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This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

Employees facing challenges in their careers – i.e. female, migrant, elderly and lower-educated employees – might expect job searches to have a low likelihood of success and might therefore more often stay in unsatisfactory positions. The goal of this study is to discover inequalities in job mobility for these employees.

We rely on a large sample of Dutch public sector employees (N = 30,709) and study whether employees with challenges in their careers are hampered in translating job dissatisfaction into job searches. Additionally, we assess whether this is due to their perceptions of labor market alternatives.

Findings show that non-Western migrant, elderly and lower-educated employees are less likely to act on job dissatisfaction than their advantaged counterparts, whereas women are more likely than men to do so. Additionally, we find that although they perceive labor market opportunities as limited, this does not affect their propensity to search for different jobs.

This paper is novel in discovering inequalities in job mobility by analyzing whether employees facing challenges in their careers are less likely to act on job dissatisfaction and therefore more likely to remain in unsatisfactory positions.

The purpose of this paper is to identify and discuss impediments in the compilation of an application for a search and seizure warrant for digital evidence and the structure of such a warrant in South African criminal cases.

This paper provides a brief overview of international and local impediments, followed by a detailed discussion of the implications of these impediments and how it is approached in various jurisdictions. The methodology of this paper consists of a literature review.

Addressing the impediments in the compilation of the application and the warrant will be beneficial for forensic investigators, the South African Police Service (SAPS) and the administration of justice in South Africa.

Search and seizures for digital evidence form part of civil, regulatory and criminal search and seizures. This study focuses on the search and seizure of digital evidence in criminal matters pursuant to mainly the provisions of the Criminal Procedure Act 51 of 1977 and the Cybercrimes Act 19 of 2020.

The originality of this paper lies in the approach to the drafting of applications for search and seizure warrants for digital information in South Africa. The contribution of the study is that, by using this approach, the SAPS can address the impediments during the application and compilation of the warrants, which would enhance the quality of investigations and contribute to the successful investigation and prosecution of crime in South Africa.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

The substantial expansion of technology and the efficacy of digital platforms in reaching young audiences have led to enhanced targeting and customization of promotional communications. Notwithstanding the expansion and efficacy of contemporary advertising platforms, scholarly attention has not kept pace with this domain of inquiry. This study aims to assess the antecedents of Google Shopping Ads (GSA) on intention to purchase behavior among the Generation Y and Z cohorts.

The current study used a quantitative approach and snowball sampling technique to gather primary data via a questionnaire and Google Forms, which resulted in the collection of 5,808 questionnaires among the cohort members. A principal component analysis and multigroup confirmatory multigroup structural equation modeling (between Generation Y and Z) were used to assess the research data and model.

The results show positive trust and perceived value associations with intention to purchase, particularly among Generation Y and Z consumers. The findings also show negative irritation, product risk and time risk associations with intention to purchase, especially among the Generation Y cohort, which indicates that young consumers generally do not observe perceived risk due to the usage of GSA.

GSA will continue to grow and become an increasingly important integrated marketing communications tool as the digital landscape develops. It can be concluded that young consumers show a high degree of perceived value and low levels of perceived risk due to the use of GSA. This study, therefore, promotes improved understanding among academics, marketers and businesses of search engine advertising among young cohorts of consumers (Generation Y and Z) in a developing country context.

Evidence-based practice is a professional standard for occupational therapists, but limited time, resources and knowledge challenge its implementation. This study aims to identify what free evidence summary sources (FESS) can be found through a simple online search, related to child/youth interventions surrounding cerebral palsy (CP), autism spectrum disorder (ASD), developmental coordination disorder (DCD), mental health or attention-deficit/hyperactivity disorder (MH/ADHD). Evidence summaries share research in concise, time-efficient manners.

An internet-based scoping review was conducted between February 2022 and July 2022, using Google, and known evidence summary producers. Evidence summaries meeting the inclusion criteria were located and catalogued. Type of agency, target audiences, purpose and distribution of evidence summaries related to diagnosis were identified for each FESS.

