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Article

Operationalising Organisational Performance in the Scope of Industry 4.0 and Industry 5.0 in Manufacturing Companies

by
Irina Serbinenko
* and
Iveta Ludviga
*
Business Department, RISEBA University of Applied Sciences, LV-1048 Riga, Latvia
*
Authors to whom correspondence should be addressed.
Sustainability 2025, 17(14), 6314; https://doi.org/10.3390/su17146314
Submission received: 1 June 2025 / Revised: 5 July 2025 / Accepted: 7 July 2025 / Published: 9 July 2025
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Abstract

Industry 4.0 and Industry 5.0 are reshaping business models and scientific concepts, bringing challenges and opportunities. Stakeholders require a performance measurement system that enables them to address challenges and effectively capture opportunities. However, the current literature lacks consistency in utilising appropriate performance measurement systems, and the authors aim to identify current trends in measuring organisational performance within the context of Industry 4.0 and Industry 5.0 in manufacturing companies. A systematic literature review, based on the PRISMA model, was conducted to identify which performance measurement systems for manufacturing companies are utilised in the context of Industry 4.0 and Industry 5.0. Findings indicate that the current literature lacks consistency regarding performance measurement systems for manufacturing companies, which encompass elements of Industry 5.0, including human-centrism and sustainability. We recommend a human-centric and sustainability-oriented approach to measuring performance in Industry 5.0, prioritising metrics that value employees as co-creators of success, integrate well-being and ethical dimensions, and focus on human-technology collaboration. Such an approach should ensure that technology supports, rather than replaces, humans, aligning organisational goals with societal and environmental values.

1. Introduction

In recent decades, employees in manufacturing companies have worked in an era of a fast-changing environment that has reshaped not only their workplaces but also their lives. Existing literature recognises five Industrial Revolutions, from the First, which started in the late 18th century, to the Fourth and Fifth, which are co-occurring in our present day. All Industrial Revolutions transformed economies and societies as a result of new technological processes. During the Industrial Revolution, significant changes reshaped existing business models, scientific paradigms, and ways of working and living. All these changes bring with them opportunities and challenges. During the Industrial Revolution, opportunities emerged from increased productivity, accelerated economic growth, and groundbreaking innovations. However, these opportunities also bring challenges, such as widening social inequality. In the past decade, new technologies have introduced additional challenges, including integrating human–robot co-working and the demand for a highly skilled workforce [1].
In manufacturing companies, adopting new technologies has a direct impact on employees’ job performance [2]. Thus, Industry 4.0 and 5.0 present challenges for both organisations and employees, as organisations need to utilise new technologies to maintain competitiveness and effectiveness in the manufacturing industry. On the other hand, employees face the need to adapt to new technologies which impact their role and skill requirements. To address these challenges and to meet the demands of Industry 4.0 and 5.0, stakeholders of manufacturing companies need to establish appropriate measurement systems for organisational performance, which assess how organisations (i) achieve goals and objectives, (ii) use resources, (iii) accomplish strategy, and (iv) deliver value to stakeholders. Moreover, they should consider employee-level drivers of organisational performance during these industrial revolutions, alongside organisational-level performance measures, because social benefits have a positive effect on Industry 4.0 implementation [3], and employee competencies pose challenges from a capability perspective [4]. However, the existing literature lacks comprehensive frameworks for measuring organisational performance that specifically address the unique challenges of Industry 4.0 and 5.0, particularly from an employee perspective [5,6].
This paper aims to analyse the main trends in measuring the organisational performance of manufacturing companies in the context of Industry 4.0 and Industry 5.0 and to classify which measures are commonly used at the organisational level and which are related to the employee perspective. The research question is: How do existing organisational performance measurement systems align with the principles of Industry 5.0? The objectives of our paper are the following: to identify the organisational performance indicators in the existing literature related to Industry 4.0 and 5.0 from 2011 to 2025; to calculate the frequency of these organisational performance indicators and to categorise them; to assess the alignment of these organisational performance indicators with the principles of Industry 5.0; and to propose recommendations for a measurement framework that can better adapt to the evolving needs of manufacturing organisations in the context of ongoing Industry 5.0.
This paper uses a systematic literature review (SLR) methodology analysing studies from the Scopus and Web of Science databases. The rest of the paper is structured as follows: first, to capture the context and challenges, Section 2 describes the history of Industrial Revolutions, focusing on the specifics of manufacturing companies and Industry 4.0 and Industry 5.0; Section 3 shows the evolution of the concept of Organisational Performance during Industrial Revolutions. Section 4 presents the SLR methodology based on the PRISMA model. In Section 5 the analysis presents the main trends for operationalising organisational performance in the literature. Finally, in Section 6 we conclude that the current metrics lack focus on human centricity and sustainability, which are characteristic features of Industry 5.0. Recommendations for developing performance measurement metrics are proposed.

