Organizational Decision-making Processes Research Articles

Agentic AI in Data Analytics: Transforming Autonomous Insights and Decision-Making

This article explores the transformative impact of Agentic AI systems on modern data analytics, examining how these autonomous agents are revolutionizing organizational decision-making processes. The article demonstrates how Agentic AI enables unprecedented automation and accuracy in data analysis across various sectors through detailed analysis of implementation strategies, architectural considerations, and real-world applications. The article encompasses key domains, including retail, financial services, and manufacturing, highlighting how these systems reduce manual intervention while improving analytical accuracy and operational efficiency. The article also addresses critical implementation challenges and organizational considerations, providing insights into successful deployment strategies and necessary adaptations for optimal utilization of Agentic AI capabilities.

Exploring Facilitators and Barriers to Managers’ Adoption of AI-Based Systems in Decision Making: A Systematic Review

Introduction—Decision making (DM) is a fundamental responsibility for managers, with significant implications for organizational performance and strategic direction. The increasing complexity of modern business environments, along with the recognition of human reasoning limitations related to cognitive and emotional biases, has led to a heightened interest in harnessing emerging technologies like Artificial Intelligence (AI) to enhance DM processes. However, a notable disparity exists between the potential of AI and its actual adoption within organizations, revealing skepticism and practical challenges associated with integrating AI into complex managerial DM scenarios. This systematic literature review aims to address this gap by examining the factors that influence managers’ adoption of AI in DM. Methods—This study adhered to the PRISMA guidelines. Articles from 2010 to 2024 were selected from the Scopus database using specific keywords. Eligible studies were included after rigorous screening and quality assessment using checklist tools. Results—From 202 articles screened, a data synthesis of 16 eligible studies revealed seven major interconnected factors acting as key facilitators or barriers to AI integration within organizations. These factors—Managers’ Perceptions of AI, Ethical Factors, Psychological and Individual Factors, Social and Psychosocial Factors, Organizational Factors, External Factors, and Technical and Design Characteristics of AI—were then organized into a complex analytical framework informed by existing theoretical constructs. Discussion—This contribution provides valuable insights into how managers perceive and interact with AI systems, as well as the conditions necessary for successful integration into organizational DM processes.

The Mediating Role of Leader-Member Exchange in the Relationship Between Paternalistic Leadership and Turnover Intention: A Study on Millennial Employees in China

This study investigates the relationship between three-dimensional paternalistic leadership and turnover intentions among millennial employees in China, with a focus on the mediating role of leader-member exchange (LMX). A sample of 241 millennial employees from private enterprises was analyzed using SPSS and PLS techniques. The findings indicate that LMX effectively mediates the influence of three-dimensional paternalistic leadership on turnover intentions. The study's use of single respondent and cross-sectional data may limit the robustness and generalizability of its conclusions. Nevertheless, the results offer valuable insights for management practices and decision-making processes in organizations. This research contributes to the literature by highlighting LMX as a crucial mediator in the relationship between three-dimensional paternalistic leadership and turnover intentions among millennial employees. It underscores the importance of further exploring LMX's mediating role in similar contexts, thereby advancing theoretical understanding and practical applications in leadership and employee retention strategies.

The Impact of Leadership Styles, Cultural Dimensions and Values on Academic Leaders

This study investigates the cultural dimensions, values, and leadership styles of school leaders in Indian K-12 and European schools, specifically focusing on cross-cultural differences. The objective is to explore how leadership styles and cultural orientations differ between Indian and European school leaders and to examine how these variations impact organizational culture and decision-making processes. A non-experimental quantitative research design was employed, utilizing standardized instruments such as the Multi-factor Leadership Questionnaire (MLQ-Form 6S), OCTAPACE, and the Scale of Individual Cultural Values (CV) to measure leadership styles and cultural dimensions. Data were collected from 165 Indian leaders across Punjab, Haryana, Delhi-NCR, and Uttar Pradesh, as well as 156 European leaders from Croatia, Hungary, Poland, and others, using purposive and convenience sampling methods. Independent t-tests and Discriminant Function Analysis (DFA) were used to compare the two regions' leadership styles and cultural orientations. The findings reveal that Indian school leaders predominantly demonstrate transformational and laissez-faire leadership behaviors, influenced by hierarchical structures prioritizing collective goals and authority delegation. Indian leaders scored higher on openness, trust, and collaboration dimensions, which align with collectivist and hierarchical cultural norms. In contrast, European leaders emphasized confrontation, authenticity, and individual autonomy, reflecting a preference for more egalitarian and individualistic decision-making approaches. These insights contribute to a deeper understanding of how leadership and cultural values shape educational practices in different contexts.

