Research article

Enabling interdisciplinary research capacity for sustainable development: self-evaluation of the Blue Communities project in the UK and Southeast Asia

Authors
  • Fiona Culhane orcid logo (University of Plymouth, Plymouth, UK)
  • Victoria Cheung orcid logo (School of Biological and Marine Science, University of Plymouth, Plymouth, UK)
  • Melanie Austen orcid logo (School of Biological and Marine Science, University of Plymouth, Plymouth, UK)

Abstract

Global challenges such as climate change, food security and human health and well-being disproportionately impact people from low-income countries. These challenges are complex and require an international and transdisciplinary approach to research, with research skills and expertise from different disciplines, sectors and regions. In addressing this, a key goal of the research project, Blue Communities, was to create and expand mutual interdisciplinary capacity of both United Kingdom and Southeast Asian Partners. An existing questionnaire on research capacity was uniquely adapted to include interdisciplinary and international aspects and distributed for the first time as an online survey to the participants of the Blue Communities project comprising researchers across all career stages. Participants were asked about their perceptions of the research capacity and culture of their organisation, team and self and whether they believed any aspects have changed since their involvement with the project. Greatest improvement was seen at the self-level where results indicated a positive relationship between an individual’s current success or skill and their improvement over the course of the research project across 18 out of 22 aspects of research capacity for Southeast Asian, and two for UK respondents. The conflict between achieving research aims, building research capacity and making societal impact was evident. Institutional support is required to value these core aspects of interdisciplinary research.

Keywords: interdisciplinary, transdisciplinary, marine and coastal ecosystems, research culture, environmental sustainability

How to Cite:

Culhane, F., Cheung, V. & Austen, M., (2024) “Enabling interdisciplinary research capacity for sustainable development: self-evaluation of the Blue Communities project in the UK and Southeast Asia”, UCL Open Environment 6(1). doi: https://doi.org/10.14324/111.444/ucloe.1970

Funding

290 Views

Published on
04 Jul 2024
Peer Reviewed

Introduction

Global challenges such as climate change, food security and human health and well-being disproportionately impact people from low-income countries (LICs) [1] and are addressed through global governance with the United Nations Sustainable Development Goals (UN SDGs) [2,3]. It is increasingly recognised in the research community, by research funders (e.g., the UK’s Global Challenges Research Fund)1 and by institutions (e.g., universities) that these challenges are complex and require an international and interdisciplinary approach to research, integrating research skills and expertise from different disciplines, sectors and regions [4,5]. Building from a zero or near zero situation and/or strengthening existing sustainable capacity in research communities is required to address these global challenges [4], and we use these terms interchangeably hereafter. With finance and research agendas dominated by the Global North [6,7], research capacity is recognised to be unevenly distributed and often limited in the regions where global challenges are most felt [8]. Research programmes aimed at addressing global challenges therefore increasingly try to embed research capacity building and/or strengthening [8]. Capacity building must increase the resilience of the individual and/or organisation, thereby ensuring their longer-term sustainability [9] to address complex global challenges.

The often-uneven coverage of global challenges research between high-income countries (HICs) and LICs is exemplified by ecosystem service research, a key link between ecosystems and human well-being, which is lacking in Southeast (SE) Asian countries [10]. Collaboration between HICs and LICs has been suggested as a way to increase research capacity across all partners and to fill such research gaps [11,12]. However, studies have shown that research capacity building in such collaborations can be limited, for example, publications are often led by authors in HIC [5,8]. Nevertheless, it should also be noted that outputs of research publications and research funding, driven largely by the funders and the research culture in HICs, are not the only indication of research capacity [13,14]. Achieving these research products, can be in conflict with building research capacity [6,8]. In addition, the UK perception of ‘good’ research may contrast with perceptions of those in other cultures [15]. Harvey et al. [8] argue that significant disruption of the current system is required to truly achieve balanced research capacity.

The Blue Communities (BC) interdisciplinary research and capacity building project recognised that marine and coastal ecosystems are essential for food security, livelihoods, health and well-being through direct human activities such as fisheries and tourism, and for regulating and supporting services such as climate regulation; and that global loss of biodiversity and ecosystem services should be addressed through an integrated approach [16].2 BC was a four-year project, funded by the UK’s Global Challenges Research Fund (GCRF), that aimed to build capacity for sustainable interactions with marine ecosystems for health, well-being, food security and livelihoods. The primary objectives were to:

  1. develop collaborative interdisciplinary research to improve the integrated management of marine and coastal environments to reduce conflict between users, mitigate risks associated with expanded or new uses, and protect fragile ecosystems while supporting livelihoods, food security, health and well-being of coastal communities.

  2. create and expand mutual interdisciplinary capacity and capability building of both UK and SE Asian Partners and the study communities in integrated planning through sustainable interactions with marine ecosystems for the health, well-being, food and livelihoods of coastal communities.

The GCRF sought to achieve ‘meaningful and equitable relationships’ [17] through the goal of building research capacity across partners involved in the projects they funded. In the BC project, ‘a ‘learn by doing’ approach, where SE Asian researchers were encouraged to lead their research studies and seek support from experienced UK researchers when needed’ was taken (Blue Communities Handbook). Throughout the project, BC activities (e.g., skills workshops, paper writing, seminars, mentorship, flexible communication, networking, formation of research ethics and health and safety committees, etc.) allowed the building of research capacity, while achieving research objectives. The project also formed an Early Career Researcher network and encouraged Early Career Researchers to develop their own funding calls, proposals and apply for additional funding that had been set aside from the original core budget to support these.

The success of this approach can be evaluated by looking at the research products; however, this will only capture the current research outputs and not the sustainable future research capacity that has been built through the project. By taking a broader perspective on research capacity from a diverse group of researchers and allowing researchers involved in the project to have an opportunity to formally reflect on and report their perceptions of how research capacity has improved through involvement with the project, we are able to gain a fuller understanding of research capacity within the group. This learning can be used to enhance or modify approaches used for capacity building in future collaborations.

The aims of this paper are to:

  • evaluate the perceptions of the current research capacity of the organisations, research teams and individuals involved in the BC project and identify potential strengths and gaps;

  • evaluate the perceptions of the change in the research capacity of the organisations, research teams and individuals attributed to involvement in BC, and link this to the approach used by the BC research programme;

  • explore demographic factors, particularly region, that may influence these perceptions;

  • evaluate the successes and challenges and their implications for growing current and future research capacity for sustainable development.

Methods

Questionnaire

The questionnaire was based on the Research Capacity and Culture Tool [18], which gathers information on participant’s perceptions of the research capacity and culture of their institution, team and self across a range of generic research capacity markers. This questionnaire was adapted by the authors to be relevant to the researchers in this project. Specifically, additional markers for assessment were added, including on interdisciplinary and international working, carrying out research that has an impact and a question about the effect of the coronavirus (Covid-19) pandemic. Further open and closed questions were added to gain more in-depth insight into the perspectives of the project participants and how these aligned with the overarching aims of the project and the work that was carried out during the project. The questionnaire was held on the JISC online platform, and the link distributed by email to the members of the BC project. Project members were mainly from academic institutions and non-governmental organisations in the UK and in four SE Asian countries – Malaysia, the Philippines, Indonesia and Vietnam. Researchers within the project ranged from those with little research experience to those with long careers in research, and categories in the survey were chosen to capture all of these career stages. The survey was distributed in February 2022 and was open for two weeks. The timing of the distribution of the survey coincided with the final two months of the four-year BC grant and therefore captured perceptions at this point in time. The survey was written in the English language and consisted of questions in four parts: (1) demography, (2) individual research capacity, (3) team level research capacity (participant’s BC team at their own institution) and (4) institution level research capacity. Questions included those with a numeric scale response to rate skills on various aspects related to research capacity and rating scale responses to assess change in research capacity. See Appendix for the full survey.

Data analysis

The demographic factor of main interest was the broad region of the respondent. To explore overall perceptions of research capacity and whether these differed between groups based on region (Global South and Global North), quantitative data were summarised based on the country of participant, or UK (/European) vs. SE Asian. Other demographic variables (gender, age, career stage/research experience and contract type) were also explored for associations with different responses to perceptions of research capacity. Due to small cell sizes, Fisher’s exact test was used to explore associations between variables throughout, with p values reported and significance taken at the 0.05 level.

To compare across unequal groups of responses to questions on what activities people participated in, what resources they benefited from, what are their motivators and barriers to carrying out research, and what they valued most from the project, responses were weighted according to the total number of individuals per group. That is, the frequency of responses is shown as the proportion of participants in a group who responded. These are presented as bar plots. Where response rates were low in certain groups, categories were combined as indicated (e.g., undergraduate plus MSc research experience).

The responses to a number of statements regarding participants’ experience in the project is visualised in side-by-side matrix plots where the size and colour of squares represent the frequency of responses against each score to each aspect of research capacity for UK (and other European) and SE Asian respondents. Matrix plots were produced using Raw Graphs 2.0.3

The relationship between the current research capacity (current success or skill across a range of aspects) and perceived improvement in capacity of these, was explored through Spearman rank correlation for the UK (and other) and the SE Asian regions. Correlation plots, R and p values indicate the strength of association between the current perceived research capacity and the perceived improvement of each aspect as a result of involvement in the Blue Communities project. A significant positive association (significant p value and positive R value) may indicate that higher levels of research capacity have resulted from involvement with the project. These were produced using ggplot2 (Wickham [19]) in R (R Core Team [20]). Significance was taken at the 0.05 level.

Results

Demographic information

A total of 56 people responded to the survey, out of approximately 115 researchers who were involved over various time periods throughout the project. Of these, most (57%) were female and aged between 31 and 50 years of age (64%) (Table 1). The largest group of respondents came from the UK (or other European countries) and the smallest from Indonesia.

Table 1.

Demographics of the BC research community who responded to the online survey with information on the total population of the BC project, where available, for comparison

Demographic variable Category Proportion of respondents (%) Number of individual respondents Total number of individuals in BC project (proportion)
Gender Female 57 32 59 (51%)
Male 41 23 56 (49%)
Prefer not to say 2 1
Age range* 18–30 16 9 -
31–50 64 36 -
51+ 18 10 -
Prefer not to say 2 1 -
Country of Institution Indonesia 7 4 16 (14%)
Malaysia 20 11 19 (17%)
Philippines 23 13 22 (19%)
UK (and other European) 33 18 42 (37%)
Vietnam 18 10 16 (14%)
  • *Four age categories were recorded in the survey, but due to low response 51–64 and 65+ categories were merged.

Most respondents to the survey came from academia (88%), though non-governmental organisations (NGOs) and government agencies were also represented (Table 2). Fifty-five per cent of researchers had fixed-term contracts and 74% had multiple work commitments. All career stages from early, mid and later career were represented in the survey, with 53% from the broader early career categories (students and PhD + five years or less experience).

Table 2.

Information about the career type, stage and formal research experience of the BC research community who responded to the online survey

Variable Category Response rate (%) Number of individuals
Sector Academia 88 49
NGO 9 5
Other (Government Agency) 4 2
Contract type Fixed term 55 31
Permanent 45 25
Research experience* Undergraduate degree and/or current MSc student 14 8
MSc and/or current PhD student 25 14
PhD with up to 5 years 14 8
More than 5–15 years post PhD 29 16
More than 15 years post PhD 18 10
Type of involvement in BC project I work only on the Blue Communities project or Blue Communities is my main research project. 27 15
My time is divided amongst multiple research projects, of which Blue Communities is one. 23 13
Blue Communities is my only research project, but I also have other work commitments such as teaching or administrative work. 9 5
My time is divided amongst multiple research projects, of which Blue Communities is one, and I also have other work commitments such as teaching or administrative work. 42 23
  • *Research experience had seven separate categories in the original survey, but due to low response rate in some groups undergraduate degree was merged with current MSc student; and MSc was merged with current PhD student.

There was evidence of an association between age and gender (p = 0.01), with more younger researchers being female; and age and experience (p < 0.01), with older researchers having more experience (for full results see Table A1). There was also an association between experience and country (p = 0.01) or region (i.e., UK and other vs. SE Asia; p = 0.02), with researchers with less experience being more likely to be from SE Asian countries.

Individual research capacity

Respondents took part in a broad range of activities throughout the project, with most people involved in publishing, presenting, analysing quantitative data, collecting data and designing studies (Fig. 1). There was no evidence of an association with the type of activities carried out and gender (p = 0.987), age (p = 0.984), experience (p = 1), contract type (p = 0.998) and country (p = 1) or region (p = 0.811) (see also Table A2). Most researchers were involved in particular with writing reports (86%) and publications (82%), collecting (61%) and analysing (61%) data and designing studies (61%). Fewer people overall were involved with applying for and securing research funding (41%), submitting financial claims (32%) and submitting health and safety assessments (21%).

Figure 1
Figure 1

Research activities respondents have been involved with as part of the BC project. Respondents could choose as many options as were relevant. The bars are weighted according to the total number of respondents from each country/region (e.g., if every respondent chose an option, each bar segment would have a value of 1).

The resources researchers benefited from were associated with the region (p = 0.002, Table A2). Respondents across all regions benefitted the most from knowledge exchange resources such as seminars (80%), networking (79%), training (79%), access to expertise (73%) and mentorship (70%) (Fig. 2). Resources such as protocol development (38%), library access (34%), health and safety guidance (30%), database management (30%) and software (27%) benefitted fewer respondents overall, but of those, benefits were felt mostly by the SE Asian respondents.

Figure 2
Figure 2

Resources respondents benefited from through the BC partnership. Respondents could choose as many options as were relevant. The bars are weighted according to the total number of respondents from each country/region (e.g., if every respondent chose an option, each bar segment would have a value of 1).

When asked what the respondents valued most from their BC experience, respondents across all across regions and career stages most valued interdisciplinary (61%) and international working (43%), publishing papers (34%) and improving their subject understanding and knowledge (30%) (Fig. 3). There was evidence of an association between age and the skills and opportunities valued (p = 0.023, Table A2), younger researchers in particular valued publishing papers and further employment opportunities. Country (p = 0.030) and region (p = 0.005) also had an association with values, with SE Asian researchers being more associated with valuing developing a positive attitude to research.

Figure 3
Figure 3

Research skills or opportunities respondents valued the most from their experience in BC. Respondents could choose up to three options. The bars are weighted according to the total number of respondents from (a) each country/region, and (b) their age (e.g., if every respondent chose an option, each bar segment would have a value of 1.

