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This study aims to investigate the importance and effect of asymmetric technological collaborations’ key success factors in developing countries. The number of collaborations between large enterprises and SMEs, known as asymmetric technological collaborations (ATC) is growing considerably. But this asymmetry in itself can increase the number and intensity of collaboration challenges. So far, limited studies have been conducted on the stability of ATCs, and most of them have been in the context of developed countries. Meanwhile, studying the strength and stability of collaboration in the nano industry with growing market value and increasing newcomers is of particular importance.

Here, with bionic engineering approach, we used chemistry for the first time to identify the main stability factors of ATCs and build our hypotheses and research model. To this end, we introduced the factors affecting the stability of the dative chemical bond as a bionic counterpart of corporate venture capital (CVC), which is a type of ATC, and proposed 4 hypotheses. We used structural equation modeling (SEM) with partial least squares (PLS) method to examine the hypothesized relationships.

The analysis of survey questionnaire data from 26 asymmetric collaborations in Iran’s nanotechnology industry shows that “learning of the acceptor company” with a negative effect, “network ties” and “development of the collaboration host region” with a positive effect and “diversity in the collaboration portfolio” with an inverted U-shaped effect are the most influential factors in the stability and continuity of CVCs, respectively.

The findings of this research can be the beginning of a broad path leading to exploring and getting inspiration from chemistry to analyze management issues.

The purpose of the study is to investigate how small- and medium-sized enterprises (SMEs) can effectively collaborate for eco-innovation using the business modes of innovation framework to emphasise three types of collaboration: “science, technology, and innovation” (STI), “learning by doing, using, and interacting” (DUI)-Vertical and DUI-Horizontal.

This analysis uses data from 838 SMEs in the Basque Country (2018–2020) to evaluate the effects of the three types of collaboration on eco-innovation. The authors employ a propensity score-based method to address potential bias associated with endogeneity in innovation studies.

The findings suggest that DUI-Vertical collaboration has a positive relationship with the development of product, process and marketing eco-innovation. Furthermore, DUI-horizontal collaboration is the most effective collaboration mode for SMEs, positively impacting their overall eco-innovation portfolio. Finally, STI collaboration is positively associated with product eco-innovation.

Policymakers should support SMEs by designing programmes that facilitate collaboration between competing firms to stimulate eco-innovation, but potential challenges of coopetition must be addressed. Rather than a generic, one-size-fit-all approach, SMEs' managers should identify the most appropriate partners corresponding to their specific eco-innovation goal, ensuring a more effective and targeted. Collaboration between science partners and SMEs should be reinforced by approximating the SMEs' needs more effectively.

This study contributes twofold. Firstly, the authors investigate whether the STI and DUI modes of innovation are determinant factors in the introduction of various types of eco-innovation. Secondly, the authors contribute to the literature on business modes of innovation by differentiating between DUI-Vertical (i.e. suppliers, customers and consultancy) and DUI-Horizontal (i.e. competitors) collaboration, thus highlighting the complexity of DUI collaboration forms.

As the foundation of social and economic development, infrastructure development projects are characterized by large initial investment, high technical requirements and thus generally delivered through complex contractor–subcontractor collaboration chains. This study aims to characterize the complexity of collaborative networks between contractors and subcontractors for infrastructure development through comparing the structural characteristics and the formation mechanisms of contractor–subcontractor collaborative networks for the following two different types of infrastructure: public works (PWCN) owned and operated by government agencies, and public utilities (PUCN) owned and operated by nongovernment agencies.

Based on the method of stochastic actor-oriented models and the longitudinal dataset of National Quality Award Projects in China during 2001–2020, this study compares how the structural characteristics of project-based collaborative networks between contractors and subcontractors for the two types of projects are different and how related micro-mechanisms, including both structure-based endogenous network effects and attribute-based exogenous homophily effects (institutional, organizational and geographical homophily), collectively underpin the formation of the networks.

