Master Thesis MSc Technology & Operations Management

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Master Thesis

MSc Technology & Operations Management

“Lean management performance considering organizational

and national culture”

Wiebren van de Schootbrugge – S2770016 Supervisor: Dr. ir. T. Bortolotti Second assessor: Dr. N.B. Szirbik

Abstract

Lean Management (LM) is a strategy for improving the competitiveness of industrial firms. The LM concept is often measured in the OM literature. Not only to find what practices belong to the LM concept but also to find what its relation is with performance. More resent studies have given voice to the importance of the moderating effect of both national culture (NC) and organizational culture (OC) on lean effectiveness. This research contributes to this field of research by using GLOBE’S cultural dimensions to measure bot the moderating effect for NC as well as OC. The results achieved from the research are often non-significant, but some cultural dimensions have moderating effects on LM. This shows the importance for managers, because they need to consider these moderating effects when implementing or using LM in different countries and/or different cultures.

Keywords

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Lean management (LM) is a strategy for improving the competitiveness of industrial firms, and because of that the correct implementation of lean management is crucial (Womack, Jones, and Roos 1990; Holweg 2007). A lot of companies try to implement these ideas of lean based on the success of the Toyota production system (Womack, Jones, and Roos 1990). The popularity among companies is understandable because research shows that lean companies outperform non-lean companies in terms of performance (Womack and Jones 1996; Swamidass 2007; Mackelprang and Nair 2010).

However, despite of many attempts the majority of the companies do not succeed with their lean programmes (Lucey, Bateman, and Hines 2005; Pay 2008; Schonberger 2008). According to Kotter (1995); Beer and Nohria (2001) and Aiken and Keller (2009) it has been reported that two out of every three organisational change projects fail. This results in a negative return on the investment made for the lean program, which is negative in itself, but it also hinders future lean implementation which can cause more severe damage to long-term competitiveness (Netland, 2015).

In relation with the implementation of LM, organizational culture (OC) can be an important influencer of the success of LM because it is widely considered to be one of the most significant factors in bringing about organizational change and modernizing (Claver et al. 1999; Kloot and Martin 2007; Mannion, Davies, and Marshall 2005; Morgan and Ogbonna 2008; Waterhouse and Lewis 2004). Just as OC, national culture (NC) can have a significant impact on the implementation of LM operations and therefore its performance (Hofer et al., 2011). Therefore, this research focusses on two critical aspects in LM and its relation with performance: OC and NC (Bortolotti et al., 2015; Naor et al., 2010; Gordon and

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4 of Wiengarten et al., (2015) also states that there is a moderating effect from OC collectivism on the relation between LM and performance. Researching the moderating effect of both NC and OC form an interesting topic of research because they have been researched apart from each other but not often together. Naor et al., (2010) and Wiengarten et al., (2015) are the only two well-known articles that researched them both. These researches showed that OC can be the cause for poor effectiveness of LM (Liker, 2004; Sim and Rogers, 2009; Atkinson, 2010; Liker and Rother, 2011). A more recent study by Bortolotti et al., (2015) showed that OC is an important factor in the implementation of lean and that some OC dimensions are more important than others. The article of Bortolotti et al., (2015) also sees a further opportunity for research into NC because of the interplay between OC and NC based on the work of Naor et al., (2010). This point of view is supported by the article of Kull, Yan, Liu and Wacker (2014), they state that certain key NC dimensions are useful in predicting LM’s effectiveness. Until now only Wiengarten, Gimenez, Fynes and, Ferdows (2015) researched the moderating role of both OC and NC on lean performance but they only focussed on one cultural dimension of collectivism versus individualism.

The aim of this research is to investigate if there is a relation between LM and performance which has already been researched many times in OM literature, for example by Womack and Jones (1996), Swamidass (2007) and Mackelprang and Nair (2010). What is new however in this research is that also the moderating effect of OC and NC on the relation between LM and performance will be investigated based on the previous research of Kull and Wacker (2010); Wiengarten et al., (2015) and Kull et al., (2014). They researched this moderating effect, but only used one dimension or only focussed on NC.

