Search results

Exposing the hidden lives of female public relations (PR) practitioners requires deep connection with those lives. Stories need to be uncovered, interrogated, and ultimately told, to shine a light on the lived experiences of those working in PR. The methods used to collect these stories require deep immersion in the field and the ethnographic method is ideal for this. Ethnographic research methods have long been utilised to gain insights into the lived experiences of individuals and communities. This chapter provides an understanding of the strengths and limitations of ethnographic research methods in capturing the nuances of women's experiences of working in PR.

Organisational ethnography is an established field in business studies and has been used to investigate disciplines cognate to PR, including advertising and media, but, to date, has failed to be fully explored in PR research. This chapter examines the potential for ethnography to open new areas of PR theory and considers its potential as a means of bridging the gap between PR theory and practice.

Ethnography is not without its limitations; key concerns surround objectivity, the role of the researcher, and that of the participant, and ethics. Nonetheless, this method would appear to offer huge potential for the study of PR practices; the diverse nature of the sector makes it a rich area to study.

This chapter explores the potential of this method to offer an opportunity to investigate areas such as working practices, ethics in practice, power, gender, diversity, and culture.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.