Evaluating the Economic Sustainability of Two Selected Urban Centers—A Focus on Amherst and Braintree, MA, USA

Abstract

While the topic of sustainable development has been extensively explored, there is a lack of quantitative assessment of economic sustainability in the scientific literature; moreover, the term is often interpreted with excessive attention to the environment but not socio-economic inequality. In addition, university cities are often considered the most sustainable, although the higher education system in the United States is often criticized for the inequality of access to it among different racial and other groups of the population. This paper adds to the debate about how the concepts of sustainability and economic development relate. Many researchers have noted that they come into conflict with each other because their ultimate goals are fundamentally different: a voluntary limitation of production and consumption in the interests of future generations and, conversely, the pursuit of well-being during our lives. We would like to explore the issue of economic sustainability, which, at first glance, may become a compromise between the two approaches outlined above. So, our study is devoted to exploring the ambiguous concept of economic sustainability, which can add some new knowledge to the understanding of how social, economic, and ecological factors relate to each other in the broader framework of sustainability. For this objective, we analyzed the economic sustainability of the town of Amherst, MA. The city’s top employer and core enterprise is the University of Massachusetts Amherst, with over 32,000 students and almost 2000 staff members. Based on a literature review, a hypothesis was put forward that a university city should have a high level of economic sustainability. To assess economic sustainability, the original methodology based on the US Cities Economic Sustainability Index (USCESI) was developed. It evaluates sustainability in three groups of parameters: society, economy, and ecology. The first group includes the level of racial diversity, the level of education of the population, and the access to medical services. The second group consists of the Gini coefficient by income level, the median cost of housing, and the unemployment rate. The environmental situation is assessed according to the Air Quality Index developed by the US Environmental Protection Agency. For comparison, the town of Braintree, MA, was chosen. As a result of the study, the USCESI was calculated for both locations. The analysis showed that both Amherst and Braintree have a high degree of economic sustainability. However, it was revealed that proximity to a significant economic center has a more powerful positive impact on economic sustainability than the location of a large university. In our paper, we proposed a new methodology for measuring economic sustainability with a special focus on inequality as a major problem in American society. The findings provide new knowledge about university cities and debunk the myth that they represent an exception to the general logic of urban development in the United States. A similar approach, with clarification of statistical indicators and a different emphasis, can be applied to other countries where inequality may be the main threat to economic sustainability, not in terms of access to higher education but in other areas.

1. Introduction

For many years, the main conceptual framework for researching how cities and nations develop has been sustainable development. With the creation of the 17 Sustainable Development Goals (SDGs), the United Nations codified the unique status of that strategy. The sustainable development concept was studied from various perspectives, including social, economic, environmental, political, and cultural considerations. While sustainable development is a clearly defined term, its variations are less definitive. Of particular interest for urban economics studies is the concept of economic sustainability. Most researchers who utilize it for empirical analysis or suggest their own vision share the opinion that this concept has no clear commonly accepted definition [1,2,3,4,5].

In the context of post-pandemic economic development, as well as growing geopolitical turbulence, sustainable development issues are becoming even more important. Cities, which concentrate the main part of added value production, may be both sustainable growth drivers and the most economically challenging places. In that regard, the goal is to form an assessment methodology for sustainable development, as well as look for the factors that would impact it and assume a particular relevance.

Another important subject connected with sustainable development is the social and economic inequality within and among towns. In this regard, of interest are university towns, as they are a form of “monocities” oriented at the production and dissemination of knowledge and knowledge-intensive technologies instead of the industrial sector and natural resources.

Typical university towns, whose territories are mostly occupied by campuses, are common in the USA. Unlike many other countries, universities here are mostly located in specialized towns versus megalopolises (even though such universities exist as well). Apart from that, despite heightened attention to the issues of inequality, the USA remains a highly polarized country in terms of socio-economic indicators—income level, access to quality education, healthcare, and housing [6,7].

An important theoretical aspect is to identify the differences between the concept of sustainable development and the concept of well-being. The situation is complicated by the fact that one of the SDGs is precisely articulated as an improvement of people’s well-being (SDG 3). However, the UN understands well-being as purely a set of factors that ensure inclusive and equal access to healthcare and opportunities for a healthy lifestyle [8].

