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The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

Much of the existing research conducted on dynamic capabilities and the microfoundations of innovation has focused either on individual or organizational factors without considering mechanisms. This paper aims to address this “process” gap by developing an integrated conceptual framework based on individual, processual and structural microfoundations as well as the interaction between and among them with respect to innovation.

To understand the theoretical and empirical landscape in building our conceptual model, we conducted a content analysis of existing research microfoundations, dynamic capabilities and innovation. Using NVivo 12, we identified and examined the individual and organizational behavior microfoundations and their interplay to propose possible processual mechanisms. We framed these process mechanisms using the sensing, seizing and reconfiguring dynamic capabilities framework.

The study emphasizes certain microfoundations that facilitate innovation-dynamic capabilities at various organizational levels. It is posited that both formal and informal strategic intelligence processes, along with directed and undirected information research methods, constitute crucial microfoundations for identifying opportunities for innovation. For the internal capture and seizing of these opportunities, we assert that the diversity of individual internal networks and the mechanisms for social integration will prove to be critical. Furthermore, the paper suggests that reconfiguring microfoundations, specifically an organization’s flexible structure and the involvement of external directors with diverse experiences, are pivotal in spurring innovation.

We combine the microfoundations approach (individual, structural and processual) with the dynamic capabilities theory (sensing, seizing and reconfiguring) to offer an integrated conceptual framework underlying innovation’s dynamic capabilities. This sets us apart from existing research by both introducing processual aspects and their multilevel interactions.

How can managers reduce information asymmetry in dyadic manager-external stakeholder relationships in a complex and evolving environment? Addressing this question has significant implications for firm survival, growth, and competitive advantage.

We have adopted a multiparadigm approach to theory building, known as metatriangulation. We integrate the dynamic capabilities, sensemaking, and evolutionary theory literatures to theorize how managers can relate to stakeholders in a complex and evolving environment.

We propose, via a conceptual framework and three propositions, “evolutionary sensemaking” as the managerial metacognitive dynamic capability that helps managers hone their understanding based on the evolutionary changes in the stakeholder’s interpretations of information quality preferences. The framework unfolds across three evolutionary stages: sensing preferences' variation of the stakeholder, seizing preferences, and transforming for complexity alignment and retention. The propositions focus on managing complexity in stakeholder information quality preference, employing cognitive capabilities to simplify, interpret, and align interpretations for effective information asymmetry reduction.

To develop the metacognitive dynamic capability of evolutionary sensemaking, managers need to train for and foster the underlying complex cognitive capabilities by enhancing their (1) perception and attention skills, (2) problem-solving and reasoning skills, and (3) language, communication, and social cognition skills, focusing specifically on reducing the complexity embedded in stakeholder cognition and diverse stakeholder preferences for information quality. Contrary to the current advice to “keep things simple” and provide “more” information to the stakeholders for opportunism reduction, trust-building, and superior governance, our framework suggests that managers hone their cognitive capabilities by learning to deal with the underlying complexity.

The proposed framework and propositions address research gaps in reducing information asymmetry. It enriches the dynamic capabilities literature by recognizing complexity (as opposed to opportunism) as an alternative source of information asymmetry, which needs to be addressed in this stream of research. It extends the sensemaking literature by identifying the complexity sources – i.e. stakeholder preferences for diverse information quality attributes and the associated cognitive preference interpretation processes. The article enhances evolutionary theory by delving into microprocesses related to information asymmetry reduction, which the existing literature does not thoroughly investigate.

The current research has developed a novel method to update the decisions regarding real-time data, named the dynamic adjusted real-time decision-making (DARDEM), for updating the decisions of a grocery supply chain that avoids both frequent modifications of decisions and apathy. The DARDEM method is an integration of unsupervised machine learning and mathematical modeling. This study aims to propose a dynamic proposed a dynamic distribution structure and developed a bi-objective mixed-integer linear program to make distribution decisions along with supplier selection in the supply chain.

The constantly changing environment of the grocery supply chains shows the necessity for dynamic distribution systems. In addition, new disruptive technologies of Industry 4.0, such as the Internet of Things, provide real-time data availability. Under such conditions, updating decisions has a crucial impact on the continued success of the supply chains. Optimization models have traditionally relied on estimated average input parameters, making it challenging to incorporate real-time data into their framework.

The proposed dynamic distribution and DARDEM method are studied in an e-grocery supply chain to minimize the total cost and complexity of the supply chain simultaneously. The proposed dynamic structure outperforms traditional distribution structures in a grocery supply chain, particularly when there is higher demand dispersion. The study showed that the DARDEM solution, the online solution, achieved an average difference of 1.54% compared to the offline solution, the optimal solution obtained in the presence of complete information. Moreover, the proposed method reduced the number of changes in downstream and upstream decisions by 30.32% and 40%, respectively, compared to the shortsighted approach.

Introducing a dynamic distribution structure in the supply chain that can effectively manage the challenges posed by real-time demand data, providing a balance between distribution stability and flexibility. The research develops a bi-objective mixed-integer linear program to make distribution decisions and supplier selections in the supply chain simultaneously. This model helps minimize the total cost and complexity of the e-grocery supply chain, providing valuable insights into decision-making processes. Developing a novel method to determine the status of the supply chain and online decision-making in the supply chain based on real-time data, enhancing the adaptability of the system to changing conditions. Implementing and analyzing the proposed MILP model and the developed real-time decision-making method in a case study in a grocery supply chain.

