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The research landscape is changing, with key global research funders now requiring institutions to demonstrate how they will preserve and share research data. However, the practice of structured research data management is very new, and the construction of services remains experimental and in need of models and standards of approach. This groundbreaking guide will lead researchers, institutions and policy makers through the processes needed to set up and run effective institutional research data management services. This ‘how to' guide provides a step-by-step explanation of the components for an institutional service. Case studies from the newly emerging service infrastructures in the UK, USA and Australia draw out the lessons learnt. Different approaches are highlighted and compared; for example, a researcher-focused strategy from Australia is contrasted with a national, top-down approach, and a national research data management service is discussed as an alternative to institutional services. The key topics covered are: research data provision; options and approaches to research data management (RDM) service provision; a spectrum of roles, responsibilities and competences; a pathway to sustainable research data services; the range and components of RDM infrastructure and services; case studies of Johns Hopkins University, University of Southampton, Monash University, the UK Data Service and Jisc Managing Research Data programmes. This book will be an invaluable guide to those entering a new and untried enterprise. It will be particularly relevant to heads of libraries, information technology managers, research support office staff and research directors planning for these types of services. It will also be of interest to researchers, funders and policy makers as a reference tool for understanding how shifts in policy will have a range of ramifications within institutions. Library and information science students will find it an informative window on an emerging area of practice.

This is the first book to discuss the sustainable development of digital scholarly information in three key aspects: economic, social and environmental sustainability. Taking as its starting point the premise that digital information systems and services form the backbone of a knowledge society and digital economy, this book explores the challenges of ensuring sustainability of information in an evolving digital world.

Purpose Drawing on the ability–motivation–opportunity theory applied to the greening of service industries, this paper aims to analyze the extent to which green human resource management plays a role in the adoption of eco-efficiency principles in the financial sector. Environmental knowledge management represents one of the key green human resource management components. Design/methodology/approach This study conducted a survey with 178 employees working within one of the largest financial banks in Brazil, which has been investing in eco-efficiency for more than ten years. Findings On the basis of structural equation modelling, this study has provided the following findings: Among all factors taken into consideration in this study, only environmental training positively influences eco-efficiency; training may be suffering owing to barriers associated with empowerment and teamwork; the eco-efficiency program of the studied company would get benefits if it provided more autonomy to employees; and finally, the eco-efficiency program of the studied bank could be more effective if connected with green teams. Originality/value To date, this is the first work that relates – with empirical evidence from Brazil – GHRM and eco-efficiency in the financial service industry.

\"This book explores background information on outreach and instruction efforts by digital library practitioners, detailed survey results from practitioners themselves, and instructional ideas such as drop-in class sessions, course-integrated instruction, training, and ways digital library practitioners can contribute to the Open Educational Resources (OER) and open pedagogy movements\"-- Provided by publisher.

Purpose Successful businesses demand high-performing human resource management practices (HRMP) and effective knowledge management capacity (KMC) to enhance the overall organizational performance. Rapid growth of both local and multinational companies operating in knowledge-intensive industries has increased the global competition in the labor market, also for the developing economies. Therefore, attracting valuable human capital, retaining talents and managing effectively knowledge to deliver on the latest technologies and innovative solutions and services are the biggest challenges in the modern IT industry. The purpose of this paper is to examine the influence of HRMP on KMC through a cross-case analysis including four companies operating in Indian IT sector. Based on the existing studies in this field, five key HRMP have been identified (i.e. recruitment and selection, training and development, compensation and reward, employee retention and career development), as well as two key processes supporting the KMC (i.e. knowledge acquisition and knowledge sharing). Design/methodology/approach The paper adopts a qualitative research method based on a multiple case study, and it uses primary and secondary data collected through desk research and field interviews. Findings Results show the existence of HRMP aiming to enhance the individual learning, motivation and retention of employees for knowledge acquisition and knowledge sharing, in the strategic perspective to improve the organizational performance. Research limitations/implications The paper presents some limitations, which may provide scope for future research. First, being the study a qualitative multiple case analysis, a more extensive research is needed to generalize the results and investigate further relationships existing between HRMP and KMC. Moreover, a deep investigation on the organizational performance dimensions (e.g. sales growth, cash turnover, financial goal achievement) is required to verify the existence of possible links. Finally, a further limit consists in considering only knowledge acquisition and knowledge-sharing processes, excluding another crucial knowledge management (KM) process such as knowledge application. As for the research implications, the paper contributes to investigate the role of HRMP in supporting KMC in Indian IT companies, which represents a context of research not so much investigated. Practical implications From a practitioner point of view, the study can be helpful to HR and KM managers for motivating employees to undertake learning processes and enhance their performance, as well as to acquire and share knowledge resources that are useful for the organization to remain innovative and stay competitive. Originality/value As the influence of HRMP on KMC has not been widely studied in the Indian IT industry, the study may open the field for further studies on a deeper investigation of the relationships existing between human resources management (HRM), KM and organizational performance in knowledge-intensive industries in India and, more in general, in developing economies.

A new version of the fuzzy logic model, called the co-active neuro fuzzy inference system (CANFIS), is introduced for predicting standardized precipitation index (SPI). Multiple scales of drought information at six meteorological stations located in Uttarakhand State, India, are used. Different lead times of SPI were computed for prediction, including 1, 3, 6, 9, 12, and 24 months, with inputs abstracted by autocorrelation function (ACF) and partial-ACF (PACF) analysis at 5% significance level. The proposed CANFIS model was validated against two models: classical artificial intelligence model (e.g., multilayer perceptron neural network (MLPNN)) and regression model (e.g., multiple linear regression (MLR)). Several performance evaluation metrices (root mean square error, Nash-Sutcliffe efficiency, coefficient of correlation, and Willmott index), and graphical visualizations (scatter plot and Taylor diagram) were computed for the evaluation of model performance. Results indicated that the CANFIS model predicted the SPI better than the other models and prediction results were different for different meteorological stations. The proposed model can build a reliable expert intelligent system for predicting meteorological drought at multi-time scales and decision making for remedial schemes to cope with meteorological drought at the study stations and can help to maintain sustainable water resources management.

Purpose This paper aims to investigate how blockchain has moved beyond cryptocurrencies and is being deployed to enhance visibility and trust in supply chains, their limitations and potential impact. Design/methodology/approach Qualitative analysis are undertaken via case studies drawn from food companies using semi-structured interviews. Findings Blockchain is demonstrated as an enabler of visibility in supply chains. Applications at scale are most likely for products where the end consumer is prepared to pay the premium currently required to fund the technology, e.g. baby food. Challenges remain in four areas: trust of the technology, human error and fraud at the boundaries, governance, consumer data access and willingness to pay. Research limitations/implications The paper shows that blockchain can be utilised as part of a system generating visibility and trust in supply chains. Research directs academic attention to issues that remain to be addressed. The challenges pertaining to the technology itself we believe to be generalisable; those specific to the food industry may not hold elsewhere. Practical implications From live case studies, we provide empirical evidence that blockchain provides visibility of exchanges and reliable data in fully digitised supply chains. This provides provenance and guards against counterfeit goods. However, firms will need to work to gain consumer buy-in for the technology following repeated past claims of trustworthiness. Originality/value This paper provides primary evidence from blockchain use cases “in the wild”. The exploratory case studies examine application of blockchain for supply chain visibility.