Many of the top barriers to research that respondents identified were related to time constraints in general [e.g., ‘Lack of time for research’ (54%), ‘Desire for work/life balance’ (41%), ‘Other work roles take priority’ (38%) and ‘Lack of suitable backfill’ (38%)] (Fig. 4). There was an association with the contract type (p = 0.009, Table A2), with those on fixed-term contracts particularly identifying lack of long-term employment and personal motivations as barriers. Covid-19 pandemic restrictions were also identified as a key barrier by 48% of respondents, particularly for SE Asian researchers (p = 0.001). Other barriers were a lack of long-term employment (27%), personal commitments (23%), fear of getting it wrong (21%) and lack of skills (20%). English language was identified by 13% of respondents as being a barrier.

Figure 4
Figure 4

Barriers to research, according to participants of the BC project. Respondents could choose as many options as were relevant. The bars are weighted according to the total number of respondents from (a) each country/region, and (b) their contract type (e.g., if every respondent chose an option, each bar segment would have a value of 1).

When asked what personally motivates them to carry out research, respondents indicated developing skills (79%), advancing their career (64%), making an impact (a problem that needs solving) (61%), increased job satisfaction (54%) and scientific curiosity (46%) (Fig. 5). These options were indicated across gender, age, contract type, regional and career stage groups showing the motivations for research were common across this group of researchers (Table A2).

Figure 5
Figure 5

Personal motivators to research, according to participants of the BC project. Respondents could choose as many options as were relevant. The bars are weighted according to the total number of respondents from (a) each country/region, and (b) their career stage (e.g., if every respondent chose an option, each bar segment would have a value of 1).

Across both broad regions, 91% of respondents agreed that they worked with interdisciplinary teams, with 66% in strong agreement with this statement (Fig. 6E); 91% agreed or strongly agreed that they feel positive about working with people from different disciplines in the future (Fig. 6O) and 89% that they had the opportunity to lead research (Fig. 6M). Sixty-eight per cent of respondents agreed or strongly agreed that they had the chance to lead a publication (Fig. 6K), of these 76% were from SE Asia. Leading publications was associated with age (p = 0.012; Table A3) and career stage (p = 0.021), with the youngest and least experienced, and oldest and most experienced not having led publications. On the whole, respondents from SE Asia responded more positively across all statements. Ninety-seven per cent of respondents from SE Asia agreed or strongly agreed that their research was relevant for making an impact in their region (making a difference to society), but this was less clear for UK respondents with 56% in agreement with this statement (Fig. 6A; p < 0.001 Tables A3 and A4). Ninety-two per cent of SE Asian respondents also agreed that they led on their own research questions (Fig. 6L; p = 0.008), compared to 56% of UK respondents. Ninety-five per cent also agreed they learnt new skills (Fig. 6J, p < 0.001), compared to 61% for UK respondents. SE Asian respondents also perceived that their career progressed, and prospects improved [Fig. 6C (88%), Fig. 6H (95%); p = 0.041, p = 0.015]. Fifty-six per cent and 67% of UK respondents agreed to the same markers on career progression and prospects.

Figure 6
Figure 6

Level of agreement to a number of statements from (a) SE Asian, and (b) UK (and other European) respondents. A five-point scale was used: Strongly disagree (−2), Disagree (−1), Neither agree nor disagree (0), Agree (1) and Strongly agree (2). Larger square and darker colour indicates higher frequency of responses in the matrix plot. Statements A–Q are abbreviated in the figure, full statements and percentage breakdowns are given in Table A4 in the Appendix.

At the individual level, across both broad regions, most respondents were confident in their success and/or skill on most aspects of research capacity, with 64% of ratings across skills being at a score of 7 or higher (Fig. 7), and with no sufficient evidence of a difference in success or skill between the regions on any aspect (Table A5). Respondents in both regions were most confident in finding and critically reviewing literature (Fig. 7E, G) with 84% scoring themselves 7 or higher. Seventy-nine per cent of respondents scored 7 or higher in presenting research (Fig. 7J) and 77% in protocol/study design (Fig. 7T). Sevent-five per cent scored 7 or higher in understanding interdisciplinary approaches and issues (Fig. 7P). Areas of lower confidence for respondents were in submitting a health and safety assessment (Fig. 7M; 32% scored 7+), financial claims (Fig. 7O; 41% scored 7+), in securing research funding (Fig. 7L; 45% scored 7+) and in submitting ethics applications (Fig. 7N; 52% scored 7+).

Figure 7
Figure 7

The relationship between SE Asian respondent and UK (and other European) respondent perceptions of their personal (individual level) current success or skill level for each aspect of research capacity (1 = no success/skill and 9 = highest possible success/skill) and change in success or skill level for each aspect as a result of involvement in the BC project (rating scale categories converted to numbers where –2 is ‘Much worse’, 0 is ‘no change’ and +2 is ‘Much better’). Correlation line, R and p values indicate Spearman’s rank correlation. Note that discrete data points are ‘jittered’ for visualisation purposes. Research capacity aspects A–V are abbreviated in the figure, full statements given in Table A6 in the Appendix.

Self-assessed success or skill in the different aspects generally was not associated with demographic variables, except in a few circumstances. There was evidence of association with age and data collection (p = 0.05, Table A5), where the 31–50-year-old age category scored themselves highest; and age and reviewing literature (p = 0.04), where older age categories scored themselves higher. Early career researchers (up to PhD student) scored themselves lower on finding literature (p = 0.02) and on publishing (p = 0.04). There was an association with gender and the scores on quantitative analysis, where some female researchers scored themselves very low (p < 0.001).

In terms of change following involvement with the BC project, all but one respondent saw improvement in the understanding of overseas issues (Fig. 7Q). SE Asian partners indicated higher improvement across 14 out of 22 markers of research capacity compared to UK partners who mainly indicated no change or a smaller degree of improvement across most markers (Fig. 7, Table A5). SE Asian respondents saw greater improvement in collecting data (Fig. 7D, p < 0.001), finding and critically reviewing literature (Fig. 7G, p < 0.001, Fig. 7E, p < 0.001), questionnaires (Fig. 7F, p < 0.001), managing projects (Fig. 7H, p = 0.018), presenting research (Fig. 7J, p = 0.008), networking (Fig. 7I, p < 0.001), referencing and data management systems (Fig. 7R, p = 0.001, Fig. 7S, p = 0.027), research reports and publications (Fig. 7U, p = 0.002, Fig. 7V, p = 0.008) and understanding interdisciplinary approaches and issues (Fig. 7P, p = 0.001). Similar to UK respondents, they mostly saw no change submitting health and safety applications (Fig. 7M, p = 0.51) and in financial claims (Fig. 7O, p = 0.12). There was no association between other demographic variables and the degree of improvement reported.

There was evidence to suggest a significant positive correlation between the current success or skill of individuals and the degree of improvement during the BC project in 18 out 22 aspects for SE Asian respondents and in two aspects [providing advice (Fig. 7K) and submitting finance claims (Fig. 7O)] for UK participants (Fig. 7). Together this evidence indicates that SE Asian respondents, on most aspects, perceived that they had improved from a lower success or skill level to achieve a success or skill level that was in line with what UK respondents had assigned themselves from the start of the project.

Team level research capacity

At the team level (the participant’s BC team at their own institution), most respondents across both broad regions were confident in the success or skill of their team across most research capacity markers, with 74% of ratings across skills being at a score of 7 or higher and with insufficient evidence of a difference in success or skill between the regions on any aspect (Fig. 8, Table A7). Eighty-six per cent of respondents scored their team 7 or higher for publications (Fig. 8U), 82% for research opportunities (Fig. 8R) and 80% for having leaders that support research (Fig. 8Q). On other aspects, there was lower confidence with 63% scoring their team 7 or higher for having incentives and support for mentoring (Fig. 8N) and for availability of software to support research activities (Fig. 8P), and 64% for having adequate resources to support staff training (Fig. 8J). There was evidence of an association with career stage and disseminating research (Fig. 8B, p = 0.044), with early career groups (up to 5 years post PhD) scoring their teams highly on this; their team’s success in providing expert advice (Fig. 8K, p = 0.010), with MSc/PhD students scoring their teams lower on this, and scholarships (Fig. 8T, p = 0.041), with MSc/PhD students and those up to 5 years post PhD scoring their teams lower on this. More experienced researchers (p = 0.007) and those on permanent contracts (p = 0.035) scored their teams higher on software (Fig. 8P). Male researchers were associated with a lower team score for engaging with external partners (Fig. 8L, p = 0.025).

Figure 8
Figure 8

The relationship between SE Asian respondent and UK (and other European) respondent perceptions of their team’s current success or skill level for each aspect of research capacity (1 = no success/skill and 9 = highest possible success/skill) and change in success or skill level for each aspect as a result of involvement in the BC project (rating scale categories converted to numbers where –2 is ‘Much worse’, 0 is ‘no change’ and +2 is ‘Much better’). Correlation line, R and p values indicate Spearman’s rank correlation. Note that discrete data points are ‘jittered’ for visualisation purposes. Research capacity aspects A–U are abbreviated in the figure, full statements given in Table A8 in the Appendix.

In terms of change following involvement with BC, there was disparity between groups, with SE Asian partners finding most aspects to be better or much better and UK respondents mostly reporting no change (Fig. 8). SE Asian respondents reported significantly higher improvement than UK respondents on all aspects except scholarships (T) (Table A7). There was no association with age, gender, career stage or contract type and the level of improvement.

There was evidence to suggest a significant positive correlation between the current success or skill of teams and the degree of improvement during the BC project in 11 out 21 aspects for SE Asian respondents and in two aspects [staff being involved in research planning (Fig. 8D) and staff training (Fig. 8J)] for UK respondents (Fig. 8). Together this evidence indicates that SE Asian respondents, on around half of research capacity markers, perceived that their teams had improved from a lower success or skill level to achieve a success or skill level that was in line with what UK respondents had assigned their teams from the start of the project.

Organisational level research capacity

At the organisational level, again most researchers rated their organisation’s success or skill highly across all or most research capacity markers in both broad regions, with 66% of ratings across skills being at a score of 7 or higher (Fig. 9). Seventy-seven per cent of respondents scored their institutions 7 or higher for accessing external funding for research (Fig. 9A), encouraging research activities relevant to creating impact (Fig. 9B), and for supporting the peer-reviewed publication of research (Fig. 9T). While only 54% of respondents scored their institutions 7 or higher for ensuring organisational planning is guided by evidence (Fig. 9D) and ensuring staff career pathways are available in research (Fig. 9E). Only for having adequate support for staff training (Fig. 9K), did UK respondents score their institutions higher than SE Asian respondents (p = 0.049, Table A9). For this aspect, 72% of UK respondents and 47% of SE Asian respondents scored their institutions 7 or higher. There was an association with career stage and scores attributed to some aspects. Later career researchers (more than 15 years post PhD), scored their institutions higher on getting external funding (Fig. 9A, p = 0.046), their institution’s access to software (Fig. 9Q, p = 0.011) and on its interdisciplinary approach (Fig. 9S, p = 0.041).

Figure 9
Figure 9

The relationship between SE Asian respondent and UK (and other European) respondent perceptions of their organisation’s current success or skill level for each aspect of research capacity (1 = no success/skill and 9 = highest possible success/skill) and change in success or skill level for each aspect as a result of involvement in the BC project (rating scale categories converted to numbers where –2 is ‘Much worse’, 0 is ‘no change’ and +2 is ‘Much better’). Correlation line, R and p values indicate Spearman’s rank correlation. Note that discrete data points are ‘jittered’ for visualisation purposes. Research capacity aspects A–T are abbreviated in the figure, full statements given in Table A10 in the Appendix.

In terms of improvement following involvement with BC, SE Asian respondents reported some improvement (‘Better’) across all markers and overall higher improvement than UK respondents across all markers, who reported mostly no change (Fig. 9, Table A9). There was evidence of an association with gender on degree of improvement on two aspects, with females more likely to report no improvement at their institution for research development policy (Fig. 9F, p = 0.006) and ethics (Fig. 9H, p = 0.005).

There was evidence to suggest a significant positive correlation between the current success or skill of institutions and the degree of improvement during the BC project in 11 out 20 aspects for SE Asian respondents and in one aspect [publication (Fig. 9T)] for UK participants (Fig. 8). Together this evidence indicates that SE Asian respondents, on around half of the research capacity aspects, perceived that their institutions had improved from a lower success or skill level to achieve a success or skill level that was in line with what UK respondents had assigned their institutions from the start of the project.

Discussion

This paper has presented quantitative data from a diverse group of researchers on the impact of the research capacity building activity in an internationally collaborative project that has taken the specific approach of ‘learning-by-doing’. Generally, this appears to have been a successful strategy based on the largely positive perceptions of the respondents to this survey but was particularly successful at the individual level with respondents from SE Asia, who attributed clear improvements across 18 out 22 aspects of research capacity to their involvement in the BC project. Here, evidence for building and strengthening of research capacity through this project was based on the perceptions of participants who were at the end of the four-year project period and is discussed in the important context of its sustainability into the future to address the ongoing global challenges.

Successes, or what worked well for current and future research capacity

The skills and opportunities valued most by the respondents of this study were interdisciplinary (chosen by 43%) and international working (chosen by 61%) to make a difference to society and 91% felt positive about continuing to work in this way in the future; one respondent reflected on ‘working with amazing international partners on issues that matter’ (BC project participant, UK) and another could see an impact in their local community: ‘the great response of the communities to our engagements’ (BC project participant, Philippines). Almost all (97%) respondents from SE Asia could see that their research was relevant for making an impact in their region, while 61% of the full group identified a problem that needs to be solved as one of the motivations for their research. While some researchers recognised the challenges and benefits of this type of working, ‘Having differing disciplines within the team is enriching and engaging despite the conflicts that came with it’ (BC project participant, Malaysia), building trusting relationships between partners, with integration and collaboration, is one of the key requirements of a successful interdisciplinary capacity building project and keeping people engaged in the process [8,9,21,22]. Capacity building is not only about transferring traditional skills but also about ‘a process of strengthening relationships that enable innovation and resilience in communities, organisations and societies’ [9], thus, the process of collaborating and working together builds capacity in itself [17]. The results of this survey suggest that the researchers involved are enthusiastic, passionate and engaged in working collaboratively and making a difference to society. Importantly, respondents expressed their hopes for continuing to work this way in the future, with 77% hoping to build upon the networks and relationships that were developed through the project. As one respondent stated: ‘I hope to continue to cooperate in the future, to develop the research direction of the project’ (BC project participant, Vietnam).

