The Innovation-Based Human Development Index Using PROMETHEE II: The Context of G8 Countries

Abstract

The current Human Development Index (HDI) has a promising potential to consider further dimensions, the technological dimensions in specific, in order to absorb various innovational aspects whenever human development is to be benchmarked among countries. Hence, the innovation-based HDI was developed herein using one of the well-known Multi-Criteria Decision Making (MCDM) techniques: the Preference Ranking Organization Method for Enrichment of Evaluations II (PROMETHEE II) considering a mixture of technological criteria, including the Global Innovation Index (GII) itself. The G8 countries, as leading countries worldwide, were investigated in this regard in order to attain such a benchmarking attempt. The model was formulated using seven criteria selected from the World Bank (WB) Open Data (such as High-technology exports as a percentage of manufactured exports, Research and development (R&D) expenditure as a percentage of GDP, and Trademark applications, …, etc.) along with the GII, for the purpose of conducting an MCDM-based evaluation model for the G8 countries. The results of the developed index affirm that the ranking of the G8 countries has distinctly been changed as a consequence of considering technological and innovational aspects, compared to the original HDI (i.e., USA +4—from 5th to 1st; Canada −4, from 2nd to 6th). By utilizing MCDM methods (including PROMETHEE II), this paper also affirms that an infinite number of indexes can be developed in the future by employing a huge number of WB indicators with respect to various MCDM approaches. Hence, international communities are in need of setting up commonly accepted guidelines in order to facilitate having a unified prioritization (i.e., unified preference) regarding the potential criteria and/or indicators to be considered globally for better sustainable development.

1. Introduction

One of the main drivers of a nation’s economic growth is the knowledge and capabilities of its national workforce [1]. A key index that gained wide global acceptance to measure both the social and economic alongside human development is the United Nations Human Development Index (HDI). HDI mainly focuses on measuring three main indicators/indexes, namely: Life Expectancy Index, Education Index (Mean of Schooling Years), and Gross National Income Index (GNI per PPP$). Having said that, although widely accepted, the HDI methodology as an index was critiqued by some scholars and hence, opening the way for new proposals that aim to better assess countries’ efforts toward sustainable development [2]. Going through the 4th industrial revolution, it is evident that innovation is key to countries’ economic prosperity and sustainable development [3,4,5]. Indeed, the relationship between innovation, human development, and GDP is particularly strong [6]. Therefore, countries are working tirelessly to build and enable their workforce to have the right skill sets to engage and initiate innovative practices/projects, as well as setting national strategies for innovation activities [5]. Additionally, the investment in education and science has a more significant impact on countries’ ecological situation, which guides and influences public policy [7]. Furthermore, empirical research findings from 35 countries indicated that R&D spending help to directly improve the national patent application, thus contributing to national development [8]. Hence, exploring not only some of the HDI indicators is essential, but also it is important to consider other indexes related to innovation. Figure 1 presents the HDI and the Global Innovation Index (GII) for the G8 countries.

The significance behind handling such a contemporary issue is driven by three motives. Firstly, the increasing number of national-level research attempts on innovations and/or sustainability and their interactions with human development under the umbrella of the circular economy [9,10,11,12]. Secondly, the current trend of handling international-based issues by conducting several research studies in order to create, improve, or critique numerous global indexes, including HDI, within the context of different sets of countries such as OECD [13], G13 [14], and Top Manufacturing Countries [15]. Finally, the recent boom in MCDM research applications aimed at designing various forms of indexes [16,17,18,19,20,21].

Considering all these facts and motives, two research questions can be raised: (1.) To what extent can the HDI be influenced by considering (GII) as one of the embedded criteria for HDI development? (2.) Considering the G8 as a global context for such an investigation, what is the overall ranking of the G8 countries with respect to the proposed HDI? Hence, this paper aims to develop an innovation-based HDI for the G8 Countries. The developed index was established based on the employment of one of the well-known Multi-Criteria Decision Making (MCDM) techniques: the Preference Ranking Organization Method for Enrichment of Evaluations II (PROMETHEE II). PROMETHEE II model was formulated using seven criteria selected from the World Bank Open Data (such as the High-technology exports as a percentage of manufactured exports, Research and development (R&D) expenditure as a percentage of GDP, and Trademark applications, … etc.) along with an additional criterion, that is, the GII, for the purpose of conducting an MCDM-based evaluation model for the G8 countries. The rest of the paper is organized as follows: Section 2 presents the relevant literature on innovation, HDI, and/or other relevant issues in G8 countries. The applied method, PROMETHEE II, is then introduced in Section 3. The application, results and discussion, and conclusions are presented in Section 4, Section 5, and Section 6, respectively.

