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The study aims to examine the validity of the gender affinity effect on social media throughout election campaigns.

This paper examines the role of gender in political discourse, using citizens' conversations on Facebook in the days leading up to Israel's 2021 elections as its case study. The analysis measured the engagement generated by male and female politicians in citizens' publicly open Facebook discussions (N = 1875) using a trend-tracking software. The analysis uses t-tests to examine differences in engagement between conversations about male versus female politicians and between posts written by male versus female authors. In addition, a two-way ANOVA analysis was conducted in an attempt to understand the shared impact of both the politicians' gender and posts authors' gender on the posts' engagement.

The study reveals that although more posts discuss male politicians, posts dealing with female politicians expressed significantly more support towards those politicians. The analysis also highlights that women tend to write more supportive posts and that most of their posts deal with female politicians. Furthermore, interaction effect analysis revealed that women's posts about female politicians generate more engagement in terms of likes, comments and number of participants than posts written by women that deal with male politicians.

The findings should encourage women politicians to run their campaigns via social media.

The study presents the first social media analysis for gender affinity effect and highlights the importance of the effect in online political communication studies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2022-0199

This paper aims to demonstrate that Facebook likes affect outcomes in nonprofit settings. Specifically, Facebook likes influence affinity to nonprofits, which, in turn, affects fundraising outcomes.

The authors report three studies that establish that relationship. To examine social contagion, Study 1 – an auction field study – relies on selling artwork created by underprivileged youth. To isolate signaling, Study 2 manipulates the number of total Facebook likes on a page. To isolate commitment escalation, Study 3 manipulates whether a participant clicks a Facebook like.

The results show that Facebook likes increase willingness to contribute in nonprofit settings and that the process goes through affinity, as well as through Facebook impressions and bidding intensity. The total number of Facebook likes has a direct signaling effect and an indirect social contagion effect.

The effectiveness of the proposed mechanisms is limited to nonprofit settings and only applies to short-term effects.

Facebook likes serve as both a quality signal and a commitment mechanism. The magnitude of commitment escalation is larger, and the relationship is moderated by familiarity with the organization. Managers should target Facebook likes at those less familiar with the organization and should prioritize getting a potential donor to leave a like as a step leading to donation, in essence mapping a donor journey from prospective to active, where Facebook likes play an essential role in the journey. In a charity auction setting, the donor journey involves an additional step of bidder intensity.

The approach the authors study is shown effective in nonprofit settings but does not appear to extend to corporate social responsibility more broadly.

To the best of the authors’ knowledge, this study is the first investigation to map Facebook likes to a seller’s journey through signals and commitment, as well as the only investigation to map Facebook likes to charity auctions and show the effectiveness of this in the field.

Mainland Chinese students are the largest group of international students globally. The role of international students in destination marketing can be seen as “Word-of-Mouth Champions”. This study attempts to examine the effect of place attachment and affinity for Mainland Chinese students on generating word-of-mouth intention towards their place of study.

Six well-trained research assistants collected paper-based questionnaires in six institutions in Macao. They chose every tenth student who passed by to fill in the questionnaire at six locations in each institution. This study employed partial least squares structural equation modelling (PLS-SEM) to estimate the strength of causal relationship among place identity, place dependence, affinity and intention to word-of-mouth.

The results of the survey from 327 students in Macao indicate that place dependence, place identity and affinity drive Mainland Chinese students to provide word-of-mouth regarding Macao. Place dependence has a positive influence on place identity, and place identity has a positive influence on affinity with residents. However, place dependence has no significant direct effect on affinity.

Evidence from this study indicates the importance of students' word-of-mouth as they as sojourners, in particular, the students' place attachment and affinity for residents is critical to positive their Word-of-mouth on destinations. This research offers insights about the potential group which need require attention.

This study fills a research gap by exploring the relationship between place attachment and social distance in influencing Mainland Chinese students' behaviour, a relationship that has rarely been investigated in tourism research. Practical recommendations are provided to the governments, universities and education enterprises according to the results of the study. From both theoretical and practical perspectives, the findings from this study suggest promoting international students to turn into real “Word-of-Mouth Champions”.

The purpose of this study is to investigate consumers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT) and complexity theory.

By using a purposive sampling method, a configurational model was developed and a questionnaire-based survey was conducted to gather responses from a Malaysian sample. A total of 223 responses were obtained. Partial least square structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) were adopted to analyze the data.

The PLS-SEM indicated that performance expectancy, effort expectancy, social influence and affinity for technology interaction were positive cryptocurrency adoption predictors, whereas regulation was a negative predictor. Based on the fsQCA, cryptocurrency adoption could be explained by six configurational paths, which comprised combinations of the proposed causal conditions: the UTAUT factors (performance expectancy, effort expectancy, facilitating condition and social influence), environmental factor (regulation) and individual factors (financial knowledge and affinity for technology interaction).

