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This chapter intends to make an extended periodization of economic discussions that have taken place in Latin America throughout its history. The task is ambitious; we begin, however, with the periodization elaborated by Oreste Popescu, which we then expand and modify. As educators, we still have to work on the training of Latin American economists, due to the lack of knowledge they have not only about the region as a whole, but also of the economic debates that took place within it. This work is a first approximation and provocation aimed to jumpstart a discussion on these issues.

This study systematically explores the literature on global niche market strategies within the fashion industry to allow the mapping of niche practices and examine the benefits, success factors and characteristics of a niche strategy. Additionally, it identifies data gaps and necessitates a detailed examination to uncover areas with inadequate information.

This study utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) method for systematic review and included 70 studies to analyze their findings.

This systematic literature review pinpoints niche strategies shaping the future of the fashion industry while developing sectors of the textile and apparel industry, fashion technology, fashion retail business, fashion media and communication, luxury fashion, sustainable fashion, adaptive clothing and transgender fashion within the fashion supply chain. A niche market strategy utilizes both pull and push marketing in the fashion industry. Scholarly literature commonly underscores the understanding of the consumer as a pivotal factor in the success of fashion niche market strategy.

This review offers a comprehensive overview of fashion niche strategy practices, aiming to inspire fashion industry professionals. It also serves as a guide for fashion industry professionals, summarizing best practices across various fashion industry sectors to help develop effective niche strategy competencies for firms.

This review thoroughly analyzes niche strategy implementation in the fashion industry, presenting an important resource for individuals new to this sector. It highlights the significance of niche strategies in improving the comprehension of emerging participants in the fashion business.

Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.

In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.

The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.

This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.

This paper aims to develop efficient and simple models for thermal distribution, melt pool dimensions and controlled phase change in the laser additive manufacturing (AM) of bulk and powder particles ceramic materials.

This paper proposes new analytical models for the AM of bulk and powder bed ceramic materials. A volumetric moving heat source, along with the complete melting of bulk and powder particle materials, is taken into account. Different values of laser absorption coefficient in solid and liquid states have been used to investigate the phase transformation. Furthermore, the pores and voids dimensions are also included in the modeling. Theoretical predictions have been compared with the experimental analyses and finite element simulations in laser to silicon nitride and laser to alumina interaction. The analysis focuses on the impact of laser power and scanning speed on the melt pool width and depth evolution into the bulk substrate and powder bed.

This study shows that the powder particles exhibit a higher thermal distribution value than the bulk substrate because of voids in the powder layer. The laser beam experiences multiple reflections in the presence of porosity/voids, thus increasing the surface absorption coefficient, which becomes relevant with the increment in the pore/void dimension. A direct relationship has been found between the laser power and melt pool dimensions, while the scanning speed displayed an inverse relationship for the melt pool width and length. Larger melt dimensions were inferred in the case of laser–powder particle interaction compared with laser–bulk substrate interaction. A close correlation was found between the analytical simulations, experimental investigations and numerical simulation results within the range of 4%–8%.

This paper fulfills an identified need to develop efficient and simplified models for ceramics laser AM by taking into account different laser absorption coefficients in solid and liquid form, voids and pores dimensions and controlled phase transformation to avoid vapors and plasma formation. The limitation of the finite element simulation model is that the solution is strongly dependent on the mesh quality and accuracy directly linked to the computation efficiency and time. A finer mesh requires a longer computing time than a coarse mesh. Finite element simulations require, however, specialized skills.

This study aims to discover and carefully review the academic works pertinent to the concepts and elements of how human resources (HRs) can be managed through digital marketing and its benefits and model of implementation.

The HR industry has seen digital transition businesses align their HR practices with cutting-edge technologies. Despite this, there are still numerous areas where conventional HR assessments must be improved. Therefore, it is important to discover why digital marketing is necessary for conducting HR practices.

The literature search found numerous published papers demonstrating the applicability of managing HRs through digital marketing. The review provided a comprehensive yet condensed overview of the philosophy behind adopting online platforms for HRs operations. The terms ‘Human Resources in Digital Marketing’ and ‘Recruiting using Digital Marketing’ were used to locate many original, peer-reviewed papers. The evidence suggests that the research was sufficiently reliable and valid.

It is recommended to use digital marketing tools and techniques to facilitate the hiring process and improve the management of HR professionals.

This conceptual paper aims to develop the vision of a novel policy tool called the digital industrial cluster (DIC) thought for a future context shaped by digital economies and Industry 4.0. The DIC departs from the industrial cluster’s precepts and take them into the digital agglomeration phenomenon.

This research uses a discursive and theoretical approach. To create a clear picture related to the research topic, this paper reviews the literature on how industrial clusters deal with digital transformation. The review takes a particular interest in industrial clusters, information and communication technologies, Industry 4.0 and policy tools for digital agglomeration.

