Modeling transitions in nation brand equity: An empirical assessment of the nation equity power grid

Abstract

The purpose of this study is to assess longitudinal nation brand performance by modeling transitions in nation brand equity and to develop a method for nation brand performance assessment. This study has two objectives: (1) to empirically test Steenkamp’s nation equity power grid conceptual framework; its categories (dominant, receding, niche, emerging, and weak nation brands), and their expected development trajectories, and (2) to identify new types of nation brands and development patterns to complement the framework. To do this, this study used objective secondary data and applied the smooth transition technique. We assessed 41 countries’ nation brand performance over the 1995–2017 period to understand the development of their nation brand equity. Particular attention was paid to countries that had significantly improved their performance and countries that had lost their brand strength. Our findings support the categories proposed by Steenkamp, but we provide a more nuanced approach to analyzing countries’ brand strength and the possible development trajectories, and introduce new categories of nation brands called volatile nation brands and booming nation brands. Our approach to using the nonlinear smooth transition demonstrated how countries’ brand strength evolved over time, and also detected the speed of any transitions; in other words, how fast nation brands moved from one level to another. Our findings benefit country brand managers, enabling them to better determine their country’s positioning and the necessary means to improve brand equity. Understanding the mechanisms behind transitions in brand equity can also help researchers link these transitions back to various economic, social, cultural, and political transitions that have occurred in nations. Our method therefore has powerful explanatory value for a wide range of marketing, economics, and other social science studies.

JEL Classification:

M31

Keywords

Brand equity nation brand nation brand index nation branding smooth transition

1. Introduction

Nation brands and nation branding have attracted considerable interest among academics, practitioners, and policymakers over the past two decades. Nation branding, according to Aronczyk (2008: 42), refers to the process that “allows national governments to better manage and control the image they project to the world, and to attract the ‘right’ kinds of investment, tourism, trade and talent, successfully competing with a growing pool of national contenders for a shrinking set of available resources.” Therefore, nation brands can be assessed through estimations of how well a brand performs in terms of exports, and in attracting tourism, immigrants and foreign direct investment (FDI) (Fetscherin, 2010). Several empirical studies have addressed the impact of strong nation brands. For example, Dimitrova et al. (2017), found that a strong nation brand contributes to improving a nation’s export volume, while numerous studies have indicated how strong nation brands attract significant amounts in domestic and foreign direct investments (FDIs) (Bose et al., 2020; Kalamova and Konrad, 2010; Lahrech et al., 2020a; Lee and Lee, 2019; Papadopoulos et al., 2016; Papadopoulos and Heslop, 2002). Studies by Caldwell and Freire (2004), Gilmore (2002), and Silvanto and Ryan (2014, 2018) have demonstrated how a strong nation brand was found to increase the number of tourists visiting a country, and to attract skilled immigrants. Furthermore, the Reputation Institute has suggested that a mere 1-point increase in a country’s reputation ranking can increase its number of tourists per capita by 0.9%, in addition to increasing export rates by 0.3% (Globenewswire, 2018). Developing a strong nation brand and increasing its strength are therefore important to various interest groups, particularly when the benefits directly relate to a country’s global status, performance, and competitiveness (Mariutti, 2017; Melnyk and Varibrusova, 2019), which then contribute significantly to the country’s gross national product (GNP) and economic development (Boisen et al., 2011, 2017; Kotler and Gertner, 2002).

Nation brands, similar to corporate or product brands, possess a significant amount of brand equity, meaning the ability to generate added financial value from well-known brands (Mariutti and Giraldi, 2021; Papadopoulos and Heslop, 2002). Numerous studies on nation branding have been conducted under the umbrella concept of place branding (e.g. Anholt, 2006; Boisen et al., 2011; Braun et al., 2014; Chan et al., 2016; Florek et al., 2019; Foroudi et al., 2016; Gertner, 2011; Hanna and Rowley, 2008), while another stream of studies has focused on smaller units of nation branding, such as city or destination branding (e.g. Florek, 2015; Florek et al., 2015; Hashim, 2012; Kerr, 2006; Lucarelli and Berg, 2011). Some studies have also addressed regional branding attempts, focusing on Africa (Abimbola, 2006), Europe (Aveline, 2006), the Nordic countries (Magnus, 2016), the Baltic Sea region (Andersson and Paajanen, 2012), and the Middle East (Cooper and Momani, 2009). Regardless of the different scope of the studies, all place brands, whether country, city, destination or region, have been found to possess significant brand equity.

While a strong nation brand is seen to reflect that nation’s progress and development, active investment in nation branding also assists further development. Any tangible achievements in making a country more competitive and unique can be actively promoted through marketing efforts, which are expected to further strengthen the nation brand and generate increased tourism, investment, trade, and other tangible and intangible benefits than bring economic benefits (Zeinalpour et al., 2013). Such efforts, however, naturally require a significant amount of resources. Since funding for place branding projects often comes from public sources, it requires objective performance evaluation to gain support from various stakeholders; hence, policymakers need tools for assessing brand performance in order to justify granting sufficient resources for such purposes and to raise public awareness of the importance of nation branding (Florek et al., 2019; Zenker, 2014).