One clear example of ‘learning-by-doing’ in action was in carrying out evidence synthesis and systematic reviews. During the project a team of UK researchers who are very experienced in systematic reviews ran a series of training sessions and provided ongoing guidance and support to SE Asian researchers in developing their own systematic reviews with research questions relevant for their region. This approach was clearly successful in that researchers in SE Asia identified critically reviewing literature as being a factor they are particularly skilled or successful at and identified this as an area of much improvement because of involvement with the project. Three systematic reviews were carried out for three of the SE Asian partner countries, all led by SE Asian researchers (publications in progress). In addition, protocols for carrying out reviews were also developed and published [23,24]. Furthermore, participants in the workshops have since gone on to teach the method to others in their institution, demonstrating the sustainable nature of this capacity building.

Notably, lead authorship in the BC project amongst the respondents was distributed between those from different countries, leaning more towards those from SE Asia, with 76% of SE Asian and 50% of UK respondents agreeing they had the opportunity to be a lead author. This was clearly appreciated by some, as one respondent described their team’s motivation as being ‘the independence granted to develop and pursue research questions’ (BC project participant, Indonesia). This is in contrast to many studies that show disparity in lead authorship between high- and low-income partner countries. For example, in the Future Climate for Africa programme, Harvey et al. [8] found only 14% of 230 publications were led by a researcher from an African institution. Interdisciplinary research, by nature, requires input from a diversity of partners coming from different knowledge backgrounds but power imbalances can mean that these different actors do not always contribute sufficiently [21]. A key feature of BC was that it was decided from the outset that early career researchers, in particular those from SE Asian partner institutions, would be prioritised in terms of leading research and publications, and were supported by more senior staff in doing this. In addition, the project established an Early Career Researcher Network, which encouraged members to apply for additional funding to support their own research questions, host seminars and share skills. Having this set out clearly and supported with leadership meant these power imbalances were explicitly addressed.

The Covid-19 pandemic restrictions presented a challenge, as reported by respondents, especially SE Asian participants (58% of SE Asian respondents identified this as a barrier to research). This was through an inability or reduced time to visit field sites and collect new data, an inability to meet project partners in person, and potentially more difficulty with Internet or resource access, as well as other personal factors. This is likely to have impacted capacity building through impacting development of personal relationships. Despite this, SE Asian partners responded positively in terms of improvement due to their involvement with the project across 18 out 22 research capacity markers. Teams adapted quickly to the new situation and in some cases changed their focus. Indeed, partners in the project demonstrated good practice in moving activities online in a sensitive and structured way [25]. In some, but not all cases, project participants recognised that they were fortunate to have the pandemic come later in the project so that personal relationships were already well established. However, where this was not the case, partners demonstrated concerted effort in building relationships online. For example, Richter et al. [25] emphasised the importance of using icebreakers in the virtual environment. This made a relatively smooth transition to moving capacity building elements and research working online.

Most respondents agreed or strongly agreed that they had the opportunity to lead research questions (80%) and publications (68%), they learnt new skills (84%), that their career level progressed (77%) and that they would have more career opportunities available (86%) to them as a result of their involvement in BC. This shows that the respondents perceive concrete and sustainable capacity building has been achieved during the project, and that partners feel they can carry on with this type of research independently into the future. One respondent reflected: ‘my involvement at the Blue Communities has increased my visibility in the local academia. This program has also significantly impacted my research and project management skills. Most importantly, my involvement with the Blue Communities has paved my career path in significant ways’ (BC project participant, Malaysia).

Challenges for sustainable current and future research capacity

An issue identified previously in research projects that aim to create impact in solving global challenges and build capacity is the conflict between research aims (e.g., advancing knowledge and publishing papers), influencing policy and building capacity [8]. Harvey et al. acknowledge that a common strategy is often used to achieve these aims, but this may not be appropriate for all, and research aims can be given priority. This conflict clearly emerged during the BC project. Just over half of respondents to the survey were on fixed-term contracts and, traditionally, publishing papers is important for career advancement, while even established researchers depend on their publication record in winning further research funding. Younger researchers, in particular, valued publishing papers and further employment opportunities (56% and 67%, respectively, of 18–30 year olds valued these skills/opportunities), but publishing was important for many respondents, with several mentioning publishing papers as a motivator for their team, and one respondent describing the motivation to be the ‘Esteem and recognition for good research published, contributing to career development and attraction of further research funding for self-determined research pathways’ (BC project participant, UK). However, tension with these motivations and the aims of building capacity and achieving real impact in communities and how this is recognised for individuals, was also felt, as one respondent described: ‘I’d say some team members are too obsessed with papers as a marker of success, and universities do not sufficiently recognise the value of impact in their promotion criteria’ (BC project participant, UK).

This tension may be driven particularly by the UK side where researchers may feel under more pressure to publish for their career progression and to meet expectations of funding bodies. Fifty-six per cent of UK respondents agreed their career had progressed during the project compared to 87% of SE Asian respondents. One SE Asian respondent noted that ‘I’m now appointed as a Senior Lecturer at a local university, and one thing that got me into this job is because my employer values my networking with the international, multidisciplinary research team of BC’ (BC project participant, Malaysia) indicating that the values in UK universities differ from those that may be found in other cultures [15]. Overall, across almost all markers and at all levels, SE Asian participants reported more positive improvement than UK participants, who only identified improvements due to involvement with the project in, at most, two markers at individual, team or institutional level. Several factors may explain this, for example, the markers given may not capture adequately what UK participants may have benefited from nor what adequately evaluates interdisciplinary aspects of research capacity [21]. However, it could also be that in some cases participants felt capacity building was acting mainly in one direction. For example, only 56% of UK respondents agreed they had been able to answer some of their own research questions compared to 92% of SE Asian respondents. One respondent said ‘Compared to traditional research projects, the career progression opportunities for UK teams may have [conversely] advanced less. The focus was on capacity development, rightly, but this may have inadvertently reduced the scientific innovation and output from UK teams because of the amount of time needed to support the partner teams’ (BC project participant, UK). While UK respondents felt positively about some aspects, for example, 83% agreed that they project managed, if these attributes are not obviously valued in their career pathways, individuals may also not value these highly. Considering that interdisciplinary researchers tend to publish less at first and have greater difficulty in demonstrating research productivity than more traditional researchers [21], the perceived lack of career development in this type of project will only exacerbate the conflict between research aims, building capacity and making an impact. The increasing importance of impact in the UK’s evaluation of higher education providers through evaluations by funding bodies such as the UK Research and Innovation’s (UKRI) Research Excellence Framework and Knowledge Excellence Framework may go some way towards valuing and incentivising researchers who participate in capacity building research.

In some cases, within the project, researchers did prioritise research aims. Other studies of international consortia have reported that researchers in the Global South can feel like ‘data sources’ in that they are not heavily involved in planning or analysing data, but only in commenting on it; that responsibility stays in the North [8]. In the BC project, researchers from both regions were involved in the collection of data to some degree, and it was clear that SE Asian respondents were involved in all aspects of research, from planning, to collecting data, to analysing and interpreting. There were instances throughout the project where SE Asian partners sometimes deferred to UK partners to carry out complex analyses. For example, one respondent observed: ‘Some [sub-]projects, while providing training at annual meetings, ended up doing the analysis for the partners rather than training and then letting partners take ownership of the research. This is reflected in some [sub-]projects not having many papers lead authored by [SE Asian] partners’ (BC project participant, UK). Harvey et al. [8] emphasised the importance of being willing to fail as part of a learning-by-doing process, thus sometimes sacrificing high-impact research outputs to focus on capacity development.

It was unexpected that UK respondents did not feel more strongly that their research capacity improved due to their involvement with the project, in particular in relation to applying and understanding interdisciplinary approaches. A greater understanding of overseas issues was the only marker where all UK respondents identified improvement. This particular marker may encompass a multitude of factors, and it may be that the parameters provided in the survey do not adequately articulate what UK researchers did learn from involvement with the project. It is important to identify these parameters and ensure more active two-way dialogue in future collaborations, so that UK or other participants from HICs are mutually learning from their project partners. Although UK researchers may have seen themselves more in the role of delivering research capacity than receiving it, there are important reasons for mutual learning and capacity strengthening. Just over half of UK researchers identified the project as having an impact in their region. This is not totally unexpected since UK partners were not working directly with local communities as SE Asian partners were. However, there are areas that could have potential impact in the UK. For example, the current discourse in the UK on the need to decolonise the curriculum [26] would clearly benefit from researchers who have experience working with other cultures and introducing this diversity through their teaching and research citations. In addition, researchers working directly with communities in LICs on sustainability issues try to highlight the knowledge that is held in the Global South as ‘the limited Western view of sustainability is stifling progress’ [27]. SE Asian partners instigated a wealth of approaches throughout the project, working creatively with local communities and practitioners. For example, researchers in Indonesia carried out participatory film making with local communities addressing sustainability issues. This resulted in changes in environmental behaviours and the formation of a film making community group dedicated to making audio visual work on behavioural change related to plastic pollution and climate change. Another example from Malaysia saw engagement with local communities resulting in greater attendance to health centres and vaccine uptake. More work is needed to reflect on and recognise the learning of UK partners in this collaboration. However, this may become more apparent over the longer term than at the point this survey was carried out.

There was disparity in resources at organisational level between UK and SE Asia, with less than half of SE Asian respondents scoring their institutions highly for having adequate resources to support staff research training, while 72% of UK respondents reported their organisations were good in this. In other studies, participants have felt that it is important to recognise this organisational inequality to manage expectations and ensure a meaningful partnership [17]. The level of improvement at the institutional level was perceived by SE Asian respondents to be more limited than at the individual level, with improvement in only around half the markers correlating with the current success. Development is still needed at an institutional or organisational level to reduce inequality in these factors, as there can be a lack of investment at higher levels, beyond the individual [8]. Despite this, 79% of SE Asian and 72% of UK respondents felt that they would build upon the international networks and relationships developed through the project.

Many respondents felt lower confidence in submitting health and safety assessments, financial claims and ethics applications, though at an individual level, there were improvements in these for SE Asian respondents, and improvement in financial claims for UK respondents. At the team and institution level, these areas were not perceived to have improved. While not all respondents would have needed to participate in these aspects, and that may explain some of the variability, these aspects may reflect a lack of facilities or support for these within organisations but also that they can be complex administrative processes where rules can be unclear even where facilities are well developed. For example, one respondent mentioned the ‘bureaucracy of financial process’ (BC project participant, Philippines) as a barrier to their team. Additionally, ethics applications are often reviewed by individuals on an ethics committee and responses to applications can depend strongly on the individual reviewers, which can vary from organisation to organisation. Similar studies have also found efficiency of researchers to be inhibited by bureaucracy or technical and administrative support in time-limited research projects [8,17]. This project worked with organisations to develop their ethical approval processes, financial management and risk assessment, and there is variability in these depending on the specific location. One respondent mentioned a team barrier as being ‘lack of administrative support in the initial stage of project’ (BC project participant, Malaysia), indicating that things did improve. Despite lower confidence indicated by respondents on these aspects, from the personal observations of the principal investigator and project manager (authors MA and VC on this paper), there was substantial improvement of SE Asian individual, team and to some extent organisational capacity in financial claims and ethics processes. This project, through learning-by-doing, adapted a flexible approach, to meet the needs of researchers in different countries and organisations and adapt to their specific circumstances. This included, for example, providing advances on funding to allow participants to travel or take part in research activities and circumvent inhibitive administrative processes.

Study limitations

There are limitations to this study, specifically that almost 90% of respondents came from academia, and to fully evaluate a transdisciplinary project, the perspectives of other actors, such as community partners, are also needed [21]. The objectives of other actors, or their perceived markers of success in research capacity needed to reach complex sustainability goals, are likely to differ from those with an academic focus, such as in terms of how capacity may translate to making an impact in communities, and this has not been captured in the responses to this survey.

The survey was only available in the English language, and this would have excluded some potential respondents. It is likely that the response to the English language acting as a barrier is an underestimate for this project, and ideally the survey would be translated to local languages to reach and get perspectives of all participants. For example, Indonesian respondents were underrepresented in the survey, and we are aware that some of the participants from Indonesia would have been restricted by the language barrier as they are non-English speakers. The BC project largely operated through English and non-English speakers relied on information being passed on by their colleagues. From this survey, we cannot say to what degree this knowledge transfer benefitted non-English speakers or if their research capacity improved. Future work should aim to assess this. Projects should ensure that local researchers form part of capacity building teams, and that ways to deliver knowledge and capacity in local languages are embedded within projects.

A longer-term assessment of research capacity will be required to evaluate if it has sustained into the future beyond the life of the project [14,28]. A key measure of research capacity is if it is lasting and if it can spread more widely in society. While this survey captured respondents’ perspectives at a specific time, just as the project was ending, this perspective could change over time, following experiences with transferring skills and knowledge to other projects or work.

Lessons learnt and implications for future projects

This study provides a broader perspective on the success of a learning-by-doing approach to building research capacity than focussing on research outputs such as publications and funding alone. There are key lessons emerging from the outputs of this study that can be used to enhance or modify approaches used for capacity building in future collaborations:

  • Identify the benefits that partners that are in the role of delivering research capacity training may receive from such partnerships, and the parameters to measure these benefits, to ensure that these are clearly recognised and therefore can be valued and incentivised in career paths.

  • Explicitly address power imbalances. This can look like, at leadership level, deciding on a strategy that prioritises certain groups to be supported in leading research and publications, for example, researchers from LICs and early career researchers. This could also include taking a flexible approach and providing additional support for administration, for example, finance, ethics.

  • Develop concrete tools/training that can be taught to and applied by participants within the time of the project, so that skills can then be passed on locally by those participants.

  • From the outset, put effort into building relationships and establishing trust between partners. In the BC project, this was established through (i) sharing roles and responsibilities, for example, holding the kick-off meeting in SE Asia, co-organised by partners there, and early scheduling of presentations from all partners; (ii) establishing an inclusive project culture, for example, mixing of groups, listening, all questions valid, patience and understanding; (iii) finding common interests, for example, social interaction around food from different cultures; and (iv) maintaining communication, for example, with follow-up in-person and online meetings.