2. Industrial Revolutions and Manufacturing Companies

The manufacturing industry is pivotal in economic growth, particularly in developing and low-income countries [7]. The industrialisation witnessed in the 18–19th centuries in the USA and Western Europe, or in the 1960s in the Middle East, underscores how enhanced productivity propels economies forward. The term ‘Industrial Revolution’ was popularised by Arnold Toynbee (1852–1883), and Wilson [8] asserts that Toynbee’s lectures were the most influential attempt to demonstrate the significance of technological changes in the British economy. Despite the term ‘revolution’ implying abrupt changes, which may seem inappropriate for the definition of ‘Industrial Revolution’, it is applicable because this period saw fundamental changes in the functioning conditions across all sectors: transportation, agriculture, manufacturing, economic policy, and the social structure of England [9]. According to Shama & Singh [10], the following Industrial Revolutions occurred in periods: Industry 1.0 (1760–1840), Industry 2.0 (1870–1914), Industry 3.0 (1950–1970), and Industry 4.0 (2011–present).
The First Industrial Revolution began in England in the late 18th century, when James Watt (1736–1819) improved a steam engine invented by Thomas Newcomen (1664–1729). This innovation sparked a technological revolution in various industrial fields, including steel production, textiles, and mining [11]. New technologies helped employers to produce more efficiently, but O’Rourke et al. [12] argue that these innovations also allowed them to use a cheap workforce, including women and children, which in turn increased skill premiums in employees’ earnings.
The Second Industrial Revolution, also known as the American Industrial Revolution, began in the USA due to inventions such as electricity, the internal combustion engine, and electrical communication [13]. According to Gangopadhyay et al. [14], America evolved from an agricultural colony to a great world industrial power thanks to industrialisation. In the 19th century, America became the centre of the main technological inventions. These are only a few of them: Andrew Carnegie used the Bessemer process of making steel and developed America’s Steel Industry, George Pullman invented a railroad sleeping car, Thomas Alva Edison invented the incandescent light bulb, Gustavis Swift introduced refrigerator to the meat industry, Henry Ford used assembly line process for automobile mass production. Kim [15] argues that while industrialisation is linked to the rise of factories and the decline of artisans’ workforce demand, it was the massive immigration of unskilled workers (1840–1920) that contributed to the spread of the manufacturing industry in the United States.
There exist three mainstreams which define the Industrial Revolution: (1) the growth of specific sectors, like cotton and iron, which involved the spread of manufacturing factories which used steam power, (2) the large population shifted from the agricultural industry to manufacturing and mining industries; (3) the entire economy broke out into a state of stable national income. Agrawal & Agrawal [16] (p. 1062) combined them into one: “…industrial revolution can be defined as the structural shift of the large proportion of the population from agricultural to manufacturing and mining sector, which caused a growth in the manufacturing sector, and ultimately increasing the national income”. Table 1 below summarises the differences between Industry 1.0 and Industry 2.0.
Mohajan [17] considers that the Third Industrial Revolution started in the early 1950s as a result of moving technologies from mechanical to digital, and that it is ongoing now. However, Roberts [18] dates the beginning of the Third Industrial Revolution to 1969, when the Advanced Research Projects Agency Network (ARPAN) was developed, and its development paved the way for the Internet and the information age. Although there are different views on the beginning of the Third Industrial Revolution, both authors agree that this revolution brought changes to all aspects of society, similar to the First and Second Industrial Revolutions. However, there is a significant difference between the Third Industrial Revolution and both previous ones—The First and Second Industrial Revolutions were characterised by skill-biased and skill-degrading technologies, and the Third Industrial Revolution, in contrast, was characterised as a skill-biased one [19]. Thus, the Third Industrial Revolution, or, according to Caselli [20], an Information Technology Revolution, as a skill-biased technological revolution, influenced workers with low learning costs to shift to new, more productive machines. In contrast, those with high learning costs remained attached to old types of machines.
To summarise the historical overview of the three Industrial Revolutions, all of them transformed old “workplaces” and their management into new structures that met the requirements of technological development and served society’s needs [21].