While nation branding is undeniably important for any country, research on nation brand management is still nascent. In their comprehensive review of nation branding literature published during the past two decades, Hao et al. (2019) addressed the limitations of the existing studies, which sparked the motivation for the present research. They noted that, while numerous scholarly studies have investigated individual countries’ branding attempts, there is a lack of knowledge on how to measure nation brand strength and performance, and how nations’ brands have developed over time. Longitudinal studies on nation branding, in particular, have remained scarce, and such studies are necessary for enhancing understanding of how nation brand equity can change over time due to various macroenvironmental factors (Hao et al., 2019). Furthermore, nation brand managers need tools for assessing how to achieve an optimal balance when investing in different strands of the brand so that the country can maximize its resource use, considering the aspects of resource scarcity, while also ensuring that resources are not idle. Following the basic principles of macroeconomics, such as the theory on the production possibility frontier, there are various trade-offs in managerial decision-making where investing in one area will result in decreasing the possibility of investing in another area and therefore one needs to find an optimal balance to compete effectively (Galles et al., 2019). The development of nation brand management tools for this purpose is therefore important, so that countries can optimize their resource outputs across all significant elements of a nation brand, rather than prioritize only some of them. For example, countries such as Australia and New Zealand have received criticism for their brand management strategy that seems to emphasize the tourism aspect while undermining the importance of other elements of the nation brand (Hall, 2010; Khamis, 2012; Pomering, 2013). Such distortions may result from a lack of nation brand management tools to understand the different facets of the nation brand and how each of these contributes to the total value of the nation brand and its role in global and regional competition.

The purpose of this study is to assess longitudinal nation brand performance by modeling transitions in nation brand equity and developing a method for nation brand performance assessment. To do this, we employed Steenkamp’s (2021) nation equity power grid as our conceptual framework, which has been proposed as a potential tool for measuring and monitoring nation brand equity over time and comparing nations’ performance to that of other nations. Our aim is to empirically test this model and its expected development trajectories, as well as to identify new types of nation brand categories by developing a method that uses objective secondary data and the smooth transition modeling technique. Our findings support this model and its main types of country brands, but our findings indicate that the development trajectories of countries’ brand performance are expected to be more gradual than those proposed in the original framework. Our paper thus contributes to emerging studies measuring nation brand management (Fetscherin, 2010; Lahrech et al., 2020b; Steenkamp, 2021) in two ways. (1) We introduce two new categories of nation brands called volatile nation brands and booming nation brands, which contributes to the theory of nation brand management. (2) We developed a nonlinear assessment method for assessing nation brand performance based on objective statistical data and modeling transitions in nation brand equity with the help of the smooth transition modeling technique. Our approach facilitates the analysis of nation brand equity over a significantly longer period than existing survey-based nation brand indices. It also signals the speed of brand development and allows for the assessment of the relative performance of a nation brand compared to its peers.

2. Review of studies assessing nation brand equity

2.1. Assessing nation brand equity through nation brand indices

Probably the most well-known instruments for measuring nation brand equity are the popular annual survey-based nation brand indices developed by practitioners, such as the Nation Brands Index (NBI) developed by Simon Anholt and the FutureBrand Country Brand Index (CBI) created by the FutureBrand Consultancy. Both indices have published annual country rankings since 2005. The NBI ranks countries based on people’s perceptions of a country across six areas of its competence (called the “hexagon”): exports (the public’s image of a country’s products and services), governance (public opinion about the national government’s competence and fairness, and its commitment to global issues), investment and immigration (the power to attract skilled people to live, work, or study in a country and how those people perceive a country’s quality of life and business environment), culture (global perceptions of each nation’s heritage and appreciation for its contemporary culture), people (the population’s reputation for competence, openness, friendliness, and other qualities such as tolerance), and tourism (the level of interest in visiting a country and the draw of natural and man-made tourist attractions (Ipsos, 2021)). The CBI assesses countries according to somewhat different dimensions. Originally, it included five dimensions—value system, quality of life, business potential, heritage and culture, and tourism—in its ranking of countries, but since its 2014–2015 ranking, it has added the sixth dimension of made in (FutureBrand, 2014, 2019). The “made-in” effect, also known as the “country-of-origin” effect, is based on the findings of several studies that have established the linkage between “made-in” or “country-of-origin” effects and nation brands (e.g. Pappu et al., 2006; Sun and Paswan, 2011; Verlegh and Steenkamp, 1999).

While both the NBI and the CBI have released annual nation brand rankings since 2005, their coverage is not sufficient for the longitudinal evaluation of nations’ brand performance. Furthermore, survey-based indices always pose a risk of bias, since they capture only one aspect of brand equity—consumer-based brand equity (Florek et al., 2019; Keller, 1993). This approach views consumers’ perceptions and mental images of countries. An alternative approach for measuring brand strength is the performance-based approach, sometimes referred to as the “company-based brand equity approach” (Fetscherin, 2010), which focuses on assessing tangible and measurable aspects of a country’s performance through statistical data (Atilgan et al., 2005). This statistics-based brand equity approach, according to many scholars (e.g. Fetscherin, 2010; Lahrech et al., 2020b), can offer a more objective way of measuring country brand strength and what a country has achieved, enabling longitudinal assessment of how brand strength and equity change over time. This approach can reveal a country’s actual investment and progress in relation to the underlying foundations of the nation brand, which is necessary to improve the country’s image and, hence, its reputation (Foroudi et al., 2016).