Figure 1. The GII and The HDI for the G8 countries. [Sources: GII [22] and HDI [23]].

Figure 1. The GII and The HDI for the G8 countries. [Sources: GII [22] and HDI [23]].

2. Relevant Literature

This section presents the relevant literature on innovation and HD for G8 countries. The following subsections provide relevant research attempts in each country separately.

Table 1. Research studies on innovation and/or HD in G8 countries.

Regional Context and/or Country	Title of the Study	Authors	Year	Investigated Aspects
ITA	A Review of the Literature on Well-Being in Italy: A Human Development Perspective	[9]	2016	Well-Being; HD
RUS	Sustainable development goals for the future of Russia	[10]	2017	SDGs
JPN	Japan’s innovation systems at the crossroads: Society 5.0.	[11]	2018	Innovation
USA; UK; CAN; GER; JPN; and Other Technologically Advanced Countries)	The dynamic relationship between technology innovation and human development in technologically advanced countries: fresh insights from quantiles-on-quantile approach.	[13]	2020	Technological innovation; HD
FRA	The role of ‘experience’ in teaching innovation in education for sustainable development in France	[12]	2022	Education; Innovation; SD

presents further research studies on innovation and/or HD in G8 countries.

2.1. USA

While the united states scored at the top G8 countries and 2nd globally in the 2022 GII rankings, it scored 5th among G8 countries’ 2021 HDI results and was ranked 21st Globally. From a knowledge advancement perspective and investing in research and development, the USA has scored at the top globally in terms of the total number of PhDs awarded in the field of science and engineering [24], which is also aligned with the highest globally in research and development reaching three-quarters of a trillion in 2022 followed by China of half a trillion [25]. This is aligned with the outcome of recent research [26], which concluded that North America is the best performer in terms of their performance of Global Innovation. Indeed, the USA, among a few other countries at the top countries attracting Venture Capital that are mainly targeting innovative practices/services and products [27], which is supported by innovation policies that are found to be in sum better than the innovation policies of the European Union (EU) [28].

2.2. UK

The UK consistently performed among the top countries in major indexes, including the HDI as well as GII, as it scored in the top 18 countries in the 2022 HDI and in the top 4 in the 2021 GII rankings. According to Belitski et al. [29], who have studied 4049 firms in the UK, firms’ investments in training and skilling increase innovation outcomes. In a recent study [13], the UK has demonstrated a strong positive effect of technology innovation and human development. Indeed, the 2021 GII ranking results in position enhancement for the UK were mainly derived from two main factors: the UK advanced in its position in both the regulatory environment as well as the intangible assets indicators. Additionally, the UK scored well at many innovation enablers, including scoring at the top of the quality of its universities’ indicator, as well as the quality of scientific publications [27].

2.3. Germany

Germany scored among the top G8 countries in the 2021 HDI (ranked 9th globally) and 3rd among G8 countries in the 2022 GII (ranked 8th globally). According to recent research [30], European countries, including Germany, France, and Italy, have relatively scored higher in both the HDI as well as CISCO Digital Readiness Index, which was also a predictor of the countries’ economic development and growth. Germany is classified among a high-income group of countries, and it was also classified to be among the globally innovative leading countries, which indicates that their innovation input returned high innovative outputs [31]. Indeed, recent research has indicated that Germany scored among the top in terms of R&D efficiency, with a focus on enabling technology-intensive industries, enabling country-wide enhanced innovative outcomes [32].

2.4. Canada

Canada maintained its 15th global rank for two consecutive years in the 2021 and 2022 HDI results (2nd in G8 countries) and a similar position in the 2022 GII (15th globally and 6th among G8 countries). Canada has maintained its global competitive position and has been classified as being among the top inventing nations for the last half century [33]. One of the indicators of innovation and countries’ economic development is the start-ups scaling up to become globally competitive. However, according to the Canadian context, there is a noted nationwide challenge of translating cutting-edge scientific research into an economy that produces the same level of innovation intensity in the private sector. Although Canada is ranked among the top in Global Competitiveness and their education system among the top globally, Rowe and Dong [34] have indicated that Canada should enhance their higher education and ecosystem-related policy.