2.1. Industry 4.0

The concept “Fourth Industrial Revolution’’ was coined by Klaus Schwab, founder and executive chairman of the World Economic Forum [22], and it was first presented during the Hannover Fair in Germany in 2011. This concept is built on previous industrial revolutions: the First, characterised by steam-powered factories, the Second by mass production, the Third by digitalisation, and, according to Schwab [23], the Fourth Industrial Revolution represents the new age, where such technologies as artificial intelligence, genome editing, 3-D printing, etc., are reshaping institutes, industries, and individuals. Kagermann et al. [24] state that Industry 4.0 is rather a strategy whose vision needs to be systematically implemented by business, academia, government, and other organisations to sustain the leadership role of Germany in a global smart-manufacturing context. Though many authors stated that Industry 4.0 is not a revolution but rather an evolution of Industry 3.0, the majority agree that new technologies disrupt whole sectors of the economy and society, and thus, it cannot be considered an evolutionary process [25]. For example, Klingenberg et al. [26] analysed the Fourth Industrial Revolution, denominated Industry 4.0, by describing the framework with three elements: technology, economy, and society. As a result, they concluded that this phenomenon can be considered as the next “revolution”. Their conclusion was based on a comparison of Industry 4.0 with previous industrial revolutions, showing that all of them had a significant impact on people’s way of life. Thanks to different definitions, there are the following names for the Fourth Industrial Revolution: in the USA, it is known as Advanced Manufacturing Partnership 2.0; in Germany—Industry 4.0 Platform; in Japan—Revitalisation/Robotics Strategy; and in South Korea—Manufacturing Innovation 3.0 [27]. Any revolution brings both challenges and opportunities, and Industry 4.0 is no exception (see Table 2).
Researchers argue that to address the challenges of Industry 4.0, more research should be undertaken in the area of human resource management (HRM) regarding such topics as (1) technological perspective, (2) sustainability, and (3) management and organisational perspective [28]. The main concern of Industry 4.0 implementation is its ability to support sustainable innovation [29], because most businesses seek sustainable operations only under the pressure of public opinion or government regulations. There is also evidence that emerging countries are not technologically prepared for Industry 4.0 [30], which may lead to a growing gap between them and the developed world. Moreover, Hirsch-Kreinsen [31] showed that in the developed world, there will be a gap between big companies which have more investment opportunities and, as a result, have better chances to implement new technologies than SMEs (small- and medium-sized enterprises) which are not prepared for digitalisation. Nevertheless, Jabbour et al. [32] argue that Industry 4.0 and environmentally sustainable manufacturing can overlap and thus generate a synergy of these two waves, which may boost green manufacturing processes. Therefore, as there are both supporters and critics of Industry 4.0, it is essential to place individuals in the roles of providers and users of new technologies, keep them aware that people create technologies and lead progress, and educate them to lower their level of uncertainty in times of change [33].

2.2. Industry 5.0

In recent years, 2021–2025, a new concept of the Fifth Industrial Revolution has emerged, and there is an ongoing discussion regarding whether this is the new Industrial Revolution, which is caused by a set of disruptive technologies or a concept which describes a set of values [34]. Though Industry 4.0 is still immature, the transition to Industry 5.0 is already evident through research expansion [35]. According to Alves et al. [36], Industry 5.0 would apply technologies of Industry 4.0 while creating value for the human factors. Khan et al. [37] argue that Industry 5.0 has its own technologies aimed at overcoming negative worker factors caused by Industry 4.0 technologies.
However, Industry 5.0 is considered not only a technology shift but rather a paradigm shift, where digitalisation has to solve Industry 4.0 challenges through value orientation [38]. Moreover, the European Commission [39] outlined that Industry 5.0 is aimed toward human-centricity, resiliency, and sustainability (Table 3).
Thus, the main feature distinguishing Industry 5.0 from Industry 4.0 is its objectives [40]. Industry 4.0 primarily focuses on economic goals, whereas Industry 5.0 emphasises ecological and social ones. To conclude, the main aim of Industry 5.0 is to balance organisational, social, and ergonomic aspects with the human at the centre [41].

