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Amsterdam Business School
Master Thesis
Cultural differences in the perception of time
“God gave the African time and the Westerner a watch”
MSc Business Studies – International Management
Student Patrick Hervé Voskuilen
Student Number 10455191
Supervisor Dr. Wendelien van Eerde
Second Reader Dr. Johan Lindeque
Date 22 January 2014
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Abstract
As a result of the current trend of globalization, cultural differences have become an important factor in international management. However, little is known about its relation to time perception, which is recognized as an important feature in both people’s lives as well as businesses. This study elaborates on this gap by developing a theoretical foundation on these subjects and extending it with a quantitative research that measures the effect of cultural differences on perception of time, with punctuality in particular. The sample consisted of 78 South African and 86 Dutch respondents. Within this sample, cultural differences and attitudes towards punctuality and lateness were measured. The findings show a small cultural difference between both countries. No significant differences were found with regard to time perception. Altogether, this study contributes to current literature by providing some evidence for a relationship between cultural differences in time perception.
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1 Table of Contents
2 Introduction ... 4
3 Literature review ... 8
3.1 Culture and firm performance ... 9
3.2 Cultural differences ... 12 3.3 Time perception ... 14 3.3.1 Punctuality ... 18 3.3.2 Lateness ... 19 3.4 Conceptual model ... 23 3.4.1 Model ... 23 3.4.2 Hypotheses ... 23 4 Method ... 24 4.1 Research method ... 24 4.2 Data collection ... 24 4.3 Measures ... 26 4.4 Data analysis ... 29 5 Results ... 31 6 Discussion ... 40 6.1 Findings... 40 6.2 Limitations ... 44 6.3 Future research ... 44 7 Conclusion ... 46 8 References ... 47 9 Appendix ... 50 9.1 Calculations - VSM 94 ... 50
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2 Introduction
In today’s globalizing world, international management is becoming more and more important. Many organizations decided to shift various activities to foreign countries to increase efficiency and effectiveness. Boundaries are slowly disappearing and a global world is emerging. The global economy and international business ventures have brought many occasions for the development of interpersonal relationships among people who were socialized into different cultures (Brislin and Kim, 2003). According to Arman & Adair (2012), these increasing cultural differences have become an important characteristic of the workforce.
I became fascinated with cultural diversity while I was living in South Africa. South Africa is a country that has to deal with many cultural differences due to the large number of ethnic groups. As a result of the former Apartheid regime, South Africa still experiences difficulties in managing this cultural diversity. Soon after my arrival in South Africa, I was introduced to the TIA principle, meaning: ‘This is Africa’. It is a saying that stresses the stereotypes among African countries. One of these stereotypes is a lack of punctuality. It is a common occurrence in Africa that someone can set up a meeting and show up late, if at all. I noticed that his stereotype is in contrast with how many Western cultures deal with punctuality. In line with this personal realization, Brislin and Kim (2003) argue that time can be a good entry point into people’s thinking about their cross-cultural preparation.
Not only Brislin and Kim (2003) address the importance of cultural differences in relation to time. Güss & Dörner (2011) mention the key role of different cultural perceptions of time in their research on complex problem solving (CPS) and dynamic decision making (DDM). Furthermore Levine, West, & Reis, (1980, p. 550) noticed almost thirty years ago that ‘A clearer picture of divergent conceptions of time is needed to avoid the counterproductive intercultural misunderstandings that presently arise’. Lastly Saunders, Van Slyke, & Vogel (2004) elaborate on several management challenges and opportunities. They state that cultural time and its
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consequences must be considered among managers to create a successful Global Virtual Team (GVT).
Notwithstanding the importance of cultural differences in relation to time, research in this field is relatively scarce. White, Valk, & Dialm (2011) also mentioned this gap by stating that the number of empirical studies of punctuality is astonishingly meager and that only two studies address punctuality within a cross-cultural context. However, some scholars conducted a study in which some temporal and cultural dimensions were measured. Macduff (2006) studied the relation between culture, time and negotiations while both Saunders et al. (2004) and Arman and Adair (2012) investigated time in relation to cultural differences in teams.
Kirkman, Lowe and Gibson (2006) on the other hand, maintained a broader and more general scope of cultural differences. They created a summary of existing research about Hofstede’s cultural dimensions and emphasized the need for more focus on research across countries.
The goal of this research is to bridge the gaps within the research of time-related cultural differences, by analyzing the effect of cross-cultural differences on the perception of time. The research of White et al. (2011) on the sociocultural nature of punctuality will be used as foundation and will be tested within two countries. This study responds to the recommendations of Kirkman et al. (2006) by conducting a research in which the effect of cultural differences on time perception is measured across two countries, namely the Netherlands and South Africa.
The Netherlands and South Africa are particularly different countries in terms of geography (both different continents), economy (the Netherlands is a developed country while South Africa is an emerging country) and culture. With respect to culture, Hofstede calculated the cultural differences between both countries, which are displayed in Figure 1. This picture shows that South Africa and the Netherlands differ in terms of power distance, individualism, masculinity and uncertainty avoidance.
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Figure 1: Cultural difference South Africa – the Netherlands (geert-hofstede.com)
However, in spite of these differences, the history of both countries is partially interrelated. In the 17th century the Dutch settled in South Africa to establish a supply-station where the ships that travelled to Dutch East India could resupply and rest. Later on, other European countries followed. The Dutch descendants (Afrikaners or Boers) got dominated by the British. The Afrikaners migrated to the inland provinces and build their own colonies like Transvaal. Soon, the British discovered diamonds in these areas, which resulted in a period of uneasy power sharing including the Boer War. Eventually the Afrikaners party (ANP) gained strong majority. They introduced the Apartheid, a system invented to gain control over South Africa’s economic and social system by maintaining white domination while extending racial segregation. An act was developed that required a national classification system in which all South Africans were classified in white, black (African), colored or Indian/Asian. After many decades of inequality, the Apartheid ended in the early 1990s through internal and external
pressure (Chokshi, M., Carter, C., Gupta, D., Martin, T. & Allen, R., 1995). According to the
mid-year population estimates from Statistics South Africa (2013) the current South African population consists of 52.982.000 people from which 79.9 percent is black, 8.7 percent is white, 9.0 percent is colored and 2.5 percent is Indian/Asian.
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The measurements of the Dutch Central Agency for Statistics (CBS) indicated that in 2013, 16.779.575 were living in the Netherlands from which 79 percent is Dutch, 9 percent Western, 2 percent Moroccan, 1 percent Dutch Antillean, 2 percent Surinamese, 2 percent Turkish and the remaining 4 percent other non-Western people.
Altogether, my affinity with both the Netherlands and South Africa and, more importantly, the contrast of these two culturally diverse countries with a joint history, yields an interesting case to address the literature gaps mentioned before. The lack of research in the field and the important role of cultural differences in relation to time perception make this research interesting and a valuable addition to current research.