2.5. France

As one of the four countries within the G8, France scored 4th in the GII 2022 rankings (12th globally), and it also scored among the top six G8 countries in 2021 HDI Rankings (28th globally for two years in a raw). According to Guner [35], France, although it scored among the top 12 countries globally in the GII, still needs to strengthen its science and research infrastructure to match its economic size and potential [36]. Indeed, as France has paid attention to Science and Technical Activities (STA) development that resulted in scientific and technical that contributed to innovation development, France is considered among potential countries to become STA World Leaders [37].

2.6. Japan

As the only Asian country in the G8 group, Japan maintained its global position for two consecutive 2020 and 2021 HDI results (19th globally) and 4th among the G8 countries. As a major hub for research and development as well as innovation, Japan scored in the top five G8 countries in the GII 2022 Rankings and 13th globally. Indeed, recent research indicated that Japan has been classified as among the group of countries that are leaders in STA (high potential and results), which is an indication that Japan has been developing processes and policies that enable new knowledge generation and implementation [37]. Additionally, the economic growth of Japan is influenced by the Nation’s proportion of R&D expenditure from its GDP as well as the number of qualified workforce, were all scored high levels compared to G8 countries [38].

2.7. Italy

According to the HDI 2021 outcomes, Italy was ranked 30th globally and 7th among G8 countries. Italy was also ranked 28th in the GII, globally and 7th among G8 countries. According to Visco [39], Italy’s R&D expenditure requires further enhancement enabling more innovation support structure and funding that will enable economic growth. Indeed, both Italy and Russia’s R&D expenditure is ranked in a similar position globally (11th Italy and 10th Russia) [25], which could be one of the indications of its current GII and HDI lagging position among G8 countries.

2.8. Russia Federation

According to the HDI 2021 outcomes, Russia was ranked 52nd globally and 8th among G8 countries. Regarding the GII, Russia was ranked 47th globally and 8th among G8. Although sustainable development goals have been critically reviewed with respect to the Russian long-term development plan that considered all sustainability dimensions: economic, environmental, and social [10], Russia scored the lowest among G8 countries in both HDI and GII. This clearly indicates that further initiatives toward better HD practices still need to be implemented.

3. Materials and Method

The original PROMETHEE method was developed in 1982 [40] and then furtherly adjusted in 1985 [41,42]. It is currently considered a well-known, practical MCDM method [43]. In order to implement PROMETHEE considering different MCDM situations, different versions of this technique have been developed, such as PROMETHEE I and PROMETHEE II. According to various research works and applications [43,44,45], the practical steps for PROMETHEE II can be summarized and listed as follows:

Step 1: Normalization of the decision matrix [R_ij] as follows:

R_ij = [(X_ij) − min (X_ij)]/[max (X_ij) − min (X_ij)]

where X_ij is the performance measure of ith alternative with respect to jth criterion; i = 1, 2, …, n; j = 1, 2, …, m. For non-beneficial criteria, the decision matrix can be rewritten as follows:

R_ij = [max (X_ij) − (X_ij)]/[max (X_ij) − min (X_ij)]

Step 2: Pairwise measurement of the evaluative differences among alternatives.

Step 3: Determination of the preference function, P_j(i, i’), using the following function:

P_j (i, i’) = 0 if R_ij ≤ R_i’j
                  P_j (i, i’) = (R_ij − R_i’j) if R_ij > R_i’j

Step 4: Determination of the aggregated preference function π (i, i’) considering the weight of each criterion as follows:

$$\pi (i,i^{\prime })={\sum }_{j=1}^m{[W}_j\ast P_j\left(i,i^{\prime }\right)]/{\sum }_{j=1}^m{W}_j$$

where $W_j$ is the weight that represents the relative importance of criterion j.

