Lean Management and Service Sector: The Moderating Effects of National Culture

Lean Management and Service Sector: The

Moderating Effects of National Culture

Master Thesis

MSc Supply Chain Management

University of Groningen

Faculty of Economics and Business

Shihao Liu

S3303357

S.Liu.20@student.rug.nl

Abstract

Lean Management was widely used by manufacturing companies and also studied by scholars for many years. Although most of cases indicate that Lean Management positively improved the operational performance of companies, many studies also reveal the failure cases of Lean Management, especially when Lean Management was implemented outside Japan. Therefore, the role of national culture is starting to get attentions in literature. On the other hand, as time went by, Lean Management was implemented in many kinds of industries especially in service sector. This paper focuses on the effectiveness of Lean Management in service sector and also the influences of national culture on the effectiveness of Lean Management in service sector. Data was collected from four countries (Netherlands, Germany, Belgium and China) via an online survey and the results show that firstly, Lean Management can positively improve the performance of service sector. Secondly, two dimensions of national culture (masculinity and power distance) positively moderate the relationship between Lean Management and operational performance and one dimension (indulgence) negatively moderates this relationship. Furthermore, results also indicate that the moderating effects could be mitigated by improving the implementation level of Lean Management. For managers, it is important to understand the influences of national culture and avoid the negative impacts of national culture by improving the implementation level of Lean Management.

1. Introduction

Lean Management, first invented and implemented by the famous Japanese Manufacturer Toyota, is widely considered as an integrated socio-technical system to achieve higher operational performance of companies (Shah & Ward, 2007; Liker, 2004; Bortolotti et al., 2015). Lean Management was deeply studied by scholars for several decades (Ohno, 1988; Sakakibara et al., 1993; Hopp & Spearman, 2004; Shah & Ward, 2007). However, most of the studies were focusing on private companies, especially manufacturing companies. Comparing to the studies focusing on manufacturing companies, the studies focusing on service sectors are relatively rare (Ahlstrom, 2004; Apte & Goh, 2004; Stentoft et al., 2011; Radnor, 2010; Bhatia & Drew, 2006; Castaldi et al., 2016). On the other hand, more and more evidences show that service industry is becoming essential and indispensable to our life and economy. For example, about 70% gross domestic product (GDP) of Europe was created by service industry, and more than 60% of employees are enlist in service industry (OECD, 2011; Damrath, 2012). These numbers are even higher in U.S., about 80% GDP was created by service industry and more than 80% employees are work in service industry (OECD, 2011; Damrath, 2012). Therefore, implement Lean Management successfully in service sector is crucial and meaningful.

gap in Lean Management research. Therefore, the research question of this study is does national culture influence the relationship between Lean Management and operational performance of service sector.

The purpose of this research is to investigate the moderating effects of national culture on the relationship between Lean Management and organizational performance in the context of service sector. The study starts with the literature review of the impact of Lean Management on operational performance and the influence of national culture. In order to implement this research, the data is collected not only from different European countries, but also from Asian countries. By investigating the influence of national culture, we can have a clear understanding that why the effectiveness of Lean Management and other improvement approaches vary from country to country. Thus, this research not only fills in the gap in literature about the influences of national culture on the effectiveness of Lean Management in service sectors, but also provides a new dimension for practitioners to evaluate Lean Management.

This research is structured in the following way. Firstly, theoretical background of this research is displayed in the next section. Subsequently, the methodology is explained in section 3. After that, section 4 presents the results and findings of this research. In the end, discussion and conclusion are presented in section 5 and 6.

2. Theoretical Background

The impact of Lean Management on performance was studied by lots of researchers for many years. There are different views in literatures. Despite some literatures revealed that the expected results of Lean Management are not always attainable (Pay, 2008), especially when lean was implemented in the condition without a high volume manufacturing (Staudacher & Tantardini, 2008), most of the literatures conclude that Lean Management has positive impact on operational performance (Cua et al., 2001; Sohal & Egglestone, 1994; Taj & Morosan, 2011; Chavez et al., 2015; Salaheldin, 2005; Sakakibara et al., 1997; Chen & Hua Tan., 2013; Filho et al., 2016). And in general, the benefits mainly from cost reduction, waiting time reduction and variability reduction (Bortolotti, Boscari & Danese, 2015).

2.2 Lean Management in service sector

In literature, most of Lean studies were focusing on manufacturing companies. As time went by, service sectors showed dramatic growth. Service sectors have started to accept the new concepts in recent years, such as Lean, BPR and Six Sigma (Radnor & Johnston, 2013). And the applicability of these improving approaches in service industry was widely discussed by scholars (Apte & Goh, 2004; Lee et al., 2008; Radnor, 2010; Andrés-López et al., 2015). However, in the context of service sectors, results might not be as good as the results in manufacturing companies. Because Lean Management was initially invented for improving efficiency and reducing waste for manufacturing companies rather than service sectors which include intangible products (Andrés-López et al., 2015). According to the study of Radnor and Walley (2008), the barriers of implementing Lean Management in service sectors include lack of clear customer focus and too many procedures or people working in silos. Scorsone (2008) indicated that administrative law and civil service restrict the implementation of Lean Management in service sectors, especially in public sectors. In order to fit with service sector, some adaptations of Lean Management are needed. For example, remove the characteristics of Lean Management which specific for manufacturing companies (Erridge & Murray, 1998).

Despite there are challenges and barriers of implementing Lean Management in the context of service sectors, literatures still revealed many successful cases (Krings et al., 2006; Radnor, 2010; Erridge & Murray, 1998; Stentoft et al., 2011). For example, the studies of Zoe Radnor (2010) demonstrated that health care sectors, central government and local governments achieved dramatic improvement on both tangible output such as waiting time and intangible outputs such as customer satisfaction after implementing Lean Management. The study of Krings et al., (2006) revealed that the efficiency of police recruitment process in Cincinnati, USA, increased significantly after implementing Lean Management.

H1: Lean Management can positively improve the operational performance of service sectors.

2.3 National Culture and Management Practice

Culture, as an important topic, was studied in literatures for many decades. Culture consists of both implicit elements and explicit elements, and these elements include values, behaviors, basic assumptions and norms which distinguish people from different groups or categories (Hofstede, 2011; Myers & Tan 2003). More specifically, national culture is about the collective way of thinking of the people who from same country (Pagell et al., 2005). Despite the fact that national culture was defined by many researchers, as one of the most representative researcher in this field, Hofstede’s definition gained most popularity. National culture, as defined by Hofstede, is “the collective programming of the mind which distinguishes the members of one group or category of people from another” (Hofstede, 1991, p.5). There is a broad tendency that people from same cultural context or same country prefer specific states of affairs over others (Hofstede, 2011).

