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Looking at the limits of artificial intelligence (AI) and controlling based on complexity and system-theoretical deliberations, the authors aimed to derive a future outlook of the possible applications and provide insights into a future complementary of human–machine information processing. Derived from these examples, the authors propose a research agenda in five areas to further the field.

This article is conceptual in its nature, yet a theoretically informed semi-systematic literature review from various disciplines together with empirically validated future research questions provides the background of the overall narration.

AI is found to be severely limited in its application to controlling and is discussed from the perspectives of complexity and cybernetics. A total of three such limits, namely the Bremermann limit, the problems with a partial detectability and controllability of complex systems and the inherent biases in the complementarity of human and machine information processing, are presented as salient and representative examples. The authors then go on and carefully illustrate how a human–machine collaboration could look like depending on the specifics of the task and the environment. With this, the authors propose different angles on future research that could revolutionise the application of AI in accounting leadership.

Future research on the value promises of AI in controlling needs to take into account physical and computational effects and may embrace a complexity lens.

AI may have severe limits in its application for accounting and controlling because of the vast amount of information in complex systems.

The research agenda consists of five areas that are derived from the previous discussion. These areas are as follows: organisational transformation, human–machine collaboration, regulation, technological innovation and ethical considerations. For each of these areas, the research questions, potential theoretical underpinnings as well as methodological considerations are provided.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

The purpose of this paper is to clarify the conceptual issues of information behaviour research by reviewing the approaches to information interaction in the context of information seeking and retrieval (IS&R).

The study uses the conceptual analysis focussing on four pioneering models for interactive IS&R proposed by Belkin, Ingwersen and Ingwersen and Järvelin.

A main characteristic of models for information interaction is the tripartite setting identifying information resources accessible through information systems, intermediary/interface and user. Dialogue is a fundamental constituent of information interaction. Early models proposed by Belkin and Ingwersen focussed on the dialogue occurring in user-intermediary interaction, while more recent frameworks developed by Ingwersen and Järvelin devote more attention to dialogue constitutive of user-information system interaction.

As the study focusses on four models developed within the period of 1984-2005, the findings cannot be generalised to depict the phenomena of information interaction as a whole. Further research is needed to model the specific features of information interaction occurring in the networked information environments in particular.

The study pioneers by providing an in-depth analysis of the ways in which pioneering researchers have conceptualised the phenomena of interaction in the context of IS&R. The findings contribute to the elaboration of the conceptual space of information behaviour research.

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

This paper aims to test the influence of external information search (EIS) on knowledge elaboration and group cognitive complexity (GCC) under the moderating effect of absorptive capacity (AC is indicated by prior knowledge base and gender diversity).

The results of three studies (one field study and two experimental studies) are reported. The first study tests the interaction between EIS and the two dimensions of AC on group knowledge elaboration in a sample of 65 organizational groups. In the second study, EIS was directly manipulated and the interaction with AC in a sample of 65 groups was tested. In the last experimental study, the AC of the boundary spanner (highest level of expertise versus lowest level of expertise) was manipulated and the effects of EIS in a sample of 37 groups were tested.

The first study reveals a significant interaction between EIS and prior knowledge base on knowledge elaboration and points toward a compensatory interplay of EIS and AC on GCC. The results of the second study indicate that EIS increases the time spent on task, as well as the efficiency of knowledge integration (GCC per unit of time). Furthermore, EIS has the strongest positive effect on GCC in groups in which at least one of the AC dimensions is average or high. The results of the last study show that the AC of the boundary spanner compensates for the lack of absorptive capacity of the group and also show that the cognitive distance between the boundary spanner and the rest of the group has a negative influence on the efficiency of knowledge integration in groups.

The limitations of Study 1, common to non-experimental research (related to causality), are dealt with in the second and third studies that establish causality between EIS and GCC.

The paper has important implications for the management of information search effort in organizational groups, in particular the groups are advised to: engage in EIS to increase their cognitive repertoire and cognitive complexity, delegate, when possible, their most competent members to engage in boundary spanning activities as they will maximize the cognitive benefits of EIS and finally minimize the cognitive dissimilarity between the boundary spanner and the rest of the group to facilitate the effective integration of novel insights into the group cognition.

This study is among the first empirical attempts to uncover the causal effect of EIS on knowledge elaboration and GCC in groups and to uncover the role of the boundary spanner in the EIS efforts.

On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context.

The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases.

The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis.

The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management.

This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.

This paper aims to enlarge ongoing debate about corporate social responsibility (CSR) proposing reflections about the role of cognitive and information flows in influencing companies’ approaches and market expectations related to CSR.

