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The introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields.

The authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013).

There are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results.

These findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.

A key issue in the literature about research libraries concerns their potential role in managing research data. The aim of this paper is to study the arguments for and against associating this task with libraries and the impact such an association would have on information professionals, and consider the competitors to libraries in this field.

This paper considers the nature of data and discusses data typologies, the kinds of data contained within databases and the implications of criticisms of the data-information-knowledge (DIK) hierarchy. It outlines the many competing agencies in the data curation field and describes their relationships to different kinds of data.

Many data are organically connected to the activities of large, domain-specific organizations; as such, it might be difficult for research libraries to assume a leadership role in curating data. It seems more likely that the qualifications of information professionals will come to be needed in such organizations and that the functions of research libraries will shift toward giving greater prevalence to their role as specialists in scholarly communication. In some cases, however, research libraries may be the best place to select, keep, organize and use research data. To prepare for this task, research libraries should be actively involved in domain-specific analytic studies of their respective domains.

This paper offers a theoretical analysis and clarification of the problems of data curating from the perspective of research libraries.

This paper aims to provide a substantial overview of features and channels of knowledge and technology transfer in light of achieving impact from science and research.

The paper is conceptual with substantial desk research undertaken. A taxonomy of transfer channels is proved and levels of impact from STI proposed.

It is found that there are different levels of value generated from science, technology and innovation, each featuring different stakeholders with different agendas and expectations. It is argued that to make knowledge and technology transfer impactful and sustainable, a long-term and holistic view and approach is required.

Against most papers about technology and knowledge transfer, this work presents an overarching overview of objects, channels and features of partners involved in transfer. It is features technology and knowledge transfer from a holistic perspective and provides useful background for future empiric studies and impact assessments.

The purpose of this editorial is to stimulate debate and discussion amongst marketing scholarship regarding the implications for scientific research of increasingly large amounts of data and sophisticated data analytic techniques.

The authors respond to a recent editorial in WIRED magazine which heralds the demise of the scientific method in the face of the vast data sets now available.

The authors propose that more data makes theory more important, not less. They differentiate between raw prediction and scientific knowledge – which is aimed at explanation.

These thoughts are preliminary and intended to spark thinking and debate, not represent editorial policy. Due to space constraints, the coverage of many issues is necessarily brief.

Marketing researchers should find these thoughts at the very least stimulating, and may wish to investigate these issues further.

This piece should provide some interesting food for thought for marketing researchers.

The present research is aimed at presenting a framework for the reuse of research data in Iran through applying the United Nations Development Program (UNDP).

The research at hand has a mixed methods design. In the qualitative section, the authors first carried out meta-synthesis and then an interview was conducted. Likewise, in the quantitative section, the reliability of the recommended framework was measured through carrying out a survey. Finally, the framework for data reuse was presented in five dimensions, namely human, organizational, policies and laws, technical, implementation and analysis.

Through structural equation modeling, the fitness of the framework was confirmed, and it was found out that the dimensions of policies, human and organizational played more prominent roles in the explanation of the framework in comparison with the other two dimensions.

Research studies in the area of data reuse have been conducted either quantitatively or qualitatively and in most of them interviews or questionnaires were used as tools for collecting data; however, due to the nature of this area and its relatively new literature in Iran, it is necessary to use mixed methods in order to be able to arrive at a proper understanding of this concept using both quantitative and qualitative approaches.

We articulate cycles of creative storying and data analysis and the wonder that motivated the project by detailing our reading, thinking and writing processes to contribute to the conceptual and practical literature on collaborative writing as method.

This paper documents a process of collaborative writing as method that produced a co-written fictional narrative that evokes questions about schooling.

Our process began with world-building for our fictional future, creating characters to serve as a lens for analysis. From our discussions of the data, we crafted a plotline to present our themes in coherent story. As we explored and shared our readings, interdisciplinarity shaped our project in unique ways.

Throughout, our collaboration and fiction-writing opened spaces for wonder, interdisciplinarity and joy that may inspire other researchers to engage in collaborative and/or creative writing processes.

Adding to the rich literature of arts-based research methods, we contribute our reflections on the pragmatics of incorporating reading, writing and thinking for collaboration and creative writing as qualitative research methods for document analysis.

The purpose of this editorial is to comment on the paper by Saunders and Wong in this issue. In doing so, the paper reflects on the notion of academic quality within marketing research, along with the systems in place to evaluate and reward it.

The paper takes a reflective, discursive approach.

The author finds that, while Saunders and Wong make a number of pertinent observations, and come up with interesting solutions, the notion of academic quality espoused in their paper is based on a logically flawed set of arguments.

The paper is primarily a personal view, and thus does not rely on any empirical research.

There are key implications for many parties involved in the creation and assessment of marketing knowledge. In particular, scholars would be well advised to consider notions of quality in relation to their own work, rather than rely unquestioningly on existing definitions. Policy makers and research managers (e.g. business school deans) also need to consider what quality in academic research really is, and how to appropriately direct and reward it.

The paper provides another perspective on the well‐established debate regarding quality, and thus it is hoped will stimulate further thinking.

The academic community has warned that predatory journals may attempt to capitalize on the confusion caused by the COVID-19 pandemic to further publish low quality academic work, eroding the credibility of scholarly publishing.

This article first chronicles the risks of predatory publishing, especially related to misinformation surrounding health research. Next, the author offers an empirical investigation of how predatory publishing has engaged with COVID-19, with an emphasis on journals related to virology, immunology and epidemiology as identified through Cabells' Predatory Reports, through a content analysis of publishers' websites and a comparison to a sample from DOAJ.

The empirical findings show that there were 162 titles related to these critical areas from journals listed on Cabells with a range of infractions, but most were defunct and only 39 had published on the pandemic. Compared to a DOAJ comparison group, the predatory journal websites were less likely to mention slowdowns to the peer review process related to the pandemic. Furthermore, another 284 predatory journals with COVID-19 engagement were uncovered from the initial exploration. These uncovered journals mostly centered on medical or biological science fields, while 42 titles came from other broader fields in social science, other STEM or humanities.

This study does not prove that predatory publications have released misinformation pertaining to COVID-19, but rather it exemplifies the potential within a complex academic publishing space. As these outlets have proven to be vectors of misleading science, libraries and the broader educational community need to stay vigilant as information intermediaries of online research.

This paper investigates the dependence structure and market risk of the currency exchange rate portfolio from the Malaysian ringgit perspective.

The marginal return of the five major exchange rates series, i.e. United States dollar (USD), Japanese yen (JPY), Singapore dollar (SGD), Thai baht (THB) and Chinese Yuan Renminbi (CNY) are modelled by the Bayesian generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model with Student's t innovations. In addition, five different copulas, such as Gumbel, Clayton, Frank, Gaussian and Student's t, are applied for modelling the joint distribution for examining the dependence structure of the five currencies. Moreover, the portfolio risk is measured by Value at Risk (VaR) that considers the extreme events through the extreme value theory (EVT).

The finding shows that Gumbel and Student's t are the best-fitted Archimedean and elliptical copulas, for the five currencies. The dependence structure is asymmetric and heavy tailed.

The findings of this paper have important implications for diversification decision and hedging problems for investors who involving in foreign currencies. The authors found that the portfolio is diversified with the consideration of extreme events. Therefore, investors who are holding an individual currency with VaR higher than the portfolio may consider adding other currencies used in this paper for hedging.

This is the first paper estimating VaR of a currency exchange rate portfolio using a combination of Bayesian GARCH model, EVT and copula theory. Moreover, the VaR of the currency exchange rate portfolio can be used as a benchmark of the currency exchange market risk.