Decision-making Process Research Articles

Impact of participation in collective action on farmers’ decisions and waiting time to adopt soil and water conservation measures

Purpose This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures. Design/methodology/approach The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures. Findings The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures. Practical implications The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures. Originality/value Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

System dynamics applied in enterprise engineering – a systematic literature review

Purpose This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises. Design/methodology/approach A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook. Findings The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified. Originality/value The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

The collaborative project "Personalized medicine for oncology" (PM4Onco) as part of the Medical Informatics Initiative (MII)

The collaborative project Personalized Medicine for Oncology (PM4Onco) was launched in 2023 as part of the National Decade against Cancer (NKD) and is executed within the Medical Informatics Initiative (MII). Its aim is to establish asustainable infrastructure for the integration and use of data from clinical and biomedical research and therefore combines the experience and preliminary work of all four consortia of the MII and the leading oncology centers in Germany. The data provided by PM4Onco will be prepared in asuitable form to support decision making in molecular tumor boards. This concept and infrastructure will be extended to 23 participating partner sites and thus improve access to targeted therapies based on clinical information and analysis of molecular genetic alterations in tumors at different stages of the disease. This will help to improve the treatment and prognosis of tumor diseases.Clinical cancer registries are involved in the project to improve data quality through standardized documentation routines. Clinical experts advise on the expansion of the core datasets for personalized medicine (PM). Information on quality of life and treatment outcomes reported by patients in questionnaires, which is rarely collected outside of clinical trials, will make asignificant contribution. Patient representatives are involved from the onset to ensure that the important perspective of patients is taken into account in the decision-making process. PM4Onco thus creates an alliance between the MII, oncological centers of excellence, clinical cancer registries, young scientists, patients, and citizens to strengthen and advance PM in cancer therapy.

Boardroom blind spots: why HR exclusion puts corporate reputations at risk

Purpose This study aims to explore the ramifications of a lack of human resources (HR) representation in corporate boardrooms. Design/methodology/approach The author draws upon her personal and professional experience as a director of human resources and as a board member for a corporation. Findings There is a fundamental misunderstanding of the strategic value that HR brings to the table. To thrive in the modern business environment, organisations must acknowledge this strategic value and actively involve HR professionals in high-level decision-making processes. Originality/value This study makes a strong and compelling case for HR’s involvement in high-level decision-making in the boardroom.

Approaches to improving valuation decision-making: a review of the literature

PurposeThe complexity of property valuation, coupled with valuers’ cognitive limitations, makes some degree of error inevitable in valuations. However, given the crucial role that valuations play in the efficient functioning of the economy, there is a need for continuous improvement in the reliability of reported values by enhancing the quality of the decision-making process. The purpose of this paper is to review previous research on valuation decision-making, with particular interest in examining the approaches to improving the quality of valuation decisions and identifying potential areas for further research.Design/methodology/approachThe paper adopts a narrative approach to review 42 research articles that were obtained from Scopus and Web of Science databases and through author citation searches.FindingsOur findings show that existing literature is skewed towards examining the use of technology in the form of decision support systems (DSS), with limited research attention on non-technological (i.e. behavioural) approaches to improving the quality of valuation decisions. We summarise the non-technological approaches and note that much of the discussions on these approaches often appear as recommendations arising from other studies rather than original investigations in their own rights.Practical implicationsWe conclude that studies investigating the effectiveness of the non-technological approaches to improving valuation decision-making are lacking, providing various avenues for further research.Originality/valueThis paper presents the first attempt to provide a comprehensive overview of non-technological approaches to improving the quality of valuation decisions.

The evolution of smart cities: Integrating technology, governance, and sustainable development

This review paper explores the evolution of smart cities, focusing on the integration of technology, governance, and sustainable development. It examines the historical origins of smart cities, the role of Information and Communication Technologies (ICTs), and the importance of effective governance structures in urban planning. Case studies illustrate successful initiatives while highlighting challenges like rapid urbanization and technological innovation. The review emphasizes the need for holistic approaches that integrate environmental, social, and economic sustainability principles. Implications for future research and practice include innovative financing mechanisms and strengthened stakeholder collaboration. Recommendations for policymakers, urban planners, and other stakeholders stress prioritizing sustainability, inclusive decision-making processes, and investment in resilient infrastructure. By embracing these principles, cities can advance towards a more prosperous, equitable, and sustainable future. Keywords: Smart Cities, Technology, Governance, Sustainable Development, Urbanization, Innovation.