The main contradiction between the two concepts is that sustainable development implies prioritizing the interests of future generations, for the sake of which some immediate desires can be sacrificed. At the same time, the classical concepts of well-being are based on the idea of the hedonic essence of consumption [9]. However, in recent years, researchers have increasingly moved toward an understanding of sustainable well-being, which, in accordance with the main trends in the lifestyle of people in many developed and developing countries, has moral restrictions that do not allow uncontrolled consumption and critical damage to nature [10,11].

Despite the fact that some immediate forms of consumption should be reduced for the sake of more sustainable development, the overall inclusive wealth per capita should not decrease. While changes in the level of inclusive capital can be easily predicted on a global scale, it is much more difficult to do so at the city level. This is due to the much greater mobility of people and, as a consequence, the variability of their socio-economic activity in cities. This is especially evident in the United States, where most densely populated cities have constantly grown, simultaneously transforming metropolitan areas surrounding their urban cores.

In this situation, some socio-economic parameters that assess certain aspects of inclusive capital can and should be somewhat rethought. For example, the most time-invariant factor is the differentiation of real estate prices. While they strive for constant growth, their mutual relations between different parts of metropolitan areas change only as a result of significant changes, such as a sharp transformation of the racial makeup. At the same time, an important indicator of inclusive capital can be a rapid assessment of the socio-economic situation in the city right now. When people choose a place to move, they often focus on opportunities for their development and the well-being of their family in the short term; while bringing with them a certain level of inclusion capital, they create a long-term perspective for the well-being of the city. This paradox reveals the reason why we study a seemingly long-term problem of sustainable development using methods of medium- and short-term analysis.

The objective of our study is to develop a quantitative assessment of economic sustainability based on the US Cities Economic Sustainability Index (USCESI) proposed by the authors. The methodology has been tested on two selected US cities. One of them is the university town of Amherst, Massachusetts (USA), with a population of 39,000 people. Its main employer is the University of Massachusetts Amherst (253rd place in the 2023 QS rankings), home to over 32,000 students and 2000 faculty members. The second town is Braintree, Massachusetts, which also has a population of 39,000 people. Braintree is part of the Greater Boston metropolitan area and is connected with this major megalopolis by a suburban railway line. The distance between Braintree and Boston is about 20 km by car. The relative location of the two cities can be seen in Figure 1.

The comparison of two cities of similar size and location is interesting because it reveals the specifics of a university city. This leads to a key research question: How does a university city in the US differ from a city without a major university in terms of the potential for economic sustainability? An obvious hypothesis is the assumption that the university, by creating an environment for the life of young, educated residents, as well as qualified teachers, also has a positive impact on the economic sustainability of the city. Therefore, we can assume that Amherst has the prerequisites for high performance in this area. To check if this is the case, it is essential to carry out a comparative analysis, and a city with a similar geographical location and almost the same population is seen as a suitable option for this.

2. Economic Sustainability and Its Attributes

Before we proceed to the main subject of this paper, we need to clearly define the economic sustainability of a city. As our goal is the quantitative assessment of this phenomenon, the definition should include measurable attributes. Therefore, the institutional and cultural factors that do not easily lend themselves to quantification will not be accounted for.

The problem of economic sustainability was studied by authors and applied to different aspects of societal life. It has been noted that sustainability plans developed in many US cities tend to neglect the issues of inequality reduction, even though there is a trend to draw more attention to this problem [12].

Another frequently addressed subject is sustainability and inequality in smart cities. The very concept of a smart city is extremely broad, with different scholars defining it differently. Yet, a common thread is the leading role of knowledge-intensive technologies and highly qualified workers in economic production [13,14]. Therefore, even though we cannot state that Amherst fully matches the notion of “a smart city”, it is logical to assume that a university city would be a likely candidate for that status.

In principle, smart cities often create conditions for greater inclusivity and inequality reduction [15]. That said, access to higher education in the US remains highly disproportionate, especially for various racial groups [16,17]. Thus, economic sustainability risks may include a gap in income, unemployment, and education attainment, as well as racial composition metrics.

