualidad en la región La Libertad. El estudio estuvo comprendido en dos etapas, una basada en entrevistas y en la recopilación de datos de fuentes bibliográficas existentes; y, una segunda para evaluar el potencial agroindustrial de cada especie vegetal nativa registrada basado en 6 criterios. De la primera etapa, se registró un total de 1403 especies vegetales nativas pertenecientes a 116 familias. Las familias con mayor riqueza fueron Astraceaae, Poaceae, Fabaceae, Solanaceae, Bromeliceae, Scrophulariaceae y Verbenaceae con 228, 103, 97, 74, 64, 53 y 40 especies, respectivamente. De la segunda etapa, las especies vegetales nativas que cumplieron con la mayoría los criterios, es decir, que tienen un alto potencial agroindustrial, fueron 5 especies: yacón (Smallanthus sonchifolius), tarwi (Lupinus mutabilis), quinua (Chenopodium quinoa), poroto (Erythrina edulis) y camote (Sweet potato).

Eikey, Elizabeth Victoria, Reddy, Madhu C, Booth, Kayla M et al.

BackgroundMobile health (mHealth) apps for weight loss (weight loss apps) can be useful diet and exercise tools for individuals in need of losing weight. Most studies view weight loss app users as these types of individuals, but not all users have the same needs. In fact, users with disordered eating behaviors who desire to be underweight are also utilizing weight loss apps; however, few studies give a sense of the prevalence of these users in weight loss app communities and their perceptions of weight loss apps in relation to disordered eating behaviors. ObjectiveThe aim of this study was to provide an analysis of users’ body mass indices (BMIs) in a weight loss app community and examples of how users with underweight BMI goals perceive the impact of the app on disordered eating behaviors. MethodsWe focused on two aspects of a weight loss app (DropPounds): profile data and forum posts, and we moved from a broader picture of the community to a narrower focus on users’ perceptions. We analyzed profile data to better understand the goal BMIs of all users, highlighting the prevalence of users with underweight BMI goals. Then we explored how users with a desire to be underweight discussed the weight loss app’s impact on disordered eating behaviors. ResultsWe found three main results: (1) no user (regardless of start BMI) starts with a weight gain goal, and most users want to lose weight; (2) 6.78% (1261/18,601) of the community want to be underweight, and most identify as female; (3) users with underweight BMI goals tend to view the app as positive, especially for reducing bingeing; however, some acknowledge its role in exacerbating disordered eating behaviors. ConclusionsThese findings are important for our understanding of the different types of users who utilize weight loss apps, the perceptions of weight loss apps related to disordered eating, and how weight loss apps may impact users with a desire to be underweight. Whereas these users had underweight goals, they often view the app as helpful in reducing disordered eating behaviors, which led to additional questions. Therefore, future research is needed.

G. Hofstede

L. Bourgeois