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The purpose of this paper is to characterise the position of highly educated African migrants in the Finnish labour market and to examine the impact of the COVID-19 pandemic on that position.

The paper is based on the biographical work stories of 17 highly educated African migrant workers in four occupation areas in Finland: healthcare, cleaning, restaurant and transport. The sample was partly purposively and partly theoretically determined. The authors used content driven thematic analysis technique, combined with by the biographical narrative concept of turning points.

Using the case of highly educated African migrants in the Finnish labour market, the authors show how student migration policies reinforce a pattern of division of labour and occupations that allocate migrant workers to typical low skilled low status occupations in the secondary sector regardless of level of education, qualification and work experience. They also show how the unique labour and skill demands of the COVID-19 pandemic incidentally made these typical migrant occupations essential, resulting in increased employment and work security for this group of migrant workers.

This research and the authors’ findings are limited in scope owing to sample size and methodology. To improve applicability of findings, future studies could expand the scope of enquiry using e.g. quantitative surveys and include other stakeholders in the study group.

The paper adds to the knowledge on how migration policies contribute to labour market dualisation and occupational segmentation in Finland, illustrated by the case of highly educated African migrant workers.

This paper analyzes the issue of wage differentials and gender discrimination in the Brazilian labor market.

The methodology is based on the log-linear equation model by Mincer (1974) and the decomposition method by Oaxaca (1973) and Blinder (1973) and was estimated using data from the National Household Sample Survey (PNAD).

The main results indicate that there was a reduction in wage differentials and gender discrimination in the majority of regions in Brazil for white workers when comparing the available years. However, for non-white workers, the degree of discrimination increased in Brazil, especially in the central-west and southeast regions. Overall, wage decompositions have suggested that women suffer from wage discrimination.

This is the first paper detailing wage discrimination across the different Brazilian regions and also controlling for usual dimensions like gender and race.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2021-0569.

Although it is well established in the academic literature that entrepreneurs share common traits, there has been limited research dedicated to evaluating psychographic profiles of the self-employed. Using the Nominal Group Technique, the authors gleaned insight from a panel of experts in an effort to segment the self-employed based on personality traits and the benefits they receive from an entrepreneurial career. The findings show that self-employed individuals can be classified into four distinct segments: Exemplars, Generals, Moms and Dads, and Altruists. Each group derives different benefits from self-employment. Understanding these benefits can greatly assist entrepreneurship educators and marketers of small business oriented products and services.

Image segmentation is one of the most essential tasks in image processing applications. It is a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc. However, an accurate segmentation is a critical task since finding a correct model that fits a different type of image processing application is a persistent problem. This paper develops a novel segmentation model that aims to be a unified model using any kind of image processing application. The proposed precise and parallel segmentation model (PPSM) combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions. Moreover, a parallel boosting algorithm is proposed to improve the performance of the developed segmentation algorithm and minimize its computational cost. To evaluate the effectiveness of the proposed PPSM, different benchmark data sets for image segmentation are used such as Planet Hunters 2 (PH2), the International Skin Imaging Collaboration (ISIC), Microsoft Research in Cambridge (MSRC), the Berkley Segmentation Benchmark Data set (BSDS) and Common Objects in COntext (COCO). The obtained results indicate the efficacy of the proposed model in achieving high accuracy with significant processing time reduction compared to other segmentation models and using different types and fields of benchmarking data sets.

The proposed PPSM combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions.

On the basis of the achieved results, it can be observed that the proposed PPSM–minimum cross-entropy thresholding (PPSM–MCET)-based segmentation model is a robust, accurate and highly consistent method with high-performance ability.

A novel hybrid segmentation model is constructed exploiting a combination of Gaussian, gamma and lognormal distributions using MCET. Moreover, and to provide an accurate and high-performance thresholding with minimum computational cost, the proposed PPSM uses a parallel processing method to minimize the computational effort in MCET computing. The proposed model might be used as a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc.

