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The purpose of this paper is to extend the h-index framework to the case that articles are counted fractionally.

Three restrictions related to the standard h-index are explained: as the standard h-index is a natural number it is a rather coarse indicator; if a scientist has published a relatively small number of publications then the h-index is completely determined by the number of publications; the standard h-index cannot be applied if publications are counted fractionally, or when magnitude values smaller than one occur.

We recall solutions we proposed in earlier publications regarding the first two problems (the use of the interpolated h-index and of the pseudo h-index) and add a new proposal to solve the third problem. The relation between the recently introduced window/field-normalized h-type index (hwf-index) and the interpolated h-index is described. A real-world example proves the feasibility of this proposal.

Colleagues have shown that the h-index and its variations have fatal flaws and hence should never be used. Yet, not everyone agrees with this opinion.

Assuming that the h-index still has some value, this paper introduces a refinement of the interpolated h-index, called the generalized interpolated h-index. In this way the h-index framework is extended to incorporate, for instance, the case that fractional counting for publications and citations is applied.

This paper aims to discuss some caveats about the findings of Part 1 of the Royal Society's report from the perspective of the choice and reliability of the source base, and the bibliometric and scientometric indicators.

The paper argues that the Royal Society's report gives too much emphasis to the growth rate of the publications of Chinese researchers when interpolating those data and forecasting that, within the decade and possibly as early as 2013, China will be ahead of even the USA in terms of the number of publications.

In an era when the “publish or perish” slogan is replaced by the “get cited or perish” mantra, the report barely discusses how much China is behind the world average and especially the above countries in terms of the most important scientometric indicators that take into account the productivity/quantity aspect and the citedness of publications as a proxy for quality.

The paper illustrates that there are much better measures for the assessment of research activity than the one‐dimensional productivity numbers, such as the h‐index or the uncitedness rate, and the citations/publication rate where China is far below and the USA is far above the world average scores, and uses some charts to paint a more realistic picture of the scientific landscape.

The purpose of this paper is to assess the viability of the scholarly search engine Microsoft Academic (MA) as a citation source for evaluating/ranking marketing journals.

This study performs a comparison between MA and Google Scholar (GS) in terms of journal coverage, h-index values and journal rankings.

Findings indicate that: MA (vs GS) covers 96.80 percent (vs 97.87 percent) of the assessed 94 marketing-focused journals; the MA-based h-index exhibits values that are 35.45 percent lower than the GS-based h-index; and that the MA-based ranking and the GS-based ranking are highly consistent. Based on these findings, MA seems to constitute a rather viable citation source for assessing a marketing journal’s impact.

This study focuses on one discipline, that is, marketing.

This study identifies some issues that would need to be fixed by the MA’s development team. It recommends some further enhancements with respect to journal title entry, publication year allocation and field classification. It also provides two up-to-date rankings for more than 90 marketing-focused journals based on actual cites (October 2018) of articles published between 2013 and 2017.

The purpose of this paper is to predict bibliometric indicators based on ARIMA models and to study the short-term trends of bibliometric indicators.

This paper establishes a non-stationary time series ARIMA (p, d, q) model for forecasting based on the bibliometric index data of 13 journals in the library intelligence category selected from the Chinese Social Sciences Citation Index (CSSCI) as the data source database for the period 1998–2018, and uses ACF and PACF methods for parameter estimation to predict the development trend of the bibliometric index in the next 5 years. The predicted model was also subjected to error analysis.

ARIMA models are feasible for predicting bibliometric indicators. The model predicted the trend of the four bibliometric indicators in the next 5 years, in which the number of publications showed a decreasing trend and the H-value, average citations and citations showed an increasing trend. Error analysis of the model data showed that the average absolute percentage error of the four bibliometric indicators was within 5%, indicating that the model predicted well.

This study has some limitations. 13 Chinese journals were selected in the field of Library and Information Science as the research objects. However, the scope of research based on bibliometric indicators of Chinese journals is relatively small and cannot represent the evolution trend of the entire discipline. Therefore, in the future, the authors will select different fields and different sources for further research.

This study predicts the trend changes of bibliometric indicators in the next 5 years to understand the trend of bibliometric indicators, which is beneficial for further in-depth research. At the same time, it provides a new and effective method for predicting bibliometric indicators.

This study aimed to identify research trends and topics in sustainability assessment in the food sector within the scope of economics, business and management research.

The authors conducted a bibliometric analysis by applying a rigid and systematic research protocol, employing bibliometric techniques and a keyword co-occurrence network. Further, the Visualization of Similarities viewer software was used to analyse publications between 1994 and 2021.

