Search

Purpose – The current scenario shows increased adoption of off-chain voting applications in decentralized autonomous organizations (DAOs) to avoid complexity and costs for user engagement in their governance. This paper aims to comprehend the trends and patterns within the DAO community with off-chain voting systems and blockchain usage. Design/methodology/approach – This exploratory study uses a two-pronged quantitative approach, combining descriptive statistical analysis and fuzzy-set qualitative comparative analysis. Input data from different DAO proposals and votes were analyzed. Findings – Results indicate that the 179 DAOs analyzed account for 26,538 proposals and 1,268,474 followers of the entire Snapshot base in January 2023, showing high concentration in engagement. The preferred social media communication channels are Twitter and GitHub, showing a decrease of Ethereum as a main chain, with Polygon and Binance Smart Chain already accounting for 22%. Basic voting can lead to greater user involvement in the voting process. Research limitations/implications – This study complements the traditional governance theory perspective and advances in the emerging literature on DAOs and blockchain with an empirical analysis. Practical implications – As blockchain technology gains increasing adoption, comprehending trends and patterns within the DAO community becomes pivotal in identifying opportunities and challenges for innovation and improvement. Social implications – Findings can facilitate the development of improved governance models and decision-making processes for DAOs, leading to a more robust and sustainable ecosystem. Originality/value – This study presents a broader IT-based governance foresight via blockchain while providing an understanding of the voting process, technology features and governance mechanisms for social community engagement and decision-making in DAOs.

The management of socio-economic infrastructure projects in developing countries, including roads, bridges, tunnels, railways, ports, airports, dams and others, presents multifaceted challenges, particularly in environments marked by complexity and uncertainty. Despite the efforts of governments in these countries, these types of projects still face numerous risks, including political, technological, regulatory, financial, and market risks. The objective of the study was to examine the practices related to the problem of the decision-making process and risk assessment in the management of socio-economic infrastructure projects in developing countries, focusing on the example of the Algerian experience. This research used a qualitative analysis of the decision-making process through 15 semi-structured interviews conducted with representatives of various institutions and administrations responsible for supervising the East-West highway project in Algeria and several focus groups conducted or observations noted at the meetings where the author participated as a principal engineer at the Ministry of Public Works (project owner) during the different phases of the implementation of this mega-project. This made it possible to carry out a global assessment of current practices and to identify the major risks that can impact the decision-making process to improve the management of socio-economic infrastructure projects in Algeria and also in developing countries. The results of the study reveal the risks related to the complexity of the external and internal environment of the projects, in which among the 13 major risks identified, 61.54% have a high criticality, 30.77% have a medium criticality, and 7.69% have a low criticality. The results show that several important aspects need to be improved, including: 1) strengthening financial stability; 2) political risk mitigation; 3) implementing economic stability measures; 4) clarifying contractual aspects; 5) promoting cultural sensitivity and communication; 6) improving cost and quality control measures. This study provides valuable guidance to governments, businesses, managers, and other individuals or groups interested in promoting the management of socio-economic infrastructure projects in developing countries.

Technology has become an essential part of modern daily life and society, influencing different aspects of human existence. This article examines the complex connection between technology and society, focusing on the differences between generations such as Gen Z and Millennials compared to Gen X and Boomers. It aims to clarify how societies might effectively utilise technological progress for their benefit. An essential aspect of this investigation is the recognition that the incorporation and assimilation of technological advancements into society structures are crucial milestones in achieving their advantages, particularly from a governmental standpoint. Furthermore, the study explores the profound influence of technology on society, with a specific focus on its ability to enhance digital supremacy, technological expertise, and generational progress. Moreover, the research examines the mutually beneficial connection between technology advancement and economic growth. It highlights the crucial importance of technological progress in stimulating economic growth, explaining how the ongoing development of technology stimulates innovation, promotes economic activity, and influences global economic conditions, including the tensions arising from different generational advancements.

