cultural tightness looseness essay

Tight and Loose Cultures: A Conversation with Michele Gelfand

Image: Steve Johnson/Unsplash

Michele Gelfand is Professor of Psychology at the University of Maryland and author of an eye-opening new book on the role that culture—and specifically how strictly different cultures enforce norms—plays in our lives. The book, Rule Makers Rule Breakers: How Tight and Loose Cultures Wire Our World explains how Gelfand’s research over the past couple of decades helps us understand some of the social forces that underlie our behaviors. Norms guide people’s behavior at all levels of social organization, from families, to companies, to entire nations, and life can look quite different when a culture’s enforcement of those norms is tight or loose.

Dave Nussbaum: Let’s start with the basics—what are tight and loose cultures and why does it matter?

Michele Gelfand: Culture is a really important puzzle—it’s omnipresent —and affects us from the moment we wake up to the moment we go to sleep. But its largely invisible . We rarely recognize how powerful it is!

One of the most important aspects of culture that we take for granted is our social norms . We follow norms constantly. And we rarely recognize how much we need norms: social norms are the glue that keep us together, they give us our identity and help us to coordinate and cooperate at such a remarkable level. What’s more, social norms are the key that unlocks societal order, and even the possibility of constructing a human society. If people didn’t abide by socially expected rules, their behavior would be unbearably unpredictable. We wouldn’t be able to coordinate our actions to do most anything—from getting place-to-place to having meaningful conversations to running schools, organizations, and our governments.

But my research has shown that some groups have much stronger norm s than others; they’re tight . Others have much weaker norms ; they’re loose . Of course, all cultures have areas in which they are tight and loose—but cultures vary in the degree to which they emphasize norms and compliance with them. Since I got my Ph.D. in cross-cultural psychology, I’ve been studying tight-loose cultures in over a hundred groups, and I’ve discovered that this distinction can help us understand differences across nations, states, organizations, and social classes, and even our own households. It’s what I call a “fractal pattern” of culture. Remarkably, tight-loose has a very similar pattern in terms of its antecedents and consequences across different levels. Tight-loose also causes a lot of conflict, but once we understand its logic, we cultivate greater cultural empathy and manage our divides more constructively.

One of the antecedents of a tight culture that you emphasize is threat. Why is threat so important in determining the tightness or looseness of a culture? And does it have to be a concrete threat, or can a just be a perceived one?

Often when we think about cultural differences, we don’t realize that they have a certain logic—a rationale that makes good sense. In our data , countries that experienced a lot of threat were tighter. Some nations experience a lot of threat—whether it is a high level of natural disasters, famine, and resource scarcity, or whether it comes from the constant threat of invasions from one’s neighbors or from a high level of population density on one’s soil that can create chaos (compare Singapore with about 20,000 people per square mile to New Zealand that has about 50 people per square mile!). It makes sense, cultures that have threat need rules to coordinate to survive (think about how incredibly coordinated Japan is in response to natural disasters). But cultures that don’t have a lot of threat can afford to be more permissive and loose.

Social norms are the key that unlocks societal order, and even the possibility of constructing a human society. If people didn’t abide by socially expected rules, their behavior would be unbearably unpredictable.

We’ve found this principle to not only apply to modern nations, but also to states within the U.S . States with the most disasters and pathogen prevalence are the tightest. We’ve even replicated this in traditional societies by analyzing ethnographies from the standard cross-cultural sample which provides information on 186 pre-industrial societies from around the world. We can reliably classify these societies in terms of tight-loose, and the tightest of the cultures in our data had more threat, just like the modern era. In more recent work with computer scientists, we’ve shown that threat indeed causes the evolution of tightness. Of course threat isn’t the only factor that affects tight-loose, and not all tight cultures have threat and not all loose cultures lack it; but it is an important predictor. Other important factors include things like diversity, debate, and mobility.

But to your second question—threat need not be objective to cause groups to tighten. It can be highly subjective, and subjective threat can also tighten us . In this way, tight-loose is an important framework to understand the rise of President Donald Trump and other leaders in Poland, Hungary, Italy, and France, among others. The gist is this: when people perceive threat—whether real or imagined, they want strong rules and autocratic leaders to help them survive. My research has found that within minutes of exposing study participants to false information about terrorist incidents, overpopulation, pathogen outbreaks, and natural disasters, their minds tightened. They wanted stronger rules and punishments.

When people think their culture is “on the brink of disaster,” their immediate response is to embrace tight rules and tough leaders.

We also found this in studies of President Trump and French Politician Marine Le Pen . People who felt threatened in our surveys (for example, by ISIS, Korea, or immigration) felt the U.S. was too loose and needed stronger rules, and this predicted their support for Trump. Leaders can also use that psychology in reverse—they can amplify and exaggerate threat and target people who are already threatened to gain popularity. This has been happening for centuries. This strategy has been enormously successful because it taps into a deep evolutionary principle that has helped nations survive for millennia. When people think their culture is “on the brink of disaster,” their immediate response is to embrace tight rules and tough leaders.

So when are tight norms better than loose ones (and vice versa)?

This is a great question because tight-loose produces a pretty predictable trade-off. In other words, it has similar liabilities and strengths depending on your vantage point for groups. Tight cultures have more order —they are more coordinated, uniform, and have people who have more self-control—after all, they have to regulate their behavior a lot to avoid punishment. Loose cultures are comparatively more disorganized and have a lot more problems with self-control since this muscle doesn’t get as much practice.

But loose cultures, from our data, are much more open —they’re open to new ideas (more creative), to new people (they’re less ethnocentric), and they’re more open to change. Tight cultures, on the flip side, tend to have much less openness—they’re less creative, more ethnocentric, and have much more cultural “inertia.” Even in our computer models, we can see that tight groups have a great resistance to change. After all, change threatens the social order, which tight groups cling to in the face of threat.

This is what I call the tight-loose trade-off —strengths in one group can be liabilities in others. Thus, when people ask me which is better—tight or loose —the answer is neither. Both tight and loose confer important strengths to groups (and liabilities)—depending on your vantage point.

One way to look at this – which I call the “ Goldilocks principle of tight-loose ”—is that groups that get too extreme—either too tight or too loose—have problems. They have higher suicide rates, lower happiness, and more instability. Extremely tight groups are very oppressive but extremely loose groups have little or no way to coordinate human behavior—what sociologists call anomie. They feel a tremendous amount of unpredictability and also suffer. The trick, I think, is that cultures often need to have different levels of norm strength given their varying ecologies but they need to ensure they don’t get too extreme.

How do you nudge a culture? For example, you’ve written about United Airlines maybe being too tight and not allowing their employees enough discretion. How do you nudge them towards looseness?

Great nudges start with a cultural audit. First and foremost, we need to analyze where an organization is in terms of the strength of its social norms, as we talk about in a recent Harvard Business Review article . But then we can negotiate the level of norm strength. For example, some organizations, like United, may indeed operate best under tight conditions, but these companies’ leaders need to know when and how to give employees more discretion—for example, in non-safety domains. At the same time, some organizations, such as Tesla, would benefit from knowing when and how to insert stronger norms into their daily practices. When already loose organizations insert some tight features into their daily operations, I call this structured looseness . On the flip side, steering a tight organizational culture into a looser state is what I refer to as flexible tightness .

The same principle, by the way, applies to our own households. Some families may need to veer tighter given their circumstances (in our data, for example, the working class , which experiences a lot of threat, is tighter, which is important for keeping kids out of trouble and avoiding falling into hard living, or poverty). But we can negotiate the domains that we are tight in and the domains we are loose in. In my own family we’re pretty tight on school habits and how the kids treat each other but we’re pretty loose in terms of how messy the kids are! Once you realize that tight-loose is negotiable it opens up a lot of creative potential in any social setting.

How do tight norms preserve power and status? For example, as women’s power grows, it seems that it affords them more looseness in how they behave, but that in turn may impinge on men’s power, feel like a threat, and inspire more tightness—can you speak about that dynamic?

Your intuition is dead on. As a general principle, women and minorities live in tighter worlds—they have less latitude and are punished more severely for violations than their majority counterparts (and this is even more pronounced in some cultures than others). When they do gain power, and have more latitude, this is a direct threat to the status quo that majority members are used to enjoying, and that is why we see high power women and minorities punished (and why we see, according to our research published in Psychological Science , that majorities let other majority members off the hook for deviant behavior).

President Trump seems like he’s got a good tightness message, but I’m curious why he’s not a terrible tightness messenger given that he flouts norms in an unprecedented way—what’s the deal there?

This is a million dollar question! As I mentioned, powerful people have more latitude to break norms, and Trump is the quintessential norm violator. The question is why do people tolerate it, particularly his working class base who tend to veer tight. My hunch is that people who support him feel so threatened by societal disruptions that they are willing to tolerate his bad behavior if they feel he will return them to the tight social order that they so desperately want.

How can we help people from tight and loose cultures understand each other better?

Just as it’s important to have IQ and EQ (emotional intelligence), we need to cultivate CQ or cultural intelligence. That means we have to understand the rules that are guiding behavior and how strictly they are enforced in order to best adapt to the local culture.

When we understand why cultures have different norms, we can have more empathy and less judgmental attitudes toward them.

When we understand why cultures have different norms, we can have more empathy and less judgmental attitudes toward them. The fact that I was born in the U.S. versus Singapore is pretty random—but if I were born there and was subject to a lot of historical and ecological threat, I would understand why there are so many restrictions—why people are able to sacrifice some freedom for security in that context. Understanding where cultural differences come from also helps to understand very puzzling behavior.

Take the fact that if you are caught importing gum into Singapore you may face a fine of up to $100,000 and/or jail time of up to two years. Many Americans would be very puzzled by this behavior. Why can’t they bring in something as innocuous as gum!? But the country’s extreme population density suggests why this ban makes sense. During the 1980s, city workers struggled to keep up with cleaning chewing gum waste, which became a public crisis. The sticky wads gummed up mailboxes and elevator buttons, and even jammed apartment keyholes and the sensors on subway system doors, causing frequent malfunctions. In a place with so many mouths per square mile, the solution was simple: get rid of the temptation. By 1992, the sale of gum was prohibited in Singapore, and people caught selling the chewy treat faced hefty fines. The ban led to some frustration at first, but today it’s widely upheld. And if you lived among more than 20,000 people per square mile, chances are that you’d support it, too.

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On the nature and importance of cultural tightness-looseness

Affiliation.

1 Department of Psychology, University of Maryland, College Park, MD, USA. [email protected]
PMID: 17100480
DOI: 10.1037/0021-9010.91.6.1225

Cross-cultural research is dominated by the use of values despite their mixed empirical support and their limited theoretical scope. This article expands the dominant paradigm in cross-cultural research by developing a theory of cultural tightness-looseness (the strength of social norms and the degree of sanctioning within societies) and by advancing a multilevel research agenda for future research. Through an exploration of the top-down, bottom-up, and moderating impact that cultural tightness-looseness has on individuals and organizations, as well as on variance at multiple levels of analysis, the theory provides a new and complementary perspective to the values approach.

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Open Access

Peer-reviewed

Research Article

Across-Time Change and Variation in Cultural Tightness-Looseness

Affiliation Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto University, Helsinki, Finland

* E-mail: [email protected]

Affiliation Department of Psychology, University of Tartu, Tartu, Estonia

Anne Mandel,

Published: December 18, 2015
https://doi.org/10.1371/journal.pone.0145213
Reader Comments

Cultural tightness-looseness, a dimension which describes the strength, multitude, and clarity of social norms in a culture, has proved significant in explaining differences between cultures. Although several studies have compared different cultures on this domain, this study is the first that targets both within-country differences and across-time variation in tightness-looseness. Using data from two nationally representative samples of Estonians, we found that the general tightness level had changed over a period of 10 years but the effect size of the change was small. A significant within country variance in 2002 had disappeared by 2012. Our results suggest that tightness-looseness, similarly to cultural value orientations, is a relatively stable and robust characteristic of culture–that is, change indeed takes place, but slowly. Future studies about across-time change and within-country variance in tightness-looseness should target more culturally diverse and socially divided societies.

Citation: Mandel A, Realo A (2015) Across-Time Change and Variation in Cultural Tightness-Looseness. PLoS ONE 10(12): e0145213. https://doi.org/10.1371/journal.pone.0145213

Editor: Kimmo Eriksson, Mälardalen University, SWEDEN

Received: September 7, 2015; Accepted: December 1, 2015; Published: December 18, 2015

Copyright: © 2015 Mandel, Realo. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Data Availability: Data (in SPSS format) can be downloaded from the following link: https://osf.io/ctysz/ .