Conclusions

There is currently a difficult balance between undertaking innovative interdisciplinary research that has societal impact and building sustainable research capacity. In this case, the BC project partners that responded to this survey perceived that the project achieved advances in all of these areas. This may provide lessons for other interdisciplinary research collaborations and capacity building efforts. The BC approach placed a strong emphasis on building relationships from the inception of and throughout the project, through a collaborative learning-by-doing process, that kept people enthusiastic and engaged to the end. However, gaps were identified by respondents in scientific innovation and in particular aspects of research capacity, and much of this may have arisen from trying to achieve what can be seen as conflicting aims. Despite the project recognising the importance of interactive dialogue and not just one-way training, for mutual capacity building [25], UK respondents reported less capacity built across most parameters. While this needs further investigation and other factors may come into play, this may in part be driven by the values of UK organisations. Institutions are responsible for incentivising individuals’ actions [9]. Currently, the incentives around research and career progression within research, particularly amongst HICs, are focused on publishing papers, and interdisciplinary researchers face challenges in having their achievements and skills recognised in traditional academic career paths [2931]. Institutions and employers need to increase their efforts to place greater value on the contributions people make in the areas of strengthening capacity and making societal impact, giving it equal or higher value to research publications. This is essential to mobilising interdisciplinary and transdisciplinary research to solve global challenges and achieve long-term sustainability.

Notes

  1. The Global Challenges Research Fund (GCRF) is a UK fund that promotes achievement of the UN SDGs in developing countries, through supporting international research. It is part of the UK’s Official Development Assistance (ODA) programme that aims to promote sustainable growth of the Organisation for Economic Cooperation and Development (OECD) selected developing countries. https://royalsociety.org/~/media/grants/schemes/ODA-GCRF.pdf?la=en-GB&hash=B51F1E2140346184856E2F87D6F4B32A.
  2. https://www.plymouth.ac.uk/research/institutes/marine-institute/our-research/blue-communities.
  3. https://rawgraphs.io/.

Acknowledgements

Thanks to all participants of the BC project who responded to the survey. Thanks to Carla-Leanne Washbourne and Keisuke Okamura for reviewing previous drafts of this paper.

Authorship contribution

All authors conceived the study. FC adapted a pre-developed survey for the current situation and all authors reviewed the survey. FC carried out the data collection, analysis and prepared the original draft. All authors reviewed and edited the manuscript for publication.

Open data and materials availability statement

The datasets generated during and/or analysed during the current study are available in the repository: https://www.doi.org/10.5255/UKDA-SN-856101.

Declarations and conflicts of interest

Research ethics statement

The authors declare that research ethics approval for this article was provided by the University of Plymouth ethics board with written support obtained from leaders of each institution where participants are based.

Consent for publication statement

The authors declare that research participants’ informed consent to publication of findings – including photos, videos and any personal or identifiable information – was secured prior to publication. Consent for this study was obtained from survey respondents on the basis that their anonymity and confidentiality is protected.

Conflicts of interest statement

The authors declare the following interests: Author MA was the Principal Investigator; VC was the Project Manager; and FC was a Research Fellow in Blue Communities.

References

[1]  IPCC. Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse Gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. IPCC.

[2]  UN. United Nations General Assembly: Transforming Our World: The 2030 Agenda for Sustainable Development. Draft resolution referred to the United Nations summit for the adoption of the post-2015 development agenda by the General Assembly at its sixty-ninth session, UN Doc. A/70/L.1 of 18 September 2015.

[3]  Biermann, F; Kanie, N; Kim, RE. (2017).  Global governance by goal-setting: the novel approach of the UN Sustainable Development Goals.  Curr Opin Environ Sust 26–27 : 26–31, Available from. DOI: http://dx.doi.org/10.1016/j.cosust.2017.01.010

[4]  Fransman, J; Hall, B; Hayman, R; Narayanan, P; Newman, K; Tandon, R. (2021).  Beyond partnerships: embracing complexity to understand and improve research collaboration for global development.  Can J Dev Stud 42 : 326–346, Available from. DOI: http://dx.doi.org/10.1080/02255189.2021.1872507

[5]  Dangles, O; Loirat, J; Freour, C; Serre, S; Vacher, J; Le Roux, X. (2016).  Research on biodiversity and climate change at a distance: collaboration networks between Europe and Latin America and the Caribbean.  PLoS One 11 e0157441 Available from. DOI: http://dx.doi.org/10.1371/journal.pone.0157441

[6]  Barrett, AM; Crossley, M; Dachi, HA. (2011).  International collaboration and research capacity building: learning from the EdQual experience.  Comp Educ 47 : 25–43, Available from. DOI: http://dx.doi.org/10.1080/03050068.2011.541674

[7]  Karlsson, S; Srebotnjak, T; Gonzales, P. (2007).  Understanding the North–South knowledge divide and its implications for policy: a quantitative analysis of the generation of scientific knowledge in the environmental sciences.  Environ Sci Policy 10 : 668–684, Available from. DOI: http://dx.doi.org/10.1016/j.envsci.2007.04.001

[8]  Harvey, B; Huang, Y-S; Araujo, J; Vincent, K; Sabiiti, G. (2022).  Breaking vicious cycles? A systems perspective on Southern leadership in climate and development research programmes.  Clim Dev 14 (7) : 1–12, Available from. DOI: http://dx.doi.org/10.1080/17565529.2021.2020614

[9]  Woodhill, J. (2010).  Capacities for institutional innovation: a complexity perspective.  IDS Bull 41 : 47–59.

[10]  Hattam, C; Broszeit, S; Langmead, O; Praptiwi, RA; Ching Lim, V; Creencia, LA. (2021).  A matrix approach to tropical marine ecosystem service assessments in South east Asia.  Ecosyst Serv 51 101346 Available from. DOI: http://dx.doi.org/10.1016/j.ecoser.2021.101346

[11]  Hammad, W; Al-Ani, W. (2021).  Building educational research capacity: challenges and opportunities from the perspectives of faculty members at a national university in oman.  SAGE Open 11 21582440211032668 Available from. DOI: http://dx.doi.org/10.1177/21582440211032668

[12]  UNEP. Capacity Building for Sustainable Development: an overview of UNEP environmental capacity development initiatives,

[13]  Chu, KM; Jayaraman, S; Kyamanywa, P; Ntakiyiruta, G. (2014).  Building research capacity in Africa: equity and global health collaborations.  PLoS Med 11 (3) e1001612 Available from. DOI: http://dx.doi.org/10.1371/journal.pmed.1001612

[14]  Hewitson, B. (2015).  To build capacity, build confidence.  Nat Geosci 8 : 497–499, Available from. DOI: http://dx.doi.org/10.1038/ngeo2465

[15]  Hoang, CH. (2021).  Glocal production of knowledge: exploring Vietnamese scholars’ perception of ‘good’ research.  Compare 53 (1) : 123–141, Available from. DOI: http://dx.doi.org/10.1080/03057925.2021.1884046

[16]  Cheung, VV; Bell, A; Creencia, LA; Fleming, LE; Goh, HC; Maharja, C. (2021).  Blue communities in Southeast Asia.  Environ Sci 30 : 96–102.

[17]  Grieve, T; Mitchell, R. (2020).  Promoting meaningful and equitable relationships? Exploring the UK’s global challenges research fund (GCRF) funding criteria from the perspectives of African partners.  Eur J Dev Res 32 : 514–528, Available from. DOI: http://dx.doi.org/10.1057/s41287-020-00274-z

[18]  Holden, L; Pager, S; Golenko, X; Ware, RS. (2012).  Validation of the research capacity and culture (RCC) tool: measuring RCC at individual, team and organisation levels.  Aust J Prim Health 18 : 62–67, Available from. DOI: http://dx.doi.org/10.1071/PY10081

[19]  Wickham, H. (2009).  ggplot2: Elegant graphics for data analysis. New York: Springer-Verlag.

[20]  R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available from: https://www.R-project.org/.

[21]  Steelman, T; Bogdan, A; Mantyka-Pringle, C; Bradford, L; Reed, MG; Baines, S. (2021).  Evaluating transdisciplinary research practices: insights from social network analysis.  Sustain Sci 16 : 631–645, Available from. DOI: http://dx.doi.org/10.1007/s11625-020-00901-y

[22]  Mcclure, A. (2020).  Inclusive, participatory and reflexive learning processes for climate resilience: key lessons from FRACTAL. FRACTAL Working Paper #9.

[23]  Zain, MA; Suhaimi, J; Dahlui, M; Goh, HC; Then, AY-H; Yakub, NA. (2022).  What are the outcomes of marine site protection on poverty of coastal communities in Southeast Asia? A systematic review protocol.  Environ Evid 11 : 2. Available from. DOI: http://dx.doi.org/10.1186/s13750-022-00255-1

[24]  Nguyen, PT; Duong, ML; Eales, J. (2020).  What is the influence on socio-economic well-being of UNESCO biosphere reserves in Southeast Asia? A systematic review protocol.  Zenodo, Available from. DOI: http://dx.doi.org/10.5281/zenodo.4136658

[25]  Richter, I; Gabe-Thomas, E; Maharja, C; Nguyen, TH; Van Nguyen, Q; Praptiwi, R. (2021).  Virtual capacity building for international research collaborations in times of COVID-19 and #Flygskam.  Front Commun 5 562828 Available from. DOI: http://dx.doi.org/10.3389/fcomm.2020.562828

[26]  Schucan Bird, K; Pitman, L. (2020).  How diverse is your reading list? Exploring issues of representation and decolonisation in the UK.  High Educ 79 : 903–920, Available from. DOI: http://dx.doi.org/10.1007/s10734-019-00446-9

[27]  Nagendra, H. (2018).  The global south is rich in sustainability lessons that students deserve to hear.  Nature 557 : 485–488, Available from. DOI: http://dx.doi.org/10.1038/d41586-018-05210-0

[28]  Vallejo, B; Wehn, U. (2016).  Capacity development evaluation: the challenge of the results agenda and measuring return on investment in the global South.  World Dev 79 : 1–13, Available from. DOI: http://dx.doi.org/10.1016/j.worlddev.2015.10.044

[29]  Radinger-Peer, V; Schauppenlehner-Kloyber, E; Penker, M; Gugerell, K. (2022).  Different perspectives on a common goal? The Q-method as a formative assessment to elucidate varying expectations towards transdisciplinary research collaborations.  Sustain Sci 17 : 2459–2472, Available from. DOI: http://dx.doi.org/10.1007/s11625-022-01192-1

[30]  Fam, D; Clarke, E; Freeth, R; Derwort, P; Klaniecki, K; Kater-Wettstädt, L. (2020).  Interdisciplinary and transdisciplinary research and practice: balancing expectations of the ‘old’ academy with the future model of universities as ‘problem solvers’.  High Educ Q 74 : 19–34, Available from. DOI: http://dx.doi.org/10.1111/hequ.12225

[31]  Guimarães, MH; Pohl, C; Bina, O; Varanda, M. (2019).  Who is doing inter- and transdisciplinary research, and why? An empirical study of motivations, attitudes, skills, and behaviours.  Futures 112 102441 Available from. DOI: http://dx.doi.org/10.1016/j.futures.2019.102441

Appendix

Appendix A: Survey questions

(note: numbers refer to the corresponding numbers in the open access data file)

Filter questions:

7. Do you currently or have you previously carried out research as part of the Blue Communities project?

Yes/No

Section 1: Demographic questions

8. What is your gender? Male/Female/Prefer not to say

9. What is your age group? 18–30; 31–50; 51–64; 65+; Prefer not to say

10. What sector do you work in? Academia, NGO, other (please state if other)

11. What research experience do you have? Undergraduate degree; Current Masters student; Researcher (post Masters, no PhD); PhD student; </ = 5 years post PhD; >5–15 years post PhD; >15 years post PhD; other

12. What is your contract type at your institution? Fixed Term; Permanent

13. In which country is your main institution located? Indonesia; Malaysia; Philippines; United Kingdom; Vietnam

14. Choose the option that best describes your association with the Blue Communities project (for the majority of the time you have worked on the project):

  • I work only on the Blue Communities project or Blue Communities is my main research project

  • My time is divided amongst multiple research projects, of which Blue Communities is one

  • Blue Communities is my only research project, but I also have other work commitments such as teaching or administrative work

  • My time is divided amongst multiple research projects, of which Blue Communities is one and I also have other work commitments such as teaching or administrative work

  • None of these options describe my association with the Blue Communities project

Section 2: Individual level

15. Please indicate any research activity you are currently involved with or have been involved with as part of Blue Communities. Tick as many as apply

  • Writing a research report, presentation or paper for publication

  • Writing a research protocol or designing a study

  • Submitting an ethics application

  • Submitting a health and safety assessment

  • Collecting data, e.g., surveys, interviews

  • Data management

  • Analysing qualitative research data

  • Analysing quantitative research data

  • Writing a literature review

  • Applying for research funding

  • Networking

  • Project management

  • Interdisciplinary research approaches and issues

  • Secured research funding

  • Co-authored a paper for publications

  • Presented research findings at a conference

  • Submitted financial claims from a research grant

  • Other

16.

  1. Based on your perception, rate your personal current success or skill level for each of the following aspects (1 = no success/skill and 9 = highest possible success/skill): 1–9/unsure

  2. And secondly, say whether you think this aspect has changed as a result of involvement with the Blue Communities project (on a scale of much worse – worse – no change – better – much better/unsure)

    16.1 Finding relevant literature
    16.2 Critically reviewing the literature
    16.3 Using a computer referencing system (e.g., Endnote)
    16.4 Writing a research protocol or designing a study
    16.5 Securing research funding
    16.6 Submitting an ethics application
    16.7 Submitting a health and safety assessment
    16.8 Submitting financial claims from a research grant
    16.9 Designing questionnaires
    16.10 Collecting data, e.g., surveys, interviews
    16.11 Using computer data management systems
    16.12 Analysing qualitative research data
    16.13 Analysing quantitative research data
    16.14 Writing a research report
    16.15 Writing for publication in peer-reviewed journals
    16.16 Providing advice to less experienced researchers
    16.17 Understanding interdisciplinary approaches and issues
    16.18 Understanding overseas issues and challenges
    16.19 Applying for research funding/writing research grants
    16.20 Networking
    16.21 Managing a project
    16.22 Presenting research findings

17. Which of the following resources have you benefited from through the Blue Communities partnership? Tick all that apply

  • Software

  • Research supervision

  • Time to undertake research

  • Research funds

  • Administrative support

  • Training

  • Library access (including online library access)

  • Protocol development

  • Access to expertise

  • Database development and management

  • Health and safety guidance

  • Research ethics guidance

  • Seminars

  • Networking meetings

  • Mentorship

  • Other (please state)

18. What research skills or opportunities do you value the most from your experience in Blue Communities? Tick up to three responses

Publishing papers; Writing successful research grants; Developing a positive attitude to research; Further employment opportunities; Subject understanding and knowledge; Confidence; Specialist technical skills and knowledge; International collaboration; Project management; Opportunity to present and disseminate work; Sharing ideas; Transdisciplinary work; Access to mentors; Other

19. What are the barriers to research for you personally? Tick all that apply

  • Lack of time for research

  • Lack of suitable backfill (someone to fill your other work commitments)

  • Other work roles take priority

  • Lack of funds for research

  • Lack of support from management

  • Lack of suitable supervision/mentorship

  • Lack of access to equipment for research

  • Lack of administrative support

  • Lack of software for research

  • Isolation

  • Lack of library/internet access

  • Personal motivations

  • Other personal commitments

  • Desire for work/life balance

  • Lack of a co-ordinated approach to research

  • Lack of skills for research

  • Intimidated by research language

  • Intimidated by fear of getting it wrong

  • English language

  • Covid-19 pandemic restrictions

  • Availability of trained staff to consult or collaborate with

  • Internet connectivity

  • Lack of long-term employment

  • Other (please state)

20. What are your motivators to conduct research for you personally? Tick all that apply

  • To develop skills

  • Career advancement

  • Increased job satisfaction

  • Study or research scholarships available

  • Dedicated time for research

  • Research written into role description

  • Colleagues are doing research

  • Research encouraged by managers

  • Grant funds

  • Links to universities

  • Forms part of post graduate study

  • Opportunities to participate at own level

  • Problem identified that needs changing (e.g., improving something your local community, benefitting environment, etc.)