Step 5: Identification of the “leaving (positive) flow” and the “entering (negative) flow” as follows:

$$\begin{gathered} \mathrm{Leaving}\mathrm{flow}\mathrm{for}\mathrm{alternative}i,{\phi }^{+}\left(i\right)=\frac{1}{n-1}{\sum }_{i^{\prime }=1}^n\pi \left(i,i^{\prime }\right);\left(i\ne i^{\prime }\right) \\ \mathrm{Entering}\mathrm{flow}\mathrm{for}\mathrm{alternative}i,{\phi }^{-}\left(i\right)=\frac{1}{n-1}{\sum }_{i^{\prime }=1}^n\pi \left(i^{\prime },i\right);\left(i\ne i^{\prime }\right) \end{gathered}$$

where n represents the number of involved alternatives; the “leaving flow” and the “entering flow” represent the extent to which a certain alternative is “dominating” the remaining alternatives and “dominated” by the remaining alternatives, respectively.

Step 6: Determination of the net outranking flow for alternative i follows:

$$\phi \left(i\right)={\phi }^{+}\left(i\right)-{\phi }^{-}\left(i\right)$$

Step 7: Ranking of the involved alternatives according to the values of $\phi \left(i\right)$; the alternative with the highest $\phi \left(i\right)$ represents the best alternative, and so.

Within the context of HDI, a selected number of research studies that employed different MCDM methods such as the Analytic Hierarchy Process (AHP), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Multi Attribute Utility Theory (MAUT), the Weight Balancing Indicator Ranks Accordance (WEBIRA), the Entropy Method For Determining The Criterion Weight (EMDCW), the Criteria Impact Loss (CILOS), the Integrated Determination Of Objective Criteria Weights (IDOCRIW), the Data Envelopment Analysis (DEA), the Quality Function Deployment (QFD), and the Fuzzy Weighted Average (FWA) are in

Table 2. Selected MCDM applications on HDI.

Title of the Study	Authors	Year	MCDM Methods	Context
The comparison of MCDM Methods, including AHP, TOPSIS and MAUT, with an Application on Gender Inequality Index	[16]	2016	Analytic Hierarchy Process (AHP); Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS); Multi Attribute Utility Theory (MAUT)	Gender Inequality Index
European Countries Ranking and Clustering Solution by Children’s Physical Activity and Human Development Index Using Entropy-Based Methods	[17]	2018	Weight Balancing Indicator Ranks Accordance (WEBIRA); Entropy Method For Determining The Criterion Weight (EMDCW); Criteria Impact Loss (CILOS); Integrated Determination Of Objective Criteria Weights (IDOCRIW)	HDI
An Integrated QFD and Common Weight DEA-Based Fuzzy MCDM Framework for Performance Ranking of Countries	[18]	2022	Data Envelopment Analysis (DEA); Quality Function Deployment (QFD); Fuzzy Weighted Average (FWA)	SDGs; HDI

. Additionally, further studies that employed the method of PROMETHEE, specifically, are listed in

Table 3. Selected PROMETHEE applications on HDI.

PROMETHEE Applications	Authors	Year	Context
An ordered clustering algorithm based on K-means and the PROMETHEE method	[19]	2018	HDI
An ordered clustering algorithm based on fuzzy c-means and PROMETHEE	[20]	2019	HDI
Wealth-adjusted Human Development Index	[21]	2021	HDI

. Further clarifications on how to employ PROMETHEE II in developing an innovation-based HDI are presented and discussed in detail within the next sections.

4. Application

The World Bank’s dataset provides various sets of databases covering a wide range of indicators dedicated to statistically investigating various global contemporary fields of knowledge and/or issues. Among all these indicators, the World Development Indicators (WDI) represent the main collection of development indicators due to their reliability, accuracy, and availability in handling data at national, regional, or global levels [46]. WDI data are collected from internationally recognized organizations, so the reliability of the data sources is ensured. Among WDIs, only 12 indicators were dedicated to technological aspects within the domain of infrastructural series. Accordingly, the data corresponding to the G8 countries were collected for 10 out of these 12 indicators due to missing data for the remaining 2 indicators. Although the collected data were based on the most recent available data (i.e., for 2020), a few missing figures (only 3 figures) were collected based on the most recent available data before 2020. Although some indicators were developed to measure one aspect twice in order to differentiate between residential and non-residential figures, such types of indicators were merged to represent the total number of a certain aspect as shown in

Table 4. The Collected Data *.

