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Collegiality is the modus operandi of universities. Collegiality is central to academic freedom and scientific quality. In this way, collegiality also contributes to the good functioning of universities’ contribution to society and democracy. In this concluding paper of the special issue on collegiality, we summarize the main findings and takeaways from our collective studies. We summarize the main challenges and contestations to collegiality and to universities, but also document lines of resistance, activation, and maintenance. We depict varieties of collegiality and conclude by emphasizing that future research needs to be based on an appreciation of this variation. We argue that it is essential to incorporate such a variation-sensitive perspective into discussions on academic freedom and scientific quality and highlight themes surfaced by the different studies that remain under-explored in extant literature: institutional trust, field-level studies of collegiality, and collegiality and communication. Finally, we offer some remarks on methodological and theoretical implications of this research and conclude by summarizing our research agenda in a list of themes.

In this paper, the authors aim to introduce international dynamic marketing capabilities (IDMCs) theoretically derived from marketing capabilities (MCs), dynamic marketing capabilities (DMCs) and international marketing capabilities (IMCs) and provide a novel conceptualization of the concept by applying a holistic view of the international enterprise.

This is a literature review that maps the current research on MCs, DMCs and IMCs and serves as a basis for the theoretical conceptualization of a novel IDMCs concept as well as for the identification of research gaps and the development of future research directions on this phenomenon.

Existing typologies of MCs, DMCs and IMCs are classified into four categories: strategic, operational, analytical and value creation capabilities. A new typology of IDMCs is proposed, consisting of digital MC and dynamic internationalization capability as strategic capabilities, agile IMC, IM excellence and absorptive capability in IM as operational capabilities, IM resilience capability, IM knowledge management capability, AI-enabled IDMC and Industry 4.0-enabled IDMC as analytical capabilities, and ambidextrous IM innovation capability as value creation capability. Finally, the authors identify research gaps and develop research questions that open future research avenues for the coming years.

This paper offers a novel view of MCs, DMCs and IMCs and argues that, in contrast to the majority of previous research, a comprehensive understanding of these is only possible if all levels are considered simultaneously: the strategic, the operational, the analytical and the value creation level. A new conceptualization and typology of IDMCs follows this logic.

The purpose of this paper is to develop a theoretical model that explains the impact of big data analytics capabilities (BDAC) on company's supply chain innovation capabilities and sustainable supply chain performance. BDAC is represented through two dimensions of big data technological capabilities (BDTC) and big data personal capabilities (BDPC). Moreover, the relationships between BDTC and BDPC with sustainable supply chain performance through the mediation effect of supply chain innovation capabilities are examined.

The study used a quantitative research approach. A survey of 400 Jordanian manufacturing companies was carried out to conduct this research. However, the responses of 207 managers were valid to be used in the analysis. In this study, the SmartPLS software was used to perform structural equation modeling using a partial least squares approach (PLS-SEM) and to examine the measurement and structural model's validity and reliability.

According to the results of this study, BDPC has a significant positive impact on supply chain innovation capabilities. Furthermore, the findings indicate that supply chain innovation capabilities are the most influential predictor of sustainable supply chain performance and act as a positive significant mediator in the relationship between BDPC and firm sustainable performance. Surprisingly, the study found that BDTC had no significant effect on supply chain innovation capabilities. Besides that, no significant relationship exists between BDTC and firm sustainable performance via the mediation effect of supply chain innovation capabilities.

This study provides an integrated research model that incorporates BDAC, supply chain innovation capabilities, and sustainable supply chain performance in order to analyze supply chain innovation and sustainable supply chain performance. This suggests that the scope of the study is broader in terms of predicting sustainable supply chain performance. As a result, the study intends to fill a gap in the literature by explaining how BDAC affects supply chain innovation capabilities and firms sustainable performance. In addition, the role of supply chain innovation capabilities as a mediator between BDAC and sustainable supply chain performance is investigated.

Implementing sustainable practices in multi-tier supply chains (MTSCs) is a difficult task. This study aims to investigate why such endeavours fail and how MTSC partners can address them.

A single-case study of a global food retail company was used in this study. Semi-structured interviews with the case firm and its first- and second-tier suppliers were used to collect data, which were then qualitatively analysed using thematic analysis.

Major barriers impeding the implementation of sustainability in multi-tier food supply chains were revealed such as the cost of sustainability, knowledge gap, lack of infrastructure and supply chain complexity. Furthermore, the findings reveal five possible solutions such as multi-tier collaboration and partnership, diffusion of innovation along the chain, supply chain mapping, sustainability performance measurement and capacity building, all of which can aid in the improvement of sustainability practices.

Future research should investigate how specific barriers and drivers affect specific aspects of sustainability, pointing practitioners to specific links between the variables that can aid in tailoring sustainability oriented investment.

This research supports managerial comprehension of MTSC sustainability, pointing out ways to improve sustainability performance despite the complex multi-tier system of food supply chains.

The research on MTSC sustainability is still growing, and this research contributes to the debate about how MTSCs can become more sustainable from the perspective of the triple bottom line, particularly food supply chains which face significant sustainability challenges.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.

To take full advantage of new technologies (e.g. machine learning), a consistent and more comprehensive knowledge sharing across organisational boundaries is required. The real estate industry often faces this challenge as well. The paper aims to approach this circumstance by analysing the real estate supply chain (RESC) and aims to identify ways to achieve a more disruption-free flow of information.

To answer the research question, a cross-sectional study was conducted using a standardised online questionnaire and structural equation modelling. The majority of the study participants came from German-speaking countries. The structural equation model was used to examine the relationships between the factors inter-organisational relationship, knowledge sharing skills and knowledge sharing.

The authors found that inter-organisational relationship has a significant influence on knowledge sharing and thus on the occurrence of information flow disruptions. Aligning shared goals of parties plays a major role to improve inter-organisational relationship. Control and supervision does not show any significant effect. Knowledge sharing skills in turn have an influence on knowledge sharing.

The alignment of interests and the creation of trust should be established in the future as core elements within the framework of contract negotiations, the lived contract and the contract itself, in order to reduce disruptions in the flow of information.

From the perspective of knowledge sharing, this study attempts to identify necessities within the framework of contractual design options that simplify and promote the inter-organisational use of algorithms to increase transactional efficiency.

Although trust and distrust as distinct phenomena are of increasing interest to operations and supply chain management (OSCM) scholars, they have been inconsistently conceptualized and there is a lack of evidence regarding the distinctiveness of their respective antecedents. This study, therefore, focuses on one of the most widely accepted dimensions of trust, benevolence, to help more fully analyse (supplier) trust and distrust (in a buyer) and explore the effects of relational norms and structural power as specific antecedents.

The study employed a scenario-based role-playing experimental method. The proposed hypotheses were tested using structural equation modelling.

The results that while relational norms increase supplier trust, power asymmetry can simultaneously generate supplier distrust, support the coexistence of supplier trust and distrust in a buyer–supplier relationship.

This study is one of the first to explore the antecedents of supplier trust and distrust in a buyer. It demonstrates that supplier trust and distrust can coexist when the relationship is characterized by relational norms and asymmetrical power. This opens important questions for future trust–distrust research.