There are several models of national culture in literature, which include single dimension models (e.g., Triandis, 1995), multiple dimension models (e.g., Hofstede, 1991) and historical-social models (e.g., Seagrave, 1995). But in operation management field, the model of Hofstede (1991) and House et al. (2004) were most cited and studied (e.g., Cagliano et al., 2011; Wiengarten et al., 2011, 2015; Kull et al., 2014). Furthermore, compare to the model of House et al. (2004), the studies of Hofstede (1980, 1984, 1991, 2011) has more significant influence on literatures (Myers & Tan 2003). And his model of national culture was supported by many studies (Newman & Nollen, 1996; van Oudenhoven, 2001; Søndergaard, 1994) and therefore valid and reliable. Thus, the model of Hofstede is used in this research. According to the studies of Hofstede (1980, 1984, 1991, 2011), national culture mainly includes the following six dimensions: Masculinity/Femininity, Individualism/Collectivism, Power Distance, Uncertainly Avoidance, Long Term Orientation and Indulgence. Many scholars indicated that there are congruencies between Lean Management and different dimensions of national culture (e.g., Cagliano et al., 2011; Wiengarten et al., 2015; Pagell et al., 2005; Wiengarten et al., 2011; Kull et al., 2014). The discussion of detailed congruence could be found in the following part.

2.4 Moderating Effects of National Culture

national culture of organizations and management practices should be considered before implementing. The research of Lozeau et al., (2002) demonstrates that the management practices which are effective in some organizations may not suitable for every organization. More specifically, Lean Management which was successfully implemented in Japan may not be able to get the expected results in different cultural context. For example, almost 70 percent of U.S. manufacturing companies were using Lean Management but less than quarter of these companies fully achieved the expected results (Pay, 2008). One of the important reasons for this might be the significant difference of national culture between U.S. and Japan.

In this study, the impact of different national culture dimensions on the relationship between Lean Management and operational performance is investigated. The level of compatibility between Lean Management and some national culture dimensions may influence the impact of Lean Management on operational performance of companies (Kull et al., 2014). In the next part, the congruence between every sub-dimensions of national culture and Lean Management will be discussed separately and the hypotheses are proposed based on the level of congruence. The higher the level of the congruence, the smoother the implementation of Lean Management will be, but the smaller the room of performance improvement will be, and vice versa. The reasons are as follows. Lean Management is the approach which can positively improve operational performance. If a national culture is highly congruent with Lean Management, then this culture should have positive impact on operational performance, and consequently the performance of companies in this cultural context should be better than the companies which the national culture is incongruent with Lean Management. Thus, the room or potential of performance improvement by implementing Lean Management should be bigger in the culture context which is incongruent with Lean Management rather than the culture which is congruent with Lean Management. In other words, the effectiveness of Lean Management should be better in the culture which is incongruent with Lean Management. Therefore, high level of congruence represents negative moderating effect of national culture on Lean effectiveness. Accordingly, high level of incongruence equates positive moderating effect on Lean effectiveness.

2.4.1 Positive Moderating Effects of National Culture on Lean Effectiveness Masculinity refers to the level of gender inequality accepted by a group of people or a culture (Kull et al., 2014; Srite & Karahanna, 2006). This dimension was not included in the work of some researchers who investigated the moderating effect of national culture on the relationship between Lean Management and operational performance (e.g., Kull & Wacker 2010; Kull et al., 2014; Larteb et al., 2015) because they think gender is not differentiated in Lean Management and therefore this dimension should has no influences on the relationship between Lean Management and operational performance. But after deeply studying this dimension, it is considered that the level of masculinity could influence the effectiveness of Lean Management on operational performance. The reasons are followed. First, people from high femininity cultural contexts, which is low masculinity, highlight friendly working atmosphere and warm relationship with colleagues (Srite & Karahanna, 2006). In Lean Management, team work and cooperation would be facilitated by these friendly atmosphere and good relationships between employees. Second, since quality of life and comfortable work environment are highlighted in high femininity cultural contexts (Srite & Karahanna, 2006), work environment should be more comfortable in high femininity culture compare to high masculinity culture. It is more likely to achieve better efficiency of work in a comfortable environment. This is also compatible with Lean Management because improving work efficiency is one of the important goals of Lean Management. Third, people from high masculinity cultural contexts are generally more assertive than people from high femininity cultural contexts (Hofstede, 2011). People who are too assertive, however, are very likely to have negative impact on the communication and cooperation within a team (Amble, 2006) and hence impede work efficiency. Therefore, culture with high assertiveness, in other words high masculinity, should impede the effectiveness of Lean Management. To sum up, features of high femininity culture are compatible with Lean Management and then have positive impact on operational performance. By contrast, high masculinity culture is inconsistent with Lean Management and therefore has bad impact on operational performance. Following this logic, the room for performance improvement by Lean Management will be partially offset by high femininity cultural context because before the implementation of Lean Management the performance is already positively improved by high femininity culture. Thus, the performance improvement gained by Lean Management in high femininity (low masculinity) culture will not be as good as the performance improvement gained in high masculinity culture. In other words, high degree of masculinity could strengthen the positive relationship between Lean Management and operational performance.

H2: The degree of masculinity positively moderates the positive relationship

Individualism is the extent to which people emphasize the preferences or needs of their own rather than the preferences or needs of a group and the extent to which people prefer to highlight themselves as individuals rather than as a member of group (Srite & Karahanna, 2006).

People who come from low individualism (high collectivism) cultural context are more likely to follow the rules and duties of their groups or systems. They highlight the harmony and integration with their groups (Hofstede, 2011). This characteristic is congruent with Lean Management because in a high collectivism cultural context employees have strong feeling of their responsibility and they are more likely to stick to the duties (Kull et al., 2014). High collectivism people generally have stronger feeling of interdependency towards their groups than the people who are from high individualism cultural contexts (Naor et al., 2010). Hence people in high collectivism cultural context are more likely to achieve collective goals by sharing information, knowledge and skills (Kull et al., 2014). This is also consistent with Lean Management because good communication and team work is highlighted in Lean Management. To sum up, the features of high collectivism culture (low individualism culture) are consistent with Lean Management and therefore have positive influence on operational performance. Hence the operational performance is already improved by high collectivism culture before the implementation of Lean Management. The room for the improvement by Lean Management is partially offset by high collectivism cultural context. Therefore, when Lean Management is fully implemented, the performance improvement gained in high collectivism (low individualism) context should not be as good as the performance improvement gained in high individualism context. In other words, performance improvement of Lean Management is bigger in high individualism culture than the performance improvement in high collectivism.

Thus, high level of individualism culture will strengthen the relationship between Lean Management and operational performance.

H3: The degree of individualism positively moderates the positive relationship

between Lean Management and the operational performance of service sectors.