Funding: This study was supported by institutional research funding (IUT2-13) from the Estonian Ministry of Education and Science. Anu Realo was supported by a grant from the Netherlands Institute for Advanced Study (NIAS) during the writing of this article. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Culture is often seen as a set of learned and shared meanings that distinguishes one group of people from another [ 1 , 2 ]. Since the emergence of comparative studies of culture, social scientists have been trying to find general cultural dimensions or orientations, not just colorful single details, to capture major cross-cultural differences (e.g., [ 3 – 10 ]). In this paper, we focus on tightness-looseness as a promising dimension for understanding cultural variation [ 11 ].

Tight cultures have clear and pervasive social norms and severe sanctions for deviant behavior, whereas loose cultures have weak norms and high tolerance of deviant behavior. A cross-cultural study involving 33 countries [ 12 ] demonstrated that both ecological and historical factors, as well as proximal and contemporaneous processes, vary across tight vs. loose nations. Tighter nations, for instance, have encountered more historical or ecological threats, like wars, natural disasters, and famine. Cultural tightness has also been related to less open media, higher levels of religiosity, stronger laws and regulations, stricter punishments, and lower crime rates [ 12 ], as well as to lower levels of CEO discretion [ 13 ], and even higher stock market comovement [ 14 ]. Relative to moderate nations, both very tight and very loose nations have lower happiness, worse health outcomes, and gross domestic product per capita [ 15 ]. A recent study [ 16 ] showed that there is a wide variation in tightness–looseness, not only across nations, but also across the 50 states of the United States, which is also associated with different ecological and historical factors, psychological traits, and state-level outcomes. On an individual level, higher tightness has been related to higher constraints in everyday situations [ 17 ], higher cautiousness, and greater need for self-regulation and structure [ 12 ].

However, despite a large number of studies on tightness-looseness over the past decade, several important questions remain unanswered. First, the stability of tightness-looseness scores across time has so far not been assessed. This is, however, an important theoretical question which needs to be answered in order to fully understand how the level of tightness-looseness in societies is changed or maintained. Secondly, as far as we know, comparative studies of tightness-looseness have been rarely conducted using large representative samples. Instead, relatively small convenience samples have been used (e.g., [ 12 , 18 , 19 ]), thus casting doubt over the generalizability of findings to a wider population [ 20 ]. (There is a recent study on cultural tightness-looseness that was carried out in representative national samples of 68 countries but in this study, authors did not directly measure tightness-looseness but proposed new indices of cultural tightness-looseness that were based on the variation (i.e., standard deviation) in different values and behavioral practices within a country [ 21 ].) Finally, relatively small and possibly biased samples have also prevented comparison of different subgroups (i.e., men vs. women, more educated vs. less educated, younger vs. older, etc.) within cultures on their level of tightness-looseness.

In the current paper, we advance the field by studying changes in tightness-looseness in Estonia over 10 years in two large nationally representative samples. This enables us to (a) study across-time changes in tightness-looseness; (b) draw conclusions about the whole population of a country; and (c) compare differences in tightness-looseness across different social subgroups (by gender, age, education, place of residence, and language used to complete the questionnaire).

The importance of studying across-time variation in tightness-looseness

Cultures change over time, with gradual yet fundamental changes occurring in people’s basic values–which are often seen as the quintessence of culture–in response to socioeconomic modernization and democratization, as well as contact with other cultures [ 22 , 23 ]. Longitudinal studies have even shown that cultural change in values, at least to a certain extent, can be predicted on the basis of a society’s socioeconomic development and religious heritage [ 24 ]. Rising socioeconomic status, in particular, tends to enforce secularization [ 22 ], as well lead to higher levels of individualism [ 25 ]. There are also examples of short-lived, but dramatic, events, like 9/11 in the United States (US), eliciting changes in the social environment and people’s behavior [ 26 , 27 ]. These results raise the question of how much other characteristics of a culture, such as tightness-looseness, change over time.

From a cross-cultural perspective to an examination of within-country variation

Cross-cultural psychologists often treat countries as homogeneous units, implicitly assuming that every member of a certain culture shares the same set of cultural characteristics with other members of that culture [ 28 ]. Although, in many cases, such a generalization may be justified, there is still evidence that intracultural differences are often larger than variations between cultures (e.g., [ 29 , 30 ]). Indeed, a broad analysis of various behavioral measures [ 31 ] showed that samples consisting of young western college students, for instance, are remarkably different from other social subgroups in the same country, even in simple visual perception tasks, but also in moral reasoning, self-concept, and heritability of IQ (these being just a few examples). Furthermore, although the US is regarded as a prototypical individualistic culture, studies have shown that the Southern US is rather collectivistic, as opposed to the more individualistic Great Plains and Mountain West areas [ 32 ]. Similarly, a recent study [ 16 ] showed that there is large variation in tightness–looseness at the state level in the US, with the Southern region being the tightest and the Northeast and the Western regions the loosest.

Aims of the present study

The aims of the current study are a) to examine change in tightness-looseness scores over time and b) to study within-country variance in tightness-looseness in Estonia, by using data from one large-scale nationally representative survey of Estonian residents conducted in 2002 (the Estonian Survey of Culture and Personality, ESCP2002; N = 1,582) and one in 2012 (the 6th wave of the European Social Survey, ESS2012; N = 1,883).

The example of Estonia (1.3 million inhabitants, population density 29/km 2 ) is particularly interesting, because it was the second loosest country (after the Ukraine) in a 33-country comparative study of cultural tightness-looseness [ 12 ]. It has been argued [ 21 ] that norms, values, and behaviors should show greater variability in loose cultures than in tight cultures, which are more homogeneous and do not allow for much variation in values and acceptable behaviors. A study showed, for instance, that different population groups (inhabitants of an isolated island, army conscripts, housewives with many children, etc.) in Estonia have remarkably different patterns of collectivism [ 33 ]. Earlier research also found considerable differences in both value preferences (e.g., [ 34 ]) and the strength of collectivistic attitudes [ 35 ] between the Estonian- and Russian-speaking populations in Estonia. Such results clearly illustrate the importance of using samples that are representative of the whole population and paying attention to within-country differences, both at the level of geographic regions and among different subgroups in society.

Considering the social, political, and economic changes that have taken place in Estonia during the past 25 years, Estonia also makes an interesting example for examining the stability of tightness-looseness over time. In early 2002, when our first set of data was collected, Estonia was still going through major changes in the structure and organization of society, having regained independence in 1991. After going through the stages of radical reform (1992–1995) and economic stabilization as well as technological modernization (1995–1999), the years 1999–2004 in Estonia were mainly characterized by integration with Europe [ 36 ]. Joining the EU and NATO in 2004 can be viewed as the end of the transition period in Estonia. During the years 2005–2007, the country enjoyed around 10% growth in GDP per year and this period was defined by an increase in economic wellbeing as well as in general life satisfaction [ 37 ]. In 2007, however, the economy began to cool down. While, during the transition phase, striving for personal autonomy and little concern for the “common good” were prevalent attitudes in Estonia [ 38 ], the economic crisis shifted attention to social development and intensified calls for social reforms [ 39 ]. It can be hypothesized that the financial restrictions applied during the economic crisis as well as the new rules and regulations that came into effect after joining the EU and NATO have made the general environment in which people act less flexible (those being only a few examples of the processes that took place in the relatively young democracy). The same changes can also be viewed in the opposite way: as diminishing the borders between countries and encouraging more intercultural interaction and thereby blurring existing national social norms. In terms of cultural values, the importance of hedonism, material well-being, self-direction, and close relations steadily grew in Estonia from 1985 to 2008 [ 40 , 41 ]. However, the major shift in values took place right after re-independence in 1990s, and the period of 2000s could rather be described in terms of relative value stability [ 42 , 43 ].

Participants

The first sample came from a study of social capital, cultural value dimensions, and identity in Estonia in 2002 (Estonian Survey of Culture and Personality, ESCP2002). The sample was randomly selected from the National Census and was representative of the Estonian population in terms age, gender, ethnicity, place of residence, and educational level (for a sample description, see also [ 44 , 45 ]). Altogether, 1,753 respondents aged 15–74 participated in ESCP2002. Complete data (with no missing values) were available for 1,582 people (889 female, 693 male; mean age 43.5, SD = 17.4); 1,328 (84%) of the respondents filled in the questionnaire in Estonian and 254 (16%) in Russian. Nineteen per cent of participants had completed primary (1–9 years), 45% secondary (10–12 years), and 36% tertiary (13 years or more) education. Twenty-six per cent of respondents lived in a big city or its suburbs, 30% in a small city or town, and 44% on a farm or in a village.

The second sample is part of the European Social Survey round 6 (ESS2012), carried out in 30 European countries ( http://www.europeansocialsurvey.org ). The sample was again randomly selected from the Estonian population and was representative of all residents of private households, aged 15 and over, regardless of their citizenship, ethnicity, or language. In total, 2,095 respondents aged 15–94 years participated in the ESS 6th round survey in Estonia. Data with no missing values were available for 1,883 participants aged 15–74 years (1,063 female, 820 male; mean age 44.9, SD = 16.7 years). Seventy per cent ( n = 1,324) of the respondents answered in Estonian and 30 per cent ( n = 559) in Russian. Eleven per cent of the participants had at least primary, 38% secondary, and 51% tertiary education. Thirty-six per cent of respondents lived in a big city or its suburbs, 33% in a small city or town, and 31% on a farm or in a village.

It was not necessary to seek approval for the present study from the Ethics Review Committee on Human Research of the University of Tartu because we were using secondary data from existing social surveys in our analyses. Both datasets (ESCP2002 and ESS2012) have been carefully cleaned of all identifying information to ensure anonymity of the data files and therefore, it is impossible that the data could be linked back to the individuals from whom it was originally collected. In both surveys (i.e., ESCP2002 and ESS2012), verbal informed content was obtained and participants were assured of the confidentiality, privacy, and anonymity of any information shared.

Tightness-Looseness Scale (TLS).

Both in the ESCP2002 and the ESS2012, participants were asked to complete a 6-item Tightness-Looseness Scale (TLS; [ 12 ]). The scale targets the strength, clarity, and number of social norms, the degree of tolerance for deviance from these norms, and overall compliance with social norms in a country, with items like “There are many social norms that people are supposed to abide in this country” and “In this country, if someone acts in an inappropriate way, others will strongly disapprove” (the items of the TLS are shown in S1 Appendix ). The instructions given to respondents were that the statements refer to the country as a whole and that the statements refer to “social norms,” which are standards for behavior that are generally unwritten. The respondents rated the items on a 6-point Likert-type scale, ranging from “Strongly disagree” (1) to “Strongly agree” (6). The scale was translated into Estonian by the second author (accuracy verified by back-translation to the original language) and to Russian by a bilingual expert of both the Estonian and Russian languages (see S1 Appendix ).

In a 33-nation study of tightness-looseness [ 12 ], the TLS showed a single-factor structure, with the first factor explaining 62% of underlying variance in an exploratory factor analysis (including data from all 33 nations, N = 6,823). Factor loadings were .68 or greater, with the exception of (reverse-coded) item #4, which had a loading of .26, in the expected direction. The national-level reliability of the scale in the abovementioned study [ 12 ] was very good (Cronbach’s α = .85), and validity across nations was also demonstrated by showing that the factor structure obtained across nations is equivalent to the factor structure found separately in each nation.

The following variables, which were available in both datasets, were selected for the defining subgroups: (a) the language in which the respondent completed the questionnaire (Estonian or Russian); (b) gender; (c) age; (d) education level; and (e) place of residence (from big city to village or farm). These particular variables were chosen because previous research about social norms, values, and personality has indicated these as potential sources of intracultural diversity (e.g., [ 22 , 34 , 46 – 50 ]).

Preliminary data analysis

Internal consistency..

Internal consistency of the TLS was assessed by Cronbach’s α. Differently from an earlier study [ 12 ], item #4 (“People in this country have a great deal of freedom in deciding how they want to behave in most situations”) did not work as expected in the current study: although it was designed to be a reverse-coded item, it showed positive correlations with the other five items in the scale (see S1 Table ). Item #4 also had, on average, the lowest correlations with the other items in the scale. To test whether the problems with item #4 might reflect difficulties in sentence comprehension, we checked whether item #4 would fit the expected model among highly educated respondents. Among people who had a higher education, the average correlation between reversed item #4 and the other TLS items was -.04 in the ESCP2002 and -.22 in the ESS2012 data. Average correlations between other TLS items varied between .19 and .34 among higher educated respondents in the ESCP2002 sample and between .29 and .40 in the ESS2012 sample, showing that the item did not work as expected, even among highly educated respondents.

