Organizational Decision Research Articles

From the backroom to the boardroom: Health care chief information officers, stereotypes, and strategic leadership in the digital transformation era.

The digital transformation of the U.S. health care system is underway, but the role of health care chief information officers (HCIOs) in that transformation has been unclear. As the landscape of health care technology continues to expand, there is an increasing need to understand the influence of HCIOs, who are in a unique position to impact key strategic decisions. We seek to demonstrate the strategic importance of HCIOs in meeting the needs of digital transformation, by managing the emergence and strategic implementation of health care technologies to benefit health care organization performance. We also propose that profession-based stereotypes inhibit HCIOs as they may be viewed as behind-the-scenes technicians rather than strategic leaders. Upper echelons (UE) theory demonstrates how HCIOs' unique perspectives gained through education, experience, and the strategic decision-making process also can influence organizational performance. We build on UE to conceptualize the degree to which profession-based stereotypes moderate the decision-making of top management teams). We present two theoretical contributions. First, we introduce a profession-based stereotype moderated model of UE specific to HCIOs. Second, we offer an analysis of the role of HCIOs as strategic leaders in the digital transformation era. We call upon health care scholars and practitioners to examine HCIOs' influence and their roles in health care organization decision-making, top management team interactions, and organizational outcomes as the digital transformation in health care continues.

When less is more: Exploring the relation between delay discounting rates in a personal and organizational context

ABSTRACT Many work-related decisions involve choosing between alternatives that differ in value (e.g., $100 or $1,000) and temporal availability (e.g., now or four years). Prior studies suggest workers prefer immediate outcomes due to organizational resource uncertainty. However, it remains unclear whether this preference stems solely from the organizational environment or is influenced by a worker’s reinforcement history. This study examined differences in monetary discounting across delays in two contexts: organizational (money allocated to work-related activities) and personal (money spent freely). Conducted in a private security corporation, participants completed two discounting tasks, each testing two amounts across seven delays. Results showed participants systematically favored immediate outcomes in the organizational context. Smaller amounts were discounted more, regardless of context, and personal discounting patterns predicted organizational decisions. Job experience was unrelated to discounting. Findings suggest immediate preferences at work may result from both organizational uncertainty and reinforcement history shaping decision-making.

Ethical Guidelines for the Application of Generative AI in German Journalism

Generative Artificial Intelligence (genAI) holds immense potential in revolutionizing journalism and media production processes. By harnessing genAI, journalists can streamline various tasks, including content creation, curation, and dissemination. Through genAI, journalists already automate the generation of diverse news articles, ranging from sports updates and financial reports to weather forecasts. However, this raises ethical questions of high relevance for media organizations and societies especially when genAI is used for more sensitive topics and at larger scale. To not jeopardize trustworthiness in journalistic organizations, it is important that the use of genAI in journalism is guided by moral principles. We therefore conducted 18 interviews with researchers and practitioners with expertise in AI-based technologies, journalism, and ethics from a German perspective in order to identify guidelines for the ethical use of genAI in media organizations. We derived requirements for the ethical introduction of genAI and actionable guidelines which explain how decision makers in media organizations should address ethical principles for the use of AI in the news production life cycle, in order to contribute to trustworthiness of journalistic organizations and products.

Preventive maintenance on highway roads

Dangerous geological processes such as landslides, mudflows, rockfalls, and bank erosion are observed in many regions of Russia. This paper aims to expand the classification of works on engineering protection of highway sections from hazardous geological processes to reduce the risk of emergencies. The issues of engineering protection of highways are considered, as well as the principles (conditions) formed in the process of their construction, which provide for timely organizational and constructive decisions at the stages of design and subsequent operation. According to the Decree of the Ministry of Transport of the Russian Federation No. 402 dated November 16, 2012, the following classification of works was approved: overhaul, repair of highways, maintenance works of highways. Not only designing new means of engineering protection of highways, but also maintaining the proper functioning of existing ones is relevant for specialists in the field of road construction. A list of recommended measures is designed to ensure reliable and fail-safe operation of retaining walls as well as to analyze the technical condition of landslide protection structures for subsequent measures to prevent emergencies. The present paper indicates a new type of work, i.e. preventive maintenance works, which may involve minor modifications to the retaining wall structure to strengthen it. When they are performed, overhaul of the site is not required.