This study offers contributions to the theoretical body of knowledge by articulating the relevance of extended UTAUT and extending the established UTAUT model by integrating external environment and personal factors, also showing the linear and nonlinear interplays of performance expectancy, effort expectancy, facilitating conditions, social influence, regulation, financial knowledge and affinity for technology interaction.

The findings facilitated practitioners’ (cryptocurrency brokers, governments and businesses) fostering of cryptocurrency adoption through the joint consideration of different factors. The factors spanned technological attributes and individual characteristics to regulation. Practitioners should acknowledge that different combinations of the aforementioned antecedents can be equally effective to increase cryptocurrency adoption. The findings suggested that these causal conditions should be considered holistically and that there is no best predictor.

In social terms, the research is expected to contribute to the dissemination of cryptocurrencies and help governments and central banks to develop, regulate and supervise digital currencies, as well as in the implementation of a digital currency ecosystem aligned with sustainable development goals. Economically, the results might foster a high cryptocurrency adoption rate and stimulate crypto-token-based business models and investment opportunities that present new means of revenue generation at individual, organizational and national levels.

This study offers unique perspectives for the body of knowledge and practice in the cryptocurrency domain, using both symmetric and asymmetric methodologies, by delineating the configurational logic involving technological capabilities, social influences, regulation and individual characteristics in facilitating more efficacious dissemination of cryptocurrencies.

The public sector use of the internet of Things (IoT) technology is an emerging field with a potential for a variety of institutional applications in the fields of information gathering and policy implementation to establish resilience for modern society. In this context, we aim to investigate the success factors which can positively influence the continuous usage intention of IoT service with the mediation effect of perceived public value.

A conceptual model based on the strong literature and theoretical background is tailored to provide factors for IoT services success in the public sector. A quantitative survey was conducted through 381 citizens using IoT services to validate the proposed conceptual model using structural equation modeling approach in order to examine the influence of identified constructs on the continuous usage intention.

The results highlighted that the proposed model successfully accounted for about 59% perceived variance in public value creation and 63% perceived variance in citizens' continuous usage intention. IoT services success is best dignified by the perceptions of citizens who use the services, therefore, this study identifies the positive role of digital society affinity in context of social sustainability and it climaxes that the real value of IoT in public sector comes from establishment of services on top of the service delivery and that's where the public value is going to be created.

The use of IoT technology in public services will fetch much benefit to the citizens as well as to the government. The study findings are significant in identifying good practices for generating public value in digital society affinity.

The integrated conceptual model explores the driving factors of citizens' inclination towards IoT technology in a social context. Through this study, we can analyze the role of perceived public value in enhancing the citizens' engagement with IoT services. The government policymakers and ICT managers take help from this study to designing IoT public services with making the government more responsive to citizens.

The purpose of this study is to examine the factors that drive superior social enterprise performance for women-led social enterprises. The authors examined the role of individual entrepreneur cognitive characteristics contributing to social enterprise performance and recommended a framework for women's social entrepreneur development.

The authors conducted an exploratory qualitative study of 22 women founders of social enterprises using a semi-structured questionnaire. In-depth interviews were conducted, and the transcripts were analyzed using thematic content analysis.

This study found a significant impact of self-efficacy on the performance of social enterprises among the studied subjects. Social support in the form of material, information and emotional support enhanced the ability of women social entrepreneurs to better achieve business sustenance and continuance of operations. The business skills of the women social entrepreneurs led them to move from just social impact generators to becoming thought leaders. The strong prosocial motivation of the founders contributed to building their resilience in the face of adversity.

This study extended the existing theories on social entrepreneurship by bringing the dimensions of entrepreneurial resilience in driving social enterprise performance along with business skills. Thus, it provided an enhanced explanation to the existing body of knowledge on contributors to superior social enterprise performance.

This study gathered insights into the role of entrepreneurship education focused on business skills, especially for women social entrepreneurs in achieving superior performance for their social ventures. This also reconfirmed the role of social support and how structurally this could be provided by educational systems to aspiring women social entrepreneurs.

The practice of social entrepreneurship by women social entrepreneurs has been growing. Its importance in developing economies because of its ability to make grassroots changes at the lower levels of society was substantive. Women have shown more inclination toward social business with an affinity for prosocial contribution. By focusing on nurturing these social enterprises, governments as well as global agencies like the United Nations and the World Economic Forum could accelerate social change. Furthermore, support for the current women social entrepreneurs as change-makers making a difference in society could be achieved.