Effective decision-making in public health organizations: reference to the COVID-19 pandemic.

The role of public health organizations during the COVID-19 pandemic was crucial. These groups acted to slow the spread of infection through the implementation of initiatives, policies, research and more. However, the rapidly changing and uncertain climate of the pandemic resulted in suboptimal processes and decision-making within these organizations. These already complex organizations and networks of people became even more nuanced. Thus, organizational decision-making processes must be improved upon based on previous experiences and lessons learnt. With minimal peer-reviewed literature available, resources for effective organizational decision-making in these organizations are scarce. This served as the impetus for this review. To conduct this literature review, both peer-reviewed and grey literature were incorporated to better understand effective organizational decision-making practices for public health organizations. Recommendations found in the literature review were identified, coded and themed to provide a novel decision-making framework to be used by public health executives. Nine key themes of effective organizational decision-making were identified, including utilize decision-making tools, define the problem and acknowledge an imminent decision, establish decision rights, outline a clear escalation path, create a supportive organizational culture, set decision objectives and goals, and evaluate decision alternatives. These findings in conjunction with existing decision-making models were used to create a seven-step effective decision-making framework for public health organizations. The review and analysis of effective organizational decision-making practices is instructive. Public health executives and decision-makers should incorporate the themes identified and employ the proposed decision-making framework to encourage improved decision-making practices.

Centralization or decentralization? Power allocation in team innovation management.

Power disparity, as an important form of internal team hierarchy, presents a "double-edged sword effect". To reconcile the inconsistent effects and systematically explore the different mechanisms of power disparity, this study constructs a comprehensive theoretical model based on power functionalism and power conflict theory, with team coordination and team conflict as dual mediators, and power legitimacy as moderator. By collecting valid questionnaires from 76 teams across 27 different types of companies in various regions, statistical analysis and hypothesis testing were conducted on the data. The results conclude that power disparity positively influences team innovation performance through the team coordination path and negatively affects it through the team conflict path. However, under the moderating effect of power legitimacy, the negative effect of the team conflict path is suppressed, and the positive effect of the team coordination path is strengthened, thus ensuring that power disparity has a positive effect on team innovation performance. This study provides a useful reference for designing the power hierarchy within enterprises, and offers profound insights into effective organizational structure and decision-making processes.

Disengagement through Algorithms: How Traditional Organizations Aim for Experts' Satisfaction

This study examines the use of algorithmic tools in traditional organizational decision-making processes. Through forty semi-structured interviews with managers, engineers, and (expert) users across six European projects, we suggest that initiators deploy algorithms not to automate actions or replace users, but to disengage themselves from prescriptive decision-making. Consequently, the responsibility to choose, select, and decide falls upon the users; they become engaged. Therefore, algorithm evaluation is oriented towards utility, interpretability, and, more broadly, user satisfaction. Further research is encouraged to analyze the advent of a 'satisfaction regime', from platforms to traditional organizations.