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.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

With the rise of the gig economy, management positions are increasingly staffed with flexible labor, so-called interim managers. They plunge into organizations for a limited period, operating in a liminal position as partly insider, partly outsider. Although several contributions to their client organizations are acknowledged, it is unknown how the interim manager’s knowledge from previous assignments is made useful in the new context under these particular working conditions. Therefore, the purpose of this paper is to increase the understanding of how the interim manager’s knowledge is transferred to the client organization while operating from a liminal position.

This paper presents an interview-based multiple case study of six interim assignments where knowledge transfer is considered a social and context-dependent process.

The findings unveil the multifaceted nature of the liminal position, which consists of task orientation, time limitation, political detachment and cultural distance. These facets contribute to knowledge transfer in terms of new shared understandings and joint interests, which in turn might create new practices that augment continuous knowledge-sharing patterns.

The results contribute to the research on flexible work arrangements by shedding light on how the liminal position, predominantly depicted as an obstacle for the individual, might facilitate knowledge transfer. Through the process of knowledge generation, it is shown how a short-term engagement might enable the organization to increase its knowledge over time.

Till now no study has been undertaken which test the knowledge management processes for creating dynamic capabilities on the basis of organization structures with interpersonal trust as an important variable. This paper serves as a preliminary study proposing an integrated conceptual model that unmistakably unifies the notions of knowledge management and dynamic capability.

Through an exhaustive literature review, the study explores the role of knowledge management in building dynamic capabilities within the organizations. Through the available literature, authors have attempted to study the relevance of knowledge management against the backdrop of Structuration theory.

Through their proposed framework, authors posit that the structural elements of an organization set the tone for knowledge management within the organization. Organizations face dynamic challenges from the external environment, and in absence of interpersonal trust the creation of dynamic capabilities becomes difficult.

First, the current study enriches the growing research interest in Knowledge management. Second, the study connects Knowledge management and interpersonal trust within the organizations, which in turn is influenced by the structure of the organization. Structures created in the organization decide the direction, quality and quantity of knowledge sharing within the organizations both through social systems and through formal reporting systems. Thus, this paper serves as a preliminary study proposing an integrated conceptual model that unmistakably unifies the notions of knowledge management and dynamic capability.

The rapidly changing international business landscape, driven by dynamic factors such as technology, emerging markets, and unpredictable crises, demands that organizations innovate to survive while gaining and sustaining competitive advantages. Culture, an intricate multilevel construct, presents challenges for transnational enterprises and international business as a key “soft” element of organizational strategy.

This paper employs a triangulated method combining a systematic literature search, machine learning, and qualitative thematic content analysis to explore the relationship between culture and innovation within the context of international business. The analysis involved scrutinizing 697 journal articles indexed in the Web of Science database.

Using k-means, which is an unsupervised machine-learning tool in Python, and hypertext preprocessor language scripting, we identified seven topic clusters and 94 keywords. Qualitative thematic content analysis facilitated the recognition of prevailing patterns in researchers' conceptualizations of the interplay between innovation and culture. We identified influential relationships between cultural configurations and innovation.

Our analysis contributes to developing a comprehensive research field map encompassing international business, innovation, and culture.

This study significantly enhances our knowledge of culture and international innovation. Future research that recognizes culture as a dynamic configuration at multiple levels (e.g. national, organizational, professional, and individual) and employs more comprehensive measures of innovation and culture could substantially advance our understanding of the intersection of culture and innovation in international business.

This study examines the bi-directional relationship between corporate social responsibility disclosure (CSRD) and ownership structure through a dynamic empirical framework in an emerging economy context.

Data over 10 years are used to investigate the response of disclosure to ownership structure variables and vice versa. Dynamic bi-directional relationships are hypothesised and empirically investigated using a panel vector autoregressive (PVAR) model. The ownership structure variables used are government ownership, block ownership and director ownership, while CSRD is constructed as a score through content analysis.

A bi-directional negative relationship between CSRD and government ownership is found, revealing a preference for the state to invest in companies with opaque disclosure. CSRD is found to respond negatively to block ownership, albeit weakly. Results also show that directors prefer to own shares in the company they manage when there are low levels of CSRD.

The current empirical set-up of using a small emerging economy may not carry to the context of larger emerging economies where the institutional context may differ. Thus, future research could use this dynamic empirical approach to re-examine the questions raised in this paper using data from other emerging economies. The use of a longer time series makes it feasible to explore further analysis what was not possible in this study, such as an impulse response analysis examining the reaction of the variables of interest, CSRD and ownership variables for a specific time horizon to particular changes or shocks associated with one of the endogenous variables in the PVAR.

A major implication is that expecting disclosure practices to improve due to government and director initiatives would be less likely in emerging economies. State and director shareholders prefer to invest in opaque companies because they may purposely choose to keep the minimum disclosure levels. The paper calls for a transparent process and ethical guidelines to guide government investment in firms.

The study investigates the bi-directional relationship between ownership structure and CSRD in contrast to the existing literature's presupposed one-way relationship between these variables by demonstrating that bi-directionality does matter. This paper also contributes to the CSRD literature in the emerging economy context. The bi-directional negative relationship between CSRD and government ownership calls for a transparent selection process of board members as representatives of the state in those companies where the government has an ownership stake. It also calls for a transparent process and ethical guidelines to guide government investment in firms.