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The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

The purpose of this paper is to examine the relationship between an individual's social capital context and entrepreneurship using a multi-level modelling framework.

This paper uses data from 87,007 individual level observations across 428 regions in 37 countries. The data comes from the 2010 and 2016 Life in Transition Surveys. The paper uses a principal component analysis to identify the different dimensions of an individual's social capital context. Subsequently, a multi-level model is employed examining the relationship between the components of an individual's social capital context and entrepreneurship (which is proxied by an individual's attempt to set up a business), whilst controlling for both country and regional effects.

Greater levels of networking, informal connections and tolerance of others have a significant positive relationship with entrepreneurial activity. Trust of institutions and others have a negative relationship with entrepreneurial activity. Regional and country differences are also important for entrepreneurship, demonstrating the importance of the multi-level and social contextual environment for business development.

Firstly, the authors present a broad, but comprehensive social contextual framework incorporating many measures of social capital when examining the importance of social capital for business development. Secondly, the work provides interesting results on the “bright and dark sides of trust” for entrepreneurship, answering calls for improved understandings on the positive and negative relationships between social capital and entrepreneurial activity. Thirdly, the paper extends the burgeoning but limited number of studies that examine the multi-level contextual environment of entrepreneurial activities.

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

The purpose of this study is to examine how five different multi-level governance (MLG) models affect place branding (PB) performance in Saudi Arabia.

In hierarchical administrative systems, central governments exert control on PB, influencing its effectiveness. While PB as such is widely studied, the effect of MLG on PB performance in centralized administrative systems remains understudied. The study is approached as a multiple case study of nine cities.

The study reveals that different MLG models indeed affect PB performance differently. Direct access to central leadership and resources boosts branding performance, while privatization promotes flexibility with similarly positive effects. Study findings, furthermore, show that some cities are considered too big to fail. Cities such as Riyadh and Neom are of prime importance and receive plenty of resources and leadership attention, while others are considered peripheral, are under-resourced and branding performance suffers accordingly. Emerging differences in PB performance associated with different MLG models are thus likely to deepen the gap between urban economic winners and losers.

This paper introduces five MLG models based on the actors involved in PB, their interactions and their access to resources. For each model, this paper assesses other factors which may influence the effectiveness of PB as well, such as access to the national leadership and staff capacity. This research thereby adds to the literature by identifying specific factors within MLG models influencing PB performance in hierarchical administrative systems.

The purpose of this paper is to make a conceptual argument for considering interactive work – i.e. work made up of micro-level exchanges or social interactions with third parties such as customers, patients or citizens – as a distinct analytical category in employment-related research. The argument is underpinned by the core role played by interactive work in valorisation.

This is a conceptual paper, with its argument based on key findings from the debates on symbolic interactionism, service work and interaction work. These are merged and combined with a valorisation perspective.

“Social interactions” and “work” have mostly been considered separately by theoretical sociology and the sociology of work. The author contends however that the two concepts should be viewed together, as social interactions at work are a constitutive feature of many occupations, jobs and tasks. This implies studying both exchange and social relationships between the different parties and their embeddedness in specific (multi-level) contexts. Moreover, there are two reasons why interactive work relates to specific working conditions: first, it involves customers or similar groups as third parties; second, it is key to valorisation. To systematically study interactive work, context-sensitive approaches spanning multiple (analytical) levels are recommended.

The article contributes to advancing the understanding of interactive work as a distinct form of work as yet under-theorised but deserving to be considered as a separate analytical category.

This qualitative study explores how multinational enterprises (MNEs) approach sustainable innovation through the lens of innovation theory and doughnut economics. The study proposes a conceptual framework to evaluate the practices of businesses and the findings illustrate how sustainable innovation occurs within two MNEs. Based on interviews with professionals of two Swedish MNEs, responsible for sustainability, the study examines how sustainable innovations lead to the redesign of core business pillars and transforms the operating market for the MNE. Overall, this study makes a theoretical contribution by formulating an application of Raworth’s (2017) doughnut model to business strategy. It also provides practical insight into the dynamics of sustainable innovation, which aims to inform and inspire further progress in sustainable development by businesses and academia.

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.

The purpose of this paper is to elaborate on how perspectives and assumptions embedded in the complexity paradigm contribute to make logistics management research better aligned with real-life logistics. This is necessary, due to increasing supply chain complexity caused by an increasing request for sustainable development (SD).

The research is exploratory and based on a narrative literature review of logistics and supply chain management (SCM) from a complexity science perspective. Qualitative research interviews have been conducted with 12 logistics and supply chain managers in international companies and have focussed on their daily experiences and the underlying assumptions related to their actual work.

Logistics and SCM research is embedded in the functionalistic paradigm with reductionistic assumptions as the dominant logic. These do not sufficiently align with the complexity related, for example, to the daily work of SD in logistics management practice.

It is proposed that the inclusion of complexity-based assumptions in logistics management research can increase realism in the advancement of the discipline. A key result is that the recognition of logistics as complex means inclusion of human and social aspects – which is apparent in any logistics process or phenomenon – in logistics knowledge creation processes.

Increased realism in logistics management research by addressing complexity, instead of merely reducing it, will provide logistics and supply chain managers with increased understanding and appropriate knowledge when they deal with emerging challenges such as SD.

Based on Boulding’s levels of complexity, this paper challenges the underlying assumptions of logistics management in research and practice, and provides reflective frameworks for advancing the discipline and aligning it to the complexity of contemporary challenges in logistics management.