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The purpose of this paper is to investigate how biological scientists form research ethics for data sharing, and what the major factors affecting biological scientists’ formation of research ethics for data sharing are.

A research model for data sharing was developed based on the consequential theorists’ perspective of ethics. An online survey of 577 participants was administered, and the proposed research model was validated with a structural equation modeling technique.

The results show that egoism factors (perceived reputation, perceived risk, perceived effort), utilitarianism factors (perceived community benefit and perceived reciprocity) and norm of practice factors (perceived pressure by funding agency, perceived pressure by journal and norm of data sharing) all contribute to the formation of research ethics for data sharing.

This research employed the consequentialist perspective of ethics for its research model development, and the proposed research model nicely explained how egoism, utilitarianism and norm of practice factors influence biological scientists’ research ethics for data sharing, which eventually leads to their data sharing intentions.

This research provides important practical implications for examining scientists’ data sharing behaviors from the perspective of research ethics. This research suggests that scientists’ data sharing behaviors can be better facilitated by emphasizing their egoism, utilitarianism and normative factors involved in research ethics for data sharing.

The ethical perspectives in data sharing research has been under-studied; this research sheds light on biological scientists’ formation of research ethics for data sharing, which can be applied in promoting scientists’ data sharing behaviors across different disciplines.

The purpose of this paper is to examine how health scientists’ attitudinal, social, and resource factors affect their data reuse behaviors.

A survey method was utilized to investigate to what extent attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. The health scientists’ data reuse research model was validated by using partial least squares (PLS) based structural equation modeling technique with a total of 161 health scientists in the USA.

The analysis results showed that health scientists’ data reuse intentions are driven by attitude toward data reuse, community norm of data reuse, disciplinary research climate, and organizational support factors. This research also found that both perceived usefulness of data reuse and perceived concern involved in data reuse have significant influences on health scientists’ attitude toward data reuse.

This research evaluated its newly proposed research model based on the theory of planned behavior using a sample from the community of scientists’ scholar database. This research showed an overall picture of how attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. This research is limited due to its sample size and low response rate, so this study is considered as an exploratory study rather than a confirmatory study.

This research suggested for health science research communities, academic institutions, and libraries that diverse strategies need to be utilized to promote health scientists’ data reuse behaviors.

This research is one of initial studies in scientific data reuse which provided a holistic map about health scientists’ data sharing behaviors. The findings of this study provide the groundwork for strategies to facilitate data reuse practice in health science areas.

This study aims to investigate the factors influencing the data sharing habits of psychologists with respect to academic reciprocity.

A research model was developed based on Ostrom’s (2003) theory of collective action to map psychologists’ underlying motivations for data sharing. The model was validated by data from a survey of 427 psychologists, primarily from the psychological sciences and related disciplines.

This study found that data sharing among psychologists is driven primarily by their perceptions of community benefits, academic reciprocity and the norms of data sharing. This study also found that academic reciprocity is significantly influenced by psychologists’ perceptions of community benefits, academic reputation and the norms of data sharing. Both academic reputation and academic reciprocity are affected by psychologists’ prior experiences with data reuse. Additionally, psychologists’ perceptions of community benefits and the norms of data sharing are significantly affected by the perception of their academic reputation.

This study suggests that Ostrom’s (2003) theory of collective action can provide a new theoretical lens in understanding psychologists’ data sharing behaviours.

This study suggests several practical implications for the design and promotion of data sharing in the research community of psychology.

To the best of the authors’ knowledge, this is one of the initial studies that applied the theory of collective action to the mechanisms of reputation, community benefits, norms and reciprocity in psychologists’ data sharing behaviour. This research demonstrates that perceived community benefits, academic reputation and the norms of data sharing can all encourage academic reciprocity, and psychologists’ perceptions of community benefits, academic reciprocity and data sharing norms all facilitate their data sharing intentions.

The purpose of this paper is to examine how data reuse experience, attitudinal beliefs, social norms, and resource factors influence internet researchers to share data with other researchers outside their teams.

An online survey was conducted to examine the extent to which data reuse experience, attitudinal beliefs, social norms, and resource factors predicted internet researchers’ data sharing intentions and behaviors. The theorized model was tested using a structural equation modeling technique to analyze a total of 201 survey responses from the Association of Internet Researchers mailing list.

Results show that data reuse experience significantly influenced participants’ perception of benefit from data sharing and participants’ norm of data sharing. Belief structures regarding data sharing, including perceived career benefit and risk, and perceived effort, had significant associations with attitude toward data sharing, leading internet researchers to have greater data sharing intentions and behavior. The results also reveal that researchers’ norms for data sharing had a direct effect on data sharing intention. Furthermore, the results indicate that, while the perceived availability of data repository did not yield a positive impact on data sharing intention, it has a significant, direct, positive impact on researchers’ data sharing behaviors.