Enhancing brain tumor detection in MRI images through explainable AI using Grad-CAM with Resnet 50

This study addresses the critical challenge of detecting brain tumors using MRI images, a pivotal task in medical diagnostics that demands high accuracy and interpretability. While deep learning has shown remarkable success in medical image analysis, there remains a substantial need for models that are not only accurate but also interpretable to healthcare professionals. The existing methodologies, predominantly deep learning-based, often act as black boxes, providing little insight into their decision-making process. This research introduces an integrated approach using ResNet50, a deep learning model, combined with Gradient-weighted Class Activation Mapping (Grad-CAM) to offer a transparent and explainable framework for brain tumor detection. We employed a dataset of MRI images, enhanced through data augmentation, to train and validate our model. The results demonstrate a significant improvement in model performance, with a testing accuracy of 98.52% and precision-recall metrics exceeding 98%, showcasing the model’s effectiveness in distinguishing tumor presence. The application of Grad-CAM provides insightful visual explanations, illustrating the model’s focus areas in making predictions. This fusion of high accuracy and explainability holds profound implications for medical diagnostics, offering a pathway towards more reliable and interpretable brain tumor detection tools.

A REVIEW PAPER ON: DECORDING THE IMPACT OF INFLUENCER MARKETING ON MODERN CONSUMER BEHAVIOUR

The Internet has become an important part of daily life in the electronic age, with approximately 5 billion users and 80% of people participating in social networks. The development of the program was then transferred to this electronic domain and the beautiful display of energy emerged as a clear method of communication. A strong influence allows local influencers to promote business and product development to solve all kinds of problems of brands and customers. This is research into the complex connection between customer dynamic cycles and the power of promotion. By uncovering speculative development and examining the evidence from a local and holistic perspective, this research aims to uncover the mysterious systems that drive the impact of buyer decisions of sensational uniqueness. Additionally, this study aims to determine the key factors that contribute to the success of business operations and their impact on businesses. Knowledge of technology. Data is collected on the basis of comprehensive analysis and processed from various sources such as sound assessments, annual consolidated reports, non-academic inventories and experts. This distinction involves a general assessment of the difference between a particular aesthetic improvement and its effect on the recipient's freedom of action. important workplaces. Factors such as partner base, emotional profile, authenticity, and accountability are seen as important factors in making a good decision. Additionally, the surprising possibility of building a relationship with fans is the main consideration that makes buyers come and see the show. An important element of trust, creativity and long-term cooperation with large companies have been proven to yield significant products. Key Words: Influencer; Influencer marketing; Decision-making process; Consumer behavior; Social media; Digital marketing; Brand engagement; Authenticity; Relationship building; Content creation; Follower engagement; Brand promotion.

Revolutionizing Supply Chain Management: Real-time Data Processing and Concurrency

In the contemporary business landscape, effective supply chain management (SCM) is paramount for organizations seeking to thrive amidst evolving market dynamics and heightened customer expectations. This research paper presents a pioneering approach to SCM that harnesses cutting-edge technologies, namely Kafka and Akka, to revolutionize data integration and decision-making processes. By leveraging Kafka as a robust distributed event streaming platform and Akka as a versatile toolkit for developing concurrent and distributed applications, our system facilitates seamless communication and coordination across diverse nodes within the supply chain network. This paper elucidates the intricacies of the proposed architecture, detailing the implementation methodology and performance evaluation metrics. Through a comprehensive examination, we demonstrate how our solution enhances supply chain visibility, fosters operational agility, and enables real-time responsiveness to market fluctuations and customer demands. Moreover, practical use cases exemplify the transformative impact of our approach on inventory management optimization, order fulfillment efficiency, and logistics optimization. Furthermore, we delve into the challenges encountered during implementation and deployment, offering insights into potential mitigative strategies. Finally, we outline avenues for future research, exploring emerging trends and opportunities in the realm of SCM empowered by Kafka and Akka technologies.