A new shortcut for competitive sports development? The purpose of and strategy for developing and introducing sepaktakraw in Taiwan.

A growing number of countries and regions have introduced emerging sports in recent years; however, few studies have been conducted to determine how and why they do so. This article focuses on why a new sport, sepaktakraw, was introduced in Taiwan and how strategies for achieving international sporting success were developed in a short period. The sports policy factors leading to the international sporting success model proposed by De Bosscher et al. were adopted as this study's analytical framework. Data were obtained from official government and sport federation documents, media reports, and semistructured interviews with 18 key stakeholders. This study revealed three main reasons for the introduction of sepaktakraw in Taiwan: (1) low introduction costs, (2) breakthroughs to win medals at the Asian Games, and (3) advantageous entry into international sports organization leadership. Seven aspects are prioritized in Taiwan's sepaktakraw development strategy: (1) obtaining government financial support; (2) institutionalizing organisational decision-making; (3) taking universities as a breakthrough point and then gradually shifting to promote popularization at the grassroots level; (4) selecting players on the basis of competition results; (5) using school badminton courts; (6) strengthening coach training; and (7) actively participating in and striving to host international tournaments. The findings could provide guidelines and examples for other countries or regions to follow when introducing new sports and moving towards the successful development of competitive sports.

Hidden Factors of Limited Time and Busyness: A Qualitative, Multicentre Study of the Reasons for Missed Nursing Care.

To explore nurses' perceptions of reasons for missed nursing care. A multicentre qualitative descriptive study was undertaken from August 2022 to January 2023. Interpretive description methodology was used. Individual interviews were conducted with 36 registered nurses and eight licensed practical nurses working in medical, surgical and intensive care units at three public university hospitals in Denmark. Using a semi-structured interview guide, nurses were asked to share their perceptions of reasons for missed care. The analysis was guided by an inductive thematic approach. The nurses' immediate responses to reasons for missed nursing care circulated around limited time and busyness. However, further analysis unfolded layers of reasons described within three themes: being challenged by workload and patients' diverse care needs; falling short on competencies; and being governed by organisational structures and decisions. The study underlines that reasons for missed nursing care are multiple and complex and extend from an individual to an organisational level. They can therefore not be seen nor targeted isolated. Furthermore, there is a need to draw attention to organisation of care and nurses' clinical decision-making to ensure that patient's fundamental care needs are met. Reducing missed nursing care calls for interventions that require nurses to change their working practices, roles and value perceptions. This study provides valuable insight into nurses' perspectives on reasons for missed nursing care, which is pertinent for designing interventions targeting missed nursing care. The study provides insight into nurses' perceptions on reasons for missed nursing care within hospital settings. The findings of the study show that reasons for missed nursing care are multiple and complex and cannot be limited to time and busyness. The findings can be used to inform future interventions aimed at reducing missed nursing care. The reporting of the study followed the consolidated criteria for reporting qualitative research. No patient or public contribution.

Impact of Dobbs v. Jackson Women's Health Organization on Female Sterilization Rates at a Texas Military Medical Center, a Retrospective Cohort Study.

