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The paper frames modern slavery as a global wicked problem and aims to provide a set of international business (IB) policy recommendations for taming it. The outlined approach can also guide IB policymaking to address other kinds of wicked problems.

This is a conceptual paper that reviews existing literature on wicked problems and integrates it with an IB policy double helix framework. The paper focuseses on the role multinational enterprises (MNEs) play in moderl slavery globally, either through global value chains or within global factory modes of operation.

As a global wicked problem, modern slavery will never be solved, but it can be re-solved time and time over. Understanding the social reproduction of modern slavery can help shift the focus from labor governance and a narrow supply chain focus toward the role of transnational governance and the need to address institutional, market and organizational failures.

The paper contributes to the gap in an overarching theory of modern slavery and systematically applies the concept of wicked problems and wickedness theory to modern slavery. Drawing on an IB policy double helix framework, the paper addresses the governance nexus between modern slavery, IB and policymaking which can in turn advance IB policy research and theory.

This study aims to critically discuss and reorient the diversity, equity and inclusion (DEI) debate toward the idea of addressing and rectifying the pervasive structural inequalities that DEI, in its undiluted form rooted in social justice (SJ), aims to combat. Drawing on Bourdieu, the study first examines the diffusion and contestation of DEI into international business (IB). It then proposes a Bourdieu-inspired agenda to advance the transposition of SJ principles into IB.

The study interpretively reconstructs the process of DEI’s ideational diffusion. It examines how the interplay between ideas and field dynamics in IB shapes ideational processes and outcomes.

In response to rising global inequalities – to which multinational enterprises (MNEs) have significantly contributed – SJ movements have propelled DEI into the wider social and political arena, including corporate boardrooms. Within IB, a diluted version of DEI – IB-DEI – emerged as a paradigm to improve MNEs’ performance, but failed to address underlying structural inequalities. As the social impacts, utility and legitimacy of DEI have been challenged, the DEI debate has come to a flux. The study proposes conceptual and contextual extension of DEI within IB and advancing socially engaged research and practice that help reinforce DEI’s core SJ purpose – tackling structural inequalities.

The study is one of the few to openly tackle SJ-IB contradictions on DEI, while advancing the application of Bourdieu to critical studies of IB.

The purpose of this study is to uncover the essential conditions for establishing a successful collaboration between the Fairmont Hotel (Makkah) staff and the senior management team to prepare for cocreating a future shared corporate vision.

This study is an action research project involving senior managers of the Fairmont Hotel (Makkah) and EHL Hospitality Business School (Lausanne, Switzerland). Data were collected from 16 hotel staff members, covering functional/department managers, team leaders, operations supervisors and operational-level employees.

This study uncovered a series of generic proposals made by the hotel staff, which are prerequisites/conditions for successful collaboration with senior management, to prepare for cocreating a future shared vision.

In response to the staff’s generic proposals, the senior management team proposed practical measures to support continued collaboration between hotel staff and the senior management team. These measures aim to maintain a collaborative approach centered on achieving future common goals and a shared vision to promote sustainable innovation in the services of the Fairmont Hotel (Makkah).

This study is innovative in two respects. First, it demonstrates a strong willingness on the part of senior management and staff to collaborate less vertically, contrary to the cultural norm in Saudi Arabia, known for its strong hierarchical distance. Second, the mutual commitment to more horizontal collaboration is not typical of five-star hotels, which are traditionally vertical and hierarchical.

Exposure to indoor air pollutants poses a significant health risk, contributing to various ailments such as respiratory and cardiovascular diseases. These unhealthy consequences are specifically alarming for athletes during exercise due to their higher respiratory rate. Therefore, studying, predicting and curtailing exposure to indoor air contaminants during athletic activities is essential for fitness facilities. The objective of this study is to develop a neural network model designed for predicting optimal (in terms of health) occupancy intervals using monitored indoor air quality (IAQ) data.

This research study presents an innovative approach employing a long short-term memory (LSTM) recurrent neural network (RNN) to determine optimal occupancy intervals for ensuring the safety and well-being of occupants. The dataset was collected over a 3-month monitoring campaign, encompassing 15 meteorological and indoor environmental parameters monitored. All the parameters were monitored in 5-min intervals, resulting in a total of 77,520 data points. The dataset collection parameters included the building’s ventilation methods as well as the level of occupancy. Initial preprocessing involved computing the correlation matrix and identifying highly correlated variables to serve as inputs for the LSTM network model.

The findings underscore the efficacy of the proposed artificial intelligence model in forecasting indoor conditions, yielding highly specific predicted time slots. Using the training dataset and established threshold values, the model effectively identifies benign periods for occupancy. Validation of the predicted time slots is conducted utilizing features chosen from the correlation matrix and their corresponding standard ranges. Essentially, this process determines the ratio of recommended to non-recommended timing intervals.

Humans do not have the capacity to process this data and make such a relevant decision, though the complexity of the parameters of IAQ imposes significant barriers to human decision-making, artificial intelligence and machine learning systems, which are different. Present research utilizing multilayer perceptron (MLP) and LSTM algorithms for evaluating indoor air pollution levels lacks the capability to predict specific time slots. This study aims to fill this gap in evaluation methodologies. Therefore, the utilized LSTM-RNN model can provide a day-ahead prediction of indoor air pollutants, making its competency far beyond the human being’s and regular sensors' capacities.

This study aims to investigate the connection between the circular economy and sustainable operations management to identify the challenges and opportunities in platform organizations. The study looks at how the stated circular economy strategies (Reduce, Reuse, Repair, Refurbish, Repurpose and Recycle) are integrated across different industries, emphasizing how they align with the e-business model. The research evaluates their contribution to achieving Sustainable Development Goal 12, which focuses on responsible consumption and production.

A literature review has analyzed CE frameworks, business models and the role of sustainable operations management practices. This study utilized secondary data analysis of platform organizations and insights from case studies to identify patterns, strategies and outcomes. The study also involved practical examinations within organizations, specifically focusing on innovative start-ups.

The analysis uses the 6R framework (Reduce, Reuse, Repair, Refurbish, Repurpose and Recycle) to uncover valuable insights into organizational practices and highlight the role of platform organizations in promoting and achieving circular economy objectives. The research findings focus on the central importance of data regulation and governance while showcasing sustainable business practices through platform organizations.

This research is significant as it connects circular economy with platform organizations’ business models, emphasizing data regulation, resource efficiency, waste reduction and aligning business practices with Sustainable Development Goal 12.