This study explores how the Balanced Scorecard is useful to investigate its application in non-profit organizations, particularly in Waqf-based Pesantrens. The Balanced Scorecard considers four aspects: financial, customer, internal business, and growth and learning. The financial perspective relied on the institution’s annual report, while customer perspectives were collected via a questionnaire distributed among 100 individuals who regularly contribute to the charitable organization. Data used to evaluate learning performance, growth, and internal business came from Pesantren directors and managers through stakeholder interviews. The results demonstrate that, among these aspects, the customer perspective holds the most significance for non-profit organizations such as Waqf-based Pesantren institutions, receiving the highest score of 43. Next comes the financial aspect with a score of 21.86, while growth and learning and internal business share a score of 20 each. This emphasizes the crucial role of prioritizing the needs of customers in the strategic planning of non-profit organizations, specifically in Waqf-based Pesantren institutions. The results contribute insights for these organizations to enhance their strategic management practices by emphasizing the importance of the customer perspective in their decision-making processes.

The article's goal is to explore how the economic, social, and environmental sustainability accounting components affect decision-making (DM) in the industrial sector of Sudan. This can assist companies in understanding and disclosing the benefits and drawbacks of their activities. The practical significance of scientific research is found in the way that the research conclusions will help to clarify sustainability-related concerns and reinforce Sudanese industrial businesses' dedication to them. Furthermore, there aren't many studies that address this subject in the context of Sudan. The results of the research show that the economic dimension has a positive impact on decision-making in the Sudanese industrial sector. It was also found that the social dimension plays a part in DM. On the other hand, DM Sudanese industrial businesses lack an environmental dimension. According to the study's recommendations, accounting regulators must develop guidelines and frameworks to help accountants measure and disclose sustainability information. Future research should continue to examine the impacts of sustainability development issues on Sudanese manufacturing firms to raise awareness of sustainability issues among accountants and management.

In Israeli society, the perception of nursing homes differs between Arab and Jewish populations. For Arab Muslims, family plays a central role in elderly care, considering it a core value in Arab culture. This study examines the elderly's involvement in deciding to move to a nursing home and utilize formal community services. Findings show that family members in the Arab community struggle with this decision, and the high involvement of the elderly themselves provides legitimacy to the decision. Muslim families take longer to decide regarding transferring to a nursing home than Jewish families, indicating the decision's complexity. Factors contributing to this matter include limited knowledge about nursing homes, lack of adapted institutional services, and difficulty obtaining culturally aligned medical care. The study highlights the need for culturally sensitive institutional services and increased knowledge accessibility. These findings can guide policymakers and healthcare providers in developing tailored solutions to address the unique needs of Israel's elderly population across diverse cultural and religious backgrounds.

Purpose: The aim of this study is to examine how the integration of Emotional Intelligence (EI) and Artificial Intelligence (AI) in leadership can enhance leadership effectiveness and influence the development of future leaders. Design / Method / Approach: The research employs a mixed-methods approach, combining qualitative and quantitative analyses. The study utilizes secondary data sources, including scholarly articles, industry reports, and empirical studies, to analyze the interaction between EI and AI in leadership settings. Findings: The findings reveal that the integration of EI and AI significantly improves decision-making, strategic planning, talent management, and communication within organizations. Leaders who leverage both EI and AI experience higher employee satisfaction, improved team performance, and enhanced organizational outcomes. Theoretical implications: This study contributes to leadership theory by introducing a novel framework that demonstrates the complementary roles of EI and AI in leadership. Practical implications: The research offers practical guidelines for leadership development, emphasizing the need for future leaders to integrate EI and AI skills in order to navigate complex business environments successfully. Originality / Value: The paper provides an original framework for the integration of EI and AI in leadership, offering new insights into how these two elements can work together to improve leadership effectiveness. Research limitations / Future research: Future research should further explore the empirical impact of EI and AI integration in various industries and leadership levels to generalize findings across broader contexts. Paper type: Conceptual.