Female sterilization is a common form of contraception in the United States. On June 24, 2022, the United States Supreme Court eliminated the federal standard protecting a woman's right to abortion via Dobbs v. Jackson Women's Health Organization. Since that time, there have been anecdotal increases in sterilization requests across the country, although there are no publications demonstrating this change. This study hypothesized that there would be increased female sterilization rates at a Texas military hospital post-Dobbs decision due to state restrictions as compared with a Washington military hospital. This study retrospectively reviewed female sterilization rates from March 2022 to April 2023. The average rate of sterilization procedures performed pre-Dobbs decision was compared to the average rate following the Dobbs decision in a Texas and Washington military facility due to different state restrictions. The rates of sterilization were also stratified among demographic groups at the Texas military facility. Female sterilizations encompassed 24/230 (10.4%) of the gynecologic surgeries performed pre-Dobbs compared to 110/629 (17.5%) cases performed post-Dobbs (P = .01) in Texas. However, sterilization rates in Washington state remained the same, with 15/80 (18.7%) benign gynecologic surgeries pre-Dobbs and 28/185 (15.1%) post-Dobbs (P = .59). The average age of sterilization pre-Dobbs was 35 years compared to 33 years post-Dobbs (P = .04). Post-Dobbs group was less likely to use a barrier method prior to sterilization (P = 0.01). The reproductive health of military medical beneficiaries at one military hospital was significantly impacted by the Dobbs v. Jackson Women's Health Organization decision. Rates of female sterilization increased significantly. In addition, patients choosing permanent sterilization were younger and were less likely to use alternative, reversible contraceptive methods prior to surgery. This study demonstrates a significant change in contraceptive choices toward methods that incur greater surgical risks and potential for regret, as well as greater financial costs to the military health system.

Student and Physician Views of How the Dobbs Decision Affects Training and Practice Location Preferences: Cross-Sectional Questionnaire Study.

By allowing for abortion bans and restrictions to take effect in the majority of US states, the 2022 Dobbs v Jackson Women's Health Organization decision portends to have lasting impacts on patient care and the physician workforce. Notably, it is already beginning to impact practice location preferences of US health care workers, evidenced by declining application rates to residency programs in abortion-restrictive states since 2022. Yet, there remains a gap in the literature regarding why this trend exists. This study aims to describe what factors are driving the practice location preferences of medical students and physicians after the Dobbs decision. This study analyzes qualitative data from a web-based, cross-sectional study. In August 2022, a nonprobabilistic sample of physicians and medical students were surveyed on social media about the impact of overturning Roe v Wade on practice location preferences, which included the free-text question "Please share your thoughts about the overturning of Roe v Wade and how it will affect your decision about your (residency/job or fellowship) programs." A total of 3 independent team members completed an inductive thematic analysis of 524 free responses, resolving differences by discussion. Approximately 1 in 4 survey respondents also completed the free-response item (524/2063, 25.4%); a total of 219 were medical students, 129 were residents and fellows, and 176 were practicing physicians. Of them, approximately half (261/524, 50.5%) resided in states where abortion bans were in place or anticipated. Those who answered the free-response item were relatively more likely to hail from states with restrictive abortion bans (P<.001) compared to those who did not, with other demographic characteristics being largely similar between the groups. Inductive thematic analysis yielded 2 broad thematic categories: patient-related and workforce-related factors influencing practice decision preferences. The 3 most common themes overall were respondent concerns regarding their patient's access to care (249/524, 47.5%), their desire not to practice or train in a state with abortion restrictions regardless of current residence (249/524, 47.5%), and their personal belief that abortion bans are human rights and/or body autonomy violation (197/524, 37.6%). Some respondents stated that the Dobbs decision would not impact their choice of practice location (41/524, 7.8%), and some supported it (35/594, 6.7%). This study shows that abortion restrictions are having an impact on the practice location preferences of the physician workforce due to both patient care and personal factors. It is important that state policy makers and others who are considering abortion restrictions also consider how to address these concerns of physicians and medical students, to avoid worsening geographic maldistribution of physicians and worsening access to care from physicians for their citizens.

