INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
A Data-Driven Research and Innovation Performance Report Based  
on IPO Model for Malaysia Higher Education Institutions  
Mohd Arif Mohd Azman1, Noor Izwanni Amil1, Anas Abdul Latiff*1,2  
1Research and Innovation Management Centre (CRIM), Universiti Teknikal Malaysia Melaka (UTeM).  
2Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal  
Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia.  
DOI: https://dx.doi.org/10.47772/IJRISS.2025.91100190  
Received: 21 November 2025; Accepted: 28 November 2025; Published: 04 December 2025  
ABSTRACT  
This paper demonstrates a systematic method for preparing higher education institution (HEI) a data-driven  
research and innovation (R&I) performance report based on implementation of the proposed R&I Ecosystem  
Framework. The ecosystem framework is an Input-Process-Output (IPO) Model and has adopted elements in the  
Malaysia Research Assessment (MyRA). The method of performance report is designed to present performance  
achievement levels, enabling relevant stakeholders to plan and implement appropriate action plans. The study  
begins with mapping MyRA criteria to the proposed ecosystem framework, which encompass input, process,  
and output, to form a complete and holistic R&I ecosystem view. Data for each criteria were analyzed using  
Microsoft Excel, and visual representations such as radar charts, statistical graphs, pie charts, and bell curve  
charts were prepared for reporting. The application of this IPO-based framework, coupled with strategic data  
visualization techniques, moves data-driven R&I performance reporting beyond descriptive accounting to  
become a powerful diagnostic and strategic tool. The results identified strengths and weaknesses (gaps) in  
specific R&I criteria, aiding top management and relevant responsibility R&I offices in formulating actionable  
plans to bridging the performance gaps and ultimately enhancing the HEI's overall R&I ecosystem, directly  
supporting the national agenda for improved R&I excellence and global competitiveness.  
Keywords: Research and Innovation, Performance Reporting, Data Analysis, Input-Process-Output (IPO) Model,  
MyRA  
INTRODUCTION  
Research and innovation (R&I) are fundamental pillars of higher education institutions (HEIs), serving as critical  
drivers of academic excellence, economic growth, and societal impact [1][2]. The performance of HEIs in these  
domains is increasingly scrutinized, not only for national ranking purposes but also for their contribution to  
addressing complex global challenges and fostering sustainable development [3]. In response, governments and  
educational authorities worldwide have established performance-based research assessment frameworks to  
evaluate, benchmark, and stimulate the quality and impact of academic research [4] [5].  
In Malaysia, this evaluative role is fulfilled by the Malaysia Research Assessment (MyRA), a comprehensive  
instrument designed to measure Research, Development, Innovation, Commercialization, and Economy  
(RDICE) activities across HEIs. MyRA is inspired by the growing recognition of the role of knowledge creation  
and innovation in national socio-economic development [6]. It assesses HEIs across a spectrum of criteria, from  
input factors like human resources and facilities to output metrics such as publications, citations, innovations  
and professional services [7]. Consequently, HEIs are under sustained pressure to formulate and implement  
strategic initiatives that enhance their RDICE excellence and achieve outstanding MyRA ratings to bolster their  
national and global visibility [8].  
A key challenge for HEI management, particularly for the offices of Deputy Vice-Chancellors of Research and  
Innovation, is the transition from mere data collection to strategic, data-driven decision-making [9]. Effective  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
performance management requires more than periodic reporting; it necessitates a holistic understanding of the  
entire R&I ecosystem to identify strengths, diagnose weaknesses, and allocate resources efficiently [10] [11].  
Traditional reporting methods often present data in silos, failing to illustrate the dynamic interrelationships  
between inputs, processes, and outputs, which is crucial for strategic intervention [12].  
The Input-Process-Output (IPO) model offers a robust theoretical lens to address this gap. As a systems theory  
framework, it provides a structured overview of how resources (Inputs) are transformed through activities  
(Process) into results (Outputs) [13] [14]. When applied to R&I management, the IPO model can offer a clear  
and systematic view of performance, making it easier to pinpoint where gaps originate and where strategic  
actions are most needed. However, while the IPO model is well-established, its explicit integration with national  
assessment frameworks like MyRA to create a practical performance reporting tool remains underexplored.  