The oil and gas industry is known for its rapid technological advancements and the complexity of its operations, increasingly relying on data-intensive management. As subsea projects—from exploration to decommissioning—become more complex and data-driven, integrating knowledge management (KM) and database management systems (DBMS) has become essential. The research specifically explores how KM and DBMS contribute to decision-making, utilizing a quantitative methodology through a questionnaire survey. Findings reveal that KM processes significantly improve the effectiveness of non-spatial data management, highlighting KM's crucial role in facilitating technology adoption and operational efficiency. However, the influence of KM on spatial data management and overall decision-making is found to be limited, indicating the necessity for more adaptive and integrated KM strategies that serve the unique requirements of database systems. This study underscores the critical but nuanced role of KM and DBMS in the oil and gas industry, advocating for tailored KM strategies to optimize database management. It suggests future research into the interplay of KM with emerging technologies like AI and machine learning to enhance database management. This investigation stresses the importance of holistic KM practices in effectively managing the intricate data landscapes of subsea project services, thereby contributing to the broader discourse on KM, DBMS, and decision-making in complex settings.

This study aims to examine the degree of financial literacy and practices of financial knowledge among MBA students in Nepal. Four prominent universities were selected for study: Tribhuvan University, Kathmandu University, Pokhara University, and Purbanchal University. The descriptive and analytical research approach was applied to analyze the data. Data were collected through questionnaires from 320 students by using convenience and stratified sampling methods. The analysis was conducted using the SPSS software system. The results highlight the complex interplay of factors influencing financial behavior and literacy among MBA students, emphasizing the importance of education, familial influence, and media exposure in shaping financial attitudes and decision-making. The study delves into several key aspects of financial behavior, influence, attitude, literacy, and knowledge sources among MBA students. Notably, respondents displayed positive financial behaviors such as reading for knowledge enhancement and prudent spending practices. Parental influence emerged as the most significant factor shaping financial decisions, followed by media and internet exposure. Respondents generally exhibited a favorable financial outlook and demonstrated understanding in various financial literacy domains, though areas for improvement, particularly in investment risk comprehension, were identified. The study shows how education, family influence, and media exposure affect MBA student’s financial think, how people handle finance, like their education and where they get information from. This is seen as reflected in financial literacy scores ranging from 1.43 to 3.86, with an average of 2.405 and a standard deviation of 0.449, suggesting below-average scores and reduced unpredictability.

Neuromarketing, an emerging subject and generating diverse body of knowledge in the extant literature, this study aims to present qualitative and quantitative knowledge of the neuroscientific domain by analysing the application of various neuromarketing tools and techniques in conducting the research studies. This paper comprises a systematic review of 61 journal articles combined with bibliometric analysis of 577 peer-reviewed journal articles following the PRISMA framework, employing content analysis and keyword co-occurrence analysis. The comprehensive analysis presented a research profile illustrating chronological trends in neuromarketing research and discovered potential new domains, demonstrating explored and unexplored practical utility in neuromarketing. The results highlight the application of Functional Magnetic Resonance Imaging (fMRI), eye-tracking, and neural networks for data analysis as prospective areas in neuroscientific research. An overview of existing neuroscientific tools was presented based on the user context and research outcomes, outlining their benefits and limitations, along with ethical concerns. A theoretical framework was proposed to illustrate the neuromarketing effect on consumer behaviour, suggesting potential areas for future investigation. The findings of the study will be of interest to scholars and marketers in providing the insights on various neuro tools and techniques, and its significant role in decision-making, such comprehension may improve marketing effectiveness.

This study contributes to the topic of small and medium‐sized enterprise (SME) decision‐making peculiarities from a resource‐based view (RBV). It provides empirical evidence on the relationship between the decision of SMEs and a variety of information sources. We analysed a comprehensive dataset drawn from the Global Competitiveness Project on SMEs' competitiveness, including cross‐sectional data of 784 businesses from eight countries. The extent of information used by SMEs is positively affected by the intensity of competition, networking and the existence of formal and informal relationships, the higher level of innovation activity and a more complex compensation system. We could only partially support the fact that the amount of information used by SMEs in decision‐making is positively influenced by their marketing practices. The SME leaders should consider the fact that their business is much smaller than their potential benchmarking counterparts, and a mere imitation of decision‐making‐related information sources is not necessarily leading to the desired outcome. [ABSTRACT FROM AUTHOR]

Automation of auxiliary business processes (specifically accounting, management, and marketing) has long ceased to be an experiment and has become necessary. This necessity is a direct result of the impact of using automated devices and technical means, as well as computing technology based on mathematical methods, on the speed of decision-making and task execution, labor cost levels, resource utilization efficiency, the number of errors, and the quality of products or services. The article outlines the modern principles and tools of automation in accounting, management, and marketing. The research highlights important aspects of business process automation and identifies some key points. Based on the results obtained, a deep analysis of the interaction between humans and machines in automated accounting, management, and marketing systems can be conducted.