Artificial intelligence and its impact on corporate social responsibility

Artificial intelligence has been a technology that is constantly innovating interaction, consumption and expression in society itself. It is essential to examine the interaction and link between corporate social responsibility and artificial intelligence. To analyze the impact of artificial intelligence on corporate social responsibility commitments and evaluate how these impacts are perceived by organizations, identifying possible benefits and threats. An exhaustive literature review was conducted on artificial intelligence and its influence on corporate social responsibility. This review allowed identifying the possible positive and negative aspects that organizations present when adapting to different social changes. It is necessary to evaluate the link between corporate social responsibility and human capital, since both areas are crucial and complement each other in an organization. It highlights an innovative approach to strategies that identifies the contributions of CSR to different aspects of human talent, both internal and external, and analyzes its influence on personnel performance, a critical factor in organizational decision-making

Exploring Strategic Management Accounting Techniques (SMAT) as Innovative Approach: Literature Review

This literature review explores innovative strategies within Strategic Management Accounting Techniques (SMAT) designed to improve organizational performance and decision-making in the current dynamic business landscape. The study conducts a systematic analysis of articles published from 1991 to early 2024, leveraging databases like Scopus and Web of Science to identify 121 relevant journals, from which the top 10 were selected for detailed review. It outlines the evolution of SMAT, presenting 16 distinct techniques while highlighting inconsistencies in their application across different contexts. The key findings indicate notable gaps in the literature, especially concerning the integration of advanced technologies and the impact of corporate governance on the effectiveness of SMAT. The paper underscores the importance for organizations to embrace innovative management accounting practices that incorporate digitalization and contingency theory to maintain competitiveness. By synthesizing existing research, this review enhances the understanding of SMAT and offers valuable insights for future research directions, urging scholars and practitioners to investigate the convergence of technology and strategic management accounting for better organizational outcomes.

Integrating Information Governance as the Foundation for Information Dashboard Design Ontology

Aim/Purpose: This paper addresses the lack of a standardized approach to information dashboard design and the absence of integrated Information Governance (IG) principles in this context. Background: This study addresses the critical role of IG principles in ensuring dashboards are reliable, secure, and effective. By integrating IG principles into the work-in-progress Information Dashboard Design Ontology (IDDO), the study aims to enhance the systematic development of dashboards, addressing real-world issues such as data governance failures in Healthcare.gov, security breaches in CRM systems and risk reporting gaps in the JPMorgan Chase “London Whale” incident. Methodology: A narrative literature review (NLR) method was employed to synthesize insights from three established IG models and prior studies. NLR was chosen for its flexibility in exploring emerging topics, such as the integration of IG with dashboard design, where existing literature is scarce. The study acknowledges the limitations of NLR, including potential selection bias, while emphasizing its value in identifying foundational insights and aligning IG principles with dashboard design needs. Contribution: This study bridges the gap between IG and information dashboard design by proposing eight relevant IG principles for integration into the work-in-progress IDDO, providing a novel framework for governance-driven dashboard design. Findings: The study derived eight IG principles aligned with common design principles: Quality, Security, Compliance, Integrity, Availability, Transparency, Accountability, and Effectiveness. Recommendations for Practitioners: Practitioners should incorporate these IG principles into their dashboard design processes to enhance data quality, compliance, user trust, and decision-making support. Recommendation for Researchers: Researchers should explore the practical application of these IG principles across various organizational contexts and assess their impact on dashboard effectiveness and user experience. Impact on Society: This approach offers a potential solution to data quality, compliance, and user trust issues in enterprise information systems, which could lead to improved organizational decision-making and enhanced end-user experiences. Future Research: Future studies should focus on the practical integration of the identified IG principles into the IDDO framework, including empirical testing and validation in real-world scenarios.

A BIBLIOMETRIC ANALYSIS OF BOARD DIVERSITY: RESEARCH TRENDS, CHALLENGES, AND FUTURE DIRECTIONS

Board diversity has become a central issue in corporate governance, with growing recognition of its potential benefits for organizational performance, decision-making, and stakeholder engagement. This paper explores the concept of board diversity, examining various dimensions such as gender, ethnicity, age, and professional background. This study examines the evolution of board diversity, significant trends, and research gaps in current literature through bibliometric analysis. This study employs bibliometric analysis to identify the key areas of research, countries, languages, starting years, top journals, and prolific authors in board diversity. Using (Scopus.Com, n.d.) as the data source, 832 records published between 2016 and 2024 with the keyword "Board Diversity" were analyzed. This research utilized The VOS Viewer software for data analysis. This study implies that the bibliometric analysis highlights essential research gaps and trends, provides a thorough picture of the topic, and points out areas that need more investigation, especially the relationship between corporate success, sustainability, and board diversity. This can direct future studies and give academics and professionals a greater understanding of the strategic value of diverse boards. The results also highlight the regional distribution of research, identifying unexplored areas that can profit from targeted investigations. Ultimately, this study is a valuable tool for anyone wishing to learn more about the changing dynamics of board diversity and how it broadly affects corporate governance.