Assessing the Risks of Risk Assessments: Institutional Tensions and Data Driven Judicial Decision-Making in U.S. Pretrial Hearings

Abstract Risk assessments, which are predictive technologies designed to augment organizational decision-making processes, are expanding globally. The use of risk assessments may lend legitimacy to official actors who routinely adjudicate highly consequential decisions alongside competing institutional pressures. But because these tools are laden with measurement errors, using them may also magnify institutional tensions and erode the legitimacy of official actors’ decision-making practices. In this article, I use interviews with judges in four large U.S. criminal courts to reveal how they strategically engaged with risk assessment scores to navigate tensions within and among different institutional logics. In pretrial hearings, judges selectively invoked risk scores to legitimate punitive sanctions that mitigated tensions from bureaucratic logics to process high caseloads with limited resources, legal logics to protect public safety and impose the least restrictive conditions, and political logics to follow the law while facing public scrutiny. I discuss the implications of these findings for future research on penal change and the uses of discretion in the age of big data.

Bibliometric Analysis of Accounting Literature on Artificial Intelligence (AI) Adoption in Organizational Functions

Artificial intelligence (AI) is a powerful technology with a high potentiality of transformative drive from traditional analog to digitalized organizational seamless decision processes efficiently and effectively. AI is an emerging area in organizational decision-making with limited number of studies across the globe. However, AI is now gaining considerable attention from the researcher, both at the local and international level. This study aims at providing a systematic review and biometric analysis on AI adoption in organizational functions using Google Scholar databases as the source of data. The study employs the steps of Prepare Reporting Items for Systematic Literature Review and Meta-Analysis Techniques PRISMA (2020) and bibliometric analysis techniques using VOS-View as a tool for analysis of publications performance over time with a view to determining the most influential articles, publication productivity, and direction of studies on AI Adoption in organizational functions for a period of ten years from 2015 to 2024. The analysis reveals that articles published in 2016 by Sage Journal recorded the highest citation of 2707, followed by MDPI Journal with total citations of 1922 in 2021, while Elsevier presents the lowest citation of 87 citations over the period of 10 years in the database used. These articles were written on more than 20 areas of application of AI in organizational functions.

Application of artificial intelligence in business management and financial market forecasting

In today's business world, artificial intelligence as a new technology has provided dynamic and flexible capabilities in organizational decision-making processes, considering that organizational decision-making often faces challenges due to the complexity and multiplicity of factors affecting it. The application of artificial intelligence as A powerful tool can be effective in improving the organizational decision-making process and improving the performance of organizational managers. Artificial intelligence is one of the popular and widely used new sciences in almost all aspects of life and can do things faster and more accurately. The numerous advantages of artificial intelligence and its wide applications today are not hidden from anyone. Financial services companies are constantly looking for ways to gain superiority in the capital market and surpass their competitors. To do this, companies are moving away from old systems and models They adopt a more agile business that includes artificial intelligence techniques in capital markets, artificial intelligence in financial markets and machine learning (ML). In capital markets, companies use artificial intelligence and ML projects in coordination with RPA robotic process automation technologies to meet customer requests, speed up financial market analysis, and more accurately identify risk in the business process.

Who versus when: Designing decision processes in organizations

This paper analyzes concurrent versus sequential decision-making in a model where two units first communicate and then make decisions, attempting to both adapt to their local conditions and coordinate with their partner. Sequential decision-making improves overall information sharing compared to concurrent decision-making. However, first movers also have an incentive to over-adapt to their state, knowing second movers will conform to their decision. A surplus-maximizing headquarters prefers sequential decision-making to concurrent if and only if (i) the two units' local conditions have sufficiently different volatilities and (ii) their need to coordinate is sufficiently asymmetric or low. Finally, sequential decision-making is shown to be optimal even when allowing for additional governance structures involving the reallocation of decision rights across the units and the headquarters and is shown to render some commonly-analyzed forms of decentralization sub-optimal.