3. Organisational Performance—Evolution of the Concept

In the previous section, we discussed how five industrial revolutions followed the emergence of new technologies. Although all Industrial Revolutions have different histories, geographies, and characteristics, they share a common influence on reshaping the industrial, economic, and social spheres globally. Moreover, the Industrial Revolution challenged and transformed scientific and economic paradigms by introducing new concepts or changing existing ones. One such concept is “Organisational Performance”—Taşkan et al. [42] showed how the concept of Organisational performance evolved from a set of simple records during the First Industrial Revolution to a holistic performance perspective at the end of the Third Industrial Revolution (see Table 4). Organisational Performance can be measured in subjective and objective ways and is the most crucial concept for all stakeholders [43], because it refers to an organisation’s ability to satisfy the expectations of its customers, employees, and shareholders. Moreover, according to Duman & Akdemir [44], Organisational Performance measurement is aimed to (i) support strategies and objectives of organisations, (ii) compare the organisations with competitors, (iii) play a role in decision-making, (iv), warn about errors, (v) motivate employees, etc. Thus, it is essential to use such measurement for Organisational Performance, which is the most appropriate for the organisation, considering its industry, competitors, and objectives.
Industry 4.0 is a technology-driven Industrial Revolution, while Industry 5.0 is a value-driven Industrial Revolution. Manufacturing companies now work during both Revolutions, and the appropriate measurement of Organisational Performance may help them better evaluate their strategies to face the challenges of ongoing technological and value changes. Bastian & Muslich [45] support the importance of non-financial measures for Organisational Performance. However, Molenda et al. [46] advocate measuring Organisational Performance by balancing financial and non-financial measures with the help of the balanced scorecard, which was introduced by Robert S. Kaplan and David P. Norton during the Third Industrial Revolution. There are different views on Organisational Performance in the literature dated after Industry 4.0 began, so it is essential to understand the existing performance measures. Therefore, a further part of the paper is devoted to a systematic literature analysis of existing trends in measuring Organisational Performance.

4. Materials and Methods

The authors conducted a SLR to find papers on performance measurement in manufacturing companies. According to Rother [47], it is appropriate to answer the specific research questions using the SLR. To mitigate potential selection bias during the SLR, we followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, which ensured a transparent and replicable selection process. Specifically, (1) we applied predefined inclusion and exclusion criteria based on relevance to Industry 4.0 and Industry 5.0 performance measurement, publication type (peer-reviewed journal articles), and time frame. (2) Two authors independently screened the titles, abstracts, and full texts, and discrepancies were resolved through discussion to reduce subjectivity. (3) A detailed search strategy was used across multiple databases (Scopus, Web of Science), which minimizes the risk of missing relevant studies. The SCOPUS and Web of Science (WoS) databases were selected for this SLR because they are widely recognised for their comprehensive coverage of high-quality, peer-reviewed academic literature across various disciplines. Together, they provide sufficient breadth and depth to ensure the retrieval of relevant and authoritative sources, meeting the rigorous standards of the PRISMA framework [48,49]. The authors conducted it following the PRISMA checklist [50], which consisted of the following steps (see Figure 1): identification, screening, eligibility, and inclusion.
To ensure transparency and enhance reproducibility, this SLR follows a clearly defined search strategy. The search was conducted using the following keywords: organisational, performance, measurement, manufacturing, Industry 4.0, and Industry 5.0. The Boolean query applied was as follows: organisational AND performance AND measurement AND manufacturing.
After excluding duplicate articles, 1045 articles remained. After the screening phase, 100 articles were left after excluding 945 articles that did not meet the chosen criteria. The search criteria were limited to open-access articles, a period spanning Industries 4.0 and 5.0 from 2011 to 2025, and English language. For SCOPUS, the search focused on business, management, and accounting, decision sciences, and social sciences. For WOS, the search included business economics. Additionally, the search targeted articles with a final version published in journals.
After excluding articles with limited access, 96 articles remained. After reading the full text of 96 articles, the authors selected 53 articles for analysis, as 9 were deemed invalid for the following reasons: they were in the wrong industry and did not mention a performance measurement system. The results are shown in Appendix A.

