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The purpose of this paper is to evaluate the effectiveness of a policy, the 2014 UK Supply Chain Plan, which aimed to create a local supply chain in a sector (offshore wind) where the central manufacturing node capabilities and knowledge are not possessed locally. It aims to address the following question: can policy create a new manufacturing supply chain from a void?

A qualitative field research approach is used to derive an original set of theoretical propositions explaining the motivation behind the Supply Chain Plan policy. The outcomes of this policy are examined 10 years later in order to provide an opportunity to observe the impact of the policy.

The conclusion is that the policy has been successful in increasing local content, and some of that local content has benefited local manufacturers. However, a lot of the increase in local content has been achieved in non-manufacturing areas or in new areas. The main issue, i.e. the lack of a central manufacturing capability, remains unaddressed. The impact of the local content policy on cost is undocumented.

There is an increasing amount of interest in regional/local supply chains after the COVID-19 pandemic and increasing geopolitical tensions. This paper's originality is to document with an industry case study the fact that manufacturing knowledge and capabilities are the central growth engine of supply chains and that creating a new manufacturing supply chain competing with well-established clusters is not a simple matter that can be achieved through a local content policy. Such policies raise critical questions about the policy makers' implicit valuation of manufacturing technology.

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect the performance of waste classification governance.

Content analysis of the existing waste classification policies is conducted using the Latent Dirichlet Allocation (LDA) model. Based on this analysis, influencing factors are identified through the technology-organization-environment (TOE) research framework. The condition configurations and action paths that cause differences in governance performance are derived using the fuzzy-set qualitative comparative analysis method (fsQCA).

The results show that there are spatial and temporal disparities in waste classification policies among different provinces/cities. In most situations, the implementation effect of policy combinations is better than that of a single type of policy, with mandatory policies playing a key role. Additionally, a single influencing factor cannot constitute the bottleneck of high governance performance. Policy topics coordinate with environmental and technical factors to influence governance performance. Finally, in light of China's actual governance situation, several targeted implications are proposed for the practical optimization of local government waste classification governance.

This paper presents a novel approach by integrating multiple heterogeneous data sources from both online and offline channels, adopting a public-government perspective and applying the fsQCA method to investigate the combined effects of technical, organizational and environmental factors on waste classification governance performance across 31 provinces and cities in China.

This paper aims to provide scholars with a deep understanding of the field through the identification of strengths and weaknesses in the literature and support decision-makers in the development of new practices in local risk management based on scientific data. The specific question in this review asks: what are the drivers and barriers to local risk management?

This paper provides an overview of the scientific literature produce over the past 20 years of the divers and barriers to local risk management. This paper presents a scoping review of peer-reviewed articles published between 2000 and 2019 inclusively in the fields of public policy and public administration.

This paper makes three main observations regarding the state of the literature. First, this paper finds that scholars mainly focus on single risk and certain regions of the world. Second, there is multiple approached used by the literature to study risk management at the local level. Third, little attention is given to the political context in which local risk management takes place.

This paper is a complete literature review of more than 500 peer-reviewed articles published in academic journals regarding risk prevention policies over the past two decades. This paper analyzed the main findings of the current literature to provide a general view of the scholarship and improve the collective understanding of risk management at the local level by providing future research avenues.

This study aims to investigate the adoption of the United Nations’ Sustainable Development Goals (SDGs) as the new performance perspective in cities. It also aims to understand how accounting for SDGs begins in city administrations by following Power’s (2015) fourfold development schema composed of policy object formation, object elaboration, activity orchestration and practice stabilization.

Focusing on a network of cities coordinated by the Finnish local government association, we analyzed the six largest cities in Finland employing a holistic multiple case study strategy. Our data consisted of Voluntary Local Reviews (VLRs), city strategies, budget plans, financial statements, as well as results of participant observations and semi-structured interviews with key individuals involved in accounting for SDGs.

We unveiled the SDG framework as an interpretive scheme through which cities glocalized sustainable development as a novel, simultaneously global and local, performance object. Integration of the new accounts in city management is necessary for these accounts to take life in steering the actions. By creating meaningful alignment and the ability to impact managerial practices, SDGs and VLRs have the potential to influence local actions. Our results indicate further institutionalization progress of sustainability as a performance object through SDG-focused work.

While prior research has focused mainly on general factors influencing the integration of the sustainability agenda, this study provides a novel perspective by capturing the process and demonstrating empirically how new accounts on SDGs are introduced and deployed in the strategic planning and management of local governments.

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.

This study evaluates how well Victorian local councils’ procurement policies align with the sustainable and circular economy (CE) approach that prioritises sustainable and regenerative practices. It proposes a set of criteria designed to effectively integrate environmental sustainability issues into purchasing policies.

