Pavel Bachmann

Multinational corporations (MNCs) play a crucial role in shaping global business trends and driving innovation across industries. As artificial intelligence (AI) continues to transform the business landscape, its strategic and managerial applications within MNCs are becoming increasingly significant. AI enhances decision-making, optimizes processes, and fosters competitive advantage by automating complex tasks, enabling predictive analytics, and improving operational efficiency. This systematic review examines the integration of AI within MNCs from 2021 to 2024, employing the PRISMA methodology. The study synthesizes findings from peer-reviewed articles indexed in Web of Science, focusing on 27 distinct functional applications of AI. The primary objective is to identify strategic and managerial applications of AI in MNCs and analyze their impact on corporate operations. Through a combination of bibliometric analysis and qualitative synthesis, the review highlights key trends in AI adoption, strategic implications, and operational transformations. Key findings reveal diverse applications of AI across supply chain optimization, market intelligence, human resource management, and customer experience enhancement. The study underscores AI's evolving role in fostering strategic agility and sustaining competitive advantage in global markets, while also addressing ethical considerations and implementation challenges.

In context of the real estate market, the majority of transactions is mediated through intermediaries. Therefore, effective marketing services are essential for achieving optimal results in selling and renting of apartments. While some marketing principles are universal, the real estate sector has specific characteristics and needs an adaptation of strategies for effectively targeting audiences. This study aims to identify the nature of marketing communication within social networks in the real estate sector, including differences of the size of apartments and different regions. Even though each estate is unique, approaches to marketing communication can be heuristically diversified. The study uses content analysis of advertisements for the sale of small and large apartments in premium locations in Prague and in other commonly sought-after locations in the Czech Republic. This involved selected advertised apartments in the period of 2023 to 2024. Individual advertisements were divided into the 4 aforementioned groups and significant factors were descriptively analyzed. It was found that the groups exhibit certain common traits within marketing communication.

Background and study goal: Social media are a societal phenomenon today, including the oldest generation, yet they are seldom used in current health research to identify the needs of persons with Alzheimer’s disease (PADs) and their carers. There is an even bigger research gap in the analysis of caregivers’ communication in online support groups and its classification according to activities of daily living (ADLs). For this, the goal of this study is to identify real-life practices of informal caregivers who care for PADs based on the analysis of their communication in Facebook groups. Methods: A sample of 1603 contributions was obtained from support groups by keyword search, manual coding, and verification; thus, the contributions in the sample are relevant for the individual basic ADLs of PADs. Next, five main conversation topics were identified for each ADL. This was done using the topic extractor based on simple parallel threaded implementation of LDA with a sparse sampling scheme and data structure. Results: The qualitative dimension of research identified discussion topics as well as specific caregiver behavior patterns for each ADL. The quantitative dimension determining the level of engagement of group members in individual ADLs was also measured. The highest engagement was found in activities of feeding and drinking, followed by bathing. In contrast, the activities of dressing, continence, and toileting attract the lowest interest. Moreover, the causal links between the topics discussed within the areas of ADLs were identified. Conclusions: The acquired knowledge can help further research focus on the most problematic areas relevant for people with AD in order to increase their quality of life and at the same time reduce the caregiver burden. The study expands the information of the demands posed by the individual caregiver activities, specifically in the context of activity-based costing or time-based activity costing.

BACKGROUND As the social media (SM) support groups provide a communication platform for caregivers to share experiences, examples of effective and ineffective care, asking questions, recommending new approaches, or venting their needs, there is still little documented on how SM can help to obtain a true picture of the caregiver burden according to activities of daily living (ADLs). OBJECTIVE The study aims to identify the real-life practice of family caregivers looking after people with Alzheimer’s disease (AD). The image of caregivers’ actual practice is determined on the basis of their experience, needs, emotions, or examples of the behavior of people with AD found on social networks. METHODS We collected a sample of 1603 posts relevant to basic activities of daily living (ADLs) which were published in two Facebook support groups related to AD. In the next step, conversation topics were identified separately for each of the six basic categories of ADLs. This was done using the topic extractor based on the simple parallel threaded implementation of Latent Dirichlet allocation with sparse LDA sampling scheme and data structure. RESULTS From the quantitative point, the study provides knowledge about the proportions of members’ interest in the individual areas of ADLs. From the qualitative point, machine learning automatically detected five discussion topics for each activity. At the same time, for each of the topics, real-life examples from the day-to-day experience of family caregivers are given. In terms of the members’ interests, statistically significant differences were found between the drinking and feeding activity and three other daily activities. Moreover, a qualitative analysis showed several causal links between the individual topics discussed within the areas of ADLs. CONCLUSIONS The acquired knowledge can help further research focus on the most problematic areas relevant for people with AD in order to increase their quality of life and at the same time reduce the caregiver burden. The study expands the knowledge of the demands posed by the individual caregiver activities, specifically in the context of activity-based costing or time-based activity costing. At the same time, it can serve as a basis for identifying the needs of caregivers in the field of innovative development or the implementation of online counseling on social networks. CLINICALTRIAL Not applicable.