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Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

Systemic risk is of concern for economic welfare as it can lower the credit supply to all the sectors within an economy. This study examines for the first time the complete hierarchy of variables that drive systemic risk during normal and crisis periods in Pakistan, a developing economy.

Secondary data of the bank, sector and country variables are used for the purpose of the analysis spanning from 2000 to 2020. Systemic risk is computed using marginal expected shortfall (MES). One-step and two-step system GMM is performed to estimate the impact of firm, sector and country-level variables on systemic risk.

The findings of the study highlight that sector-level variables are also highly significant in explaining the systemic risk dynamics along with bank and country-level variables. In addition, economic sensitivity influences the significance level of variables across crisis and post-crisis periods and modifies the direction of relationships in some instances.

The study examines the systemic risk of a developing economy, and findings may not be generalizable to developed economies.

The outcome of the study provides a comprehensive framework for the central bank and other regulatory authorities that can be translated into timely policies to avoid systemic financial crisis.

The negative externalities generated by systemic risk also affect the general public. The study results can be used to avoid the systemic financial crisis and resultantly save the loss of the general public's hard-earned holdings.

The firm, sector and country-level variables are modeled for the first time to estimate systemic risk across different economic conditions in a developing economy, Pakistan. The study can also act as a reference for researchers in developed economies as well regarding the role of sector-level variables in explaining systemic risk.

This research examines the impact of integrating lean manufacturing (LM) principles and Industry 4.0 (I4.0) into the product development process (PDP) of manufacturing companies in southern Brazil, with the objective of improving market performance (MP).

A survey was conducted with 110 product development managers to evaluate the level of LM and I4.0 principles, PDP phases, and the improvement of MP. Quantitative analysis was employed to analyse the data, including confirmatory factor analysis (CFA) and ordinary least squares (OLS) hierarchical regression.

The study reveals that integrating LM and I4.0 principles in the PDP enhances product development and positively impacts the MP of manufacturing companies. Additionally, I4.0 partially mediates the LM-PDP relationship, while LM partially mediates the I4.0-PDP relationship, highlighting their interdependence rather than one being a prerequisite for the other.

The study has limitations regarding its narrow focus on product development managers in Brazil and the absence of multiple case studies.

The study emphasises the importance of coordinated efforts in manufacturing companies to adopt and manage both LM and I4.0 principles, as they positively impact all phases of the PDP and ultimately contribute to the overall MP of the companies.

The novelty of this study lies in its systemic approach, examining the relationships and effects of LM and I4.0 principles on the PDP, and demonstrating how these effects manifest in manufacturing companies.

This research aims to examine the challenges of recruiting participatory action research (PAR) in managing innovation projects. An enhanced methodology based on PAR was developed to mitigate the challenges related to recruiting PAR in managing innovation projects. The proposed methodology was evaluated by comparing it to established methodologies/frameworks such as Scrum, Design Thinking (DT) and The Lean Startup (TLS). The evaluation aimed to determine the advantages and limitations of the proposed methodology in managing innovation projects.

The proposed enhanced methodology consists of eight steps, ranging from developing an understanding of the industry and business structure to learning and knowledge management. In addition, the enhanced methodology uses other techniques, such as Force field analysis and 12 boundary questions.

The research findings indicate that using the proposed methodology can improve the formalization of collaboration in PAR, enabling the organization to respond better to market changes. It helps define the project scope more clearly, encouraging innovation, addressing communication barriers and considering different worldviews and practical issues. Based on the findings, the proposed enhanced methodology could complement other methodologies/frameworks such as Scrum, DT and TLS.

The current research adds to the existing literature by identifying the challenges of recruiting PAR in managing innovation projects. A deductive reasoning process was utilized because there is no comprehensive research concerning the challenges of recruiting PAR in managing innovation projects. On the other hand, the PAR 4-phase cycle has been reviewed and enhanced to manage innovation projects.

The proposed methodology was used in a new product development project. The case study was done on one of the payment service provider companies that design, develop and deploy a digital product for marketing, installation, repair and maintenance of electronic funds transfer at point of sale devices.

No research has yet sought to identify the challenges of using PAR in innovation project management (IPM). Identifying the challenges associated with applying PAR in the IPM and providing an enhanced methodology to mitigate the challenges could fill a gap in IPM studies.

People with intellectual disability die prematurely and from avoidable causes. Innovative solutions and proactive strategies have been limited in addressing this disparity. This paper aims to detail the process of developing a risk stratification tool to identify those individuals who are higher risk of premature mortality.

This study used population health management principles to conceptualise a risk stratification tool for avoidable deaths in people with intellectual disability. A review of the literature examined the existing evidence of causes of death in people with intellectual disability. A qualitative methodology using focused groups of specialist clinicians was used to understand the factors that contributed towards avoidable deaths in people with intellectual disability. Delphi groups were used for consensus on the variables for inclusion in the risk stratification tool (Decision Support Tool for Physical Health).

