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The purpose of this paper is to examine the impact of the type of disclosure used by social media influencers on consumer evaluations of influencer transparency, product performance expectations and how those factors ultimately influence purchase intentions.

An experiment was conducted with 321 participants recruited from MTurk to test a moderated serial-mediation model.

The results indicate that when consumers become cognizant that an influencer’s branded promotional post may have been motivated by an underlying financial relationship, they evaluate the influencer as significantly less transparent if a more ambiguous disclosure is used relative to a clearer disclosure. Transparency perceptions of the influencer impact consumers’ perceptions of product efficacy as well as purchase intentions.

Social media influencers are rapidly emerging as a popular marketing tool for brand managers, but consumer response to this form of promotion is not well understood. To the best of the authors’ knowledge, this is the first study to investigate how the type of endorsement disclosure used by a social media influencer impacts consumer perception of influencer transparency, product efficacy and purchase intentions. Further, this research demonstrates the applicability of the persuasion knowledge model in the domain of influencer marketing.

Entrepreneurship is ubiquitous, but it is not unequivocally a human force for social and economic good. Critical perspectives of the entrepreneur, entrepreneurship, and entrepreneurial success (and failure) are evolving in the scholarly literature. Dark side theory has emerged as a language for critiquing the dominant narratives of entrepreneurship portrayed in scholarship, education, planning, policy, and other forms of practice. This chapter draws from dark side entrepreneurship theory, Baumolian entrepreneurship, and exemplars of counterculture to craft language for an emerging theory of misfit entrepreneurship, which consists of misfit entrepreneurs and alternative enterprises. Alternative enterprises and misfit entrepreneurs are conceptualized, and literary examples (i.e., Robin Hood and Song Jiang) and modern-day examples (i.e., Hacker groups) are supplied. The unique actions and impacts of misfit entrepreneurs and alternative enterprises are offered for discussion. This new theory of misfit entrepreneurship leaves readers with exploratory questions that enhance critical perspectives and modern understandings of entrepreneurship today.

Across different research fields, it is increasingly acknowledged that gender is not a binary variable and goes beyond the male–female dichotomy. At the same time, gender is a prominent social cue that affects evaluations and interactions among individuals. Thus, gender can impact social processes on many levels in complex ways. Meetings provide arenas where key social processes unfold that are relevant to the organization. Understanding which role gender takes in this context is therefore central to organizations as well as meeting research. This chapter provides a critical review of research to date on social influence in meetings, specifically zooming in on the role of gender. The authors conducted a multi-step systematic literature review and identified 43 studies across a wide area of disciplines (e.g., psychology, communication, and management). The authors put special emphasis on the methodologies employed across this work since a comprehensive understanding of the applied methods is core for a synthesis of research results. Through the analysis, the authors pinpoint six variables – individual gender, sex role orientation, gender composition, gender salience, contextual factors such as task type and organizational settings, and the construction of gender as a social concept – that are directly related to gender and which represent factors that are critical for the role of gender in the meeting context. Thereby, this chapter aims to provide a roadmap for researchers and practitioners interested in the role of gender during workplace meetings. The authors conclude by highlighting methodological and managerial recommendations and suggest avenues for future research.

In this research, the authors aim to investigate the impact of product display quantity on consumers' online purchase intention through the diminished pain of payment, in light of signaling theory and mental accounting theory. Additionally, the authors test the role of price in this psychological mechanism.

The authors use a combination of online studies and field experiments to test our predictions. Four online studies are conducted to test the main effect of product display quantity on purchase intention (Studies 1A and 1B), the mediating effect of the diminished pain of payment (Study 2), and the moderating role of price (Study 3). Two field experiments are conducted to strengthen the robustness of our findings.

The findings suggest that product display quantity has a significantly positive impact on purchase intention, mediated by the diminished pain of payment, and this effect is moderated by price.

This is the first study to investigate the effect of product display quantity on online purchase intention. This research advances the discussion of product display quantity, which provides retailers and consumers with a convenient way to communicate with each other and leads to a more relaxed purchase experience.

Online influencers are increasingly used by brands around the globe to establish brand communication. This study aims to investigate the characteristics of social media content in terms of presentation style and brand communication among online influencers in China. The authors identified how characteristics of social media posts influence young consumers’ engagement with the posts.

The authors analyzed 1,779 posts from the Sina Weibo accounts of ten top-ranked online influencers by combining traditional content analysis with Web data crawling of audience engagement with social media posts.

Online influencers in China more frequently used photos than videos to communicate with their social media audience. Altogether 8% and 6% of posts carried information about promotion and event, respectively. Posts with promotional incentives as well as event information were more likely to engage audiences. Altogether 22% of the sampled social media posts mentioned brands. Posts with brand information, however, were less likely to engage audiences. Furthermore, having long text is more effective than photos/images in generating likes from social media audiences.

Combining content analysis of social media posts and engagement analytics obtained via Web data crawling, this study is, to the best of the authors’ knowledge, one of the first empirical studies to analyze influencer marketing and young consumers’ reactions to social media in China.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.