The next chapter discusses the literature background on the aspects of LM,

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6 Literature review and hypotheses creation

Lean management (LM)

Shah and Ward (2007) tried to define LM because of the many different definitions provided and because there was no consensus about a definition. Eventually they defined LM as an integrated socio-technical system which main objective is to eliminate waste by currently reducing or minimizing supplier, customer and internal variability. This definition alone already shows the many facets of lean production. To come to a definition of what this research will see as LM, a short recap of existing literature is needed to explain choices. There are many articles on the measurement of lean production but among others the one of Shah and Ward (2003) is the most comprehensive and used. Therefore, this research also uses the measures that Shah and Ward (2003) have developed for lean manufacturing. They operationalized the different measures of LM as four different bundles. These bundles are just-in-time (JIT), total quality management (TQM), total preventive maintenance (TPM), and human resource management (HRM). They limit their analysis to four bundles that are oriented internally to reflect a firm’s approach to managing its manufacturing operation. For this research, only three bundles are used to cover the area of LM. To come to this the article of Bortolotti et al., (2015) on the sand cone model is used. In that article it is

explained that every organization should have a fitness bundle for further implementing lean practices such as TQM and JIT. Fitness adds an important dynamic dimension to lean. A ﬁt manufacturer has a foundation of strong practices which allow it to stay lean under changing circumstances and over longer periods of time, making it adaptable to a dynamic

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7 Organizational culture (OC)

In the current literature OC is defined in multiple ways, but in this research the definition of Schein (1985, p.9) is used. Schein (1985, p. 9) defines OC as “A pattern of shared basic assumptions that the group learned as it solved its problems of external adaptation and internal integration, that has worked well enough to be considered valid and, therefore, to be taught to new members as the correct way to perceive, think, and feel in relation to those problems”. That is, culture refers to visible artefacts of an organization and embraces beliefs, values and attitudes. This definition is used by McDermott, Gregory and Stock (1999);

Prajogo and McDermott (2005); Stock, McFadden and Gowen (2007); Losonci, Kása,

Demeter, Heidrich and Jenei (2017). All their researches contain OC, and they research it in relation to TQM, lean and reductions of errors. This shows that the definition is used in relation to improvement programs and is therefore relevant for this research. Based on an in-depth literature review by Jung et al., (2009) it is concluded that there exist more than 100 dimensions to measure OC. The various measurement models are the ones by Quinn and Rohrbaugh (1983), Schein (1984), Hofstede et al. (1990), O’Reilly et al. (1991), and House et al. (2004). After the following part of NC, the choice of which measurement model is used in this research will be explained because the aim is to use the same method to measure both OC and NC.

National Culture (NC)

The current literature that researches the influence from NC on lean implementation or performance uses two different definitions that are more or less the same. However, for the sake of clarity only one is mentioned in this research. In this research the most appropriate and newest is used. According to Hofstede and Hofstede (2005), national culture is the ‘collective programming of the mind’ that makes one nation distinctively different from another. This definition shows that NC is a behaviour that a certain group of people share that are distinct from another group. National cultures are extremely hard to change

because they are deeply ingrained in their societies (Krafcik 1988; Womack, Jones, and Roos 1990). Over the last three decades, several scholars have developed frameworks for

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8 consensus about which method is the best to use in which situation as researchers still use both methods (Netland, 2016; Pakdil and Leonard, 2017; Kull, Yan, Liu and Wacker, 2014; Wiengarten et al., 2015; Naor et al., 2010; Vecchi and Brennan, 2011; Caglian et al., 2011; Pagell, Katz and Sheu, 2005). However, in line with Bortolotti et al., (2015), Naor et al., (2010) and Kull et al., (2014) this research will use the GLOBE dimensions for both OC and NC because the GLOBE project explores the cultural dimensions at the societal and

organizational levels. Further it concludes that the set of nine dimensions can examine both NC and OC (House et al., 2004, chapter 5) and this helps a lot with the research that will be done. The definitions of the nine cultural dimensions are shown in Table 1.

Table 1: Definitions of GLOBE cultural dimensions (House et al., 2004, pp. 11–13).

Power Distance (PD) The degree to which members of an organization or society expect and agree that power should be stratiﬁed and concentrated at higher levels of an organization or government.

Institutional Collectivism (IC) The degree to which organizational and societal institutional practices encourage and reward collective distribution of resources and collective action.

In-group Collectivism (IG) The degree to which individuals express pride, loyalty, and cohesiveness in their organizations or families.

Future Orientation (FO) The degree to which individuals in organizations or societies engage in

future-oriented behaviours such as planning, investing in the future, and delaying individual or collective gratiﬁcation.

Performance Orientation (PO)

The degree to which an organization or society encourages and rewards group members for performance improvement and excellence.

Gender Egalitarianism (GE) The degree to which an organization or society minimizes gender role differences while promoting gender equality.