In the race to forecast consumer behaviours and purchase patterns, a culmination of new ideas, theories, and research is brought forth and used. One such contemporary study on consumer behaviour is the subject of neuromarketing. An underlying theme among several key concepts in defining neuromarketing is the ability to measure consumers’ brain activities; it aims to understand the reasoning and reactions toward specific offerings. Although the field of study has garnered worldwide interest, the subject of neuromarketing is only starting to gain traction in Malaysia, with only a few existing literatures observed. This study plans to assess the readiness of companies in Malaysia to implement neuromarketing as part of their overall strategic marketing plan, as well as the comfort level of companies in deploying neuromarketing to increase the effectiveness of the companies’ performance. By applying mixed-method research, several small to medium-sized enterprises (SMEs) would be selected to explore and subsequently examine their comprehension, readiness, and implementation of neuromarketing.

This study proposes and evaluates a novel approach utilizing ensemble machine learning techniques for personalized meal services to address a critical gap in understanding AI-powered decision-making within the food delivery and restaurant industry. We draw inspiration from diverse fields, including non-traditional simulation methodologies and open innovation dynamics, to create a framework that leverages the combined strengths of individual algorithms. Three machine learning algorithms – decision trees, logistic regression, and naïve Bayes – are rigorously evaluated for their efficacy in classifying and assigning algorithms within an ensemble model for a new service. A simulated dataset, informed by expert tagging, is the training ground, ensuring practical relevance. We employ the voting probability metric on a held-out test set to provide a robust measure of accuracy in this critical task. Our findings reveal the significant potential of AI-powered personalized meal services. Ensemble models demonstrate high accuracy, showcasing the collaboration of combining individual algorithms. This originality lies in applying ensemble techniques to a business case with far-reaching implications for management and societal well-being. Beyond technical success, we explore this technology’s broader impact. AI-powered food recommendations can enhance accessibility for individuals with dietary needs, promote healthier lifestyles through nutritious meal suggestions, and generate new job opportunities. Acknowledging limitations and future research avenues, we invite further exploration of diverse machine learning algorithms and broader applications across various domains.

This study investigates how consumers make decisions when using online food delivery services in Thailand, with a particular focus on the price-related factors that influence their choices. The research adopts a mixed-method approach, combining quantitative and qualitative data collection and analysis. Quantitatively, data was gathered from 392 respondents through closed-ended questionnaires, and statistical analysis software was used, employing binary regression to explore the relationship between various independent variables (including gender, age, education, marital status, income, residence, experience, reasons, information sources, frequency, and expenses) and the price war strategy, which serves as the dependent variable. Qualitatively, in-depth interviews were conducted with ten purposively selected participants. The qualitative data were analyzed using content analysis and the NVivo software program. The study's results highlight the significant influence of income and information on the price-related decisions in Thailand's online food delivery market. Moreover, consumers in Thailand prioritize factors like price sensitivity, value perception, convenience, promotions, and cultural food preferences when selecting online food delivery services. This understanding is essential for businesses operating in this market to effectively meet consumer preferences and succeed in the competitive online food delivery industry.

Abstract As companies look to differentiate themselves with the help of their suppliers, the need for robust and sophisticated purchasing and supply management (PSM) processes that allow for informed decision-making [...]

