arXiv subjects

Dariusz Reśko

Publications and source records attributed to Dariusz Reśko.

2 recordsLinked to original sources

arXiv2025

Data Protection and Corporate Reputation Management in the Digital Era

This paper analyzes the relationship between cybersecurity management, data protection, and corporate reputation in the context of digital transformation. The study examines how organizations implement strategies and tools to mitigate cyber risks, comply with regulatory requirements, and maintain stakeholder trust. A quantitative research design was applied using an online diagnostic survey conducted among enterprises from various industries operating in Poland. The analysis covered formal cybersecurity strategies, technical and procedural safeguards, employee awareness, incident response practices, and the adoption of international standards such as ISO/IEC 27001 and ISO/IEC 27032. The findings indicate that most organizations have formalized cybersecurity frameworks, conduct regular audits, and invest in employee awareness programs. Despite this high level of preparedness, 75 percent of surveyed firms experienced cybersecurity incidents within the previous twelve months. The most frequently reported consequences were reputational damage and loss of customer trust, followed by operational disruptions and financial or regulatory impacts. The results show that cybersecurity is increasingly perceived as a strategic investment supporting long-term organizational stability rather than merely a compliance cost. The study highlights the importance of integrating cybersecurity governance with corporate communication and reputation management, emphasizing data protection as a key determinant of digital trust and organizational resilience.

cs.CR↗

arXiv2025

The Impact of Artificial Intelligence on Enterprise Decision-Making Process

Artificial intelligence improves enterprise decision-making by accelerating data analysis, reducing human error, and supporting evidence-based choices. A quantitative survey of 92 companies across multiple industries examines how AI adoption influences managerial performance, decision efficiency, and organizational barriers. Results show that 93 percent of firms use AI, primarily in customer service, data forecasting, and decision support. AI systems increase the speed and clarity of managerial decisions, yet implementation faces challenges. The most frequent barriers include employee resistance, high costs, and regulatory ambiguity. Respondents indicate that organizational factors are more significant than technological limitations. Critical competencies for successful AI use include understanding algorithmic mechanisms and change management. Technical skills such as programming play a smaller role. Employees report difficulties in adapting to AI tools, especially when formulating prompts or accepting system outputs. The study highlights the importance of integrating AI with human judgment and communication practices. When supported by adaptive leadership and transparent processes, AI adoption enhances organizational agility and strengthens decision-making performance. These findings contribute to ongoing research on how digital technologies reshape management and the evolution of hybrid human-machine decision environments.

cs.CY↗