Tea is an important economic product in China, and tea picking is a key agricultural activity. As the practice of tea picking in China gradually shifts towards intelligent and mechanized methods, artificial intelligence recognition technology has become a crucial tool, showing great potential in recognizing large-scale tea picking operations and various picking behaviors. Constructing a comprehensive database is essential for these advancements. The newly developed Tea Garden Harvest Dataset offers several advantages that have a positive impact on tea garden management: 1) Enhanced image diversity: through advanced data augmentation techniques such as rotation, cropping, enhancement, and flipping, our dataset provides a rich variety of images. This diversity improves the model’s ability to accurately recognize tea picking behaviors under different environments and conditions. 2) Precise annotations: every image in our dataset is meticulously annotated with boundary box coordinates, object categories, and sizes. This detailed annotation helps to better understand the target features, enhancing the model’s learning process and overall performance. 3) Multi-Scale training capability: our dataset supports multi-scale training, allowing the model to adapt to targets of different sizes. This capability ensures versatility and accuracy in real-world applications, where objects may appear at varying distances and scales. This tea garden picking dataset not only fills the existing gap in the data related to tea picking in China but also makes a significant contribution to advancing intelligent tea picking practices. By leveraging its unique advantages, this dataset becomes a powerful resource for tea garden management, promoting increased efficiency, accuracy, and productivity in tea production.
Purpose – This study investigates the Influence of parental and peer connections on Financial Literacy and saving Behavior among Indonesian youth. It examines how social agents shape financial competence and explores the mediating role of financial Literacy and the moderating role of self-control in enhancing saving habits.
Design/methodology/approach – A quantitative research design was used a cross-sectional online survey. Data were collected from 350 students enrolled in applied colleges across Indonesia. Constructs such as Financial Literacy, self-control, saving Behavior, and social influences were measured using confirmed multi-item Likert scales. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. Bootstrapping with 5,000 resamples was conducted to test the significance of direct, indirect, and moderating effects.
Findings – The findings reveal that both parental and peer influences significantly enhance youth financial literacy, which positively affects saving Behavior. Financial Literacy mediates the relationships between social impact and saving Behavior. Self-control positively moderates the effect of financial Literacy on saving Behavior, suggesting that individuals with higher self-discipline are more likely to translate financial knowledge into saving practices.
Research limitations/implications – The study’s reliance on self-reported data and a purposive sample of applied college students may limit the generalizability of the results. However, the findings emphasize the need for integrated financial education programs that involve families and peer groups, as well as behavioral training to strengthen self-regulation.
Originality/value – This research contributes to the limited body of literature on youth saving Behavior in emerging economies by showing the interplay between social influences, Financial Literacy, and self-control. It offers theoretical insights based on Social Learning Theory and the Behavioral Life Cycle Theory, as well as practical recommendations for designing culturally relevant financial literacy programs for youth.
Production management. Operations management, Management. Industrial management
Santiago Gregorio Acuña, Marcelo Oscár Gim´enez, Mariela Grinberg
et al.
This study presents a quantitative system dynamics model developed to understand and enhance nuclear safety culture and operational performance in nuclear power plants. The model employs causal loop diagrams and stock-and-flow diagrams, created using Vensim PLE+ software, to capture and simulate the complex interactions that define safety culture dynamics. Recognizing the fundamental role of organizational culture in maintaining nuclear safety, the model incorporates key elements such as leadership, risk perception, continuous improvement, internal communication, and the commitment of management and personnel. Through an extensive literature review and expert consultations, the research integrates critical variables into the model, grounded in frameworks from the International Atomic Energy Agency (IAEA) and the World Association of Nuclear Operators (WANO). Simulating a decade of safety culture management dynamics, the model reveals the impact of management strategies, demonstrating the effectiveness of continuous improvement initiatives and proactive leadership in enhancing safety outcomes. Stress tests conducted under extreme scenarios validated the model's robustness, reaffirming its applicability in safeguarding safety culture under intensified production pressures. The findings provide actionable insights for nuclear safety professionals and decision-makers, promoting environments that support safety-focused practices. This model serves as a comprehensive tool to advance safety culture in nuclear operations, offering valuable perspectives for both theoretical discourse and practical nuclear safety management.