Unveiling the intellectual nexus between Peirce’s synechism and Goldratt’s theory of constraints: insights for management and organization studies

Purpose Charles Sanders Peirce (1839–1914), recognized as the father of philosophical pragmatism, has been described as a philosopher’s philosopher. Eliyahu Moshe Goldratt (1947–2011), considered the father of the management philosophy theory of constraints (TOC), has been described as being, first and foremost, a philosopher. The TOC body of knowledge is mainly preserved as concrete methodologies used in the management discipline. By examining the foundational elements of synechism and the TOC, the purpose of this study is to investigate the intellectual connections between the arguments and legacies of Goldratt and Peirce. Although this connection is worthy of much further investigation, the research emphasizes the possible implications from a management philosophy perspective. Design/methodology/approach Based on a “review with an attitude,” the authors first examined the foundations of Goldratt’s TOC through the lens of Peirce’s synechism. Next, the authors then examined how the study of Peirce combined with a selection of contemporary research in the management and organizational studies domain could point out a direction toward completing Goldratt’s unfinished intellectual work to establish a unified science management while addressing some of the current gaps in the TOC body of knowledge. Findings Major findings show that synechism’s growth may extend TOC knowledge, improving managerial practice in organizations. Findings on the convergent ideas of both also reveal that Goldratt valued all synechism categories, emphasizing the importance of not overlooking Firstness. Furthermore, the study analyzes the abductive inference demonstrated in the two use cases, introducing an additional metaphor to the management of organizational systems inspired by Peirce’s philosophical concepts. The research concludes that incorporating TOC and synechism principles can enhance management and organizational practices and enrich management philosophy and theories. Research limitations/implications This pioneering research opens promising opportunities to draw parallels between Peirce and Goldratt. Interdisciplinary collaboration will enhance the rigor and validity of integrating synechism and TOC. Experts in organizational behavior, systems theory and complexity science can provide valuable insights into this debate, while practitioners and consultants could help identify barriers and opportunities for integrating synechistic principles. Practical implications The study proposes a novel abductive approach using Peirce’s cable metaphor as an initial framework to build a unified science of management based on evolutionary stages: TOC, common sense and connectedness. Originality/value This research reinforces the argument that contemporary management practices need philosophical thinking. The authors argue that re-evaluating the foundations of management thought enriches the decision-making process in organizations and the understanding of contemporary theories in management and organizational studies.

The Role of Decentralised Managers in Decision-Making in a Large Industrial Company

The importance of decentralised managers in the organisational decision-making process has been the subject of studies advocating different concepts. This study aims to comprehend the role of decentralised managers in the decision-making process of a large industrial company. To this end, the case study method was adopted. Semi-structured interviews were conducted with the organisation’s top manager and decentralised managers. Based on the results of this investigation, it was possible to see that the organisation’s decentralised managers have a high degree of influence on the decision-making process and are responsible for adapting strategies and decisions according to the specific needs of their areas of activity. Therefore, this study significantly contributes to the theoretical and practical understanding of organisational decision-making processes. Furthermore, it provides a valuable foundation for further research into the decision-making processes of decentralised managers, thereby addressing a gap in the existing literature on their influence on organisational decision-making.

Bridging power and fairness: unravelling the impact of informal networks on organisational justice in the ARAB region

PurposeWasta, the prevailing form of informal networks in the Arab region, exerts a significant controversial influence on organisations in this region. Despite the pervasive negative perceptions and alleged detrimental effects of Wasta, it remains a frequently employed practice. This research aims to comprehensively explore the influence of Wasta on organisational justice across organisations in the Arab world, with Jordanian organisations taken as an illustrative case.Design/methodology/approachEmploying a qualitative approach, semi-structured interviews were conducted with 20 employees from various industries in Jordan.FindingsThe study reveals that Wasta significantly affects distributive, procedural and interactional justice within organisations, eliciting feelings of unfairness and hopelessness among employees.Practical implicationsThis study recommends that HR departments focus on implementing ethical policies and standards to enhance transparency in organisational decision-making processes. By understanding and addressing the implications of Wasta, organisations can foster a more just and equitable workplace environment.Originality/valueThis study advances our understanding of informal network theories in the Arab world by highlighting the interconnectedness between Wasta and organisational justice, and its profound impact on the work environment and employees. This study also explains how Wasta directly influences decision-making processes, at high managerial levels.