Assertiveness (AS) The degree to which individuals in organizations or societies are assertive, confrontational, and aggressive in social relationships.

Uncertainty Avoidance (UA) The extent to which members of an organization or society strive to avoid uncertainty by relying on established social norms, rituals, and bureaucratic practices.

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9 Lean management (LM) and performance

Even though in the introduction it was stated that despite the many attempts the majority of the companies do not succeed with their lean programmes (Lucey, Bateman, and Hines 2005; Pay 2008; Schonberger 2008), and that it has been reported that two out of every three organisational change projects fail (Kotter, 1995; Beer and Nohria, 2001; Aiken and Keller, 2009), the majority of empirical studies supports the overall positive impact of LM on a firm’s operational performance (Moyano-Fuentes and Sacristán-Díaz, 2012). The main benefits consist of reducing process variability, scraps, and rework time, which in turn reduce production costs and lead times and increase process flexibility and quality

conformance (Bortolotti et al., 2015). Because LM is divided in four different bundles These four different bundles (JIT, TQM, TPM, HRM) also can all have their different influence on performance. Shah and Ward (2003) where the first to take all the four bundles of LM together to find out what the influence is on performance and how the various bundles might be intertwined with each other. The last suggestion comes from the point of view from researchers that argue that a lean production system is an integrated manufacturing system requiring implementation of a diverse set of manufacturing practices (e.g. Womack and Jones, 1996). The results of Shah and Ward (2003) suggest that each of the bundles of lean practices under study contribute substantially to the operating performance of plants. Shah and Ward (2003) were the first to report the ﬁnding that each of the bundles

contributes to performance, this result may seem intuitive but in fact, Flynn et al. (1995) report that JIT and common infrastructural practices have a positive effect on performance, but that TQM has no signiﬁcant effect. On the other hand, McKone et al. (2001) ﬁnd that JIT, TQM and TPM all contribute to their weighted performance index. For this research the new proposed lean bundles that have been mentioned before are used. These three lean bundles are the fitness, JIT and the TQM bundles proposed by Bortolotti et al., (2015). Based on the findings of Shah and Ward (2003), Moyano-Fuentes and Sacristán-Díaz (2012) and Bortolotti et al., (2015) the first three hypotheses for this research are provided.

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10 Organizational culture (OC), National culture (NC), Lean management (LM) and performance The role of OC in determining organization success has been researched since the 80s (Ouchi,1981; Deal and Kennedy,1982; Peters and Waterman,1982), and have provided empirical evidence on the relationship between OC and performance (Gordon and DiTomaso,1992; Lee and Yu, 2004; Nikolic et al., 2011; Prajogo and McDermott, 2011). Research has also shown that organisational culture can affect operations in various forms (Bates et al., 1995). Differences in organisational culture are mainly expressed through differences at the level of practices while the core of organisational culture is conceptualised through its values (Hofstede et al., 1990). Most of these studies have focussed on one or two of the bundles of Shah and Ward (2003). Much of the research was on TQM, to achieve superior performance (Detert et al., 2000; Nahm et al., 2004; Prajogo and McDermott, 2005; Naor et al., 2008; Patel and Cardon, 2010; Baird et al., 2011; Narasimhan et al., 2012).

However, knowing something about TQM and OC does not say anything about the other lean bundles and OC because there isn’t a universal OC proﬁle that always guarantees the success (Denison and Mishra, 1995; Fey and Denison, 2003; Prajogo and McDermott, 2011). Researchers have defended the existence of different and heterogeneous ideal OC proﬁles, each working as a driver for a particular management program or improvement initiative (e.g., Detert et al., 2000). Even though most of the research that has been done sees OC as an antecedent of LM, this research will take the point of view of Wiengarten et al., (2015) which states that collectivism has a moderating effect on the relation between LM practices and performance. However, the article of Wiengarten et al., (2015) only takes IC into

account. Therefore, to support the statement that all cultural dimensions might have a moderating effect on the relation between LM practices and performance, the article of Kull and Wacker (2010) is used. Kull and Wacker (2010) did research into the influence the cultural dimensions have on the relation between quality practices and performance. They base their research on the observation of Lozeau et al., (2002) who state that an

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11 research they state that it would be good to also look at OC. Because of this empirical

evidence on the importance of NC and OC on LM and performance this study will research the moderating impact of eight out of the nine cultural dimensions of GLOBE (House et al., 2004). In line with other studies (Aksu, 2003; Kull and Wacker, 2010; Naor et al., 2010; Bortolotti et al., 2015), the gender egalitarianism dimension was not included in this study. The definitions of the nine cultural dimensions have been shown earlier in Table 1. Based on these definitions the following set of hypotheses specify the moderating effect of the GLOBE cultural dimensions on the relation between the three LM bundles and performance. This implies that for every cultural dimension six hypotheses are computed. Three for an OC-dimension on the three different bundles, the same holds for the NC-OC-dimension.

