Identifying Research Fields within Business and Management: A Journal Cross-Citation Analysis

A discipline such as business and management (B&M) is very broad and has many fields within it, ranging from fairly scientific ones such as management science or economics to softer ones such as information systems. There are at least three reasons why it is important to identify these sub-fields accurately. Firstly, to give insight into the structure of the subject area and identify perhaps unrecognised commonalities; second for the purpose of normalizing citation data as it is well known that citation rates vary significantly between different disciplines. And thirdly, because journal rankings and lists tend to split their classifications into different subjects – for example, the Association of Business Schools (ABS) list, which is a standard in the UK, has 22 different fields. Unfortunately, at the moment these are created in an ad hoc manner with no underlying rigour. The purpose of this paper is to identify possible sub-fields in B&M rigorously based on actual citation patterns. We have examined 450 journals in B&M which are included in the ISI Web of Science (WoS) and analysed the cross-citation rates between them enabling us to generate sets of coherent and consistent sub-fields that minimise the extent to which journals appear in several categories. Implications and limitations of the analysis are discussed

Thoughts on Siponen and Klaarvuniemi’s ‘Demystifying Beliefs about the Natural Sciences in IS’: The way forward

This is a comment on the paper by Siponen and Klaarvuniemi concerning the natural sciences. It argues that many of their points are correct but have been made before, particularly within critical realism. It suggests that the way forward is via a ‘mechanisms’ view of natural (and social) science

Exploring the Referral and Usage of Science Fiction in HCI Literature

Research on science fiction (sci-fi) in scientific publications has indicated the usage of sci-fi stories, movies or shows to inspire novel Human-Computer Interaction (HCI) research. Yet no studies have analysed sci-fi in a top-ranked computer science conference at present. For that reason, we examine the CHI main track for the presence and nature of sci-fi referrals in relationship to HCI research. We search for six sci-fi terms in a dataset of 5812 CHI main proceedings and code the context of 175 sci-fi referrals in 83 papers indexed in the CHI main track. In our results, we categorize these papers into five contemporary HCI research themes wherein sci-fi and HCI interconnect: 1) Theoretical Design Research; 2) New Interactions; 3) Human-Body Modification or Extension; 4) Human-Robot Interaction and Artificial Intelligence; and 5) Visions of Computing and HCI. In conclusion, we discuss results and implications located in the promising arena of sci-fi and HCI research.Comment: v1: 20 pages, 4 figures, 3 tables, HCI International 2018 accepted submission v2: 20 pages, 4 figures, 3 tables, added link/doi for Springer proceedin

The UK Research Assessment Exercise (RAE 2008) and retail research output

The 2008 Research Assessment Exercise (RAE) in the United Kingdom provides a further opportunity to consider changing trends and patters in retail research, following on a previous commentary (Dawson et al. 2004). This comparison with shows that pressures continue to mount and are impacting retail knowledge creation and dissemination practices, not least in terms of those engaged in retail research, the topics and approaches utilised, the publication tactics and strategies and thus the standing of retail research in the UK and its reputation internationall

Peer review and citation data in predicting university rankings, a large-scale analysis

Most Performance-based Research Funding Systems (PRFS) draw on peer review and bibliometric indicators, two different method- ologies which are sometimes combined. A common argument against the use of indicators in such research evaluation exercises is their low corre- lation at the article level with peer review judgments. In this study, we analyse 191,000 papers from 154 higher education institutes which were peer reviewed in a national research evaluation exercise. We combine these data with 6.95 million citations to the original papers. We show that when citation-based indicators are applied at the institutional or departmental level, rather than at the level of individual papers, surpris- ingly large correlations with peer review judgments can be observed, up to r <= 0.802, n = 37, p < 0.001 for some disciplines. In our evaluation of ranking prediction performance based on citation data, we show we can reduce the mean rank prediction error by 25% compared to previous work. This suggests that citation-based indicators are sufficiently aligned with peer review results at the institutional level to be used to lessen the overall burden of peer review on national evaluation exercises leading to considerable cost savings

Towards Autopoietic Computing

A key challenge in modern computing is to develop systems that address complex, dynamic problems in a scalable and efficient way, because the increasing complexity of software makes designing and maintaining efficient and flexible systems increasingly difficult. Biological systems are thought to possess robust, scalable processing paradigms that can automatically manage complex, dynamic problem spaces, possessing several properties that may be useful in computer systems. The biological properties of self-organisation, self-replication, self-management, and scalability are addressed in an interesting way by autopoiesis, a descriptive theory of the cell founded on the concept of a system's circular organisation to define its boundary with its environment. In this paper, therefore, we review the main concepts of autopoiesis and then discuss how they could be related to fundamental concepts and theories of computation. The paper is conceptual in nature and the emphasis is on the review of other people's work in this area as part of a longer-term strategy to develop a formal theory of autopoietic computing.Comment: 10 Pages, 3 figure

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant

Addressing stability challenges of using bimetallic electrocatalysts: the case of gold?palladium nanoalloys

Bimetallic catalysts are known to often provide enhanced activity compared to pure metals, due to their electronic, geometric and ensemble effects. However, applied catalytic reaction conditions may induce restructuring, metal diffusion and dealloying. This gives rise to a drastic change in surface composition, thus limiting the application of bimetallic catalysts in real systems. Here, we report a study on dealloying using an AuPd bimetallic nanocatalyst (1 : 1 molar ratio) as a model system. The changes in surface composition over time are monitored in situ by cyclic voltammetry, and dissolution is studied in parallel using online inductively coupled plasma mass spectrometry (ICP-MS). It is demonstrated how experimental conditions such as different acidic media (0.1 M HClO4 and H2SO4), different gases (Ar and O-2), upper potential limit and scan rate significantly affect the partial dissolution rates and consequently the surface composition. The understanding of these alterations is crucial for the determination of fundamental catalyst activity, and plays an essential role for real applications, where long-term stability is a key parameter. In particular, the findings can be utilized for the development of catalysts with enhanced activity and/or selectivity

How simulation modelling can help reduce the impact of COVID-19

Modelling has been used extensively by all national governments and the World Health Organisation in deciding on the best strategies to pursue in mitigating the effects of COVID-19. Principally these have been epidemiological models aimed at understanding the spread of the disease and the impacts of different interventions. But a global pandemic generates a large number of problems and questions, not just those related to disease transmission, and each requires a different model to find the best solution. In this article we identify challenges resulting from the COVID-19 pandemic and discuss how simulation modelling could help to support decision-makers in making the most informed decisions. Modellers should see the article as a call to arms and decision-makers as a guide to what support is available from the simulation community