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This chapter studies a snowball sampling method for social networks with endogenous peer selection. Snowball sampling is a sampling design which preserves the dependence structure of the network. It sequentially collects the information of vertices linked to the vertices collected in the previous iteration. The snowball samples suffer from a sample selection problem because of the endogenous peer selection. The author proposes a new estimation method that uses the relationship between samples in different iterations to correct selection. The author uses the snowball samples collected from Facebook to estimate the proportion of users who support the Umbrella Movement in Hong Kong.

The aim of this paper is to present a sampling method using virtual networks to study “hard‐to‐reach” populations. In the ambit of social research, the use of new technologies is still questioned because the selection bias is an obstacle to carry on scientific research on the Internet. In this regard, the authors' hypothesis is that the use of social networking sites (Web 2.0) can be effective for the study of “hard‐to‐reach” populations. The main advantages of this technique are that it can expand the geographical scope and facilitates the identification of individuals with barriers to access. Therefore, the use of virtual networks in non‐probabilistic samples can increase the sample size and its representativeness.

To test this hypothesis, a virtual method was designed using Facebook to identify Argentinean immigrant entrepreneurs in Spain (214 cases). A characteristic of this population is that some individuals are administratively invisible in national statistics because they have double nationality (non‐EU and EU). The use of virtual sampling was combined with an online questionnaire as a complementary tool for Web 2.0 research in behavioural sciences.

The number of cases detected by Facebook and the virtual response rate is higher than traditional snowball technique. The explanation is that people increase their level of confidence because the researcher shows his personal information (Facebook's profile) and also participates in their groups of interest (Facebook's groups). Moreover, the online questionnaires administration allows the quality of the information to be controlled and avoids duplication of cases.

The present article is the first that uses Facebook as an instrument to study immigrants. Therefore its adoption represents a great challenge in the social research field because there are many barriers of access and search. It also proposes a novel mix of traditional methodologies updated with the use of new virtual possibilities of studying hard to reach populations, especially in areas of social research where the contributions of these methods are less developed.

The purpose of this paper is to uncover the service quality dimensions that influence satisfaction with wineries and future intentions to return among Chinese consumers. With the rapidly growing popularity of wine consumption among Chinese consumers, an increasing number of Chinese consumers are visiting wineries in Western countries. However, while substantial research about wine tourism in Western countries has been published, there is very little research available with respect to wine tourism in China and the Chinese winery visitors who visit them.

A convenience sampling method was selected. Specifically, snowball sampling was used to collect the study’s data due to the limited number of Chinese consumers who drink wine and who have been involved with wine tourism. Research assistants who speak Chinese fluently used snowball sampling to recruit Chinese consumers in Yentai region who had participated in wine tourism in the past and asked them to complete the research survey. The research assistants distributed 200 surveys through a snowball sampling and collected a total of 179 responses.

The study’s results suggest that wine tasting operations, such as a variety of wines at tasting room tastings, and the quality of the wines tasted, along with staff attitudes are critical components that influence Chinese wine tourists’ satisfaction and loyalty.

The major contribution of this paper is that it builds on extant wine tourism literature by providing insights into the characteristics of Chinese wine tourists. The paper also illuminates the linkage between winery service quality attributes and Chinese wine tourists’ satisfaction and loyalty.

The results of the study provide a useful guide to both academics and winery operators interested in developing a competitive winery service quality strategy for Chinese wine tourists.

Given the scarcity of literature linking winery service quality attributes and Chinese wine tourists’ satisfaction and loyalty, this study is one of the few studies to explore this relationship.

Informed decisions about sampling are critical to improving the quality of research synthesis. Even though several qualitative research synthesists have recommended purposeful sampling for synthesizing qualitative research, the published literature holds sparse discussion on how different strategies for purposeful sampling may be applied to a research synthesis. In primary research, Patton is frequently cited as an authority on the topic of purposeful sampling. In Patton’s original texts that are referred to in this article, Patton does not make any suggestion of using purposeful sampling for research synthesis. This article makes a unique contribution to the literature by examining the adaptability of each of Patton’s 16 purposeful sampling strategies to the process of qualitative research synthesis. It illuminates how different purposeful sampling strategies might be particularly suited to constructing multi‐perspectival, emancipatory, participatory and deconstructive interpretations of published research.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.

The purpose of this paper is to discuss the practical use of theoretical sampling as a method for selecting data that provide a richer and deeper understanding of the phenomenon being investigated.

Theoretical sampling is a well-known method in grounded theory studies to seek additional data based on concepts developed from initial data analysis. This method involves following where the data have led to expand and refine the evolving theory during the analytical process. However, there is a dearth of information detailing the practical steps needed to undertake theoretical sampling.

The authors used the theoretical sampling method in their study in four ways: asking additional interview questions and/or widening the scope of existing interview questions; recruiting participants with additional diversity of attributes within the same group; and adding a new group of participants and expanding research settings.

Theoretical sampling is a valuable and practical method for the purpose of addressing gaps in the data in qualitative research. When using theoretical sampling, it is essential to consider potential strategies for countering challenges that may arise. Practical recommendations are offered on the use of theoretical sampling during data analysis, for the purpose of achieving theoretical integration.

Because of competition, residential property developers use a variety of promotional tools to gain recognition and increase their market share and the demand for housing, and to manage their customer relations. This study aims to examine what real estate developers did to detect the need for types of housing, and pricing and promoting housing. It also sought clues about how they manage customer relations in residential sales.

In this study, semi-structured interviews were conducted with real estate developers. This study has heuristic characteristics based on qualitative data. Document reviews, descriptive analysis and discourse analysis were carried out on the interview data and other sources. As purposeful sampling is generally used in qualitative studies; intensity sampling, homogeneous sampling, criterion sampling and snowball sampling were used together in this study.