A pilot of the Decision Support Tool for Physical Health within specialist intellectual disability service demonstrated effective utility and acceptability in clinical practice. The tool has also demonstrated good face and construct validity. A further study is currently being completed to examine concurrent and predictive validity of the tool.

To the best of the authors’ knowledge, this is the only study that has used a systematic approach to designing a risk stratification tool for identifying premature mortality in people with intellectual disability. The Decision Support Tool for Physical Health in clinical practice aims to guide clinical responses and prioritise those identified as at higher risk of avoidable deaths.

Engaging with customers and addressing unmet value have become increasingly challenging within multi-stakeholder environments of service innovation. Therefore, this paper aims to address this challenge by studying how strategic design abilities address unmet value in service engagement strategies.

The authors conducted a qualitative inductive study at a multinational corporation and interviewed marketing and design professionals on their innovation practices in service engagement strategies.

From the inductive analysis, this study identified three strategic design abilities that effectively contribute to addressing unmet value throughout the co-evolving process of service engagement: envisioning value, modelling value and engaging value. Based on this, this study proposes the emerging co-evolving loop framework of service engagement strategies.

The limitation of this emerging theory is a lack of broad generalizability with mutual exclusivity or collective exhaustiveness across industries. A theoretical implication of the framework is the integration of strategic design and services marketing towards co-created engagement strategies.

The service engagement loop framework can be of great value to service innovation processes, for which an integrated, cross-functional approach is often missing.

The findings further suggest that next to a methodological skillset, strategic design abilities consist of a distinct mindset.

This paper introduces strategic design abilities to address unmet value and proposes a novel co-evolving loop framework of service engagement strategies.

Sustainability is increasingly at the forefront of the public debate in Europe and the world. However, despite this increased interest, research seems to have partially ignored the importance of its social dimension and the issues related to social equity, people care, protection and personal development at all stages of society and, consequently, of business. Accordingly, this paper aims at investigating the “soft” dimensions of sustainability, integrating its mainstream “technical storyline” with a “human/social storyline”.

In this paper a taxonomy of the main key drivers of the soft dimension of sustainability is proposed and tested on a sample of Italian companies. Through interviews with their managers, actions and needs in terms of sustainability soft drivers are identified.

The achieved results demonstrated that the case companies differently integrated the soft dimensions of sustainability within their companies. All the sample companies are aware of the role of social sustainability. According to the proposed taxonomy, the systemic drivers of soft sustainability are the main shared ones.

The paper provides new insights into the essence of the organizational soft dimensions and their centrality in the overall achievement of sustainability for companies. It also offers managerial insights into how to effectively manage these dimensions and policy implications about the need for clearer consideration.

This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.

The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.

The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.

This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.

The purpose of this paper is to examine Asian Americans' perceptions of the police, specifically how they construct support. Although such literature has been growing in recent years, research on Asian American interactions with the police remains limited. Additionally, this paper is situated within the theoretical framework of system justification theory to account for Asian Americans' views of the police.

This study relies on interview data collected from 20 Asian Americans residing in mid-Atlantic states. Participants were either recruited directly by the researchers or through the snowball-sampling method.

Police support is influenced by perception of neighborhood safety, personal police contact and empathetic feelings toward the police. Specifically, regarding the latter component, humanizing or empathizing with police officers is a form of rationalizing individual police misconduct that reinforced police legitimacy. Most participants had similar characteristics and displayed police justification. Additional research is needed regarding what characteristics or patterns are likely to lead to lower levels of police justification.

This article's findings improve our understanding of system justification among Asian Americans, particularly as it relates to policing.

Industry 4.0 defines the application of digital technologies on business infrastructure and processes. With the increasing need to take into account the social and environmental impact of technologies, the concept of Society 5.0 has been proposed to restore the centrality of humans in the proper utilization of technology for the exploitation of innovation opportunities. Despite the identification of humans, resilience and sustainability as the key dimensions of Society 5.0, the definition of the key factors that can enable Innovation in the light of 5.0 principles has not been yet assessed.

An SLR, followed by a content analysis of results and a clustering of the main topics, is performed to (1) identify the key domains and dimensions of the Industry 5.0 paradigm; (2) understand their impact on Innovation 5.0; (3) discuss and reflect on the resulting implications for research, managerial practices and the policy-making process.

The findings allow the elaboration of a multileveled framework to redefine Innovation through the 5.0 paradigm by advancing the need to integrate ICT and technology (Industry 5.0) with the human-centric, social and knowledge-based dimensions (Society 5.0).

The study detects guidelines for managers, entrepreneurs and policy-makers in the adoption of effective strategies to promote human resources and knowledge management for the attainment of multiple innovation outcomes (from technological to data-driven and societal innovation).