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Cooperative agreements between universities and firms (U–F) have gained prominence. However, the literature on organisational culture and the formation of cooperation agreements is scarce. This study aims to analyse, from the perspective of the managers of small- and medium-sized enterprises (SMEs) and those in charge in universities, the perceptions of the influence of organisational culture on this type of U–F cooperation.

To this end, multiple case studies were adopted, involving cooperation agreements between a Portuguese and eight SMEs incubated in UBImedical. Semi-structured interviews were used to gather information, aiming to understand the meaning, importance and possible obstacles caused by organisational culture in this U–F cooperation agreement.

Content analysis of the results obtained leads to the conclusion that cultural compatibility is a crucial factor for successful U–F cooperation. The exchange of knowledge, mutual trust and flexibility between those involved are identified as key determinants to build shared norms that allow a more productive, assertive union.

The study represents an important tool to support SME managers and those in charge of universities, as the evidence obtained can help them to define policies and actions with regard to the U–F cooperation process. More precisely, these SME and university managers could give more attention to culture in future cooperation agreements.

This study advances understanding of the role of organisational culture in a cooperation agreement since this was a gap identified in the literature on the topic. It also contributes to the existing body of work on U–F cooperation, demonstrating that organisational culture is considered important by partners in these agreements and should be adjusted towards compatible alignment of each party’s expectations.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

This study aims to explore the effects of long-term orientation (LTO) and strategy formation mode on corporate social responsibility. While many researchers have investigated how large businesses address corporate social responsibility (CSR), there is little empirical evidence on how small- and medium-sized businesses implement CSR or what individual drivers shape this process.

The paper surveyed 282 small and medium-sized managers from the United Kingdom. The respondents were recruited using platform Prolific Academic.

The findings reveal that LTO is a prerequisite for developing CSR and shapes strategy formation mode. The findings also suggested that deliberate strategies are positively related to CSR. The results are consistent across different components of LTO (futurity, continuity and perseverance) and CSR types (internal and external).

The results show that all aspects of LTO are relevant for CSR in SMEs. Besides LTO, deliberate strategy formation model is an important factor contributing to CSR. The paper presents as first an empirical contribution to the strategy literature by examining positive relationship between LTO and deliberate strategy formation mode.