The most telling racial indicator is the racial diversity level. Generally, its increase leads to a reduction in interracial inequality, which is even more visible in the higher education sector [18,19]. Apart from the above-mentioned factors, real estate and insurance are critically important for the American context of economic sustainability. According to Florida [20], the real estate market is the main cause of social and economic polarization in cities all over the world. With a clear connection between people’s health and quality of life, it is especially fair for the United States [21].

Urban health has an impact on the sustainability level in the face of strong and sudden shocks: the healthier the city, the more efficient the city’s response to challenges, the less dangerous are risks, and the faster the city recovers from adverse ramifications. In a traditional vision, urban health reflects the outcomes of the environment (both physical and social) that impact dwellers’ well-being and quality of life in urban areas [22]. A city with a good health level has higher sustainability and may mitigate the impact of risks.

For the US, the main indicator of urban health is access to medical services [23,24,25]. This domain is fraught with acute inequality, which, in turn, relates to an extremely uneven coverage of the population with medical insurance. Lack of access to quality medical services makes the entire community vulnerable to various types of epidemics and chronic non-infectious diseases. This problem is related to issues of racial inequality since the most vulnerable groups are non-white residents of urban and rural areas [26,27,28].

Without a doubt, economic sustainability may not be analyzed without being aware of the environmental issues [29]. They may be conditionally divided into climatic and environmental. Climate change is one of the key challenges of economic sustainability [30]. Despite the importance of this subject, we will leave out climatic factors, as the scope of this paper is limited to two rather small towns located 130 km from one another, and their climate conditions are very similar.

Economic sustainability is most often studied in a macroeconomic context, even in other scientific fields [31,32,33]. However, according to the objectives of our study, it is necessary to reconceptualize this term for urban studies. The traditional definition of sustainable development proposed by the Brundtland Commission can be taken as a basis [34].

So, we define economic sustainability as a state of a society, economy, and environment that implies minimal risks for the long-term development of a city. Such assessment is to be trilateral: social, economic, and environmental. To be able to identify specific indicators that would help us assess these dimensions, let us address the experience of previous scholars.

To assess the environmental situation in the cities, it was decided to use a single indicator, albeit a complex one. It is the commonly accepted Air Quality Index (see below for details). Several scholars point out the powerful contribution of air quality differentiation to unequal conditions of achieving economic sustainability. These assessment dimensions correspond to the classic three pillars of sustainability: social, economic, and environmental [35]. Given the focus of this article on the issue of economic sustainability, special emphasis is placed on socio-economic topics. In addition to that, as we differentiate economic sustainability from sustainable development, it was important not to give it too much importance in the index, which could lead to distortions not directly connected with the urban economy. In this study, we propose to resolve the tension between sustainable development and well-being through the concept of sustainable well-being. One of its aspects is economic sustainability. In order to pay more attention to the “sustainable” component of this concept, we will analyze the AQI in detail. Accordingly, well-being will be understood relatively narrowly, from a purely socio-economic perspective.

3. Developing City Economic Sustainability Index

By summing up the rationale behind the selection of economic sustainability indicators, we can form their final composition (see

Table 1. Primary indicators used to assess economic sustainability.

Indicator	Assessment Dimension	Source
Air Quality Index (AQI)	Environment	[36]
Gini Coefficient	Economy	[37]
Housing Value	Economy	[37]
Unemployment Level	Economy	[37]
Racial Diversity	Society	Calculated by the authors based on the data [37]
Educational Attainment	Society	[37]
Insurance Coverage	Society	[37]

).

Let us look closely at each of the indicators in terms of primary data collection and processing. An important goal was to narrow down divergent indicators to values that may be compared and put under a single index. Hence, most of the collected primary data were normalized, which will be further explained below.

4. Environment

The AQI is a dimensionless evaluation of air quality calculated by the United States Environmental Protection Agency (EPA). This index factors in the emissions of five main pollutants:

a.

Ground-level ozone;

b.

Particle pollution (also known as particulate matter, including PM2.5 and PM10);

c.

Carbon monoxide;

d.

Sulfur dioxide;

e.

Nitrogen dioxide [38].

The EPA-collected data on the concentration of the five listed pollutants are combined into a single index in accordance with the following algorithm [38]. The AQI is the highest value calculated for each pollutant as follows:

1.

Identify the highest concentration among all the monitors within each reporting area and truncate as follows:

a.