This study validated its novel theorized model based on the theory of planned behavior (TPB). The study showed a holistic picture of how different data sharing factors, including data reuse experience, attitudinal beliefs, social norms, and data repositories, influence internet researchers’ data sharing intentions and behaviors.

Data reuse experience, attitude toward and norm of data sharing, and the availability of data repository had either direct or indirect influence on internet researchers’ data sharing behaviors. Thus, professional associations, funding agencies, and academic institutions alike should promote academic cultures that value data sharing in order to create a virtuous cycle of reciprocity and encourage researchers to have positive attitudes toward/norms of data sharing; these cultures should be strengthened by the strong support of data repositories.

In line with prior scholarship concerning scientific data sharing, this study of internet researchers offers a map of scientific data sharing intentions and behaviors by examining the impacts of data reuse experience, attitudinal beliefs, social norms, and data repositories together.

This research investigates how the availabilities of both metadata standards and data repositories influence researchers' data reuse intentions either directly or indirectly as mediated by the norms of data reuse and their attitudes toward data reuse.

The theory of planned behavior (TPB) was employed to develop the research model of researchers' data reuse intentions, focusing on the roles of metadata standards, data repositories and norms of data reuse. The proposed research model was evaluated using the structural equation modeling (SEM) method based on the survey responses received from 811 STEM (science, technology, engineering and mathematics) researchers in the United States.

This research found that the availabilities of both metadata standards and data repositories significantly affect STEM researchers' norm of data reuse, which influences their data reuse intentions as mediated by their attitudes toward data reuse. This research also found that both the availability of data repositories and the norm of data reuse have a direct influence on data reuse intentions and that norm of data reuse significantly increases the effect of attitude toward data reuse on data reuse intention as a moderator.

The modified model of TPB provides a new perspective in apprehending the roles of resource facilitating conditions such as the availabilities of metadata standards and data repositories in an individual's attitude, norm and their behavioral intention to conduct a certain behavior.

This study suggests that scientific communities need to develop more supportive metadata standards and data repositories by considering their roles in enhancing the community norm of data reuse, which eventually lead to data reuse behaviors.

This study sheds light on the mechanism of metadata standard and data repository in researchers' data reuse behaviors through their community norm of data reuse; this can help scientific communities and academic institutions to better support researchers in their data sharing and reuse behaviors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0431

The purpose of this research is to investigate the factors that influence engineering researchers’ data reuse behaviours.

The data reuse behaviour model of engineering researchers was investigated by using a survey method. A national survey was distributed to engineering researchers in the USA, and a total of 193 researchers responded.

The results showed that perceived usefulness, perceived concerns and norms of data reuse have significant relationships with attitudes toward data reuse. Also, attitudes toward data reuse and the availability of data repositories were found to have significant influences on engineering researchers’ intention to reuse data.

This research used a combined theoretical framework by integrating the theory of planned behaviour (TPB) and the technology acceptance model (TAM). The combination of the TPB and the TAM effectively explained engineering researchers’ data reuse behaviours by addressing individual motivations, norms and resource factors.

This research has practical implications for promoting more reliable and beneficial data reuse in the engineering community, including encouraging positive motivations toward data reuse, building community norms of data reuse and setting up more data repositories.

As prior research on data reuse mainly used interviews, this research used a quantitative approach based on a combined theoretical framework and included diverse research constructs which were not tested in the previous research models. As one of the initial studies investigating data reuse behaviours in the engineering community, the current research provided a better understanding of data reuse behaviours and suggested possible ways to facilitate engineering researchers’ data reuse behaviours.

The purpose of this paper is to investigate how attitudinal, normative and control beliefs influence scientists’ article sharing through ResearchGate.

A survey method was employed to examine a research model of scientists’ article sharing through ResearchGate. A total of 264 survey responses from biological scientists in the USA were used to evaluate the research model by using partial least square based structural equation modeling.

The results showed that scientists’ attitudinal beliefs (i.e. perceived relationship, reputation and risk), normative beliefs (i.e. subjective norm, perceived academic culture and community norm of article sharing) and control belief (i.e. perceived ease of use) all significantly affect their attitudes toward article sharing and article sharing intentions through ResearchGate.

The theory of planned behavior (TPB) was used to develop the research model, and the specific research constructs from prior literature were incorporated in the model. The TPB and related research constructs nicely explained biological scientists’ article sharing through ResearchGate.

