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Computer usage has become commonplace and there has been an increasing number of local efforts in organising indigenous information for individual and institutional utility. Access to information online or in CD‐ROM media is now just a matter of money; at the same time access to indigenous information has remained a challenging effort both for the user and the infomediary. Information services/products of all kinds are being generated by various agencies in the government, public and private sectors and are emerging out into the Indian information marketplace. There are a number of abstracting journals, which, in a natural process of migration, are now available in dual formats – print as well as machine readable. Besides bibliographic information, service providers are generating factual information – as directories of all descriptions, financial and commercial data, full texts of case laws, export‐import policy and so on. In this paper an attempt is made to present an overview of some of the important electronic databases developed in India or on Indian topics.

This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020.

This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients.

This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries.

The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources.

Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources.

This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.

Library automation is required in academic libraries to meet the dynamic demands of clients. This study aims to investigate the level of clients’ satisfaction of Sam Jonah library automation.

The study utilized the descriptive research design by using an exploratory case study research method. A disproportionate stratified random sampling was used to select 322 respondents (undergraduates, postgraduates and lecturers/researchers) who consented to participate in the study. Questionnaire and informal interview were used for the data collection.

The study showed that more than half of the clients of Sam Jonah library were moderately satisfied with the library’s automation. Clients mostly access internet/Wi-Fi and reference service. Patronage of the services including photocopying, borrowing of books (circulation), e-resources/academic databases, institutional repository, library website and the OPAC was not encouraging. Increase in user education was recommended to improve their usage.

The study was limited to only one academic library, namely, Sam Jonah library of the University of Cape Coast, Ghana.

The study provides insight into a case study of satisfactory level of clients in accessing automated services of Sam Jonah Library to serve as a basis for further research.

The purpose of this research is to study various issues concerning the IR software/system involved in development of institutional repositories (IRs) in India.

The survey research method was used. The data collection tool applied for the study was a web questionnaire, which was created with the help of software provided by surveymonkey.com

It was observed that 79 per cent of the institutions had implemented the DSpace IR software package. The respondents considered the End‐user interface to be the top ranking IR‐system feature. It was found that all IRs supported Text (HTML, Postscript, PDF, Spreadsheet etc.) file formats. Half of the respondents marked bitstream copying as a long‐term preservation strategy. Almost all institutional repositories were OAI‐PMH‐compliant.

Only Indian institutional repositories were studied.

This is the first detailed study focusing on the IR system/software aspects of IR. The present study has identified the existence of 16 functional IRs, some of which were not registered in any of the directories such as ROAR, Open DOAR.

This study seeks to examine the postgraduate students of two universities (Tarbiat Moallem and Tarbiat Modares) in Tehran to discover how they use online databases and general search engines.

This study was carried out focusing on postgraduate students' use of online databases provided by information providers (IPs). A sample population was selected among some postgraduate students, as patrons of central libraries of two universities in Tehran. The study was performed by means of a questionnaire given to the participants. Initially, on the basis of a sample pre‐test multi‐choice questionnaire, four information providers were selected as information hosts that were well known to the sampled students. Afterwards, the main questionnaire was developed and distributed among participants. Both participating libraries had a separate e‐databases hall for postgraduate students, so, when coming to use the online computers to search the databases, students were asked to fill out the questionnaires according to their experiences on using online resources. The study was implemented during October to December 2006 and the sample population were those postgraduate students who used the central libraries' e‐resources in campus during the period.

The results show that 63.4 per cent of respondents use online databases, followed by search engines (24.3 per cent), and print materials (11.3 per cent). Participants ranked Google as the most favourable search engine. In a comparison to using databases versus search engines, 58.4 per cent of respondents stated that they use online databases for seeking scientific information, while 33.6 per cent use search engines.

The originality of this study lies in the fact that it reveals postgraduate students' evaluation of four online IPs that are well known to most of the students in this study.

Implementing food safety measures (FSMs) have become a prerequisite for food firms looking to export internationally. Many exporters find it difficult to comply with multiple regulations, and their consignments are often rejected at borders due to food safety concerns. Hence, harmonization in food safety standards is arguably the most contentious topic regarding the export market since it affects international trade. Accordingly, the paper uses the case of Indian seafood exporters to identify key FSMs, investigate stringency associated with them and rank international markets based on degree of stringency for selected FSMs.