Ozone (ppm)—truncate to three decimal places;

b.

PM2.5 (µg/m³)—truncate to one decimal place;

c.

PM10 (µg/m³)—truncate to an integer;

d.

CO (ppm)—truncate to one decimal place;

e.

SO₂ (ppb)—truncate to an integer, NO₂ (ppb), and truncate to an integer.

2.

Using the AQI Technical Assistance Document, find the two breakpoints that contain the concentration. The document can be read in [38], p. 9.

3.

Calculate the AQI for each pollutant using the following formula:

$${\mathrm{A}\mathrm{Q}\mathrm{I}}_{\mathrm{p}}=\frac{{\mathrm{A}\mathrm{Q}\mathrm{I}}_{\mathrm{h}\mathrm{i}\mathrm{g}\mathrm{h}}-{\mathrm{A}\mathrm{Q}\mathrm{I}}_{\mathrm{l}\mathrm{o}\mathrm{w}}}{{\mathrm{B}\mathrm{P}}_{\mathrm{h}\mathrm{i}\mathrm{g}\mathrm{h}}-{\mathrm{B}\mathrm{P}}_{\mathrm{l}\mathrm{o}\mathrm{w}}}\left({\mathrm{C}}_{\mathrm{p}}-{\mathrm{B}\mathrm{P}}_{\mathrm{l}\mathrm{o}\mathrm{w}}\right)+{\mathrm{A}\mathrm{Q}\mathrm{I}}_{\mathrm{l}\mathrm{o}\mathrm{w}}$$

where AQI_p is the AQI index for pollutant p, C_p is the truncated concentration of pollutant p, BP_high is the concentration breakpoint that is greater than or equal to C_p, BP_low is the concentration breakpoint that is less than or equal to C_p, AQI_high is the AQI value corresponding to BP_high, and AQI_low is the AQI value corresponding to BP_low.

4.

The final value of the AQI index is the maximum value among all AQI_p.

The results of the index calculation are the dimensionless indicators ranging from 0 to 500. The interpretation of values is recorded in the analytical materials provided by the AQI. The distribution of values by residents’ health hazards may be found in

Table 2. AQI basics for ozone and particle pollution.

Levels of Concern	Values of AQI	Description of Air Quality
Good	0 to 50	Air quality is satisfactory, and air pollution poses little or no risk.
Moderate	51 to 100	Air quality is acceptable. However, there may be a risk for some people, particularly those who are unusually sensitive to air pollution.
Unhealthy for Sensitive Groups	101 to 150	Members of sensitive groups may experience health effects. The general public is less likely to be affected.
Unhealthy	151 to 200	Some members of the general public may experience health effects; members of sensitive groups may experience more serious health effects.
Very Unhealthy	201 to 300	Health alert: The risk of health effects is increased for everyone.
Hazardous	301 and higher	Health warning of emergency conditions: everyone is more likely to be affected.

Note: derived from [39].

.

The EPA provides open-access AQI data [36]. However, the index is calculated not only at the county level but also at the level of individual towns. In this regard, we had to assume that air quality in the analyzed towns matches the average level for counties. Amherst is in Hampshire County, while Braintree is in Norfolk County.

For a better understanding of the context and specificity of the territories under study, let us conduct a retrospective analysis of the AQI values dynamics for the two counties (which include Amherst and Braintree), the state of Massachusetts, and the United States of America overall. To that end, we built a graph presented in Figure 2.

As the AQI data may have a considerable variation (from 0 to 500), they are traditionally analyzed in relation to the median value rather than the mean. On the graph, we may see that the amplitude of yearly median values is not very high, from 32 to 48, which corresponds to good air quality. Incidentally, both extremes have been registered in Norfolk County. Quite visible is the downward trend, which took place in all four territories before 2020, but in the last two years (2021–2022) it has changed to growth. It is more pronounced in Norfolk and Hampshire counties (that said, the 2020 values were lower there). This is indicative of a rather substantial aggravation of the environmental component of sustainability within common values.

AQI data are available for 2022, but the main part of the statistics collected by the US Census Bureau is restricted to the year 2021 as of this writing; hence, the AQI for 2021 will be used in further analysis.

