The effects of negative social media connotations on subjective wellbeing of an ageing population: A stressor-strain-outcome perspective

In recent years, users' privacy concerns and reluctance to use have posed a challenge for the social media and wellbeing of its users. There is a paucity of research on elderly users' negative connotations of social media and the way these connotations contribute to developing passive behaviour towards social media use, which, in turn, affects subjective wellbeing. To address this research vacuum we employed the stressor-strain-outcome (SSO) approach to describe the evolution of passive social media use behaviour from the perspective of communication overload, complexity, and privacy. We conceptualized subjective wellbeing as a combination of three components-negative feelings, positive feelings, and life satisfaction. Negative and positive feelings were used to derive an overall affect balance score that fluctuates between 'unhappiest possible' and 'happiest possible'. The proposed research framework was empirically validated through 399 valid responses from elderly social media users. Our findings reveal that communication overload and complexity raise privacy concerns among social media users, which leads to passive usage of social media. This passive social media use improved the subjective wellbeing favourably by lowering negative feelings and raising positive feelings and life satisfaction. The findings also revealed that respondents' overall affect balance leans towards positive feelings as a consequence of passive social media use. This study contributes to the field of technostress by illuminating how the SSO perspective aid the comprehension of the way passive social media use influences the subjective wellbeing of its users.

Fired by an algorithm? Exploration of conformism with biased intelligent decision support systems in the context of workplace discipline

Purpose

The importance of artificial intelligence in human resource management has grown substantially. Previous literature discusses the advantages of AI implementation at a workplace and its various consequences, often hostile, for employees. However, there is little empirical research on the topic. The authors address this gap by studying if individuals oppose biased algorithm recommendations regarding disciplinary actions in an organisation.

Design/methodology/approach

The authors conducted an exploratory experiment in which the authors evaluated 76 subjects over a set of 5 scenarios in which a biased algorithm gave strict recommendations regarding disciplinary actions at a workplace.

Findings

The authors’ results suggest that biased suggestions from intelligent agents can influence individuals who make disciplinary decisions.

Social implications

The authors’ results contribute to the ongoing debate on applying AI solutions to HR problems. The authors demonstrate that biased algorithms may substantially change how employees are treated and show that human conformity towards intelligent decision support systems is broader than expected.

Originality/value

The authors’ paper is among the first to show that people may accept recommendations that provoke moral dilemmas, bring adverse outcomes, or harm employees. The authors introduce the problem of “algorithmic conformism” and discuss its consequences for HRM.

The anatomy of ‘fake news’: Studying false messages as digital objects

Public concern about ‘fake news’ skyrocketed following the 2016 US presidential election and the Brexit referendum, and has only intensified since then. A burgeoning body of research on the topic is emerging, and conceptual clarity is vital for this research to converge into a cumulative body of knowledge; the purpose of this article is to underline and address some of the conceptual clutter and ambiguities around the concept of fake news and situate it within its social context. To do so, we first discuss the problems with current terminology and conceptualisation, and then draw on recent developments on the ontology of digital objects and their attributes to shift the focus from fake news to false messages, a type of syntactic digital objects comprised of content and structure and characterised by attributes of editability, openness, interactivity, and distributedness. Then we expand this concept further by placing it within a network of actors and digital objects. Our analysis uncovers several areas of research that have been overlooked in the study of fake news.