Abstract This abstract presents the methodological approach employed in a comprehensive study focusing on decision making in a collaborative manner in disaster management, with a specific emphasis on cross-border disasters in the Balkan region. Disasters, characterized by their sudden and profound impacts on human life, property, and the environment, necessitate a well-coordinated response. Emergency management, which encompasses preparation, response, and recovery phases, relies on the collective efforts of diverse agencies, organizations, and individuals to ensure an efficient response. The preparedness phase is particularly vital, entailing the formulation and execution of plans, policies, and procedures to effectively respond to disasters. Cross-border disasters, which transcend international borders and affect multiple countries and communities, present unique challenges due to the need for coordination and cooperation among various national governments and organizations. This research addresses the multifaceted aspects of disaster preparedness and cross-border disaster management within the intricate context of the Balkan region. The management of disasters demands a coordinated and proactive approach, especially when dealing with cross-border disasters. International cooperation and effective communication are essential for an effective response and minimizing the disaster’s impact on affected communities. Consequently, it is imperative to establish collaborative frameworks that enhance cross-border disaster risk reduction on various levels. To construct the components of a cross-border emergency preparedness framework, an extensive literature review was conducted, identifying ten essential pillars for disaster management. Subsequently, 129 recommendations formed the initial framework, which became the subject of a Delphi study. In this study, 104 experts from 12 participating Balkan countries aimed to reach a consensus on the framework’s elements. The study unveiled common aspects necessary for a cross-border preparedness framework tailored to the Balkans’ geographical characteristics. This framework was jointly endorsed by various emergency management experts with distinct functions and roles in disaster response. The process and results of this thesis underscore the critical need among Balkan countries to establish a tangible and sustained collaborative environment. This environment should foster a shared mindset and create a pathway towards resilient and sustainable cross-border emergency management cooperation and unity among Balkan countries.

Although big data will bring worth for business throughout the entire worth chain, the integration of details analytics about the decision-making procedure is nevertheless a battle. This specific study, based on an ordered literature review, thematic evaluation and qualitative interview findings, proposes 6 steps to create every relevance and rigor in the technique of analytics driven choice generating. Our findings illuminate the main key phases in this specific option procedure, for example matter characterization, evaluation of earlier outcomes, model development, data collection, information analysis, along with techniques on insights within the context of program strategies. Although outcomes are assessed in a sequence of steps, the analysis identifies them interdependent and iterative as. The suggested 6 phase analytics driven choice making process, pragmatic evidence from service techniques, and later scientific studies agenda, source the groundwork for upcoming scholarly research, and can work as a step smart guidebook for internet business professionals.

Theoretical background: The rapid and exponential technological advancements have far-reaching impacts on management information systems, management practices, and human life. The promising outcomes in Artificial Intelligence and cutting-edge research on semantic networks and natural language processing have motivated the authors to envision the future of management technology. Purpose of the article: Our paper focuses on the new communication facilities and artificial intelligence models used to process management-type queries in natural language. Research methods: The article discusses recently developed technologies, proposed by Google and Microsoft, notably Google Bard and Bing integrated with ChatGPT-4. Both chatbots use Generative AI methods and large language models to understand domain-based queries and generate answers. Main findings: The practical and social implications of new models in management practice are discussed. To illustrate the qualities and weaknesses of the features of new technologies, four examples of management decision-making are discussed. The case studies also show differences between these two technologies. Finally, the paper concludes by summarizing the expectations and limitations of Generative AI applications in management. The paper is one of the first publications describing and demonstrating the idea of interfaces in natural language in business-oriented applications.

The study aims to discuss the impact of the analysis of events after the reporting date (subsequent events) on management decision-making. In the interval between the end of the reporting period and the publication of the annual financial report, company management may learn about events that either occurred during the reporting period but were previously unknown or occurred when the financial report was already prepared but not approved. The consequences of these events can be so serious that they require adjustments to the financial statements, changes in the company’s strategy and tactics, and radical management transformations. The paper structures such events depending on their impact on business performance and the procedure for reporting and identifies the determinants and mechanisms for their analysis and correct accounting. To assess the complex impact of events after the reporting period on the financial results of a company, an integral indicator is proposed, a set of management measures is defined in accordance with the values of this indicator, and the mechanism for its calculation and use is demonstrated on the example of a hypothetical scenario. The sensitivity analysis of this indicator to fluctuations in the weighting coefficients of its components was performed using the Monte Carlo method. In an environment where transparency, accountability, trust between key stakeholders, adaptability, and proactivity are crucial for effective management, this indicator can be used as an effective metric that is taken into account by auditors, regulators, clients, investors, company management, etc.