The following research question was developed.
What is the effect of cross-cultural differences on time perception?
First, this question will be interpreted in its broadest sense. Later on, this research will particularly focus on three cultural dimensions and its relation on punctuality and lateness. The Netherlands and South Africa are the countries that will form the base of the research.
This thesis is structured as follows. The first section includes a literature review based on desk research. Within this literature review, a brief introduction will be given about the current trend in the internationalization of businesses followed by an overview of the literature on culture and time perception. Furthermore, some hypotheses will be developed and displayed in a conceptual framework. Next, the method section will elaborate on the research method, data collection, measures and data analysis. Following on the method section, the results of the hypothesis testing will be presented. A final section remarks on some points of discussion, where the results will be discussed and compared to the existing literature, some gaps in this research will be defined and some suggestions for future research will be given. Finally a summary of the research will be provided.
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3 Literature review
According to Dunning (1998), the last decades witnessed a gradual movement towards a world economy. He identified three main drivers for this movement. The first driver is the growing importance of intangible assets and the need to exploit these to other markets. Kirca et al. (2011) also mention this driver as one of the two interdependent propositions of internalization theory. They argue that organizations internalize markets up to the point at which the benefits of further internalization exceed or are equal to the costs (Kirca et al., 2011). The other proposition they emphasize on is choosing cost-effective foreign locations for MNE activities.
Another driver of the shifts towards a world economy is the developments in technology, communication, transport and reduction of investment barriers (Dunning, 1998). Lastly Dunning (1998) emphasizes the fact that intra-firm relationships with and between stakeholders are emerging.
With respect to the drivers of globalization, many scholars studied the relationship between global diversification and performance of Multinational Enterprises (MNEs). Gomez-Mejia and Palich (1997) state that the more globally diversified companies are, the better they perform. However, Lu and Beamish (2004) on the other hand argue that high geographical diversification is related to a decrease in firm performance. This negative relationship is caused by transaction- and coordination costs associated with increased multinationality. Despite of the advantages of greater international expansion like learning, reduced liability of foreignness and exploitation of assets, the firm’s more extensive international network will lead to higher costs.
Whether global diversification has a positive or negative outcome on performance depends on the firms’ absorptive capacity and its tangible and intangible assets in generating benefits of internationalization (Chang and Rhee, 2011). These intangible assets, including proprietary relationships and knowledge, are not easily exchangeable and often embedded in culture (Greco, Cricelli and Grimaldi, 2013; Kirca et al., 2011). This makes culture a valuable element in determining the outcome of global diversification.
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3.1 Culture and firm performance
It is hard to find an overarching definition of culture within the current literature due to a lack of consensus. During the years, many definitions of culture have been suggested. However, according to Tayeb (1994), culture is often defined as some combination of norms, values, feelings, thinking, roles, rules, behavior, beliefs, attitudes expectations, meanings and so on. Geert Hofstede, one of the most famous researchers who studied this topic, defined culture as ‘the collective programming of the mind which distinguishes the members of one human group from another’ (Hofstede, 1980a , in Kirkman, Lowe, & Gibson, 2006, p.286).
With regard to Reinecke, Nguyen, Bernstein, Näf and Gajos (2012), culture influences and is influenced by several factors. First cultural influences stem from factors like language, religion, education, social and political norms and values. These factors determine the design of a culture. On the other hand, many studies suggest that people’s thinking, behavior and preferences are formed by culture (Reinecke et al., 2012).
Within the broad concept of culture, different hierarchies are identified. Some studies distinguish between existing cultures across various levels of society. According to Pizam, (1993), in Chen, Cheung and Law, (2012) culture exists at national levels, at industrial levels, occupational levels, corporate levels and organizational levels In the current research, the main distinction is made between national cultures and organizational cultures. Lau and Ngo (1996) explain organizational culture as a construct that is made up of a common understanding and things that are shared between organizational members.
Schneider (1988) further elaborates on the difference between those two types of cultures by introducing the model of Schein (1985) that argues that culture is represented at three levels. The first level consists of behavior and artifacts. Norms and values cover the second level. The third level includes underlying assumptions. Behavior and artifacts are relatively easy to observe in contrast to underlying assumptions, which are harder to detect. Schneider (1988) argues that the first two levels may be modified by organizational culture, which means that organizational cultures can be created, maintained or changed by organizations itself. National cultures on the
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other hand consist mostly of underlying assumptions. Hereby the interrelatedness between corporate- and national culture appears. The country’s national culture plays a major role in the development of an organizational culture (Lau and Ngo, 1996). Due to the fundamental role of the national culture in the development of other cultures, this research will focus on national cultures. However, when comparisons are made between national cultures, the risk of stereotyping all individuals within a country comes in. To deal with this risk, subcultures have to be taken into account (Kirkman et al., 2006).
Kekäle, Fecikova and Kitaigorodskaia (2004) investigated subcultures within organizations. Just like national cultures, organizational cultures do not appear to be homogeneous. The existence of subcultures rises in proportion to physical size, specialization and departmentalization. The bigger the population, the more isolated the groups within this population will be. This also counts for their viewpoints. According to Kekäle et al. (2004) subcultures can be described by sets of features characteristic of them (p. 1096). These features can include education, sharing specific background, association with the community, personality, gender and age.
It is important for MNEs to obtain knowledge about possible subcultural differences within the country they operate in. This way, managers do not naturally assume that all stakeholders from a particular country respond to for example conflicts in the same manner (Kozan, 2002).
Despite of the many definitions of culture, culture can play a crucial role within the organizations policies, both internally as well as externally. With respect to the external part, cultural diversity between national cultures comes in. Gomez-Mejia and Palich (1997) focus on the impact of this cultural diversity on the performance of MNEs. Cultural diversity is defined as “the representation, in one social system, of people with distinctly different group affiliations of cultural significance” (Cox, 1993, in Kulkarni, 2012).
Cultural diversity can influence the performance of an organization in different ways. First of all, it can impact the transfer of technical know-how and general management expertise.
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Besides this transfer of essential knowledge, the effectiveness of technology implementation may also be influenced. Furthermore, Gomez-Mejia and Palich (1997) argue that cultural barriers like cultural diversity may hinder the development and transfer of organizational innovations from one unit to another unit within the global firm. Different preferences and languages but also different norms and values may foster these problems. Innovation needs an ambiance of flexibility with rules and routines; otherwise the creation of new innovations will be impeded.