Furthermore, the power of any framework is unlocked through effective data analysis and visualization. Data  
visualization techniques, such as radar charts and statistical graphs, are proven to enhance the comprehension of  
complex datasets, enabling stakeholders to quickly grasp trends, comparisons, and gaps that might be obscured  
in raw data or tabular reports [15]. The synergy of a coherent conceptual framework like IPO with advanced data  
analytics represents a significant opportunity to improve strategic R&I management in HEIs.  
Therefore, this paper demonstrates a systematic method for preparing HEI R&I performance reports by  
implementing a proposed Research and Innovation Ecosystem Framework based on the IPO model and mapped  
to MyRA criteria. This study begins by mapping MyRA criteria to the IPO framework to form a complete  
ecosystem view. Subsequently, it details how data for each criteria were analyzed and visualized using accessible  
tools like Microsoft Excel to generate actionable insights for top management and relevant responsibility R&I  
offices. The ultimate aim is to provide a holistic and systematic reporting method that not only tracks  
performance but also actively informs strategic planning and continuous improvement in the R&I domain.  
Input-Process-Output (IPO) Model and MyRA Criteria Mapping  
Research is an important element in the excellence of a university. It plays a significant role in exploring new  
knowledge and innovations. Outstanding research and innovation outcomes have a profound impact, not only  
on the advancement of knowledge but also on societal progress and well-being. Additionally, they address  
challenges faced by industries and communities. MyRA evaluates three main aspects: input, process, and output,  
covering eight criteria as outlined in Table 1. Consequently, HEIs have formulated and implemented strategic  
initiatives to enhance RDICE excellence and achieve outstanding MyRA ratings.  
Fig. 1 Summary of the research and innovation ecosystem based on MyRA criteria mapping, covering input,  
process, and output (IPO)  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
Table 1 MyRA Criteria (2023 Amendment) by Section  
Sections  
MyRA Criteria  
A
B
C
D
E
General Information  
Quality and Quantity of Researchers  
Quality and Quantity of Research  
Quality and Quantity of Postgraduates  
Innovation  
F
Professional Services and Awards  
Networking and Outreach  
Support Facilities  
G
H
The IPO model provides an overview of how a system or process functions [14]. It aids in planning, analyzing,  
and improving effectiveness by clearly outlining the inputs required to initiate a process, how the process  
operates, and the outputs generated. Applied to research and innovation, the IPO model offers a clear and  
systematic view of performance achievements, facilitating strategic actions for reducing gaps and enhancing  
strengths.  
MyRA criteria as outlined in Table 1 evaluates three main aspects: input, process, and output. However, the  
sections are not organized according to these aspects. Thus, a detailed study was conducted to map each MyRA  
criterion to the IPO model, forming a comprehensive research and innovation ecosystem as shown in Fig. 1.  
Outputs also feedback into inputs. For example, research collaborations with industries to develop products and  
the revenue generated from sales can fund new research projects. Additionally, technologies derived from such  
projects can be transferred to local communities through Knowledge Transfer Programs.  
Inputs for research and innovation include four key elements: funding (Research Grant), human resources  
(Postgraduate/Post-Doctoral), collaboration (Networking), and research infrastructure (Facilities) is depicted as  
Fig. 2. The process involves research and innovation activities conducted by researchers using these inputs.  
Outputs are categorized into publications, innovations, awards and recognitions, income generation, knowledge  
or technology diffusion project, and talent development.  
Fig. 2 Relationship between input and output in research and innovation based on MyRA criteria mapping  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
Through Strategic Plan based on IPO Model in Fig. 1, HEI in Malaysia aims to achieve a higher MyRA rating  
to elevate RDICE excellence and enhance its national and global visibility. Typically, Office of Deputy Vice-  
Chancellor for Research and Innovation is responsible for planning and implementing strategic initiatives to  
meet this target. To achieve this, current performance must be reported periodically to accurately identify  
strengths and weaknesses. Based on these gaps, appropriate action plans can be developed, and improvements  
can be implemented by relevant responsibility office. Therefore, a comprehensive and systematic method for  
reporting research and innovation performance is essential.  
Data Analysis  
Data analysis in the context of research performance management is not merely a procedural task of processing  
numbers, it is a critical exercise in transforming raw data into strategic intelligence. A systematic approach to  
data analysis, comprising collection, validation, cleaning, transformation, and modelling, is paramount for  
extracting meaningful insights, drawing valid conclusions, and supporting evidence-based decision-making at  
both operational and strategic levels [9].  
