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The purpose of this paper is to explore and characterize knowledge integration approaches for integrating external knowledge of suppliers into new product development projects.

This paper is based on a multiple, in-depth case study of six product development projects at three knowledge-intensive manufacturing firms.

Firms make purposeful choices to devise knowledge integration approaches when working in collaborative buyer – supplier projects. The knowledge characteristics of the supplier input guide the choice of either coupling knowledge sharing and combining across firms or decoupling knowledge sharing (across firms) and knowledge combining (within firms).

This study relies on a limited number of case studies and considers only one supplier relationship in each project. Further studies could examine the challenge of knowledge integration in buyer – supplier relationships in different contexts, i.e. in relation to innovation complexity and uncertainty.

Managers need to make choices when designing knowledge integration approaches in collaborative product development projects. The use of coupled and decoupled approaches can help balance requirements in terms of joint problem-solving across firms, the efficiency of knowledge integration and the risks of knowledge leakage.

The conceptualization of knowledge integration as knowledge sharing and knowledge combining extends existing perspectives on knowledge integration as either a transfer of knowledge or as revealing the presence of pertinent knowledge without entirely transmitting it. The findings point to the complexity of knowledge integration as a process influenced by knowledge characteristics, perspectives on knowledge, openness of firm boundaries and elements of knowledge sharing and combining.

Knowledge sharing in research communities has been considered indispensable to progress in science. The aim of this paper is to analyze the mechanisms restricting knowledge sharing in science. It considers three categories of academia–industry knowledge transfer and a range of individual and contextual variables as possible predictors of knowledge-sharing restrictions.

A unique empirical data sample was collected based on a survey among 212 life science researchers affiliated with universities and other non-profit research institutions. A rich descriptive analysis was followed by binominal regression analysis, including relevant checks for the robustness of the results.

Researchers in academia who actively collaborate with industry are more likely to omit relevant content from publications in co-authorship with other academic researchers; delay their co-authored publications, exclude relevant content during public presentations; and deny requests for access to their unpublished and published knowledge.

This study informs policymakers that different types of knowledge-sharing restrictions are predicted by different individual and contextual factors, which suggests that policies concerning academia–industry knowledge and technology transfer should be tailored to contextual specificities.

This study contributes new predictors of knowledge-sharing restrictions to the literature on academia–industry interactions, including outcome expectations, trust and sharing climate. This study augments the knowledge management literature by separately considering the roles of various academic knowledge-transfer activities in instigating different types of knowledge-sharing restrictions in scientific research.

The purpose of this paper is twofold: first, to propose a methodology to empirically investigate the longitudinal development of social media content concerning buildings characterized by iconic architecture and second, to report on the application of this methodology.

We collected and analyzed empirical data of social media content shared via Instagram between 2011 and 2019 on 16 buildings that can be considered iconic architecture projects. Using an automated pipeline, we collected and processed 264,000 posts and 140,000 images from Instagram for the selected case studies. By studying the posting activity of Instagram users through time series analysis and conducting content analysis of the social media posts by means of both image classification and topic modeling, we report on the development of users’ capturing and reception of the selected case studies on Instagram over time.

First, we identify two distinct time patterns of social media content: instantly popular buildings whose popularity fades over time and buildings that gradually gain popularity over time. Second, we distinguish differences in the content of social media posts: some buildings are primarily covered for their architectural features and others for their cultural function and facilities.

Using empirical investigation of Instagram data on iconic architectural projects, we have identified a correlation: buildings primarily posted for their architecture are generally also the ones to gain instant online popularity that subsequently faded over time. In contrast, buildings primarily posted for their function and facilities slowly gained popularity on the social media platform over time.

This study aims to examine whether senior Enron executive emails celebrated, or at least left a space for, corporate irresponsibility. Engaging with prior organizational-focused research, we investigate how corporate emails sent by senior executives help constitute Enron by communicating to employees senior management’s stance about important topics and social characters.

The study analyzes the 527,356 sentences contained in 144,228 emails sent by Enron senior executives and other employees in the three-year period (1999–2001) before the company’s collapse. Sentences are used as the base-level speech unit because we are interested in identifying the tone and emotions expressed about specific topics and stakeholders. Tone is measured using Loughran and McDonald’s (2016) financial dictionary approach, and emotion is measured using Mohammad and Turney’s (2013) NRC word-emotion lexicon. Least Absolute Shrinkage and Selection Operator (LASSO) regressions are used to explore the determinants of senior management tone and emotions.

The analysis illustrates that while both senior executives and other employees utilized email to help accomplish task-related activities, they employed different evaluative tones to talk about key topics and stakeholders. Also important is what is left unsaid, with a “spiral of silence” emanating from senior management that created a space for corporate irresponsibility.

Combining advanced computerized textual analysis with qualitative techniques, we analyze a unique dataset to explore micro details involved in using email to communicate a tone at the top. The findings illustrate how what is said or not said by senior management contributes to the constitution of an organization.

This study aims to analyze and assess 21 years of media coverage (2000–2020) of Flix, a small industrial village located in an rural area on north-eastern Spain, which has endured in these years a severe environmental and industrial crisis, with a strong potential for stigmatization of the place.

The research is conceptualized under the Social Amplification of Risk Framework, a theoretical/conceptual approach aimed at accounting for the huge gaps that often arise between public perception of technological or environmental risks of some technologies, products and places and the expert estimations of these risks. The authors studied the coverage on Flix by a local, a regional and a national newspaper through a content analysis where the corpus (1,524 news pieces) was coded for several variables, including tone, genre and thematic area.

The studied coverage was in general overwhelmingly negative and strongly focused on “bad news” relating to pollution and deindustrialization, although this was much less the case in the local newspaper than in the regional and, in particular, the national newspaper. Thus, a territorially escalated pattern clearly emerges from our research concerning the stigmatization potential of news media coverage for the specific case under scrutiny.

To the authors’ knowledge, this is the first time such a longitudinal study of media coverage and its potential for place stigmatization is performed with this specific territorial perspective.

Following the example of the critical management education tradition, the purpose of this paper is to argue whether we should keep EE vital by disturbing it, in particular by interrogating that which has seemingly become “untouchable” from interrogation.

This paper takes inspiration from Paolo Freire’s work by proposing a pedagogical approach to entrepreneurship education which builds on an iterative and interactive process, oscillating between deconstructing and reconstructing entrepreneurship, creating space for invention in the classroom. The paper provides exemplary contributions in developing suggestions as to ways forward.

The ways forward being proposed in this paper include entrepreneurship educators engaging students as co-learners, and evoking their curiosity to pose new questions about the phenomenon; “grounding” students in their own creativity and supporting them to build the confidence needed to develop alternative understandings of how entrepreneurship can function – for themselves, in their future organizations and for society as a whole; and challenging our own teaching positions, and adopting a pedagogical process of invention, stimulating curiosity, co-creation, thought-provoking questions and entrepreneurial action.

This paper provides ways forward in keeping EE “fresh”, by sketching how we need to teach about entrepreneurship, adopting the critical insights emerging in the field. The paper argues how we do not only need other models and approaches to understand entrepreneurship, but also to understand learning and education.

This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.

The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.

This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.

The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.

Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.