Additionally, other departments within the organization can be influences by cultural differences. Marketing has to deal with differences in consumer preferences that result from cultural diversity. To reach the desired product demand, the marketing mix has to be adapted to the country’s culture (Gomez-Mejia and Palich, 1997). Besides the influence of cultural diversity on customers, it has also implications for people within the firm. First of all the management, Gomez-Mejia and Palich (1997) argue that the more different cultures are, the more difficult it is to effectively supervise the various subsidiaries. Within this headquarter-subsidiary relationship, it will be harder and more expensive to obtain accurate and complete information about the agencies due to greater complexity. This complexity is created through difficulties related to for instance interpersonal dynamics. These interpersonal dynamics can be heterogeneous perceptions and unclear communication among individuals within all divisions of the multinational (Gomez-Mejia and Palich, 1997). Finally, Gomez-(Gomez-Mejia and Palich (1997) elaborate on the influence of this cultural heterogeneity on Human Resources. Human Resource best practices need to be tailored to specific cultures with respect to areas as compensation and rewards, performance appraisal, staffing, and labor relations. This will lead to higher costs and many pitfalls and the associated risks.
Hutzschenreuter, Kleindienst and Lange (2013) argue that the degree of MNE awareness of these inter-country differences can determine the effect on firm performance. Culture, may have a significant influence on the performance levels of MNEs which makes cultural differences an important factor to consider.
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3.2 Cultural differences
Cultural differences express the extent to which cultures differ from one another on several dimensions. Cultural differences can be described using the four dimensional Cultural-, Administrative-, Geographical- and Economical distance (CAGE) framework from Ghemawat (2001). This framework gives an indication of the overall distance between countries. Administrative distance is measured by the number of political and historical association shared by the countries like colonial ties and legal systems. Geographical distance includes the physical size of the country, average within-country distances to borders, access to infrastructure like waterways and oceans and lastly topography (Ghemawat, 2001). The wealth and richness of countries is related to economical distance. The quantity and costs of human resources, financial resources and other resources like the availability natural resources, determine the economic position of a country. The fourth dimension is cultural distance, which can be explained as a country’s cultural attributes like language or social norms, determine how people interact with one another and with companies and institutions. Ghemawat (2001) argues that these cultural attributes often create distance by influencing the choices that consumers make between substitute products because of their preferences for specific features. This theory is not only applicable to consumers but on all social interactions within and outside the company.
There are many scientists who researched the impact of differences in culture. Kogut and Singh (1988) developed a formula to measure the cultural distance dimension by calculating the difference on culture between a particular home country and various host countries. Their theory is based on Hofstede’s four dimensions. Hofstede developed a framework of four different cultural dimensions; he extended this framework with a fifth dimension a few years later (Hofstede, 1980a , in Kirkman, Lowe, & Gibson, 2006). The first dimension is individualism. Individualism points out the strength of the ties people have to other people in the community. It can be characterized by universalism; self-interest and the ‘I’ focus. Collectivism on the other hand, is the opposite variant in which people are integrated particular tight, loyal in-groups,
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illustrated by ‘we’. The second dimension measured is power distance. The dimension describes to what extent inequality in power distribution is accepted. Masculinity is the third dimension, which refers to the distribution of the traditional male and female roles in societies. Male roles are considered to be assertive, competitive and strong. Female roles, in contrast, are more focused on solidarity, negotiation and intuition. Uncertainty avoidance, the fourth dimension, makes a distinction between the level people avoid uncomfortable and unstructured situations. Features of uncertainty avoiding cultures are strict laws and rules, safety and believe in an absolute truth. Cultures who accept uncertainties are characterized by, tolerance, little rules and no structure. Finally the fifth dimension is long-term versus short-term orientation, whereas long-term is future oriented and can be expressed through thrift and perseverance. Short-term orientation on the other hand, is focused on the past and present.
Reinecke, Nguyen, Bernstein, Näf and Gajos (2012) conducted a study in which they found that (national) culture determines the way events are scheduled online. Whereas Reinecke et al. (2012) focused mainly on individualism, this study extends that focus by investigating three dimensions of Hofstede; individualism, power distance and uncertainty avoidance. The dimensions masculinity and long-term orientation are disregarded since they do not say much about punctuality.
First, a test was established to determine whether Hofstede’s work on cultural differences could be replicated in 2013. The main starting point of this study is the expectation that South Africa and the Netherlands differ in terms of cultural dimensions. With respect to the first dimension, Reinecke et al. (2012) found that the Netherlands are more individualist than South Africa. This leads to the first hypothesis:
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Furthermore, previous research shows that the Netherlands score lower on power distance and higher on uncertainty avoidance compared to South Africa, resulting in the following hypotheses:
H2: South Africa scores higher on power distance compared to the Netherlands H3: South Africa scores lower on uncertainty avoidance compared to the Netherlands
Cultural differences are an important factor to consider within (international) organizations. Although there may be some universality among organizational structures that are required around the world, these differing national cultures in which organizations are located, frequently give those structures substantially different meanings (Smith, 1992). Moreover differing national cultures can play a major role in organizational processes like choosing entry modes (Kogut and Singh, 1988), transfer of knowledge (Gomez-Meija and Palich, 1997) and the acceptance and implementation of human resource practices (Gomez-Meija and Palich, 1997; Schneider, 1988). However, not much attention is paid to the influence on an essential feature of social and organizational life, time. Plans, performance, productivity and pay are all strongly related and often measured by time (Whipp, Adam and Sabelis, 2002).
In the following, the concept of time perception and its link to cultural differences will be examined.
3.3 Time perception
How cultures differ in their perception of time is still a relatively unknown field of research. This is demonstrated by the relatively incomplete and dispersed character of current research. Yet, there is some research that provides relevant theory for this study.
To explain time perception, the general concept of time use in needs further explanation. Levine (2013) wrote a report in which he elaborates on the relation between time use and happiness. Levine stresses value of time in general by arguing that ‘our lives are lived in time’ (Levine, 2013). Time use determines physical, social, psychological and economic wellbeing. Temporal beliefs and behaviors are expressed in our culture, geography, climate, religion, social class, educational level and political and economic stability of our surroundings (Levine, 2013).
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This study will further examine this relationship between time use and how it is mirrored in culture. Levine (2013) ends his report to the United Nations with several recommendations in which he states that when policies are crafted, attention must be paid to culturally sensitive temporal dimensions. He supports this statement by giving an example of varying attitudes towards working on a schedule across cultures. This view is shared by Mangaliso (2001), who highlights the relationship between culture and time. He argues that differences in attitudes towards time often present a problem when people conduct business across cultures.
Brislin and Kim (2003) studied intercultural interactions in relation to time. They developed a list of ten issues that provides a good starting point for understanding cultural approaches involving time. The first concept of time that they introduce is clock and event time. Clock time characterizes people that are careful about time. Event time on the other hand, focusses on organizing days around various events/activities. Once you participate in an event, you can only start with a new event once the first event is finished.