First, the authors identify the key FSMs by using the Delphi method. Then, the authors apply the Fuzzy analytical hierarchical process (FAHP) method to calculate weights of the FSMs as criteria. Lastly, the authors apply the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to rank markets. To compute fuzzy TOPSIS, weights are derived from fuzzy AHP.

This study’s findings suggest that product and process standards, traceability requirements and tolerance limits for residues are the most stringent FSMs, among others. Besides, the overall ranking of markets reveal that the European Union (EU), the USA and Japan ranked lowest and perceived to have the most stringent food safety requirements.

The paper offers guidance to firms and policymakers to manage their efforts and resources during food safety implementation by focussing on critical FSMs. Researchers will get insights about FSMs for further empirical investigation. To the authors’ knowledge, no study examined the stringency associated with various FSMs in the seafood industry.

The purpose of this paper is to develop data envelopment analysis (DEA) models and algorithms for efficiency improvement when the inputs and output weights are restricted and there is fixed availability of inputs in the system.

Limitation on availability of inputs is represented in the form of constant sum of inputs (CSOI) constraint. The amount of excess input of an inefficient decision-making unit (DMU) is redistributed among other DMUs in such a way so that there is no reduction in their efficiency. DEA models have been developed to design the optimum strategy to reallocate the excess input.

The authors have developed the method for reallocating the excess input among DMUs while under CSOI constraint and parameter weight restrictions. It has been shown that in this work to improve the efficiency of an inefficient DMU one needs the cooperation of selected few DMUs. The working of the models and results have been shown through a case study on carbon dioxide emissions of 32 countries.

The limitation of the study is that only one DMU can expect to benefit from the application of these methods at any given time.

Results of the paper are useful in situations when decision maker is exploring the possibility of transferring the excess resources from underperforming DMUs to the other DMUs to improve the performance.

This strategy of reallocation of excess input will be very useful in situations when decision maker is exploring the possibility of transferring the excess resources from underperforming DMUs to the other DMUs to improve the performance. Unlike the existing works on efficiency improvement under CSOI, this work seeks to address the issue of efficiency improvement when the input/output parameter weights are also restricted.

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are collected by variable probability sampling. Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate the model parameters very well in small to moderately sized stratified samples.

For repairable systems (RSs), reliability estimation is generally performed using virtual age models. Virtual age models consider the effect of maintenance actions by reducing system age using restoration factor (RF). RF is generally estimated from system failure data using various statistical methods. However, RSs such as railway systems experience various types of maintenance actions at different times during their life cycle. To consider all these different types of actions, we need multiple RFs in the virtual age model. As failure data are limited, the estimation of so many parameters becomes a complex problem and it can lead to erroneous inferences. These RFs are representative of effects of maintenance activities on the system. Therefore, these can be predicted from the information about the maintenance actions performed on the system. The paper aims to discuss these issues.

The paper considers different types of maintenance actions to predict RF of the system. These maintenance actions involve the replacement of components at some level of assembly. Each component in an assembly has its own impact on assembly restoration. RF for assembly/systems can be obtained by aggregating effects of multiple component replacement using analytical hierarchy process . The RF values obtained for different types of maintenance actions are then used to calculate the virtual age of the system at different failure points. Using these virtual age failure points, suitable distribution is fitted and parameters are estimated. The distribution and parameters provide information about reliability of the system at any point of time.

This paper provides an easier approach that gives different RFs for different types of PM and CM. To calculate RFs, it considers the impact of maintenance actions performed as well as the impact of the component on which they are performed. It is simpler and gives more consistent results than other approaches, which estimate RF using different statistical methods.

This paper provides an alternative approach to predict RF parameters instead of estimating these parameters using statistical methods. Estimation of parameters using different statistical methods is complex in nature and gives erroneous and inconsistent results. The approach given in this paper is simpler and gives more reliable results. This approach can be useful in estimating parameters for RSs when failure data are limited.