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We illustrate the potential of diaries for advancing scholarship on organization studies and grand challenges. Writing personal diaries is a time-honored and culturally sanctioned way of animating innermost thoughts and feelings, and embodying experiences through self-talk with famous examples, such as the diaries written by Anne Frank, Andy Warhol, or Thomas Mann. However, the use of diaries has long been neglected in organization studies, despite their historical and societal importance. We illustrate how different forms of analyzing diaries enable a “deep analysis of individuals’ internal processes and practices” (Radcliffe, 2018) which cannot be gleaned from other sources of data such as interviews and observations. Diaries exist in different forms, such as “unsolicited diaries” and “solicited diaries” and have different purposes. We evaluate how analyzing diaries can be a valuable source to illuminate the innermost thoughts and feelings of people at the forefront of grand challenges. To exemplify our arguments, we draw on diaries written by medical professionals working for Doctors Without Borders as part of our empirical research project conducted in extreme contexts. We show the value of unsolicited diaries in revealing people’s thought world that is not apprehensible from other modes of communication, and offer a set of practical guidelines on working with data from diaries. Diaries serve to enrich our methodological toolkit by capturing what people think and feel behind the scenes but may not express nor display in public.

In recent years, the robotic process automation (RPA) technology, a software-based method to automate routine tasks in business processes, has gained significant interest and adoption. However, many implementation projects fail and current literature lacks a synthesis and comprehensive overview of factors that challenge the implementation of RPA, have an impact on success or failure of projects, or, play an enabling role in an RPA project. Hence, the purpose of this research is to identify key factors that should be considered by organizations when conducting an RPA project.

The paper adopts a qualitative methodology based on data collected in a systematic literature review (SLR) and interviews with 10 RPA experts. Using inductive coding, an integrated framework of key factors is developed.

The results suggest that the key factors for a successful RPA introduction can be divided into human, organizational and technical factors. Important aspects include for example project management techniques, capabilities and skills of employees, as well as data security considerations.

The paper contributes to knowledge by synthesizing previously dispersed knowledge into an integrated framework, as well as by complementing previous results with new qualitative, empirical data. Additionally, the RPA-specific factors are put into the perspective of persistent problems in information systems development.

Institutional, economic, social and technological advancements enable openness to cope with wicked public management issues. Although open innovation (OI) is becoming a new normality for public sector entities, scholarly knowledge on this topic is not fully systematized. The article fills this gap, providing a thick and integrative account of OI to inspire public management decisions.

Following the SPAR-4-SLR protocol, a domain-based literature review has been accomplished. Consistently with the study purpose, a hybrid methodology has been designed. Bibliographic coupling permitted us to discover the research streams populating the scientific debate. The core arguments addressed within and across the streams were reported through an interpretive approach.

Starting from an intellectual core of 94 contributions, 5 research streams were spotted. OI in the public sector unfolds through an evolutionary path. Public sector entities conventionally acted as “senior partners” of privately-owned companies, providing funding (yellow cluster) and data (purple cluster) to nurture OI. An advanced perspective envisages OI as a public management model purposefully enacted by public sector entities to co-create value with relevant stakeholders (red cluster). Fitting architectures (green cluster) and mechanisms (blue cluster) should be arranged to release the potential of OI in the public sector.

The role of public sector entities in enacting OI should be revised embracing a value co-creation perspective. Tailored organizational interventions and management decisions are required to make OI a reliable and dependable public value generation model.

The article originally systematizes the scholarly knowledge about OI, presenting it as a new normality for public value generation.

This paper aims to explore the development and application of place crowd safety management tools for areas of public assembly and major events, from a practitioner perspective.

The crowd safety risk assessment model is known as design, information, management-ingress, circulation, egress (DIM-ICE) (Still, 2009) is implemented to optimise crowd safety and potentially throughput. Three contrasting case studies represent examples of some of the world’s largest and most challenging crowd safety projects.

The paper provides some insight into how the DIM-ICE model can be used to aid strategic planning at major events, assess potential crowd risks and to avoid potential crowd safety issues.

It provides further clarity to what effective place management practice is. Evidence-based on the case studies demonstrates that the application of the DIM-ICE model is useful for recognising potential place crowd safety issues and identifying areas for require improvement.

Crowd science is an emerging field of research, which is primarily motivated by place crowd safety issues in congested places; the application and reporting of an evidence-based model (i.e. DIM-ICE model) add to this. The paper addresses a research gap related to the implementation of analytic tools in characterising place crowd dynamics.

The study aims to paint a representative picture of the current state of search interfaces of Swedish online museum collections, focussing on search functionalities with particular reference to subject searching, as well as the use of controlled vocabularies, with the purpose of identifying which improvements of the search interfaces are needed to ensure high-quality information retrieval for the end user.