Strongly related to clock time is the second concept: punctuality, which will be discussed in greater detail later on. The third concept is task and social time during the workday, which focuses on what percent of time, is spent on social activities and what on task/job related activities. The fourth issue is polychronic and monochronic time use. Polychronic time use refers to a more loosely way of scheduling life that is characterized by a strong focus on event time and the ability of performing different activities at the same time. Contrary to cultures that use polychronic time, are monochronic cultures. These cultures expect punctuality and prefer doing one activity at one time (Brislin and Kim, 2003; Reinecke et al. 2012).
How work and leisure time are balanced is the fifth issue described by Brislin and Kim (2003). Sixth is a fast or slow pace of life. Levine and Norenzayan (1999) researched this pace of life in 31 countries. They found that the pace of life was fastest in Japan and the countries of Western Europe and slowest in economically undeveloped countries. They argue that the predictors:
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colder climates, economically productive countries and individualistic cultures have a significant faster pace of life and are thus related to time perception.
Dealing with long periods of silence is the seventh concept. Cultures differ in the way they experience silence, some cultures think is comfortable, and some find it frustrating. The eighth concept deals with past, present and future orientation. Ninth, time can be perceived as a symbol, like time is money but also time is status. The last concept of time is time efficiency.
Time is an extremely complex concept that is associated with several time visions (Saunders et al., 2004). These so-called time visions differ across countries, and in terms of geography: longitudinally (Western vs. Eastern) and latitudinally (northern vs. southern cultures). The first two time visions mentioned by Saunders et al. (2004) correspond with the investigation of Brislin and Kim (2003). The clock time vision views time as a scarce commodity that can be lost, spent or wasted. This vision is often held by American, Anglo-Saxon, Germanic and Scandinavian countries (Brislin and Kim 2003; Saunders et al. 2004). An event time vision is the opposite of the clock time vision by perceiving time as something cyclical, continuous (holistic) and epochal (Saunders et al., 2004). Since there is an unlimited supply of time, wasting time is not a concern. In this vision, time is consistent with the Japanese long-term holistic view and their predilection for tradition and rituals.
According to Saunders et al. (2004), the third time vision is called timeless. This vision exists mainly in Buddhist and Hindu regions and is characterized by the fact that they perceive time to be insignificant. Quick decisions are avoided since opportunities, risks and dangers eventually reappear over time. This way creativity is stimulated.
The final vision of time is called the harmonic vision that is promoted by Confucianism and Taoism. This vision seeks temporary harmony within the person, among individuals and between society and nature (Saunders et al. 2004).
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Saunders et al. (2004) argue, “These time visions of all individuals are shaped by the society in which they live and refined by the organizations in which they work” (p. 22). This argument demonstrates the influence of cultural differences on the vision of time.
Within the broad concept of time, this research will highlight punctuality aspect. Punctuality and lateness may be considered as the complement of each other. They may have both economic as well as psychological implications for an organization. Punctuality and lateness can influence the quantity and quality of the services and products produced in the organization (Koslowsky, 2000). According to the existing literature, punctuality and lateness can both be linked to culture and personality. The relation between personality and punctuality is investigated by Back, Schmukle and Egloff (2006). They measure the relationship between three behavioral indicators of punctuality (time of arrival, earliness and lateness) and the Big Five personality factors. They focus on the factors conscientiousness, agreeableness and neuroticism. A high level of conscientiousness (actively managing goals, being organized, dependable, dutiful, orderly, self-confident, self-disciplined and deliberate) turned out to be related to all punctuality indicators. Agreeableness, that determined both time of arrival and earliness, can be characterized as straightforward, altruistic, cooperative, courtesy, compliance, modesty and tender-mindedness. The third personality factor, neuroticism, correlated with earliness and is characterized by very sensitive to stress, anxious, depressive, self-unsure, impulsive, vulnerable, nervous and irritable.
Another personality characteristic is explained by Koslowsky (2000). This research explains the relationship between time urgency and the components of a behavioral pattern. One of these patterns is Type A Behavioral Pattern (TABP), which is associated with high levels of competitiveness, high need for achievement, deep sense of time urgency (feeling of having not enough time), impatience, easily aroused, anger and hostility. Within TABP, time is considered as a scarce resource and people want to use it as efficient as possible. This is comparable to clock time, which is described earlier. Furthermore studies found that people with type A behaviors,
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arrive at scheduled appointments earlier than do Type Bs; complete questionnaires more quickly and devote less time to relaxation and sleep.
Notwithstanding the fact that personality is an essential and interesting factor within a culture, this research will further elaborate on the effect of culture on perception of time and in particular punctuality and lateness.
3.3.1 Punctuality
This research will focus on the second concept of Brislin & Kim (2003), punctuality. Koslowsky (2000) defines punctuality as a discrete behavior that only occurs if an individual arrives on time. Levine et al. (1980) researched the difference in punctuality between Brazil and the United States. They found that Brazilians are less concerned with lateness and are more frequently late. However, they stated that there is a need for future research that delineates other parameters of time perception both between and within nations. A few years later Levine and Bartlett (1984) extended this research. They investigated cross-cultural differences in attitudes and behaviors concerning time, punctuality and pace of life and the relationship of these measures to coronary heart diseases. These studies took place in Japan, Taiwan, Indonesia, Italy, England and the US. Their findings indicate that Japan scores highest on average walking speed (pace of life) and working speed. Furthermore they identified two types of behaviors. Type A behavior is characterized by a sense of time urgency, punctuality, arriving early, judging the lapse of one minute sooner and being impatient (Levine and Bartlett, 1984). Type B behavior can be identified as the opposite.
White, Valk and Dialmy (2011) conducted research regarding punctuality within a cross-cultural context in which they measured the sociocross-cultural nature of punctuality among university students in Estonia, Morocco and the US. They produced a measure called the On Time Window (OTW) that indicates the level of wideness and flexibility for what counts as ‘on time. According to White et al. (2011) the appropriateness of being early or being late depends on local norms and
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the nature of the meeting (formal or informal). This relation is formulated in the following hypothesis:
H4: The nature of the meeting (informal, formal and highly formal) affects the On Time Window (OTW)
They concluded that norms of punctuality can vary across cultures, which raises the expectation that this could also be applicable for South Africa and the Netherlands. Mangaliso (2001) highlights the difference in culture between Western and African countries by saying that the Western concept of time management will be ineffective at best, and dysfunctional at worst, if it is carelessly pitted against the African conception of time. Based on this finding, the following hypotheses were developed:
H5: South Africa has a larger On Time Window compared to the Netherlands
This hypothesis is divided into two sub hypotheses that function as determinants of the OTW.
H5a: South Africa has a higher tolerance for lateness compared to the Netherlands
H5b: South Africa has a higher tolerance of inappropriately earliness compared to the Netherlands
Furthermore White et al. (2011) emphasize the fact that these punctuality norms appear to be fuzzy both within and across cultures. This is why more research on this topic is needed. Dishon-Berkovits and Koslowsky (2002) underscore the importance of studying employee punctuality from an applied perspective because of its positive outcomes. Both managers and employees may benefit from this behavior since punctual employees seem to be less likely to engage in withdrawal behavior and have often high levels of commitment, satisfaction and job involvement (Dishon-Berkovits and Koslowsky, 2002).