A Comparative Study of Abortion Laws in India and USA – With Special Reference to Women’s Rights and Reproductive Autonomy

The changes in the laws regarding abortion in India and the USA have a relation with societal attitudes toward women's rights and reproductive autonomy. India's Medical Termination of Pregnancy Act has evolved over time, allowing abortions under specific circumstances. However, the challenges persist due to centric and socio-economic factors. The USA established a constitutional right to abortion in the case of Roe-vWade decision in 1973 and Dobbs-vs-Jackson Women's Health Organization decision in 2022 which overturned federal protections leading to growing factors on rights over women's autonomy. Historical, cultural, and political factors determine the nature of the abortion laws in India and the USA. The Medical termination of Pregnancy Act empowers Indians-all women, irrespective of her being married or single-to undergo abortions before the completion of 24 weeks of gestation; however, this only recognises sovereignty as in all matters related to the female's reproductive health and life. The United States rolled back a century's worth of legal abortions in the decision case that led to the overturning of Dobbs -vs- Jackson Women's Health Organization after years of Roe -vs- Wade. It's going to increase the barriers coming under geographical location, socio-economic, and political consideration, which results in a problem in accessing the abortion service, which is provided both safely and legally, the amendment in India's Medical Termination of Pregnancy Act of giving importance to women autonomy related to abortion and US the Dobbs -vs- Jackson decision overturns the Roe -vs- Wade leading to restrictions for gaining access. Both countries in the present fight for reproductive justice and women's rights under the abortion laws have placed high emphasis on the aspect of fair access to reproductive health care.

Resolving the “three-fit” problems in enterprise information systems: a design science approach with ontological solutions

PurposeAddressing integrity, flexibility and interoperability challenges in enterprise information systems (EISs) is often hindered by the “three-fit” barrier, which encompasses vertical, horizontal and transversal fit problems. To overcome these obstacles, we propose solutions aimed at defining the business view of EIS. This study addresses these issues by proposing solutions tailored to the business view of EIS. Specifically, it introduces the core ontology of sensitive business processes (COSBP), a conceptual framework designed to formalize and define the multidimensional dimensions of sensitive business processes (SBPs). By providing a unified structure of central concepts and semantic relationships, COSBP enhances both knowledge management (KM) and business process management (BPM) in organizational contexts.Design/methodology/approachThis paper adopts the design science research methodology covering the phases of a design-oriented research project that develops new artifacts, such as the COSBP ontology, based on SBP modeling requirements. Following a formal multi-level, multi-component approach, COSBP is structured into sub-ontologies across different abstraction levels. Built upon the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) foundational ontology, COSBP integrates and extends core concepts from core domain ontologies in business processes. The framework specifies six key modeling dimensions of SBPs – functional, organizational, behavioral, informational, intentional and knowledge – each represented as a distinct class of ontological modules (OMs).FindingsCOSBP offers a semantically rich and precise framework for modeling SBPs, addressing complexity and ambiguity in conceptual modeling. It supports the creation of expressive and effective SBP models while enabling consensus-driven representation at a generic level. Additionally, COSBP serves as a foundation for extending modeling notations and developing tools that align with these notations. Its application in enterprise environments improves the integration, adaptability and interoperability of EISs, ultimately enhancing organizational processes and decision-making.Originality/valueThe development of the COSBP ontology holds considerable potential for application in various industries beyond its original focus on business process management and KM. The ontology’s capability to semantically model sensitive, knowledge-intensive and dynamic processes can be extended to other real-life scenarios in other complex domains and sectors – for example, finance and banking, government and public services, insurance, manufacturing and supply chain management, retail, E-commerce, logistics and transportation crisis management, government and public services, higher education and so on. By integrating artificial intelligence (AI) with the COSBP ontology, we aim to enable more intelligent decision-making, process monitoring and improved management of SBPs in knowledge-driven domains.