  • Desire to prove a theory/hunch, science curiosity

  • To keep the brain stimulated

  • Increased credibility

  • Other

21. State how much you agree or disagree with the following statements as a result of your involvement in the Blue Communities programme (Rating scale):

21.1 The research I carried out during Blue Communities was relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.) in my region
21.2 I had the opportunity to lead research work and/or contribute ideas that directed the research
21.3 I learned new technical specialist skills
21.4 I have had the opportunity to be the lead author on one/more than one publication
21.5 I project-managed
21.6 I did not have time to learn all that I might have during Blue Communities
21.7 I wrote new research grants during my time on Blue Communities
21.8 I worked with interdisciplinary teams
21.9 I felt some types of training were missing from the Blue Communities project
21.10 I feel positive about working with people from different disciplines in the future
21.11 I have been able to answer some of my own research questions
21.12 I will build upon the international networks and professional relationships that have been developed through the Blue Communities programme
21.13 I could have led more work than I did during the Blue Communities project
21.14 I think I will have more opportunities available to enhance my future career as a result of the work I have conducted for the Blue Communities programme
21.15 My career level has progressed as a result of my involvement in Blue Communities
21.16 I thought the Blue Communities research could have been more interdisciplinary
21.17 My institution rewards or recognises my achievements linked to Blue Communities

Section 3: Team level

22.

  1. Based on your perception, rate your Blue Community team’s (at your own institute) current success or skill level for each of the following aspects (1 = no success/skill and 9 = highest possible success/skill): 1–9/unsure

  2. And secondly, say whether you think this aspect has improved as a result of involvement with the Blue Communities project (on a scale of much worse – worse – no change – better – much better/unsure)

    22.1 Has adequate resources to support staff research training
    22.2 Has funds, equipment or admin to support research activities
    22.3 Does team level planning for research development
    22.4 Ensures staff involvement in developing that plan
    22.5 Has team leaders that support research
    22.6 Provides opportunities to get involved in research
    22.7 Does planning that is guided by evidence
    22.8 Conducts research activities relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.)
    22.9 Supports applications for research scholarships/degrees
    22.10 Has mechanisms to monitor research quality
    22.11 Has experts accessible for research advice
    22.12 Disseminates research results at research forums/seminars
    22.13 Supports an interdisciplinary approach to research
    22.14 Has incentives and support for mentoring activities
    22.15 Has external partners (e.g., government agencies, communities, public) engaged in research activities/planning
    22.16 Supports the peer-reviewed publication of research
    22.17 Has software available to support research activities
    22.18 Has adequate ethics support and planning
    22.19 Has adequate health and safety support and planning
    22.20 Has adequate data management support and planning
    22.21 Has adequate finance management support and planning

23. What are the biggest barriers to research in your team? Free text

24. What are the biggest motivators to research in your team? Free text

Section 4: Organisation level

25.

  1. For each aspect, firstly rate your perception of your organisation’s (e.g., your University, Research Centre, NGO, etc.) success or skill level (1 = no success/skill and 9 = highest possible success/skill): 1–9/unsure

  2. And secondly, say whether you think this aspect has improved as a result of involvement with the Blue Communities project (on a scale of much worse – worse – no change – better – much better/unsure)

    25.1 Has adequate resource to support staff research training
    25.2 Has funds, equipment or admin to support research activities
    25.3 Has a plan or policy for research development
    25.4 Has senior managers that support research
    25.5 Ensures staff career pathways are available in research
    25.6 Ensures organisational planning is guided by evidence
    25.7 Access external funding for research
    25.8 Encourages research activities relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.)
    25.9 Has software programs for analysing research data
    25.10 Has mechanisms to monitor research quality
    25.11 Has experts accessible for research advice
    25.12 Supports interdisciplinary approaches to research
    25.13 Has regular forums/bulletins to present research findings
    25.14 Engages external partners (e.g., government agencies, communities, public) in research activities/planning
    25.15 Supports applications for research scholarship/degrees
    25.16 Supports the peer-reviewed publication of research
    25.17 Has adequate ethics support and planning
    25.18 Has adequate health and safety support and planning
    25.19 Has adequate data management support and planning
    25.20 Has adequate finance management support and planning

26. Any other comments: Free text

Appendix B: Tables

Table A1.

Significant associations are highlighted between demographic variables based on Fisher’s exact test

Demographic variable Category Fisher’s exact test p value Note
Gender Age 0.009 More younger people are female
Experience/Career stage 0.581
Contract 0.749
Country 0.083
Region 0.070
Age Experience/Career stage 0.004 Older people have more experience
Contract 0.142
Country 0.432
Region 0.429
Experience Contract 0.063
Country 0.008 People with less experience more likely to be from Asia but experienced people from both
Region 0.017 People with less experience more likely to be from Asia but experienced people from both
Contract Country 0.317
Region 0.517
Table A2.

Significant associations are highlighted between individual level questions (linked to Figs 15 in the main text) with demographic variables based on Fisher’s exact test

Question Demographic variable Fisher’s exact test p value
Research Activity (Fig. 1) Gender (removed ‘prefer not to say’) 0.987
Age (removed ‘prefer not to say’) 0.984
Experience [Very small categories combined, i.e., Undergraduate + Current MSc student; Post MSc (no PhD) + PhD student] 1.000
Contract type 0.998
Country 1.000
Region 0.811
Resources (Fig. 2) Gender (removed ‘prefer not to say’). 0.950
Age (removed ‘prefer not to say’) 0.973
Experience [Very small categories combined i.e., Undergraduate + Current MSc student; Post MSc (no PhD) + PhD student] 1.000
Contract type 0.985
Country 0.981
Region 0.002
Research skills and opportunities valued (Fig. 3) Gender (removed ‘prefer not to say’) 0.116
Age (removed ‘prefer not to say’) 0.023
Experience [Very small categories combined i.e., Undergraduate + Current MSc student; Post MSc (no PhD) + PhD student] 0.276
Contract type 0.089
Country 0.030
Region 0.005
Barriers to research (Fig. 4) Gender (removed ‘prefer not to say’) 0.365
Age (removed ‘prefer not to say’) 0.131
Experience [Very small categories combined i.e., Undergraduate + Current MSc student; Post MSc (no PhD) + PhD student] 0.949
Contract type 0.009
Country 0.015
Region 0.001
Motivators (Fig. 5) Gender (removed ‘prefer not to say’) 0.932
Age (removed ‘prefer not to say’) 0.639
Experience [Very small categories combined i.e., Undergraduate + Current MSc student; Post MSc (no PhD) + PhD student] 0.946
Contract type 0.552
Country 0.943
Region 0.340
Table A3.

Significant associations are highlighted between individual level questions (linked to Fig. 6 in the main text) with demographic variables based on Fisher’s exact test

Demographic variable Letter code Statement Fisher’s exact test p value Notes
Age A Relevant for impact 0.297
B Rewarded by institution 0.472
C Career progressed 0.192
D Wrote grants 0.812
E Interdisciplinary teams 0.011 Almost everyone agreed with this, older researchers agreed more strongly
F Carry on relationships 0.051
G Lacking interdisciplinarity 0.358
H Future career opportunities 0.052
I Project managed 0.047 Those in older age categories agreed with this while others showed a range of responses
J Technical skills 0.113
K Lead a publication 0.013 The youngest age category disagreed with this statement, while most others agreed
L My own research questions 0.105
M Lead research 0.209
N Training missing 0.100
O Positive interdisciplinary working 0.044 Most strongly agreed with this, one group who preferred not to say their age were neutral/unsure
P Lack of time 0.274
Q Could have led more 0.094
Career/Experience A Relevant for impact 0.212
B Rewarded by institution 0.295
C Career progressed 0.397
D Wrote grants 0.836
E Interdisciplinary teams 0.559
F Carry on relationships 0.894
G Lacking interdisciplinarity 0.136
H Future career opportunities 0.848
I Project managed 0.259
J Technical skills 0.196
K Lead a publication 0.021 Most individuals from all career stage groups agreed with this, but individuals from the most experienced group and from the least experienced groups disagreed
L My own research questions 0.115
M Lead research 0.828
N Training missing 0.668
O Positive interdisciplinary working 0.270
P Lack of time 0.803
Q Could have led more 0.048 PhD students and the most experienced researchers agreed that they could have led more
Contract A Relevant for impact 0.238
B Rewarded by institution 0.103
C Career progressed 0.847
D Wrote grants 0.932
E Interdisciplinary teams 0.671
F Carry on relationships 0.438
G Lacking interdisciplinarity 0.221
H Future career opportunities 0.476
I Project managed 0.362
J Technical skills 0.440
K Lead a publication 0.692
L My own research questions 0.508
M Lead research 0.236
N Training missing 0.100
O Positive interdisciplinary working 1.000
P Lack of time 0.799
Q Could have led more 0.477
Gender A Relevant for impact 0.076
B Rewarded by institution 0.369
C Career progressed 0.227
D Wrote grants 0.033 More males were neutral on this aspect, while females wither strongly disagreed or agreed and strongly agreed
E Interdisciplinary teams 0.045 More males strongly agree with this, while females mostly agreed or strongly agreed
F Carry on relationships 0.463
G Lacking interdisciplinarity 0.449
H Future career opportunities 0.038 More males strongly agree with this, while females mostly agreed or strongly agreed
I Project managed 0.789
J Technical skills 0.178
K Lead a publication 0.602
L My own research questions 0.152
M Lead research 0.957
N Training missing 0.491
O Positive interdisciplinary working 0.005 More males strongly agree with this, while females mostly agreed or strongly agreed
P Lack of time 0.456
Q Could have led more 0.104
Region A Relevant for impact 0.001 SE Asia researchers mostly strongly agreed, more UK researchers gave a neutral response
B Rewarded by institution 0.818
C Career progressed 0.041 SE Asia researchers mostly strongly agreed, more UK researchers gave a neutral response
D Wrote grants 0.104
E Interdisciplinary teams 1.000
F Carry on relationships 0.374
G Lacking interdisciplinarity 0.206
H Future career opportunities 0.016 SE Asia researchers mostly strongly agreed, more UK researchers gave a neutral response
I Project managed 0.535
J Technical skills 0.001 SE Asia researchers mostly strongly agreed, more UK researchers gave a neutral response
K Lead a publication 0.113
L My own research questions 0.009 SE Asia researchers mostly strongly agreed, more UK researchers gave a neutral response
M Lead research 0.600
N Training missing 0.665
O Positive interdisciplinary working 0.512
P Lack of time 0.603
Q Could have led more 0.043 SE Asia researchers mostly responded neutrally, while UK researchers gave a range of responses here, but none strongly agreed
Table A4.

Codes, full statement and percentage level of agreement associated with Fig. 6 in the main text

Letter code given in Fig. 6 Full statement associated with code Group Level of agreement as percentage of group
Strongly disagree Disagree Neutral Agree Strongly agree Don’t know
A The research I carried out during Blue Communities was relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.) in my region Full Group 3.6 0.0 12.5 35.7 48.2 0.0
UK/Other European 5.6 0.0 38.9 44.4 11.1 0.0
SE Asia 2.6 0.0 0.0 31.6 65.8 0.0
B My institution rewards or recognises my achievements linked to BC Full Group 7.1 1.8 25.0 32.1 26.8 7.1
UK/Other European 5.6 5.6 27.8 27.8 33.3 0.0
SE Asia 7.9 0.0 23.7 34.2 23.7 10.5
C My career level has progressed as a result of my involvement in BC Full Group 1.8 1.8 19.6 32.1 44.6 0.0
UK/Other European 0.0 5.6 38.9 27.8 27.8 0.0
SE Asia 2.6 0.0 10.5 34.2 52.6 0.0
D I wrote new research grants during my time on BC Full Group 7.1 14.3 23.2 19.6 33.9 1.8
UK/Other European 16.7 16.7 5.6 33.3 27.8 0.0
SE Asia 2.6 13.2 31.6 13.2 36.8 2.6
E I worked with interdisciplinary teams Full Group 1.8 0.0 5.4 25.0 66.1 1.8
UK/Other European 0.0 0.0 11.1 22.2 61.1 5.6
SE Asia 2.6 0.0 2.6 26.3 68.4 0.0
F I will build upon the international networks and professional relationships that have been developed through the BC programme Full Group 0.0 1.8 17.9 26.8 50.0 3.6
UK/Other European 0.0 0.0 16.7 38.9 33.3 11.1
SE Asia 0.0 2.6 18.4 21.1 57.9 0.0
G I thought the BC research could have been more interdisciplinary Full Group 7.1 28.6 23.2 19.6 17.9 3.6
UK/Other European 5.6 50.0 0.0 11.1 22.2 11.1
SE Asia 7.9 18.4 34.2 23.7 15.8 0.0
H I think I will have more opportunities available to enhance my future career as a result of the work I have conducted for the BC programme Full Group 1.8 1.8 10.7 33.9 51.8 0.0
UK/Other European 0.0 5.6 27.8 33.3 33.3 0.0
SE Asia 2.6 0.0 2.6 34.2 60.5 0.0
I I project-managed Full Group 7.1 1.8 14.3 39.3 37.5 0.0
UK/Other European 11.1 0.0 5.6 50.0 33.3 0.0
SE Asia 5.3 2.6 18.4 34.2 39.5 0.0
J I learned new technical specialist skills Full Group 1.8 1.8 12.5 37.5 46.4 0.0
UK/Other European 0.0 5.6 33.3 55.6 5.6 0.0
SE Asia 2.6 0.0 2.6 28.9 65.8 0.0
K I have had the opportunity to be the lead author on one/more than one publication Full Group 7.1 7.1 17.9 19.6 48.2 0.0
UK/Other European 5.6 16.7 27.8 22.2 27.8 0.0
SE Asia 7.9 2.6 13.2 18.4 57.9 0.0
L I have been able to answer some of my own research questions Full Group 0.0 3.6 16.1 39.3 41.1 0.0
UK/Other European 0.0 5.6 38.9 27.8 27.8 0.0
SE Asia 0.0 2.6 5.3 44.7 47.4 0.0
M I had the opportunity to lead research work and/or contribute ideas that directed the research Full Group 3.6 1.8 5.4 28.6 60.7 0.0
UK/Other European 0.0 0.0 11.1 33.3 55.6 0.0
SE Asia 5.3 2.6 2.6 26.3 63.2 0.0
N I felt some types of training were missing from the BC project Full Group 5.4 26.8 37.5 19.6 5.4 5.4
UK/Other European 0.0 50.0 22.2 16.7 5.6 5.6
SE Asia 7.9 15.8 44.7 21.1 5.3 5.3
O I feel positive about working with people from different disciplines in the future Full Group 0.0 1.8 5.4 17.9 73.2 1.8
UK/Other European 0.0 0.0 11.1 11.1 72.2 5.6
SE Asia 0.0 2.6 2.6 21.1 73.7 0.0
P I did not have time to learn all that I might have during BC Full Group 5.4 12.5 17.9 42.9 21.4 0.0
UK/Other European 0.0 5.6 16.7 55.6 22.2 0.0
SE Asia 7.9 15.8 18.4 36.8 21.1 0.0
Q I could have led more work than I did during the BC project Full Group 14.3 17.9 30.4 30.4 7.1 0.0
UK/Other European 16.7 33.3 11.1 38.9 0.0 0.0
SE Asia 13.2 10.5 39.5 26.3 10.5 0.0
Table A5.