The paper builds upon the research streams related to the information asymmetry and cognitive distance, for identifying through the interpretative lens provided by systems studies, possible key drivers on which policymakers, researchers and practitioners should act for building a suitable, shared and long-term oriented path for CSR.

The paper defines a scenario map about CSR in the light of information asymmetry and cognitive distance. Such a map supports both researchers and practitioners in better understanding actions and paths required for building a shared approach to CSR.

Recognizing the multidimensionality of CSR and the multiple managerial and organizational contributions provided for underling its advantages for companies, the paper focuses the attention on the elements and conditions able to promote, stimulate and encourage companies’ CSR strategies.

The paper provides a fresh conceptual framework for explaining conditions and elements required for ensuring the success of strategies for CSR. Adopting a systems view, the paper overcomes the limitations related to a reductionist view about advantages and results of CSR to call the attention on the conditions that should be met for ensuring the emergence of a shared approach to CSR.

This study sought to distinguish characteristics of cognitive processes while using information technology. In particular, it identifies similarities and differences between mind wandering and cognitive absorption in technology-related settings in an effort to develop a deeper understanding of the role that mind wandering plays when using information technology.

Data was gathered using an online survey including responses from 619 English-speaking adults in 2019. We applied a confirmatory factor analysis and used a robust variant of maximum likelihood estimator with robust standard errors and a Satorra–Bentler scaled test statistic. The data analysis procedure was conducted with the R environment using the psych package for descriptive analysis, and lavaan to investigate the factorial structure and the underlying correlations.

We discuss the benefits of carefully differentiating between cognitive processes in Information Systems research and depict avenues how future research can address current shortcomings with a careful investigation of neurophysiological antecedents.

To date, mind wandering has been explored as a single phenomenon, though research in reference disciplines has begun to distinguish varieties and how they distinctly impact behavior. We demonstrate that this distinction is also important for our discipline by showing how two specific types of mind wandering (i.e. deliberate and spontaneous mind wandering) are differently correlated with sub-dimensions of cognitive absorption, a well-studied construct.

The purpose of this paper is twofold: to provide a clear picture on the cognitive biases affecting managers’ decision-making process of implementing a performance management system (PMS), and to identify managerial practices, measures and the key challenges to manage the cognitive biases in the corporate strategy.

Semi-structured interviews, based on theoretical milestones of performance management and cognitive psychology, gathered from 104 experienced professionals’ evaluations on the likelihood and impact of managers’ cognitive biases in PMS implementation, potential solutions as well as drivers and connected criticalities.

Recurring cognitive biases, together with considerable impacts, emerged in the first, and most strategic, phases of the PMS implementation. The authors developed a roadmap to support corporate transition to integrate behavioral strategy into the PMS implementation aiming to achieve economically and efficiently sound performance.

From the view of proper behavioral strategy affirmation in performance management literature, in a small way, the authors contribute to a desirable taxonomy of cognitive biases so differentiated decision-making scenarios may be built to compare results and draw new observations. Behavioral studies could transversally connect the cognitive biases of performance management to actors’ sociodemographic features and personality types. Practitioners may check biases affecting their organizations by means of the questionnaire and, consequently, adopt the framework illustrated to reduce them.

Performance management literature has constantly investigated positive and negative behavioral factors related to the PMS. This study, instead, makes a theoretical and methodological contribution to the PMS implementation as a decision-making process. The authors propose a theoretical framework that integrates cognitive psychology insights and applies measures to reduce biases.

Introducing technology at work presents a special challenge as learning is tightly integrated with workplace practices. Current design-based research (DBR) methods are focused on formal learning context and often questioned for a lack of yielding traceable research insights. This paper aims to propose a method that extends DBR by understanding tools as sociocultural artefacts, co-designing affordances and systematically studying their adoption in practice.

The iterative practice-centred method allows the co-design of cognitive tools in DBR, makes assumptions and design decisions traceable and builds convergent evidence by consistently analysing how affordances are appropriated. This is demonstrated in the context of health-care professionals’ informal learning, and how they make sense of their experiences. The authors report an 18-month DBR case study of using various prototypes and testing the designs with practitioners through various data collection means.

By considering the cognitive level in the analysis of appropriation, the authors came to an understanding of how professionals cope with pressure in the health-care domain (domain insight); a prototype with concrete design decisions (design insight); and an understanding of how memory and sensemaking processes interact when cognitive tools are used to elaborate representations of informal learning needs (theory insight).

The method is validated in one long-term and in-depth case study. While this was necessary to gain an understanding of stakeholder concerns, build trust and apply methods over several iterations, it also potentially limits this.

Besides generating traceable research insights, the proposed DBR method allows to design technology-enhanced learning support for working domains and practices. The method is applicable in other domains and in formal learning.