In this study, data pertaining to the mapped MyRA criteria were meticulously collected by appointed Data  
Managers from various offices and subsequently validated during official MyRA audit sessions as mandated by  
the Ministry of Higher Education (MoHE). This rigorous process ensures the integrity and reliability of the  
dataset.  
The subsequent analytical phase focused on translating this validated data into accessible and actionable  
visualizations using Microsoft Excel. The selection of specific chart types was deliberate, each serving a distinct  
purpose in communicating different dimensions of performance, from holistic overviews to detailed, and criteria  
specific analyses. The following figures exemplify this approach.  
Fig. 3 presents a radar chart, which is instrumental for providing a holistic, multi-dimensional performance  
profile. This visualization allows for the simultaneous comparison of all key R&I categories against predefined  
targets or benchmark values. The enclosed area visually represents the overall performance strength, while the  
asymmetries in the web's shape instantly reveal relative strengths and weaknesses across the ecosystem. Gaps  
between the achieved performance (the plotted line) and the target (the outer ring) are immediately apparent,  
directing management's attention to areas requiring strategic intervention, such as 'Innovation' or 'Networking',  
which may be lagging behind strengths in 'Publications'.  
Fig. 3 Radar chart for holistic R&I performance assessment. This chart compares strengths and weaknesses  
across evaluated categories and highlights gaps from targets or full marks  
Fig. 4 utilizes a bar chart to effectively display trends over time. This temporal analysis is crucial for tracking  
progress, evaluating the impact of past initiatives, and forecasting future performance. For instance, a chart  
depicting the annual number of postgraduate students or research grants over a five-year period can reveal growth  
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trajectories, stagnation, or decline, enabling management to assess the effectiveness of talent development or  
research culture initiatives.  
Fig. 3 Bar chart for trend analysis. This chart visualizes performance data over multiple periods (years), revealing  
growth patterns, stability, or declines in key metrics.  
Fig. 5 combines a stacked bar chart with a dot plot to offer a sophisticated analysis of composite scores. The  
stacked bar can break down an overall score into its constituent sub-criteria, showing the contribution of each to  
the total. The dot plot, positioned alongside, clearly marks the target value for each category. This side-by-side  
comparison allows stakeholders to not only see the current achievement level but also to precisely quantify the  
performance gap for each sub-criterion, facilitating more nuanced and targeted action plans.  
Fig. 5 Composite analysis using a stacked bar chart. This visualization breaks down overall scores into sub-  
criteria contributions and explicitly marks the target for each, enabling precise gap analysis  
Fig. 6 employs a pie chart to illustrate the composition or distribution of a particular R&I output. This is  
particularly useful for showing proportional contributions, such as the percentage distribution of publications  
across different faculties, the share of research income from various sources (example, government grants,  
industry contracts), or the breakdown of innovation types (example, patents, copyrights, prototypes). This helps  
in understanding the structure of the research portfolio and resource allocation.  
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Fig. 6 Pie chart shows the percentage breakdown of a whole into its constituent parts, useful for understanding  
the composition of different categories  
Finally, Fig. 7 features a bell curve chart (normal distribution graph). This statistical visualization is used to  
analyze the distribution of a dataset, such as the research publication output among academic staff. The chart  
plots the frequency of individuals against their performance level. It helps identify the mean performance, the  
variation within the research community, and the presence of high performers (the right tail) and those who may  
need more support (the left tail). This analysis is vital for designing equitable and effective capacity-building  
programs and research leadership strategies.  
Fig. 7 Bell curve chart for performance distribution analysis. This chart shows the distribution of a performance  
metric (example., publication count per researcher) across a population, indicating the mean, variation, and the  
presence of high and low performers  
In summary, this multi-faceted data analysis approach moves beyond descriptive statistics. By employing a suite  
of complementary visualizations, it provides a deep, multi-layered understanding of the university's R&I  
ecosystem, forming a robust evidence base for the performance reporting discussed in the following section.  
Performance Reporting  
The final stage is preparing research and innovation performance reports. The ultimate objective of the  
systematic data analysis is to facilitate strategic performance reporting that directly informs decision-making  
and action. The transition from analyzed data to an actionable performance report is critical; it is at this stage  
that insights are contextualized and translated into tangible intervention plans for top management and the  
relevant responsibility R&I office. The reports generated through this methodology are designed not as static  
historical records, but as dynamic management tools focused on the MyRA evaluation criteria and the  
university's strategic plan.  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
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The integrative approach of this study, which combines the conceptual structure of the IPO model with granular  
data analysis, empowers stakeholders to answer two fundamental questions: (a) Where in the research and  
innovation ecosystem (example, in which input, process, or output category) are the most significant weaknesses  
or gaps? and (b) What is the detailed nature of these performance gaps to inform corrective measures?  