Power distance is the extent to which individuals of a society agree and expect the power inequality (Srite & Karahanna, 2006; Kull et al., 2014). In other words, power distance is the accepted level of power inequality. The larger the power distance, the more power inequality is accepted, and vice versa.

young people and they are respected and feared by young people (Hofstede, 2011). Thus, when implementing Lean Management, power is more likely to be controlled by old people rather than capable young people. Second, in the mind of lower level employees who from high power distance culture, mangers always know the best and the best ideas always from superiors (Kull et al., 2014). In this situation employees are not able to share and express their ideas and opinions properly. But empowerment of employees is a crucial factor for successful Lean implementation (Scherrer-Rathje et al., 2009) and in order to ensure the successful implementation of Lean Management the employees have to be able to take responsibilities and make decisions rather than waiting the best solutions from the top. Therefore, large power distance is inconsistent with Lean Management and then have negative influence on operational performance. Hence before implementing Lean Management, the performance of organizations from small power distance culture should be better than the performance of organizations from large power distance culture. Therefore, the improving room of performance is bigger in large power distance culture. Lean Management could make a bigger improvement on performance in large power distance culture when Lean Management is highly implemented. To sum up, the positive relationship between Lean Management and operational performance will be strengthen by high degree of power distance culture.

H4: The level of power distance positively moderates the positive relationship

between Lean Management and the operational performance of service sectors.

2.4.2 Negative Moderating Effects of National Culture on Lean Effectiveness Uncertainty avoidance is the extent of an individual, group or nation that relies on existing standards and procedures to reduce unpredictable activities (House et al., 2004; Srite & Karahanna, 2006; Kull et al., 2014). The level of feelings of threatening by unpredictable events is examined by this dimension (Srite & Karahanna, 2006).

incrementally (Sully de Luque & Javidan, 2004). On the other hand, the effectiveness of Lean Management is achieved by incremental change, and these incremental changes are usually come from continuous feedback. Obviously, the features of high uncertainty culture are similar to some features of Lean Management and these features are positive to operational performance. Hence the performance of companies should be better in high uncertainty avoidance culture than the performance in low uncertainty avoidance culture. Therefore, the room for performance improvement is bigger in low uncertainty avoidance culture than the room in high uncertainty avoidance culture. When Lean Management is highly implemented in high uncertainty avoidance culture, the performance improvement will not be as good as the improvement in low uncertainty avoidance culture because the positive influences of high uncertainty avoidance and Lean Management is partially overlapped. To sum up, the relationship between Lean Management and operational performance should be mitigated by high level of uncertainty avoidance culture.

H5: The degree of uncertainty avoidance negatively moderates the positive

relationship between Lean Management and the operational performance of service sectors.

Indulgence is defined as the level of people try to control and restrain their impulses and desires (Hofstede, 2011; Hofstede-Insights, 2017). Stronger control is usually called Restraint and relatively weak control is described Indulgence (Hofstede, 2011; Hofstede-Insights, 2017).

which is highly important to Lean Management. These traits are highly compatible with Lean Management and therefore have positive impact on operational performance. Thus, before the implementation of Lean Management the operational performance of companies should be better in high indulgence culture than in low indulgence culture. Accordingly, compare to low indulgence culture, the room of performance improvement by Lean Management is smaller in high indulgence culture. Therefore, high indulgence culture could mitigate the effectiveness of Lean Management on operational performance. H6: The degree of indulgence negatively moderates the positive relationship

between Lean Management and the operational performance of service sectors.

Long term orientation describes the level of a culture endorses, inspires or encourages people for dealing with challenges of future or doing long term oriented behaviors (Hofstede-Insights, 2017; House et al., 2004). These long term oriented behaviors include be thrifty, planning and investing for future (Kull et al., 2014).

Thus, high level of long term orientation culture mitigates the effectiveness of Lean Management.

H7: The degree of long term orientation negatively moderates the positive

relationship between Lean Management and the operational performance of service sectors.

Figure 1

3. Methodology

Lean Management and organizational performance of service sector are the independent variable and the dependent variable of this research. National culture is assumed to be the moderator in this research. For identifying valid measures of constructs which include Lean Management, operational performance and national culture, the related literatures about the constructs were reviewed.

dimension is from 0 to 100. Higher value of that dimension means people are more likely to be the state that dimension described and vice versa. The reliability of the data and the reason that why the data of Hofstede-Insights website is used are discussed in the following part.

For the measurement of Lean Management, like many previous studies about Lean Management (e.g., Samson & Terziovski, 1999; Cua et al., 2001; Shah & Ward, 2003, 2007; Rahman & Bullock, 2005; Bortolotti et al., 2015) in literatures, the practices of Lean Management are divided into soft and hard in this research. Hard practices represent analytical or technical tools which implemented to improving production or efficiency of a company while soft practices highlight people, relations and managerial principles (Bortolotti et al., 2015). But in order to ensure the fitness between Lean practices and service sectors, some adaptations of Lean practices were made. In this research soft Lean practices are measured by 4 perceptual scales which include top management leadership for quality, continuous improvement, small group problem solving and multi-function employees. For hard Lean practices, 4 perceptual scales are used which include cleanliness and organization, statistical process control, autonomous maintenance and design for quality. Every item was evaluated by a seven-point Likert scale (1 indicating “strongly disagree”, 7 indicating “strongly agree”).

For the measurement of operational performance, four main dimensions (e.g., cost, flexibility, quality and delivery) are used. To making the dimensions of measurement fit with the context of service sector, the four dimensions for measuring operational performance are adapted from the related measurements in literature (e.g., Cua et al., 2001; Bortolotti et al., 2015). In order to investigate the operational performance and compare it with the performance with competitors, the items (e.g., speed of service, on time delivery, cost of service, service capability and performance, conformance to service specification and ability of handling change) of each dimension were evaluated by a five-point Likert scale (1 indicating “poor, much worse than competitors”, 5 indicating “superior, much better than competitors”). The complete scales of all constructs could be found in Appendix.

3.2 Sampling and data collection

Since the aim of this research is to investigating the moderating effect of different national culture on the effectiveness of Lean Management, data was collected from four different countries which include Netherlands, China, Germany and Belgium. The reason for choosing these four countries is that these countries are from both Europe and Asia, it is possible to compare the national cultures between not only different countries but also different continent.

The research unit of this study is organizations of service industry. Data was collected from both public service sectors and private service organizations. LinkedIn and the websites of organizations were used in order to find the contact information of service organizations. The people of service organizations were contacted by email or telephone once the contact information was available. The questionnaire was sent to them by email. In order to ensure the quality and truthfulness of the response, only middle or higher level managers of service organizations were contacted. Compare to normal employees, middle and higher managers have clearer understanding of the situation and the performance of their organizations.

During about six weeks, 883 questionnaires were sent out to four countries. More specifically, 436 questionnaires were sent to China, 251 questionnaires were sent to Netherlands, 196 questionnaires were sent to Germany and Belgium. In the end 281 responses were collected from four countries and the response rate is 31.8%. In total 156 valid responses were collected but more than half of the valid responses are from China. It is hard to analyze the influence of national culture if most of the data is from one single country. Therefore, the number of Chinese responses have to be cut and in the end 71 responses which include the data from all four countries are left. The summary of all 71 responses is showed in Table 1.

