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The subject of this paper is the idea of Brain–Computer Interface (BCI). The main goal is to assess the potential impact of BCI on the design, use and evaluation of information retrieval systems operating in libraries.

The method of literature review was used to establish the state of research. The search according to accepted queries was carried out in the Scopus database and complementary in Google Scholar. To determine the state of research on BCI on the basis of library and information science, a specialist LISTA abstract database was also searched. The most current papers published in the years 2015–2019 in the English language or having at least an abstract in this language were taken into account.

The analysis showed that BCI issues are extremely popular in subject literature from various fields, mainly computer science, but practically does not occur in the context of using this technology in information retrieval systems.

Due to the fact that BCI solutions are not yet implemented in libraries and are rarely the subject of scientific considerations in the field of library and information science, this article is mainly based on literature from other disciplines. The goal was to consider how much BCI solutions can affect library information retrieval systems. The considerations presented in this article are theoretical in nature due to the lack of empirical materials on which to base. The author's assumption was to initiate a discussion about BCI on the basis of library and information science, not to propose final solutions.

The results can be widely used in practice as a framework for the implementation of BCI in libraries.

The article can help to facilitate the debate on the role of implementing new technologies in libraries.

The problem of BCI is very rarely addressed in the subject literature in the field of library and information science.

This paper addresses a gap in research literature in the fields of blockchain technology (BC), supply chain network dynamics (SC) and network effect phenomena (NE). Extant BC and SC literature describes the potential benefits to be reaped through the adoption of BC technology. While BC technology does not yet meet the researched expectations of adoption, performance and efficacy, the authors analyze the three inter-related fields (BC, SC and NE) to bridge this gap in theory.

This paper begins with a research review correlating the technological fundamentals of BC technology into fundamental value propositions for SC logistics contexts. The authors review the gap between these theoretical technological functions and the current ecosystem of BC applications. With an overarching understanding of BC in SC contexts, this paper then explores the phenomena of NE and attempts to synthesize various interrelated aspects of the three fields (BC, SC and NE). Research frameworks from extant literature are used for cross-comparing legacy software/information system solutions with potential and existing BC-based solutions. Case studies are utilized to support this analysis.

Several key considerations and themes are identified to better inform practitioner and researcher decision-making. Novel insights pertain to BC platform architecture and application modularity, integrated governance and decision-making capabilities, and the automation capabilities that arise from a healthy application and smart contract ecosystem.

The core contribution is the synthesis of network effect theory with SC phenomena and BC theory and the exploration of how these three fields are inter-related in the maturation of BC technology. Specifically, the authors deepen insights from extant literature by contextualizing findings with relevant interdisciplinary theoretical frameworks.

Current literature argues that citizen engagement platforms must be used to gather citizens’ feedback to provide improved quality of services to citizens. However, limited studies consider the challenges faced by practitioners at the local level during the incorporation of those feedback for continuous service improvement. As a result, these services fail to fulfil the need of citizens. The purpose of this study is to structure the relationship between citizens’ feedback and continuous service improvement to meet the need of citizens.

Design science research methodology has been adapted under which a case study approach has been followed to investigate one of the citizens’ engagement platforms in Ireland.

The results from this study highlighted that practitioners faced challenges (e.g. capacity, risk and constraints) in terms of fulfilling the needs of citizens and there is a lack of structured approach to continuously provide improved services to them.

This study provides a structured approach in the form of a process model to showcase how citizens’ feedback can be incorporated for continuously providing improved services to the citizens.

This research provides a prescriptive view to assist municipalities during the incorporation of citizens’ feedback for continuous service improvement while addressing the challenges they face during this process.

This paper proposes a process model based on the guidelines of the open group architecture framework enterprise architecture and the collaboration with practitioners that would assist local authorities in continuously providing improved services to the citizens.

The purpose of this paper is to understand the association between the capacity to use enterprise architecture tools and the effectiveness of business model digitalization in companies.

The authors used two research strategies – survey and focus group – to analyze the relationship between maturity in using enterprise architecture (EA) and digital maturity, under the perspective of sociomateriality.

The use of EA is not a strategic competence that contributes to building sustainable competitive advantage, in the process of business model digitalization. On the other hand, top management’s determination and clarity, expressed by its sponsorship to communicating the strategy, contribute to the integration, engagement and adaptability of those involved and are responsible for higher maturity in the digitalization of business models.

The statistical treatment used does not allow understanding the causality between the variables.

It provides executives with important elements for clarifying and operationalizing digital business models.

