Search results

Following the growing adoption of social media, many entrepreneurs are launching personal social media channels. This study focuses on the effect of entrepreneurs' shared information on We Media platforms on the value relevance of their earnings.

Using entrepreneurs' We Media data collected from A-share-listed companies on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2018, this study investigates the effect of the data on the value relevance of earnings using the modified Ohlson model. The authors applied textual analysis to retrieve entrepreneurial We Media data acquired manually from Weibo.

We Media platforms can increase the value relevance of earnings. Entrepreneurs can enhance investor trust by establishing social ties with investors. Investors are more likely to recognize earnings information publicized by enterprises, owing to internal consistency. Particularly, value relevance improves significantly with more personal information being posted and more “likes” being acquired on entrepreneurs' We Media accounts. This positive effect is more obvious in privately owned and highly marketized regions.

The findings extend the research on the economic consequences of We Media as an important information channel, enrich the research on the social media posting behavior of entrepreneurs and provide a reference for enterprises to instill trust using new information disclosure methods and for governments to establish a safe internet environment to promote the sustainable development of the capital market.

This study aims to explore possible behavioural change venues, beyond the traditional approach to financial education, using the capability-opportunity-motivation behaviour theoretical framework of behavioural change.

The study included 45, semi-structured, in-depth interviews of young adults to explore which elements of financial behaviour formation should interventions target to be effective.

To strengthen capability, the study recommends behavioural education and training for boosting financial knowledge and skills, enablement of financial independence and modelling for empowering self-control and reducing impulsiveness. To boost motivation, gamification of modelling is advised for boosting responsible financial behaviour as part of the identity and inducing consideration of future consequences. Persuasion is advised for inducing positive emotions while incentivization and coercion are advised for empowering self-conscious intentions. To rise opportunity, the study proposes incentivization and coercion imposed by parents, and governmental efforts regarding restriction, enablement and environmental restructuring.

The study brings recommendations for developing efficient interventions for strengthening responsible financial behaviour that may help design type-specific education programmes to promote responsible financial behaviour.

The present study attempts to explore new venues in intervention design that break away from the traditional approach of financial education focused on knowledge and skills that is proven to be ineffective

For decades, conflict resolution (CR) educators working cross-culturally have struggled with a fundamental dilemma – whether to offer western, evidence-based approaches through a top-down (prescriptive) training process or to use a bottom-up (elicitive) strategy that builds on local cultural knowledge of effective in situ conflict management. This study aims to explore which conditions that prompted experienced CR instructors to use more prescriptive or elicitive approaches to such training in a foreign culture and the implications for training outcomes.

There are two parts to this study. First, the authors conducted a literature review to identify basic conditions that might be conducive to conducting prescriptive or elicitive cross-cultural CR training. The authors then tested the identified conditions in a survey with experienced CR instructors to identify different conditions that afforded prescriptive or elicitive approaches. Exploratory factor analysis and regression were used to assess which conditions determined whether a prescriptive or elicitive approach produced better outcomes.

In general, although prescriptive methods were found to be more efficient, elicitive methods produced more effective, culturally appropriate, sustainable and culturally sensitive training. Results revealed a variety of instructor, participant and contextual factors that influenced whether a prescriptive or elicitive approach was applied and found to be more suitable.

This study used empirical survey data with practicing experts to provide insight and guidance into when to use different approaches to CC-CR training effectively.

This study sought to understand which food allergen labeling systems (non-directive, semi-directive, and directive) were attended to and preferred by 34 participants with food hypersensitivity and their perceived corporate social responsibility (CSR) and behavioral intention towards a restaurant that identifies food allergens on menus.

This study used an online survey with open-ended and ranking questions, combined with eye-tracking technology, to explore participants' visual attention and design preferences regarding four menus. This study utilized one-way repeated measures analysis of variance (RM-ANOVA) and heat maps to analyze participants' menu-reading behaviors. A content analysis of survey responses and a ranking analysis of menus were conducted to understand the reasons behind consumers' preferred menu designs.

The advisory statement was not much attended to. Participants identified food allergen information significantly quicker with the directive labeling system (icons) than the other two systems, implying they were eye-catching. Semi-directive labeling system (red text) has lower visit count and was more preferred than two other systems; each labeling system has its strengths and limitations. Participants viewed restaurants that disclosed food allergen information on menus as socially responsible, and they would revisit those restaurants in the future.

This study was one of the first to explore, through use of eye-tracking technology, which food allergen labeling systems were attended to by consumers with food hypersensitivity. The use of triangulation methods strengthened the credibility of the results. The study provided empirical data to restauranteurs in the US on the values of food allergen identification on restaurant menus, although it is voluntary.

Prospective students and other stakeholders in the education system use global and national rankings as a measure of the quality of education offered by different higher educational institutions. The ranking of an Institution is seen as a measure of reputation and has a significant role in attracting students. But are students happy in the top-ranked institutions? Does a high rank translate into high student satisfaction? This study answers this question taking data from top educational institutions in India.

This study examines how the top-ranked higher education institutions in India fare on student satisfaction. Using the data on key performance indicators published by the National Institutional Ranking Framework (NIRF) and student satisfaction scores of these institutions reported by NAAC, the study explores a possible relationship between the ranking of an institution and its student satisfaction score.

The study finds no significant relationship between the ranking of an institution and its student satisfaction score. The only institutional performance dimension which has a positive correlation with student satisfaction is graduate outcome. The diversity dimension is seen to be negatively correlated with student satisfaction.

The importance of modifying the ranking frameworks to account for the real drivers of student satisfaction is highlighted. The items in the student satisfaction survey should be regularly updated to reflect the actual concerns of the students. This is very important given the fact that the number of Indian students going abroad for higher education recorded a six-year high in 2022 at 750,365.

With more than 50,000 institutions catering to over 40 million students, India has the largest higher education system in the world. Given the high level of competition among these institutions, ranking and accreditation have become important parameters used by students for selection of an institution. But do top-ranked higher education institutions have the most satisfied student community? The assumption is disproved using the most credible secondary data. This study is the first of its kind in the Indian context. It has huge implications for the most respected ranking frameworks.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.