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This study aims to assess the alignment of South Korea’s government-certified social enterprises (GCSEs) with prevailing social enterprise (SE) models, notably the entrepreneurial nonprofit, social cooperative and social business models delineated in the “Emergence of Social Enterprises in Europe” (Defourny and Nyssens, 2012, 2017a, 2017b) and the “principle of interest” frameworks (Defourny et al., 2021). Thereby, it seeks to situate these enterprises within recognized frameworks and elucidate their hybrid identities.

Analyzing panel data from 2016 to 2020 for 259 GCSEs, this study uses tslearn for k-means clustering with dynamic time warping to assess their developmental trajectories and alignment with established SE models, which echoes the approach of Defourny et al. (2021). We probe the “fluid” identities of semi-public sector SEs, integrating Gordon’s (2013) notion that they tend to blend various SE traditions as opposed to existing in isolation.

Results indicate that GCSEs do align with prevalent SE frameworks. Furthermore, they represent a spectrum of SE models, suggesting the versatility of the public sector in fostering diverse types of SEs.

The concept of a semi-public sector SE model has been relatively uncharted, even though it holds significance for research on SE typologies and public sector entrepreneurship literature. This study bridges this gap by presenting empirical evidence of semi-public SEs and delineating the potential paths these enterprises might take as they amalgamate various SE traditions.

This study aims to determine the ink removal efficiency of papers with different recycling numbers and to examine some electrophotographic printing properties.

The base papers prepared according to the INGEDE 11p standard are subjected to six recycling stages (RS) under equal conditions. The physical-optical properties of the papers obtained at the end of each RS are measured and CMYK (cyan, magenta, yellow, key) color measurement scales are printed on each paper with electrophotographic printing. Color measurements of the printed papers are measured using the X-Rite eXact spectrophotometer, adhering to the ISO 13655:2017 standard. According to the measurement results of the optical properties, the ink removal efficiency of each recycling step is determined as a percentage (%) using some formulas.

As general, according to DEMLab and IERIC data, it is determined that the ink removal efficiency increased as the recycling repetition increased. In DEMf factor values, the highest deinking efficiency is obtained after the fourth RS. There is no significant difference between the printing properties of the samples.

It has been a matter of curiosity that papers lose their properties after how many RS. Many studies have been carried out on this subject and it has been presented by experimental methods that the printability properties of papers increase or decrease after which RS. This study can be a pioneer for future studies.

This paper aims to compare the surface roughness and hardness of three commercially available self-curing acrylic resins for dental use, under different polymerization conditions.

A comparative in vitro study was conducted using a convenience sample of 12 × 5 × 2 mm blocks with n = 40 for each material (Nic Tone, Arias Plus and Orthocryl®), with subgroups according to the polymerization method: conventional (C) and polymerization under ambient conditions (A). The surface roughness of the materials was measured using a profilometer; hardness was measured with a portable hardness tester. Additionally, surface morphology as well as particles size and morphology were evaluated with scanning electron microscopy.

There were significant differences in roughness and hardness values between the three self-curing acrylic resins (p < 0.05), as well as within each self-curing acrylic resin according to the polymerization method used (p < 0.05). The samples polymerized with the conventional method presented lower surface roughness and hardness values.

This study provides scientific evidence of values not provided by manufacturers in relation to the surface roughness and hardness of these materials, and all of them met the ideal minimum values of surface roughness, regardless of the polymerization technique used.

This chapter differentiates stress from generalized anxiety, discussing the nature and prevalence of each among college students. The chapter then delves into generalized anxiety in detail, covering instruments that measure generalized anxiety, cultural considerations associated with generalized anxiety and the causes, consequences, prevention and treatment of generalized anxiety among college students. The next section of the chapter focuses on social anxiety among college students, similarly addressing its defining characteristics, prevalence, cultural considerations, causes, consequences, prevention and treatment. The final section of the chapter follows a similar structure in discussing posttraumatic stress disorder (PTSD) among college students. Throughout the chapter, attention is devoted to neurotransmitters and brain structures that are involved in anxiety and its treatment through antianxiety medications. Case examples are used to help bring theoretical concepts and research findings to life.

This study aims to comprehensively investigate the electron beam powder bed fusion (EB-PBF) process for copper, offering validated estimations of melt pool temperature and morphology through numerical and analytical approaches. This work also assesses how process parameters influence the temperature fluctuations and the morphological changes of the melt pool.

Two distinct methods, an analytical model and a numerical simulation, were used to assess temperature profiles, melt pool morphology and associated heat transfer mechanisms, including conduction and keyhole mode. The analytical model considers conduction as the dominant heat transfer mechanism; the numerical model also includes convection and radiation, incorporating specific parameters such as beam power, scan speed, thermophysical material properties and powder interactions.

Both the analytical model and numerical simulations are highly correlated. Results indicated that the analytical model, emphasising material conduction, exhibited exceptional precision, although at substantially reduced cost. Statistical analysis of numerical outcomes underscored the substantial impact of beam power and scan speed on melt pool morphology and temperature in EB-PBF of copper.

This numerical simulation of copper in EB-PBF is the first high-fidelity model to consider the interaction between powder and substrate comprehensively. It accurately captures material properties, powder size distribution, thermal dynamics (including heat transfer between powder and substrate), phase changes and fluid dynamics. The model also integrates advanced computational methods such as computational fluid dynamics and discrete element method. The proposed model and simulation offer a valuable predictive tool for melt pool temperature, heat transfer processes and morphology. These insights are critical for ensuring the bonding quality of subsequent layers and, consequently, influencing the overall quality of the printed parts.