≥101 7 9.86% Size of organization 0~50 employees 25 35.21% 51~250 employees 15 21.13% ≥251 employees 31 43.66% Type of industry Banking 20 28.17% Consulting 13 18.31% Taxing 4 5.63% Education 4 5.63% IT 8 11.28% Others 22 30.98% Type of ownership Private 45 63.38% Public 26 36.62%

According to table 1, most of the responded companies were aged below 20 years old and more than 40% of them has more than 250 employees. The type of these service companies includes banking, consulting, taxing, education and IT. Both private (37%) and public service sectors (63%) are included.

The data of national culture is from the latest version Hofstede-Insights website which provide the value of different dimensions of national culture for each country. The data of Hofstede-Insights website is based on the book “Cultures and Organizations: Software of the Mind” (2010 edition). The book provides scores of different dimensions of national culture for 76 countries. These data were based on the IBM study of international populations by different scholars for many years (Hofstede-Insights, 2017). Thus the data of national culture should be reliable.

Figure 2 shows the value of each national culture dimension of four different countries. According to figure 2, Netherlands has lowest level of masculinity but highest level of individualism between four countries. The level of uncertainty avoidance is in the middle between Germany and China but far below Belgium. Another European country Germany is in the similar level of several dimensions with Netherlands. For example, the level of power distance of Germany and Netherlands is almost the same, but much lower than China and Belgium. And the level of individualism and uncertainty avoidance has no big difference between Germany and Netherlands. Both of them are in a relatively high level compare to China. But compare to Netherlands, Germany has a very high level of masculinity which is in the same level with China. Belgium has the highest level of uncertainty avoidance and also high level of long term orientation which is similar with China and Germany. Individualism of Belgium, which is basically in the same level with other European countries, is in a very high level. The indulgence and masculinity level are between Netherlands and Germany but Belgium has the highest power distance level in the three European countries which is slightly lower than China. China, as an Asian country, has big differences in many dimension compare to the other three European countries. For example, China has the highest level of power distance and the lowest level of individualism, uncertainty avoidance and indulgence between four countries. China, however, has high masculinity level which is exactly same with Germany. All four countries have high level of long term orientation but China is the highest one.

3.3 Reliability and Validity

solving (α =.841), continuous improvement (α =.739) and top management leadership for quality (α=.846). Each of them was measured on a scale from 1 (Strongly Agree) to 7 (Strongly Disagree). The α-value for soft lean practices is 0.910 which is much bigger than the benchmark (0.7). That means the scale for soft lean practices is highly reliable (Nunnally & Bernstein, 1979). In addition, the value of Cronbach’s alpha for every dimension of soft lean practices is also displayed in the table below. The results show that the scale of each sub-dimension of soft lean practices is also reliable.

Exploratory factor analysis (EFA) for both soft lean practices and hard lean practices was conducted on SPSS. The Rotated Component Matrix reflects that from MFE1 to MFE3 all strongly load on multifunction employees. Similarly, for the other three sub-dimensions which include small group problem solving, continuous improvement and top management leadership for quality, each item loads strongly on its predefined sub-dimension. That means these scales are measuring the constructs which they intended to measure. Although there are two items of top management leadership for quality and one item of small group problem solving load slightly on other sub-dimensions, these items also strongly load on their predefined dimensions and none other items load more than one factor. Therefore, the convergent validity is warranted.

Table 2

Soft lean practices (α =.910)

Construct and item wording SL

Multi-function employees (α =.750) MFE1 0.92 MFE2 0.88 MFE3 0.76 Small group problem solving (α =.841)

SGPS1 0.91 SGPS2 0.89 SGPS3 0.79 SGPS4 0.74 Continuous improvement (α =.739) CI1 0.88 CI2 0.82 CI3 0.76 Top management leadership for quality (α =.846)

TMLQ4 0.66

Hard lean practices were also measured by four sub-dimensions which include autonomous maintenance (α=.835), statistical process control (α=.900), Cleanliness and organization (α =.895) and Design for quality (α=.908). Similar to soft lean practices, each of the sub-dimensions of hard lean practices was also measured on a scale from 1 (Strongly Agree) to 7 (Strongly Disagree). The α-value of hard lean practices (0.930) shows that the scale for hard lean practices is highly reliable. And the value of Cronbach’s alpha for every sub-dimension of hard lean practices also shows that the scale of each sub-dimension of hard lean practices is reliable.

The Rotated Component Matrix below reflects the results of EFA for hard lean practices. Similar to the results of soft lean practices, items from AM1 to AM3 all strongly load on autonomous maintenance. For the other three sub-dimensions which include statistical process control, cleanliness and organization, design for quality, each item loads strongly on its predefined dimension. That shows these scales are measuring the intended constructs. There are two items from sub-dimension cleanliness and organization also slightly load to sub-dimension design for quality but the overall result is very good and hence the convergent validity of hard lean practices is supported and valid.

Table 3

Hard lean practices (α =.930)

Construct and item wording SL

Autonomous maintenance (α =.835 AM1 0.82 AM2 0.79 AM3 0.75 Statistical process control (α =.900)

SPC1 0.91 SPC2 0.84 SPC3 0.83 SPC4 0.72 Cleanliness and organization (α =.895)

CO1 0.85 CO2 0.79 CO3 0.54 Design for quality (α =.908)

DQ3 0.78 DQ4 0.74 DQ5 0.68

Operational performance of companies is measured by means of 7 items. All of them on a scale from 1 (Poor, much worse than competitors) to 5 (Superior, much better than competitors). The value of Cronbach’s alpha (.871) reveals that the scale of operational performance is highly reliable. The result of EFA for operational performance reflects that only one dimension was extracted and all items strongly load on that dimension. Therefore, the discriminate validity of performance is supported by the result.

4. Results

Before analyzing data, mean of each item was calculated. Both Lean Management which is the independent variable and operational performance which is the dependent variable were presented by the mean of their items. But this is not done for the moderator which is national culture. The reason is that the hypotheses are formed and based on each dimension of national culture and each dimension has only one item. Therefore, there is no need to present moderator as a computed variable.

Table 4

Descriptive statistics and correlation

Variables Mean SD 1 2 3 4 5 6 7 8 9 1. LeanSoft 5,50 ,95 2. LeanHard 5,29 ,99 ,850** 3. LeanAll 5,40 ,93431 ,963** ,961** 4. NC_PD 64,18 19,81 ,070 ,172 ,126 5. NC_IN 41,04 28,36 ,061 -,065 -,002 -,921** 6. NC_MA 49,66 23,09 ,068 ,154 ,115 ,890** -,866** 7. NC_UA 42,86 17,27 -,166 -,244* -,213 -,679** ,683** -,522** 8. NC_LO 81,32 9,24 -,093 ,018 -,040 ,855** -,925** ,930** -,399** 9. NC_ID 39,87 19,77 -,087 -,185 -,141 -,935** ,930** -,959** ,739** -,883** 10.Performance 3,69 ,65 ,780** ,692** ,766** -,073 ,207 -,151 ,000 -,246* ,132 **. Correlation is significant at the 0.01 level (2-tailed).