Power distance (PD): Following House et al., (2004) PD is high when the power inside a company is concentrated at higher levels and PD is low when power is divided to more lower levels. According to Rother (2009) individuals are expected to contribute to enhancing processes by detecting problems and suggesting improvements in firms that follow LM. As stated before, lower PD prefers employee participation in improvement and decision-making processes. Thus, we can state successful lean organizations are usually characterized by lower PD because they are likely to have a greater ability to identify and eliminate waste, and therefore improve operational performance through LM (Naor et al., 2008). Further substantiation to this point of view is given by Kull et al., (2014) who state that the more a culture values PD the less effective LM will be because employees are more reluctant to expose problems and because in high PD countries and plants the managers will most likely be the ones that do incremental changes even though they are not in day-to-day business. Thus:

H2a1: The impact of fitness practices on performance is stronger in plants that have lower PD.

H2a2: The impact of JIT practices on performance is stronger in plants that have lower PD. H2a3: The impact of TQM practices on performance is stronger in plants that have lower PD. H2a4: The impact of fitness practices on performance is stronger in countries that have lower PD.

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12 H2a6: The impact of TQM practices on performance is stronger in countries that have lower PD.

Institutional Collectivism (IC): According to Naor et al., (2010) scholars have argued that high institutional collectivism creates teamwork. Furthermore, team activities such as quality circles have been found to improve quality and decrease the number of defects (Flynn et al., 1994). Managerial beliefs encouraging collective actions such as teamwork and integration are necessary to obtain higher performance when applying, for example, time-based

manufacturing practices (Nahm et al., 2004), HRM (Patel and Cardon, 2010), and TQM (Baird et al., 2011). Furthermore, following Wiengarten et al., (2015) Lean practices such as cellular manufacturing, TPM, Kanban, pull production systems and the likes requires a

knowledgeable workforce that collectively understands the importance of lean and practices it. These practices require a collectivistic mindset with a long-term perspective. This includes the training and educating of the workforce about the challenges and benefits of these lean practices. Therefore, this research argues that a favourable NC and/or OC increases the efficacy of LM practices. Different said, a collectivistic culture leads to more effective and efficient LM practices and thus to better performance. Because the LM practices Wiengarten et al., (2015) mention are subdivided into different LM bundles, the following hypotheses are proposed:

H2b1: The impact of fitness practices on performance is stronger in plants that have higher IC.

H2b2: The impact of JIT practices on performance is stronger in plants that have higher IC. H2b3: The impact of TQM practices on performance is stronger in plants that have higher IC. H2b4: The impact of fitness practices on performance is stronger in countries that have higher IC.

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13 In-group collectivism (IG): People’s loyalty to their organizations and related values such as pride and cohesiveness can lead to more effective LM adoption. People in high IG cultures recognize the interdependence with each other and emphasize relatedness with groups (Naor et al., 2010). Duties and obligations are important determinants of social and

organizational behaviours in high IGC cultures, and a strong distinction is made between in-groups and out-in-groups (Gelfand et al., 2004). According to Kull et al., (2014) a high IG culture produces a positive impact on LM's effectiveness, because employees are more willing to share information in such companies and provide higher quality products. Also, a strong duty to improve in such a culture should result in commitment to process redesign and JIT. A lack of cooperation within the facility slows efforts toward throughput reduction, disrupting efﬁcient ﬂow and thus reducing delivery performance (Storch and Lim, 1999). Thus:

H2c1: The impact of fitness practices on performance is stronger in plants that have a higher IG.

H2c2: The impact of JIT practices on performance is stronger in plants that have a higher IG. H2c3: The impact of TQM practices on performance is stronger in plants that have a higher IG.

H2c4: The impact of fitness practices on performance is stronger in countries that have a higher IG.

H2c5: The impact of JIT practices on performance is stronger in countries that have a higher IG.

H2c6: The impact of TQM practices on performance is stronger in countries that have a higher IG.