Medical physics. Medical radiology. Nuclear medicine, Radioactivity and radioactive substances
Munyem Ahammad Muyeed, Moslema Hoque Oeishee, Abu S.M. Mohsin
The transition to sustainable energy solutions is critical for achieving net zero emissions, particularly in the transportation sector. This study presents a comprehensive cost-benefit and net-zero emission impact analysis of hybrid photovoltaic (PV)-grid-battery systems designed for electric vehicle (EV) charging stations in Bangladesh, which evaluates various configurations of PV systems, battery storage, and grid connectivity during the preliminary design phase, optimizing energy provision and system reliability based on demand load profiles reflecting anticipated EV usage patterns. The proposed system supports up to 54 EVs within 24 h, with a total demand load of 2800 kW. The study focuses on five locations—Dhaka, Sirajganj, Faridpur, Cumilla, and Habiganj—selected based on solar irradiance levels and urban density. Using the HOMER Pro database, the analysis identifies significant seasonal variations in solar radiation, with Sirajganj achieving a peak of 6.05 kWh/m2/day in April. Energy performance analysis across the five locations shows that generic flat-plate PV systems contribute nearly 100 % of the total annual energy production, with specific yields ranging from 67,882,490 kWh/yr in Cumilla to 75,474,534 kWh/yr in Sirajganj. The three different variant configurations for the EVCS were evaluated in order to determine the best scenario for efficiency, each being composed of PV generation, grid connectivity, and energy storage combinations. In Case 3, grid sales exceed purchases, with Dhaka reporting the highest grid sales at 39,025,459 kWh/yr. The renewable fraction stabilizes at around 90.5 % in Case 3 across all locations, demonstrating balanced integration of renewables. Simpler system configurations yield higher ROIs, with Case 1 in Cumilla achieving 171.8 %. The study recommends a grid-connected net metering system to optimize excess PV energy contributions. The proposed system can reduce energy costs by up to 30 % compared to grid-only solutions. This research underscores the role of PV-grid-battery systems in advancing Bangladesh towards a net-zero emissions future with a decrease of approximately 910,395.488 kg CO2 per year, offering a scalable and economically feasible model for EV charging infrastructure. Deploying EV charging stations in Bangladesh presents challenges, including site selection based on population densities and travel patterns and integrating PV systems into EVCS networks without proper sizing guidelines. The intermittent nature of solar energy necessitates hybrid energy management solutions, highlighting the need for strategic planning to ensure reliable and sustainable EVCS operations.
The advent of digital technologies has brought substantial improvements in various domains. This article provides a comprehensive review of research emphasizing AI-enabled IoT applications in poultry health and welfare management. This study focused on poultry welfare since modern poultry management is confronted with issues relating to standardized parameters for welfare assessment and robust monitoring systems, particularly for broilers ’ health and disease outbreak prevention. Evidence has shown that modern digital technologies have high possibilities for intelligent automation of current and future poultry management operations to facilitate high-quality and low-cost poultry production. Therefore, this study presents a systematic review of the current state-of-the-art AI-enabled IoT systems and their recent advances in developing intelligent systems in this domain. Also, the study provides an overview of the critical applications of identified digital technologies in poultry welfare management. Lastly, the study discusses the challenges and opportunities of AI and IoT in poultry farming.
Purpose: Today, the efficient management of supply chains plays a fundamental role in the market and economy. The supply chain is a network of facilities working together to make and move products from upstream to downstream to provide customers with highly qualified products and services. Nowadays, construction has become a growing and huge industry sector worldwide. One of the supply chains that needs proper management is related to the construction industry. The purpose of this article is to optimize this type of supply chain by minimizing its total costs.