In table 4, the descriptive statistics which include mean and standard deviation is displayed. More importantly the inter correlations (Pearson Correlation) between each construct are also presented in table 4. The construct Lean Management is divided into soft lean practices and hard lean practice. According to the results, all sub-dimensions of national culture are significantly correlating with each other (p<0.01). Similarly, the two sub-dimensions of Lean Management are also significantly correlating with each other (p<0.01). More importantly, in the main model the combined Lean construct (include both soft and hard practices) has a significant correlation with operational performance at the 0.01 level (r=.766). Look into detail, both hard lean practices and soft lean practice have a significant correlation with operational performance (p<0.01). And compare to hard lean practices (r=.692, p<0.01), the correlation between soft lean practices and operational performance is even more significant (r=.780, p<0.01). In addition, significant correlation relationship is also found between a sub-dimension of national culture and operational performance. The result shows that long term orientation is significantly correlating with operational performance at the 0.05 level.

4.2 Regression analysis: Lean Management and operational performance Hypothesis 1 is tested in this section by regression analysis. Regression analysis is a method for testing how dependent variable will change according to the change of independent variable (Huberty, 2003).

Since there are differences of the availability of people and capital resources between big and small organizations, compare to small organizations big companies are more likely to implement Lean Management (Shah & Ward, 2003). Therefore, company size might be a

Table 5

Regression Analysis

Model 1 Model 2

Step and variables B SE B SE

factor which influences Lean effectiveness and hence was selected as a control variable in this research. In order to test the relationship, two models were conducted. Model 1 include a control variable which is company size. In the second model, Lean Management as an independent variable is added. The outcomes of regression analysis between Lean Management and operational performance are displayed in table 5.

According to table 5, the R square of first model (R square=0.01) shows that the control variable (company size) has no significant influence on operational performance. More importantly, the results of model 2 shows that there is a significant positive relationship between Lean Management and operational performance (β=0.54, p<0.001). And the R square of second model is 0.60 which means the combination of Lean Management and company size can account for 60% of the variation in operational performance. These results reveal that the hypothesis 1 is supported. In other words, the increase of the implementation level of Lean Management will lead to the increase of operational performance of organizations.

4.3 Regression analysis: the moderating effects of national culture.

In this section, the moderating effect of each dimension of national culture is tested by conducting new regression analyses. In order to avoid multicollinearity in moderation test, the value of independent variable which is Lean Management and moderators which are the sub-dimensions of national culture were standardized before doing the regression analysis. After that, the interaction variables were created by computing the product of the mean of Lean Management, which is sum-variable, and each sub-dimensions of national culture. In the end, six interaction variables were created, named Lean_X_MA, Lean_X_IN, Lean_X_PD, Lean_X_UA, Lean_X_ID and Lean_X_LO respectively. The results are displayed in the tables below.

Table 6

Moderating Test - Masculinity

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

R square 0.01 0.66 0.68

∆ R square 0.65*** 0.02*

*** p<.001 ** p<.01 * p<.05

Firstly, the result of moderating test for masculinity is showed in table 6. The control variable, which is company size, is included in the first model. In model 2, the standardized variables which include Lean Management and masculinity are included. Model 3 includes the interaction variable which is the product of two standardized variables. According to the second model, both Lean Management (β=0.55, p<0.001) and masculinity (β=-0.12, p<0.01) significantly correlated to operational performance. More importantly, model 3 shows that there is a significantly moderating effect of masculinity on the relationship between Lean Management and operational performance (β=0.09, p=0.03). That means the positive impact of Lean Management on operational performance is positively influenced by the level of masculinity. This moderating effect is showed by figure 3.

Figure 3

Secondly, table 7 presents the outcome of moderation test for individualism. According to model 2, there is a significant relationship between individualism and operational performance (β=0.10, p<0.05). Model 3 shows that the moderating effect of individualism is not significant (β=-0.07, p=0.09), which means that the relationship between Lean Management and operational performance is not influenced by individualism. Therefore, hypothesis 3 is rejected.

Table 7

Moderating Test - Individualism

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

Intercept 3.85 0.20 3.80 0.13 3.77 0.13 Control Company size -0.07 0,09 -0.07 0.05 -0.06 0.05 Main effects Lean Management 0.53*** 0.05 0.56*** 0.05 Individualism 0.10* 0.04 0.10* 0.04 Two-way interaction Lean_X_IN -0.07 0.04 R square 0.01 0.64 0.66 ∆ R square 0.63*** 0.02 *** p<.001 ** p<.01 * p<.05

The results of moderating test for power distance is displayed by table 8. The significant relationship between power distance and operational performance is showed by model 2 (β=-0.09, p<0.05). But more importantly, model 3 shows that the moderating effect of power distance is significant (β=0.10, p=0.03). This moderating effect is displayed by figure 4.

Table 8

Moderating Test - Power Distance

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

Lean_X_PD 0.10* 0.04 R square 0.01 0.63 0.66 ∆ R square 0.62*** 0.03* *** p<.001 ** p<.01 * p<.05 Figure 4

Figure 4 reveals that when Lean Management is not implement or the implementation level is very low, the operational performance of service sectors is better in low power distance cultures. However, when Lean Management is highly implemented, the operational performance has no difference between high power distance culture and low power distance culture. In other words, the negative effect of power distance on performance is mitigated by Lean Management. Figure 4 clearly shows that compare to low power distance culture, the positive relationship between Lean Management and operational performance is stronger in high power distance culture. Therefore, the hypothesis 4 is supported.

performance (β=-0.07, p=0.09). That means the positive impact of Lean Management on operational performance will not be influenced by the level of uncertainty avoidance. Therefore, the hypothesis 5 is rejected.

Table 9

Moderating Test - Uncertainty Avoidance

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

Intercept 3.85 0.20 3.84 0.13 3.87 0.12 Control Company size -0.07 0,09 -0.10 0.05 -0.10 0.06 Main effects Lean Management 0.56*** 0.05 0.61*** 0.06 Uncertainty Avoidance 0.08* 0.04 0.08* 0.04 Two-way interaction Lean_X_UA -0.07 0.10 R square 0.01 0.63 0.65 ∆ R square 0.62*** 0.02 *** p<.001 ** p<.01 * p<.05

The moderating test for indulgence was conducted and the result is displayed in table 10. Model 2 shows that indulgence (β=0.12, p<0.01) have significant relationship with operational performance. On the other hand, the model 3 shows that there is a significantly negative moderating effect of indulgence on the relationship between Lean Management and operational performance (β=-0.10, p=0.02). That means the positive impact of Lean Management on operational performance is negatively influenced by the level of indulgence. The relationship is showed by figure 5.