The research develops the vision of the DIC as a new policy tool, building its foundations on both industrial clusters and digital economies; furthermore, the DIC was compared with other policy tools based on digital agglomeration to understand the similarities, differences and advantages of the former. Finally, this paper discussed where the DIC could find its way toward implementation and what externalities could be expected from doing so.

This research could be useful for policymakers and cluster organizations looking to deploy policy tools that take advantage of industrial clusters and digital transformation. Besides, the theoretical foundations presented could lead researchers to empirical identification of early incarnations of the DIC.

This paper develops theoretical principles for a new policy tool that connects industrial clusters, digital agglomeration and Industry 4.0 for the first time.

TiO₂ thin films were deposited by Pulsed Laser Deposition (PLD) on glass substrates at 27°C and 100°C. The extraction efficiency of evanescent light from the deposited nanolayers and their thickness profiles in the range of (1-100) nm was evaluated using the Differential Evanescent Light Intensity (DELI) imaging method. This optical microscopy technique is based on capturing the evanescent light emitted by the material layer deposited on the substrate. The results were analyzed and discussed in terms of the effective penetration depth parameter. The effective scattering cross-section of the TiO₂ nanometer particles was estimated.

Sustainable development goals and the climate change agenda are becoming widely promoted topics of research for the 21st century. The role of cities is increasingly recognised as central to investigating these topics. Yet, the field of informal sector entrepreneurship which so many urban entrepreneurs in developing countries depend upon is seldom considered. To redress this imbalance, this study aims to develop a decision model in accordance with institutional theory (IT) and resource dependency theory (RDT) for city managers to deploy. The model identifies and prioritises optimal strategies to address the three areas of sustainability requirements environment society and economy within the study context of Bangladesh.

This study used a mixed methods research design. In the qualitative part, the authors identified the three areas of sustainability requirements (i.e. environment, society and economy) and their corresponding strategies involving the informal sector that operates within the urban environment. In the quantitative part, the authors applied fuzzy quality function deployment (QFD) integrated with the 0-1 non-linear optimisation technique to identify optimal strategies.

The findings show that strategies such as legitimate frameworks, waste management, allocation of urban public space and training programs contribute in important ways to the three areas of sustainability requirements.

The proposed decision model will assist policy-makers and city managers to prioritise sustainability requirements and implement optimal strategies to address those requirements.

Through the integration of IT and RDT, the decision model developed in this study is unique in its application to urban-based informal entrepreneurship in the context of developing countries. The effective application of the fuzzy QFD approach and the optimisation model in the context of urban-based informal entrepreneurship also offers unique contributions to the field of study.

Cities are becoming smarter and more optimized because of digital transformation, reducing costs, increasing safety, attracting investment, ensuring sustainability, and increasing viability. As a result of this optimization, they are becoming smart cities. Smart cities use the Internet of Things’ devices, such as connected sensors, lights, and smart meters, to improve infrastructure and design by gathering and analyzing real-time citizen data. In this research, different conceptions of smart cities and their interconnections with digital transformation are presented. Therefore, the purpose of this chapter is to analyze how digital transformation may help manage smart cities. As a result, a thorough and integrated evaluation of the SCOPUS database will be conducted in order to address the following questions: (1) What are smart cities? (2) What is digital transformation? (3) How does digital transformation help to manage smart cities? The results point out that technologies and digital abundance, which include artificial intelligence, blockchain, and Internet of Things, play a crucial role in managing a controlled and automated infrastructure in smart cities. These favor the development of suitable places to live, work, and have fun, with a better quality of life for everyone.

This study empirically examined consumer adoption attitudes and behaviors toward nonfungible tokens (NFTs). Findings indicate that consumer attitudes toward NFTs are influenced by perceived usefulness, reliability and profit expectancy and that strong attitudes are associated with purchase intentions. Additionally, the relationship between attitudes and purchase intentions was moderated by technology optimism.

The authors utilized a partial least squares (PLS) model to examine the hypotheses in this empirical analysis. Obtaining a sample of actual NFT holders or experienced users is challenging. A total of 105 individuals participated in the study as valid responders by answering the screening question in the questionnaire. The authors opted for the PLS model as a research approach due to the limited size of the consumer population in the NFT market.

This study discovered that the adoption of NFTs was affected by technical aspects such as usefulness and reliability and the potential for future asset growth. Furthermore, the degree of attitude-to-intention conversion varied based on optimism, an inherent characteristic.

This study offers valuable insights for NFT owners, content providers and trading firms. For the NFT market to expand, it must meet consumers' expectations for the desired content features and asset investment attributes. Additionally, customer targeting strategies should attract and appeal to technology enthusiasts with an optimistic outlook on technology.

The authors conducted an initial empirical analysis of actual NFT consumers, an area of research studied sparingly despite its significance.