To the best of our knowledge, only a few existing studies have aimed to measure nation brand performance by using the performance-based brand equity approach. The first such study was completed by Fetscherin (2010), who developed the country brand strength index (CBSI) to measure 32 countries’ brand performance across five dimensions (exporting, tourism, FDI, immigration, and government environment) for 2007 using secondary data. The findings of the study correlated significantly with the Anholt NBI results, since they used similar factors to assess the nations’ brands, albeit with different sets of data. Exporting, tourism, FDI, and immigration were measured using per capita statistical data, while the government environment was measured through the governance environment index developed by Li and Filer (2007), which included the following indicators: exercise of political rights, rule of law, public trust, free flow of information, and level of corruption.

In another study, Lahrech et al. (2020b) further developed the CBSI to rank the brand performance of 131 countries over the 2007–2015 period. The stated purpose of creating the new index, named the “modified country brand strength index” (MCBSI), was to develop a complementary index for the Anholt NBI that would have a stronger correlation with it than the CBSI (Lahrech et al., 2020b). The MCBSI model assessed countries using the same dimensions as the CBSI, but included also human development index to capture the soft aspects of nation brands. Similar to the CBSI, it used statistical data, but employed relative values instead of per capita measures, which the authors claimed provided more objective figures (Lahrech et al., 2020b). Although the study used longitudinal data, it did not explain why certain countries’ rankings had significantly changed over the assessed years, which was a limitation of the study.

2.2. Synthesizing common dimensions used in assessing nation brand equity

Despite advances in the measuring of nation brand equity, debates about the aspects of nation brands that matter most are still ongoing (e.g. Mariutti and Tench, 2015; Melnyk and Varibrusova, 2019; Rojas-Méndez, 2013; Steenkamp, 2021). While there is not, and perhaps never will be, a single set of dimensions for assessing country brands, the existing nation brand indices suggest that certain commonly used factors can serve as a starting point for studies measuring nation brand equity. Table 1 summarizes the dimensions used in the indices reviewed in the earlier paragraphs.

Table 1.

Dimensions used in nation brand indices.

Index	Dimensions used	Sources of data	Type of brand equity approach	Number of countries ranked
Anholt Nation Brands Index (NBI)	Export, governance, investment and immigration, culture, tourism, people	Consumer survey	Consumer-based	50
Futurebrand Country Brand Index (CBI)	Value system, quality of life, business potential, heritage and culture, tourism, made in effect	Consumer survey	Consumer-based	75
Country Brand Strength Index (CBSI)	Export, governance, FDI, immigration, tourism	Secondary data	Statistics-based	32
Modified Country Brand Strength Index M(CBSI)	Export, governance, FDI, immigration, tourism, Human development index	Secondary data	Statistics-based	131

FDI: foreign direct investment.

Across the reviewed indices, the dimensions most commonly used to assess nation brand performance are tourism, governance, exports and investment. Tourism and exports are mentioned in all four indices, as the made in element of the CBI is linked to exports. Three of the four indices refer to governance/government and investment and immigration; as secondary data are also available for these dimensions, they were included in our model. Culture and people-related aspects are also measured through some of the indices, but, we excluded these dimensions for methodological reasons. While those dimensions are important for nation brand equity, their assessment requires comprehensive longitudinal composite indices, which were unavailable for the study period, or had changed their methodology during that time period.

2.3. Empirical assessments of nation brand equity: scales and frameworks

Since countries spend billions of dollars on their nation branding and marketing efforts, the stakeholders naturally expect returns on such investment and the ability to assess the effectiveness of branding attempts across a range of critical success factors. Consequently, an increasing number of recent academic studies on place brand management have developed assessment tools and frameworks to measure and monitor the success of such branding attempts (e.g. Bose et al., 2016, 2020; Lee and Lee, 2019; Rani, 2019; Steenkamp, 2021). These studies have often focused on assessing a country’s performance according to one or a few of the common dimensions of nation brands. Bose et al. (2016), for example, developed a scale to measure place brand equity from an investment attractiveness perspective that included aspects of brand awareness, brand image, perceived quality, and brand loyalty. Rani (2019), however, developed a four-component model to assess the same aspects as Bose et al. (2016) to determine how they affected place branding and helped to attract tourism. In another study, Bose et al. (2020) developed a scale for assessing place brand equity from the perspective of public diplomacy. The scale was intended to measure how recognizable a place was to the target audience and what kind of positive or negative images the targeted people had of the place. Elsewhere, Lee and Lee (2019) used the NBI framework to explain how the South Korean nation brand was developed strategically by its government to attract foreign investments through multinational corporations, which consequently boosted Korea’s reputation for strong research and development (R&D) performance. This, in turn, affected consumers’ brand-equity perceptions of the country’s products, making them more nation-brand desirable. Although these previously mentioned works advanced the assessment of place brand performance, they focused only on the consumer brand equity approach and were limited to only a few aspects of nation brand equity, such as investment or tourism. Consequently, more research and tools are needed to measure nation brand performance, which would include a more comprehensive view of the different factors that comprise nation brands. Moreover, most of the previously discussed studies used either survey- or interview-based data, which is cross-sectional and can be subjective in nature. This limitation encouraged us to develop a statistics-based nation brand equity assessment tool using objective, longitudinal secondary data.