Cronbach’s α for the 6-item scale (item #4 reversed, according to the expected model) was .47 in the ESCP2002 data and .51 in the ESS2012 data. When item #4 was left out, Cronbach’s α increased to .61 for the ESCP2002 data and to .71 for the ESS2012 data. Therefore, item #4 was left out in all further analyses. Excluding any other single item did not improve internal consistency of the scale. Thus, we calculated the mean tightness score across five items of the TLS (higher scores indicate greater tightness).

A confirmatory factor analysis (CFA; Maximum likelihood method) was used to verify whether the single-factor tightness-looseness model [ 12 ] fit the current data. In both datasets, the 5-item single-factor model reached an acceptable fit [ 51 ], i.e., AGFI and CFI > .95 and RMSEA = < .06, when residual covariances between items #1 and #2 and items #5 and #6 were included in the model (see S1 Text for a detailed description of CFA).

Measurement invariance.

Measurement invariance (MI) between the two datasets (i.e., between 2002 and 2012) and between different subgroups (i.e., defined by questionnaire language and participant gender, age, education level, and domicile) was assessed before any comparisons were made, because scalar measurement invariance is a requirement for the valid contrasting of group means, especially when comparisons are made across time [ 52 ].

The MI analysis confirmed that it was feasible to compare mean tightness scores between the ESCP2002 and ESS2012 samples, and also between different subgroups within each sample, because scalar measurement invariance criteria were met, CFIs > .90, RMSEAs < .08 [ 53 ]. The only exception was the oldest age group (65–74 years) in the ESCP2002 data and, therefore, this age group is not included in the following across-time and within-country (ESCP2002) comparisons. More information about the measurement invariance analysis can be found in the S1 Text and in S2 , S3 and S4 Tables; descriptive statistics about the distribution of respondents among different subgroups are presented in Table 1 .

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https://doi.org/10.1371/journal.pone.0145213.t001

Across-time change and within-country variance in tightness scores

Across-time and within-country differences in tightness-looseness scores were tracked with a univariate analysis of variance (ANOVA) and Student’s t-test using SPSS v. 22.0. Fig 1A shows that the mean tightness score is higher in the ESS2012 ( M = 4.02; SD = .74) than in the ESCP2002 data ( M = 3.86; SD = .77). The difference is statistically significant, although the effect size is small ( F (1, 3463) = 35.49, p < .001, η 2 p = .010; all reported p -values are Bonferroni-corrected for multiple comparisons). The same tendency is evident across all social subgroups studied (see Table 1 ). The mean tightness score in the ESCP2002 was the same as the non-standardized tightness score for the Estonian sample ( n = 188; mean age 32 years; 86% female; 52% students) in a 33-country comparative study [ 12 ] for which data were collected in 2001.

All p -values are Bonferroni-corrected.

https://doi.org/10.1371/journal.pone.0145213.g001

To check whether questionnaire language, respondent gender, age, education level, or place of residence would, in addition to sample (ESCP2002 vs. ESS2012), contribute to differences in average tightness scores, these variables were added one-by-one into a two-way factorial ANOVA model (together with the sample factor).

As there were no significant differences in average tightness scores between people who had filled in the questionnaire in Estonian and those who had filled it in in Russian ( Fig 1B ; see Table 1 Language for descriptive statistics), respondents are not separated by language in further analysis.

As expected, the main effect of sample (ESCP2002 vs. ESS2012) was significant in all comparisons ( F (1, 2626–3461) = 21.65–38.34, p < .001, η 2 p = .006–.011). In addition to sample , only education level (see Fig 1E ) showed a significant main effect ( F (2, 3459) = 4.08, p = .017, η 2 p = .002), with the average tightness score being higher for people who have a lower education level, but the difference was significant only between primary and tertiary education (for all mean values, see Table 1 ).

Several other factors showed statistically significant interactions with sample . The interaction between sample and gender ( F (1, 3461) = 4.96, p = .026, η 2 p = .001) indicated that tightness in men had risen more than in female respondents (all mean values are presented in Table 1 ) over the period of ten years, and the difference between men and women was significant only in the ESCP2002 data ( F (1, 1580) = 7.60, p = .006, η 2 p = .002).

The interaction between sample and respondent age ( F (2, 2626) = 3.72, p = .024, η 2 p = .003) revealed that tightness scores in the ten years had risen the most among 15–29 ( F (1, 2626) = 20.1 p < .001, η 2 p = .008) and 30–44 year-old respondents ( F (1, 2626) = 22.1 p < .001, η 2 p = .008). There were no significant differences in tightness scores between the age groups either in the ESCP2002 or in the ESS2012 sample. As already mentioned, the group of 60–74-years-olds was not included in the ANOVA analysis, because the scalar measurement invariance assumption was not fulfilled for this group.

Sample and level of education also revealed a significant interaction in average tightness scores ( F (2, 3459) = 4.37, p = .013, η 2 p = .003), meaning that, in 2002, tightness scores decreased as education level increased, but, in the ESS2012 sample, there was no significant difference in tightness between the three education levels. Overall tightness rose significantly among people with secondary ( F (1, 3459) = 5.74, p = .017, η 2 p = .002) and tertiary education ( F (1, 3459) = 40.27, p < .001, η 2 p = .012).

Across-time change in single-item responses.

Finally, in order to better understand the factors behind the rise in the mean tightness score in Estonia from 2002 to 2012, changes in response to single TLS items were tracked. Fig 2 shows the mean (± 95% confidence intervals indicated by error bars) responses to single TLS items, separately for the ESCP2002 (left) and ESS2012 (right) samples. It is evident that in 2012 people still agreed that there are rather many social norms in Estonia (item #1) and that people will disapprove of inappropriate behavior (item #5). These perceptions had not changed in the ten years.

*** p < .001.

https://doi.org/10.1371/journal.pone.0145213.g002

At the same time, in the year 2012, people reported having clearer expectations of how they should act in certain situations (item #2; ESCP2002 M = 3.98. SD = 1.25, ESS2012 M = 4.14, SD = 1.06; t (3115) = -4.06, p < .001, d = -0.14) and stronger general agreement about appropriate and inappropriate behaviors (item #3; ESCP2002 M = 3.58. SD = 1.24, ESS2012 M = 3.82, SD = 1.11; t (3202) = -6.01, p < .001, d = -0.20) than in 2002. Also, compliance with social norms had significantly risen (item #6; ESCP2002 M = 3.29. SD = 1.18, ESS2012 M = 3.70, SD = 1.07; t (3219) = -10.64, p < .001, d = -0.34).

Tightness-looseness, defined as the strength of social norms and tolerance of deviant behavior, was recently proposed as a core or critical dimension along which cultures vary [ 12 ]. Cultural tightness–looseness has even been shown to moderate the effects of cultural values at the national level, among many other things, with Hofstede’s individualism–collectivism and power distance having significantly stronger effects on various outcomes in culturally tighter countries [ 54 ]. However, as cultures are not static but “constantly changing, open systems of attitudes, norms, behaviors, artefacts, and institutions that people reinforce but also continually modify or even challenge through diverse means of participation and engagement” (p. 789, [ 55 ]), it is also important to examine change across time as well as within-country variation in tightness-looseness in order to understand and model cultural change. The current study was undertaken to fill this substantial gap in our knowledge. Specifically, we examined across-time variation and within-country differences in tightness-looseness by surveying two large and nationally representative samples of Estonians about their perception of tightness-looseness in their country over a period of 10 years, that is, from 2002 to 2012.

Across-time change in tightness-looseness

Measurement invariance analyses showed that cultural tightness-looseness is a valid and reliable cultural construct, with a stable structure over a ten-year period, across and within different social subgroups. The mean tightness score in 2002 ( M = 3.86) was the same as the non-standardized tightness score for the Estonian convenience sample in a 33-country comparative study [ 12 ] for which data were collected in 2001. Thus, our findings show that, even in loose countries, such as Estonia, where norms, values, and behaviors show greater variability than in tight countries, convenience or unrepresentative samples may adequately reflect the general population (see [ 21 ], for a differing view).

In terms of across-time change in tightness-looseness, the results of the current study show that cultural tightness in Estonia rose significantly from 2002 to 2012, although the effect size of the change was small. It is argued by several theorists as well as demonstrated by empirical research (e.g., [ 22 , 25 , 56 ]) that socioeconomic development in a society brings systematic and pervasive cultural changes, including changes in people’s basic value orientations. In 2002, when our first data were collected, Estonia was still a transitional country, on a path of re-integration with Europe, with joining the EU and NATO in 2004 marking the end of the transition period [ 36 ]. The economy grew rapidly until 2007, then declined considerably during the financial crisis of 2008–2009, and began to slowly rise again during 2010–2012. We cannot say with any certainty whether, or to what extent, the slight rise in tightness that we saw in 2012, as compared to 2002, is due to changes in social and/or economic development in Estonian society during this period. It is, however, highly likely that tightness scores rose from 2002 to 2012 because new rules and norms for behavior (the previous ones were turned upside-down when Estonia regained its independence in 1991) had finally become established. This interpretation is further supported by the item-level analysis of the TLS, which revealed that, whereas the perceived number of social norms had not changed from 2002 to 2012, people felt that the norms were clearer and there was more general agreement about appropriate vs. inappropriate behavior in 2012 than in 2002. The expected compliance with social norms had also risen significantly. Thus, this perceived clarification of social norms can, on the one hand, be viewed as an indication of cultural stabilization (e.g., related to the end of the transition phase in Estonia), but, on the other hand, can explain the rise in cultural tightness–there is now more agreement about what appropriate behaviors in this culture are.

To sum up, the current study showed that the level of perceived tightness in a culture can change over a period of ten years. However, despite the fact that Estonian society has undergone some major changes during the time period studied, the effect size of the change in the mean tightness score was relatively small. Thus, our results suggest that tightness-looseness, similarly to cultural value orientations, is a relatively stable and robust characteristic of culture–change indeed takes place, but slowly [ 42 , 46 , 57 ]. However, further studies need to be conducted to test these findings in other countries with either a more stable or a more turbulent economic and political history, in order to find out whether, and how much, changes in social structure, politics, or economic growth/decline affect the perceived strength of social norms in a culture.

Within country-differences in tightness-looseness

Although the mean tightness score in Estonia had risen slightly from 2002 to 2012, the small within-country differences that were present in 2002 (tightness scores were slightly higher for females than males, and lower for people who had higher education compared with those who had primary or secondary education) had disappeared by 2012. The fact that social norms were perceived more clearly and there was more agreement about appropriate vs. inappropriate behavior in 2012 than 2002 might also explain why the within-country differences that were present in 2002 had vanished by 2012. Yet, the main finding of our study is that despite Estonia being a loose country, which, by definition, means that is has greater within-country heterogeneity in norms, behaviors, and values than tight countries, we were not able to identify any significant within-country differences in TLS in terms of age, gender, place of residence, education, or ethnicity. But, as already noted, Estonia is a relatively loose, yet a very small country, and therefore, further research about intracultural variation in tightness-looseness should target larger societies with more diverse populations. For example, a recent study [ 16 ], using a theoretically constructed index of tightness-looseness, showed that within-country differences in large countries, where people come from varying cultural backgrounds, can be evident.

Clearly, the most surprising finding of this study was that we did not find any significant differences in tightness-looseness between the Estonian-speaking majority (roughly 68%) and Russian-speaking minority populations. This finding is especially remarkable as many previous studies have shown that there are large differences in value preferences between the Estonian- and Russian-speaking populations in Estonia [ 38 , 58 , 59 ]. Also, one might have expected that the so-called “Bronze soldier crisis” that took place in 2007 [ 60 , 61 ] would have shifted perceptions of tightness-looseness among the Estonian- and Russian-speaking populations in different directions. However, similarly to 2002, there were no differences in perceived social norms between ethnic Estonians and Estonian Russians in 2012, and the overall agreement about acceptable and unacceptable behavior had risen. Thus, although a recent report [ 62 ] shows that there is still a strong division across linguistic, ethnic, and socioeconomic lines in Estonia, with Estonian- and Russian-speakers living in different ‘cultural spaces’ (both in terms of residential and work-place segregation, as well in media use), the two ethnolinguistic groups seem to share the same perception of the strength of social norms and deviant behavior in their country. However, one should bear in mind here that the measure of tightness-looseness that we used in our study, the TLS, only tells us about the perceived strength and clarity of social norms in Estonia but not about the content or specific expressions of these social norms. Thus, while Estonian- and Russian-speakers agree about the level of societal permissiveness in Estonia, their values and social norms might still be different.