Temporal trends and predictive modeling of air pollutants in Delhi: a comparative study of artificial intelligence models

Air pollution monitoring and modeling are the most important focus of climate and environment decision-making organizations. The development of new methods for air quality prediction is one of the best strategies for understanding weather contamination. In this research, different air quality parameters were forecasted, including Carbon Monoxide (CO), Nitrogen Monoxide (NO), Nitrogen Dioxide (NO2), Ozone (O3), Sulphur Dioxide (SO2), Fine Particles Matter (PM2.5), Coarse Particles Matter (PM10), and Ammonia (NH3). Hourly datasets were collected for air quality monitoring stations near Delhi, India, from November 25, 2020 to January 24, 2023. In this context, five intelligent models were developed, including Long Short-Term Memory (LSTM), Bidirectional Long-Short Term Memory (Bi-LSTM), Gated Recurrent Unit (GRU), Multilayer Perceptron (MLP), and Extreme Gradient Boosting (XGBoost). The modelling results revealed that Bi-LSTM model had the best predictability performance for forecasting CO with (R2 = 0.979), NO with (R2 = 0.961), NO2 with (R2 = 0.956), SO2 with (R2 = 0.955), PM10 with (R2 = 0.9751) and NH3 with (R2 = 0.971). Meanwhile, GRU and LSTM models performed better in forecasting O3 and PM2.5 with (R2 = 0.9624) and (R2 = 0.973), respectively. The current research provides illuminating visuals highlighting the potential of deep learning to comprehend air quality modeling, enabling improved environmental decisions.

AI surveillance: Reclaiming privacy through informational control

With the rise of algorithmic management, the deployment of AI surveillance has proliferated in the modern workplace. AI surveillance relies on advanced computational methods to draw statistical inferences about workers from their data. These inferences are subsequently used by employers to inform various organisational and managerial decisions. This commodifies workers into statistical entities, which objectifies and instrumentalises the value of human work as a series of data points for algorithmic analysis. The article explores how this transformation impacts the precarious role of privacy in the employment context, which already navigates the inherent informational imbalances that arise from the structural subordination of workers to employers and are further exasperated by AI surveillance. It focuses on the remedies of EU law that instantiate specific notions of informational control as a core ingredient to privacy and data protection. This involves consideration of the General Data Protection Regulation, as well as the jurisprudence of Articles 7 and 8 of the European Charter of Fundamental Rights, and Article 8 of the European Convention of Human Rights. The article argues that a greater emphasis on workers’ informational control consolidates existing privacy protections and mitigates the systemic risks of data-driven commodification.

Investigating the Underpinning Criteria of Employees’ Social Sustainability and Their Impact on Job Satisfaction in the U.A.E. Construction Sector