2.4. Toward longitudinal nation brand equity assessment: the nation equity power grid

In a recent study on nation brand management, Steenkamp (2021) developed the nation equity power grid for use as a tool for measuring and monitoring nation brand equity. The grid is based on two dimensions: nation vitality, which consists of the combined strengths of the differentiation, relevance, and energy of a nation, and nation stature, which consists of perceived national esteem and knowledge about the country. According to Steenkamp (2021), a nation’s vitality essentially results from the growth of its nation brand equity, while a nation’s stature relates to the longevity of the brand equity. Nations can fall into one of four quadrants of the grid: dominant nation brands, receding nation brands, niche/emerging nation brands, and weak nation brands, as depicted in Figure 1.

Figure 1.

Nation equity power grid (authors’ illustration based on Steenkamp, 2021: 11).

According to the model, the dominant nation brands are those of countries that possess high stature and vitality and such countries are considered to be the ones setting global trends and leading and shaping global economic, political, and cultural environments (Steenkamp, 2021). Their position may be difficult for other countries to challenge. Receding nation brands are those that were once dominant nation brands, but which have lost their vitality and competitiveness, although they are still held in high esteem for nostalgic reasons. Steenkamp (2021) categorized niche and emerging nation brands as benefiting from high vitality, which gives them significant growth potential, but means that they suffer from low nation brand stature compared to dominant and receding nation brands. Finally, weak nation brands are those with low scores for both vitality and stature, describing countries that many people may know little about or not even be aware of (Steenkamp, 2021).

The nation equity power grid is particularly interesting, because it proposes two development trajectories in nation brand performance, what Steenkamp (2021) describes as “two common trajectories” (p. 11). First expected trajectory is when a weak nation brand moves, via a niche or emerging nation brand, to become a dominant nation brand, and a second is when a previously dominant nation loses its brand strength and turns into a receding brand and ultimately into weak nation brand, unless it is able to revive the brand (Steenkamp, 2021). Steenkamp (2021) proposed that the United Kingdom could be considered an example of a country that has shifted from a dominant nation to a receding nation, since it was once known as a world leader due to its domestic industries, institutions, and culture. Conceptually, this model can assist country brand managers to assess their country’s performance on the grid, but to the best of our knowledge, the model has not yet been validated by empirical data. Furthermore, the nation equity power grid may be a somewhat simplistic categorization of nation brands and the expected development patterns, and other possible development patterns and country brand types may be discovered.

3. Methodology

The literature review discussed in the previous section revealed that the most commonly used factors for assessing nation brand performance were exports, investments, immigration, tourism, and governance, which served as the starting point for our study. In order to assess longitudinal nation brand performance, our methodology consisted of three steps: creation of a longitudinal nation brand index, followed by application of smooth transition modeling to assess countries’ ranking and any changes in their long-term brand performance, and finally we used a clustering method to partition the data into clusters for data analysis. These steps are discussed in more detail in the following subsections, which discuss our research design.

3.1. Step 1: constructing a longitudinal nation brand index

First, to create the index, we built a dataset for a number of countries for which historical secondary data on different dimensions of nation brand equity were publicly available. As discussed earlier, we wanted to assess the countries’ longitudinal brand performance through the factors of export, investment, immigration, tourism, and governance. These same factors were also used in the Fetscherin (2010) CBSI ranking. We aimed to gather panel data for a number of countries for the longest possible period for which data was available. Longitudinal data for export, investment, immigration, and tourism were obtained from the World Bank, while the governance data were obtained from the PRG/International Country Risk Guide, which includes corruption, law and order, and bureaucratic quality as indicators of governance. Consequently, we identified 41 countries for which all the necessary data was available from 1995 to 2017 (see Table 2 for a list of the countries). Informed by Fetscherin (2010), we constructed the CBSI as follows

Table 2.

Augmented Dicky Fuller test prior to the fitting of smooth transition modeling.