Significant associations are highlighted between individual level questions (linked to Fig. 7 in the main text) with demographic variables based on Fisher’s exact test

Demographic variable Letter code Aspect of research capacity Success level Fisher’s exact test p value Improvement level Fisher’s exact test p value Explanatory notes
Age A Qualitative analysis 0.378 0.497
B Quantitative analysis 0.150 0.900
C Apply funding 0.386 0.578
D Data collection 0.048 0.178 31–50-year-olds scored better overall
E Review literature 0.036 0.789 Older age categories scored better
F Questionnaires 0.360 0.573
G Finding literature 0.062 0.185
H Manage a project 0.283 0.597
I Networking 0.816 0.538
J Present research 0.408 0.139
K Provide advice 0.204 0.253
L Secure grants 0.789 0.217
M Health and safety 0.854 0.638
N Ethics 0.470 0.292
O Finance claims 0.795 0.378
P Interdisciplinary approaches 0.669 0.585
Q Overseas issues 0.589 0.438
R Referencing system 0.552 0.852
S Data management 0.114 0.571
T Protocol or study design 0.600 0.664
U Research report 0.226 0.490
V Publication 0.344 0.502
Career A Qualitative analysis 0.555 0.827
B Quantitative analysis 0.228 0.409
C Apply funding 0.418 0.737
D Data collection 0.439 0.269
E Review literature 0.108 0.176
F Questionnaires 0.502 0.895
G Finding literature 0.015 0.056 More early career researchers (up to PhD student) scored themselves lower on this
H Manage a project 0.263 0.997
I Networking 0.928 0.191
J Present research 0.813 0.961
K Provide advice 0.175 0.413
L Secure grants 0.077 0.141
M Health and safety 0.201 0.409
N Ethics 0.695 0.295
O Finance claims 0.283 0.994
P Interdisciplinary approach… 0.535 0.872
Q Overseas issues 0.257 0.398
R Referencing system 0.165 0.058
S Data management 0.266 0.937
T Protocol or study design 0.866 0.965
U Research report 0.172 0.407
V Publication 0.037 0.640 More early career researchers (up to PhD student) scored themselves lower on this
Contract A Qualitative analysis 0.894 0.732
B Quantitative analysis 0.961 0.298
C Apply funding 0.365 0.295
D Data collection 0.954 0.148
E Review literature 0.360 1.000
F Questionnaires 0.819 0.582
G Finding literature 0.076 0.557
H Manage a project 0.320 1.000
I Networking 0.143 0.370
J Present research 0.402 0.363
K Provide advice 0.717 1.000
L Secure grants 0.752 0.334
M Health and safety 0.193 0.356
N Ethics 0.871 0.295
O Finance claims 0.199 0.405
P Interdisciplinary approaches 0.193 0.420
Q Overseas issues 0.344 1.000
R Referencing system 0.848 0.106
S Data management 0.622 0.411
T Protocol or study design 0.957 0.536
U Research report 0.589 0.649
V Publication 0.899 0.822
Gender A Qualitative analysis 0.226 0.289
B Quantitative analysis 0.001 0.135 Most males and females scored themselves mid-high on this, but some females scored themselves very low on this
C Apply funding 0.408 0.598
D Data collection 0.294 0.282
E Review literature 0.523 0.110
F Questionnaires 0.328 0.215
G Finding literature 0.850 0.214
H Manage a project 0.552 0.957
I Networking 0.731 0.233
J Present research 0.589 0.654
K Provide advice 0.757 0.431
L Secure grants 0.896 0.339
M Health and safety 0.338 0.509
N Ethics 0.824 0.768
O Finance claims 0.868 0.135
P Interdisciplinary approaches 0.854 0.110
Q Overseas issues 0.092 0.359
R Referencing system 0.217 0.718
S Data management 0.416 0.221
T Protocol or study design 0.755 0.240
U Research report 0.864 0.485
V Publication 0.153 0.633
Region A Qualitative analysis 0.523 0.021 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
B Quantitative analysis 0.351 0.028
C Apply funding 0.371 0.229
D Data collection 0.074 0.001 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
E Review literature 0.688 0.001
F Questionnaires 0.560 0.001
G Finding literature 0.870 0.001
H Manage a project 0.085 0.018
I Networking 0.244 0.001
J Present research 0.446 0.008
K Provide advice 0.955 0.380
L Secure grants 0.605 0.301
M Health and safety 0.090 0.514
N Ethics 0.899 0.124
O Finance claims 0.356 0.135
P Interdisciplinary approaches 0.531 0.001 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
Q Overseas issues 0.444 0.848
R Referencing system 0.287 0.001 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
S Data management 0.687 0.027
T Protocol or study design 0.525 0.083
U Research report 0.887 0.002 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
V Publication 0.818 0.008
Table A6.

Codes and full description of aspect of research capacity associated with Fig. 7 in the main text

Letter code given in Fig. 7 Full research capacity aspect associated with code
A Analysing qualitative research data
B Analysing quantitative research data
C Applying for research funding/writing research grants
D Collecting data, e.g., surveys, interviews
E Critically reviewing the literature
F Designing questionnaires
G Finding relevant literature
H Managing a project
I Networking
J Presenting research findings
K Providing advice to less experienced researchers
L Securing research funding
M Submitting a health and safety assessment
N Submitting an ethics application
O Submitting financial claims from a research grant
P Understanding interdisciplinary approaches and issues
Q Understanding overseas issues and challenges
R Using a computer referencing system (e.g., Endnote)
S Using computer data management systems
T Writing a research protocol or designing a study
U Writing a research report
V Writing for publication in peer-reviewed journals
Table A7.

Significant associations are highlighted between team level questions (linked to Fig. 8 in the main text) with demographic variables based on Fisher’s exact test

Demographic variable Letter code Aspect of research capacity Success level Fisher’s exact test p value Improvement level Fisher’s exact test p value Notes
Age A Impactful research 0.978 0.886
B Disseminates research 0.997 0.658
C Planning with evidence 0.993 0.619
D Team level planning 0.958 0.817
E Staff involved in plans 0.990 0.820
F Data management 0.921 0.500
G Ethics 0.664 0.445
H Finance management 0.894 0.356
I Health and safety 0.942 0.191
J Staff training 0.183 0.867
K Expert advice 0.913 0.896
L External partners 0.911 0.922
M Funds, equipment, admin 0.831 0.541
N Mentoring 0.706 0.945
O Research quality 0.986 0.359
P Software 0.974 0.138
Q Leaders support research 0.931 0.799
R Research opportunities 0.950 0.360
S Interdisciplinary approach 0.957 0.503
T Scholarships 0.100 0.872
U Publication 0.339 0.450
Career A Impactful research 0.733 0.995
B Disseminates research 0.044 0.978 Early career, students and <5 years post PhD scored their teams highly on this
C Planning with evidence 0.418 0.276
D Team level planning 0.586 0.753
E Staff involved in plans 0.700 0.826
F Data management 0.696 0.838
G Ethics 0.104 0.214
H Finance management 0.305 0.695
I Health and safety 0.623 0.333
J Staff training 0.818 0.888
K Expert advice 0.010 0.530 PhD students scored their teams lower on this
L External partners 0.722 0.648
M Funds, equipment, admin 0.431 0.880
N Mentoring 0.283 0.420
O Research quality 0.128 0.821
P Software 0.007 0.352 More experienced researchers scored their teams higher on this than early and mid-career researchers
Q Leaders support research 0.346 0.747
R Research opportunities 0.054 0.808
S Interdisciplinary approach 0.293 0.876
T Scholarships 0.041 0.665 Some early career groups – PhD students and up to 5 years post PhD – scored their teams lower on this than other groups
U Publication 0.388 0.180
Contract A Impactful research 0.386 0.798
B Disseminates research 0.187 0.551
C Planning with evidence 0.647 0.766
D Team level planning 0.592 0.798
E Staff involved in plans 0.494 0.699
F Data management 0.063 0.940
G Ethics 0.946 0.420
H Finance management 0.801 0.724
I Health and safety 0.544 0.191
J Staff training 0.886 0.564
K Expert advice 0.873 0.683
L External partners 0.980 1.000
M Funds, equipment, admin 0.539 0.930
N Mentoring 0.107 0.100
O Research quality 0.703 0.933
P Software 0.035 0.619 Some of those on fixed-term contracts scored their teams lower than those on permanent contracts
Q Leaders support research 0.567 0.929
R Research opportunities 0.733 0.487
S Interdisciplinary approach 0.129 0.742
T Scholarships 0.920 1.000
U Publication 0.522 0.938
Gender A Impactful research 0.905 0.588
B Disseminates research 0.715 0.549
C Planning with evidence 0.622 0.358
D Team level planning 0.685 0.403
E Staff involved in plans 0.547 0.606
F Data management 0.448 0.684
G Ethics 0.101 0.209
H Finance management 0.279 0.271
I Health and safety 0.078 0.870
J Staff training 0.902 0.711
K Expert advice 0.608 0.108
L External partners 0.025 0.916 More male researchers scored their teams lower on this
M Funds, equipment, admin 0.458 0.518
N Mentoring 0.284 0.354
O Research quality 0.842 0.904
P Software 0.171 0.720
Q Leaders support research 0.465 0.839
R Research opportunities 0.917 0.554
S Interdisciplinary approach 0.686 0.267
T Scholarships 0.297 0.188
U Publication 0.074 0.588
Region A Impactful research 0.519 0.024 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
B Disseminates research 0.199 0.001
C Planning with evidence 0.932 0.003
D Team level planning 0.663 0.001
E Staff involved in plans 0.102 0.001
F Data management 0.840 0.001
G Ethics 0.710 0.001
H Finance management 0.629 0.001
I Health and safety 0.651 0.001
J Staff training 0.375 0.003
K Expert advice 0.527 0.001
L External partners 0.100 0.001
M Funds, equipment, admin 0.438 0.001
N Mentoring 0.765 0.020
O Research quality 0.817 0.009
P Software 0.486 0.004
Q Leaders support research 0.290 0.001
R Research opportunities 0.261 0.001
S Interdisciplinary approach 0.239 0.001
T Scholarships 0.503 0.070
U Publication 0.365 0.001 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
Table A8.

Codes and full description of aspect of research capacity associated with Fig. 8 in the main text

Letter code given in Fig. 8 Full research capacity aspect associated with code
A Conducts research activities relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.)
B Disseminates research results at research forums/seminars
C Does planning that is guided by evidence
D Does team level planning for research development
E Ensures staff involvement in developing that plan
F Has adequate data management support and planning
G Has adequate ethics support and planning
H Has adequate finance management support and planning
I Has adequate health and safety support and planning
J Has adequate resources to support staff research training
K Has experts accessible for research advice
L Has external partners (e.g., government agencies, communities, public) engaged in research activities/planning
M Has funds, equipment or admin to support research activities
N Has incentives and support for mentoring activities
O Has mechanisms to monitor research quality
P Has software available to support research activities
Q Has team leaders that support research
R Provides opportunities to get involved in research
S Supports an interdisciplinary approach to research
T Supports applications for research scholarships/degrees
U Supports the peer-reviewed publication of research
Table A9.

