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The purpose of this paper is to investigate the impact of two dimensions of technological relatedness, namely technological similarity and complementarity, on collaborative performance, plus the mediating role of collaboration network stickiness and the moderating role of partner expertise and geographical distance in interfirm collaboration contexts.

This study takes Chinese Scientific and Technological Achievements (STA) of inter-firm collaboration in five high-tech fields in 2010–2020 as the sample and uses OLS regression to test the hypothesis.

Technological similarity and complementarity positively affect collaborative performance. Partner expertise negatively moderates the relationship between similarity, complementarity and collaborative performance. Geographical distance positively moderates the relationship between similarity and collaborative performance while negatively moderates that between complementarity and collaborative performance. Collaboration network stickiness partly mediates the relationship between similarity and collaborative performance.

This study expands literature on inter-firm collaboration, especially research on the antecedents of collaborative performance. Moreover, this study not only compensates for lack of empirical analysis in partner selection research, but also utilizes second-hand data to enhance the objectivity of analysis. Additionally, we enrich the research on the moderating role of partner expertise and geographical distance as well as the mediating role of collaboration network stickiness.

Research in the business-to-business (B2B) and user entrepreneurship literature agrees that “user-driven” perspectives allow entrepreneurs to develop innovative products superior to conventional products. Other researchers argue that such “user-driven” products have limited success and limited impact in certain markets (e.g. niche and industrial markets). This study aims to understand the extent to which user input or co-creation becomes critical in determining product performance.

The key informant approach is used for data collection. Data were collected using a survey instrument via an online panel. Existing scales are used to measure all the focal constructs. Partial least square-based structural equation modeling was used to check for the psychometric properties of the scales and test the hypotheses.

The results indicate that user entrepreneurship is significantly related to firm collaboration efforts and customer collaboration efforts in the B2B market. Both firm collaboration efforts and customer collaboration efforts are significantly related to product performance and mediate the relationship between user entrepreneurship and product performance. Also, findings show that there is an “n” relationship between firm collaboration efforts and product performance.

This study supports the concerns raised by researchers about the dark side of value co-creation and highlights that value co-creation can impede product performance when user entrepreneurs lay too much emphasis on the collaboration processes.

Supply chain collaboration (SCC) is an important element that contributes to enhanced performance. Nonetheless, there is still a need to understand its role in servitization implementation and outcomes. This study aims to address this gap by looking at the impact of SCC on servitization and performance when considering service levels (base, intermediate and advanced).

Following a quantitative research design, data were collected from firms in pharmaceutical sector.

Moderation effects were tested. Results suggest that SCC is a crucial moderator when it comes to the influence of service levels on servitization consequences and performance, particularly to advanced and intermediate services.

This study contributes to the literature by providing further empirical evidence of the impact of intermediate and advanced services shedding light into the moderating role of SCC.

Inter-organizational collaboration is the organizational guarantee and key link to achieve the goals of megaproject management. Project governance has always played an important role in the construction of megaprojects, but the relationship between project governance and organizational collaboration is unclear. The purpose of this study is to explore the role paths of different project governance mechanisms in influencing the collaborative behaviors of stakeholders and collaborative performance and to elucidate the mechanism of project governance on inter-organizational collaboration.

A conceptual framework was developed based on a comprehensive literature review, termed the structural equation model (SEM). The hypotheses of the model were tested based on data obtained from a questionnaire survey of 235 experts with experience in megaprojects within the construction industry in China.

The results show that project governance positively contributes to the collaborative behavior of megaproject stakeholders and the collaborative performance of the project team. Collaborative behavior acts as a partial mediator between project governance and the collaborative performance of the megaproject inter-organization alliance. The complexity of the project modulates the relationship between the governance mechanism of the project and the collaborative behavior of the stakeholders, which affects the collaborative performance of the megaproject inter-organization alliance.

The findings provide theoretical and practical implications for promoting positive collaborative behavior among stakeholders in megaproject selection and improving the collaborative performance of megaproject inter-organization alliances.

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.

This study assesses how the transactive memory systems (TMS) framework extends to cross-organizational ties. This research also treats TMS dimensions (i.e. knowledge specialization, coordination and trust) as distinct variables, each with unique contributions toward innovation.

This study used a survey to collect data. Out of the 140 Fintech firms registered with OJK in Indonesia in 2021, 101 firms responded to the invitation to participate in the survey. Structural equation modeling was used to analyze the data.

The authors find evidence that collaborating with partners displaying high knowledge specialization leads to radical innovation, while low knowledge specialization collaborations lead to incremental innovation. Both relationships are moderated by the level of coordination and trust between collaborating partners, underlining the impact of TMS on the cross-organizational collaboration aspect. Finally, while incremental innovation leads to higher performance, radical innovation does not enhance performance in the short term.

This study explains how Fintech peer-to-peer lending firms' proficiency in pursuing innovation depends on their liaison with the collaborative partners.

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.

This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A theoretical framework shows the relationship between artificial intelligence, supply chain resilience strategy and firm performance.

A questionnaire is developed to survey the MSMEs of India. A sample size of 307 is considered for the survey. The employees working in MSMEs are targeted responses. The conceptual model developed is tested empirically.

The study found that eight hypotheses were accepted and two were rejected. There are five mediating variables in the current study. Artificial intelligence, the independent variable, positively affects all five mediators. Then, according to the survey and analysis of the final 307 responses from MSMEs, the mediating variables significantly impact the dependent variable, firm performance.

This study is limited to emerging markets only. Also this study used only cross sectional data collection methods.

This study is essential for supply chain managers and top management willing to adopt the latest technology in their organisation or firmfor a better efficient supply chain process.

This study investigated artificial intelligence-based supply chain resilience for improving firm performance in emerging countries like India. This study tried to fill the research gap in artificial intelligence and supply chain resilience.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

The study research aims to examine the effects of supply chain management practices on risk mitigating (RM) by studying the correlation between social ties, institutional support, interagency cooperation and external flexibility in public healthcare sectors. Moreover, this research examines the impact of RM on supplier trust, and also the authors examine the relationship among supplier trust and logistics performance.

The authors used a structural equation model (SEM) based on 539 quantitative data from Ethiopian healthcare organizations. The model included control variables like company size and position to understand better how employees perceive risk mitigation.

The study's findings indicate that interagency collaboration and external flexibility positively affects RM. On the other hand, RM positively impacts supplier trust and also the supplier trust has a positive effects on performance dimensions. This study also shows that RM has not positively impacting institutional support and social ties.

The study investigation may help the pharmaceutical industry, healthcare service SC agencies and other stakeholders better understand the effects of supply chain management practices on RM and obtain information on progress made thus far.

This research helps managers and their organizations to manage the risk associated with their organizations. Though, this study focuses on Ethiopian healthcare SCM. The authors expect the findings might apply to other countries organizations with comparable demographic or SCM features.