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The purpose of this paper is to unfold how different digital marketing tools and strategies influence recruitment effectiveness. More specifically, it focusses on understanding if, and how, information sources’ credibility, content marketing, and organisational reputation influence candidates’ decision to apply for a job in the Portuguese market.

A qualitative research, aligned with a content analysis, was conducted to focus on the insights from the 21 participants interviewed, to understand their thoughts and experiences regarding the subject.

The results show that digital marketing tools owned by the company are seen to be more credible and more relevant for the job application decision. LinkedIn is considered to be a more credible platform for advertising job openings than Facebook. In terms of content marketing, LinkedIn has a positive influence on candidates’ decision, as well as companies’ reputation.

This study provides practical implications which are useful for both HR and marketing managers, namely, the implementation of an integrated marketing communication strategy, the reinforcement of the company’s website and LinkedIn page and a presence on universities’ platforms, and also in terms of the information that content marketing should focus on.

This research paper incorporates marketing insights into a well-known HRM subject – recruitment, and thus adds further knowledge to the literature and prepares the ground for researchers who wish to explore this subject further.

How can students become transformational leaders if they are left alone to grapple with the emotional toll of climate change, preparing for careers while scientists sound the alarm that business as usual is untenable? Ecoanxiety, solastalgia, and climate grief are the affective undercurrents in sustainability and environmental science classrooms. This case study discusses strategies used to support students' emotional well-being in an introductory sustainability class and a co-curricular climate change support group program at Oregon State University. Psychologists and sustainability educators created space for students and faculty to engage in authentic dialogues confronting the emotional uncertainty of the climate crisis and working together to define their roles building a resilient future.

This paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest's four-component model of antecedents for ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners.

This research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning the years 2015–2020. This review's narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods.

In the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest's component model of antecedents for ethical decision-making as a stable framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI.

This paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest's model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.