Ethics of Artificial Intelligence(AI)

In today's research and development, artificial intelligence (AI) ethics are a complex and urgent issue. Concerns about artificial intelligence (AI) systems' possible effects on people, communities, and the larger global environment are raised as these systems are incorporated into more and more facets of society. This study examines the ethical implications of artificial intelligence (AI), looking at topics including privacy, fairness, accountability, transparency, and the possibility of prejudice and discrimination in AI algorithms and decision-making processes. The study endeavours to contribute to the establishment of frameworks and rules that encourage the responsible and ethical use of AI technologies, guaranteeing their conformity with society values and the preservation of human rights, by critically assessing these ethical issues. Keywords:-AI ethics , artificial intelligence, ethics, machine ethics, robotics, challenges.

Structural and Cultural Othering: An Organizational Culture Perspective on Young People’s Participation in Decision-making in Sport Organizations

The purpose of this article is to examine the role played by organizational culture in young people’s continuing underrepresentation in decision-making bodies, despite structural changes, in the context of Norwegian sport organizations. Data is based on a questionnaire centred on the experiences of young people in sport governance ( n = 32 youth representatives) and semi-structured interviews with young (under 26 years) and older representatives of organizations affiliated with the Norwegian Olympic and Paralympic Committee and Confederations of Sports ( n = 10). Findings show that Norwegian sport organizations foster a cultural understanding of young people which takes its structural expression in the separation of elements that are ‘othering’ the youth. Youth have also limited access to resources of power as a result of a lack of trust in older leaders. Prevailing culture mirrors an adult society in which young people need to upgrade their level of professionalism through education before they are invited to decision-making processes.

Deep learning-based classification of anti-personnel mines and sub-gram metal content in mineralized soil (DL-MMD)

De-mining operations are of critical importance for humanitarian efforts and safety in conflict-affected regions. In this paper, we address the challenge of enhancing the accuracy and efficiency of mine detection systems. We present an innovative Deep Learning architecture tailored for pulse induction-based Metallic Mine Detectors (MMD), so called DL-MMD. Our methodology leverages deep neural networks to distinguish amongst nine distinct materials with an exceptional validation accuracy of 93.5%. This high level of precision enables us not only to differentiate between anti-personnel mines, without metal plates but also to detect minuscule 0.2-g vertical paper pins in both mineralized soil and non-mineralized environments. Moreover, through comparative analysis, we demonstrate a substantial 3% and 7% improvement (approx.) in accuracy performance compared to the traditional K-Nearest Neighbors and Support Vector Machine classifiers, respectively. The fusion of deep neural networks with the pulse induction-based MMD not only presents a cost-effective solution but also significantly expedites decision-making processes in de-mining operations, ultimately contributing to improved safety and effectiveness in these critical endeavors.

A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making

In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reconciliation, this paper reviews AP, RL and hybrid methods (e.g., novel learn to plan techniques) for solving Sequential Decision Processes (SDPs), focusing on their knowledge representation: symbolic, subsymbolic or a combination. Additionally, it also covers methods for learning the SDP structure. Finally, we compare the advantages and drawbacks of the existing methods and conclude that neurosymbolic AI poses a promising approach for SDM, since it combines AP and RL with a hybrid knowledge representation.

Psychological Trust Dynamics in Climate Change Adaptation Decision-Making Processes: A Literature Review