Country	Augmented Dickey-Fuller Test p-value	Country	Augmented Dickey-Fuller Test p-value
Argentina	0.8575	Jordan	0.7824
Australia	0.522	Kuwait	0.5941
Austria	0.4317	Morocco	0.6413
Bahrain	0.5147	Netherlands	0.4876
Belgium	0.07806	Norway	0.3464
Brazil	0.3273	Paraguay	0.8831
Canada	0.5753	Peru	0.8879
Chile	0.3203	Philippines	0.609
China	0.809	Portugal	0.2781
Columbia	0.5982	Singapore	0.4004
Costa Rica	0.8797	South Africa	0.1018
Egypt	0.6515	South Korea	0.6621
Finland	0.3366	Sweden	0.8243
France	0.6649	Taiwan	0.7079
Haiti	0.3919	Thailand	0.4203
Iceland	0.3623	Tunisia	0.655
India	0.5077	Turkey	0.8265
Indonesia	0.1385	United Kingdom	0.5656
Israel	0.05293	United States	0.7132
Italy	0.2144	Uruguay	0.7242
Jamaica	0.6221

C B S I_{i t} = N e x p o r t_{i t} + N f d i_{i t} + N g o v e r n a n c e_{i t} + N i m m i g r a t i o n_{i t} + N t o u r i s m_{i t}

(1)

Where

N v a r i a b l e_{i t} = N o r m a l i z e d s c o r e o f v a r i a b l e_{i t} = \frac{v a r i a b l e_{i t} - M e a n (v a r i a b l e_{i t})}{S t a n d a r d d e v i a t i o n (v a r i a b l e_{i t})}

The subscript i corresponds to the country and the subscript t corresponds to the year from 1995 to 2017. After normalizing the data, we summed all the normalized scores to create the index.

3.2. Step 2: smooth transition modeling

After calculating the longitudinal CBSI index for the sample countries, we applied smooth transition modeling to determine the performance of each country according to its CBSI position over time, whether the country had shifted from one regime to another, and how fast such transition had occurred. Regime one in smooth transition was controlled by coefficient α and regime two was controlled by coefficient α + β. The speed of the transition from regime one to regime two was controlled by γ; the higher the γ coefficient, the faster the transition from one regime to another.

We used the smooth transition modeling suggested by Granger and Teräsvirta (1993) and Lin and Teräsvirta (1994) to determine any structural changes in the nations’ brand index time series. Smooth transition analysis has been used to examine the growth effects of liberalization (Leybourne et al., 1997) or disinﬂationary experiences of Australia, Canada and New Zealand (Leybourne and Mizen, 1999). The smooth transition model was also applied to equity market co-movement between Central and Eastern European countries (Hungary, Poland, the Czech Republic, and Russia) and equity markets in developed countries (Chelley-Steeley, 2005). Compared to these broad economic studies, to the best of our knowledge, smooth transition modeling has been used less frequently in marketing studies.

For the purposes of the research, the model could measure changes in the nation brand indices over time, allowing for a smooth transition between two or three periods. This was accomplished by ﬁtting a nonlinear trend to these indices and thus estimating the commencement and duration of a transition period during which nation brand index ranking increased or decreased. We considered the following logistic smooth transition regression model for the time series $N_{i t}$

N_{i t} = α + β S_{t} (γ, τ) + u_{t}

(2)

where ut is a zero mean stationary (0) process. The smooth transition between the two time periods or regimes is controlled by the logistic function $S_{t} (γ, τ)$ defined as

S_{t} (γ, τ) = {[1 + \exp (- γ (t - τ T))]}^{- 1}, γ > 0

where T is the sample size, i refers to the country’s brand index (CBSI) and t refers to time. The assessment period was 1995–2017. Before applying smooth transition, the stationarity of the CBSI series must be inspected for each country over time. A stationary series implies a horizontal fluctuation and only one level, with no trend from one level to another; in such cases, the smooth transition approach cannot be applied. By contrast, non-stationary series indicate non-horizontal fluctuations and a trend involving at least two stationary levels or regimes in the country’s CBSI series, and smooth transition modeling can be applied. The model assumes a smooth change from one stationary regime with mean α to another stationary regime with mean α + β. If β > 0, it indicates an upward trend; however, if β < 0, it indicates a downward trend. Change between two levels or regimes is controlled by the parameter γ, which determines the speed of transition from one level or regime to another one. Small γ values indicate a gradual change while large γ values signal an abrupt, rapid change. The parameter τ specifies the timing of the transition midpoint, representing halfway in the move from regime one to regime two.

As explained earlier, the CBSI series must be tested for stationarity before the smooth transition model can be applied. To verify this, we used the Augmented Dickey–Fuller test (Dickey and Fuller, 1979). The results of the test (see Table 2) indicate that we failed to reject the null hypothesis of the unit root in each country’s CBSI time series, as all p-values are greater than 5%. In short, all series were non-stationary, indicating at least two stationary levels or regimes, and smooth transition modeling can be applied.

3.3. Step 3: clustering

The third step in our methodology is the use of a clustering method to partition level-1 α coefficients and level-2 α + β coefficients data into groups. There are many clustering methods and techniques to partition the data into clusters, but k-means is the simplest and most well-known one. The k-means method is based on minimizing the sum of square error (SSE) between the mean of the cluster and the data point within the cluster. The idea behind it is to partition the data into k clusters so that each data point or observation belongs to the cluster with the nearest mean. The existence of outliers in a dataset can be an issue for k-means, since it can yield a non-representative cluster (Barnett and Lewis, 1994). An alternative method that is robust to the presence of outliers is the k-medoids method (Kaufman and Rousseeuw, 1990), where data points are selected as medoids rather than around the mean. In other words, each data point or observation belongs to the cluster with the nearest medoid rather than the nearest mean as in the k-means method. A medoid of a cluster is considered as the data point with the smallest average distance to other data points within the same cluster and it is therefore located in the middle of the cluster. This makes the k-medoids method robust to the existence of outliers. Since the United States was identified as an outlier country in our dataset (see Appendix 1), k-medoids was selected as an appropriate clustering method.