Food delivery applications (FDAs) are becoming more and more well-liked across Generations X, Y and Z, with Asia experiencing the biggest growth. These three generations of consumers have distinct views toward using FDAs because they were influenced by various social environments, cultures and experiences. Therefore, marketers ought to present customers with various values. The purpose of this study is to investigate how the theory of consumption values (TCV) affects the intention of various generational cohorts to continued usage intentions.

Online surveys were distributed to 745 Thai customers who had previously ordered meals from FDAs to collect information. The data were analyzed using partial least squares structural equation modeling and multigroup analysis.

Results reveal that there are significant differences among Generations X, Y and Z, while emotional value is insignificant. Generation X is concerned about functional and conditional value, whereas Generation Y expresses the highest concern on epistemic and social value. Meanwhile, Generation Z pays attention to epistemic, functional and social value.

The novelty of this study contributes to TCV affecting the different FDAs consumption value among Generations X, Y and Z, while the previous research only focused on gender and age difference, and this study firstly combines FDAs with TCV to predict the consumers’ intention to continuously use FDAs in the post-COVID-19 outbreak.

This paper aims to develop and present a new planning framework of social marketing, known as consumer research, segmentation, design of the social programme, implementation, evaluation and sustainability (CSD-IES).

The proposed framework is based on recent theoretical developments in social marketing and is informed by the key strengths of existing social marketing planning approaches.

The CSD-IES planning framework incorporates emerging principles of social marketing. For example, sustainability in changed behaviour, ethical considerations in designing social marketing programmes, the need for continuous research to understand the changing needs of the priority audience during the programme and the need for explicit feedback mechanisms.

The CSD-IES framework is a dynamic and flexible framework that guides social marketers, other practitioners and researchers to develop, implement and evaluate effective and sustainable social marketing programmes to influence or change specific behaviours based on available resources.

This paper makes an important contribution to social marketing theory and practice by integrating elements of behaviour maintenance, consideration of ethical perspectives and continuous feedback mechanisms in developing the CSD-IES framework, bringing it in line with the global consensus definition of social marketing.

The purpose of this paper is to explore China’s online wine market segmentation on the basis of the wine-related lifestyle (WRL). Moreover, this study can provide further understanding and reference about China’s wine market segmentation research, which is limited at present. This work can be helpful for those who want to do further research in the Chinese wine market. It is good for wine importers wanting to import wine to China to understand the Chinese wine consumers.

Survey data were obtained from a sample of 3,369 participants through cooperation between the College of Enology and the Yesmywine.com website. Questionnaire items included gender, age, area distribution, unit price, bottles consumed, drinking frequency, drinking time, wine-related knowledge, etc. Combined with the influence factors of the WRL, a structural equation model was developed. The data analysis, particularly employing principal component analysis, enabled the identification of five market segments.

Five distinct segments were identified within the wine market and designated as follows: wine official consumption type enthusiastic fancier; enjoyment consumption; fashionable consumption; and new, young wine drinkers.

The research data were derived from Yesmywine, one of the largest online wine sale platforms. However, the impact of yesmywine is much smaller compared with Tmall and Taobao and Jingdong. In this paper, we can see that WRL is increasingly becoming a part of Chinese people’s daily lives, especially for the enthusiastic and fancier wine consumers, which is the official type of wine consumer. Next, an analysis of time series under the data of the near future years should be conducted to find the online wine segmentation market variation trend. Moreover, it is important to conduct cross-culture comparison between the Chinese and Australians. Brand positioning can be improved by better understanding China’s online wine market segmentation.

WRL segmentation is valuable for the wine importers and producers in west France, Italian, Germany and so on, as they want to develop China’s wine market and understand the mindset of Chinese wine consumers. The wine importers in China should focus more on consumers that enjoy wine along with newer and younger wine drinkers.

This paper analyzes a large sample (3,369) and therefore is useful for understanding online wine market segmentation and wine consumption behavior in China owing to China’s limited wine market segmentation literature. This paper is the first to use WRL tool to segment China’s online wine market. Moreover, the research data have reference value for those who want to learn more about China’s online wine market, as yesmywine is one of the largest online wine-sale platforms. It also gives some managerial implications for wineries and wine marketers that will be helpful to wine companies in understanding the emerging Chinese wine market and in enacting wine marketing strategies more effectively.