Design/methodology/approach: An attempt has been made to develop an optimization model for the construction supply chain, considering all the important elements involved in the construction process, i.e. contractors, designers, suppliers of materials and construction materials, as well as three important and basic flows in the construction industry, i.e. the flow of manpower, the flow of equipment and machinery, and the flow of materials. All indices, parameters, decision variables, objective functions and constraints have been introduced and presented in the proposed model.
Findings: The model proposed by GAMS optimization software was solved and the obtained results included the lowest construction cost as well as the optimal amount of construction materials and materials, labour, equipment, and machinery based on the required construction size.
Research limitations/implications: The application of the supply chain in the construction industry is a relatively new topic. In the classic supply chain, the flow of materials and output at the end of the chain includes the manufactured product, while in the construction supply chain, the final output includes a building or a structure. Individuals, industries and even countries incur a lot of construction costs to meet their needs in the field of construction. The current study was influenced by limitations such as access to real data and the impossibility of handling a real case study, because the problem of designing the construction supply chain has wide dimensions and requires access to all dimensions of the construction industry chain, from upstream to downstream.
Practical implications: With the definition and expansion of the concept of supply chain and the use of supply chain management in manufacturing industries and the positive results it brought in various manufacturing industries, supply chain management emerged in the construction industry. Meanwhile, researchers, major contractors, and large construction companies are trying to find methods to take advantage of the supply chain management approach. Also, the stakeholders of the construction industry can enable active decision-making and agile responses to market fluctuations by continuously monitoring and updating the results of cost sensitivity analysis.
Social implications: Optimizing the construction supply chain can lead to reduced costs, improved project timelines, and enhanced sustainability. However, it may also impact local communities through job displacement, environmental concerns, and social inequality. Balancing efficiency with social responsibility is crucial to ensure equitable outcomes in construction projects.
Originality/value: By now, there has been no reference available in the literature in the field of construction supply chain considering the designer, the flow of manpower and the flow of drawings and technical documents. The proposed model is comprehensive and includes the construction chain, considering all aspects such as the flow of required materials and materials, the flow of labour, the flow of required equipment and machinery, the flow of plans and documents, and designers and contractors.
Cerati Giuseppe, Elmer Peter, Gartung Patrick
et al.
mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both threadand data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain. Prospects for an mkFit implementation of the track fit are also discussed.
Owing to its multidisciplinary nature, the operations management (OM) and information systems (IS) interface distinguishes itself from the individually focused perspective of both fields. The number and depth of contributions in this department can help both disciplines advance to better address important theoretical and practical challenges of the business world. In this paper, we study the characteristics of problems at the interface between OM and IS, and review past work that has been instrumental in setting the tone and direction of research at this interface. We extend our discussion to provide directions for future research at the OM and IS interface in the domains such as smart city management, healthcare, deep learning and artificial intelligence, fintech and blockchain, Internet of Things and Industry 4.0, and social media and digital platforms.
Arjaree Saengsathien, Dashashai Nontapa, Wuttichai Jantep
et al.
Cold chain management is a necessary part of reducing food loss and maintaining food safety in production, storage, and distribution activities along a supply chain. However, the adoption of cold chain logistics by Thailand’s agricultural and food sectors remains underdeveloped. The golden apple snail supply chain is an important part of the economy in Northeast Thailand, however, it is facing losses due to food waste. Consequently, this study aims to analyse supply chain operations and propose guidelines that help reduce food loss towards building an unbroken cold chain. A case analysis at Baan Huakwa, Kalasin, one of the main golden apple snail storage facilities, was selected as a starting point for the snowball sampling technique used in this cold chain study. Following an assessment of current cold chain management practices at the facility, a supply chain operations reference model and value chain were used to systematically suggest possible improvements. The study found that this specific cold chain breaks during transport from the snail farmers to the storage/packaging facility. It also found that a lack of control over the environment and a lack of product forecasting sometimes lead to snail shortages or oversupply. Furthermore, the length of delivery and amount of time stored at improper temperatures with the use of only an ice cooler and pickup tarpaulin can result in spoilage. The option of investing in temperature-controlled trucks is considered. This study provides key recommendations for relevant stakeholders to enable them to implement the changes necessary to improve the existing cold chain system. This study can be further applied as a reference for perishable food supply chains.