The Information Cocoons in Military Decision Making and Strategies for Coping

As we all know, the information cocoon has a broad impact on people's basic cognitive abilities such as memory, decision-making, and judgment. This article first extends the concept of information cocoons to the field of command and decision-making behavior, and studies the harm and response measures of information cocoons to command and decision-making. The paper first elaborates on the causes of information cocoons, including technical factors, organizational structure factors, and psychological factors. Secondly, the harm of information cocoons to command decision-making was analyzed, including hindering accurate judgment of the battlefield situation, increasing battlefield risks, and increasing the likelihood of battlefield losses.Then, corresponding measures were proposed, including the application of technical means and optimization of organizational structure and decision-making processes. Finally, the importance of improving psychological resilience and leadership abilities was emphasized. The research conclusion of this article is helpful for command decision-makers to effectively overcome the challenges brought by the information cocoon to command decision-making and improve the correctness of decision-making.

CEO Turnover and Openness of Decision-making Processes in the Post-succession Phase: Exploring a Threat-rigidity Perspective

This study examines how top leader turnover in the public sector affects organizational strategic decision-making processes in the post-succession phase. Survey responses of managers were combined with a novel database on CEO turnover in the U.S. Federal Government. Drawing on threat-rigidity theory, we hypothesize that as CEO turnover is perceived as a threatening event for both managers and CEOs themselves, organizations as a whole respond by becoming more rigid, centralizing strategic decision-making and restricting the flow of information. This has knock-on effects on the quality of strategic decisions and their implementation, with detrimental effects on the delivery of public services.

Impact of Corporate Governance Structures on Strategic Decision-Making Processes in Organizations

Impact of Corporate Governance Structures on Strategic Decision-Making Processes in Organizations

Inside the Black Box: Understanding Organizational Decision-Making Processes in VC Funds

Inside the Black Box: Understanding Organizational Decision-Making Processes in VC Funds

Determine Intraday Trading Currency's Trend Framework Evidence From Machine Learning Techniques

The purpose of this study is to determine the intraday hourly trading trends of currencies using predictive modeling techniques. The study encompasses two distinct intraday time intervals of 30 minutes and 1 hour, analyzing currencies from 8 different countries. It incorporates the use of wavelets MODWT to identify trends and noise in intraday currency analysis. Three predictive models, namely Support Vector Regression, Recurrent Neural Network, and Long Short-Term Memory, are applied to relative time series data to predict intraday trading currency trends. The study reveals significant noise presence in three currencies based on MODWT analysis. Additionally, it demonstrates that deep learning techniques, such as LSTM, outperform traditional machine learning approaches in accurately predicting intraday currency trends. This study contributes substantially to the theoretical understanding of international finance and provides practical insights for real-time problem-solving in currency markets. Further, this research adds to the discourse on leveraging sophisticated analytical methods within the domain of business intelligence to enhance decision-making processes in organizations operating within dynamic and complex financial environments.

Applying Design Thinking to Develop AI-Based Multi-Actor Decision-Support Systems: A Case Study on Human Capital Investments

Artificial intelligence, particularly machine learning, has revolutionized organizational decision-making processes by assuming many decision responsibilities traditionally allocated to humans. In this scenario, decision-support systems based on AI have gained considerable relevance, although the attitudes of managers toward intelligent agents are still unbalanced towards human intervention in decision-making. An additional level of complexity arises when the development of these systems occurs within the context of investments in human capital, such as startup funding or organizational development. In this field, decision-making becomes even more critical, since it implies the will, goals, and motivations of every human actor involved: the investors and those seeking investments. termed multi-actor decision-making, this process involves multiple individuals or groups of individuals who, starting from non-coincident objectives, must reach a mutual agreement and converge toward a common goal for the success of the investment. Considering these challenges, this study aims to apply the design thinking technique as a human-centered methodology to support the design of an AI-based multi-actor decision-support system, conceived by Mylia (The Adecco Group), in the field of organizational development. Additionally, the integration of strategic organizational counseling will be introduced to facilitate the modeling of internal DM processes within the provider organization, enabling the seamless flow of internal behaviors from the decision-support system’s conceptualization to its integration in the external market.