The study operationalizes a theoretical and measurement model, through a strategy that used simultaneously a survey and a focus group, which allowed to know associations between technological capacities and maturity in digital business models.

To meet customers' expectations on shorter lead times, high product availability, flexibility, and variation in delivery and return options, retailers have turned their attention to warehousing and are making big investments in technology. Currently, technology providers are pushing for smart warehousing, a new and under-researched phenomenon. This study aims to conceptualize the term and examine pathways toward implementing smart warehousing.

An exploratory survey was administered to 50 leading Swedish retailers in varying segments. A two-tailed t-test for equality of means was used to detect significant differences between current and future states.

The study found that future smart warehouses will be automated, autonomous, digital, and connected, but that retailers will follow different paths along this journey, driven by contextual trends, e.g. sales growth, wider product assortment, shorter lead-time offerings, and integration of brick-and-mortar and online stores. Interestingly, the study revealed that many of the retailers that aim to create smart warehouses in five years are not the retailers with the most developed technology today.

The paper operationalizes smart warehousing in two dimensions: degree of automation and degree of digitalization and connectivity of information platforms. Based on the findings, 16 theoretical propositions are put forth that, based on contextual factors, explain different pathways for retailers to implement smart warehousing.

The empirical insights and theoretical discussions provide practically useful guidance, including outlined trends, for selecting and benchmarking automation and complementary technologies in warehouse operations.

This paper conceptualizes and operationalizes smart warehousing – an original approach. It is also one of the first to investigate the technological transformation in retail warehousing empirically, explaining how and why retailers choose different pathways toward smart warehousing.

This chapter discusses the growing importance of research-related information in the face of increased complexities and competitiveness within higher education environments globally. It provides some reflections on the importance of institutional research cultures to effectively address these challenges, focussing on the African context, and the role of effective research support through institutional structures such as a dedicated research office. The increasingly strategic role of research management has led to the need for a more active and visionary role in the positioning of institutions by supporting decision-making and contributing to the development and visibility of institutional research portfolios. The authors provide their insights into the scope of research-related information, the need for research offices to perform this strategic function, how these information sets can be applied in reports, evidence-based decisions, institutional showcasing, and enhanced research support. The chapter includes aspects to consider when establishing a research-related information management function within institutions.

Despite corporate communications having an immense impact on corporate success, there is a lack of dedicated techniques for their management and visualization. A potential strategy is to apply business process management (BPM) approach with business process model and notation (BPMN) modeling techniques.

The goal of this study was to gain empirical insights into the cognitive effectiveness of BPMN-based corporate communications modeling. To this end, experimental research was performed in which subjects tested two modeling notations – standardized BPMN conversation diagrams and a BPMN extension with corporate communications-specific concepts.

Standard conversation diagrams were demonstrated to be more time-efficient for designing and interpreting diagrams. However, the subjects made significantly fewer mistakes when interpreting the diagrams modeled in the BPMN extension. Subjects also evolved positive perceptions toward the proposed extension.

BPMN-based corporate communications modeling may be applied to organizations to depict how formal communications are or should be performed consistently, effectively and transparently by following and integrating with BPM approaches and modeling techniques.

The paper provides empirical insights into the cognitive effectiveness of corporate communications modeling based on BPMN and positions the corresponding models into typical process architecture.

The tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.

This work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioners of the tourism sector.

Among the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.

Both academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.

This study aims to develop a hierarchical model that uncovers the relationships between challenges confronting Africa's organ transplant supply chain systems.

Eleven challenges (variables) were identified after a comprehensive review of the existing literature. The contextual interactions among these variables were analysed from the perspectives of health-care stakeholders in two sub-Saharan Africa (SSA) countries (Nigeria and Uganda), using Delphi-interpretive structural modelling-cross-impact matrix multiplication applied to classification (MICMAC) techniques.

The findings reveal that weak regulatory frameworks, insufficient information systems and a lack of necessary skills make it challenging for critical actors to perform the tasks effectively. The interaction effects of these challenges weaken organ supply chains and make it less efficient, giving rise to negative externalities such as black markets for donated organs and organ tourism/trafficking.

This paper establishes a solid foundation for a critical topic that could significantly impact human health and life once the government or non-profit ecosystem matures. The MICMAC analysis in this paper provides a methodological approach for future studies wishing to further develop the organ supply chain structural models.

The study provides valuable insights for experts and policymakers on where to prioritise efforts in designing interventions to strengthen organ transplantation supply chains in developing countries.

This study is one of the first to empirically examine the challenges of organ transplant supply chains from an SSA perspective, including theoretically grounded explanations from data collected in two developing countries.