3.3.2 Lateness
The counterpart of punctuality is lateness behavior. Lateness is defined by Sagie, Koslowsky and Hamburger (2002) as arriving at work after the scheduled time. This study is in
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line with Rogelberg, Scott, Agypt, Williams, Kello, McCausland and Olien (2013), who also investigated the concept of lateness. They investigated how lateness is construed by employees by examining base rates of meeting lateness. Finally they studied the perceived consequences from a participant perspective. Their findings show that lateness to meetings is both an objective clock based phenomenon as well as a subjective, socially contextual phenomenon. The clock based aspect is for example the comparison between the scheduled time and arrival time. Socially contextual factors on the other hand, can be the level of disruptiveness when someone is late or whether the meeting already started and if the latecomer missed essential information. All these factors influence the way lateness to meetings is perceived (Rogelberg et al., 2013).
Foust, Elicker and Levy (2006) investigated the attitude that is associated with lateness. They define lateness attitude as how one feels and thinks about being late to work and measured affective and cognitive reactions to lateness behavior. Foust et al. (2006) developed and validated a measure of employees’ attitudes towards lateness at work. This measure included three content domains: (1) affective response to his or her own lateness to work, (2) an individual’s affective response to his or her co-workers ‘lateness to work, and (3) an individual’s beliefs or cognitions about being late to work in general.
The research in lateness attitude corresponds with the second study of Rogelberg et al. (2013) since they investigate the perceived consequences by asking how the participant feels when someone is one to five or six to ten minutes late. Rogelberg et al. (2013) identified two broad categories. The first category is that lateness of others can lead to a negative mood state in those who already arrived. The second category is that lateness can have an impact on the perceptions of the late individual. This means that when someone arrives late (regularly), this can have a negative effect on his or her relationships with colleagues and management, which will eventually influence the late attendant’s career opportunities.
Within the investigations into lateness, Koslowsky (2000) developed a framework including factors that influence lateness. Based upon the key role of culture within lateness, a
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final hypothesis was established to investigate whether culture determines the base rate of meeting lateness. The expectations are based on the argument of Mangaliso (2001) about the dysfunctionality and ineffectiveness of African time management.
H6: South Africa has a higher base rate of meeting lateness compared to the Netherlands
Koslowsky (2002) states that time is related to cultural contexts in two ways; from a societal and organizational perspective. In fact, Koslowsky makes the same distinction as Schneider (1988) by differentiating between national and corporate level. The societal perspective can be illustrated with the research of Manrai and Manrai (1995). They found a difference between perceptions of work and social leisure time between high context cultures (Asia, the Middle East and South America) and low context cultures (Western Europe). High context cultures are characterized as polychronic and social interactions are much more important than keeping schedules. Low context cultures are perceived to be monochronic. This means that time is treated as a tangible asset, divided into small units, and people use it in a linear way. Besides the societal level, the organization socialization process on the individual should be considered. Organizational norms and cultures can influence employees work behavior and thus time perception (Koslowsky, 2000). However, this research will focus on national cultures.
Current research contains some evidence for an effect of culture on both punctuality as well as lateness behavior. According to Rogelberg et al. (2013) it is reasonable to expect that individuals in certain national cultures will be more affected by meeting lateness than others, which makes it another rich area for future research. Foust, Elicker and Levy (2006) confirm this statement by arguing that culture can play a significant role in determining peoples’ view on timeliness. They also mention the difference in concepts of work time and leisure time between Western versus Middle East cultures. Furthermore Kanekar and Vaz (1993) and Levine et al. (1980) state that there are cross-national differences in punctuality, although this is only tested in a limited number of countries. Not many scholars include African countries in their studies,
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which makes a research that compares a European country (the Netherlands) with an African country (South Africa) a valuable addition to current research.
Next, a conceptual model will be presented that includes an overview of the hypotheses that are established in the theoretical framework.
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3.4 Conceptual model
3.4.1 Model
Figure 2: Conceptual model
3.4.2 Hypotheses
H1 South Africa scores lower on individualism compared to the Netherlands
H2 South Africa scores higher on power distance compared to the Netherlands
H3 South Africa scores lower on uncertainty avoidance compared to the Netherlands
H4 The nature of the meeting (informal, formal and highly formal) affects the On Time
Window (OTW)
H5 South Africa has a larger On Time Window compared to the Netherlands
H5a South Africa has a higher tolerance for lateness compared to the Netherlands
H5b South Africa has a higher tolerance of inappropriately earliness compared to the
Netherlands
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4 Method
This section will provide an overview of the methodological aspects of this study. A
description of the research method will be given; furthermore data collection and measures will
be explained. Finally some attention will be paid to the way data analysis was performed.
4.1 Research method
This study is based on a deductive research approach, which involves the testing of a theoretical proposition by making use of, in this case, quantitative research. The survey method was used to pursue a structured collection of data from a sizeable population. An Internet mediated self-administered questionnaire was developed to collect the data in an efficient and cost effective manner. The questionnaire was in English and was composed of three different constructs. However, a Dutch version was needed for distribution in the Netherlands. The English version was translated to Dutch and subsequently the survey was translated back to English by a English and Dutch native speaker. Once the survey was available in two languages, a pre-test was run. Both surveys were distributed among 5 persons who completed it and gave feedback. This feedback was integrated in order to optimize the surveys and made them ready to use.
4.2 Data collection
The first step within the data collection process was selecting a sample of the whole population. Since this study makes a comparison between the Netherlands and South Africa, the labor force of both countries was chosen as total population. According to Collins dictionary, ‘the labor force consists of all the people that are able to work in a country or area’. A sample was selected through non-probability sampling. A combination of self-selection sampling and snowball sampling was used to reach sufficient respondents, at least 50 respondents from each country was desirable. Once the survey was ready, it was launched with Qualtrics. This program facilitates quick and easy distribution of a survey and delivers a complete dataset once the survey is finished. All data were collected in a timeslot of three weeks.
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The survey link was distributed via different mediums like Facebook, Twitter, email and Internations, which is a large expat forum. Participants were asked to participate in a study of ‘International Management and time perception’. The two survey links were distributed among Dutch and South African participants in Dutch and English. Collecting data in the Netherlands turned out to be easier than in South Africa. However, the snowball sampling technique delivered a large amount of respondents. A logistics firm, some lecturers of Stellenbosch University and various South African friends were willing to help filling in the survey and distributing it among other South Africans.