Significant associations are highlighted between institution level questions (linked to Fig. 9 in the main text) with demographic variables based on Fisher’s exact test

Demographic variable Letter code Aspect of Research Capacity Success level Fisher’s exact test p value Improvement level Fisher’s exact test p value Notes
Age A External funding 0.893 0.537
B Impactful research 0.501 0.699
C External partners 0.188 0.112
D Planning with evidence 0.139 0.950
E Career pathways 0.382 0.683
F Research development policy 0.861 0.582
G Data management 0.565 0.212
H Ethics 0.667 0.979
I Finance management 0.863 0.290
J Health and safety 0.396 0.962
K Staff training 0.990 0.976
L Experts 0.960 0.322
M Funds, equipment, admin 0.911 0.728
N Research quality 0.698 0.270
O Dissemination 0.755 0.898
P Leaders support research 0.335 0.825
Q Software 0.642 0.386
R Scholarships 0.627 0.954
S Interdisciplinary approach 0.584 0.713
T Publication 0.453 0.612
Career A External funding 0.046 0.485 Early–mid (post MSc up to 15 years post PhD) level were more likely to score their institution lower on this
B Impactful research 0.853 0.455
C External partners 0.074 0.194
D Planning with evidence 0.285 0.372
E Career pathways 0.179 0.453
F Research development policy 0.578 0.938
G Data management 0.551 0.855
H Ethics 0.088 0.498
I Finance management 0.214 0.433
J Health and safety 0.186 0.236
K Staff training 0.199 0.366
L Experts 0.255 0.278
M Funds, equipment, admin 0.693 0.451
N Research quality 0.280 0.722
O Dissemination 0.116 0.533
P Leaders support research 0.702 0.298
Q Software 0.011 0.090 Later career (more than 15 years post PhD) were more likely to score their institution higher on this
R Scholarships 0.236 0.428
S Interdisciplinary approach 0.042 0.772 Later career (more than 15 years post PhD) were more likely to score their institution higher on this
T Publication 0.198 0.688
Contract A External funding 0.672 0.626
B Impactful research 0.807 0.700
C External partners 0.964 0.969
D Planning with evidence 0.185 0.834
E Career pathways 0.233 0.417
F Research development policy 0.300 0.681
G Data management 0.749 0.717
H Ethics 0.864 0.770
I Finance management 0.923 0.717
J Health and safety 0.986 0.435
K Staff training 0.701 1.000
L Experts 0.372 0.897
M Funds, equipment, admin 0.387 0.929
N Research quality 0.838 0.294
O Dissemination 0.541 0.936
P Leaders support research 0.847 0.676
Q Software 0.140 0.237
R Scholarships 0.908 0.454
S Interdisciplinary approach 0.933 0.628
T Publication 0.290 1.000
Gender A External funding 0.630 0.683
B Impactful research 0.298 0.100
C External partners 0.650 0.313
D Planning with evidence 0.449 0.154
E Career pathways 0.553 0.087
F Research development policy 0.765 0.007 Females were more likely to report no improvement on this aspect in their institution
G Data management 0.446 0.115
H Ethics 0.981 0.006 Females were more likely to report no improvement on this aspect in their institution
I Finance management 0.597 0.408
J Health and safety 0.780 0.558
K Staff training 0.976 0.229
L Experts 0.796 0.407
M Funds, equipment, admin 0.822 0.393
N Research quality 0.928 0.479
O Dissemination 0.974 0.854
P Leaders support research 0.971 0.420
Q Software 0.624 0.796
R Scholarships 0.999 0.329
S Interdisciplinary approach 0.590 0.595
T Publication 0.503 0.639
Region A External funding 0.931 0.001 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
B Impactful research 0.879 0.003
C External partners 0.905 0.002
D Planning with evidence 0.960 0.001
E Career pathways 0.762 0.001
F Research development policy 0.932 0.001
G Data management 0.988 0.001
H Ethics 0.501 0.001
I Finance management 0.972 0.001
J Health and safety 0.695 0.001
K Staff training 0.050 0.001 UK researchers were more likely to score a high score (above 7) for their institutions on this. Several SE Asian researchers scored their institutions mid (5–7) on this, though some also scored gave the highest score. SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
L Experts 0.952 0.002 SE Asia researchers indicated higher improvement, while UK researchers indicated no change or lower degree of improvement
M Funds, equipment, admin 0.313 0.001
N Research quality 1.000 0.001
O Dissemination 0.886 0.008
P Leaders support research 0.384 0.001
Q Software 0.806 0.013
R Scholarships 1.000 0.001
S Interdisciplinary approach 0.744 0.002
T Publication 0.888 0.001
Table A10.

Codes and full description of aspect of research capacity associated with Fig. 9 in the main text

Letter code given in Fig. 9 Full research capacity aspect associated with code
A Access external funding for research
B Encourages research activities relevant to creating impact (e.g., making a difference to society, SDGs, local communities, policies, management, etc.)
C Engages external partners (e.g., government agencies, communities, public) in research activities/planning
D Ensures organisational planning is guided by evidence
E Ensures staff career pathways are available in research
F Has a plan or policy for research development
G Has adequate data management support and planning
H Has adequate ethics support and planning
I Has adequate finance management support and planning
J Has adequate health and safety support and planning
K Has adequate resource to support staff research training
L Has experts accessible for research advice
M Has funds, equipment or admin to support research activities
N Has mechanisms to monitor research quality
O Has regular forums/bulletins to present research findings
P Has senior managers that support research
Q Has software programs for analysing research data
R Supports applications for research scholarship/degrees
S Supports interdisciplinary approaches to research
T Supports the peer-reviewed publication of research

 Open peer review from Amartya Nandi

Review

Review information

DOI:: 10.14293/S2199-1006.1.SOR-SOCSCI.AJGR3Y.v1.RQQKHX
License:
This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

ScienceOpen disciplines: Education , Earth & Environmental sciences
Keywords: environmental sustainability , Environmental science , research culture , interdisciplinary , marine and coastal ecosystems , Sustainability , transdisciplinary

Review text

Work is commendable, best of luck

reach at amartya.res@gmail.com for collab



Note:
This review refers to round 2 of peer review.

 Open peer review from Keisuke Okamura

Review

Review information

DOI:: 10.14293/S2199-1006.1.SOR-SOCSCI.AMJY73.v1.RVRCNM
License:
This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

ScienceOpen disciplines: Education , Earth & Environmental sciences
Keywords: environmental sustainability , Environmental science , research culture , interdisciplinary , marine and coastal ecosystems , Sustainability , transdisciplinary

Review text

This review focuses on the preprint entitled ‘ Enabling interdisciplinary research capacity for sustainable development: Self-evaluation of the Blue Communities project in the UK and Southeast Asia ’, authored by Fiona Culhane, Victoria Cheung and Melanie Austen [ 1 ].

Firstly, I commend the authors for meticulously reviewing my feedback [ 2 ] and the other reviewer’s [ 3 ]. They have earnestly engaged with points they deem useful and necessary, significantly enhancing the quality of research dissemination by appropriately revising the paper. Notably, the analysis section shows a noticeable improvement from the previous version, rendering it even more valuable.

Below, I present my thoughts on the revised version [ 1 ]. I conducted the review while adhering to the ‘ General Factors Ratings ’ outlined in the journal’s peer-review guidelines. I took note of each aspect: (a) Level of importance, (b) Level of validity, (c) Level of completeness and (d) Level of comprehensibility. To illustrate the relationship between each point raised and its respective aspects, I have indicated the corresponding aspect (a–d) at the end of each comment. I have not classified these into ‘Major’ or ‘Minor’ categories.

I acknowledge that there might be points in this review where the authors might not necessarily agree. If there are instances due to my misunderstanding or misinterpretation, there is no need to consider those. The decision on whether the authors should address my suggestions (and, if addressed, whether it is done appropriately) will be left to the overseeing editor unless specifically requested otherwise. Even if the overseeing editor deems the current version acceptable for publication without further revision, I have no objection.

A) Comments on the study’s validity and ‘Discussion’

  1. It is noted that responses were received from 56 out of approximately 115 individuals (line 165). It would be beneficial to understand the profile of the non-respondents, including information such as their country/region and sector involvement (academic, NGO, governmental, etc.). As this survey targets project participants, this information should be reasonably ascertainable. This clarification is crucial for discussing the validity of conclusions drawn from the responses of these 56 individuals. For instance, if the other approximately 55 non-respondents hold significantly different perceptions or inclinations, it could influence the assessment of the BC project, consequently affecting broader implications and discussions in line with those changes. Non-response is inevitable and typical in this type of survey research, but if there are aspects of sampling bias that can be discussed from the profile of non-respondents, they should be addressed. [a, b, c]
  2. Regarding the discussion on the ‘limitations’ in Section 4.3, further elaboration on the potential impacts or biases arising from these limitations on the outcomes and analyses of this study would be beneficial. [a, b, c]
  3. Regarding lines 613–614, the authors have not specifically detailed the ‘key lessons’ they have gleaned and how they intend to ‘modify’ or ‘enhance’ their approach. This point is crucial in this kind of survey research, and a more specific discussion would be beneficial. A structured subsection like ‘Lessons learned and implications for future projects’ could aid clarity. Related discussions are also found around lines 545–546. [a, c, d]
  4. There needs to be more clarity regarding the relationship between the ‘Discussion’ (Section 4) and the ‘Conclusion’ (Section 4.4). For instance, the content discussed towards the end of the ‘Conclusion’ section, highlighting issues within the current academic system, is not entirely evident if it directly derives, with persuasive evidence, from the survey conducted or is a kind of ‘Discussion’ segment. It would benefit from further consideration. [b, c, d]
  5. In line with the previous point and echoing comments [ 2 ] on the Version 1 preprint, it is essential to consistently acknowledge the limited scope of insights derived from the responses of these 56 individuals. The scope of conclusions drawn from this data is inherently limited, whether deductively or inductively. Caution must be exercised in drawing conclusions regarding the success or evaluation of the BC project, let alone in making definitive assertions about broader aspects like the nature of ‘interdisciplinary research’ or the ‘academic system’. Exhaustive discussion on internal and external validity is crucial to elevate the paper’s quality. Ensuring a robust discussion and adequately substantiating these aspects within the paper is essential to presenting a compelling argument. [b]
  6. As demonstrated in the current manuscript, combining quantitative and qualitative approaches is commendable and recommended. These two approaches should complement each other judiciously to address their respective limitations. While Section 4 shows instances where this combination is aptly done, there still seems to be an inclination towards an episode-driven discussion overall. Presumably, the authors aim to introduce discourse heard from participants and prior studies as corroboration or support after establishing quantitative evidence from the survey. At times, this intent might not be entirely clear. In this regard, two points are noted:
    • The frequent use of ‘most’ (respondents/markers/levels/parameters), echoing previous review comments [ 2 ], could benefit from specifying figures (‘how many out of how many’ and/or ‘%’). Alternatively, referencing a corresponding table might aid in maintaining the link between the quantitative analysis and qualitative discussion more appropriately. Especially with ‘most respondents’, it is crucial to scrutinise whether it genuinely applies to the population under consideration for deriving various conclusions and implications. [c, d]
    • Additionally, there appear to be instances where individual anecdotes or specific participant remarks more or less determine the overall project evaluation (success) or situation, not necessarily aligning effectively with the quantitative analysis results (typical instances being lines 473–479). Reassessing the appropriateness of such descriptions is advisable. Distinguishing between success experiences or lessons learned at an individual respondent level (obtained from personal responses) and those pertinent to the project as a whole (derived or inferred from statistical approaches) while effectively integrating them in discussions would be advantageous. [b, c]

B) Comments on the presentation of analysis results

  1. The arrangement of the bar graphs in Figures 1 to 5 needs more clarity in their sequence from top to bottom. Being clear about the order of the bars is fundamental. Usually, this information is discernible from the figures but is unclear in the current manuscript. [d]
  2. A minor point regarding Figures 3 (b) and 4 (b) is that reconsidering the horizontal bar graph domain might be advisable. If my understanding of this bar graph is correct, the graph scale extends to a theoretically unattainable upper limit, which might not be scientifically reasonable. [d]
  3. Figures 7 to 9 offer a clearer and significantly enhanced visual representation, marking the most noticeable improvement compared to the Version 1 preprint. To enhance the clarity of these diagrams, the following point should be noted. Line 157 mentions the ‘trend line’, referring to two line segments in each panel of Figures 7 to 9. However, it is not evident what the slope and intercept of these lines signify. An explanation of this point would help readers to understand how these relate to the displayed ‘R’ values. (Note that the ‘R’ value does not represent the slope of the ‘trend line’.) [d]
  4. Although unnecessary to include in the paper, as previously suggested in the review [ 2 ] of the Version 1 preprint, the overlaying histograms for Southeast Asia and the UK corresponding to Figures 7 to 9 for each variable could provide useful insights. If not already attempted, it is worth exploring as it would reveal additional insights not visible from scatterplots.
  5. The authors employ Fisher’s exact test regarding hypothesis testing. Note that Fisher’s exact test is valid when both row and column totals are fixed by design. However, considering the conclusions and discussions the authors aim to draw, it appears they seek to generalise beyond the 56 respondents’ group. Providing clarification on the intended ‘population’ for drawing conclusions and assessing whether the use of Fisher’s exact test remains sufficiently appropriate would be beneficial. [b, c]
  6. Lines 311–313, 347–349 and 383–386 conclude that ‘[…] improved from a lower success or skill level to achieve the same success or skill level that UK respondents/teams/institutions started the project with’. However, this assessment might not be entirely suitable. From the questionnaire, it appears respondents from Southeast Asia evaluated changes in their success or skill levels primarily concerning their own past, not necessarily making direct comparisons with the success or skill levels of UK respondents. [b]

C) Miscellaneous

  1. The data and its metadata on the open repository appear to remain unchanged. It would be advisable to ensure their update coincides with the publication of the latest version. [c, d]
  2. Accruing experience in critically analysing research from diverse perspectives is crucial in academia and society. This belief aligns with the asserted importance of interdisciplinary capacity building highlighted in the authors’ manuscript. I hope that an open platform like UCL Open: Environment , where diverse opinions are exchanged, and various perspectives are considered, fosters a culture that promotes interdisciplinary collaboration. I desire the authors’ paper to be appropriately published and contribute to the advancement of social sciences and better academia-society relationships as envisioned by the journal.

Keisuke Okamura

Washington D.C., USA

17 th December 2023

References

[ 1 ] Culhane, Fiona E. and Cheung, Victoria and Austen, Melanie (2023). Enabling interdisciplinary research capacity for sustainable development: Self-evaluation of the Blue Communities project in the UK and Southeast Asia, 2017-2021. https://doi.org/10.14324/111.444/000189.v2

[ 2 ] Keisuke Okamura (2023). Review of ‘Growing interdisciplinary research capacity for sustainable development: Self-reported evaluation’. https://doi.org/10.14293/S2199-1006.1.SOR-SOCSCI.APE1TG.v1.RRZRYX

[ 3 ] Carla-Leanne Washbourne (2023). Review of ‘Growing interdisciplinary research capacity for sustainable development: Self-reported evaluation’. https://doi.org/10.14293/S2199-1006.1.SOR-SOCSCI.AHPMPZ.v1.RMKJUG



Note:
This review refers to round 2 of peer review.

 Open peer review from Keisuke Okamura

Review

Review information

DOI:: 10.14293/S2199-1006.1.SOR-SOCSCI.APE1TG.v1.RRZRYX
License:
This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

ScienceOpen disciplines: Education , Earth & Environmental sciences
Keywords: environmental sustainability , Environmental science , research culture , interdisciplinary , marine and coastal ecosystems , Sustainability , transdisciplinary

Review text

This review focuses on the preprint titled ‘ Growing interdisciplinary research capacity for sustainable development: Self-reported evaluation ’, authored by Fiona Culhane, Victoria Cheung, and Melanie Austen [ 1 , 2 ].