There has been a growth in interest among academics and professionals in psychological trust dynamics during climate change adaptation. This literature review aimed to examine the research concerning trust dynamics in climate change adaptation from different levels of analysis, encompassing the different phases of adaptation and considering the importance of trust in climate change decision-making. The method consisted of systematically reviewing researches on this topic published in scientific articles, by using appropriate and relevant search keywords (e.g., trust, community, natural hazard, climate change adaptation, decision-making) in academic databases. A total of 25 studies met inclusion criteria. All the articles focused on the latter phases of the climate change adaptation cycle, specifically implementation and monitoring/evaluation, with limited attention devoted to decision-making related to earlier phases of preparation, assessment of risks, and identification and selection of adaptation options. The reviews also indicates that psychological trust is related to different adaptive actions (e.g., adoption of renewable energy technologies), and low- and high-impact mitigation behaviors (e.g., acceptance of paying taxes for actions that mitigate climate change). Therefore, this review underscores the significant role of psychological trust dynamics in shaping individuals’ decision-making processes concerning climate change adaptation, thereby yielding immediate and direct implications for climate systems. Therefore, it is essential to actively promote the culture of trust within the context of climate change adaptation.

Top-down and bottom-up initiatives for the Walloon landscapes and their inhabitants

Landscape protection implies selecting values for preservation and legitimising specific interests while potentially excluding others. Literature on landscape protection recognises the need to move beyond the expert-dominated conservationist paradigm. Based on an analysis of laws, decrees, charters, web documents and semi-structured interviews, this research examines the processes and results of public involvement in landscape protection in Wallonia. While ‘democratisation’ of the landscape gains ground in institutional protection tools, citizen initiatives are mostly carried by only a few inhabitants or isolated groups and wield limited influence in the decision making process. Nonetheless, citizens’ groups increasingly invoke landscape interest in local initiatives, expressing a desire to share their values and develop local projects. This observation underlines a gap in participation processes. Rights and responsibilities of the population depend not only on their place in the decision-making process but also on their interests and attitudes towards their landscapes.

The effectiveness of public participation through forest advisory committees: Twenty years of shifting perspectives of Local Citizens Committee members in Ontario

In Canada, the most widespread approach to citizen participation in forestry decision-making is forest advisory committees. In this paper, we report on the results of a survey of forest advisory committee members that has been repeated every few years since 2001. We clustered the survey questions to create composite variables representing seven dimensions of the functioning and effectiveness of forest advisory committees: efficiency, representation, voice, decision-making process, trust in forest managers, effectiveness, and the availability, relevance, complexity and trustworthiness of information. While most committee members continue to view the process positively, after a steady improvement of committee members’ overall assessments since 2001, in the most recent survey, the proportion of those who are unsatisfied has grown. Moreover, effectiveness has consistently been assessed less favourably than the other six dimensions that we considered—dimensions upon which effectiveness presumably depends. Part of the reason is that a significant minority of committee members feel that they have little meaningful influence over forest management and that the relevance of the committees has declined. This points to the need for continual attention from policymakers to the matter of how and how much forest advisory committees are enabled to influence the direction of forest management.

Geology as Unconforming Infrastructure For the Hosting of Nuclear Waste

As the dramatic consequences of climate change finally begin to motivate governments around the world to explore how to move away from a dependence on fossil fuels, nuclear power is back on the agenda in the UK as a potential energy source. However, this new-found enthusiasm confronts a fundamental challenge—namely, that the radioactive wastes, accumulating since the very first nuclear power stations were built in the 1950s, have yet to be made safe for the long-term future. At the governmental level, there is a clear international commitment to the view that the most secure option for the management of radioactive waste matter is burial deep underground in an engineered geological disposal facility (GDF). Finland leads the international field, and the repository at Onkalo is expected to be fully operational by 2025. The Swedish government approved plans for the construction of an underground repository for spent nuclear fuel in 2022, with Canada, France, Japan, Switzerland, the UK, and the USA all actively engaged in siting and design initiatives. Strategies for generating public acceptance of geological disposal vary, as do the modes of engagement, the investments of time and money afforded, and the decision-making processes. These processes are conceptually and politically challenging. They require not only technical expertise and scientific understanding across an entire range of disciplines, but also the imaginative capacity to think across scales of time and space in what Ele Carpenter (2016: 14) has suggestively referred to as ‘reverse mining’.