Once both surveys were closed, data of 164 respondents was collected. 78 South Africans completed the South African survey; the Dutch survey on the other hand, resulted in 86 responses. According to the demographic characteristics displayed in Table 1, it can be seen that the dataset consisted of 78 South African respondents and 86 Dutch respondents. With respect to gender, the data was evenly distributed with 82 males and 82 females. The average age of the dataset was 34.6 (SD = 13,95) with a range between 20 years to 86 years. Age is not normally distributed within the whole sample. This is caused by a high peak within the age 23-26 in the Dutch sample that account for some 50% of all Dutch respondents. This leads to a peaked distribution with a Kurtosis of 5.9. The mean in the South African dataset was 37,7 years (SD = 13,3), substantially higher contrary to the Netherlands with an average age of 31,8 (SD = 14,0). Most respondents (28%) were academically trained professionals. Years of education is approximately normally distributed, with an average of 12.2 years. With respect to the means of both variables, the South African sample followed more years of education (M = 14,2) and has a relatively higher job level (M = 5,2) compared to the Netherlands with (M = 10,4) and (M = 3,9) respectively.
Lastly, the South African respondents were asked to specify their ethnic origin. The data shows that 83,3 percent of the South African sample was white.
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TABLE 1
Demographic characteristics of the sample
4.3 Measures
The survey instrument was based on several existing, tested measures that have been retrieved from previous research. Within this study, the data included measurements on cultural differences, numbers of meetings a week, meeting lateness base rate, lateness, earliness and several control variables. In the next section, each of these measurements will be further explained.
Cultural differences were measured by using the Values Survey Module 94 (VSM94)
developed by Geert Hofstede. This widely used instrument determines the cultural values of
Total (N=164) South Africa (N=78) The Netherlands (N=86)
Mean Freq. % Skewness Kurtosis Mean Freq. % Skewness Kurtosis Mean Freq. % Skewness Kurtosis
Gender Male 1.5 82 50,0 1,5 39 50,0 1,5 43 50,0 Female 82 50,0 39 50,0 43 50,0 Age 0-20 34,6 2 1,2 1,258 0,872 37,7 1 1,3 1,231 0,592 31,8 1 1,2 2,213 5,943 (yrs) 21-40 120 73,2 53 67,9 67 77,9 41-60 30 18,3 16 20,5 14 16,3 61-80 11 6,7 8 10,3 3 3,5 80-100 1 0,6 0 0,0 1 1,2 Education 0-3 12,2 1 0,6 0,193 -0,665 14,2 0 0,0 -0,289 -0,626 10,4 1 1,2 0,687 0,950 (yrs) 4-7 19 11,6 5 6,4 14 16,6 8-11 60 36,6 15 19,2 45 52,3 12-15 40 24,4 22 28,2 18 20,9 16-19 33 20,1 27 34,6 6 7,0 20-23 11 6,7 9 11,5 2 2,3
Job No paid job (incl students) 4.5 18 11,0 5,2 4 5,1 3,9 14 16,3
Unskilled/semiskilled 9 5,5 0 0,0 9 10,5
Generally trained office worker 14 8,5 8 10,3 6 7,0
Vocationally trained 23 14,0 4 5,1 19 22,1
Academically trained 46 28,0 22 28,2 24 27,9
Managers of subordinates 39 23,8 30 38,5 9 10,5
Managers of managers 15 9,0 10 12,8 5 5,8
Nationality South Africa 1.5 78 47,6 the Netherlands 86 52,4
Ethnicity black 2.2 1 1,3 2,2 1 1,3
white 65 83,3 65 83,3
coloured 9 11,5 9 11,5
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people between two or more countries. It consists of 20 questions, four content questions for each cultural dimension that is answered on a five-point scale. An example of such a content question is ‘How often do you feel nervous or tensed at work?’ which is a determinant of uncertainty avoidance. Besides the questions, the VSM94 also provides three formulas to calculate the country scores for each dimension. Once the country scores are calculated, the scores of both countries will be compared. This does not involve statistical testing. Since VSM94 is an existing instrument that is frequently used, it has already been tested on reliability and validity.
As mentioned before, three dimensions are highlighted in this study, namely power distance, individualism and uncertainty avoidance because of the expectation that there is a relation between these dimensions and time perception. Moreover, according to Hofstede’s country scores there seems to be a significant difference on these dimensions between South Africa and the Netherlands. Besides skipping two dimensions, another change to the original instrument was made. The scale in the first question was reversed beforehand from ‘extremely important-not at all important’ to ‘not at all important-extremely important’. This was taken into account when calculating the dimensions.
Cultural differences were also measured at the individual level. Individual scores were measured by simply calculating an average individual score per dimension per country.
Number of meetings a week is measured by simply asking the question ‘How many times
a week do you have a meeting?’ This question serves as an introduction for the following meeting lateness base rate question. Therewith an indication of the average number of meetings in each country is developed.
Meeting lateness base rate is used in the study of Rogelberg et al. (2013). Due to the
absence of literature in meeting lateness frequency, the question ‘Is meeting lateness a common workplace occurrence?’ was added in order to see what percentage of meetings started late or on time.
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Earliness and lateness are measured in two different ways, based on two instruments. The
first instrument is developed by Rogelberg et al. (2013). Eight lateness scenarios with varying factors were sketched; on time versus 5 minutes late, group started versus group chit-chatting and last member to arrive versus other members had not arrived yet. Respondents could indicate whether they view the scenario as late (1, yes) or not (0, no). Once all data is collected, the percentage of time each scenario was viewed as ‘lateness’ is calculated.
White et al. (2011) developed an instrument that consists of seven items that are used to measure definitions of ‘early’ and ‘late’ and the influence of the character of the meeting (formal versus informal). With respect to the reliability, it turned out that the seven punctuality items are consistent (Cronbach alpha = .76). These seven scenarios, that are similar to scenarios used by Levine et al. (1980), were integrated in this survey. Each question consists of a scenario about work related appointments or a social engagement and an indication of the time at which a person arriving would be inappropriately early or inappropriately late. For example, a participant reads that a government official asks a government worker to meet him at a café at 10:00 a.m. Subsequently the participant was asked ‘Suppose the worker does not arrive until after 10:00. At what time would you consider the person to be inappropriately late?’ The score of the participant on this item is the difference between the stated meeting time (10:00) and the time reported by the participant as inappropriately late (e.g. 10:10). All scores are averaged to produce a measure called OTW (On-Time Window). This measure gives an indication of flexibility for what counts as ‘on time’.
Control variables remained in the last section of the survey. Most control variables were
based on the Values Survey Module 94 developed by Hofstede. The first two questions measured gender and age. Gender was coded as followed 1 = Male and 0 = Female. The South African survey continued with a question in which respondents indicated their ethnicity. Luksyte, Waite, Avery and Roy, (2013) emphasize the essence of considering ethnicity or race as an important factor in lateness. Due to the presence of several large ethnical groups within South Africa, this
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could be of significant value. Currently the official ethnical classification in South Africa is as follows: black African, white, colored, Indian, Asian and other (Economist, 2012).