The study found that real estate developers were inadequate at advertising and promoting, allocated little budget for promotion and did not use technology sufficiently. The real estate developers gave discounts at rates that did not actually desire, had to create payment plans, and as a result, they lost customers because they could not manage customer relations well.

Interviews were conducted with 15 real estate developers who have been selling residential properties for more than 10 years in Süleymanpasa and Çorlu districts of Tekirdag. Data obtained are mostly qualitative.

This study aimed to determine real estate developers’ ability to implement a variety of promotional strategies and manage customer relations. Results and conclusions can offer significant clues about real estate developers with similar characteristics. Its conclusions of this study can be compared to similar studies of real estate developers in many regions of Turkey.

The purpose of this paper is to discuss the issues in studying hidden populations, with particular focus on methodology used to investigate ethnic minority entrepreneurs who illegally run their businesses in the UK. In this paper, on reflection, the authors look at what issues should be considered before engaging with such communities, as we identify current approaches and evaluate their merits.

Certain methodological problems are faced by researchers working with hidden populations, and this paper explores these using a sample of Ukrainian illegal self‐employed construction workers operating in London. Semi‐structured interviews with 20 Ukrainians showcase the issues raised and help illustrate the limited applicability of some commonly used research methods to ethnic minority entrepreneurship studies. The authors used an intermediary to help gain access to these illegal migrants in order to satisfy the sensitive issues of this vulnerable group of respondents.

The authors analyse the ethical considerations, problems and issues with access to such data, discuss early and more recent sampling methodologies and the ways to estimate the size of hidden population. This paper, hence, establishes the state‐of‐the‐art approaches in this field and proposes potential improvements in achieving representativeness of the data. Using the Ukrainian illegal self‐employed construction workers as an example, this paper evaluates the choices made by the researchers.

The main contribution of this paper is to showcase the methodological issues emerging when studying hard‐to‐reach groups and to emphasise the limited applicability of some methods to research on hidden populations.

The purpose of this paper is to understand Eco-Apparel consumption behavior in consumers who care about the environment.

A snowball sampling technique was used to recruit 16 participants for in-depth interviews.

Two attitude-behavior gaps existed: the gap between environmental attitude and Eco-Apparel purchasing behavior; and the gap between Eco-Apparel attitude and Eco-Apparel purchasing behavior. There were two connections: product and emotional benefits leaded to Eco-Apparel purchasing behavior; and personal cost benefits, emotional benefits, and economic considerations leaded to Eco-Apparel using and disposing behavior. These gaps and connections suggested participants have certain standards regarding Eco-Apparel consumption. First, the standard of purchasing Eco-Apparel was the same as regular apparel. Second, participants did not want to expend much effort. Third, for some participants, emotional benefits (e.g. fun, good feeling, satisfaction) were important.

The small sample size and the snowball sampling technique limit generalization of the study’s findings.

These findings might be of interest to apparel manufacturers and retailers who want to re-enforce consumers’ positive attitudes leading to actual purchase and consumption behaviors.

The current study for the first time examines the attitude-behavior gaps, proposes reasons behind these gaps, as well as connections between benefits and Eco-Apparel usage and disposal behaviors. In addition, the proposed framework is the first attempt to illustrate the relationships among gaps, connections, and consumption standards.

The purpose of this paper is to test a process model of coping with job loss by examining the impact of distal to proximal variable sets for incrementally explaining two distinct subjective well‐being variables: life satisfaction and unemployment stigma. A second purpose is to test for mean differences between study scales for increasingly long‐term unemployed individuals.

A unique sample of unemployed victims completed an online survey investigating the impact of six variable sets on life satisfaction and unemployment stigma. These sets fall within the McKee‐Ryan et al. taxonomy and included: human capital and demographics; personal and financial coping resources; cognitive appraisal; escape‐focused coping; problem‐focused coping; and job search effort.

Results partially supported the hypothesized variable set impact order on both life satisfaction and unemployment stigma. In addition some significant differences on study variables were found comparing four unemployed groups: up to six months; and three progressively long‐term unemployed groups, i.e. seven to 12 months; 13 to 24 months; and over 24 months, with the over 24 month unemployed respondents (23 per cent of the sample) suffering the most.

The cross‐sectional self‐report study research design is the foremost limitation. However, given the challenges of collecting unemployment related‐data on such a diverse sample, the unemployment agency/job services recent‐job‐loss‐respondent longitudinal data collection approach used in previous research was not an option. The one‐factor test found that only 15 per cent of “common method variance” was explained by the first factor, suggesting that this is not an overriding limitation. Survey constraints necessitated using shortened validated scales in several instances. However, the authors did select the highest loading items when shortening scales and such scales were generally reliable.

Implications of study results for careers and steps to prevent longer‐term unemployment are discussed. There seemed to be a general “disconnect” between unemployed respondent self‐ratings of positive skill assessment, networking comfort, and proactive search, all of which were fairly high, against recent behavioral job search which was lower. This disconnect suggests that it may be hard for many unemployed to objectively look at their job search process.

A unique unemployed sample, primarily executives, middle managers and professional, salaried individuals, with most being longer‐term unemployed, was utilized. Initial psychometric support for several new scales was found, including unemployment stigma and behavioral job search. This study represented a fairly comprehensive test of the McKee‐Ryan et al. taxonomy for correlates of psychological well‐being during unemployment specifically applied to life satisfaction and unemployment stigma. An innovative on‐line data collection approach, snowball sampling, was used.