In conclusion, our results suggest that tightness-looseness is a relatively stable and robust characteristic of culture with low levels of within-country variation, at least in small and culturally uniform settings, such as Estonia. Future studies about across-time change and within-country variance in tightness-looseness should target more culturally diverse and socially divided societies.

Supporting Information

S1 appendix. items of the tightness-looseness scale..

https://doi.org/10.1371/journal.pone.0145213.s001

S1 Text. Reliability and validity of the Tightness-Looseness Scale.

https://doi.org/10.1371/journal.pone.0145213.s002

S1 Table. Inter-item correlations between the items of the Tightness-Looseness Scale.

https://doi.org/10.1371/journal.pone.0145213.s003

S2 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between ESCP2002 and ESS2012 data.

https://doi.org/10.1371/journal.pone.0145213.s004

S3 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between different subgroups in the ESCP2002 data.

https://doi.org/10.1371/journal.pone.0145213.s005

S4 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between different subgroups in the ESS2012 data.

https://doi.org/10.1371/journal.pone.0145213.s006

Acknowledgments

This study is based on a Master's thesis by Anne Mandel defended in the Department of Psychology, University of Tartu in 2014. We are grateful to Jüri Allik and Delaney Michael Skerrett for their helpful comments on earlier drafts of this article.

Author Contributions

Conceived and designed the experiments: AR. Performed the experiments: AR. Analyzed the data: AM AR. Contributed reagents/materials/analysis tools: AM AR. Wrote the paper: AM AR.

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DOI: 10.1037/0021-9010.91.6.1225
Corpus ID: 2615659

On the nature and importance of cultural tightness-looseness.

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Cultural tightness–looseness and national innovativeness: impacts of tolerance and diversity of opinion

Carsten Deckert 2 &
Rahel M. Schomaker 1

Journal of Innovation and Entrepreneurship volume 11 , Article number: 29 ( 2022 ) Cite this article

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The links between innovativeness as a driver of economic performance, and the determinants of innovativeness have been investigated by management scholars and economists for decades, focusing mostly on “hard factors” as investment in research and development, or education. Focusing on a relatively neglected, but in times of globalization even more important aspect, the influence of cultural characteristics on innovativeness, we apply different econometric models to test for links between cultural tightness and looseness on the one hand, and national innovativeness on the other hand. We find that cultural tightness—in the sense of homogenous and intolerant societies—has a negative link to national innovativeness, while cultural looseness—in the sense of tolerant and diverse societies—displays a positive link to national innovativeness.

Introduction

The connection between innovation and economic performance has been discussed in management literature as well as economic theory for several decades, with the overall conclusion that the economic performance of countries not least depends on their innovativeness (Freeman, 1996 , 2002 ; Porter, 1990 ; Verspagen, 2006 ). Given this relevance of innovativeness for societies and economies, potential driving factors have been examined, with human capital, property rights, education, research institutions being among the most extensively used explanatory factors, even if they explain only a part of the variance in innovativeness among countries (Taylor, 2016 ). Thus, we focus on an additional group of potential explanatory factors, cultural characteristics, taking stock of the analysis of Landes ( 2002 : 516) that states that “culture makes all the difference” when it comes to economic development and, hence, innovativeness as it influences the creation and dissemination of knowledge in a country.

Putting national innovativeness center stage, the paper at hand focuses on cultural characteristics as potential driving factors, in detail the concept of tightness and looseness as developed by Gelfand et al., ( 2011a , 2011b ), and Uz ( 2015a , 2015b ). The paper proceeds as follows: after this introduction and short considerations of the concepts of innovativeness and tightness/looseness, we empirically test our hypotheses. Applying different econometric methods, we find that tightness, understood as low tolerance, isolation, and a homogenous society, affects national innovativeness negatively, while looseness in the sense of tolerant and diverse societies has a positive influence on national innovativeness. After a reflection of these findings against the backdrop of current research, we draw some policy recommendations.

Literature review

National innovativeness

Innovativeness can be defined based on approaches that focus on the adoption of new ideas in a social system, as emphasized by diffusion theory (e.g., Rogers, 2003 ), or ‘the quality of being innovative’ (Kumar, 2014 : 3; for details on different definitions of innovativeness see Deckert & Schomaker, 2018 ). The latter one constitutes the approach that is taken in this study. Thus, innovativeness comprises conditions which “need to be created for a system to continuously—not just intermittently—induce innovations” and “which can relate to individuals, companies, networks and teams and to whole societies as a multidimensional construct with many levels” (Trantow et al., 2011 : 3).

Related to the idea by Trantow et al. ( 2011 ), national innovativeness as being focused on in our study can also be understood as innovative capacity (Furman et al., 2002 ; Porter & Stern, 2001 ), propensity to innovate (Williams & McGuire, 2010 ) or innovation performance (Adam, 2013 ; Gault, 2014 ). In other words, it is “a country’s potential […] to produce a stream of commercially relevant innovations” (Porter & Stern, 2001 : 29), and “the ability of a country to produce and commercialize a flow of innovative technology over the long term” (Furman et al., 2002 , p. 899). Not only the outcome in terms of realized or diffused innovations matter, but also “the fundamental conditions, investments and policy choices that create the environment for innovation in a particular location” (Porter & Stern, 2001 : 23). National innovativeness depends on knowledge and technology creation and diffusion, thus the support provided by national institutions as research policies, or “networks of related actors and institutions such as entrepreneurs, private enterprises with professional research and development facilities, public research institutes and universities” (Deckert & Schomaker, 2018 ). These systems are typically referred to as National Innovation Systems (NIS) or National Systems of Innovation (NSI), and focused on in this paper (Freeman, 1995 ; Freeman & Soete, 1997 ; Lundvall, 1999 , OECD, 1997 ).

Cultural factors—the tightness–looseness concept

The concept of cultural tightness–looseness as cultural traits was introduced in anthropology to classify different forms of traditional societies along a continuum (Pelto, 1968 ). Later, Triandis ( 1989 ) proposed the concept as an important cultural dimension of modern societies, complementing other cultural features or characteristics as used for classification of cultures before.

Tightness–looseness in the cultural context is defined by Witkin and Berry ( 1975 : 16) as the “degree of hierarchical structure among sociocultural elements in a society” and addresses issues of pressure to conform and social control. According to Triandis ( 1989 : 511), “ingroup members behave according to the ingroup norms” in tight cultures, whereas in loose cultures either norms are unclear or deviations from norms are tolerated. In a similar vein, Carpenter ( 2000 : 41) argues that in tight cultures “norms are explicit and stringently enforced”, while in loose cultures “behaviors that constitute proper behavior are relatively flexible and more freely chosen” and “deviations from norms are more tolerated”. Finally, Gelfand ( 2012 : 420) defines tight societies as “societies that have strong norms and a low tolerance for deviant behavior” and loose societies as “societies that have weak norms and a high tolerance for deviant behavior”.

While cultural dimensions for modern societies typically focus on certain values (e.g., Hofstede, 2003 ; House et al., 2004 ), the concept of tightness–looseness focusses on social or cultural norms (Gelfand, 2012 ; Gelfand & Jackson, 2016 ), i.e., “socially agreed-on standards for behavior” (Gelfand et al., 2017 : 800). Gelfand et al. ( 2006 ) distinguish between two key components of tightness–looseness in this regard: first, the strength of social norms as manifested by their number and clarity, and, second, the degree of sanctioning as revealed by the tolerance of deviation from social norms.

Tight societies are usually more homogenous and isolate themselves from external cultural influences (Triandis, 1989 ). Thus, on average, loose cultures are seen as more creative as they are more open to different ideas, different people and different cultural influences (Gelfand, 2018 ). Triandis ( 1989 ) proposes a weak linear relation of tightness to collectivism. As individualism is usually associated with creativity and innovation (Lubart, 2010 ), loose societies should also be more creative due to a higher level of individualism. Gelfand et al. ( 2006 ) propose that individuals in loose societies usually have a greater promotion focus Footnote 1 and a greater preference of the cognitive style of innovators. Footnote 2 Furthermore, organizations in loose societies have a tendency towards experimentation, trial and error as well as a culture of lower constraints.

Hence, cultural tightness and looseness, respectively, exhibit close relations not only to individual behavior, but also to cultural and socio-economic institutions (Gelfand et al., 2011a : 1102). According to North ( 1991 : 97) institutions are “the humanly devised constraints that structure political, economic and social interaction”. While they can be differentiated in more formal and informal institutions, there is some evidence that social, political and economic institutions are not independent of each other, and a result of societal action and preferences: “Economic institutions, and institutions more broadly, are endogenous; they are, at least in part, determined by society, or a segment of it. Consequently, the question of why some societies are much poorer than others is closely related to the question of why some societies have much ‘worse economic institutions’ than others” (Acemoglu et al., 2005 : 389). Thus, Acemoglu and Robinson ( 2013 ) argue that societal and political institutions of a country shape its economic institutions. Centralized and pluralistic political institutions such as secure property rights for all citizens, equal opportunities and checks of power set incentives for innovation, as they guarantee functioning markets and foster the market entry of new products, processes or business models. Following this argument, tightness and looseness as factors being correlated to societal values and expressed political preferences, necessarily influence economic institutions via elections, the composition of organizations and organizational behavior.

One important chain of transmission is related to cultural factors. Based on categories from the GLOBE study, Schomaker and Deckert ( 2020 ) specify cultural dimensions that influence political institutions and therewith national innovativeness. These dimensions are Power Distance, In-Group Collectivism and Performance Orientation (Deckert & Schomaker, 2018 ). From these, Power Distance Footnote 3 and In-Group Collectivism Footnote 4 show a close connection to cultural tightness, as typically high degrees of both of these indicators are related to severe restrictions in personal freedom. A high Power Distance implies stronger tendencies to unequal power distribution, stable and scarce power bases, high levels of corruption, unequal opportunities for the members of society and limited upward social mobility (House et al., 2004 ). Power Distance is negatively correlated with innovativeness, pluralistic institutions seem to be conducive to innovations while exclusive institutions are detrimental to innovations.

The impact of In-Group Collectivism may be explained through the degree of exclusiveness and clanism in a society that may lead to a solidification of the status quo, as these factors help existing elites to maintain and consolidate their position (Deckert & Schomaker, 2018 ). Thus, the high correlation between In-Group Collectivism and a high degree of cultural tightness makes it plausible to assume the same effects for the latter one (Triandis, 1989 ).

Based on these considerations, it can be derived that loose societies due to individual behavior as well as their institutional framework depict a higher level of national innovativeness, while tight groups and societies—and therewith the respective economies—show lower levels of innovative behavior and enabling institutions, and therewith national innovativeness.

Operationalization of cultural tightness–looseness

As for an operationalization of the concept of cultural tightness–looseness as delineated above, two approaches are discussed in literature: first, the tightness score of Gelfand et al., ( 2011a , 2011b ), and, second, the cultural tightness–looseness (CTL) index of Uz ( 2015a , 2015b ).

For constructing the respective scores, Gelfand et al. ( 2011a ) collected primary data from 6960 individual respondents in 33 countries. Footnote 5 For doing so, a survey of six questions was used, tackling the number and clarity of social norms, agreement on social norms, freedom of behavior, degree of sanctioning and compliance to social norms. The items are rated on a Likert scale with six response levels and ranked (Gelfand et al., 2011b ). Footnote 6 The higher a country is ranked on the tightness score, the higher its cultural tightness is.

Uz ( 2015a ) applies the concept of variance to determine cultural tightness–looseness, as tight cultures are usually homogenous (Triandis, 1989 , 1994 ), with less variation across individuals in a tight society (Gelfand et al., 2006 ). For constructing the respective indicator, she uses secondary data from the 4th wave of the World Values Survey (WVS) as conducted in 2000, and calculates the standard deviation of selected items from this survey. The higher the standard deviation of a country, the looser the respective society is (Uz, 2015a ).