Finally, the respondent could indicate the years of education (high school, college, university etc.) and his or her job level. Job level was codified into seven categories; 1 = no paid job (includes full-time students), 2 = unskilled or semi-skilled manual worker, 3 = generally trained office worker or secretary, 4 = vocationally trained crafts person, technician, informatician, nurse, artist or equivalent, 5 = academically trained professional or equivalent (but not a manager of people), 6 = manager of one or more subordinates (non-managers) and 7 = manager of one or more managers.
Lastly a single open-ended item about the conceptualization of lateness was added, used in the study of Rogelberg et al. (2013). This question reads, “ Think about a time you considered yourself or someone else to be late to a meeting. Now describe why in your mind you classified it as lateness.” The participants’ answers were analyzed by using a coding system developed by Rogelberg et al. (2013). Nevertheless, some changes were made to this coding system. Due to a lack of responses that could be coded as ‘readiness’, this code was replaced by two other codes; ‘informed’ and ‘valid explanation’. These codes appeared to be more useable.
4.4 Data analysis
First, all data was imported into IBM SPSS Statistics 20. Some missing values were identified. A list wise deletion procedure was performed to delete cases that were incomplete for all variables. The HOTDECK (HD) macro technique was used to replace the missing values in the dataset. Once the missing values were replaced, the total sample size was N=164.
Subsequently both data sets where merged into one complete dataset. A new variable ‘nationality’ was created to distinguish the South African respondents from the Dutch. Some additional variables where computed like an individual score for each cultural dimension and the individual OTW score. To calculate the OTW score, the data of the seven items to measure ‘early’ and ‘late’, had to be transformed from a specific moment of time to exact minutes. First all
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answers needed to become consistent, for instance 15.10, 15u.10 and 3.10pm were all changed into 1510. In the case of calculating lateness into exact minutes, this was done by simply subtracting the given amount by 1500. The final variables that were added to the dataset included a categorized version of ‘age’ and ‘years of education’. Finally age and years of education where recoded into new variables that indicated groups.
With this final dataset, a descriptive analysis was performed followed by a measure of the correlations between variables. By running several t-tests and chi-square tests, the difference was measured between South African and Dutch respondents. The results of the data analysis will be presented in the next section.
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5 Results
This section will elaborate on the outcomes of the data analysis. First a check for reliability on the measures was executed. Then, the results of the main analyses are presented. Finally, the qualitative analysis will be discussed.
With respect to the reliability of the variables, the results indicated poor Cronbach alphas, as specified in Table 2. All three variables that measured the three cultural dimensions of Hofstede tend not to be reliable. The alphas of individualism (α .420), power distance (α .379) and uncertainty avoidance (α .126) are not even close to the criterion of at least .7 used to establish an acceptable level of reliability. Apparently this low consistency is a common occurrence in studies that used Hofstede’s VSM94 module (Spector, Cooper and Sparks, 2001). The results should be used with caution.
Furthermore, a correlation analysis was performed to identify relationships between the variables. The outcomes are specified in Table 2.
Firstly, age (r = 0.165, p< 0.05), years of education (r = 0.211, p< 0.01) and job level (r = 0.304, p< 0.01) are positively correlated to power distance. Moreover, the final scenario about the government official that arrives late showed a positive relationship with power distance (r = 0.171, p< 0.05). Also, a strong positive correlation was found between the number of meetings and both years of education (r = 0.275, p< 0.01) and job level (r = 0.310, p< 0.01). Lastly, evidence was found that higher job levels are related to a higher age (r = 0.391, p< 0.01) and more years of education (r=0.190, p< 0.05).
-32- T ABL E 2 C orr el at ions and R el iabi li ti es EAR 1 Stu de nt, b ef ore 3.00 , e arly ? LAT E3 Fri en d, afte r 1.00 , late ? EAR 2 Fri en d, be fore 1.00 , e arly ? LAT E4 G ov erm en tw ork er, afte r 10.0 0, lat e? LAT E1 Stu de nt, a fte r 3.00 , late ? LAT E5 G ov ern m en t off ic ial, afte r 10: 00 . lat e? LAT E2 Te ach er, afte r 3.00 ,lat e? 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 1 In div id ualis m (α .420 ) 2 Po w er dis ta nce 0,408* * (α .379 ) 3 U nce rta in ty a vo id an ce 0,172* 0,060 (α .126 ) 4 La ten es s (1) 0,008 ─0 ,064 ─0 ,012 (α .511 ) 5 EAR 1 0,110 0,026 ─0 ,002 ─0 ,052 (x) 6 EAR 2 0,103 0,072 0,071 ─0 ,039 0,586* * (x) 7 LAT E 1 0,092 ─0,038 ─0 ,143 0,101 0,475* * 0,320* * (x) 8 LAT E 2 0,162* 0,119 ─0 ,040 ─0 ,030 0,332* * 0,191* 0,502* * (x) 9 LAT E 3 0,083 0,146 0,066 -0,117 0,297* * 0,466* * 0,339* * 0,517* * (x) 10 LAT E 4 0,014 0,055 0,044 ─0 ,053 0,393* * 0,210* 0,472* * 0,317* * 0,254* * (x) 11 LAT E 5 0,015 0,171* 0,116 ─0 ,043 0,251* * 0,126 0,375* * 0,327* * 0,268* * 0,766* * (x) 12 N r m ee tin gs 0,083 0,191* 0,104 ─0 ,052 ─0 ,205 ** ─0 ,149 ─0 ,169 * ─0 ,024 ─0,064 -0,152 ─0 ,109 (x) 13 Bas e r at e 0,011 0,001 0,109 0,074 ─0 ,019 -0,082 ─0 ,187 * ─0 ,173 * -0,145 -0,111 -0,069 -0,076 (x) 14 G en de r 0,061 ─0 ,028 0,076 ─0 ,103 0,024 ─0 ,093 0,031 ─0 ,039 -0,130 0,071 0,102 -0,034 0,013 (x) 15 Age ─0 ,031 0,165* 0,008 0,004 0,186 0,054 ─0 ,148 ─0 ,136 ─0 ,166 * 0,170* 0,064 0,010 -0,082 0,072 (x) 16 Ed ucat ion 0,088 0,211* * ─0 ,007 -0,030 ─0 ,149 ─0 ,112 0,010 ─0 ,023 0,040 -0,063 0,024 0,275* * 0,009 -0,054 -0,019 (x) 17 Jo b 0,092 0,304* * 0,096 -0,025 0,073 0,069 ─0 ,088 0,052 0,050 0,152 0,200* 0,310* * -0,132 -0,010 0,391* * 0,190* (x) 18 N at ion alit y ─0 ,379 ** ─0 ,517 ** ─0 ,008 0,035 0,000 ─0 ,055 ─0 ,003 -0,067 -0,066 -0,087 ─0 ,164 * ─0 ,160 * -0,008 0,000 ─0 ,211 ** ─0 ,440 ** ─0 ,365 ** (x) 19 Eth nici ty 0,153 0,152 0,108 0,059 0,096 ─0 ,015 0,013 -0,031 -0,143 0,019 -0,002 0,129 0,155 0,019 -0,157 -0,015 0,040 0,000 (x) *p < 0.05, ** p < 0.01
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Once the reliability of the scale was assessed, the main analyses were carried out. The first analyses correspond to the cultural aspect. A country score based on each of the three cultural dimensions of Hofstede was calculated. These calculations can be found in Appendix 9.1. The outcomes are displayed in Figure 3 (left) together with Hofstede’s original country scores (right).