Country Code	High-Technology Exports (Current US$)	High-Technology Exports (% of Manufactured Exports)	Industrial Design Applications	Patent Applications	Researchers in R&D (per Million People)	Research and Development Expenditure (% of GDP)	Trademark Applications	GII **
CAN	25572229417	15.332	7530	34,565	4516.304	1.698	147,267	50.80
GER	182351776932	15.500	40,638	62,105	5393.146	3.144	264,669	57.20
FRA	87120395046	23.144	31,196	14,313	4926.189	2.355	290,194	55.00
GBR	58143796335	22.997	32,731	20,649	4683.766	1.708	278,699	59.70
ITA	32892825253	8.586	25,364	11,008	2671.835	1.534	100,872	46.10
JPN	102751095238	18.601	31,650	288,472	5454.683	3.263	421,166	53.60
RUS	6524883012	9.134	10,589	34,984	2721.681	1.098	398,240	34.30
USA	141538563122	19.484	50,743	597,172	4821.228	3.450	870,306	61.80
NOTE	- High-technology exports are products with high R&D intensity, such as aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery. - Industrial design applications are applications to register an industrial design with national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Hague System. - Patent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention--a product or process that provides a new way of doing something or offers a new technical solution to a problem. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years. - Researchers are professionals who conduct research and improve or develop concepts, theories, models, techniques, instrumentation, and software of operational methods. - Gross domestic expenditures on research and development (R&D), expressed as a percent of GDP. They include both capital and current expenditures in the four main sectors: Business enterprise, Government, Higher education, and Private non-profit. - Trademark applications filed are applications to register a trademark with a national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Madrid System.

* Source: World Bank open data [46], except the last column GII **; ** Source: Global Innovation Index 2022 [22].

(i.e., columns 4, 5, and 8) resulting in a reduction of the total number of indicators from 10 to 7 indicators. The 8th criterion was represented by the GII and collected from the Global Innovation Index report [22]. Accordingly, eight criteria were utilized to conduct the PROMETHEE II model, as shown in Table 4: (1.) High-technology exports (in USD), (2.) High-technology exports (% of manufactured exports), (3.) Industrial design applications, (4.) Patent applications, (5.) Researchers in R&D (per million people), (6.) Research and development expenditure (% of GDP), (7.) Trademark applications, and (8.) GII.

A further illustration of how the innovation-based HDI can be developed for the G8 countries using the proposed approach herein (PROMETHEE II) is presented in the next section.

5. Results and Discussion

The direct results of the PROMETHEE II application were employed such that adjustment factors can be generated in order to adjust GII original scores. The resulting PROMETHEE II scores represent the competitive advantage capabilities to be considered for each country. Hence, the influence of considering all technological criteria was represented by such a competitive advantage bonus assigned to each country to reflect its relative innovation capabilities compared to all investigated countries. The influence of the adjusted/developed GII score was then multiplied by the original HDI of each country in order to generate what is called herein the innovative-based HDI.

The results of the developed PROMETHEE II model (i.e., final PROMETHEE II results) for the USA, Japan, Germany, France, UK, Canada, Italy, and Russia were 4.171, 1.904, 1.809, 0.818, 0.436, −2.799, −2.814, and −3.526, respectively. Then, a normalized score for each G8 country was computed, considering the USA as a reference point (i.e., best practice due to its corresponding highest score). Accordingly, the normalized scores (in percentages) for the USA, Japan, Germany, France, UK, Canada, Italy, and Russia were 100.00%, 70.55%, 68.31%, 56.44%, 51.47%, 9.45%, 9.24%, and 0, respectively. These percentages were considered as adjustment factors on the original GII, as shown in

Table 5. The results of the PROMETHEE II model and the proposed innovative-based HDI.

Country Code	Original GII *	Adjustment Factor on Original GII (in %)	Non-Normalized Adjusted GII	Normalized Adjusted GII	Original HDI **	Innovation-Based HDI	Innovation-Based HDI (in %)	Rank
USA	61.8	100.00%	123.600	100.00	0.921	0.921	92.1%	1
JPN	53.6	70.55%	91.415	73.96	0.925	0.684	68.4%	3
GER	57.2	69.31%	96.844	78.35	0.942	0.738	73.8%	2
FRA	55	56.44%	86.041	69.61	0.903	0.629	62.9%	5
GBR	59.7	51.47%	90.426	73.16	0.929	0.680	68.0%	4
CAN	50.8	9.45%	55.599	44.98	0.936	0.421	42.1%	6
ITA	46.1	9.25%	50.366	40.75	0.895	0.365	36.5%	7
RUS	34.3	0.00%	34.300	27.75	0.822	0.228	22.8%	8

* Source: Global Innovation Index 2022 [22]; ** Source: Human Development Reports [23].