Table 10

Moderating Test - Indulgence

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

Two-way interaction Lean_X_ID -0.10* 0.04 R square 0.01 0.66 0.69 ∆ R square 0.65*** 0.03* *** p<.001 ** p<.01 * p<.05 Figure 5

According to figure 5, when the implementation level of Lean Management is low, the operational performance of service sectors is better in high indulgence cultures. In high implementation level of Lean Management context, however, the difference of operational performances between high indulgence context and low indulgence context is very small. The positive effect of indulgence on operational performance is mitigated by Lean Management. The positive relationship between Lean Management and operational performance is stronger in low indulgence context rather than high indulgence context. Hence, the hypothesis 6 is supported.

Table 11

Moderating Test - Long Term Orientation

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE

Intercept 3.85 0.20 3.80 0.13 3.79 0.13

Control

Company size -0.07 0,09 -0.07 0.05 -0.06 0.06

Main effects

Long term orientation -0.10* 0.04 -0.10* 0.04 Two-way interaction Lean_X_LO 0.04 0.04 R square 0.01 0.64 0.65 ∆ R square 0.63*** 0.01 *** p<.001 ** p<.01 * p<.05

Last but not least, the result of moderating test for long term orientation is showed by table 11. According to model 2, there is a significant relationship between long term orientation and operational performance (β=-0.10, p<0.05). Model 3 reveals that the moderating effect of long term orientation is not significant (β=0.04, p=0.27), which means that the relationship between Lean Management and operational performance is not influenced by long term orientation. Therefore, hypothesis 7 is rejected.

Additional analysis

positively moderates the relationship between soft lean practices and operational performance (β=-0.09, p=0.04). However, individualism has no moderating effect on the relationship between Lean Management and operational performance. The possible reasons for that are discussed in discussion part.

5. Discussion and limitations

Firstly, this research argues that Lean Management has positive impact on the operational performance of service sectors and then tests the effectiveness of Lean Management in service sectors. The result shows that Lean Management does positively improve the performance of service sectors and this finding is in line with the results of previous researches which focuses service sectors (Ahlstrom, 2004; Apte & Goh, 2004; Stentoft et al., 2011; Radnor, 2010; Bhatia & Drew, 2006). Secondly, this paper argues that each sub-dimension of national culture has moderating effect on the effectiveness of Lean Management and six corresponding hypotheses have been made. In the end, the moderating effect of three sub-dimensions of national culture has been proved. More specifically, masculinity and power distance positively moderate the relationship between Lean Management and operational performance of service sector and indulgence negatively moderates the relationship between Lean Management and performance of service sector. According to the findings, the effectiveness of Lean Management should be best in the culture with high level of masculinity, power distance and low indulgence level. Surprisingly, we found that Japanese culture is highly compatible with this profile. Japan has extremely high masculinity level and relatively high power distance level. Moreover, indulgence of Japan is also in a low level, especially compare with western countries. This unexpected finding partially explains that why the effectiveness of Lean Management is remarkably good in Japan.

As described earlier, this paper found that masculinity and power distance positively moderate the relationship between Lean Management and operational performance of service sector. But it does not mean that masculinity and power distance can positively improve the effectiveness of Lean Management. And the performance of service sectors in high Lean Management level is not necessarily better in high masculinity culture than low masculinity culture. This is also applied to power distance. These could be found in figure 3 and figure 4. The figures clearly show that masculinity and power distance positively moderate the relationship between Lean Management and operational performance by reducing the performance in low lean context rather than improving the performance in high lean context. Similar for indulgence but just in the opposite side. Although indulgence negatively moderates the relationship between Lean Management and operational performance of service sector, it does not necessarily mean that the effectiveness of Lean Management is worse in high indulgence context (see figure 5). By contrast, the average performance of service sector is better in high indulgence context rather than low indulgence context. And indulgence negatively moderates the relationship between Lean Management and operational performance by improving the performance in low lean context rather than reducing the performance in high lean context. Therefore, managers of service sectors should avoid the pitfalls that take it for granted thinking high masculinity or power distance context could positively improve the effectiveness of Lean Management. Actually the average performance of service sectors is even worse in high masculinity and power distance culture context.

difference of performance between different national cultural contexts. Therefore, in order to reduce the negative influences of national culture on the effectiveness of Lean Management, increasing the implementation level of Lean Management is the solution. This is the second useful suggestion for managers.

Interestingly, although the moderating effect of national culture is not found on the relationship between hard lean practices and operational performance, additional analysis reveals that it does exist on the relationship between soft lean practices and operational performance. All three dimensions of national culture (masculinity, power distance and indulgence) which been found have moderating effect on the effectiveness of combined Lean Management also have moderating effect on the effectiveness of soft lean practices. Actually the moderating effect is even more significant in soft lean practices. This suggests that in service industry, national culture might be more interrelated with soft lean practices rather than hard lean practices. On the other hand, another unexpected finding is that individualism positively moderates the relationship between soft lean practices and operational performance in service sectors. This moderating effect is not exist when using combined Lean Management which includes both hard and soft lean practices. In addition, individualism also has no moderating effect on the relationship between hard lean practices and operational performance. These findings suggest that hard lean practices probably mitigate the moderating effect of these dimensions of national culture on the relationship between soft lean practices and operational performance in the context of service sector. The effectiveness of Lean Management in manufacturing industry has already been widely proved in literature (e.g., Sakakibara et al., 1997; Sohal & Egglestone, 1994; Cua et al., 2001; Taj & Morosan, 2011; Chavez et al., 2015; Filho et al., 2016). Recent years the effectiveness and applicability of Lean Management in service sector which include both public and private are also gained some attentions in literature (e.g., Ahlstrom, 2004; Apte & Goh, 2004; Stentoft et al., 2011; Radnor, 2010; Bhatia & Drew, 2006; Castaldi et al., 2016). Although Kull et al (2014) and Larteb et al (2015) studied the moderating effect of national culture on lean effectiveness in manufacturing industry, there were no studies testing the moderating effect of national culture on lean effectiveness in the context of service sector before. This research contributes to the research field by filling this gap. There is the moderating effect of three dimensions (masculinity, power distance and indulgence) of national culture exists on lean effectiveness in service sector.

5.2 Limitations and future research

more than 150 valid responses were got from four different countries, they are not evenly divided in four countries (It has to mention that 150 is not the ideal number but it is acceptable for basic researches). For example, less than 5 responses are from Belgium or Germany but more than 100 responses are from China. Therefore, in order to reduce the big differences of response number between different countries, the responses from China have to be cut. In the end, only 71 responses in total left. The small sample size might be a limitation of this research. One suggestion for future research is to getting a bigger sample size and the responses are evenly divided in each countries. This could make the results and conclusions more persuasive, convinced and most importantly, more reliable.