Fig. 8 exemplifies this high-level diagnostic function. It displays a performance profile for a specific domain in  
this case, research project management using a radar chart. This visualization provides an immediate, at a glance  
assessment of health and performance across key indicators. Management can instantly identify which aspects  
of project management are strong (example, "Proposal Submission") and which are critical vulnerabilities  
(example, "Timeframe Management" and "Publication Output"). The distorted shape of the web graphically  
underscores imbalances in the process, signaling that while the university is effective at initiating research  
projects, it faces challenges in seeing them through to completion and translating results into market-ready  
innovations. This high-level gap analysis is the crucial first step that directs managerial attention to the areas of  
greatest need.  
Fig. 8 Performance profile for research project management using a radar chart. This high-level diagnostic tool  
visually identifies strengths and critical gaps across key process indicators, guiding strategic prioritization.  
Once a high-priority gap is identified from the radar chart, Fig. 9 demonstrates the subsequent drill-down  
analysis. It takes one specific weak item from the performance profile which is Timeframe Management, and  
provides a detailed breakdown using a stacked bar chart. This moves the analysis from diagnosing what is wrong  
to understanding why it is wrong.  
Fig. 9 Detailed analysis of a performance gap using a stacked bar chart. This drill-down visualization  
deconstructs a key indicator to reveal the underlying causes, enabling the formulation of precise and actionable  
improvement plans.  
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The chart reveals the composition of the failure to meet the completion target, breaking it down by the status of  
ongoing projects. It might show, for instance, a significant portion of projects stalled at the experimental work  
or data analysis stages, with fewer than expected at the manuscript preparation stage. This granular detail is  
invaluable for the relevant office, it moves the discussion from a generic "we need to improve project  
completion" to a specific, actionable insight: "We need to implement targeted research support services, such as  
data analysis workshops and scientific writing retreats, to help researchers progress from the mid-to-late stages  
of their projects."  
In conclusion, the performance reporting methodology illustrated by Fig. 8 and Fig. 9 creates a powerful  
feedback loop for research management. The holistic view of the radar chart enables strategic prioritization,  
while the detailed stacked bar chart facilitates operational planning. This two-tiered reporting structure ensures  
that improvement efforts are not only data-driven but are also precisely targeted, increasing the likelihood of  
successfully bridging performance gaps and enhancing the university's overall R&I ecosystem.  
CONCLUSIONS  
This study has demonstrated the efficacy of a holistic and systematic approach to research and innovation  
performance reporting by integrating the Input-Process-Output (IPO) model with robust data analysis and  
visualization. The proposed framework, mapped directly from the MyRA criteria, successfully reframes  
disparate performance metrics into a coherent ecosystem narrative. This provides a critical structural  
understanding of how strategic inputs such as search grants, human capital, networking, and facilities are  
transformed through research activities into a spectrum of outputs, from publications and innovations to talent  
development and income generation.  
The application of this IPO-based framework, coupled with strategic data visualization techniques, moves  
performance reporting beyond descriptive accounting to become a powerful diagnostic and strategic tool. The  
multi-level reporting from the holistic overview offered by radar charts to the granular, root-cause analysis  
enabled by stacked bar charts empowers university management and responsibility R&I office with actionable  
intelligence. It allows them to not only identify that a gap exists but to pinpoint where in the ecosystem it  
originates and what its specific nature is, enabling the formulation of precise and effective intervention plans.  
In essence, this method bridges a critical gap between raw performance data and strategic action. It provides a  
replicable model for HEIs to transition from reactive data collection to proactive, evidence-based management  
of their research and innovation ecosystem. By offering a clear line of sight from inputs to outputs, this approach  
ensures that improvement efforts are strategically aligned, efficiently targeted, and ultimately, more effective in  
enhancing institutional research performance and impact in line with national and global benchmarks.  
ACKNOWLEDGMENT  
This work was sponsored by Universiti Teknikal Malaysia Melaka (UTeM). The author would like to  
express gratitude to the Centre for Research and Innovation Management (CRIM), UTeM for the continuous  
support of this work.  
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