From this point of departure, she calculates three indices (Uz, 2015a , 2015b ): The domain-specific index contains data from the Morally Debatable Behaviors Scale (MDBS) of 68 countries, Footnote 7 which measures the tolerance for moral deviations, i.e., acceptability of prostitution, abortion, divorce, euthanasia, and suicide. The domain-general index calculates the mean of the standard deviations of all 124 items of the WVS of 64 countries. The combination index categorizes items of 65 countries according to the domains of work, family and religion and determines a score of the standard deviation of the domains. Footnote 8

Uz ( 2015a ) proposes the application of the combination index as it conflates the advantages of the other two indices (domain-specific index and domain-general index). The combination index has great variety of values as well as great validity, and its weights of items is independent of the number of survey questions in the respective category.

Hence, the two indicators as discussed measure the same concept—tightness–looseness—applying different methodologies and with a different message: While in the tightness score of Gelfand et al. ( 2011a ) high values indicate for tight cultures, in the cultural tightness–looseness index combination index of Uz ( 2015a ), high values stand for loose societies.

While the concept of tightness and looseness often is discussed separately from other concepts of cultural dimensions typically used in empirical work (see e.g., Deckert & Schomaker, 2018 ), interrelations between different approaches can be identified. Overall, the tightness score of Gelfand et al. ( 2011b ) has a statistically significant, negative correlation to individualism and a statistically significant, positive correlation to Power Distance as used by Hofstede ( 2003 ), with the Hofstede-dimension of Individualism being positively related to innovativeness, the dimension of Power Distance being negatively related to innovativeness (Deckert & Nyssen Guillén, 2017 ). The indicator of Uz ( 2015a ) is negatively correlated to conformity, and, as will be discussed in the following, positively correlated to innovation as measured by the Global Innovation Index (Uz, 2015b ).

Thus, our empirical strategy is based on the following hypotheses as derived from theoretical considerations how tightness and looseness may affect innovativeness. Our working hypothesis is that cultural tightness has a negative relation to national innovativeness, and conversely cultural looseness has a positive relation to national innovativeness. Based on this, we scrutinize the hypotheses as follow in our empirical tests:

The tightness score (TS) of Gelfand et al. ( 2011a ) has a negative relation to national innovativeness.

The cultural tightness–looseness combination index (CTL_C) of Uz ( 2015a ) has a positive relation to national innovativeness.

Data and methodology

With a view on the data available, we decided to apply a multi-step research design: firstly, we test the different measures for cultural tightness/looseness and the measure for innovativeness as delineated above for correlations both of the ranks as well as the values.

Secondly, we apply a hierarchical cluster analysis to group together countries that are “close” to one another in terms of cultural looseness on the one hand, and innovativeness on the other hand. Thus, this technique allows us to detect groups by proceeding sequentially from tighter, less inclusive clusters to larger more inclusive clusters (Bridges, 1966 ).

Thirdly, taking into consideration that the results may be affected by potential endogeneity issues, therewith using this approach only supplementary, we follow up with the theoretical discussion of potential causal links between cultural factors and innovativeness. Due to methodological and data limitations, in empirical studies, these tests are hardly to be found (e.g., Taylor, 2016 ). Nonetheless, being aware of the existing restrictions, we apply regression models to test in how far cultural characteristics could be interpreted as drivers of innovativeness.

As the measure of innovativeness on the country level, the values of the Global Innovation Index (GII) for 2019 are used, as there is already sound evidence for the indicator being a suitable measure for innovativeness in the context of cultural influences (e.g., Deckert & Nyssen Guillén, 2017 ; Deckert & Schomaker, 2018 ). The Global Innovation Index is calculated as the simple average of two sub-indexes, the Innovation Input Sub-Index and the Innovation Output Sub-Index. While the first sub-indicator comprises facilitators of innovation activities such as human capital and infrastructure, the second sub-indicator scrutinizes the results of innovation activities (Cornell University, INSEAD and WIPO, 2019 ).

Furthermore, we use data from the Innovation Union Scoreboard (IUS)/European Innovation Scoreboard (EIS) for 2013 as a robustness check. The IUS/EIS is published annually by the European Commission and measures the innovativeness of the EU member states with an index of about 25 indicators (Hollanders & Janz, 2014 ). Thus, the IUS offers a more homogenous data set, as European member states are usually culturally closer than states of different continents. The Global Innovation Index (and the Innovation Union Scoreboard) in the regression models constitute for the dependent variable.

As measures for cultural tightness/looseness, the tightness score of Gelfand et al. ( 2011a ), and the cultural tightness–looseness combination index of Uz ( 2015a ), respectively, are used. In the regression models, these indicators are applied as independent variables.

Due to the composition of the respective indices—indices for tightness/looseness, as well as index for innovativeness—index values stand for ordinal scales. Hence, in a first step, we used rank correlations to detect links between cultural values and innovativeness. These rank correlations measure the relationship between rankings of different ordinal variables. The correlation coefficient in these cases indicates for the degree of similarity between rankings of two variables, and is used to assess the significance of the relation between the variables. In our case, we use Spearman’s rho test.

Nonetheless, in particular as the number of groups is very high, there are no general reservations regarding the application of regression models that are usually used for metric data (Zumbo & Zimmerman, 1993 ). Hence, in later stages of our empirical strategy we treat the variables as metric for correlation analysis, factor analysis, and regression analysis.

The regressions apply a Generalized Linear Model with a log link. This model fits a link between one or a vector of explanatory variables (and sometimes also one or a vector of control variables), and a dependent variable. In our case, the independent variables are the indices for tightness/looseness as delineated above, while the dependent variable is national innovativeness, measured in GII (as well as other specifications for robustness checks). The regression coefficient displayed in such models—Exp( B )—cannot be interpreted as in linear Ordinary Least Square regressions, but indicates for the odd ratio that innovativeness measured in GII increases once the respective independent variable increases. Footnote 9

As can be drawn from Table 1 , there is a high, positive and statistically significant (1% level) correlation between the Global Innovation Index and the rank cultural tightness–looseness combination index. This is in line with the findings of Uz ( 2015a ) for data from 2007 that the combination index is positively correlated to innovation as measured by the Global Innovation Index (Uz, 2015b ).

As for the correlation using the rank of the tightness score and the rank of the Global Innovation Index, see Table 2 , a slightly negative, but insignificant correlation can be stated.

As can be drawn from Table 3 , these results hold also for correlation analysis using not the ranks, but the metric values. As for the cultural tightness–looseness combination index, a significant and positive correlation with the Global Innovation Index exists.

The correlation between the tightness looseness score and the Global Innovation Index remains insignificant, but is negative also applying the metric measures (see Table 4 ).

A hierarchical factor analysis supports our findings. As can be drawn from Fig. 1 , two groups of countries can be differentiated between—countries with a high level of innovativeness and a high degree of looseness, and countries with a low level of both innovativeness and looseness, thus a high tightness. This substantiates the hypothesis that there is a close link between the concepts.

Clusters of cultural tightness–looseness and innovativeness. Source: Authors’ compilation

Based on these findings, taking into consideration the methodological caveats as discussed above, we apply regression models on the respective variables. As for this step of our empirical strategy, the following picture can be drawn: we find the following significant positive impact of the cultural tightness–looseness index (CTL_C) on national Innovativeness, while there is a slightly negative, non-significant impact of the tightness score on national innovativeness (see Table 5 ).

Summing up, scrutinizing the outcomes as delineated above, we find some empirical support for our general hypothesis that there is a negative link between cultural tightness and innovativeness. Hypothesis 1—cultural tightness has a negative relation to national innovativeness, and conversely cultural looseness has a positive relation to national innovativeness, respectively—is supported by our empirical findings.

In detail, Hypothesis 1.1—tightness as measured by Gelfand et al. ( 2011a ) is affecting national innovativeness negatively—has to be rejected due to the missing significance. Nonetheless, while the respective coefficient remains insignificant, the algebraic sign is negative, indicating for a negative relation between tightness and innovativeness.

Secondly, Hypothesis 1.2—looseness as measured via the cultural tightness–looseness combination index of Uz ( 2015a ) has a positive relation to national innovativeness—is supported by our empirical findings: as can be drawn from Table 3 , there is a positive, statistically significant impact of the cultural tightness–looseness on national innovativeness, even if the respective coefficient is relatively small. Accordingly, an increase of looseness measured in the cultural tightness–looseness enhances the odd ratio of an increase of the innovativeness. Footnote 10

For robustness checks, we tested different alternative specifications of national innovativeness, e.g., the Rank Global Innovation Index (values for 2019), data from the Global Innovation Index for 2014, and the IUS Summary Innovation Index for 2013.

As the ranks used for the estimations as shown in Table 6 are inverted—with least innovative countries showing high ranks—the negative impact of looseness indicates for the causal relation as assumed.

As can be drawn from Tables 7 and 8 , the outcome using the Global Innovation Index 2014 and the IUS Summary Innovation Index 2013 as the dependent variable more or less replicate our findings as delineated above, indicating for a high level of robustness of our findings.

As expected following our theoretical delineations, a significant positive relation between cultural looseness—as measured by Uz ( 2015a )—on national innovativeness exists. Nonetheless, these finding due to missing significance do not hold for the data as provided by Gelfand et al. ( 2011a ). Even if methodological restrictions do not allow us to make a clear-cut statement about a causal relationship, we assume the link not being coincidental, but causal by nature. Further research applying more control variables to an adjusted data base may shed light on this. Overall, we can conclude that our working hypothesis is sufficiently underpinned by the outcomes of the different models and specifications using the cultural tightness–looseness index, so that we can assume this positive relation between innovativeness and cultural looseness being real.

Nonetheless, we have to take a deeper look on the non-significant results. Scrutinizing the disparate methodological approaches applied in the indices, one plausible assumption is that the missing significance in the models using the indicator as provided by Gelfand et al. ( 2011a ) can be explained by methodological differences in indicator construction, compared to Uz ( 2015a ).

First, there is a significant difference in the number of surveyed countries. Gelfand et al. ( 2011a ) include data from 33 nations, while the cultural tightness–looseness combination index by Uz ( 2015a ) is based on data from 65 nations. Furthermore, there is not a complete overlap of countries, as about 30% of the countries in the study by Gelfand et al. ( 2011a ) are not included in the study by Uz ( 2015a ).

Second, there are differences in the sampling of data within the covered nations. Sampling of data is a critical issue as there are not only national differences of tightness–looseness (Chan et al., 1996 ; Gelfand et al., 2011a ; Uz, 2015a ), but also regional differences within nations (Chua et al., 2019 ; Harrington & Gelfand, 2014 ; Uz, 2016 ). The World Values Survey (WVSA, 2020 ) used by Uz ( 2015a ) usually has sample sizes of between 1000 and 1500 respondents per country. The main distributions of the samples are according to country characteristics such as percentage of urban and rural population. Gelfand et al. ( 2011a ) have sample sizes between 111 and 312 respondents per country, and respondents are exclusively from the urban population. A focus on urban population could lead to a bias in answers, as people from rural areas are typically tighter than people from urban areas (Triandis, 1989 ).

Third, there are differences in measurement. Gelfand et al. ( 2011a ) use primary data, i.e., they directly ask people about the tightness in their respective societies, while Uz ( 2015a ) uses secondary data from the WVS and indirectly infers the tightness via the variance of answers. Uz ( 2015a ) criticizes that Gelfand et al. ( 2011a ) do not measure tightness, but rather perception of tightness. The different procedures imply that Gelfand et al. ( 2011a ) use a measure of central tendencies (mean value), while Uz ( 2015a ) uses a measure of spread (standard deviation). Furthermore, Gelfand et al. ( 2011b ) only ask questions about tolerance for norms in general. As there is a “discrepancy between the principle and the practice of tolerance” (van Doorn, 2012 : 6), there is typically an inconsistency between general norms people claim to abide by and specific norms people apply with regard to controversial issues. This means that self-assessment of general tolerance is typically higher than self-assessment of specific tolerance, especially for controversial issues. Questions on specific tolerance regarding controversial issues such as religion, political views and sexual orientation are included in the WVS used by Uz ( 2015a ). All in all, it could be argued that the answers in the study of Gelfand et al. ( 2011a ) are expected to be biased towards looseness due to the focus on urban population and on general tolerance.

Scrutinizing these considerations and the fact that a larger sample usually provides better results in empirical research, we can plausibly assume that the data sample used by Uz ( 2015a ) provides not only a higher sample quality due to the additional variance of countries and aspects covered, but also a better basis for estimation models.