Employing the Specific, Measurable, Assignable, Realistic and Time-bound (SMART) framework, a multi-dimensional content analysis guided by the goal-setting theory was applied to evaluate all 79 Victorian local councils’ procurement policies. This approach provided an assessment of policy specificity, measurability, assignability, realism and time sensitivity in promoting environmental sustainability through purchasing policies.

The findings underscored a significant deficiency in policy adherence to all SMART criteria concerning environmental sustainability, hindering the effective green purchasing decisions within government entities. This lack of integration of greening in purchasing policy poses challenges for manufacturers of waste-derived goods, obscuring the procurement objectives of these critical public sector customers.

The paper contributes to the sustainable procurement (SP) discourse by proposing guidelines aimed at improving the efficacy of governmental purchasing of sustainable products. These guidelines address the broader imperative to mitigate the environmental impacts of governmental spending on less sustainable goods, thereby fostering ecological sustainability and promoting responsible consumption.

While past studies have often relied on subjective content analysis methods, the SMART assessment used to develop the environmental sustainability criteria for purchasing policies, which distinguishes this study from previous governmental policy evaluation studies. This approach marks a departure from traditional governmental policy evaluation studies, offering a more structured analysis of policy effectiveness in promoting SP practices.

The purpose of the study is to propose a new perspective to explain how China's rapid growth in patenting is partially driven by corporate strategic patenting to influence local governments. The authors highlight the role of strategic patenting and local government-business relations in creating the gap between the patent boom and underlying technological progress in China.

The authors investigate the relationship between local government-business relations and corporate strategic patenting behaviors, measured as a higher ratio of patent filings to patent awards, by collecting data from three successive NADS surveys of government-business relations in 292 Chinese municipalities, paired with detailed patenting and subsidy data of 3,756 publicly listed corporations obtained through text mining.

The authors find that, while R&D investment and patent subsidies do drive corporate patenting, firms in jurisdictions with lower-quality government-business relations are more likely to engage in strategic patenting. Moreover, the negative impact of government-business relations on strategic patenting is moderated by political connections, as the strategic patenting of firms without political connections is more sensitive to government-business relations. The authors further show that firms obtain significant benefits from patenting in the form of additional subsidies from local innovation and industrial policies in the years following.

Rolling back patent subsidies will reduce strategic patenting to a limited extent. The local governments in emerging markets need to increase the capacity to implement industrial policy and provide market-based opportunities for firms to access innovation inputs.

The authors provide an updated and fresh perspective to understand the phenomenon of China's patent boom by showing that patenting can be driven by corporate strategies to adapt to local institutions and influence government policy. The authors extend the analysis of strategic patenting to emerging markets.

The purpose of this paper is to define the local integration rate and how it is calculated to assess its relevance as a national performance indicator for the Moroccan automotive industry.

The research methodology first followed a systematic review approach through the analysis of published research articles and academic works. This study then followed a qualitative approach based on semi-structured interviews with various actors in the Moroccan automotive industry. Finally, the findings of this work were reinforced by a case study to analyze the supply chain of a locally produced vehicle.

The results indicate that the local integration rate as calculated today overestimates the performance of the automotive industry and does not systematically guarantee a significant creation of value added.

Due to the confidentiality of the data in terms of turnover, payroll and purchase prices as well as the large number of suppliers in the different supply chains of the car manufacturer, the case study focused on only one of the six existing ecosystems.

On the basis of research work on the Moroccan automotive industry as well as interviews with various actors, the local integration rate is unanimously considered as a viable performance indicator. This study has not only led us to the method of calculating this rate by the Ministry of Industry but also demonstrated its limitations while proposing a new method of calculation to increase the value added.

This paper aims to understand how the global supply chain in the medical device industry embraces resilience by adopting agility approach following COVID-19.

This study adopts an interpretative approach to examine the qualitative data drawn from interviews and observation under dynamic capability theory. The data collection concerned multiple stakeholders involved in purchasing and supply management in the medical device market: manufacturing suppliers, channel partners, hospital management and end-users. The coding analysis uses an application that helps the researchers categorise the nodes and extend the existing literature.

The findings show that global supply chain leaders leverage the dynamic capability by centralising the business process decision to respond to the shifting demand from the local governments to the national health ministry, shaping the partnership style from the area- to the funnel-based agreement, even though it exposes a risk of product acceptability from the end-users, encouraging the distributor to convert just-in-time approach into holding safety stock to avoid penalty from missing the procurement target even and restructuring the local partners’ debts to manage long-term performance.

This study extends the emerging literature in international business by underpinning dynamic capability theory.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.