5. Results and Discussion

This study aimed to explore the existing organisational performance measurement in the context of manufacturing companies operating during Industry 4.0 and Industry 5.0 and assess its alignment with the principles of Industry 5.0. After a SLR, the authors identified all types of performance measurement mentioned in the 53 retained articles and recorded the frequency of their mention. As a result, 59 types of performance measurement were mentioned in the reviewed 53 articles, while 39 (66%) of them were mentioned only once, 7 of them twice, 1 of them three times, 3 of them four times, 7 of them five times, and 1 of them six times and 1 of them 9 times.
The objective of this study was also to categorise the types of organisational performance measurements currently used in the existing literature. As a result, they were grouped into three main categories: financial, non-financial, and sustainability-oriented measurements.
  • Financial measurements were typically operationalised through rate of asset turnover, ability to provide revenues, cost structure, ability to achieve goal (profitability), liquidity, marginal revenues, productivity, profitability, and net margin ratio [51,52].
  • Non-financial metrics included operational efficiency indicators such as speed, flexibility, and dependability [53], as well as overall equipment effectiveness (OEE) [54] and balanced scorecard approaches [55,56].
  • Sustainability-oriented metrics addressed both environmental (e.g., emissions, waste reduction) and social (e.g., employment, gender equality, employee satisfaction) dimensions [57,58].
These categories include two levels: organisational and employee-level. Organisational-level measurements emphasise aggregated outcomes such as profitability, system efficiency, and strategic goals [59,60,61], while employee-level measurements focus on individual contributions and personal development, such as labour productivity, task execution, and engagement in green practices [62,63].
Most of the identified measurements reflect priorities focused on technological advancement and economic efficiency. Organisational performance measurement frameworks currently emphasise automation, operational excellence, and strategic control mechanisms. Even sustainability-oriented measurements tend to be quantifiable and efficiency-driven, often lacking integration with human and societal dimensions. While dynamic and integrated performance systems (e.g., DPMS and PMS) represent a step towards adaptability and learning [64,65], they remain largely technocentric, with limited inclusion of human-centric values.
The final research objective was to evaluate how well current metrics align with the values and goals of Industry 5.0—a paradigm shift that emphasises human-centricity, social responsibility, and ecological balance [40,41]. The analysis reveals that existing measurement systems are still anchored in paradigms, primarily evaluating economic and operational aspects.
While social performance is sometimes included under sustainability metrics, key Industry 5.0 values—such as employee well-being, inclusivity, human–machine collaboration, and job meaningfulness—are largely absent from these metrics. For example, none of the reviewed studies proposed indicators for measuring employee engagement in strategic decisions, quality of work life, or collaborative effectiveness between humans and AI systems, which are central to Industry 5.0. Thus, we conclude that most indicators which are currently used in organisational performance measurement have emerged before the conceptualisation of Industry 4.0 and 5.0. This means that the operationalisation of performance has not yet fully adapted to capture their distinctive characteristics.
This gap suggests a critical need for new organisational performance measurement frameworks that explicitly incorporate human-centric dimensions. Industry 5.0 metrics should not only complement traditional indicators but also reflect values such as dignity at work, participatory innovation, and social cohesion. In response to this gap, Table 5 proposes new organisational performance measurements aligned with Industry 5.0, including examples of both organisational- and employee-level metrics. These include:
  • Employee well-being: Job satisfaction, work–life balance, and psychological safety.
  • Human–machine collaboration: Efficiency and satisfaction in collaborative tasks.
  • Strategic inclusivity: Employee participation in organisational planning and innovation.
  • Societal impact: Company contributions to community welfare, education, and inclusive growth.
By embedding such metrics, organisations can better align organisational performance measurement with the principles of Industry 5.0, ensuring that technological progress goes hand-in-hand with human and societal advancement.
To enhance the clarity of the proposed performance framework, Figure 2 visualises the organisational and employee-level metrics aligned with Industry 5.0 dimensions.