The empirical results provide evidence that while the two networks are both characterized by relatively low levels of network density, PWCN is more globally connected around a minority of superconnected contractors as compared with PUCN. The results further reveal that compared with PUCN, the formation of PWCN is more significantly related to the structure-based anti in-isolates effect, suggesting that PWCN is more open for new entrant subcontractors. With regard to the attribute-based homophily effects, the results provide evidence that while both significantly and positively related to the effects of organizational (same company group) and geographical homophily (same location), the formation of PWCN and PUCN is oppositely driven by the institutional homophily effect (same ownership type).

As an exploratory effort of using network perspective to investigate the formation mechanisms of contractor–subcontractor relationships in the infrastructure development domain, this study contributes to a network and self-organizing system view of how contractors select subcontractors in different types of infrastructure projects. The study also provides insights into how contractor–subcontractor collaborative relationships can be better manipulated to promote the development of complex infrastructure in different contexts.

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

This paper aims to provide a deeper understanding of what collaborative leadership in interorganizational systems entails.

The empirical basis consists of the dynamics observed during two behavioral simulations involving seven stakeholders with managers and professionals as participants, dealing with a complex regional development issue.

The authors describe what functions collaborative leadership in multiparty collaboration serve by discussing relevant literature and introducing a system psychodynamic perspective on leadership that focuses on the emerging dynamics between a leading party and other stakeholders. The relational dynamics between the leading party on the one hand and the other stakeholders on the other, are described and interpreted, taking the larger systemic context into account.

The authors discuss some important group dynamics aspects that emerge in a multiparty context that can be used by participants in and facilitators of such complex systems in order to foster effective collaboration.

Multiparty systems are set up to deal with some important societal challenges that require the integration of insights, resources and interests across several organizations and societal actors, therefore this study provides important insights into the complexity of collaborative leadership emergent in such contexts in which position power is lacking.

The study provides a qualitative, in depth analysis of the collaborative leadership as it emerges in a multiparty context simulated by an experiential learning context.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

This research aims to investigate how organisational and contextual factors affect supply chain collaboration and how that, in turn, influences firms' competitive advantage in the garment industry in the context of Vietnam, a developing country.

Following a qualitative research design, in-depth interviews were conducted with senior managers who are involved in supply chain collaboration in twelve garment companies in Vietnam. The data were recorded, transcribed and analysed using NVivo 12. Based on the literature and interview findings, a research model underpinned by the relational view (RV) and institutional theories, with organisational and contextual factors being the antecedents and competitive advantage as the outcome of supply chain collaboration, was proposed.

The findings showed that organisational and contextual factors induce both internal, supplier and customer supply chain collaboration. There is also a positive relationship between supply chain collaboration and competitive advantage. Based on these findings, a strategy matrix for supply chain collaboration is also put forward.

This is one of the first empirical attempts to investigate the role of organisational and contextual factors as potential antecedents of supply chain collaboration and its effects on competitive advantage in the garment industry. The research is expected to enrich both the literature and management practices on supply chain collaboration in the context of developing countries.

Despite the quantity of collaborations, the vocational network of the housing production in Ankara during its first five years (1923–1928) remains dispersed. The aim of this study is to identify all the actors of housing production and their collaborations which shaped Ankara's urban development as the new capital city.

The study engages with the literature and archival documents to identify the actors of the housing production, i.e. architects, master-builders, public institutions, private companies, contractors and entrepreneurs, and their resultant vocational network in the housing production in Ankara during 1923–1928.

Due to different agendas, such as speculation, financial interests or patriotism, the construction industry in Ankara had become an arena where many paths intersected, forming an intertwined vocational network. The profession of contractor became popular, and local architects, engineers and even individuals of various other professions began to work as mediators for foreign companies and public institutions, which required support especially in large-scale projects.

The dispersed information revealed that the actors of the housing production remained mostly anonymous, or only the famous architects were commemorated; however, others could be found within the lines of the established literature on Ankara and/or in archival documents. This research not only focuses on “salient” actors but also highlights the “silent” actors of the housing production and prepares charts to clarify the vocational network in Ankara during its first five years to contribute to the future studies on Ankara and its housing.

It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.

The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.

The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.

The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.

To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.