Hence, coming to terms with the interpretation of our results, we only observe a significant positive relation to innovativeness when tightness–looseness is measured as a spread of norms as in the study of Uz ( 2015a ). This indicates that pluralism or diversity of opinions in a society is conducive to innovativeness. However, loose culture does not mean a high individual tolerance in general, but rather the endurance of low and high specific tolerance of controversial issues within an open society.

Our results on the role of diversity on the societal level is in line with studies tackling the macro-level with regard to economic development (Alesina et al., 2003 ; Gören, 2014 ; Montalvo & Reynal-Querol, 2005 ), as well as the meso- and micro-level, focusing on creativity and innovation with regard to regional units or teams. Cultural and functional diversity in teams have a positive impact on creativity (Paulus et al., 2012 , 2016 ; Reiter-Palmon et al., 2012 ; Stollberger et al., 2019 ). However, team diversity needs to be balanced by participatory safety to strengthen team identity and increase the receptiveness for different individual perspectives (Deckert, 2019 ). Likewise, for urban regions there is evidence that a diverse and heterogeneous region will attract more creative people, accelerates knowledge diffusion, and leads to a higher rate of innovation and ultimately economic growth (Florida, 2004 ). Diverse societal norms, values and ethics can induce technological innovation and the diffusion of new ideas, “heterogeneity improves problem-solving” and “heterogeneous groups of people with limited abilities can do better than homogeneous groups of high-ability problem-solvers” (Bove & Elia, 2017 : 228; also Ager & Brückner, 2013 , Ottaviano & Peri, 2006 ).

Hence, while diversity can lead to more conflict, on the micro- as well as the macro-level (Alesina & La Ferrara, 2005 ; Esteban & Ray, 2011 ; Montalvo & Reynal-Querol, 2005 ), it also can enhance creativity, if it is a disagreement about the related task (task conflict), solved in a constructive way, and of low intensity (Paulus et al., 2012 , 2016 ; Reiter-Palmon et al., 2012 ; Stollberger et al., 2019 ). Hence, if managed constructively, diversity is an asset for innovativeness more than an obstacle.

Applying correlation analysis, factor analysis and regression analyses, we were able to show that loose cultures on average display a higher national innovativeness, with cultural looseness having a positive link to innovativeness. Nonetheless, this significant positive link between looseness on national innovativeness only holds when tightness–looseness is measured as a spread of norms following Uz ( 2015a ).

At this point, we draw to the reflections by Koestler ( 1967 ) who calls humans “social holons”—a term derived from the Greek word “holos” for whole, and the suffix “on”, typically assigned to parts (as in proton). A “social holon” features a tension between the preservation of its individuality and the integration into a larger unit (e.g., family, nation), respectively. Understood in this way, different cultures position themselves on different spots along the continuum between preservation (individualism) and integration (collectivism). In this framework, cultural tightness as measured by Uz ( 2015a ) signifies how clearly this spot can be determined, i.e., if every individual in a society agrees on one spot (tight and homogeneous), or if people in a society can inhabit different spots (loose and heterogeneous).

With regard to innovativeness, we find that it is pluralism or diversity of opinions on specific controversial issues in a society rather than high individual tolerance that fosters innovation. This implies that it is not only necessary to give freedom to the individual, as John Stuart Mill ( 2002 : 69) argues when he says that “it is important to give the freest scope possible to uncustomary things, in order that it may in time appear which of these are fit to be converted into customs”. Moreover, it is necessary to have culture-specific norms as guiding principles, as Haidt ( 2013 : 359) reasons: “We need groups, we love groups, and we develop our virtues in group, even though those groups necessarily exclude nonmembers”. This dichotomy is the inherent paradox in the concept of looseness of Uz ( 2015a ), and thus in the mechanisms fostering innovativeness. The knack seems to be the capacity of a society to simultaneously endure groups with different degrees of tolerance towards controversial issues and to manage the peaceful exchange between these groups. It is looseness in this sense that is conducive to innovativeness.

Appendix 1: Summary statistics

		Minimum	Maximum	Mean	Standard deviation
CTL_C	64	.00	119.80	53.1141	26.56960
GII	64	22.30	63.65	41.5083	11.29005
GII SUB-Index Input	64	29.22	72.15	50.1927	11.29187
GII SUB-Index Output	64	13.32	57.49	32.8173	11.88716
Rank CTL_C	64	1.0	64.0	32.500	18.6183
Rank GII	64	1.0	64.0	32.500	18.6188
Rang GII SUB-Index Input	64	1	64	32.50	18.619
Rang GII SUB-Index Output	64	1	64	32.50	18.6186

Data Gelfand

		Minimum	Maximum	Mean	Standard deviation
CTL	32	1.6	12.3	6.578	2.7862
GII	32	25.36	61.73	48.7263	9.24454
GII SUB-Index Input	32	31.26	72.15	57.5775	9.75359
GII SUB-Index Output	32	19.10	57.49	39.8641	9.69809
Rank CTL	32	1.0	32.0	16.500	9.3783
Rank GII	32	1.0	32.0	16.500	9.3800
Rank GII SUB-Index Input	32	1.0	32.0	16.500	9.3800
Rank GII SUB-Index Output	32	1.0	32.0	16.500	9.3800

Appendix 2: List of countries Gelfand et al.

Australia

Austria

Belgium

Brazil

Estonia

France

Germany (former East)

Germany (former West)

Greece

Hong Kong

Hungary

Iceland

India

Israel

Italy

Japan

Malaysia

Mexico

Netherlands

New Zealand

Norway

Pakistan

People’s Republic of China

Poland

Portugal

Singapore

South Korea

Spain

Turkey

Ukraine

United Kingdom

United States

Venezuela

Appendix 3: List of countries Uz

Albania

Algeria

Argentina

Austria

Bangladesh

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Canada

Chile

China

Croatia

Czech Republic

Denmark

Egypt

Estonia

Finland

France

Germany

Great Britain

Greece

Hungary

Iceland

India

Indonesia

Iran

Ireland

Italy

Japan

Jordan

Kyrgyzstan

Latvia

Lithuania

Luxembourg

Macedonia

Malta

Mexico

Moldavia

Morocco

Northern Ireland

Netherlands

Nigeria

Pakistan

Peru

Philippines

Poland

Portugal

Puerto Rico

Romania

Russian Federation

Saudi Arabia

Serbia & Montenegro

Singapore

Slovakia

Slovenia

South Africa

South Korea

Spain

Sweden

Tanzania

Turkey

Uganda

Ukraine

United States of America

Venezuela

Vietnam

Zimbabwe

Appendix 4: Data for index construction by Uz

Index	No. of countries	Questions included
Domain specific index	68 (without Iraq and Israel)	WVS, Wave 4, Card W (Morally Debatable Behavior Scale, MDBS): V204, V206, V207, V209, V210, V211, V212, V213
Domain general index	64 (without China, Iraq, Israel, Saudi Arabia, Singapore and Venezuela)	WVS, Wave 4, all Cards
Combination index	65 (without China, Iraq, Israel, Pakistan and Venezuela)	WVS, Wave 4, Card C (work), Card D (family), Card E (politics) and Card F (religion) Card A (importance of domains) used as a weight

Index

No. of countries

Questions included

Domain specific index

68 (without Iraq and Israel)

WVS, Wave 4, Card W (Morally Debatable Behavior Scale, MDBS): V204, V206, V207, V209, V210, V211, V212, V213

Domain general index

64 (without China, Iraq, Israel, Saudi Arabia, Singapore and Venezuela)

WVS, Wave 4, all Cards

Combination index

65 (without China, Iraq, Israel, Pakistan and Venezuela)

WVS, Wave 4, Card C (work), Card D (family), Card E (politics) and Card F (religion)

Card A (importance of domains) used as a weight

Explanatory notes:

WVS: World Values Survey ( https://www.worldvaluessurvey.org/wvs.jsp ).

1 Countries which answered more than 90% of relevant questions ( n = 70).

2 Questions from the respective Cards that have been asked in 90% of the countries.

3 “These 124 values and behaviors asked across countries include what is important in life, child rearing values, ways of spending leisure time, tolerance for different people, moral values, work values, family values, gender roles, politics, democracy, opinions about different formal and informal intuitions [sic], religion and religious beliefs/behavior, feelings of belonging and national identity” (Uz, 2015b , p. 2).

Availability of data and materials

The data will be made accessible upon request.

For the self-regulation of motivational states, Higgins ( 1997 , 1998 ) proposes a concept of promotion focus and prevention focus. The promotion focus is characterized by a tendency to approach positive outcomes as expressed in a preference to look for hits and avoid errors of omission (Higgins, 1997 ). It is concerned with “accomplishments, hopes, and aspirations” (Higgins, 1998 : 17). The prevention focus is characterized by a tendency to avoid negative outcomes, which is expressed in a preference to avoid misses and errors of commission (Higgins, 1997 ). It is concerned with “safety, responsibility, and obligations” (Higgins, 1998 : 17).

Kirton ( 1989 ) distinguishes between the cognitive styles of adaptors and innovators. While adaptors usually “accept the generalized theories, policies, customary viewpoints or […] ‘paradigms’” of a given problem, innovators “detach the problem from its cocoon of accepted thought, to reconstruct the problem and its attendant paradigm while in the pursuit of a solution” (Kirton, 1989 : 6).

Power Distance is defined as the “degree to which members of a collective expect power to be distributed equally” (House et al., 2002 , p. 6).

In-Group Collectivism is defined as the “degree to which individuals express pride, loyalty, and cohesiveness in their organizations and families" (House et al., 2002 , p. 6).

For a full country list see Appendix .

In detail, the following questions were asked: 1. There are many social norms that people are supposed to abide by in this country. 2. In this country, there are very clear expectations for how people should act in most situations. 3. People agree upon what behaviors are appropriate versus inappropriate in most situations this country. 4. People in this country have a great deal of freedom in deciding how they want to behave in most situations. (Reverse coded) 5. In this country, if someone acts in an inappropriate way, others will strongly disapprove. 6. People in this country almost always comply with social norms. The index was tested for reliability and validity It was examined if people have low variability in their perceptions of the strength of social norms and the degree of tolerance for deviance in their respective country, if there is significant between-nation variance in the construct, and if country-level means are reliable at the culture level. For a detailed description of the methodology used by Gelfand et al. ( 2011a ) see the supplemental material of the respective article (Gelfand et al., 2011b ).

For a detailed overview of the three indexes developed by Uz ( 2015a ), see the table in the Appendix of the paper at hand, and the supplemental material of the respective article (Uz 2015b ).

Thus, a coefficient Exp( B ) > 1 stands for a positive impact, while Exp( B ) < 1 stands for a negative impact.

Due to the nature of the data—innovativeness scores were measured chronologically later than the cultural scored—and additional tests, a potential “reverse causality” can be neglected. Likewise, biases caused by “omitted variables” that influences both, innovativeness and the cultural features, are not impossible, but unlikely. As cultural values and characteristics are a relatively stable trait, influencing factors would have to be rooted at least partly in the ancient history of the respective country, while the actions and policies as measured in the innovation indices (independent variables) were implemented only recently; thus, heterogeneity is unlikely to occur.

Abbreviations

Cultural tightness–looseness combination index

Global Innovation Index

Tightness score

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Tightness and Looseness: When Culture Does and Does Not Matter in Conflict

A recent article published in Science helps to resolve an age-old dispute about culture and conflict: Does it really matter? The study conducted in 33 nations by a team headed-up by Michele Gelfand at the University of Maryland found that the answer to the question do cultural differences really affect conflict experiences, processes and outcomes is a resounding – it depends. It depends on how tight the culture is around disputes.

Conflict practitioners and scholars have been split on this issue for years. Although some suggest that many of our basic principles and practices of constructive conflict resolution (integrative negotiation, mediation, etc.) are largely universal (e.g., Bouge, 2006; Deutsch, 1985; Fry, 2006; Tjosvold, Johnson & Johnson, 2006), others take issue with this (e.g., Faure, 1985; Lederach, 1994; Sampson, 1993), arguing that our standard thinking and practice is Western-biased and appropriate methods will differ radically in other cultural settings.

The Gelfand study revealed that one major meta-difference between cultural groups is their level of tightness versus looseness. Tighter cultures have many strong norms and high sanctioning of deviant behavior around areas like family disputes, business negotiations, or being in conflict with elders. Looser cultures have weaker social norms and less sanctioning of those who don’t follow the norms. For example, Malaysia, Pakistan, India and South Korea were found to have generally tighter cultures, while Estonia, Hungary, Israel and the Netherlands were found to have looser cultures.