This study aims to develop a modelling framework of housing supply dynamics within the context of urban microsimulation systems. Housing markets have witnessed substantial investigation over recent decades, predominantly concerning residential demand. However, comparatively limited attention has been directed towards comprehending the housing supply dynamics. Housing policy disconnects with the developers’ market behaviours, which leads to significant mismatch between the housing construction and affordable housing needs of the population. Research attention should be made in comprehending the residential construction market activities. To address this gap, this study developed an autoregressive distributed lag (ARDL) model and analyzed the temporal evolution of housing construction.

An ARDL model was developed to address the issue of temporal modelling of the housing supply. An empirical study was conducted in the Greater Toronto and Hamilton Area (GTHA) based on a longitudinal housing starts data set from 1998 to 2020. The model integrates diverse variables, including macroeconomic conditions, property development costs, dwelling prices and opportunity costs. Notably, the model captures both the path-dependent effects stemming from supply market fluctuations and the temporal lag effect of influential factors.

The findings reveal that the supply-side’s responsiveness to market condition alterations may span up to 18 months. The model has reasonable and satisfying performance in fitting the observed starts. The methodological foundations laid will facilitate future modelling of housing supply dynamics.

This study innovatively separated the modelling of housing supply within the context of urban microsimulation, into two parts, the modelling of housing starts and completion. The housing starts are determined in a complex and regressive process influenced by both the micro-economic environment and the construction cost and housing market trends. Through the temporal modelling method, this study captures how long it would take for the housing supply to respond to multiple factors and provides insight for urban planners in regulating the housing market and leveraging various policies to influence the housing supply.

Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.

The objective of this study is to investigate the interaction effect between incentive type (financial and compassionate incentives) and the ethicality of merchant strategy on consumer willingness to post positive reviews, while also examining potential variations in consumer responses based on consumption experience, shopping frequency and social class.

Building upon construal level theory, we hypothesized the moderating influence of the ethicality of merchant strategy and examined the three-way interaction among consumers’ demographic characteristics (i.e. consumption experience, shopping frequency and social class), incentive type and the ethicality of merchant strategy. To empirically test our hypotheses, we conducted four experiments and employed ANOVA for data analysis.

The ethicality of merchant strategies moderates the association between incentive type and consumer willingness to post positive reviews, with compassionate incentives eliciting more pronounced moral judgments toward merchant strategies compared to financial incentives. The moderating effect of the ethicality of merchant strategy on the relationship between incentive type and consumer willingness to post positive reviews is particularly strong among consumers who have favorable consumption experiences, engage in frequent shopping and belong to lower social classes.

This study contributes to the existing literature on online reviews by examining the impact of compassionate incentives on consumer review behaviors, analyzing the ethicality of merchant strategies within the realm of online reviews and investigating variations in consumer responses to merchant strategies regarding consumption experience, shopping frequency and social class.

The purpose of this study is to determine what technological strategies were used within each of the phases of the ADDIE framework when developing content for professional training. The study also examined the affordances of those technologies in training.

A PRISMA systematic review methodology (Moher et al., 2015) was utilized to answer the four questions guiding this study. Specifically, the PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols (PRISMA-P, Moher et al., 2015) was used to direct each stage of the research, from the literature review to the conclusion. In addition, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA principles; Liberati et al., 2009) are used to guide the article selection process.

The findings reveal that the majority of the studies were in healthcare (36%) and education (24%) and used an online format (65%). There was a wide distribution of ADDIE used with technology across the globe. The coding for the benefits of technology use in the development of the training solution revealed four trends: 1) usability, 2) learning approaches, 3) learner experience and 4) financial.

This systematic review only examined articles published in English, which may bias the findings to a Western understanding of how technology is used within the ADDIE framework. Furthermore, the study examined only peer-review academic articles from scholarly journals and conferences. While this provided a high level of assurance about the quality of the studies, it does not include other reports directly from training providers and other organizations.

These findings can be used as a springboard for training providers, scholars, funders and practitioners, providing rigorous insight into how technology has been used within the ADDIE framework, the types of technology, and the benefits of using technology. This insight can be used when designing future training solutions with a better understanding of how technology can support learning.

This study provides insight into the uses of technology in training. Many of these findings and uses of technology within ADDIE can also transfer to other aspects of society.

This study is unique in that it provides the scholarly community with the first systematic review to examine what technological strategies were used within each of the phases of the ADDIE structure and how these technologies provided benefits to developing a training solution.

This study is based on the enforcement record from Canada’s natural mutual fund regulator. This record documented a small subset of mutual fund dealers who had been disciplined for their misconduct from 2007 to 2014. The purpose of this paper is to determine what factors contribute to mutual fund dealers’ time to first financial fraud offense. The longer the time to fraud, the healthier the mutual fund industry and the better a mutual fund dealer’s career.

Based on the belief that adversity reveals true character, the study approaches a mutual dealer’s career success from human capital, socio-demographic and organizational sponsorship points of view by measuring dealers’ success as their time from career beginning to first instance of financial fraud. Ordinary least square regression analysis was used to identify if those factors, including provision of supervisor reminders, gender, position and penalties, are related to career success within the Canadian mutual fund regulatory framework. The research is based on a small sample of mutual fund dealers who had been disciplined for their misconduct from 2007 to 2014.

The study finds that a supervisor’s reminders positively contribute to the career success of a mutual fund dealer in the form of extending their time to fraud. As well, being female is an adverse factor to career success even when both female and male dealers received about the same level of supervisor reminders. It also finds that being in a management position has no association with time to fraud.

The study establishes the statistically significant positive relationship between time to fraud and supervisor’s reminders for mutual fund dealers. At the same time, it shows that human capital and access to organizational resources, measured by being in a management position, have no significant relation to when fraud is committed. This result indicates the value of continuing education for all mutual fund dealers, both inexperienced and experienced.