(1) General comments

The objective of the authors’ manuscript is to quantitatively and/or qualitatively validate the effectiveness of the interdisciplinary collaborative approach, specifically the ‘learning-by-doing’ method, implemented in the Blue Communities (BC) project. This validation is accomplished through surveys and questionnaires administered to participants. The ultimate goal is to gain insights and draw lessons from the research findings, with the aim of enhancing and advancing capacity building through interdisciplinary collaboration in various other present and future cases.

However, the current manuscript needs improvement in several aspects from both internal and external validity perspectives. I hope that the authors will find my comments in this review helpful and incorporate them to enhance the next version of their work. If there are any comments that may be deemed unacceptable due to my misunderstanding or lack of comprehension, the authors are free to disregard them. Moreover, since some comments regarding data presentation and other aspects have already been provided in another review [ 3 ], I will refrain from repeating them here. In fact, I concur with many of the points raised in Ref. [ 3 ]. I recommend referring to it as well and utilising its suggestions to improve the manuscript.

(2) Internal validity perspective

The authors’ decision to publicly share the collected data [ 2 ], along with the questionnaire used, is commendable in terms of promoting transparency and reproducibility. This practice is highly recommended as it enhances the value of open peer-review.

Regarding the adequacy of the questionnaire’s development, I will not address that issue in this review. However, it appears that the authors may not be fully utilising the obtained data. Each respondent answered multiple questions, encompassing individual-level, team-level, and organisation-level aspects, as well as questions regarding attributes and demographics like gender, country of affiliation, and research career stage. As a result, numerous cross-tabulations or regression analyses could be conducted among these question responses.

For instance, attributing a specific perception exhibited by early career researchers in response to a particular question solely to the brevity of their career can be misleading. In reality, it could be influenced by the research environment they are situated in or even their predisposition. Additionally, exploring the correlation between responses to individual-level questions and those related to team-level or organisation-level inquiries would be beneficial. By further harnessing the response data in this manner, it is worth considering methodologies that can yield more dependable and conclusive analytical outcomes.

Regression analysis is a useful tool that can provide valuable insights beyond simple cross-tabulation. However, it is essential to ensure that the regression model satisfies various conditions necessary for causal inference. While acknowledging the limitations, conducting regression analysis can yield helpful insights. Using the CSV data publicly available in Ref. [ 2 ], I present below an example of regression analysis that I have attempted and found suggestive. I hope you find it beneficial.

In this example, I will outline a method for capturing the factors or drivers of perception formation regarding the effectiveness of the BC project at the individual level using regression analysis. This is likely a significant concern for the authors as well. The authors have collected response data for various aspects (e.g. ‘Finding relevant literature’, ‘Critically reviewing the literature’, etc.) in terms of ‘personal current success or skill level’ (rated on a scale of 1–9, hereafter denoted as ‘ x ’) and the perception of how each aspect changed as a result of the BC project (rated on a 5-point scale from ‘much worse’ to ‘much better’, hereafter denoted as ‘ y ’). Therefore, a simple regression model can be formulated with ‘ y ’ as the response variable and ‘ x ’ along with other variables such as gender, country of affiliation, employment type, and research career stage as explanatory variables. If the variable ‘ y ’ is coded as ordered integers, such as 1–5 or –2 to +2, an ordered logit model would be suitable for the regression analysis.

Considering that the number of valid observations (respondents) is relatively small (around 50), it is not feasible to include a large number of explanatory variables. Thus, it becomes crucial to carefully select the most important explanatory variables. With regards to the research career variable, it would be preferable to treat it as individual dummy variables based on their respective values rather than as a single ordered variable. However, this approach may result in an excessive number of explanatory variables compared to the number of observations, making it impractical for this study. Therefore, it is important to strike a balance between the number of explanatory variables and the available sample size in order to ensure the reliability and validity of the regression analysis.

When actually conducting the regression analysis at the individual level, it becomes evident that, in the case of most y -variables, the corresponding x -variables or country of affiliation (either individually or in combination) demonstrate statistical significance, while other variables do not. This process enables a more reliable comprehension of the factors that influence changes in each y -variable. By meticulously interpreting the outcomes from both qualitative and empirical perspectives, deeper insights into the effectiveness of the BC project can be obtained. Consequently, this would further augment the value of the paper by providing a more comprehensive understanding of the project’s impact.

If conducting regression analysis poses challenges, I suggest conducting more detailed descriptive analyses as a minimum. To gain further insights, it would be beneficial to create histograms for different attributes such as gender and country of affiliation, and overlay them for comparison, for both the x and y variables defined earlier. Additionally, creating scatterplots with corresponding x and y pairs as axes would provide valuable information. To account for the discrete nature of the responses, consider introducing jittering. Varying the marker styles in the scatterplot based on attributes like gender and country of affiliation and overlaying them for comparison is also recommended. These visual representations will enhance the understanding of the data and facilitate comparisons across different attributes.

Performing these analyses, including overlaid histograms and scatterplots, will indeed offer a clearer understanding of the distributions of perceptions ( x and y ) across different attributes, as well as the associations between x and y within various attributes. These insights can yield valuable findings and contribute to a more comprehensive understanding of the data. Furthermore, conducting these analyses can serve as valuable preparation for the previously mentioned regression analysis. I highly encourage the authors to explore these visualisations if feasible, as they can provide valuable insights and enhance the overall analysis of the data.

(3) External validity perspective

Overall, I get the impression that the authors’ manuscript resembles more of a report on the organisational activities or activity records specifically of the BC project, rather than a research paper that contributes to the academic knowledge base or provides lessons for other (future) cases.

In the Discussion and Conclusion sections, there are instances where the authors attempt to extrapolate their analysis and interpretations to general theories related to career development, the academic environment, or interdisciplinary collaboration, in an effort to draw significant implications. However, there seem to be logical leaps in many parts of the manuscript. For example, generalising specific comments from certain individuals in the open-ended responses and using them to justify the overall evaluation of the BC project or attempting to derive universal conclusions lacks sufficient credibility.

It is important to ensure that the conclusions drawn in the manuscript are supported by robust evidence and rigorous analysis. Additionally, generalisations should be made cautiously, considering the limitations of the study and the specific context of the BC project. Providing a clear rationale and using appropriate references or theoretical frameworks can strengthen the credibility and reliability of the manuscript’s conclusions.

From that perspective, I suggest revisiting the Discussion and Conclusion sections and carefully examining the descriptions regarding the level of external validity. If the goal is to produce impactful content that is relevant to a broad audience, as advocated by UCL Open: Environment , it is desirable to uncover valuable insights beyond the specific BC project. By doing so, this paper will become even more valuable as a publication in the journal, as it will offer insights and lessons that can be applied to a wider range of contexts and contribute to the broader academic knowledge base.

(4) Miscellaneous

  1. It is recommended to include the actual number of respondents alongside the response rate in Tables 1 and 2. This will provide readers with a better understanding of the sample size and the proportion of participants who responded to the survey.
  2. In my view, the numbers indicated with ‘%’ next to the bar graphs in Figures 1–5 should be removed. These numbers can be misleading and confusing since they do not correspond to the length of the bars.
  3. When stating phrases like ‘Most respondents felt...’, it is advisable to quantify the extent of ‘most’ using the format like ‘X out of Y respondents (Z%)’. This will provide a quantitative representation and enhance the clarity of the statement.
  4. In Section 2.2 (Questionnaire), it is necessary to provide more specific and detailed explanations about the methods of questionnaire development, distribution, and collection, including the survey duration.
  5. In the Supplementary Material and the file named ‘Survey_Questions.pdf’, each question item should be labelled with a number or symbol for individual identification, and it is strongly recommended to ensure a one-to-one correspondence between each response in the data file.
  6. In the response data (CSV file), it seems that responses related to age groups and sectors of affiliation have been removed. If there is a deliberate reason for omitting these responses, it should be mentioned in the document to avoid any confusion or misinterpretation.
  7. It would be advantageous to provide a more compelling rationale for the relative superiority of the ‘learning-by-doing’ approach compared to other approaches. While it is generally expected that any approach implementing in a project could yield positive outcomes, the key lies in demonstrating how the benefits derived from the ‘learning-by-doing’ approach outweigh those that would have been obtained through alternative approaches. This will strengthen the argument and provide a clearer understanding of why the ‘learning-by-doing’ approach is recommended.

(5) Overall impression

This manuscript has the potential to significantly enhance its academic and societal value by conducting a more comprehensive analysis considering both internal and external validity. To achieve this, it would be beneficial to provide meticulous descriptions of the approach employed to draw conclusions, ensuring transparency and clarity. Additionally, improving the methods of data visualisation, presentation, and delivery will contribute to a more effective communication of the research findings. By implementing these enhancements, the overall quality and impact of the paper can be greatly improved, leading to a more valuable contribution to the academic and societal discourse.

References

[ 1 ] Culhane, Fiona E. and Cheung, Victoria and Austen, Melanie (2022). Self-reported Change in Research Capacity Following Participation in an Interdisciplinary Research Project, 2017-2021. https://doi.org/10.14324/111.444/000189.v1

[ 2 ] Culhane, Fiona E. and Cheung, Victoria and Austen, Melanie (2022). Self-reported Change in Research Capacity Following Participation in an Interdisciplinary Research Project, 2017-2021. [Data Collection]. Colchester, Essex: UK Data Service. https://doi.org/10.5255/UKDA-SN-856101

[ 3 ] Washbourne, Carla-Leanne (2023). Review of ‘Growing interdisciplinary research capacity for sustainable development: Self-reported evaluation’. https://doi.org/10.14293/S2199-1006.1.SOR-SOCSCI.AHPMPZ.v1.RMKJUG

Keisuke Okamura

Washington D.C., USA

15 th July 2023



Note:
This review refers to round 1 of peer review and may pertain to an earlier version of the document.

 Open peer review from Carla-Leanne Washbourne

Review

Review information

DOI:: 10.14293/S2199-1006.1.SOR-SOCSCI.AHPMPZ.v1.RMKJUG
License:
This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

ScienceOpen disciplines: Education , Earth & Environmental sciences
Keywords: environmental sustainability , Environmental science , research culture , interdisciplinary , marine and coastal ecosystems , Sustainability , transdisciplinary

Review text

Many thanks for the opportunity to review this interesting article, based on a survey of experiences from participants in a large-scale, interdisciplinary, cross-country research and capacity building project. The article fits within the scope of UCL Open: Environment and provides novel information and insights likely to be of interest to the wider community. I have provided some general and detailed comments and feedback below. Overall, my sense is that the article would be strengthened by relatively minor revisions, mostly focussed on data analysis and presentation.

Comments:

Title: I am not convinced that the title fully does justice to the scope and nature of the article. I would be tempted to switch out ‘Growing’ for a different term that sounds more purposeful / intentional like ‘Enabling’ or ‘Supporting’. While I realise it makes it a lot longer, the sub-title could be rephrased to better capture 1) the nature of the evaluation 2) the link with the project 3) maybe the counties involved e.g. : self-evaluation of the ‘Blue Communities’ project [in the UK and Southeast Asia]

Abstract:

  • ODA funding might need further explanation, or perhaps don’t include in the abstract and only in the body text
  • Line 50: ‘Results were mainly positive’ is too vague here. What do you mean by ‘positive’?
  • Is it possible to include any of the more detailed insights / findings?

Body text

  • Line 63: Why was the UoL 2026 strategy highlighted here? It is a good example, but feels a little arbitrary as so many institutions have similar strategies. Was this one particularly ground-breaking?
  • Line 71 / 72: Consistency with the terms ‘capacity strengthening’ and ‘capacity building’. Make it clear if there is an intended difference between the two uses here and throughout the paper.
  • Line 94 / 95: It would be good to have a footnote with a bit more detail about the nature of GCRF. Especially if the reference to ODA funding is retained in the abstract.
  • Line 106: As above re: GCRF. It would be good to be a bit more explicit about the way in which the nature of this funding influence the scope and approach of the project
  • Line 114: Were these funding calls based on the redistribution of funds already won for the project, or was this something in addition?
  • Line 140: More detail about the survey is needed here. Who developed the survey (Author FC is stated in the author contributions, were their other contributors)? Who distributed the survey and how (via email to the project members, during meetings, through newsletters, via social media etc.)? How long was the survey open for / when did you decide how to close the survey?
  • Line 143: Explain more here how you defined the different career stages (shown in Section 1 of the survey). You do come back to this later in the paper, but it would be helpful to have a brief sense here of what the categories were and how you chose to define these stages.
  • Line 184: What kinds of ‘other’ institutions were represented?
  • Table 2: Check final formatting of table, as the separation between the definitions in the final row could be made clearer
  • Results: Did you use any more detailed statistical approaches to explore the correlations and differences between responses? This strikes me as being especially useful in the case of the data currently presented in Figures 6-9. These are really nicely illustrative, but a further exploration of the correlation would be very instructive.
  • Figure 1, 2, 3a, 4a, 5a: Reconsider the colour scheme used here. The ‘UK and other European’ category would benefit from being recoloured in something more contrasting
  • Figure 3b, 4b, 5b: Reconsider the colour scheme used here. It would be better to use a scheme more clearly distinct from the accompanying charts to the left.  Perhaps it would be better onscreen to use a gradient based on one colour for the categories in (a) and a different colour for (b).
  • Figures 6-9: Why are the categories in reverse order top to bottom? (i.e. ending with A rather than starting)
  • Line 251: See also comments below re: creating a separate section for ‘Limitations of the study’
  • Figures 7-9: For quick visual communication of the results, I would advise keep the x axis consistent on all charts even where there is no data (e.g. some of the (b) charts showing the difference in response)
  • Line 429-430: By ‘this study’ you are referring to the project overall, rather that this manuscript?
  • Line 491-492: I think it is fine to be more definite here. There is plenty of evidence that the value placed on different aspects of the University differs from place to place.
  • Line 503-504: Not absolutely necessary to include, but notable that there are some attempt to change this through the links between REF and Knowledge Exchange Framework (KEF)
  • Line 564-565: As above re: explaining a little more about GCRF and ODA link
  • Line 595-603: I would personally relocate this from the conclusion to a separate section on limitations of the study. This could do right at the end of the methods, or discussion, depending on the preferences of the author. Add in the point about the survey only being available in English.


Note:
This review refers to round 1 of peer review and may pertain to an earlier version of the document.