In addition, Gelfand and her colleagues have found that there may exist in any conflict setting certain amplifiers , suppressors and reversers which make cultural differences regarding disputing more and less relevant and influential. For instance, when situations are ambiguous, cultural symbols and artifacts are present, and there is high time pressure, cultural norms will have more impact on disputing. However, in situations of low social monitoring and accountability, the effects of cultural norms on conflict may be altogether absent.

These factors are likely to work together. So if a mediator is working with cultural groups who share tight norms around disputing – and in a situation where those norms are amplified – then yes, cultural differences will play a major role. If working in the reverse – with loose norms that are currently suppressed – culture will play much less of a role.

Categories: Blog, Culture and Conflict

Published October 4, 2011

July 2, 2014

Tightness and Looseness: A New Way to Understand Differences across the 50 United States

By Jesse Harrington & Michele Gelfand

E pluribus unum —“Out of many, one”—was the first official motto of the United States, adopted by the founding fathers and enshrined in the nation’s Great Seal in 1782. In its statement of unity, it exemplifies the differences inherent in the United States—a fitting description for a singular nation defined by innumerable internal divergence. Yet, few organizing principles exist to explain these differences, which find their expression in divergent ecologies, histories, average personality traits, and various state outcomes. Why, for instance, is the incidence of illicit substance use greater in states like Hawaii, Alaska, and New Hampshire relative to Mississippi, Ohio, and Oklahoma, but incidents of discrimination much higher in the latter than the former? Why do states like Colorado and Connecticut exhibit traits associated with greater impulsivity and greater tolerance, while other states, such as Alabama and Kansas, exhibit the opposite patterns? What might shed light on the difference in anti-immigrant attitudes between Arizona and New York, states with similarly large populations of illegal immigrants? In all, what does this seemingly diverse and wide array of state-level differences have in common?

Although the United States is often parsed on a red versus blue dichotomy, our lab suggested another framework by which to understand differences amongst the states in a paper published in the Proceedings of the National Academy of Sciences : states vary in terms of their tightness or looseness , which captures whether states have strong norms and little tolerance for deviance (tight) or weak norms and greater tolerance. As anyone who has traveled widely in the United States can attest, the range of behavior across states is incredibly diverse. Finding a singing cowboy playing the guitar in his underwear may indeed be a hard thing to find outside of New York City, for instance. In this study, we document not only how states vary in tightness-looseness, but why they vary—in large part based on the ecological and historical differences between the states.

The strategy of examining how cultures vary harkens back as far as Herodotus in his classic, Histories . More recently, Geert Hofstede greatly spurred these efforts with the publication of his book Culture’s Consequences , detailing the extent to which certain values (for instance, collectivism versus individualism) are endorsed across nations. More recently, we have broadened the toolkit even more and begun to study how cultures vary beyond values. For instance, we showed that cultures vary in the strength of social norms (i.e., tightness) across 33 nations and demonstrated that this cultural dimension is distinct from the various value dimensions proposed by Hofstede and others (e.g., the GLOBE research project ). Consistent with the idea that cultural differences often arise from differences in ecological and historical conditions, we found that tight countries have experienced a wide range of ecological and historical threats whereas loose countries experienced fewer. The strong norms that characterize tight nations help humans coordinate their social action in the face of numerous survival threats. Loose nations can ”afford” more latitude and permissiveness because they face far fewer natural and human made threats.

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In this study, we wanted to see whether tightness, and its predictors and outcomes, could be applied to the state level. We reasoned that while the U.S. is generally a loose culture, we might find that there is wide variation in tightness across the 50 states. For inspiration, we drew on Vandello and Cohen’s classic study which created an index of state level collectivism using archival data and we created a new index that measures the strength of norms and punishments across the states.

Check out the map of tightness to diagnose where your state is. Tighter states—those with stronger rules and greater punishment for deviance—are located primarily in the South and the Midwest, while looser states are located in the North East, the West Coast, and some of the Mountain States. We calculated state tightness with a composite index, compiling multiple variables. This includes items that reflect the strength of punishments in states, including the legality of corporal punishment in schools, the percentage of students hit/punished in schools, the rate of executions from 1976 to 2011, and the severity of punishment for violating laws, as well as the degree of permissiveness or deviance tolerance in states, which includes the ratio of dry to total counties per state and the legality of same-sex civil unions. The index also captures the strength of institutions that constrain behavior and enforce moral order in states, including state-level religiosity and the percentage of the total state population that is foreign, an indicator of diversity and cosmopolitanism.

Like our international study, our research on the 50 states shows that some striking similarities in why states vary in the strength of their social norms: Tight states have more threatening ecological conditions, including a higher incidence of natural disasters, poorer environmental health, greater disease prevalence, and fewer natural resources. Tight states were also found to have greater perceptions of external threat, reflected in the desire for more national defense spending and greater rates of military recruitment. This may have a historical basis, as states with a large amount of slave-owning families in 1860—those states that were “occupied” by the North and lost the backbone of their slave-based economy following the Civil War—are tighter. In all, we argue that ecological and historically based threats necessitate greater coordinated action to promote collective survival. One might use this construct to predict, for example, that states that increasingly have natural disasters, resource threats, or even terrorism threats might start to become tighter.

This study also helps to explain the vast differences we see in personality across the United States. Tighter states had a higher average of conscientiousness—a personality characteristic associated with lower impulsivity, greater self-control, orderliness, and conformity—relative to looser states. In contrast, looser states had greater average openness—a personality characteristic associated with non-traditional values and beliefs, tolerance toward difference, and cosmopolitanism. There are many other interesting differences between tight and loose states. Tight states have greater social organization (less instability and greater cohesion), better indicators of self-control (lower alcohol and illicit abuse), and lower rates of homelessness relative to loose states. However, they also exhibited higher incarceration rates, greater discrimination, lower creativity, and lower happiness, as compared to loose states. Tight and loose states each have their own advantages and disadvantages.

As you might expect, the map of state-level tightness-looseness approximates the electoral map of the past few decades, with states voting for conservative, Republican candidates falling on the tighter side and states voting for the more liberal, Democratic candidates falling on the looser side. Yet, conservatism and tightness are distinct, with tightness being a different and broader construct. Conservatism and liberalism are value systems that take the form of individual beliefs, while tightness and looseness describe an external social reality that exists independently of any one individual.

Our study is not without potential criticisms. First, it is important to note that our results are purely correlational, and accordingly, we can’t infer causation in the data. We have been using some other methods, including laboratory experiments and computer modeling, to strengthen the causal case that tightness is an adaptation to ecological and historical threats. Second, this study was only done in the context of the U.S. which is relatively loose, and in effect, allows for a lot of state variation. It remains to be seen whether other tight countries (e.g., Japan) have as much variation. S. Finally, we focused on the state level, but clearly there is also some interesting within-state variation that could be examined. For example, although Louisiana is a tight state, New Orleans may be a fairly loose city with a lot of behavioral flexibility. Likewise, although California is loose, it has pockets of tight counties. In our case, we were interested in broad, state level differences rather than specific localities. Other researchers may be interested in other levels of analysis to explore the construct.

In conclusion, E pluribus unum is an accurate descriptor of the United States. Out of many, seemingly disparate variables, it is important to seek a general, unifying principle to explain their concordance. We show that tightness may be one such candidate.

Michele Gelfand is a professor and distinguished university scholar teacher at the University of Maryland.

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I work in marketing, i love sports, culture, creativity and enjoy helping people. i am thankful for much of what life offers, and am getting better at dealing with the unexpected :-) this blog is a way to share some of my passions, reads and thoughts. don't hesitate to reach out to me, on this blog or social media., a new cultural construct: “tightness” & “looseness” of societies.

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People who are interested in cross-cultural behavior and cultural differences between countries ( like me ) will likely know Hofstede’s work , or the works of Edward T. Hall and Fons Trompenaars . I learned about them in business school, and absolutely loved to think about their frameworks, which are almost mainstream today. In the last years I also discovered the Shalom H. Schwartz , who created, ran, and still runs a very complete survey about the values that individuals from different countries have (achievement, hedonism, power, self-direction…). But recently, I discovered a relatively new cultural theory: the theory of cultural tightness and looseness .

The theory of cultural tightness–looseness looks at the strength of social norms and the degree of sanctioning within societies

The theory of cultural tightness and looseness says that there is contrast between the degree to which social entities are “tight” (have many strongly enforced rules and little tolerance for deviance) versus “loose” (have few strongly enforced rules and greater tolerance for deviance). It has been developped by Michele Gelfand , a Professor of Psychology at the University of Maryland. In the first article about the concept , which has been published in 2006, she and her colleagues explain their theory of cultural tightness–looseness (again: it’s about the strength of social norms and the degree of sanctioning within societies). But most of the attention came after a Science article ( pdf ), which came out in 2011.

Watch her explain it for her university:

Or watch her expain it on FOX News:

Click on the image to watch Michele Gelfand explain the tightness concept (source: FOX News)

I love how the reporter asks “ Why do a study like that? How does it help us? ” (01:30). I mean, she’s not wrong, why should we have another cultural construct and rate continents, countries, regions… along that concept? Her response is that it will help people understand how a society’s norms can be very different from one’s own, which is something different from knowing how individual values differ. People in Singapore and people have almost identical “indulgence” scores on the Hofstede dimensions (46 and 48 respectively, see here ), but Singapore – known as The Fine City – has a very high tightness score. I know that 🙂

A photo taken in Singapore in 2012

Beyond the initial papers that define the construct, the interesting papers are the following ones, which prove (or not) that looking at norms and the sanctioning of norms make sense. In academia, we say that researchers verify the concept’s “ ecological validity ” meaning that research seeks to prove a concept’s real-world relevance. So far, Gelfand and colleagues have tested the ecological validity of “tightness-looseness” in two studies, one at a global country level, and one at the USA State level.

On a global level, Gelfand has worked with 42 colleagues from across the world to gather data about the level of tightness across the globe. They asked people to approve or disapprove statements like “ There are many social norms that people are supposed to abide by in this country ” or “ In this country, if someone acts in an inappropriate way, others will strongly disapprove ” or “ People in this country almost always comply with social norms ,” and used the responses to calculate the countries’ tightness scores.

Image via akinokure.blogspot.com

The results, published in Science , indicate that cultures that are quite tight include places like Singapore, Japan, Pakistan, while loose societies include countries like New Zealand, the Netherlands, the United States. But beyond this, they proved – or at least strongly supported – the ecological validity of the concept by linking the level of tightness to socialization in societal institutions, the strength of everyday recurring situations, micro-level psychological affordances or ecological and historical threats.

For example, about the latter, they explain (I removed some correlation parentheses to make it easier to read): “ Tight nations [ relative to loose nations ] have a dearth of natural resources, including a lower percentage of farmland, higher food deprivation, lower food supply and production, lower protein and fat supply, less access to safewater, and lower air quality. Tight nations face more disasters such as floods, tropical cyclones, and droughts and have had more territorial threats fromtheir neighbors during the period 1918–2001. ”

The second study that looks to solidify the ecological validity of the tightness looseness construct appeared this week. It doesn’t look at tightness on the global level, but on the US national level. Together with a doctoral student, Jesse Harrington, Professor Gelfand just released a paper that will appear in a new issue of the Proceedings of the National Academy of Sciences and that develops a valid and reliable state-level tightness–looseness index, provides state rankings (see below), and shows how tightness is related to ecological and man-made threats, personality characteristics, and state-level outcomes.

Image via phys.org

Loose states, in green, are found primarily in the North East, the West Coast, and include some Mountain states, while tight states, in blue, are primarily in the South and parts of the Midwest of the United States. “ Our study shows there is a quantifiable principle that can account for a large swath of state differences in ecological and human-made conditions, personality characteristics, and various state outcomes, ” said Gelfand as reported on Phys.org . “ Tight states tend to be more socially stable, orderly and exhibit more personal self-control—yet tightness is also linked to higher incarceration rates, greater discrimination, lower creativity, and lower happiness, ” Harrington added.

Tight states tend to be more socially stable, orderly and exhibit more personal self-control—yet tightness is also linked to higher incarceration rates, greater discrimination, lower creativity, and lower happiness

Gelfand and Harrington hope that their new research on tightness and looseness will ultimately inform national conversations and policy decisions on critical topics. “ A better understanding of the cultural variation across the 50 states is critical to improving communication, cooperation, and progress when it comes to making decisions that affect our nation, ” Gelfand said. “ The challenges we face as a nation require cooperation if we want real change. This research might help us understand why we differ and to help us to develop common ground. ”

Tightness = lots of signs like these (image via psychology.umd.edu)

Whill policy makers in the US and beyond, or even companies, will use this research in the future? It will probably take time for the construct of tightness and looseness to become mainstream, as the coverage still comes from papers and specialized scientific blogs. I guess is will then spill over to be taught in business school and relayed by consultants.