The construction sector holds a paramount position in the economic landscape of any country, serving as its foundational pillar. This sector, characterized by its diverse and dynamic environment, is crucial in job creation across various domains, including transportation, real estate, manufacturing, trade, warehousing, wholesale, and leasing services. Employing about one quarter of the global workforce, its significance is undeniable. Despite its pivotal role, the construction sector grapples with significant mental health and social sustainability challenges. Reports in recent years indicate that approximately one in four individuals worldwide experiences various forms of mental disorders. A study by the Global Burden of Disease in 2010 revealed that around 400 million people globally suffer from depression with projections suggesting that depression could be the leading cause of employee mortality by 2030. This underscores the critical need to address mental health and well-being issues in this sector. While the existing literature has presented numerous studies and reliable scales linking employee mental health and well-being to factors such as job satisfaction, productivity, absenteeism, and low turnover rates, these studies often operate in isolation, concentrating on specific aspects of mental health. This study views mental health and well-being as essential parts of defining social sustainability as a comprehensive concept. Moreover, limited research has been conducted to assist organizations in decision making and facilitate efforts to enhance the social sustainability of employees in the construction sector, highlighting a noticeable research gap. To address this gap, our study adopted a comprehensive mixed-methods approach, incorporating semi-structured interviews, surveys, and structural equation modeling to identify the underpinning criteria that define the social sustainability of employees. This study accordingly incorporated the identified criteria to evaluate the relationship and impact of these factors on employees’ job satisfaction, ultimately contributing to the assurance of social sustainability for employees within the construction sector in the UAE. This holistic approach seeks to establish the intricate relationship between employees’ job satisfaction and their mental health, providing valuable insights for guiding organizational decisions and fostering improvements in employee social sustainability in the construction sector generally and the UAE construction sector in particular.

Sustainable Design Factors and Solutions Analysis and Assessment for the Graphic Design Industry: A Hybrid Fuzzy AHP–Fuzzy MARCOS Approach

Within the realm of graphic design sustainability, selecting appropriate solutions has become a crucial strategic decision for organizations aiming to optimize their operations. This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach, integrating a fuzzy analytical hierarchy process (FAHP) and fuzzy measurement alternatives and ranking according to compromise solution (FMARCOS). Evaluation criteria for graphic design sustainability are determined through consultation with experts, with their judgments expressed using linguistic terms based on fuzzy numbers. Criteria weights are calculated using FAHP, and the ranking and selection of the optimal potential solution are determined using FMARCOS. Subsequently, sensitivity analysis of the criteria weights is conducted to validate the results. Findings indicate that the integrated FAHP and FMARCOS model provides a robust and adaptable assessment framework for graphic design sustainability, enabling companies to navigate complexities strategically and effectively. The key contribution of this research is its emphasis on a systematic and objective model, offering practical insights relevant to the industry. It also serves as a valuable benchmark for future research in similar fields.

AI in Corporate Governance: Navigating Critical and Comfortable Aspects

Today Artificial Intelligence (AI) and related technologies have become a disruptive force in the market, impacting every aspect of a business. AI's roles in corporate governance (CG) practices are important; it, however, has to be seamlessly integrated for the desired outcomes. This research aims to assess the critical and comfortable aspects of AI for CG in organisations, specifically in the manufacturing sector. The research employed a qualitative strategy since the strategy aids in exploring a phenomenon comprehensively. In line with the qualitative strategy, semi-structured interviews with experts from the manufacturing industry were conducted as subject of this research. Thematic analysis was done on data using ten experts, ranging from China’s manufacturing industry. The findings reveal that AI is quite important for CG since it can improve all the parts of CG, focusing on risk management and decision-making. Interviews with experts emphasised that AI has facilitated rational decision-making and risk management in organisations. Yet the findings also showed that AI in CG was not quite without challenges, such as data quality, ethics and employee resistance. Nonetheless, appropriate mitigation strategies can be implemented, like robust data governance frameworks and training programs for employees that can make AI a critical aspect of CG and ensure that it is comfortably integrated into business operations. Overall, this research has significant managerial implications since it highlights the need for AI in CG by addressing the challenges faced with AI integration.

Typical mathematical models used in automated systems of organizational management

The article considers typical mathematical models used in automated control systems (ACS), a type of which are automated organizational control systems (ACOC), with the aim of making optimal management decisions. In our time, it is impossible to solve the problems of managing the economy by mechanically increasing the number of the governing apparatus, because the scale of the work requires such a number of people that cannot be directed to the sphere of management. An analysis of the most common types of tasks solved by managers at all levels of management is carried out: inventory management, distribution, mass service, ordering, replacement. An example of solving the problem of inventory management at a warehouse is given. A general description of mathematical models used in deterministic tasks of organizational and economic decision-making in organizational systems is given and the conditions for their application are given.