In following the k-medoids clustering method, the data implied the number of clusters/groups in the level-1 α coefficient and the level-2 α + β coefficient. The results from this clustering revealed three clusters in each level using the elbow and within-cluster sum of squares (WSS) methods (see Figure 2).

Figure 2.

Clustering with the elbow and within-cluster sum of square (WSS) methods. (a) and (b) Number of clusters.

The clustering indicates that while there are three types of nation brands that have experienced rather steady development over time—that is, they have remained within the same cluster—there are also certain (groups of) countries that have gone through unique development patterns, which will require further elaboration. Table 3 below presents the different clusters of countries and shifts of certain countries between the clusters, as well as the mean and median values placing them in a given cluster. Countries’ positions and transitions are based on their α coefficients and their corresponding α, β, α + β, and γ values over the assessed years 1995 to 2017. The next chapters discuss our empirical results regarding different nation brand types in more detail.

Table 3.

Clusters for level 1 and level 2.

Cluster A
Mean(L1) = 6.712							Mean(L2) = 7.174					Median(L1) = 4.390						Median(L2) = 5.528
L1	Norway	Italy	Australia				Sweden	Canada		South Korea		France	UK	USA
L2	Norway					China	Sweden					France	UK	USA			Finland
Cluster B
Mean(L1) = 1.286							Mean(L2) = 0.751					Median(L1) = 1.398						Median(L2) = 0.301
L1	Jordan			South Africa	India	China	Singapore		Chile		Portugal	Morocco	Israel	Austria		Taiwan	Finland				Netherlands	Iceland	Belgium
L2		Italy	Australia	South Africa	India		Singapore	Canada	Chile	South Korea	Portugal	Morocco	Israel	Austria	Indonesia	Taiwan		Brazil	Turkey	Thailand	Netherlands	Iceland	Belgium
Cluster C
Mean(L1) =-1.935							Mean(L2) =-2.230					Median(L1) =-1.815						Median(L2) =-2.345
L1				Haiti	Peru	Uruguay	Colombia		Jamaica		Philippines	Tunisia	Egypt	Paraguay	Indonesia	Kuwait	Costa Rica	Brazil	Turkey	Thailand	Argentina	Bahrain
L2	Jordan			Haiti	Peru	Uruguay	Colombia		Jamaica		Philippines	Tunisia	Egypt	Paraguay		Kuwait	Costa Rica				Argentina	Bahrain

L1: Level One; L2: Level Two.

4. Empirical results: part 1

The results show clustering applied to level 1 (α) and level 2 (α + β), both of which were obtained from smooth transition results using equation (2) applied for the constructed nation brand index from equation (1). We explored Steenkamp’s (2021) nation equity power grid model and its nation brand categories in the first step of the data analysis, as we expected to identify such countries. In this step, we focused on identifying those categories described as weak, emerging, niche and dominant nation brands. The following sections describe these expected categories in more detail.

4.1. Weak nation brands

Of the assessed countries, weak nation brands (Cluster C in Table 3) include Haiti, Peru, Uruguay, Colombia, Jamaica, the Philippines, Tunisia, Egypt, Paraguay, Kuwait, Costa Rica, Argentina and Bahrain, which originally had and retained a weak nation brand. This finding thus aligns with how Steenkamp characterized such countries, as those countries that “people around the world know little about” and which have low vitality and stature (Steenkamp, 2021: 12). Therefore, such countries would require significant brand development attempts to improve their status.

4.2. Emerging nation brands

Steenkamp (2021) characterized emerging nation brands as those countries that “are seen as upcoming, dynamic and innovative but do not have the required brand stature” (p. 12). Thus, they are expected to have demonstrated significant development at least in some aspects of the brand. In our model, emerging nation brands are those countries that originally belonged to Cluster C (weak nation brand), but which shifted over the assessed time period to a higher category (Cluster B). Hence, they have demonstrated their ability to strengthen their nation brands, as they have been able to shift upward. Such countries include Indonesia, Brazil, Turkey and Thailand. For an example of such a shift, Figure 3 below presents the underlying breakdown of the nation brand elements in the case of Indonesia’s nation brand development. From this we can conclude that the most significant factors in boosting Indonesia’s brand over the years, especially after 2005, were tourism, FDI, exports, and governance.

Figure 3.

Breakdown of the nation brand variables in development of Indonesia’s nation brand.