Figure 3: Country scores on cultural dimensions
The results show that both South Africa (88) as well as the Netherlands (98) score high on individualism. Though, South Africa scores lower on individualism compared to the Netherlands, which means that H1 is supported. Power distance on the other hand, is related to relatively low scores (SA=8) (NL=11) compared to Hofstede’s original scores. Furthermore, these country scores do not correspond to the second hypothesis and therefore H2 is rejected. With regard to uncertainty avoidance, the scores are similar to Hofstede’s calculations. However, South Africa (60) has a higher score than the Netherlands (50), which results in rejection of H3.
In addition to measuring the three cultural dimensions on country level, the hypotheses were also tested by calculating individual scores on cultural dimensions. From this individual perspective, South Africa scores higher in individualism (M=4,33) and power distance (M=3,86) compared to the Netherlands (M=4.01 and M=3.36 respectively). This means that H1 should be rejected while H2 can be accepted. With regard to uncertainty avoidance, both countries show similar individual scores, which is not in line with H3. Therefore H3 is not supported.
0 20 40 60 80 100
IND PDI UAI IND
Hofstede PDI Hofstede UAI Hofstede SA NL
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When comparing the individual scores from Table 3, they are neither in line with the scores on country level nor with Hofstede’s original scores.
TABLE 3
Individual scores on cultural dimensions
An independent-samples t-test was conducted to measure if there is a significant cultural difference between South Africa and the Netherlands. As the results in Table 3 indicate, a significant difference in terms of individualism and power distance between South Africa and the Netherlands (p< 0.05) was found. No significance was found in the comparison of uncertainty avoidance scores for South African and Dutch people (p> 0.05). Putting all these facts together, we may assume that South Africa and the Netherlands do differ in terms of culture.
The results with respect to earliness and lateness show the following. First, the number of meetings a week and the meeting lateness base rate was identified. Compared to the South African respondents (M=3.2), Dutch respondents had less meetings a week (M=2.8). Moreover, according to the data, Dutch respondents have a slightly higher meeting lateness base rate (48.3%) then South Africans (47.4). A Chi square test for independence indicated no significant association between nationality and the base rate, χ² (1, n=136) = .000, p = 1.000. Thus, there is no support found for the sixth hypothesis.
Within the concept of meetings, White et al. (2011) make a distinction between formal and informal scenarios. To investigate whether formality plays a significant role in determining
South Africa the Netherlands T-test
M SD M SD Sig. (2-tailed) Individualism 4,33 0,43 4,03 0,32 .000* Power distance 3,86 0,45 3,36 0,39 .000* Uncertainty avoidance 3,06 0,56 3,06 0,46 .919 *p<0.05
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earliness and lateness, a paired sample t-test was executed on the data, collected for two different scenarios (formal versus informal).
TABLE 4
The effect of the nature of the meeting
Table 4 shows that there is a significant difference in the On Time Window in a formal setting and an informal setting. In the scenario where the student arrives late at the meeting with his teacher (formal occasion), people tend to be less flexible in their OTW compared to a meeting with a friend (informal occasion).
This is also the case for earliness. The eta square value gives an indication of the size of this effect. In this case the eta squared of pair 1, pair 2 and pair 3 do all exceed the .14 guideline that points to a large effect. For this reason, H4 can be accepted. Moreover, some notable comments were found that are in line with these findings:
‘A friend can never be too late or too early.’ - Respondent #5
The results show no significant difference in terms of a formal (meeting with teacher) and a highly formal (meeting with government official) meeting. Moreover, no substantial differences between South Africa and the Netherlands were measured in terms of the effect of the formality of the occasion on the OTW.
Total South Africa the Netherlands
N Sig. (2tailed) Eta squared N Sig. (2tailed) Eta squared N Sig. (2tailed) Eta squared Pair 1 student late-friend late 149 .000* 0,57 71 .000* 0,53 78 .000* 0,64 Pair 2 student late-gov. worker late 156 .174 0,01 73 .147 0,03 83 .698 0,00 Pair 3 gov. worker late-friend late 152 .000* 0,55 71 .000* 0,49 81 .000* 0,64 Pair 4 student early-friend early 134 .000* 0,40 60 .000* 0,42 74 .000* 0,38 Pair 5 teacher late-gov. official late 159 .052 0,02 73 .135 0,03 86 .134 0,03
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To check whether there are differences between South Africa and the Netherlands in the definitions of early and late, an overview is created of the participant’s responses to the punctuality scenarios. This summary is displayed in Table 5.
TABLE 5
Summary statistics of responses to seven punctuality items by country
Subsequently, all seven punctuality scores were averaged for each participant to create an indication of the level of wideness and flexibility for what counts as ‘on time’, known as the OTW score. The South African OTWs (M=20.5, SD=10.1) were slightly larger than the Dutch OTWs (M=18.5, SD=7.7; p = .200, two-tailed). However, this difference is not significant. If we take a more detailed look, on item level, only one significant difference was identified, namely the official arrives late to meet the worker. On average, Dutch respondents call the official late after 9.5 minutes while South African respondents are more flexible (M=12.7). In addition to these results, another analysis was carried out to gain a broader insight within the different perceptions of lateness between two countries. By measuring the number of times a scenario was identified as lateness, a rate for each country was created. All output is displayed in Table 6.
Total South Africa the Netherlands T-test
Item M SD Mode M SD Mode M SD Mode
Sig. (2-tailed)
Student arrives early to meet teacher 22,8 17,3 30 22,8 16 15 22,8 18,4 30 .998 Student arrives late to meet teacher 9,5 6,7 10 9,5 5,7 10 9,4 7,6 5 .969 Teacher arrivees late to meet student 9,2 10 10 10 12,6 10 8,6 7,2 10 .401
Friend arrives early for lunch 43,5 32,5 30 45,4 36 30 41,8 29,2 30 .521
Friend arrives late for lunch 34,3 23,1 30 35,9 26,9 30 32,9 19,2 30 .415 Worker arrives late to meet official 10,4 8,7 10 11,2 9,3 10 9,7 8,1 10 .274 Official arrives late to meet worker 11 9,5 10 12,7 11,7 10 9,5 6,8 10 .045*