.

The results of multiplying each adjustment factor on original GIIs were then added to the original GIIs as a competitive advantage bonus resulting in generating non-normalized adjusted GII scores for each G8 country. The normalized version of the GII was then multiplied by the original HDI resulting in an innovative-based HDI. The last two columns in Table 5 represent the innovative-based HDI (in percentages) and the corresponding rank of each G8 country, respectively. According to the proposed innovative-based HDI, the USA, Germany, Japan, UK, France, Canada, Italy, and Russia were ranked 1st (92.1%), 2nd (73.8%), 3rd (68.4%), 4th (68.0%), 5th (62.9%), 6th (42.1%), 7th (36.5%), and 8th (22.8%), respectively. The changes in the final ranking of the innovative-based HDI compared to the original HDI are presented in

Table 6. Ranking change in the developed innovation-HDI compared to the original HDI.

Country Code	Original HDI	Original HDI Rank	Innovation-Based HDI (The Proposed HDI)	Innovation-Based HDI Rank	Ranking Change
USA	0.921	5	0.921	1	+4
GER	0.942	1	0.738	2	−1
JPN	0.925	4	0.684	3	+1
GBR	0.929	3	0.680	4	−1
FRA	0.903	6	0.629	5	+1
CAN	0.936	2	0.421	6	−4
ITA	0.895	7	0.365	7
RUS	0.822	8	0.228	8

. The ranking changes for USA, Germany, Japan, UK, France, and Canada were +4, −1, +1, −1, +1, and −4, respectively. Italy and Russia remained in the same rank, 7th and 8th, respectively.

Accordingly, Table 6 illustrates that the US jumped four positions and ranked #1 as a consequence of considering innovation within the developed HDI herein. In contrast, Canada dropped four positions. Italy and Russia remained at the bottom, which confirmed the same level of HDI regardless of GII’s influence and consideration. Aspects of the developed procedure and the final results corresponding to all G8 countries are presented in Table 5 and Table 6.

Considering the positive correlation between a circular economy with innovation, and the positive correlation between circularity and HDI from another angle as well [47], the results affirm the significance of merging innovation and HDI in order to develop a single index that reflects HD with respect to innovation capabilities. Indeed, it is stressed that the era of globalization is labeled by technological advancement that results in the movement of investments and manpower among countries which enhances the need for investigating the correlation among HDI and other indexes and/or variables such as the GII Education Index (EI) and Unemployment Rate (UR) [48]. On top of all these previous views in this regard, recent research attempts are also consistently parallel with such an orientation considering significant aspects such as benchmarking among countries [49,50,51], sustainability [49,52,53], and circular economy [54,55].

The idea of adjusting HDI for the purpose of penalizing countries’ performance towards human development has already been introduced, considering the corresponding environmental impact when 19 countries dropped at least one position in the HDI ranking list due to the consideration of the sustainability adjustment [56]. Thus, the linkage between human development and sustainability has been investigated when functional approaches have been proposed to measure them effectively; further, the most significant inference that can be concluded in this regard is that mature countries, in terms of human development, provide double efforts towards practicing sustainable tasks and such mature countries are responsible for assisting unmatured countries in achieving better sustainable development practices [57]. In order to obtain a better understanding of the practical influence of sustainability in such a development-labeled era, the linkages among HDI as well as the environmental performance index (EPI) have recently been investigated quantitatively via a dynamic panel modeling within selected countries, and it can be concluded that HDI is linked positively with EPI in a sense that “higher human capital accumulation leading to lower environmental damage and better environmental performance” [58]. Additionally, within the context of G8 countries and with the aid of the Vector Auto Regression (VAR) model and penal regression, it has been concluded that there has been a positive and significant relationship between innovation and economic growth over the last 2 decades [59]. Such a fact can also be considered in order to support the outcomes of several previous studies that handled critical sustainable development aspects in G8 countries such as research and innovation [60], efficiency estimation [61], International Energy Agency (IEA) policies [62], financing development [63], and the effect of foreign direct investment, technological innovation, and financial development on CO₂ emission [64].