On the other hand, the data is only collected from one Asia country and three European countries. The national cultures of North American countries, South American countries and African countries are not included in the database. If the data of these countries are also included in the future research, more interesting and useful results might be found and make the conclusion more valid.

Finally, the ownership of the service sectors is not divided in this research, because most of the Chinese respondents are from public sectors while basically all of the European respondents are from private sectors. Future studies are suggested to divide the data into different ownerships and further explore the variance of moderating effects of national culture on lean effectiveness between different ownerships.

6. Conclusion

Lean Management is using globally by more and more organizations and Lean Management is also transforming from the approach which was especially designed for manufacturing world to the approach which could be widely used in many different sectors. These realities reveal that it is important and meaningful to investigate and understand the applicability of Lean Management on different industries and also the influences of different national culture on lean effectiveness.

important to Lean Management. Furthermore, these findings also prove that the moderating effect of national culture exists in the context of service industry, hence provide a new insight and perspective about culture issues of Lean Management to literature and managers.

References

Agarwal, R., Green, R., Brown, P. J., Tan, H., & Randhawa, K. (2013). Determinants of quality management practices: an empirical study of New Zealand manufacturing firms. International Journal of Production Economics, 142(1), 130-145.

Apte, U. M., & Goh, C. H. (2004). Applying lean manufacturing principles to information intensive services. International journal of services technology and management, 5(5-6), 488-506.

Ahlstrom, P. (2004). Lean service operations: translating lean production principles to service operations. International Journal of Services Technology and Management, 5(5-6), 545-564.

Al-Najem, M., Dhakal, H., & Bennett, N. (2012). The role of culture and leadership in lean transformation: a review and assessment model. International Journal of Lean Thinking, 3(1), 119-138.

Andrés-López, E., Gonzalez-Requena, I., & Sanz-Lobera, A. (2015). Lean service: reassessment of lean manufacturing for service activities. Procedia engineering, 132, 23-30.

Amble, B. (2006). Don't be too assertive. Management-issues. Retrieved 24 January, 2018, from http://www.management-issues.com/news/3709/dont-be-too-assertive/

Bhatia, N., & Drew, J. (2006). Applying lean production to the public sector. The McKinsey Quarterly, 3(1), 97-98.

Bortolotti, T., Boscari, S., & Danese, P. (2015). Successful lean implementation: Organizational culture and soft lean practices. International Journal of Production Economics, 160, 182-201.

Cua, K. O., McKone, K. E., & Schroeder, R. G. (2001). Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. Journal of operations management, 19(6), 675-694.

Chavez, R., Yu, W., Jacobs, M., Fynes, B., Wiengarten, F., & Lecuna, A. (2015). Internal lean practices and performance: The role of technological turbulence. International Journal of Production Economics, 160, 157-171.

Cua, K. O., McKone, K. E., & Schroeder, R. G. (2001). Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. Journal of operations management, 19(6), 675-694.

Cagliano, R., Caniato, F., Golini, R., Longoni, A., & Micelotta, E. (2011). The impact of country culture on the adoption of new forms of work organization. International Journal of Operations & Production Management, 31(3), 297-323.

Chen, Z., & Hua Tan, K. (2013). The impact of organization ownership structure on JIT implementation and production operations performance. International Journal of Operations & Production Management, 33(9), 1202-1229.

Castaldi, M., Sugano, D., Kreps, K., Cassidy, A., & Kaban, J. (2016). Lean philosophy and the public hospital. Perioperative Care and Operating Room Management, 3, 25-28. Country comparison. Retrieved October 22, 2017, from Hofstede-Insights: https://www.hofstede-insights.com/country-comparison/

Damrath, F. (2012). Increasing competitiveness of service companies: developing conceptual models for implementing Lean Management in service companies.

DeHart-Davis, L., Marlowe, J., & Pandey, S. K. (2006). Gender dimensions of public service motivation. Public administration review, 66(6), 873-887.

Erridge, A., & Murray, J. G. (1998). The application of lean supply in local government: the Belfast experiments. European Journal of Purchasing & Supply Management, 4(4), 207-221.

Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of operations management, 28(1), 58-71.

Godinho Filho, M., Ganga, G. M. D., & Gunasekaran, A. (2016). Lean manufacturing in Brazilian small and medium enterprises: implementation and effect on performance. International Journal of Production Research, 54(24), 7523-7545.

Guimarães, M., & Crespo de Carvalho, J. (2012). Lean healthcare across cultures: state-of-the-art. American International Journal of Contemporary Research, (6), 187-206. House, R. J., Hanges, P. J., Javidan, M., Dorfman, P. W., & Gupta, V. (Eds.). (2004). Culture, leadership, and organizations: The GLOBE study of 62 societies. Sage publications.

Hofstede, G. (1984). Culture's consequences: International differences in work-related values (Vol. 5). sage.

Hofstede, G. (1991). Cultures and Organizations: Software of the Mind. NewYork: McGraw-Hill.

Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online readings in psychology and culture, 2(1), 8.

Huberty, C. J. (2003). Multiple correlation versus multiple regression. Educational and Psychological Measurement, 63(2), 271-278.

Hopp, W. J., & Spearman, M. L. (2004). To pull or not to pull: what is the question?. Manufacturing & service operations management, 6(2), 133-148.

Ismail Salaheldin, S. (2005). JIT implementation in Egyptian manufacturing firms: some empirical evidence. International Journal of Operations & Production Management, 25(4), 354-370.

Krings, D., Levine, D., & Wall, T. (2006). The use of" lean" in local government. PUBLIC MANAGEMENT-LAWRENCE THEN WASHINGTON-, 88(8), 12.

Kull, T. J., & Wacker, J. G. (2010). Quality management effectiveness in Asia: The influence of culture. Journal of operations management, 28(3), 223-239.

Liker, J. K. (2004). The toyota way. Esensi.

Lozeau, D., Langley, A., & Denis, J. L. (2002). The corruption of managerial techniques by organizations. Human relations, 55(5), 537-564.

Larteb, Y., Haddout, A., & Benhadou, M. (2015). National culture impact on lean leadership and lean manufacturing maturity-Case study of multinationals based in Morocco. International Journal of Research in Engineering and Technology, 4(2), 542-547.

Love, P. E., Davis, P. R., Edwards, D. J., & Baccarini, D. (2008). Uncertainty avoidance: public sector clients and procurement selection. International Journal of Public Sector Management, 21(7), 753-776.

Liker, J., & Rother, M. (2011). Why Lean Programs Fail. Lean Enterprise Institute. Lee, S. M., Olson, D. L., Lee, S. H., Hwang, T., & Shin, M. S. (2008). Entrepreneurial applications of the lean approach to service industries. The Service Industries Journal, 28(7), 973-987.

Myers, M. D., & Tan, F. B. (2003). Beyond models of national culture in information systems research. Advanced topics in global information management, 2, 14-29.

Negrão, L. L. L., Godinho Filho, M., & Marodin, G. (2017). Lean practices and their effect on performance: a literature review. Production Planning & Control, 28(1), 33-56.