4.3. Niche nation brands

Niche country brands are those that, according to Steenkamp (2021), have high brand vitality, often in a specific area of the brand, such as economic development, culture, or political systems, but not across all elements of the nation brand. According to our cluster analysis, the countries in Cluster B represent niche nation brands, which include South Africa, India, Singapore, Chile, Portugal, Morocco, Israel, Austria, Taiwan, the Netherlands, Iceland and Belgium. Such countries have been successful in building strong and stably developing niche brands. In this category, the speed of development has been significantly faster than in the emerging nation brand category (see Table 3 for the mean and median values). For example, Israel benefits from its reputation as the world’s leading country in attracting and supporting innovation and start-up companies, but at the same time it has certain weaknesses in its political environment in the long-term disputes between Israel and the Arab countries (Dubinsky, 2022). Therefore, as an example, it can be argued that while Israel’s nation brand has strengths, it also has certain weaknesses in some areas of its nation brand, which places it into this category. At the same time, arguably none of these countries has a strong nation brand across all elements of nation branding.

4.4. Dominant nation brands

Dominant nation brands are understood as being the leading brands that benefit from high stature and high vitality (Steenkamp, 2021). We identified the United States, the United Kingdom, France, Norway and Sweden as dominant nation brands, which have been able to maintain their position in this competitive category (Cluster A). The mean and median values in levels 1 and 2 in Table 3 for this leading cluster mean that such countries are also rapidly developing their nation brand strength compared to those in Cluster B (niche nation brands), which makes it difficult for niche countries to make the shift into the dominant nation brand category. This supports the findings of many scholars (e.g. Anholt, 2010; Fetscherin, 2010; Steenkamp, 2021) that once a country has been able to reach such a position, it is difficult to be challenged.

4.5. Receding nation brands

As characterized by Steenkamp (2021), receding country brands include those countries that used to be dominant nation brands, but lost their vitality, and hence are no longer among the dominant brands. Steenkamp (2021) further stated that such countries “struggle to maintain their relevance, energy and perhaps even differentiation in a changed marketplace” (p. 12). We identified four such countries (Italy, Australia, Canada and South Korea) that were initially positioned in the dominant brand category (Cluster A), but their brand strength has decreased over time, placing them in Cluster B. This means that such countries are today better described as niche nation brands. While their position is still rather strong, and their performance across many of the nation brand elements is strong, their development has been more stagnant compared to the dominant nation brands and they have not been able to develop their brands at the same speed as their original peers in the dominant nation brand category. It may be that such receding country brands are also prioritizing their brand management strategies in a way that places more value on some brand aspects such as tourism, while undermining other important brand elements, which may cause the nation brand to lose its overall strength. For example, Australia’s brand management strategies have been criticized for relying on such an approach in the past, with its main focus on tourism promotion (Pomering, 2013), but more recently the country has engaged in various campaigns to re-brand the nation to be better positioned in a globalized world and to attract investment and immigrants, and boost its trade (Khamis, 2012). Therefore, from a brand management perspective, receding nation brands may have potential and resources for improving the brand strength, but a country may not fully optimize its resource use. Through more careful resource allocation and comprehensive brand building, these countries may be able to strengthen the basic pillars of their brands and improve their status to avoid further loss of brand strength.

5. Empirical results: part 2

In addition to identifying the expected nation brand categories described by Steenkamp (2021), as discussed in the previous chapter, our data also indicated unique development patterns in country brand strength, which signal that certain countries belong to new types of country brands not depicted by Steenkamp. These will be discussed next.

5.1. Volatile nation brands

In Table 3, Jordan is identified as representing a new type of negative nation brand development pattern that we label as “volatile nation brand.” The volatile nation brand is witnessed when a country that was once among emerging nation brands has experienced volatility in its development, which has caused a significant decline in the brand strength. Figure 4 below presents the breakdown of nation brand components and illustrates that while Jordan has improved its tourism, export and immigration over the years, it has faced decline in FDI and governance environment.

Figure 4.

Breakdown of the nation brand variables in development of Jordan’s nation brand.

5.2. Booming nation brands

Booming nation brands is the second new category revealed by our data. A booming nation brand is one that has been able to develop its brand strength significantly faster than any of its peers across the assessed years, moving to a position as a new entrant in the dominant nation brand category. China and Finland can be seen to have experienced such development. Figure 5 presents the breakdown of China’s nation brand elements and illustrates that, despite volatility in its governance environment, it has improved significantly in terms of other aspects of the brand. However, due to a recent decrease in its FDI, it may be expected that while China may continue to develop its brand strength and influence in the global world, it may not do so with the same speed as in the past.

Figure 5.

Breakdown of the nation brand variables in development of China’s nation brand.

Figure 6 below presents the breakdown of Finland’s nation brand components over the assessed years. It indicates that while the other aspects of its brand are strong, FDI has experienced some fluctuation. However, due to its strong performance in governance, the country may be able to improve its ability to attract FDI.

Figure 6.

Breakdown of the nation brand variables in development of Finland’s nation brand.