Ankita Kukshal, Ravi Sharma, Hirak Jyoti Kalita
et al.
Abstract One of the main challenges for healthy hydrocarbon yields from the production wells is the sand production, and its control assumes significant importance for successful production operations. The prime objective remains to control the sand production without compromising on the fluid flow rates. Sand production is conventionally associated with diverse heterogeneous formations, especially poorly consolidated formations. Scrutinizing fluid flow rates at different orientations of perforations is a valuable analysis in controlling the sand production. This study was conducted to examine the case of sand production in a few development wells from Malleshwaram field of the Krishna Godavari (KG) basin in south India and provide alternatives to arrest this sand production. The influence of oriented perforations on fluid flow rates to minimize sanding tendencies was examined. Sand grain diameter was estimated using the distribution plots of the grain sizes obtained from the photomicrographs, and the average value of the grain size was estimated around 100 μm. The fluid flow model was simulated for actual scenario in the hydrocarbon bearing Nandigama formation using finite element modeling (FEM). Sanding tendencies in these formations were studied at varying depletion rates. Critical draw down pressure (CDDP), which is a function of both critical bottom hole pressure and reservoir pore pressure, for well 1 and well 2 is estimated as 4650 Psi and 3400 Psi, respectively, at 0% depletion. CDDP was used to estimate the onset of sanding, and the flow rate for horizontal perforation was calculated as 0.024548 $${\mathrm{m}}^{3}$$ m 3 /sec. Strength parameters, namely the unconfined compressive strength (UCS) and cohesion, were also investigated in all the wells to decipher the formation strength and a possible linkage to sanding. These results present a completely fresh analysis of the sanding potential and the related parameters responsible for it in these formations. Fluid flow rates for the producing reservoir are studied at different set of oriented and sized perforations. It was observed that a hiked flow rate in horizontal perforations maintains the production in a safe and no-sanding zone. This study provides vital information and a workflow for similar heterogeneous complex formations for designing the well completions, augmenting economic production and reinforcing future reservoir management.
Kaylla Lage Jordão, Tiago José Menezes Gonçalves, Daniela da Gama e Silva Volpe Moreira de Moraes
Este trabalho propõe um modelo multicriterial de avaliação de desempenho para apoiar o processo de gestão em instituições públicas. O modelo foi aplicado ao setor de obras, manutenção e serviços de uma instituição federal. A Metodologia Multicritério de Apoio à Decisão - Construtivista (MCDA-C) foi o instrumento de intervenção adotado para a obtenção e análise dos dados por ser capaz de tratar diferentes tipos de informações e por elicitar os objetivos de decisão conforme os valores dos decisores, possibilitando que eles reflitam sobre suas prioridades e preferências. Como resultados, o modelo possibilitou (i) a medição do desempenho do setor a partir dos aspectos considerados relevantes pelo decisor; (ii) a análise da evolução no desempenho de cada indicador e de suas tendências; (iii) o entendimento dos principais problemas de desempenho do setor e dos pontos passíveis de melhoria; (iv) e a realização de recomendações para resolver os problemas de desempenho identificados.
Production management. Operations management, Production capacity. Manufacturing capacity
The role of national culture interactions is important in operations management and supply chain management decisions. Yet, cross‐cultural research in this field is limited. Our goal in this study is to review relevant research, to raise awareness about the critical role of national culture among operations management and supply chain management researchers, and to offer directions for future research. To achieve this goal, we report our research findings in three major categories: (i) Operational Decisions (innovation, and research and development, quality management, workforce management, performance measurement, and risk, security and disaster management); (ii) Supply Chain Management (buyer–supplier interactions, governance mechanisms, outsourcing, and offshore operations); and (iii) Interdisciplinary Topics (entrepreneurship, investments, joint ventures, and mergers and acquisitions). We also suggest methodological considerations for future research by those interested in studying national culture.