СОВРЕМЕННЫЕ ПОДХОДЫ К ТРАНСФОРМАЦИИ ПОТРЕБИТЕЛЬСКОГО ПОВЕДЕНИЯ РАБОТНИКОВ УГОЛЬНОЙ ОТРАСЛИ НА РЫНКЕ МЕДИЦИНСКИХ И ФАРМАЦЕВТИЧЕСКИХ ТОВАРОВ И УСЛУГ

In modern conditions, for pharmacy, as an integral part of healthcare, new concepts and technologies of pharmaceutical services and, in general, pharmaceutical care, aimed at consumers of medicines of different categories and professional groups, have become a powerful incentive for further development. Important importance in working with consumers of medical and pharmaceutical goods and services is attached to marketing research of consumer behavior; the study of preferences in the selection of goods factors influencing the decision to purchase. Of particular importance is the consumer behavior of modern pharmacy customers, which is changing due to an imbalance between the state of the pharmacy system's customer base and existing methods of customer counseling. There is a need to focus on different segments of consumers, each of which requires specific client technologies that contribute to the transformation of consumer behavior from "standard" to individual, corresponding to the status, mentality, financial capabilities, level of information literacy, typology of the buyer. Studying the assessments and opinions of respondents helps to identify patterns in consumer behavior and makes it possible to develop a more thoughtful strategy for information and advisory work with employees of the coal industry, paying special attention to issues of pharmaceutical consulting, information, attentive service, the use of new forms and methods of work that would increase consumer interest in purchasing effective and safe medicines. The consumer's decision-making process is considered, as a rule, as part of the following stages: consumer awareness of the problem, information search, evaluation and selection of purchase alternatives, purchase, use of purchase and evaluation of the solution. The factors of consumer behavior or purchasing decisions in relation to the buyer are conditionally divided into internal and external. Pharmaceutical organizations that sell medicines seek to influence consumer behavior by building their activities based on the concept of marketing. Knowledge of the basics of marketing is necessary to manage consumer behavior in the market.

When We Are Happy, We Are the Same—Emotions as a Boundary Condition for the Impact of Cultural Differences on Strategic Decisions

AbstractStrategic decision-making research has mainly relied on the values-based approach to culture. However, the dynamic constructivist approach to culture has shown that cultural tendencies may also be altered by contingency factors in the decision-making process itself. We theorize based on the appraisal tendency framework as well as the concept of cultural affordances that emotions, such as happiness, can alter the cultural dispositions of managers from Western and East Asian contexts. To test our hypotheses, we conduct a lab-in-the-field experiment with 187 executives from China and Germany, and measure emotions based on participants’ psychophysiological skin conductance responses. Our results show that happiness moderates and can even reverse initial cultural dispositions in executives’ strategic decision-making behavior. These findings suggest that emotions may be important contingency factors that can alter the initial cultural dispositions of decision makers in the strategy process.

Artificial intelligence as a new answer to old challenges in maternal-fetal medicine and obstetrics.

Following the latest trends in the development of artificial intelligence (AI), the possibility of processing an immense amount of data has created a breakthrough in the medical field. Practitioners can now utilize AI tools to advance diagnostic protocols and improve patient care. The aim of this article is to present the importance and modalities of AI in maternal-fetal medicine and obstetrics and its usefulness in daily clinical work and decision-making process. A comprehensive literature review was performed by searching PubMed for articles published from inception up until August 2023, including the search terms "artificial intelligence in obstetrics", "maternal-fetal medicine", and "machine learning" combined through Boolean operators. In addition, references lists of identified articles were further reviewed for inclusion. According to recent research, AI has demonstrated remarkable potential in improving the accuracy and timeliness of diagnoses in maternal-fetal medicine and obstetrics, e.g., advancing perinatal ultrasound technique, monitoring fetal heart rate during labor, or predicting mode of delivery. The combination of AI and obstetric ultrasound can help optimize fetal ultrasound assessment by reducing examination time and improving diagnostic accuracy while reducing physician workload. The integration of AI in maternal-fetal medicine and obstetrics has the potential to significantly improve patient outcomes, enhance healthcare efficiency, and individualized care plans. As technology evolves, AI algorithms are likely to become even more sophisticated. However, the successful implementation of AI in maternal-fetal medicine and obstetrics needs to address challenges related to interpretability and reliability.