As the AQI assumes values from 0 to 500, these values should be normalized in the composite index for usability purposes. At the same time, one more methodological detail connected with the use of the AQI needs to be considered. Some assessed pollutants may be the result of human activity, while their concentration depends on physical and geographical conditions. Therefore, it is not correct to normalize values for all of the United States—the climate, relief, soil, and vegetation of New England, where the towns under study are located, have nothing to do with, say, the Sonoran Desert. In this regard, the median AQI values for the two counties were normalized from 0 to 1 by a multitude of values in 13 Massachusetts counties (there is a total of 14 counties in this state, but there are no data for Nantucket County due to its small territory and low population density).

As a result, the counties obtained the values in the format of 0 to 1. They were then subtracted from 1 so that the higher value corresponded to better air quality.

5. Economy

The goal of assessing the economic dimension within the index was to factor in the indicators that have not only an economic but also a high social value. That is, in lieu of the indicators characterizing the volume of the economy or its industrial structure, we used indicators that are directly related to the effects on people.

Since the breakthrough works of Gunnar Myrdal [40,41], researchers have often turned to the concept of cumulative causation in inequality studies [42,43,44,45]. The longer inequality between some groups of the population persists, the more its negative effects accumulate in space and, in accordance with the logic of the multiplier effect, increase. The most important factor of this kind, particularly in the context of strong social and economic inequality in the USA, is income polarization [46,47,48]. The traditional method of assessing inequality is the Gini coefficient [49,50], calculated in accordance with the formula:

$$\mathrm{G}=\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}\left|{\mathrm{y}}_{\mathrm{i}}-{\mathrm{y}}_{\mathrm{j}}\right|}{2{\mathrm{n}}^2\overline{\mathrm{y}}},$$

where n is the number of households, ${\mathrm{y}}_{\mathrm{i}}$ is the share of the household i income in the total income, ${\mathrm{y}}_{\mathrm{j}}$ is the share of the household j income in total income, and $\overline{\mathrm{y}}$ is the arithmetic mean (value) of income shares of the households.

The Gini coefficient reflects the degree of social stratification by a certain attribute under study, in our case by median per capita income. The result of the calculation assumes values from 0 to 1; the closer it is to 1, the higher the level of inequality. As the range of values for the Gini coefficient is 0 to 1, this indicator does not require being normalized.

The American statistics published by the US Census Bureau do not require the calculation of the Gini coefficient, as its values are published in the ready-for-analysis format (based on the aforementioned parameter). Notably, this indicator, just like all the other ones derived from the statistical databases, was collected on the NHGIS project website [27]. This is a usable database of official statistics from 1790 to date compiled by researchers from the University of Minnesota.

The two other economic indicators used also reflect the economic conditions of society. They are the median cost of real estate and the unemployment level. Just like the polarization of income level, these are major factors determining the possibilities of the city to develop sustainably (see [51,52,53,54,55]).

For these two indicators, it was decided, just like for the AQI, to linearly normalize values from 0 to 1 for the set of values for the state of Massachusetts. This was performed to mitigate the discrepancies connected with emissions and avoid results that are too high, as Massachusetts is one of the most economically thriving US states, and its comparison to states with completely different economic specializations and other population compositions would be incorrect.

The economic dimension differs from the social dimension in that all its indicators are directly related to money or production. The Gini coefficient is calculated based on income data calculated in US dollars, the same currency that estimates the value of real estate. The unemployment rate largely determines how well the labor market matches the vacancies offered by the economy.

6. Society

The bloc of “society” indicators implies the assessment of social and economic indicators that represent, to a larger extent, the condition of the residents rather than the economy of the city. Unlike economic measurement, in this case, parameters that do not have a direct monetary equivalent are assessed. All of them have an implicit impact on the sustainability of city development.

Indicators were selected by the logic of assessing social capital as an important factor of economic sustainability [56,57]. Given the US context (the importance of interracial inequality and a disproportion in terms of access to education and medical services), it was decided to select three indicators: racial diversity, education attainment, and insurance coverage. All these determinants, to a large extent, define the level of social capital in US cities [58,59,60].

Ethnic and/or racial diversity is often seen as a key social factor in shaping sustainable development to avoid domination by any one group. This has been proven in examples from higher education [61], food justice [62], and healthcare [63].

