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This study develops a conceptual framework and a series of instruments for capturing researchers' data-sharing practices in the social sciences, by synergizing the theory of knowledge infrastructure and the theory of remote scientific collaboration.

This paper triangulates the results of three studies of data sharing across the social sciences, with 144 participants in total, and classifies the confusion, “frictions” and opportunities arising from such sharing into four overarching dimensions: data characteristics, technological infrastructure, research culture and individual drivers.

Based on the sample, the findings suggest that the majority of faculty and students in social science research do not share their data because many of them are unaware of the benefits and methods of doing so. Additional findings regarding social scientists' data-sharing behaviors include: (1) those who do share qualitative data in data repositories are more likely to share their research tools than their raw data; and (2) perceived technical support and extrinsic motivation are both strong predictors of qualitative data sharing (a previously underresearched subtype of social science data sharing).

The study confirms the previously hypothesized nature of “friction” in qualitative data sharing in the social sciences, arising chiefly from the time and labor intensiveness of ensuring data privacy.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2020-0079.

Owing to the recent surge of interest in the age of the data deluge, the importance of researching data infrastructures is increasing. The open archival information system (OAIS) model has been widely adopted as a framework for creating and maintaining digital repositories. Considering that OAIS is a reference model that requires customization for actual practice, this paper aims to examine how the current practices in a data repository map to the OAIS environment and functional components.

The authors conducted two focus-group sessions and one individual interview with eight employees at the world’s largest social science data repository, the Interuniversity Consortium for Political and Social Research (ICPSR). By examining their current actions (activities regarding their work responsibilities) and IT practices, they studied the barriers and challenges of archiving and curating qualitative data at ICPSR.

The authors observed that the OAIS model is robust and reliable in actual service processes for data curation and data archives. In addition, a data repository’s workflow resembles digital archives or even digital libraries. On the other hand, they find that the cost of preventing disclosure risk and a lack of agreement on the standards of text data files are the most apparent obstacles for data curation professionals to handle qualitative data; the maturation of data metrics seems to be a promising solution to several challenges in social science data sharing.

The authors evaluated the gap between a research data repository’s current practices and the adoption of the OAIS model. They also identified answers to questions such as how current technological infrastructure in a leading data repository such as ICPSR supports their daily operations, what the ideal technologies in those data repositories would be and the associated challenges that accompany these ideal technologies. Most importantly, they helped to prioritize challenges and barriers from the data curator’s perspective and to contribute implications of data sharing and reuse in social sciences.

It is widely recognized that sharing data is beneficial not only for science but also for the common good, and researchers are increasingly expected to share their data. However, many researchers are still not making their data available, one of the reasons being that this activity is not adequately recognized in the current reward system of science. Since the attribution of data sets to individual researchers is necessary if we are to include them in research evaluation processes, the purpose of this paper is to explore the feasibility of linking data set records from DataCite to the authors of articles indexed in the Web of Science.

DataCite and WoS records are linked together based on the similarity between the names of the data sets’ creators and the articles’ authors, as well as the similarity between the noun phrases in the titles of the data sets and the titles and abstract of the articles.

The authors report that a large number of DataCite records can be attributed to specific authors in WoS, and the authors demonstrate that the prevalence of data sharing varies greatly depending on the research discipline.

It is yet unclear how data sharing can provide adequate recognition for individual researchers. Bibliometric indicators are commonly used for research evaluation, but to date no large-scale assessment of individual researchers’ data sharing activities has been carried out.

The purpose of this paper is to report on an information gathering study on users’ research data-related challenges and proposals for library research data services (RDS). This study probes how early career researchers visually conceptualize the research process in their disciplines, their self-reported research data challenges, and their recommendations for library RDS.

Two focus group sessions were undertaken with a total of eight early career researchers. Adopting the visual narrative inquiry method, the participants were asked to sketch the general research process in their domain. The individuals’ illustrations of the research process were then used as the basis for reflecting on their data-related needs and potential RDS that would assist them during the research process.

Participants presented a research process that was more personal and, in most cases, more imperfect than the research lifecycle models that academic libraries are increasingly using for RDS development and communication. The authors present their data-related challenges, which included data access barriers, low knowledge of best practices for research data management, the need for a deeper understanding of post-publication impact, and inconsistent awareness of existing library and institution RDS. The authors outline RDS recommendations that participants proposed, which included a web-based tools, customized training sessions, and “distilled” guides to research data best practices.

The study flagged users’ gaps in understandings of existing library and institutional RDS, suggesting that there may be an opportunity to engage users in the design of communications plans for services. The findings from this user study will inform the development of RDS at the institution.

This paper puts forth a methodological approach that academic libraries can adapt for understanding users’ needs and user-generated design solutions.

Academic social (question and answer) Q&A sites are now utilised by millions of scholars and researchers for seeking and sharing discipline-specific information. However, little is known about the factors that can affect their votes on the quality of an answer, nor how the discipline might influence these factors. The paper aims to discuss this issue.

Using 1,021 answers collected over three disciplines (library and information services, history of art, and astrophysics) in ResearchGate, statistical analysis is performed to identify the characteristics of high-quality academic answers, and comparisons were made across the three disciplines. In particular, two major categories of characteristics of the answer provider and answer content were extracted and examined.

