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This study aims to examine how the legitimacy of internal auditing is reconstructed during enterprise resource planning (ERP)-driven technological change.

The study is based on the comparative analysis of internal auditing and its transformation due to ERP implementations at two case firms operating in the food sector in Egypt – one a major Egyptian multinational corporation (MNC) and the other a major domestic company (DC).

Internal auditors (IAs) at MNC saw ERP implementation as an opportunity to reconstruct the legitimacy of internal auditing work by engaging and partnering with actors involved with the ERP change. In doing so, the IAs acquired system certifications and provided line functions and external auditors with data-driven business insights. The “practical coping mechanism” adopted by the IAs led to the acceptance (and legitimacy) of their work. In contrast, IAs at DC adopted a purposeful strategy of disengaging, blaming and rejecting since they were skeptical of the top management team's (TMT's) sincerity. The “disinterestedness” led to the loss of legitimacy in the eyes of the stakeholders.

The article offers two contributions. First, it extends the literature by highlighting a spectrum of behavior displayed by IAs (coping with impending issues vs strategic purposefulness) during ERP-driven technological change. Second, the article contributes to the literature on legitimacy by highlighting four intertwined micro-processes – participating, socializing, learning and role-forging – that contribute to reconstructing the legitimacy of internal auditing.

The purpose of this paper is to explore how internal auditors’ (IAs) roles have changed because of the diffusion of neoliberal ideologies in the Ukrainian public sector.

A qualitative methodological approach was applied. Data were collected from 29 semi-structured interviews with public sector auditors in Ukraine’s central government; secondary data analysis was also performed.

IAs’ role in Ukraine’s central government has changed significantly, with reforms attempting to move to performance auditing. Consequently, Ukrainian central government IAs appeared in the multi-expectation situation, due to the division of the role senders into two different areas. On one hand, IAs are expected to perform new roles set by the Ministry of Finance of Ukraine, while their traditional role as “watchdogs” is still expected by managers (heads of institutions). Diverging expectations resulted in the role conflict that impedes the change in IAs’ role and performance auditing introduction in the Ukrainian central government. Moreover, we identify factors that motivate IAs to prioritise managers’ expectations, while trying to cope with the existing role conflict in Ukraine’s central government.

This study makes a threefold contribution by enriching the understanding of auditors’ roles, role conflicts that public sector auditors may experience and factors that influence how auditors cope with such conflicts, through the lenses of role theory; exploring the change in roles with the emergence of performance auditing; and shedding light on public sector auditing in the less explored context of a post-Soviet country.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

This paper aims to analyze the ethical responses of the fashion industry to the first wave of the COVID-19 pandemic when the entire world was shocked by the rapid spread of the virus. The authors describe lessons from emergency ethics of care in the fashion industry during the initial months of COVID-19, which can assist fashion managers in improving ethical decisions in future operations.

Rapid qualitative research methods were employed by conducting real-time, in-depth interviews with key informants from multinational fashion companies operating in Spain, a severely affected region. A content analysis of news articles published during the first months of 2020 was conducted.

Five critical disruptions in the fashion industry were identified: (1) changes in public needs, (2) transportation and distribution backlogs, (3) defective and counterfeit supplies, (4) stakeholder relationships at stake and (5) managers' coping challenges. Additionally, five business survival responses with a strong ethics of care component were identified, implemented by some fashion companies to mitigate the damage: (1) adapting production for public well-being, (2) enhancing the flexibility of logistic networks, (3) emphasizing quality and innovation, (4) reinventing stakeholder collaborations and (5) practicing responsible leadership.

Despite the well-documented controversies surrounding unethical practices within the fashion industry, even during COVID-19, our findings inform managers of the potential and capability of fashion companies to operate more responsibly. The lessons learned can guide fashion companies' operations in a post-pandemic society. Furthermore, they can address other grand challenges, such as natural disasters, geopolitical conflicts and climate change.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.