Institutt for strategi og entreprenør­skap

Industrial Marketing Management 136 s. 15-33 Doi: https://doi.org/10.1016/j.indmarman.2026.05.011

While there is an increasing number of B2B studies about sustainability, few centre on the issue of biodiversity loss and the business network processes needed to address this. In this paper, we focus on the Swedish forestry sector to investigate the role of alternative accounts made by actors not typically considered as part of the business network (e.g. NGOs, individual activists, ecotourism organisations or investigative journalists), in governing business relationships towards managing biodiversity loss. Through a combination of the sustainability accounting literature and the Industrial Network Approach (INA), we provide a new lens for understanding how network change is pre-mobilised in issue-based nets. Specifically, we introduce the concept of network nudging. We further draw on governmentality to show how the alternative accounts use ethical and emotive discourses to challenge dominant business logics. The paper emphasises the importance of inclusive, dialogical engagement with marginalised voices to strengthen relational governance. We conclude by arguing how current understandings of how sustainability is managed within issue-based nets is enhanced by including the pre-mobilising efforts of alternative accounts.

Journal of Accounting and Public Policy 57 s. 1-31 Doi: https://doi.org/10.1016/j.jaccpubpol.2026.107433

The increasing adoption of Artificial Intelligence (AI) technologies in accounting practices is reshaping traditional processes, offering unprecedented opportunities while also posing significant challenges for organizations. However, previous research has primarily focused on large accounting firms, leaving AI adoption patterns in non-accounting firms, where 76% of accountants are employed, largely underexplored. This study addresses this gap by conducting the first comprehensive comparative analysis of AI adoption, uncovering novel insights into levels, drivers, and barriers of AI integration and how they differ between accounting and non-accounting firms. Based on 35 semi-structured interviews, the study reveals an interplay between organizational-level and individual-level factors that shape adoption of different types of AI: robotic process automation (RPA), analytical AI (i.e., machine learning), and generative AI (i.e., large language models (LLMs)). It applies the Technology-Organization-Environment (TOE) framework as analytical lens and extends it by incorporating an individual dimension drawn from the UTAUT framework. The analysis reveals distinct patterns. Accounting firms predominantly employ RPA and ML for assurance-driven tasks such as transaction testing, anomaly detection, and regulatory compliance, while non-accounting firms adopt AI largely for predictive financial forecasting and process optimization. Key barriers, including rigid business models in accounting firms and organizational silos in non-accounting firms shape adoption trajectories. This study contributes to the field of accounting and auditing research by offering a nuanced understanding of how organizational context and professional logics uniquely influence AI adoption. It provides actionable insights for academics, practitioners, and policymakers, emphasizing the need for cross-functional collaboration, regulatory frameworks, and AI literacy initiatives to foster effective adoption across diverse sectors.

The journal of business & industrial marketing 41(13) s. 1-10 Doi: https://doi.org/10.1108/JBIM-01-2025-0016

Purpose The purpose of this paper is to discuss when an observed process requires investigation as a network-like phenomenon. The research question is as follows: How does the way of observing a network-like phenomenon impact on what aspects it is possible to shed light on, and conceptualise? Design/methodology/approach The research design is based on the basic characteristics of network-like phenomenon identified in Industrial Network research; non-linearity, connectivity and self-organising. Three types of observation logics are discussed, especially what aspects each can bring forward. A published study is used to illustrate the discussion empirically. Finally, the authors discuss the relation between chosen observation logic, drawing of borders and possibility to conceptualise. Findings The findings stress that each research project concerning a network-like phenomenon should rest on a conscious choice of observation logic; an awareness that network-like phenomena always take place on a network level; and finally, a consciousness that each observation logic can provide clear images of certain – but not all – forces involved. This implies that researching network-like phenomena in general should allow a plurality of ways to observe. Research limitations/implications See above. Practical implications The paper sheds light over the importance of recognising network-like phenomenon; especially how self-organising can be identified and acted on, in processes of significance for businesses, organisations and society at large. Social implications See above. Originality/value The paper draws attention to the fact that behind the commonly used case study research design radically different observations logics might be hiding, with different ability to catch the content and consequences of interactivity, non-linearity and self-organising.

ACM Ubiquity 2026(May) s. 8-8 Doi: https://doi.org/10.1145/3819594

GenAI is coming for the comfortable, not the creative minds Generative AI provides organizations with conversation (an always-on, endlessly patient interface for any simple question), distillation (summarizing vast volumes of text), and fabrication (generating the flood of standard documents and compliance material that modern bureaucracies seem to need). Together, these capabilities can automate "bullshit jobs" while raising the bar for what counts as genuinely original work, as companies rethink how they recruit, train, and create value.

Construction Management and Economics s. 1-17 Doi: https://doi.org/10.1080/01446193.2026.2660109