In the first step, a set of 21 search interface criteria was identified, based on related research and current standards in the domain of cultural heritage knowledge organization. Secondly, a complete set of Swedish museums that provide online access to their collections was identified, comprising nine cross-search services and 91 individual museums' websites. These 100 websites were each evaluated against the 21 criteria, between 1 July and 31 August 2020.

Although many standards and guidelines are in place to ensure quality-controlled subject indexing, which in turn support information retrieval of relevant resources (as individual or full search results), the study shows that they are not broadly implemented, resulting in information retrieval failures for the end user. The study also demonstrates a strong need for the implementation of controlled vocabularies in these museums.

This study is a rare piece of research which examines subject searching in online museums; the 21 search criteria and their use in the analysis of the complete set of online collections of a country represents a considerable and unique contribution to the fields of knowledge organization and information retrieval of cultural heritage. Its particular value lies in showing how the needs of end users, many of which are documented and reflected in international standards and guidelines, should be taken into account in designing search tools for these museums; especially so in subject searching, which is the most complex and yet the most common type of search. Much effort has been invested into digitizing cultural heritage collections, but access to them is hindered by poor search functionality. This study identifies which are the most important aspects to improve.

This paper aims to analyze the extent to which education for sustainable development (ESD) training enhances university teachers’ professional competence and whether it has the same effect in the digital as in the face-to-face format.

A training concept was developed based on the professional action competence model. Between 2018 and 2021, 19 training sessions were conducted with 183 university teachers: ten in face-to-face sessions and nine in the digital format. Questionnaires were administered before and after the training to determine its impact.

Overall, the training proved to be effective. There was a significant increase in professional knowledge and self-efficacy after the training, but there was no change in motivation. The face-to-face and digital formats proved to be equally effective.

The long-term effect of the training could not be determined.

There should be regular ESD training and coaching for university teachers.

There has been little research on the effectiveness of ESD teacher training, and no comparison between the face-to-face and digital approaches exists. It has been possible to train a relatively large number of university teachers from a wide range of subject areas, about two-thirds of whom have had no previous ESD experience.

This integrative review was conducted to provide an overview of existing research on digital (in)equity and the digital divide in developed countries.

We searched academic and grey literature to identify relevant papers. From 8464 academic articles and 183 grey literature, after two levels of screening, 31 articles and 54 documents were selected, respectively. A thematic analysis was conducted following the steps suggested by Braun and Clarke and results were reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The results showed that most articles and papers were either from Europe or North America. Studies used a range of research methods, including quantitative, qualitative and mixed methods. The results demonstrated four major dimensions of the digital divide among various vulnerable groups, including digital literacy, affordability, equity-deserving group-sensitive content and availability or access to infrastructure. Among vulnerable groups, low-income people were reported in the majority of the studies followed by older adults, racial and ethnic minorities, newcomers/new immigrants and refugees, Indigenous groups, people with disabilities and women. Most reported barriers included lack of access to the internet, digital skills, language barriers and internet costs.

To the best of our knowledge, there have been limited attempts to thoroughly review the literature to better understand the emerging dimensions of digital equity and the digital divide, identifying major vulnerable populations and their unique barriers and challenges. This review demonstrated that understanding intersectional characteristics (age, gender, disability, race, ethnicity, Indigenous identity and immigration status) and their interconnections is crucial for analyzing the dynamics of digital (in)equity and divide.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

For a long time, researchers have stressed the importance of identity for collaborative supply relationships. Accordingly, it has been proposed that supply relationships may be efficiently managed by establishing a shared collective identity among partners. However, this strategy may challenge the partners' individual distinctiveness and thus lead to adversarial relationship outcomes. In this article, it is argued how and when establishing an intergroup relational identity may be a better choice than building a collective identity.

The conceptual research is based on an analysis of previous literature. Relational identity theorizing and the theory of intergroup leadership are applied to build on and extend previous views on identity in interorganizational contexts.

It is proposed that when supply chain actors are subject to identity threats in collaborative supply relationships, such threats are driven by the imbalance of power between or among the parties. Therefore, establishing an intergroup relational identity should be preferred over a collective identity in situations characterized by a high identity threat.

Future studies could support this article's theoretical suggestions with empirical evidence.

Intergroup relational identity preserves the distinctiveness of all parties involved in a collaborative relationship and is based on their individual contributions. Managers could support a collaborative environment and promote a shared vision between or among organizations through appropriate rhetoric.

This study contributes to an understanding of the relational aspects of interorganizational behavior by adapting social psychological theories to this area of research.