6. Conclusions

This paper analyses the main trends in measuring the organisational performance of manufacturing companies in the context of Industry 4.0 and Industry 5.0 and to classify which measures are commonly used at the organisational level and which are related to the employee perspective. By aligning these measures, organisations can effectively evaluate both high-level performance and the specific contributions of employees, fostering a system of accountability and continuous improvement.
Based on the above, we conclude that for a comprehensive approach to measuring organisational performance within the scope of Industry 4.0 and 5.0, it is advisable to combine financial and non-financial metrics, as well as sustainability-oriented metrics. Frequently used frameworks include the balanced scorecard and integrated performance systems, which incorporate financial outcomes and operational efficiencies. It is equally important to incorporate sustainability, including environmental, social, and circularity metrics, to align with modern sustainability demands. Moreover, organisations utilise dynamic and real-time performance monitoring systems for continuous improvement. This combination offers a robust framework tailored for measuring and improving organisational performance in manufacturing industries.
However, the results reveal that organisational performance measurement in the context of Industry 4.0 and Industry 5.0 does not currently demonstrate a strong trend towards human-centric metrics. This lack of emphasis on human-centric metrics may create a gap between Industry 5.0’s value-driven approach and the current performance measurement practice. To adopt a human-centric approach to measuring performance in Industry 5.0, organisations should prioritise metrics that value employees as co-creators of success, integrate well-being and ethical dimensions, and focus on human–technology collaboration. Such an approach ensures that technology supports, rather than replaces, human contributions, aligning organisational goals with societal and environmental values.
More focus should be given to employee-level and employee-centric metrics to capture the specifics and goals of manufacturing companies in Industry 5.0. For example, mental health, job satisfaction, work–life balance, and psychological safety can be measured through surveys and continuous feedback mechanisms. Metrics related to employee training and learning could be used to track employee upskilling in collaborative technologies (e.g., robotics, AI) and their ability to adapt to new tools and workflows. Additionally, it may be beneficial to assess the alignment of roles with employees’ strengths, autonomy, and career progression opportunities. In line with technological advancements, it is recommended that the success of human–technology partnerships be evaluated in terms of generating innovative solutions, improving processes, and driving new product development.
At the organisational level, measures could also include metrics related to societal value creation. For example, an assessment of the organisation’s impact on the local community (e.g., creating jobs, improving living standards) or metrics for corporate social responsibility (CSR) projects involving employees. The authors developed a visual framework summarising proposed organisational performance measurements for Industry 5.0 (Figure 2).
The findings of this study have implications for researchers and managers. This study enhances the understanding of existing performance measurement approaches, supporting manufacturing managers in developing Industry 4.0 and 5.0 strategies. It proposes more human-centred measures for harnessing the value of humans in Industry 5.0. Managers of manufacturing companies can use the proposed metrics to capture performance at the organisational or employee levels. We recommend a human-centric and sustainability-oriented approach to measuring performance in Industry 5.0 and prioritizing metrics that value employees as co-creators of success, integrate well-being and ethical dimensions, and focus on human–technology collaboration. Such an approach should ensure that technology supports, rather than replaces, humans in manufacturing companies. Such metrics would enable the alignment of organisational goals with societal and environmental values. Managers should use metrics that capture innovation engagement, strategic decision participation, and team collaboration. These indicators foster a culture of inclusivity, creativity, and co-development, which supports a human-centric approach. Industry 5.0 encourages organisations to contribute to society. Metrics such as community engagement, knowledge sharing, and diversity outreach help managers ensure their company plays a positive societal role, improving its reputation and stakeholder trust.
Current research has certain limitations. It is based solely on data from the SCOPUS and Web of Science databases; therefore, the article may have missed relevant studies due to differences in indexing. The time frame limitation excludes the latest development. Despite applying structured inclusion criteria and independent screening by two authors, subjective judgment may have influenced the selection and categorisation of organisational performance measurements, especially when interpreting context or grouping metrics.
Future studies could focus on such performance measurement systems for future research. These systems support the evaluation of strategies for facing the challenges presented by Industry 4.0 and 5.0 from the employee perspective.

Author Contributions

Writing—original draft, I.S.; Writing—review & editing, I.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Organisational Performance Measurement in Manufacturing During Industry 4.0 and Industry 5.0