Nunnally, J. C., & Bernstein, I. H. (1979). Psychometric theory. PsycCRITIQUES, 24, 275– 280.

Naor, M., Linderman, K., & Schroeder, R. (2010). The globalization of operations in Eastern and Western countries: Unpacking the relationship between national and organizational culture and its impact on manufacturing performance. Journal of operations management, 28(3), 194-205.

Ohno, T. (1988). Toyota production system: beyond large-scale production. crc Press. OECD. (2011). Employee structure 2010. Austrian Federal Economic Chamber.

Pay, R. (2008). Everybody’s jumping on the lean bandwagon, but many are being taken for a ride. Industry Week, 5.

Pagell, M., Katz, J. P., & Sheu, C. (2005). The importance of national culture in operations management research. International Journal of Operations & Production Management, 25(4), 371-394.

Rahman, S. U., & Bullock, P. (2005). Soft TQM, hard TQM, and organisational performance relationships: an empirical investigation. Omega, 33(1), 73-83.

Radnor, Z., & Walley, P. (2008). Learning to walk before we try to run: adapting lean for the public sector. Public money and management, 28(1), 13-20.

Radnor, Z. (2010). Transferring lean into government. Journal of Manufacturing Technology Management, 21(3), 411-428.

Radnor, Z., & Johnston, R. (2013). Lean in UK government: internal efficiency or customer service?. Production Planning & Control, 24(10-11), 903-915.

Radnor, Z. J. (2010). Review of business process improvement methodologies in public services. AIM Research.

Shah, R., & Ward, P. T. (2003). Lean manufacturing: context, practice bundles, and performance. Journal of operations management, 21(2), 129-149.

Sohal, A. S., & Egglestone, A. (1994). Lean production: experience among Australian organizations. International Journal of Operations & Production Management, 14(11), 35-51.

Staudacher, A. P., & Tantardini, M. (2008). Lean production implementation: a survey in Italy. Dirección y Organización, (35), 52-60.

Shah, R., & Ward, P. T. (2007). Defining and developing measures of lean production. Journal of operations management, 25(4), 785-805.

Samson, D., & Terziovski, M. (1999). The relationship between total quality management practices and operational performance. Journal of operations management, 17(4), 393-409. Suzuki, H. (1976). Age, seniority and wages. Int'l Lab. Rev., 113, 67.

Scherrer-Rathje, M., Boyle, T. A., & Deflorin, P. (2009). Lean, take two! Reflections from the second attempt at lean implementation. Business horizons, 52(1), 79-88.

Stentoft Arlbjørn, J., Vagn Freytag, P., & de Haas, H. (2011). Service supply chain management: A survey of lean application in the municipal sector. International Journal of Physical Distribution & Logistics Management, 41(3), 277-295.

Scorsone, E. A. (2008). New development: what are the challenges in transferring Lean thinking to government?. Public Money and Management, 28(1), 61-64.

Sakakibara, S., Flynn, B. B., & Schroeder, R. G. (1993). A framework and measurement instrument for just-in-time manufacturing. Production and Operations Management, 2(3), 177-194.

Seagrave, S. (1995). Lords of the rim: The invisible empire of the overseas Chinese. Putnam Adult.

Sakakibara, S., Flynn, B. B., Schroeder, R. G., & Morris, W. T. (1997). The impact of just-in-time manufacturing and its infrastructure on manufacturing performance. Management Science, 43(9), 1246-1257.

The 6 dimensions of national culture. Retrieved November 18, 2017, from

Hofstede-Insights: https://www.hofstede-insights.com/models/national-culture/

Triandis, H. C. (1995). Individualism & Collectivism. Boulder, Colorado: Westview Press. Taj, S., & Morosan, C. (2011). The impact of lean operations on the Chinese manufacturing performance. Journal of manufacturing technology management, 22(2), 223-240.

Walton, M., & Rao, V. (2004). Culture and public action. Stanford University Press. Womack, J. P., & Jones, D. T. (2010). Lean thinking: banish waste and create wealth in your corporation. Simon and Schuster.

Wong, M. (2007). The role of culture in implementing lean production system. Advances in Production Management Systems, 413-422.

Wiengarten, F., Gimenez, C., Fynes, B., & Ferdows, K. (2015). Exploring the importance of cultural collectivism on the efficacy of lean practices: Taking an organisational and national perspective. International Journal of Operations & Production Management, 35(3), 370-391.

multi-country study. International Journal of Operations & Production Management, 31(5), 554-578.

Appendix

Lean Management

Soft-lean practices

Please indicate to what extent you agree/disagree with the following (circle one number): 1 strongly disagree, 2 disagree, 3 slightly disagree, 4 neutral, 5 slightly agree, 6 agree, and 7 strongly agree.

Multi-function employees

MFE1 Our employees receive training to perform multiple tasks

MFE2 The longer an employee has been at this organization, the more tasks they learn to perform

MFE3 Employees are cross-trained at this organization, so that they can fill in for others, if necessary

Small group problem solving

SGPS1 Our organization forms teams to solve problems

SGPS2 In the past three years, many problems have been solved through small group sessions

SGPS3 Problem solving teams have helped improve service processes at this organization

SGPS4 Employee teams are encouraged to try to solve their own problems, as much as possible

Continuous improvement

CI1 If we do not constantly keep improving and learning, our performance will suffer in the long term

CI2 Continuous improvement makes our performance a moving target, which is difficult for competitors to attack

CI3 We believe that improvement of a process is never complete; there is always room for more incremental improvement

TMLQ1 All major departments heads accept their responsibility for quality TMLQ2 The top priority in evaluating management is quality performance TMLQ3 Our management creates and communicates a vision focused on quality

improvement

TMLQ4 Our management is personally involved in quality improvement projects

Hard-lean practices

Please indicate to what extent you agree/disagree with the following (circle one number): 1 strongly disagree, 2 disagree, 3 slightly disagree, 4 neutral, 5 slightly agree, 6 agree, and 7 strongly agree.

Autonomous maintenance

AM1 Employees are able to detect and treat abnormal service conditions AM2 Employees inspect and monitor the performance of their own AM3 Basic check of equipment is done by employees

Statistical process control

SPC1 A large percentage of the services are currently under statistical quality control

SPC2 We make extensive use of statistical techniques to reduce variance in services

SPC3 We use charts to determine whether our services are in control SPC4 We monitor our services using statistical process control Cleanliness and organization

CO1 Our organization emphasizes putting all tools and equipment in their place CO2 We take pride in keeping our organization neat and clean

CO3 Our organization is kept clean at all times Design for quality

DQ1 Departments work in a coordinated manner in the service development process

DQ2 The quality of new services is emphasized, compared with other objectives, such as costs or schedule

DQ3 Service specification and procedures for new services are clear DQ4 Implementation and effectiveness are considered in the service design

process