This study suggests that academic libraries can better promote their scientists’ article sharing through digital platforms such as institutional repositories as well as scholarly social media. This can be achieved by emphasizing its benefits, including potential relationships or collaborations, positive academic reputation and community norms of article sharing, and by decreasing scientists’ concerns about copyright infringements and effort expectancy involved in article sharing.

As one of the initial studies in scientists’ article sharing through ResearchGate, this study provides a holistic picture of how attitudinal, normative and control beliefs all affect scientists’ article sharing through ResearchGate.

There are a variety of benefits associated with the use of YouTube for learning purposes, such as YouTube is a free open-access tool students can use to facilitate their learning. This study investigates whether an attitudinal factor (i.e. perceived usefulness) and the factor's antecedents, resource quality factors (i.e. credibility, currency, coverage and relevance), normative factor (i.e. subjective norm) and control factor (i.e. perceived ease of use) all affect college freshmen's behavioral intentions to use YouTube for academic learning purposes.

This research employs the theory of planned behavior (TPB) to explore the attitudinal, normative and control factors associated with college freshmen's behavioral intentions to use YouTube for academic learning. After developing a quantitative survey given to 182 college freshmen in a Southeastern institution in the United States of America, structural equation modeling (SEM) was used to examine the seven hypotheses and the research constructs.

The results indicate that attitudinal factor (i.e. perceived usefulness) and its antecedents, resource quality factors (i.e. currency, coverage and relevance) and normative factor (i.e. subjective norm) have a statistically significant effect on college freshmen's intentions to use YouTube for academic learning purposes.

This study suggests that individual motivations (i.e. perceived usefulness and subjective norm) and resource quality factors (i.e. currency, coverage and relevance) play into college freshmen's decisions to use YouTube for learning purposes, while other research indicates that the system or application itself factors into students' decisions to use technology for learning.

This study suggests that college freshmen are more likely to use YouTube for academic learning purposes when the freshmen hold favorable attitudes about the platform and when the freshmen believe the freshmen's peers are also using YouTube to supplement in-class learning.

This is an initial study that focuses on college freshmen's behavioral intentions to use YouTube for academic learning purposes. This research demonstrates the roles that peers as well as resource quality factors play in students' decisions to use specific technology to enhance the students' learning.

The purpose of this paper is to investigate how scientists’ prior data-reuse experience affects their data-sharing intention by updating diverse attitudinal, control and normative beliefs about data sharing.

This paper used a survey method and the research model was evaluated by applying structural equation modelling to 476 survey responses from biological scientists in the USA.

The results show that prior data-reuse experience significantly increases the perceived community and career benefits and subjective norms of data sharing and significantly decreases the perceived risk and effort involved in data sharing. The perceived community benefits and subjective norms of data sharing positively influence scientists’ data-sharing intention, whereas the perceived risk and effort negatively influence scientists’ data-sharing intention.

Based on the theory of planned behaviour, the research model was developed by connecting scientists’ prior data-reuse experience and data-sharing intention mediated through diverse attitudinal, control and normative perceptions of data sharing.

This research suggests that to facilitate scientists’ data-sharing behaviours, data reuse needs to be encouraged. Data sharing and reuse are interconnected, so scientists’ data sharing can be better promoted by providing them with data-reuse experience.

This is one of the initial studies examining the relationship between data-reuse experience and data-sharing behaviour, and it considered the following mediating factors: perceived community benefit, career benefit, career risk, effort and subjective norm of data sharing. This research provides an advanced investigation of data-sharing behaviour in the relationship with data-reuse experience and suggests significant implications for fostering data-sharing behaviour.

This research investigated how biological scientists' perceived academic reputation, community trust, and norms all influence their perceived academic reciprocity, which eventually leads to their data sharing intentions.

A research model was developed based on the theory of collective action, and the research model was empirically evaluated by using the Structural Equation Modeling method based on a total of 649 survey responses.

The results suggest that perceived academic reputation significantly increases perceived community trust, norm of data sharing, and academic reciprocity. Also, both perceived community trust and norm of data sharing significantly increases biological scientists' perceived academic reciprocity, which significantly affect their data sharing intentions. In addition, both perceived community trust and norm of data sharing significantly affect the relationship between perceived academic reciprocity and data sharing intention.

This research shows that the theory of collective action provides a new theoretical lens for understanding scientists' data sharing behaviors based on the mechanisms of reputation, trust, norm, and reciprocity within a research community.

This research offers several practical implications for facilitating scientists' data sharing behaviors within a research community by increasing scientists' perceived academic reciprocity through the mechanisms of reputation, trust, and norm of data sharing.

The collective action perspective in data sharing has been newly proposed in this research; the research sheds light on how scientists' perceived academic reciprocity and data sharing intention can be encouraged by building trust, reputation, and norm in a research community.