Ten FESS were found, which produced 113 intervention-focused evidence summaries within the past 10 years. These FESS were aimed at a variety of target audiences: service providers, service users, parents/families, researchers and commissioners, and were produced primarily by non-profit/charity organisations (6 of 10) who were trying to fill a gap in evidence. Forty-eight evidence summaries were related to ASD, 34 to CP, 29 to MH/ADHD and two to DCD.

A catalogue of FESS that exist online was produced, to support evidence-based practice for paediatric occupational therapists with limited resources, and may support improved health promotion and informed decision-making for service users. No consistent framework for FESS evidence summaries exists at this time.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.

A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.

The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.

The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

The objective of this research is to analyze how omnichannel consumer journey design (OCJD) influences the online customer experience (OCE) and e-satisfaction in consumers' multirooming behavior (searching for information in online and offline channels and purchasing the product online).

The problem-solving theory and experiential marketing perspective are the theoretical background that enables the establishment of five hypotheses. A survey is conducted on multiroomers who had purchased a product online, following an online and offline research journey.

The results showed that OCJD directly and indirectly (through online consumer experience) influences e-satisfaction. Females and younger individuals exhibited higher levels of e-satisfaction.

First, this research analyzes consumers' multichannel search strategies. Second, the consumer journey is incorporated into the study of multichannel retailing. Third, an emergent typology of cross-channel free-riding behavior is analyzed: multirooming.

Healthcare providers are under pressure due to increasing and more complex demands for services. Increased pressure on budgets and human resources adds to an ever-growing problem set. Competent leaders are in demand to ensure effective and well-performing healthcare organisations that deliver balanced results and high-quality services. Researchers have made significant efforts to identify and define determining competencies for healthcare leadership. Broad terms such as competence are, however, inherently at risk of becoming too generic to add analytical value. The purpose of this study is to suggest a holistic framework for understanding healthcare leadership competence, that can be crucial for operationalising important healthcare leadership competencies for researchers, decision-makers as well as practitioners.

In the present study, a critical interpretive synthesis (CIS) was conducted to analyse competency descriptions for healthcare leaders. The descriptions were retrieved from peer reviewed empirical studies published between 2010 and 2022 that aimed to identify healthcare services leadership competencies. Grounded theory was utilised to code the data and inductively develop new categories of healthcare leadership competencies. The categorisation was then analysed to suggest a holistic framework for healthcare leadership competence.

Forty-one papers were included in the review. Coding and analysing the competence descriptions resulted in 12 healthcare leadership competence categories: (1) character, (2) interpersonal relations, (3) leadership, (4) professionalism, (5) soft HRM, (6) management, (7) organisational knowledge, (8) technology, (9) knowledge of the healthcare environment, (10) change and innovation, (11) knowledge transformation and (12) boundary spanning. Based on this result, a holistic framework for understanding and analysing healthcare services leadership competencies was suggested. This framework suggests that the 12 categories of healthcare leadership competencies include a range of knowledge, skills and abilities that can be understood across the dimension personal – and technical, and organisational internal and – external competencies.

This literature review was conducted with the results of searching only two electronic databases. Because of this, there is a chance that there exist empirical studies that could have added to the development of the competence categories or could have contradicted some of the descriptions used in this analysis that were assessed as quite harmonised. A CIS also opens for a broader search, including the grey literature, books, policy documents and so on, but this study was limited to peer-reviewed empirical studies. This limitation could also have affected the result, as complex phenomenon such as competence might have been disclosed in greater details in, for example, books.

The holistic framework for healthcare leadership competences offers a common understanding of a “fuzzy” concept such as competence and can be used to identify specific competency needs in healthcare organisations, to develop strategic competency plans and educational programmes for healthcare leaders.

This study reveals a lack of consensus regarding the use and understanding of the concept of competence, and that key competencies addressed in the included papers are described vastly different in terms of what knowledge, skills and abilities they entail. This challenges the operationalisation of healthcare services leadership competencies. The proposed framework for healthcare services leadership competencies offers a common understanding of work-related competencies and a possibility to analyse key leadership competencies based on a holistic framework.