Nr.ArticleOrganisational
Performance Measurements		Method
1Horváth, D., & Szabó, R.Z. (2019) [59].Financial and non-financial Qualitative case study, grounded theory
2Baines, T., & Lightfoot, H.W. (2013) [60].Non-financialCase study
3Bhattacharya et al. (2014) [61].Non-financialCase study, interview, Analytic Network Process (ANP)-based Green Balanced Scorecard method
4Dubey et al. (2017) [57].Financial and non-financialEmpirical study, survey-based approach
5Dey, P.K., & Cheffi, W. (2013) [58].Non- financial and sustainability-orientedPrimary and secondary data collection using AHP approach
6Bititci et al. (2015) [66]. Maturity-orientedQualitative research design, including multiple case studies
7Padilla-Lozano, C.P., & Collazzo, P. (2021) [67]. Non-financial and sustainability-orientedQuantitative, cross-section method
8Malik et al. (2021) [68]. Sustainability-orientedQuantitative survey research design, cross-sectional data
9Gerschewski, S., & Xiao, S.S. (2015) [69]. FinancialMixed Methods
10Rahamneh et al. (2023) [70].Non-financialSurvey, structural equation modelling approach
11Brax et al. (2021) [71]. Financial and non-financialSLR and inductive reasoning
12Kocmanova, A., & Simberova, I. (2012) [72]. Environmental and social-orientedA combination of descriptive and multi-dimensional statistical methods
13Hasegan et al. (2018) [64]. Non-financialThe study was conducted using six-stage action research for developing DPMS with real-time control of independent variables on the production lines to study the impact
14Sardi et al. (2020) [65].Non-financialLongitudinal case study
15Al-Tit, A.A. (2017) [73]. Financial and non-financialStudy
16Watts, T., & McNair-Connolly, C. J. (2012) [74]. Non-financialLiterature review
17Maware, C., & Adetunji, O. (2019) [53]. Non-financialQuantitative study
18Afy-Shararah, M., & Rich, N. (2018) [54]. Non-financialTheory building, based on longitudinal case studies using a pluralist methodology of interviews, observation and secondary data.
19Fechete, F., & Nedelcu, A. (2019) [75]. Financial and non-financialA mathematical model for the calculation of the total performance formula
20Bühlerm et al. (2016) [76]. FinancialQuantitative survey
21Uribetxebarria et al. (2021) [77].FinancialQuantitative survey
22Rabbi et al. (2020) [78]. Green supply chain-orientedLiterature review, a BBN-based probabilistic mode
23Moldavska, A. (2017) [79]. Sustainability-orientedA study with a cross-disciplinary approach, questionaries, and interviews
24Uddin et al. (2021) [80].KPI-orientedQualitative research
25Abdullah et al. (2019) [81].Non-financialQuantitative study
26Sifumba et al. (2017) [82]. FinancialQuantitative research
27Pollard et al. (2022) [83].Circularity-orientedExploratory research with a qualitative approach
28Choe, J.M. (2016) [84]. Financial and non-financialEmpirical examination
29Panagiotakopoulos et al. (2015) [85].Sustainability-orientedReview
30Islam et al. (2019) [86].FinancialLiterature review
31Laitinen et al. (2018) [87]. FinancialLiterature review
32Amhalhal et al. (2022) [88]. Financial and non-financialEmpirical Study
33Abdollahbeigi, B., & Salehi, F. (2020) [55].Balanced scorecardQuantitative method
34El-Garaihy et al. (2022) [89].Supply chain-orientedSurvey
35Oyewo et al. (2022) [56]. Balanced scorecardSurvey research design
36Montoya-Reyes et al. (2020) [90]. Financial and non-financialStudy
37Kustono, A.S. (2020) [62]. Employee performance-orientedThe research with a quantitative approach, and the research design—cross-sectional.
38Silva et al. (2014) [91].Financial and non-financialStudy
39Di Luozzo et al. (2023) [92]. Non-financialSLR
40Hamann et al. (2023) [93]. FinancialMeta-Analysis
41Jwijati et al. (2023) [94]. Financial and non-financialLiterature review
42Choe, J.M. (2018) [95]. Supply chain-orientedQuantitative study
43Abdollahbeig, B., & Salehi, F. (2020) [96]. Financial and non-financialQuantitative study
44Holopainen et al. (2024) [97]Sustainability-orientedSLR
45Huang, Q., & Kumarasinghe, P.J. (2024) [98]FinancialQuantitative study
46Ogbari, M.E. (2024) [99]Financial and non-financialQuantitative cross-sectional analytic design
47Pattnaik, S.C., & Sahoo, R. (2020) [100]Financial and non-financialSurvey study using the descriptive research design
48Mohamad et al. (2017) [101]Balanced scorecardEmpirical study
49Ciemleja, G., & Lace, N. (2011) [51]FinancialQuantitative and qualitative methods
50Ambroise (2020) [52]FinancialQuantitative method
51Salisu, Y., & Bakar, L. J.A. (2019) [63]Non-financialQuantitative method
52Van Thuong, C., & Singh, H. (2023) [102]Balanced scorecardQuantitative method
53Nuhu et al. (2022) [103]Financial and non-financialQuantitative method