Although several theoretical concepts imply different determinants of female entrepreneurship, the literature lacks a consensus on their significance. The aim of this paper is to verify how industry specificity influences the gender pay gap and its relation to female entrepreneurship.

The authors distinguish industries based on the gender equality level, measured jointly by two factors: pay gap level and female participation rate. The study has been conducted among 22 European countries with relatively similar institutional backgrounds. The authors carry out the analysis based on the panel regression models, which enable the authors to verify two predefined research questions.

The results of panel regression models indicate that industry specificity plays a significant role in the relation between the pay gap and female entrepreneurship. Generally, it can be concluded that gender pay gap as a measure of gender inequality is dependent on the industry specificity. The dependence is especially visible in the breakdown of male- and female-dominated industries.

The findings are consistent with the assumption that the gender pay gap is a discriminatory factor for women willing to become entrepreneurs in certain industries. The findings of the study may constitute a vital tool in planning to overcome it.

This study aims to provide a cutting-edge evaluation of the sharing economy's impact within the realm of tourism and hospitality. The primary objectives guiding this research are as follows: to uncover the prevalent discussions and debates within the tourism and hospitality sector concerning the implications and effects of the sharing economy on urban destinations; and to analyse how scholarly inquiries and empirical investigations have contributed to a comprehensive comprehension of the intricate theoretical foundations and practical intricacies inherent in the sharing economy. This exploration takes place within the extensive expanse of existing literature.

The study used the non-conventional method for data mining. An artificial intelligence (AI) tool called www.dimensions.ai was used to mine data between the year 2002 and 2021. After which the data was analysed, using Citespace software that assisted in building themes for answering the research questions.

The sharing economy has multifaceted implications for rural and urban destinations. For instance, the findings demonstrated that emotional solidarity fosters community bonds between tourists and residents, enhancing authenticity. While, management firms optimise short-term rentals, boosting revenue and occupancy rates despite capped at 20%. It further demonstrated that the sharing economy disrupts traditional accommodations, especially hotels, impacting rural and urban destinations differently based on location and regulatory flexibility. Technological advancements would shape the digital future, transforming the resource in sharing and connectivity in urban settings.

Management firms or agents significantly enhance property facilities, revenue and occupancy rates. Properties managed by professionals perform better in terms of revenue and occupancy; furthermore, traditional accommodations need innovative strategies to compete with sharing economy platforms. Policymakers must consider location-specific regulations to balance sharing economy impacts. Embracing technological advancements ensures urban destinations stay relevant and competitive.

Emotional solidarity fosters bonds between residents and tourists, contributing to a sense of community. Management firms contribute to local economies and stability. However, Airbnb's impact on traditional accommodations raises concerns about the effect on residents and communities.

The study incorporates classical sociology theory to understand emotional solidarity and extends the concept of moral economy to guide economic behaviour in the sharing economy. The analysis also underscores the influence of technological trends such as mobile technology, Internet of Things, AI and blockchain on sharing practices in reshaping existing theoretical frameworks in the sharing atmosphere. Furthermore, the co-creation of value theory highlights collaborative interactions between hosts and guests, shaping the sharing economy experience. Consumer segmentation and choice theories shed light on sharing economy dynamics. Institutional and location-based theories provide insights into regulatory and location-specific impacts.

This research contributes by comprehensively exploring the multifaceted implications of the sharing economy on a tourist destination. It delves into emotional solidarity, management firm roles and location-specific impacts, enriching the understanding of the sharing economy's effects. The application of co-creation of value theory and examination of platform technologies offer fresh perspectives on value creation and user engagement. The study's focus on practical dimensions guides stakeholders in optimising the benefits and addressing challenges posed by the sharing economy in urban contexts. The exploration of moral economy and its relevance to the sharing economy provides a novel perspective, while the examination of technological influences on sharing practices contributes to understanding the digital future of the sharing economy.