Consequently, considering all these efforts within the relevant literature towards obtaining a better understanding of the linkages between HDI and sustainability, it can be concluded that G8 countries, in specific, are in need of taking forward strategic steps to draw a strategic roadmap considering any form of alliances such as global strategic projects, globalized initiatives, and unified key performance indicators (KPIs) in order to ensure developing and launching a generic and consistent performance measurement instrument among countries. Without a doubt, such critical responsibilities should be assigned to the G8 countries, the worldwide policymakers, as these countries represent reference benchmarking points through which other countries can find and follow best sustainable practices with respect to mature human development aspects.

Some critical issues such as environmental sustainability and cultural diversity represent potential topics to be investigated in future research. Indeed, a 10-year data set corresponding to the OCED countries has been critically analyzed recently in order to conclude that human development contributes positively and significantly towards better environmental sustainability [65]. Hence, the concept of the Environmental Human Development Index (EHDI) was introduced due to the fact that the missing aspect that has always been overlooked by the traditional HDI was that “it does not take into account the concept of sustainability and, more precisely, it is lacking in the environmental component specification” [66]. In addition, the social interactions embedded in cultural diversity within various communities and countries should also be considered for further investigation, as several research attempts have recently linked such a critical phenomenon to sustainable development [67,68,69]. Thus, it is recommended that comprehensive investigations should be conducted in countries labeled with low sustainability at various levels in order to obtain a deeper understanding of the causes of the weak sustainability aspects concerning human development [66].

It is also very important to note that even though the Gender-Related Development Index (GDI) and the Gender Empowerment Measure (GEM) were created to handle gender inequality issues, these indexes have always been misused in the human development reports due to the different misinterpretations, which leads to mismatched policy implementation issues at national and international levels [70].

The research attempt herein has been conducted with the assumption that the World Bank set of data represents the most commonly accepted and reliable source of global data, which is true to some extent; however, data quality and accuracy are somehow limited due to the inconsistency in data collection approaches among countries as well as due to the variety in technological capabilities in different regions worldwide. Such a dilemma necessitates the creation of a global protocol development to ensure accurate and consistent approaches for data collection worldwide.

Finally, although the corresponding literature on MCDM is rich with several methods and techniques, the simple logic behind employing PROMETHEE II herein in its simplest form is to: (1.) Utilize the available data in its current forms directly (i.e., there is no need for subjective scaling, expert opinions, or fuzzy intervals/fuzzy numbers). (2.) Avoid the complexity of almost all fuzzy MCDM methods. (3.) Focus on measuring the effectiveness of each alternative (i.e., each country in this case) in achieving the best outcome with respect to each criterion rather than focusing on measuring the efficiency of each country by looking at countries’ outputs (results) considering their inputs (resources), which can be performed by DEA. (4.) Avoid the subjectivity embedded in various methods such as in the AHP or the Interpretive Structural Modeling (ISM). (5.) Avoid the unsuitability of other methods in the current case, such as Goal Programming or Interpretive Structural Modeling (ISM).

6. Conclusions

This paper argues that the current HDI has a promising potential of considering further dimensions, specifically technological dimensions, in order to absorb various innovational aspects whenever human development is to be benchmarked among countries. Hence, the innovation-based HDI was developed herein using PROMETHEE II, considering a mixture of technological criteria, including the GII itself. The G8 countries, as leading countries worldwide, were investigated in this regard in order to attain such a benchmarking attempt. The results of the proposed HDI affirm such an argument in the sense that the ranking of the G8 countries has distinctly been changed as a consequence of considering technological and innovational aspects, compared to the original HDI (i.e., USA +4—from 5th to 1st; Canada −4, from 2nd to 6th).

From a technical point of view, this paper also affirms that MCDM methods (including PROMETHEE II) have great potential in developing global indexes. The nature of most of the MCDM techniques in handling the decision-making dilemma in the form of multiple criteria corresponding to any set of alternatives (countries in such cases) facilitates dealing with a complex and unlimited number of aspects (i.e., conflicting criteria). Moreover, the final ranking list provides a clear benchmark instrument for the countries aiming to draw their strategic vision toward achieving their global objectives, considering the performance of the best practices (i.e., countries) as global reference points. Consequently, an infinite number of indexes for the purposes of measuring various global aspects can be developed in the future by employing a huge number of WB indicators with respect to various MCDM approaches. Hence, international communities are in need of setting up commonly accepted guidelines in order to facilitate having a unified prioritization (i.e., unified preference) for the potential criteria and/or indicators to be considered globally for better sustainable development.