The racial diversity level was estimated based on the Herfindahl–Hirschman index in accordance with the formula:

$$\mathrm{H}\mathrm{H}\mathrm{I}={\mathrm{S}}_1^2+{\mathrm{S}}_2^2+\dots +{\mathrm{S}}_{\mathrm{n}}^2,$$

where ${\mathrm{S}}_1^2,\mathrm{ }{\mathrm{S}}_2^2$ are shares (percentages) of racial groups in the total population.

After the calculation, the results (from 0 to 10,000) are converted into a non-percentage format (from 0 to 1) for the convenience of further analysis: 100 = 0.01; 10,000 = 1. As the index interpretation implies the logic of “the lower the index value, the higher the diversity”, the results in the format of 0 to 1 were subtracted from 1 for the convenience of integration.

Education attainment and medical insurance coverage were estimated based on the statistics about people aged 25 and over with a bachelor’s degree and higher, as well as the share of people of any age that have at least one medical insurance. The values vary from 0 to 1; the higher they are, the better the situation in the town.

Education was highlighted as a critical aspect of sustainable development in the Brundtland Commission report [34]. Since the publication of the report, close attention has been paid to the problems of equal access to quality education. In this regard, it is necessary to consider the US context, where higher education is an indicator of socio-economic status since it is often either provided on a commercial basis or implies a lack of time for full-time work. In this regard, obtaining a bachelor’s degree has an element of elitism.

7. Economic Sustainability Index (USCESI)

All the collected data was converted into the format from 0 to 1, the logic being that “the higher the value, the higher is the economic sustainability level.” The “environmental” dimension is represented by one indicator, while “society” and “economy” are represented by three. For the two latter ones, mean values were used for the formula. Thus, the formula is as follows:

$$\mathrm{U}\mathrm{S}\mathrm{C}\mathrm{E}\mathrm{S}\mathrm{I}=\sqrt[3]{\mathrm{A}\mathrm{Q}\mathrm{I}\times \mathrm{S}\mathrm{o}\mathrm{c}\times \mathrm{E}\mathrm{c}\mathrm{o}}$$

where the AQI is a normalized median value of the Air Quality Index, Soc is the mean of three normalized indicators of the “society” dimension, and Eco is the mean of three normalized indicators of the “economy” dimension.

This formula matches the calculation of the geometric mean. This method proved to be efficient when calculating the Human Development Index developed by the UN [64].

8. Results

Let us consider the index calculation results. Firstly, we need to draw our attention to individual USCESI indicators to identify the specificity of the cities in question/studies (see Figure 3).

Perhaps the most unexpected result of the calculation was that by almost every parameter, the economic sustainability of Amherst, a university town, is lower than Braintree. Particularly surprising is the value of education attainment—a mere 0.28. Let us recall that the values of this indicator were normalized for many other towns in Massachusetts, which has a high concentration of university towns. For Braintree, this indicator was 0.44.

A possible explanation could be that many jobs are generated within and around the university; these jobs relate to furnishing the needs of students and faculty: security, grounds maintenance, shops, and public catering facilities inside and near the campus. It also bears reminding that most bachelor students were not included in the assessment, as the US statistics only factor in persons aged 25 and older (implying that most students are younger than that). At the same time, Braintree is quite a prosperous suburb of Boston, and it is highly possible that the main stratum of its population is white-collar workers, i.e., educated, qualified, and privileged employees of various corporations.

Insurance coverage varies insignificantly, and both towns have a high value of it (0.84 in Amherst and 0.92 in Braintree). The difference in some other indicators in favor of Braintree has a trivial explanation: Amherst has a lower racial diversity, as the accessibility of education is uneven for white and non-white population groups (with a noticeable exception of Asian Americans), while the real estate oriented toward students should logically be cheaper than in the suburbs.

The only dimension where Amherst proved to be far more successful than Braintree is the environment. Hampshire County, where the university town is located, boasts the best air quality in Massachusetts as of 2021; therefore, Amherst achieved the maximum score (1) by that measure. The indicator of Norfolk County where Braintree is located is also high (0.67).

