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This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This chapter is born out of concern about the perception of the physical and symbolic place of the live-in housekeeper, both in socioeconomic, and historical terms, as well as the architectural and social dynamics of the home. An intersectional and teleological analysis of the intrinsic devaluation of paid social reproduction work is carried out, based mainly on gender, race, and class inequalities. Ultimately, the chapter tries to locate the position in which the maid finds herself in the domestic environment, both in family relationships and in the symbolism inherent to the concept of the maid’s room. Based on sociological, philosophical, and anthropological analysis, the ambiguous place of domestic workers becomes clearer, promoting a reflection on the very concept of family and household. Thus, the chapter proposes to achieve a hermeneutic dive into the experience of this working class, revealing a hierarchical system beyond the socioeconomic, but above all, of their subjectivities.

This study aims to examine how young consumers perceive the advertising effectiveness of endorsements by virtual idols and how endorsements by virtual idols differ from endorsements by real human celebrities such as traditional celebrities and online influencers.

An experimental study was conducted with 400 randomly selected young respondents in China in December 2022. A 3 × 2 factorial design was used to test how the type of celebrity endorser and level of product involvement influence the persuasiveness of advertising aimed at young adults. Among 400 respondents, the average age was 21.5 years. A total of 193 male and 207 female respondents participated in the experiment.

Young consumers find virtual idols, online influencers and traditional celebrities attractive. Although virtual idols are the least credible among the three types of celebrity endorsers, young consumers tend to be more convinced by their endorsements of products with low levels of consumer involvement than those with high levels of involvement. Among the three types of celebrity endorsements, young consumers find traditional celebrities the most effective. In addition, young consumers’ attitudes toward celebrity endorsers mediate the impact of celebrity endorsers’ attractiveness and credibility on their attitudes toward the advertisements. The perceived level of product involvement moderates the transfer of meaning from the attitude toward the celebrity endorsers to the attitude toward the advertisement.

First, when choosing celebrity endorsers to advertise products targeting young consumers, marketing communication practitioners should give priority to the endorsers’ perceived credibility, as young consumers have a variety of views about them that can significantly affect their attitudes toward the advertisement. Second, real human celebrity endorsers are more effective than virtual idols in celebrity endorsements. However, virtual idols may be suited for use in advertisements to promote products with low involvement levels, such as soft drinks.

To the best of the authors’ knowledge, this is the first experimental study to attempt to analyze the effectiveness of virtual idols in advertising aimed at young consumers. This is also the first comparative study to introduce virtual idols as celebrity endorsers in product advertising and to compare their effectiveness with that of the two other types of commonly discussed celebrity endorsers, traditional celebrities and online influencers.

The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

This study aims to determine and evaluate the artificial intelligence (AI) development and competitiveness of the top 20 countries that receive the highest number of tourists with the entropy technique for order of preference by similarity to the ideal solution (TOPSIS)-integrated method.

This study is based on Global AI Index data published by Tortoise Media. Based on this index, according to the World Tourism Organization (UNWTO) report, the top 20 destinations that will host the highest number of tourists in 2022 were evaluated in seven different subpillars, which are talent, infrastructure, operating environment, research, development, government strategy and commercial. These seven subpillars of the index were considered as criteria, and the top 20 tourist destinations were included in the research as decision alternatives.

The analysis results show that the three most important AI criteria are operating environment, infrastructure and government strategy. Furthermore, the first three countries with the best AI performance according to the weighted criteria were the USA, China and the UK, respectively.

Considering that AI technologies will direct tourist behavior in a world where technology is rapidly developing, it is recommended that the countries that receive the highest number of tourists improve their AI performance.

When the relevant literature is examined, there is a limited number of studies examining the AI development and competitiveness of the top tourist destinations and weighting the Global AI Index values. Therefore, this study contributes to the gap in the relevant literature.

COVID-19 has rendered many firms' business models, strategies and performance vulnerable, including entrepreneurial financials. Some managed to survive, while others drowned in the epidemic swamp. This study offers an exceptional model to fill the gap.

Employing a rigorous qualitative design, the study utilizes a novel framework that integrates institutional theory (IT) and corporate entrepreneurial strategy (CES). Semi-structured interviews were conducted, and thematic analysis identified key themes: external environment, institutional environment and organizational response, CES and performance and survival.

The study reveals the dual nature of the external and institutional environment, acting as both facilitators and barriers for entrepreneurial financial firms (EFFs). It highlights the robust CES exhibited by these firms during the pandemic, demonstrating their adept balancing and integration of different CES components in their organizational response. The EFFs employ a mix of financial and nonfinancial indicators for performance assessment, yielding varied outcomes based on contextual factors.

EFFs and stakeholders are guided to adapt their business models, balance institutional pressures, implement CES and evaluate performance. It advocates collaboration within the entrepreneurial finance ecosystem and leveraging opportunities emerging from the pandemic, including new market segments, technologies, innovations and regulatory changes.

This topic is underexplored in many emerging economies. Fresh perspectives and rigor frameworks are developed on how EFFs navigate and capitalize on the pandemic under uncertainties.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

The purpose of this paper is to validate the theoretical finding that digital MNEs avoid physical presence norms of permanent establishment and royalty characterization rules for business and royalty taxation, respectively, to escape tax incidence in the market economy, using information, communication and technology features and transfer pricing (TP) manipulations.

Multiple case studies of MNEs from technology sector, based on judicial decisions in 141 cases, over taxability of profits earned from Indian economic activities. Additional in-depth case study of the Uber Group to study the tax avoidance structures under platform economy, by routing of Indian profits through The Netherlands, a tax haven.

The study finds a significant number of digital MNEs earning profits from India and avoiding tax by defying physical presence and royalty characterization. In majority of the cases, demand-side business activities are discharged through incorporating and remunerating affiliates at cost plus low markup, thus avoiding tax incidence, using TP manipulations under the arm’s length principle applied by governments for benchmarking the intragroup transactions of the MNEs.

The research findings validate the view that digital features promote tax avoidance in the market economy.

The originality of the study lies in the validation of profit shifting through digital features from the developing market economy and portending that digital MNEs defy physical presence to avoid business taxation through TP manipulations.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.