The results reveal that high-quality answers on academic social Q&A sites tend to possess two characteristics: first, they are provided by scholars with higher academic reputations (e.g. more followers, etc.); and second, they provide objective information (e.g. longer answer with fewer subjective opinions). However, the impact of these factors varies across disciplines, e.g., objectivity is more favourable in physics than in other disciplines.

The study is envisioned to help academic Q&A sites to select and recommend high-quality answers across different disciplines, especially in a cold-start scenario where the answer has not received enough judgements from peers.

Over the past decade, many research works in various disciplines have benefited from the endless ocean of people and their potentials (in the form of crowdsourcing) as an effective problem-solving strategy and computational model. But nothing interesting is ever completely one-sided. Therefore, when it comes to leveraging people's power, as the dark side of crowdsourcing, there are some possible threats that have not been considered as should be, such as recruiting black hat crowdworkers for organizing targeted adversarial intentions. The purpose of this paper is to draw more attention to this critical issue through investigation of its different aspects.

To delve into details of such malicious intentions, the related literature and previous researches have been studied. Then, four major typologies for adversarial crowdsourced attacks as well as some real-world scenarios are discussed and delineated. Finally, possible future threats are introduced.

Despite many works on adversarial crowdsourcing, there are only a few specific research studies devoted to considering the issue in the context of cyber security. In this regard, the proposed typologies (and addressed scenarios) for such human-mediated attacks can shed light on the way of identifying and confronting such threats.

To the best of the authors' knowledge, this the first work in which the titular topic is investigated in detail. Due to popularity and efficiency of leveraging crowds' intelligence and efforts in a wide range of application domains, it is most likely that adversarial human-driven intentions gain more attention. In this regard, it is anticipated that the present research study can serve as a roadmap for proposing defensive mechanisms to cope with such diverse threats.

The purpose of this paper is to apply trust perspective and attachment theory and determined that relational embeddedness, anxiety attachment, and avoidance attachment are major factors influencing the trust of tenants in owners/developers of shopping centers. The authors also examined whether tenants transfer this trust to new shopping center developers and the consequent effect on relational performance.

This research was empirically based on primary data collected from new shopping center developers and the consequent effect on relational performance. Structure equation modeling was employed to verify and validate the research model.

Data collected from 250 shopping center tenants were analyzed, and the findings indicate that relational embeddedness, anxiety attachment, and avoidance attachment positively affect the trust of store tenants in the owners or developers of shopping centers. Furthermore, the authors determined that trust in existing shopping center developers was transferred to new shopping center developers, which consequently enhanced relational performance.

The findings contribute to trust transfer research and provide actionable guidelines to organizations intending to provide intermediary business services.

This paper aims to develop a barrier cap option model, i.e. a cap option model where default can occur at any time before the maturity date, to evaluate the equity and the default risk of a bank. The model implies the bank as a liquidity provider that one institution carriers out both lending and deposit-taking functions under the same roof. This paper studies the impacts of demand deposits and capital regulation on the optimal bank interest margin, i.e. the spread between the loan rate and the deposit rate.

This paper characterizes the bank’s equity value by a barrier cap option framework. In the model, default can occur at any time before the maturity and loan markets are imperfectly competitive.

This paper has two main results. First, increases in demand deposits reduce the bank’s interest margin and further increase the bank’s default risk. The negative effect on the optimal bank interest margin which ignores the barrier leads to significant overestimation; the positive effect on the default risk which ignores the barrier leads to underestimation. Second, the same pattern of capital regulation as previously applies. Capital regulation as such makes the bank more prone to loan risk-taking, thereby adversely affecting the stability of banking system.

This paper reintroduces the knock-out value and bank interest margin determination within a synergy banking function to the cap option model. The results confirm the need to model bank equity as a barrier cap option and demonstrate its usefulness in capital regulation.

The purpose of this paper is to analyze the wastewater discharge and a zero-wastewater-discharge (ZWD) reproduction plan is designed for a paper mill in Taiwan.

The proposed model of ZWD reproduction planning is established using the fuzzy comprehensive evaluation and Taguchi method to determine the overall wastewater recovery rate. Still the prior studies failed to address a systematic approach to optimize the waste water recovery rate.

The optimal solution for clean water is 500 tons, recovery electrodialysis reversal is 345 tons, the wastewater reuse performance is 1.3 and waste heat recycling performance is 0.8, the larger number is performed well. The results shows that the maximum overall waste water recovery rate is 97.8 percent.

A paper mill is strived for improving their sustainable development. In real situation, there is a need to address the qualitative information and qualitative data to carry out the optimal ZWD reproduction planning.

The purpose of this paper is to develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model.

This paper applies the failure mode and effects analysis technique and Taguchi experimental design method, develops a green product C2C performance evaluation system that considers the fuzzy impacts of environmental laws and regulations, green goodwill, and environmental efficiency of targeting countries, and decides both the optimal green production plan and estimated optimal life cycles.

This study compares the different degree of maturity in environmental regulations, and various recycling situations are simulated to demonstrate the successful applicability of the proposed model as well as the incentive policy for Taiwan, the USA and Bangladesh.

Previous studies failed both to develop a holistic recycling production plan which is able to consider both the optimal combination of recycled components used and final green products produced with the maximum total resultant sales profit and to consider the potential failure phenomenon of recycled components adopted in the final product. Furthermore, most prior studies ignored the influence of environmental law, goodwill of the product and the efficiency of recycling mechanism of the community.