A lower indicator may be explained by the fact that Norfolk, in general, and Braintree, in particular, have larger industrial enterprises than Hampshire, where the main employers are universities and colleges. Thus, Braintree is home to a major transmission production (brakes, motors for elevators) under the Altra Industrial Motion brand, which employs 10,000 people. Other large Braintree-based companies relate to the media industry and knowledge-intensive developments in medicine (in particular, a branch of Haemonetics company, one of the leaders in blood and plasm donorship equipment). This also partially explains Braintree’s higher education attainment level.

Let us proceed to the result of the USCESI calculation and its components (sub-indices). The calculation results are presented in Figure 4.

It is apparent that Amherst is quite substantially lagging compared to Braintree in terms of “economy” and “society” dimensions. The reasons for that were examined above, but it is important to emphasize Braintree’s main advantage, which is its proximity to Boston. So, our analysis showed that the proximity of a large economic center has a more powerful positive impact on economic sustainability than the presence of a university campus within the boundaries of the city, which, to a large degree, shapes the economic specialization of the city.

However, high economic activity has a flip side to it: a large volume of emissions into the air. That said, since the productions concentrated in Braintree and Norfolk County on the whole are oriented toward knowledge-intensive technologies, the quality of air is quite favorable.

Despite a considerable environmental advantage, the total USCESI value is slightly lower than in Braintree: 0.61 against 0.62. At first glance, these indicators may seem very close, yet the analysis of the individual components of the index shows that there is a better situation with economic sustainability in the Boston suburb rather than in a university town.

This allows for the conclusion that a university town is a victim of its own status, a monotown in a sense. The economy of Amherst does not lend itself to diversification like that of Braintree, where innovative and knowledge-intensive productions were set up. Even though the US’s technology parks are almost invariably associated with the concentration of universities (e.g., Silicon Valley in California, the Silicon Prairie in Texas, and the Research Triangle in North Carolina), they still form autonomous territories. Employees of such regions have different demands than students. This applies to living standards, consumption patterns, and leisure pastimes. Therefore, Amherst University graduates will more likely move to Boston agglomeration in search of work and Braintree, with its location close to its core, looks like quite an appealing option.

9. Conclusions

As part of this study, an economic sustainability assessment methodology was developed. It factors in the context of American society and the US urban economy and may be applied to other cities in other countries if adjusted accordingly, including the selection of the most significant indicators.

We emphasize the removal of the contradiction between sustainable development, sustainability, and well-being. Bearing in mind that these three concepts do not always share a common theoretical and ideological basis, we start from the idea that economic sustainability meets the aspirations of urban residents. At least this is true for US university towns, where the conscious consumption agenda is integrated into the educational process and lifestyle. So, our conceptual framework is to consider economic sustainability as a multifactorial phenomenon that reflects the development of the city’s economy, in which not only is the potential of future generations not violated but the rights of today’s residents are not infringed.

The USCESI can be used in reporting on sustainability in US cities. When such reports are compiled for a large sample of cities, new insights can be drawn about the relationship between sustainability and the socio-economic, demographic, and other factors that determine the diversity of American cities.

Our case studies of Amherst and Braintree showed that a city’s seemingly strong specialization in providing higher education services can actually have negative effects on economic sustainability. Although higher education plays a key role in helping communities adapt to economic, social, and environmental challenges at the local, national, and global levels, the specific nature of the US educational system can reverse this logic. In an environment where higher education is one of the most visible dimensions of racial inequality, college city status may maintain a negative status quo that prevents US cities from transitioning to new, more sustainable economic development principles.

The proposed economic sustainability methodology certainly has limitations. It may be further elaborated in subsequent studies. The suggested improvement may be introduced by complicating the assessment method of the “environmental” dimension to include other metrics of environmental conditions: water and soil pollution or greening (NDVI). However, the formula, in this case, will probably have to be supplemented with a certain scaling mechanism, as the focus on socio-economic aspects is a crucial methodological premise of economic sustainability assessment [65]. For a greater focus on environmental issues, the current conceptual framework will have to be replaced with sustainable development.

Another idea for a more complex analysis is to expand the methodology to other US cities and states. To allow this, the normalizing principle will have to be changed in the calculation algorithm to account for the substantial social and economic disproportions within the country. Also, it would be very informative to consider the temporal aspect in future studies. Because the very idea of sustainability is based on a long-term perspective, it is necessary to discover trends in sustainability performance over time.