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Sustainability 17 06314 g001
Figure 1. PRISMA model (Created by authors).
Figure 1. PRISMA model (Created by authors).
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Figure 2. Proposed organisational performance metrics for Industry 5.0.
Figure 2. Proposed organisational performance metrics for Industry 5.0.
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Table 1. Differences between the First and Second Industrial Revolutions.
Table 1. Differences between the First and Second Industrial Revolutions.
1.0 Industrial Revolution2.0 Industrial Revolution
Fields of technology development:Textile, steam power, and iron makingSteel, chemicals, electricity
Transport industryRailroads started to expand thanks to wrought iron and steam locomotivesThe rail network expanded thanks to steel, which is long-lasting and has greater strength
Development ofLarge-scale production of chemicals used for making soap, glass, etc.
Glassmaking, paper machine, and gas lightening		Chemicals such as synthetic dyes, mauveine, etc.
Petroleum industry, maritime industry, rubber and fertilizer industries, automobile industry, marine and telecommunication industries
Banking and financing of firmsIncrease in the number of country banks, which issued notes, made short borrow/lent and discounting (payments between businessmen)
Development of London banks and bill brokers as intermediaries between agricultural and industrial sectors		Growth in banking, selling securities to finance outside Europe investments
Increasing the use of cheques and decreasing the use of bills
The emergence of clearing banks
Development of financial institutions which provided saving opportunities for workers and lower middle class
Created by authors based on Agarwal & Agarwal [16].
Table 2. Challenges and opportunities for Industry 4.0.
Table 2. Challenges and opportunities for Industry 4.0.
OpportunitiesChallenges
Productivity growth
New job creation
Raise new HR practices aimed at motivating knowledge workers
Reduced barriers between inventories and markets
Increased application of Artificial Intelligence (AI)
Fusion of technologies
Improved quality of life thanks to robotics
Advanced interconnection thanks to the Internet of Things (IoT)		Yield of greater inequality
Disruption of the labour market
Increase in skill segregation thanks to the growing demand for talented employees
Increase in social tenses
Cybersecurity threats
Personal security threats
Personal data security threats
Disruptions in educational models
Disruptions in business models
Emerging ethical concerns
Created by authors based on Xu et al. [22].
Table 3. Elements of Industry 5.0.
Table 3. Elements of Industry 5.0.
Human-Centred DesignResiliencySustainability
The main driver and innovative factor
Focus on employees
Adaptation of the processes and system to employees
Basic requirements for achieving maturity levels for digitalisation and AI		Stabilisation policy
Creation of competitiveness
Use of modern technologies and approaches		Implementation of environmental solutions
Business models with sustainable aspects
Involvement in strategic planning
Monitoring of sustainability indicators
Created by authors based on Hein-Pensel et al. [40].
Table 4. Organisational Performance (OP) models/measurements during 1–3 Industrial Revolutions (IRs).
Table 4. Organisational Performance (OP) models/measurements during 1–3 Industrial Revolutions (IRs).
Industrial Revolutions (IRs)Organisational Performance (OP) Models/Measurements
1IRThe concept OP was a set of records that included labour costs, material movement, and general expenses. Data from these records was used only for control and short-term decision-making.
2IRThe evolution of the concept OP started with new accounting practices (divided into financial, capital, and cost accounting) and ended with the DuPont System, as well as Tableau De Bord. Although the latter two measurements of performance were more advanced than previous ones, they still had one significant disadvantage—a limited indication of future performance.
3IRThe concept OP evolved from the Residual Income method with no consideration of non-financial measures to an integrated and holistic framework, the Flexible-Strategy Game Card for strategic performance management
Created by authors based on Taşkan et al. [42].
Table 5. Proposed organisational performance metrics for Industry 5.0.
Table 5. Proposed organisational performance metrics for Industry 5.0.
Organisational Performance
Measurement
Category		Organisational-Level MetricsEmployee-Level Metrics
Financial
-
Profit margin—Profitability—Economic growth—Company productivity
-
Individual productivity—Task efficiency—Cost-effectiveness of individual output
Non-Financial
-
Overall Equipment Effectiveness (OEE)—Process speed, flexibility, dependability
-
On-time task completion—Adaptability to change—Maintenance of reliability
Sustainability—Environmental
-
Emissions reduction—Waste and hazardous material reduction—Circular economy index
-
Compliance with green practices—Energy-saving behaviours—Waste minimisation behaviours
Sustainability—Social
-
Workforce diversity—Gender equality- Employment growth
-
Contribution to collaboration—Inclusivity in teamwork—Employee satisfaction
Human-Centric Metrics (New)
-
Job quality index—Organisational learning capacity—Human–machine collaboration index
-
Well-being and work–life balance—Autonomy and participation—Ergonomic satisfaction
Strategic Engagement (New)
-
Employee engagement in innovation—Inclusion in strategic planning—Ethical governance
-
Individual innovation contributions—Involvement in decision-making—Leadership potential
Societal Impact (New)
-
Community development initiatives—Education/training outreach—Social value creation
-
Volunteering participation—Knowledge-sharing in communities—Civic engagement
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Serbinenko, I.; Ludviga, I. Operationalising Organisational Performance in the Scope of Industry 4.0 and Industry 5.0 in Manufacturing Companies. Sustainability 2025, 17, 6314. https://doi.org/10.3390/su17146314

AMA Style

Serbinenko I, Ludviga I. Operationalising Organisational Performance in the Scope of Industry 4.0 and Industry 5.0 in Manufacturing Companies. Sustainability. 2025; 17(14):6314. https://doi.org/10.3390/su17146314

Chicago/Turabian Style

Serbinenko, Irina, and Iveta Ludviga. 2025. "Operationalising Organisational Performance in the Scope of Industry 4.0 and Industry 5.0 in Manufacturing Companies" Sustainability 17, no. 14: 6314. https://doi.org/10.3390/su17146314

APA Style

Serbinenko, I., & Ludviga, I. (2025). Operationalising Organisational Performance in the Scope of Industry 4.0 and Industry 5.0 in Manufacturing Companies. Sustainability, 17(14), 6314. https://doi.org/10.3390/su17146314

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