This review analyzes published data on manure management practices used to mitigate methane (CH4) and nitrous oxide (N2O) emissions from animal operations. Reducing excreted nitrogen (N) and degradable organic carbon (C) by diet manipulation to improve the balance of nutrient inputs with production is an effective practice to reduce CH4 and N2O emissions. Most CH4 is produced during manure storage; therefore, reducing storage time, lowering manure temperature by storing it outside during colder seasons, and capturing and combusting the CH4 produced during storage are effective practices to reduce CH4 emission. Anaerobic digestion with combustion of the gas produced is effective in reducing CH4 emission and organic C content of manure; this increases readily available C and N for microbial processes creating little CH4 and increased N2O emissions following land application. Nitrous oxide emission occurs following land application as a byproduct of nitrification and dentrification processes in the soil, but these processes may also occur in compost, biofilter materials, and permeable storage covers. These microbial processes depend on temperature, moisture content, availability of easily degradable organic C, and oxidation status of the environment, which make N2O emissions and mitigation results highly variable. Managing the fate of ammoniacal N is essential to the success of N2O and CH4 mitigation because ammonia is an important component in the cycling of N through manure, soil, crops, and animal feeds. Manure application techniques such as subsurface injection reduce ammonia and CH4 emissions but can result in increased N2O emissions. Injection works well when combined with anaerobic digestion and solids separation by improving infiltration. Additives such as urease and nitrification inhibitors that inhibit microbial processes have mixed results but are generally effective in controlling N2O emission from intensive grazing systems. Matching plant nutrient requirements with manure fertilization, managing grazing intensity, and using cover crops are effective practices to increase plant N uptake and reduce N2O emissions. Due to system interactions, mitigation practices that reduce emissions in one stage of the manure management process may increase emissions elsewhere, so mitigation practices must be evaluated at the whole farm level.
Online video streaming is one of the channels of the current economic development of e-commerce. In this technology era, our lifestyle is gradually moving towards electronic development and the public use of e-commerce applications for their businesses. Online video streaming strategies, therefore, benefit marketers, and this is mainly due to their cost-effective properties. The main objective of this research is to investigate the influences of online video streaming on customers’ online purchase intention. Three independent variables include perceived credibility, perceived ease of use and perceived usefulness are used to study the influence of online video streaming on the consumers’ online purchase intention. A set of self-administered questionnaires was distributed to 215 respondents from three states in Malaysia which are Johor, Melaka and Selangor, who had the experience of online purchases that were affected by online video streaming. The collected data are then analysed using SPSS and Smart PLS software. The results of the analysis indicated that all three independent variables have a significant impact on consumers' online purchase intentions through online video streaming. In conclusion, this research is important to e-marketers in order to allow them to gain a better understanding of the online purchasing behaviour of their customers
Production management. Operations management, Business
Kampker Achim, Triebs Johannes, Hollah Ansgar
et al.
Due to the conceptual degrees of freedom in their product structure, electric vehicles offer high potential for remanufacturing-oriented product design. This potential is, however, not realized yet. Remanufacturing as one fundamental element of a circular economy is characterized by specific challenges caused by uncertain information about the condition and the timing of the returning product. By means of a case study within the remanufacturing industry, the effects of uncertainties on remanufacturing operations are examined and different approaches within the field of production management to meet these specific challenges are pointed out. Based on the result of the case study a production management framework outlining fields of action to deal with remanufacturing specific uncertainties is developed. In this context, the requirements for remanufacturing of electric vehicles are derived by analyzing similarities from other industry sectors. In conclusion, a solution approach for the implementation for electric vehicles is presented for strategic, tactical and operational procurement logistics and remanufacturing operations.