But the early academic publications are setting very solid foundations for the construct , making it a very viable approach to look at cross-cultural matters through a society’s social norms, rather than through its individuals’ values. I’m looking forward to reading more about this stream of research, which will certainly develop in the next years.

Loose vs. tight societies (Discover Magazine, by Razib Khan)

Is Your Culture ‘Tight’ or ‘Loose’? The Answer Could Explain Everything

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By Neil Gross

Sept. 14, 2018

RULE MAKERS, RULE BREAKERS How Tight and Loose Cultures Wire Our World By Michele Gelfand 376 pp. Scribner. $28.

There is a longstanding debate among social scientists about what ultimately drives human behavior. Do ideals, symbols and beliefs lead people to act as they do? Or are the wellsprings of action and the drivers of history less ethereal: money, fear, the thirst for power, circumstance and opportunity, with culture as an afterthought?

Scholars in the first camp are culturalists; in the second, materialists. And the disagreement between them is not merely academic. It spills over into heated policy debates about crime, poverty, immigration, economic development and everything in between.

In “Rule Makers, Rule Breakers,” the psychologist Michele Gelfand sides with the culturalists. “Culture is a stubborn mystery of our experience and one of the last uncharted frontiers,” she writes. Her aim isn’t to guide readers through all the complex elements that make up a culture, but to draw attention to one aspect she believes has been ignored: the social norms — or the often informal rules of conduct, the dos and don’ts, the sources of tsking and raised eyebrows — that emerge whenever people band together.

According to Gelfand, cultures can be located along a continuum from “tight” to “loose” depending on the strictness of these rules. “Tight cultures,” she observes, “have strong social norms and little tolerance for deviance, while loose cultures have weak social norms and are highly permissive.” Think of the difference between a gathering for buttoned-up middle-aged churchgoers and a party for 20-somethings in Bushwick, Brooklyn.

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Please note you do not have access to teaching notes, how does cultural tightness-looseness affect attitudes toward a local vs foreign brand transgression.

International Marketing Review

ISSN : 0265-1335

Article publication date: 25 September 2023

Issue publication date: 12 December 2023

This study aims to examine how cultural tightness at the national level and individual level influences consumer attitudes toward a brand's wrongdoing depending on the brand's country of origin and severity of the transgression.

Design/methodology/approach

Employing data from two tight-culture countries (China and South Korea) and a loose-culture country (the USA), two experiments were conducted to examine the proposed hypotheses.

The authors found that although consumers across cultures universally punish strong (vs weak) transgressions more severely, consumers in a tight-culture country, China, are more forgiving of a local (vs foreign) brand in both strong and weak transgression conditions, and forgiveness is higher for the strong transgression. Moreover, this buffering effect observed for Chinese consumers is stronger for those with high personal cultural tightness in the strong transgression condition. However, it emerges only in the weak transgression condition for South Korea, another tight-culture country. As hypothesized, no buffering effect for a local brand was found in a loose-culture country, the USA. Consumers from a loose culture assess transgression severity independently, and the punishment is harsher for strong transgressions than for weak transgressions.

Originality/value

This study fills a research gap by revealing that consumers from tight (vs loose) cultures would react differently to brands following a transgression depending on the brand's country of origin. It provides implications by examining how national-level and individual-level cultural tightness jointly affect post-transgression attitudes. It also presents a more nuanced perspective that the local brand's buffering effect is contingent on the degree of tightness and severity of transgression, even in similar culturally tight countries.

Brand transgression
Cultural tightness and looseness
Local brand
Foreign brand
Buffering effect

Acknowledgements

The authors would like to thank the IMR Associate Editor for suggesting the cognitive dissonance theory in the development of hypotheses, which was very helpful in improving this research. The first author gratefully acknowledged funding from China Scholarship Council (No: 202006140176).

Ge, J. , Jo, M.-S. and Sarigollu, E. (2023), "How does cultural tightness-looseness affect attitudes toward a local vs foreign brand transgression?", International Marketing Review , Vol. 40 No. 6, pp. 1456-1479. https://doi.org/10.1108/IMR-06-2022-0151

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Differences Between Tight and Loose Cultures: A 33-Nation Study
Abstract. With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ...
PDF On the Nature and Importance of Cultural Tightness-Looseness
Most (if not all) of the CAHRS Working Papers are available for reading at the Catherwood Library. For information on what's available link to the Cornell Library Catalog: ... On the Nature and Importance of Cultural Tightness-Looseness CAHRS WP07-05 Page 8 of 57 require rigid norms to foster the coordination necessary to produce crops for ...
Tight and Loose Cultures: A Conversation with Michele Gelfand
Michele Gelfand is Professor of Psychology at the University of Maryland and author of an eye-opening new book on the role that culture—and specifically how strictly different cultures enforce norms—plays in our lives. The book, Rule Makers Rule Breakers: How Tight and Loose Cultures Wire Our World explains how Gelfand's research over the ...
PDF On the Nature and Importance of Cultural Tightness-Looseness
aliban)—a poi. t to which we return later in the discussion.Proposition 1A. Tightness-looseness consists of the strength of social norms (number and clarity) and th. strength of sa. ctioning (tolerance for deviance from norms).Proposition 1B. Tightness-looseness is distinct from individuali.
The relationship between cultural tightness-looseness and COVID-19
Here we predict that cultural tightness-looseness will explain variation in cases and deaths during COVID-19. Beyond advancing theory on how social norms help societies respond to collective threat, this research holds important practical implications that might help societies deal with later waves of COVID-19 and future threats more generally.
PDF Differences between Tight and Loose Cultures: A 33-Nation Study
insight into how tightness-looseness operates in modern nations. The goal of this research is to fill this void. Drawing on theorizing in cultural psychology (5, 6), we propose that tightness-looseness is part of a complex, loosely integrated system that involves processes across multiple levels of analysis (Fig. 1). We
On the nature and importance of cultural tightness-looseness
Abstract. Cross-cultural research is dominated by the use of values despite their mixed empirical support and their limited theoretical scope. This article expands the dominant paradigm in cross-cultural research by developing a theory of cultural tightness-looseness (the strength of social norms and the degree of sanctioning within societies ...
Across-Time Change and Variation in Cultural Tightness-Looseness
Cultural tightness-looseness, a dimension which describes the strength, multitude, and clarity of social norms in a culture, has proved significant in explaining differences between cultures. Although several studies have compared different cultures on this domain, this study is the first that targets both within-country differences and across-time variation in tightness-looseness. Using data ...
PDF The relationship between cultural tightnessâ€"looseness and COVID-19
57 countries for which tightness data are available. The data were downloaded on Oct 16, 2020, and are available online. Cultural tightness-looseness. To assess cultural tightness-looseness, we used a previously published measure. 2. that averages six items, including, for example, "There are many social norms
The cultural dimension of tightness-looseness: An analysis of
The importance of tightness-looseness as a dimension that explains a considerable amount of variance between cultures was demonstrated by Gelfand et al. (2011). Tight nations have many strong norms and a low tolerance of deviant behaviour, whereas loose nations have weak social norms and a high tolerance of deviant behaviour.
On the nature and importance of cultural tightness-looseness
This article expands the dominant paradigm in cross-cultural research by developing a theory of cultural tightness-looseness (the strength of social norms and the degree of sanctioning within societies) and by advancing a multilevel research agenda for future research. Cross-cultural research is dominated by the use of values despite their mixed empirical support and their limited theoretical ...
Cultural tightness-looseness and national innovativeness: impacts of
Secondly, Hypothesis 1.2—looseness as measured via the cultural tightness-looseness combination index of Uz has a positive relation to national innovativeness—is supported by our empirical findings: as can be drawn from Table 3, there is a positive, statistically significant impact of the cultural tightness-looseness on national ...
Tightness and Looseness: When Culture Does and Does Not Matter in
It depends on how tight the culture is around disputes. ... The Gelfand study revealed that one major meta-difference between cultural groups is their level of tightness versus looseness. Tighter cultures have many strong norms and high sanctioning of deviant behavior around areas like family disputes, business negotiations, or being in ...
Tightness and Looseness: A New Way to Understand Differences across the
For instance, we showed that cultures vary in the strength of social norms (i.e., tightness) across 33 nations and demonstrated that this cultural dimension is distinct from the various value ...
Being a tough person in a tight world: Cultural tightness leads to a
Research on cultural tightness-looseness developed in parallel with psychological research on dominance and power, as two separate fields. To the best of our knowledge, the present research is the first to examine people's own power motivation in the context of cultural tightness-looseness. 7.1. Limitations and future avenues
Universal and culture-specific patterns of tightness-looseness ...
The study by Chua et al. is the first of its kind to investigate cultural variation in the strength of social norms, or tightness-looseness (TL), across the 31 Chinese provinces.Research has illuminated important differences in cultures that are tight (i.e., those that have strict rules and punishments for deviance) from cultures that are loose (i.e., those that have weaker rules and are more ...
Cultural tightness-looseness: Ecological affordances and implications
The nexus between culture and personality has long been an interest among scholars and researchers throughout history and across multiple disciplines. Traditionally, echoing its dominance in the broader field of culture and psychology, research has focused on the link between personality and cultural values. In this chapter, we complement this research and expand it to focus on the nexus ...
A New Cultural Construct: "Tightness" & "Looseness" of Societies
The theory of cultural tightness-looseness looks at the strength of social norms and the degree of sanctioning within societies. The theory of cultural tightness and looseness says that there is contrast between the degree to which social entities are "tight" (have many strongly enforced rules and little tolerance for deviance) versus ...
Is Your Culture 'Tight' or 'Loose'? The ...
Gelfand's thesis is that mapping the tightness or looseness of the cultures of various groups — nations, regions, social classes, companies, friendship circles — helps explain things that ...
PDF The influence of uncertainty and cultural tightness- looseness on the
The main purpose of this study is to give more insights in the influence of culture and uncertainty on the decision-making process of entrepreneurs. Literature indicates a possible effect of cultural tightness and personal uncertainty on the decision-making process of an entrepreneur. An entrepreneur who experiences the culture as tight may ...
On the Nature and Importance of Cultural Tightness-Looseness
Abstract. Cross-cultural research is dominated by the use of values despite their mixed empirical. support and their limited theoretical scope. This article expands the dominant paradigm in cross ...
How does cultural tightness-looseness affect attitudes toward a local
This study aims to examine how cultural tightness at the national level and individual level influences consumer attitudes toward a brand's wrongdoing depending on the brand's country of origin and severity of the transgression.,Employing data from two tight-culture countries (China and South Korea) and a loose-culture country (the USA), two ...
(PDF) Cultural tightness-looseness: Its nature and missiological
Cultural tightness appears to be a reaction to strong environmental threats to a people's. health and physical safety, such as war, isolation, susceptibility to natural disasters, and disease ...

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Across-Time Change and Variation in Cultural Tightness-Looseness

The importance of studying across-time variation in tightness-looseness

From a cross-cultural perspective to an examination of within-country variation

Aims of the present study

Participants

Tightness-Looseness Scale (TLS).

Preliminary data analysis

Measurement invariance.

Across-time change and within-country variance in tightness scores

Across-time change in single-item responses.

Across-time change in tightness-looseness

Within country-differences in tightness-looseness

Supporting Information

S1 Text. Reliability and validity of the Tightness-Looseness Scale.

S1 Table. Inter-item correlations between the items of the Tightness-Looseness Scale.

S2 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between ESCP2002 and ESS2012 data.

S3 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between different subgroups in the ESCP2002 data.

S4 Table. Results of measurement invariance tests of the Tightness-Looseness Scale between different subgroups in the ESS2012 data.

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On the nature and importance of cultural tightness-looseness.

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Cultural tightness–looseness and national innovativeness: impacts of tolerance and diversity of opinion

Introduction

Literature review

Cultural factors—the tightness–looseness concept

Operationalization of cultural tightness–looseness

Data and methodology

Appendix 1: Summary statistics

Data Gelfand

Appendix 2: List of countries Gelfand et al.

Appendix 3: List of countries Uz

Appendix 4: Data for index construction by Uz

Availability of data and materials

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Is Your Culture ‘Tight’ or ‘Loose’? The Answer Could Explain Everything

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