6. Conclusion

While there have been recent advances in studies on nation branding assessment and brand equity, it is still a nascent area of research compared to similar research on city/destination branding or place branding (e.g. Bose et al., 2020; Cleave and Arku, 2017; Florek, 2015; Herezniak and Anders-Morawska, 2015; Rani, 2019). According to a review of place branding effectiveness assessment, Florek et al. (2019) found that most existing scholarly studies in this domain, and well-known nation brand indices, such as the Nation Brands Index developed by Simon Anholt and the Country Brand Index created by the FutureBrand Consultancy, focused on consumer brand equity, with performance-based brand equity receiving less attention, perhaps due to the more complex methods needed to study it empirically. However, even Anholt (2006) has criticized the use of survey-based data, which are prone to bias if the sample is limited or respondents come from different backgrounds. Therefore, recent attempts to build alternative nation brand indices have adopted a performance-based brand equity perspective (Fetscherin, 2010; Lahrech et al., 2020b), using secondary data to measure nation brand equity. Adopting a similar approach, we used secondary data to assess longitudinal brand equity development, employing smooth transition modeling to test the categories and expected development trajectories of Steenkamp’s (2021) nation brand equity grid.

We assessed 41 countries’ nation brand performance over 1995–2017 to understand the development of their nation brand equity. Our findings support the country brand types proposed by Steenkamp (2021). The “two common trajectories” (Steenkamp, 2021: 11) of the model, the first in which a weak nation brand moves to a niche or emerging nation brand to become a dominant nation brand, and the second in which a previously dominant nation declines to become a receding and ultimately weak nation brand, are partially supported by our findings. We argue that while such development trajectories are possible, movement from one extreme to another is rare. The latter trajectory is rare, as it would require a significant socio-economic disruption in such a country. Furthermore, the former development trajectory is also rare, since most countries are constantly strengthening their nation brands, which therefore makes the development of a weak nation brand into a dominant nation brand very challenging. In other words, such a country would have to perform at an exceptional level in terms of its development. Thus, while extreme shifts in nation brand strength are rare, our model identified more realistic development patterns by identifying new types of volatile and booming nation brands, in terms of which a country was able to shift its position upward or downward one category based on its development over two decades.

We propose that further studies should focus especially on those countries identified as having a volatile or booming nation brand, as both these types are currently neglected areas in research. These phenomena are of great interest to researchers in developing a more detailed understanding of the underlying reasons and identifying measures to improve the brand. For nations that have lost brand equity, studies of brand revitalization strategies (e.g. Rodner and Kerrigan, 2018) and rebranding (e.g. Amujo and Otubanjo, 2012) can offer valuable insights. Booming nation brands, on the other hand, can be revealing examples of brand re-positioning or of wider large-scale socio-economic development.

Our study contributes to emerging research on nation brand management (Fetscherin, 2010; Lahrech et al., 2020b; Steenkamp, 2021). In addition to identifying new types of country brand profiles (volatile and booming nation brands) to complement Steenkamp’s pioneering work, we developed a comprehensive method for assessing longitudinal brand strength over a longer period than in previous empirical studies. In addition, to the best of our knowledge, no previous study has used smooth transition modeling to study nation brand equity. While this method has been used in economic research, its application to nation brand equity assessment is a novel approach. Our approach of using the nonlinear smooth transition model proved to be a powerful tool for assessing longitudinal nation brand performance, since it not only indicated how countries’ brand strength evolved over time, and the relative performance of countries compared to their peers, but also precisely identified the speed of transitions, in other words, how fast nation brands moved from one level to another.

Our study revealed several interesting findings that are not only of great importance to nation branding research, but also open a new pathway for using data-driven models in such research. According to our model, α, β, and γ are the three important coefficients that control the evolution over time of a country’s nation brand performance. More precisely, researchers should consider the three coefficients together in order to understand how a nation brand evolves from one regime to another and how fast the transition takes place. This would allow policymakers to determine their countries’ standing in terms of brand performance, and whether their countries’ brands are evolving and how fast; thus, our model provides an econometric tool to help policymakers to assess the effect of any policy changes aimed at enhancing the brand of a nation and assessing how fast the results of such policy changes are likely to be reflected in the actual performance of the country. Our applied method is also important for academics, since understanding the mechanisms behind transitions from one regime to another can also help researchers link these transitions back to various economic, social, cultural, and political transitions that have occurred in nations. Our method therefore has powerful explanatory value for a wide range of marketing, economics, and other social science studies.

Our study has some limitations. To date, there is still no common agreement on how brand performance should be operationally measured, what the most appropriate methods of assessment are, or what indicators should be considered to measure it (Florek et al., 2019); thus, our selected indicators are not necessarily the only ones applicable for the stated purpose. Future studies could extend our approach by considering additional aspects of nation brands and using relevant secondary data with appropriate indicators; for example, culture and heritage are commonly used variables in nation brand assessment and future studies could assess nation brand performance by including these variables once secondary data become more widely available. In addition, our findings are limited to the 1995–2017 period, as secondary data for all dimensions were not available beyond that time. Future studies would benefit from assessing countries’ performance over a longer time span. Finally, we were not able to discuss in detail any of the sample countries’ more specific nation brand development trajectories, which should be addressed by further research.

Footnotes

Appendix

Acknowledgements

We are grateful to the editor and anonymous reviewers of Australian Journal of Management for their constructive comments and suggestions.

Final transcript accepted 09 October 2022 by Dr. Andrew Jackson.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Abdelmounaim Lahrech

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