To the best of the authors’ knowledge, this research study was one of the first studies on women social entrepreneurs focusing on the factors of self-efficacy, social support and entrepreneurial resilience contributing to social enterprise performance. This study combined the social entrepreneurship intention theory with entrepreneurial resilience and business skills to understand the factors leading to successful social enterprise performance for women social entrepreneurs.

This study aims to explore how social media affects decision-making among tourists and whether there is a potential effect of age, which is studied through generations. For this purpose, baby boomers, Gen X, Gen Y and Gen Z tourists are studied and real-time implications are offered.

The study adopts a descriptive and exploratory design where the conceptual model of social media-based decision-making is developed through a review of the literature. Quantitative analysis is conducted on primary data from 600 Indian tourists. This is done using a self-administered questionnaire adopted from Gulati (2022) after checking its validity and reliability. The statistical analysis for hypothesis testing is done using PLS-SEM path modelling on pooled data. To study the categorical moderating effect of generations, partial least squares multigroup analysis (PLS-MGA) is performed as a paired comparison on every successive generation.

After testing every successive younger generation with an older generation through PLS-MGA, none of the pairs found any significant differences in path coefficients, as the values obtained were 0.05 < p < 0.95 for all five paths (SM → NR, SM → IS, SM → E, SM → P, SM → PPB). This indicates all the generations behave in a similar manner irrespective of them being older or younger, and age does not moderate social media’s impact on decision-making among Indian tourists.

The study establishes India as a unique geographical market and suggests tourism marketers to treat all generations at par, irrespective of age, as they behave and interact with social media in a similar manner. But, because this study is restricted to a single geographical location, i.e. India, further regions can be explored for global generalisation. Future research can also explore other demographics for combined, moderated analysis. Findings from the study suggest that marketers should ensure that equal attention is given to all generations as they engage with social media in a similar manner. Targeted marketing using artificial intelligence can help in ensuring custom ads. Personalisation according to generations can also facilitate greater purchases.

The study fills a major population and knowledge gap by exploring a topic that has been highly under-researched. Also, the study adopts an inclusive approach by analysing all the generations, both younger and older, to understand the potential effect of age on moderating the impact that social media has on tourist decision-making. Further, real-time suggestions and implications are offered to tourism marketers with special reference to the Indian tourism industry.

Most scientific research has focused on understanding Ponzi schemes from the point of view of the schemes and their operators, based on qualitative analysis. This paper aims to analyze Ponzi schemes from the perspective of their investors, emphasizing behavioral aspects, which have been little explored in the scientific literature, especially in quantitative research. In this way, the authors sought to understand the effects of heuristics and cognitive biases in understanding investor behavior.

A logistic regression was carried out with Brazilian investors, some of them participants in Ponzi schemes, who answered a structured questionnaire by means of a survey.

The authors found that social pressures, overconfidence and deliberate ignorance lead to credulity, generating little risk analysis and the desire to make a lot of money quickly.

Helping investors improve their levels of information through financial education and self-knowledge about their behavior. Contribute to the competent authorities in the search for improvements in the information displayed to investors.

Understanding the mechanisms used when making a financial decision from the point of view of investors in general, but especially those exposed to Ponzi schemes, has the mission of enlightening them about the importance of financial education and the weight of psychological factors so that they can reduce the effects of heuristics and analysis biases when faced with a financial decision.

The basis of this work will be the inclusion of psychological variables and financial education, adapting existing models in an attempt to demonstrate the effects they may or may not have on mental accounting in the specific case of investors

Pulse check on discipline degrees for changed status quo is vital to ensure global futures for international enrolments (IEs). While employers spend less on training and more on innovating, can IEs manage time spent wisely and profitably (self-sufficiency) via collecting demand-driven credentials (micro-credentialing, Mc)? Due to limited research on Multidisciplinary, Micro-credentialing (MdMc), communication among stakeholders becomes difficult – there is no sense of self-sufficiency and course crossbreed lags; thus, diploma initiatives rarely succeed. Hence, MdMc aims to generate industry-necessitated, new knowledge hybrids where courses could generate adaptable Md links and intersections towards self-sufficiency. We propose a methodology based on Md content analysis on rapidly deployable knowledge bases suitable for multisector employability: a market survey to identify new knowledge areas. The outcome is to be knowledge mapped to identify gaps in skills required for applications to meet across disciplines. Finding the nature of these gaps intends to present possible knowledge links and intersections among courses. Diagrammatised and textual analysis of self-sufficiency-related benefits that could forge robust faulty-industry partnerships will be discussed – to demonstrate fluidity between credentials and careers. The resulting MdMc rigour model would present avenues for new content, training programmes, and a potential HE-industry manifesto. This MdMc model may offer a quick and dynamic process of epistemic, accessibility and instructional rigour checks to achieve professional currency towards self-sufficiency for IEs.