The knowledge trends regarding “sustainability assessment” in the research area of business economics demonstrated a notable evolution of the topics analysed, ranging from indicators and policy analyses in agriculture and fishery sectors, to the topic of sustainability life cycle assessment (LCA) and management systems. In business and management research areas, the main theoretical frameworks used for sustainability assessment in the food sector included the triple-bottom line (TBL) and the LCA, and the main research topics were food chain logistics, bio-based products, retailers, consumption patterns and crop-based biodiesel options.

This study employed only the WoS database and future studies could incorporate other scientific databases. Regarding future research, more emphasis could be laid on food retailers given their prevalence as demonstrated by the study and past research.

The findings can help all participants in the food global value chain to make better decisions to guide their sustainability efforts and assessment. Moreover, this research reveals that companies need to be actively engaged with their stakeholders and pay special attention to consumer patterns and perceptions.

The bibliometric research focus on business and management research areas using the Web of Sciences categories, starting from the research area of business economics to the analysis of the food sector's sustainability assessment.

The purpose of this study was to map the quantity (frequency), quality (impact) and structural indicators (correlations) of research produced on cloud computing in 48 countries and 3 territories in the Asia continent.

To achieve the objectives of the study and scientifically map the indicators, data were extracted from the Scopus database. The extracted bibliographic data was first cleaned properly using Endnote and then analyzed using Biblioshiny and VosViewer application software. In the software, calculations include citations count; h, g and m indexes; Bradford's and Lotka's laws; and other scientific mappings.

Results of the study indicate that China remained the most productive, impactful and collaborative country in Asia. All the top 20 impactful authors were also from China. The other most researched areas associated with cloud computing were revealed to be mobile cloud computing and data security in clouds. The most prominent journal currently publishing research studies on cloud computing was “Advances in Intelligent Systems and Computing.”

The study is the first of its kind which identified the quantity (frequencies), quality (impact) and structural indicators (correlations) of Asian (48 countries and 3 territories) research productivity on cloud computing. The results are of great importance for researchers and countries interested in further exploring, publishing and increasing cross country collaborations related to the phenomenon of cloud computing.

The paper aims to propose the use of spline functions for the description and visualization of discrete informetric data.

Interpolating cubic splines: are interpolating functions (they pass through the given data points); are cubic, i.e. are polynomials of third degree; have first and second derivatives in the data points, implying that they connect data points in a smooth way; satisfy a best‐approximation property which tends to reduce curvature. These properties are illustrated in the paper using real citation data.

The paper reveals that calculating splines yields a differentiable function that still captures small but real changes. It offers a middle way between connecting discrete data by line segments and providing an overall best‐fitting curve.

The major disadvantage of the use of splines is that accurate data are essential.

Spline functions can be used for illustrative as well as modelling purposes.

Splines have hardly ever been used or studied in the information sciences.

Freshwater availability is reducing globally, due to increasing demand with population growth and climate change and is disproportionately impacting developing countries. This study aims to investigate the dynamics of water access and consumption across all regions of Thailand with various characteristics and water systems. Understanding the relationship between institutional, economic and climate variables in Thailand’s water management is important for water scarcity planning. Our paper fills a gap in the literature by examining the determinants of water consumption and exploring potential water management policies.

The authors empirically analyze the determinants of water consumption in Thailand, including institutional, economic and climate variables. The authors use data sets from both metropolitan and provincial waterworks authorities (PWA), as well as economic and meteorological macro-level data. The authors also adopt an auto-regressive distributed lag (ARDL) model and a Johansen cointegration test to estimate short- and long-run effects of the variables on water consumption.

The authors confirm a negative relationship between water pricing and consumption and verify a positive relationship between economic growth and water consumption across most regions of Thailand. Furthermore, the authors reveal a clear relationship between climate factors and water consumption and an inverse relationship between income and water consumption in metropolitan area. Findings indicate that authorities, especially PWA, should examine high water use in agriculture and develop regulations to ensure equitable water distribution to sustain economic growth. The authors recommend that water prices are increased within specific income thresholds to prevent impacting low-income families and to secure higher public revenue. In pursuit of environmental sustainability, the authors also recommend increasing public awareness of freshwater scarcity through education programs and investment in water-saving technologies. Differences among regions should be considered when developing water management strategies, which could be monitored through the respective water boards.

This study provides deep insight into the key factors that drive both water prices and water consumption in poor and rich areas. The unique nature of the research indicated that the paper will be of interest to policymakers and the academic community. The findings are relevant for water consumption management in Thailand and other developing countries with similar characteristics.