This research aims to assess the impact of digitization on management efficiency and strategic decision-making, a pivotal aspect in the contemporary business world. By integrating digital technologies with traditional mathematical models and analyzing survey data from 250 management professionals, the study provides a comprehensive understanding of the multifaceted effects of digitization. The principal outcomes from the mathematical analyses, including Marginal Cost Analysis, Break-Even Analysis, and Linear Programming, indicate substantial improvements in operational efficiency following digitization. Specifically, Marginal Cost Analysis shows a significant decrease in the cost of production, and Break-Even Analysis reveals a reduction in the break-even point by approximately 15%, underscoring enhanced cost-effectiveness. Linear Programming results demonstrate a 20% improvement in resource allocation efficiency. The survey analysis complements these findings, revealing a positive perception of digitization in enhancing managerial adaptability, efficiency, and decision-making effectiveness, with average rating improvements of 0.3, 0.4, and 0.5 points, respectively, on a 5-point scale. Regression analysis further highlights the positive influence of technological affinity on decision-making effectiveness. However, ANOVA results suggest variability in the impact of digitization across different industry sectors, necessitating sector-specific digital strategies. Digitization significantly elevates management efficiency and strategic decision-making capabilities. The integration of digital tools with traditional management techniques results in more informed, efficient, and strategic business decisions. However, the varied impact across sectors and the rapid pace of technological advancement calls for continuous adaptation and sector-specific strategies. These findings provide vital insights for businesses navigating the digital era, emphasizing the strategic integration of digital tools in management practices for sustained success and competitiveness.

This paper explores the role of artificial intelligence (AI) in contemporary management. The author examines how artificial intelligence contributes to the enhancement of leadership efficiency and the optimization of business processes. The focus is on analyzing the capabilities of artificial intelligence for learning, reasoning, self-correction, and their impact on decision–making in the managerial sphere. The article discusses the economic benefits that enterprises can gain from integrating artificial intelligence, including improving the quality of managerial decisions and strengthening competitive advantages.The author describes the evolution of artificial intelligence through generations of models from OpenAI, highlighting their growing abilities in understanding and processing natural language. Examples of the use of artificial intelligence in data analytics are provided, making the findings relevant for both theoretical researchers and practitioners. The article can be useful for those interested in innovative approaches to management and business development.

Innovative projects can be very costly, and making mistakes in their implementation can be expensive for organizations and investors. Therefore, appropriate procedures are needed to minimize the likelihood of such errors, facilitate strategic decision-making, and optimize investments. This paper presents a methodology for assessing the viability and potential of cryptocurrency and blockchain projects based on evaluating individual project components and synthesizing these assessments.The proposed approach suggests considering a project as a collection of individual components with clear metrics that can be assessed; various assessments of these metrics are introduced. As a result, a project manager or investor assigns ratings to its metrics when analyzing several projects and then calculates a final assessment for each project. A project manager can determine the most promising project by comparing the reviews of several projects.This methodology stands out for its simplicity and clarity, and a significant advantage is its reliance on only publicly available data. This approach can be applied as the first step in making investment decisions regarding a specific project when working with investment funds or launchpads, for example. AcknowledgmentThe paper is prepared within the scientific research project “Fundamentals of the phase transition to the additive economy: From disruptive technologies to institutional socialization of decisions” (№ 0121U109557), funded by the general fund of the state budget of Ukraine.

This study examines the influence of founder characteristics on the selection of business growth strategies in companies undergoing an initial public offering (IPO). The research is based upon quantitative analysis of data from entrepreneur-led IPOs on the London Stock Exchange. The study investigates the impact of founder’s work experience, external directorships, education, age, ownership, and the presence of a founder–CEO, on the choice between mergers and acquisitions (M&A) and research and development (R&D) as growth strategies. The results show that founders with a throughput functional background and extensive external directorships are more likely to adopt M&A as a growth strategy. Moreover, founders with higher education levels and a PhD are more inclined towards R&D investment. The findings also suggest that older founders are more likely to invest in R&D, whilst higher levels of ownership tends to deter R&D expenditure. Interestingly, the presence of a founder–CEO is associated with a lower likelihood of investing in R&D and a higher propensity for M&A, although these correlations are not statistically significant. These results shed light on the influence of founder characteristics on strategic decision-making during the IPO stage and provide implications for understanding the dynamics of business growth strategies in transitioning companies.