Future orientation (FO): People in high FO cultures value long-term success and are prepared for potential disruptions. They have a strong propensity to save now and invest for the future (Ashkanasy et al., 2004). Cultures with high FO prefer strategic thinking, encourage knowledge acquisition, develop long-term objectives, and accept ﬂexible organizational structures (Kull and Wacker, 2010). A company’s philosophy promoting long-term thinking sustains a successful LM implementation (Liker, 2004; Achanga et al., 2006). In fact, Flynn et al. (1994) observed that a high FO supports continuous improvement, which in turn

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14 involved in TQM programs is characterized by a long-term orientation and strategic

approach to management and stressed the importance of these values to obtain successful results. A high FO culture increases the effectiveness of LM practices (Kull et al., 2014). Thus:

H2d1: The impact of fitness practices on performance is stronger in plants that have a higher FO.

H2d2: The impact of JIT practices on performance is stronger in plants that have a higher FO. H2d3: The impact of TQM practices on performance is stronger in plants that have a higher FO.

H2d4: The impact of fitness practices on performance is stronger in countries that have a higher FO.

H2d5: The impact of JIT practices on performance is stronger in countries that have a higher FO.

H2d6: The impact of TQM practices on performance is stronger in countries that have a higher FO.

Performance orientation (PO): A performance orientation encourages challenging goals and creates motivation to achieve bottom line results (Snell and Dean, 1994). Baird et al. (2011) found that companies that focused on results and had high performance expectations extensively implement TQM and achieve better performance. Lean ﬁrms often use incentives to direct employees’ behaviour toward lean goals (Fullerton and McWatters, 2002). Because training and development are more encouraged in high PO cultures, employees in such cultures are more open to learning and as feedback is given on time performance, employees in high PO cultures will be encouraged to seek further progress in reducing setup time, rather than be satisﬁed with one-time achievements (Kull et al., 2014) Therefore, a high PO culture increases the effectiveness of LM. Thus:

H2e1: The impact of fitness practices on performance is stronger in plants that have a higher PO.

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15 H2e4: The impact of fitness practices on performance is stronger in countries that have a higher PO.

H2e5: The impact of JIT practices on performance is stronger in countries that have a higher PO.

H2e6: The impact of TQM practices on performance is stronger in countries that have a higher PO.

Assertiveness (AS): AS is the degree that individuals are confident, confrontational and aggressively defend their positions (Hartog, 2004). Lower AS promotes the involvement of employees and encourages a willingness to share resources and information (Naor et al., 2010). Wincel and Kull (2013) claim that higher AS is likely to result in a less effective LM implementation. Kull and Wacker (2010) claim in their paper that AS negatively moderates the performance of QM in a facility. In the article of Kull et al., (2014) they further state that a high AS culture will reduce the effectiveness of LM. Thus:

H2f1: The impact of fitness practices on performance is stronger in plants that have lower AS. H2f2: The impact of JIT practices on performance is stronger in plants that have lower AS. H2f3: The impact of TQM practices on performance is stronger in plants that have lower AS. H2f4: The impact of fitness practices on performance is stronger in countries that have lower AS.

H2f5: The impact of JIT practices on performance is stronger in countries that have lower AS. H2f6: The impact of TQM practices on performance is stronger in countries that have lower AS.

Uncertainty avoidance (UA): People in a UA culture seek orderliness, consistency, structure, formalized procedures, and laws to cover situations in their daily lives (Triandis, 1989). Formal policies and speciﬁc procedures, which are valued in a high UA culture, resonate well with LM practices (Kull et al., 2014). These increase the effectiveness of waste reduction initiatives in reducing cost, speeding deliveries and enhancing qualities. All these are

constructs of the overall performance used in this research. To further state the moderating effect, Spear and Bowen (1999) and Liker (2004) state that higher UA promotes LM

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16 important for lean ﬁrms to face variations and unpredictable results, and thus are

recognized as the basis of an effective lean implementation that can lead to better performance. Thus:

H2g1: The impact of fitness practices on performance is stronger in plants that have higher UA.

H2g2: The impact of JIT practices on performance is stronger in plants that have higher UA. H2g3: The impact of TQM practices on performance is stronger in plants that have higher UA. H2g4: The impact of fitness practices on performance is stronger in countries that have

higher UA.

H2g5: The impact of JIT practices on performance is stronger in countries that have higher UA.

H2g6: The impact of TQM practices on performance is stronger in countries that have higher UA.

Human orientation (HO): Cultures with a high HO strongly recognize human rights,

egalitarianism, forgiveness, sensitivity, and situational uniqueness (Kull and Wacker, 2010). Individuals in a high HO culture are motivated primarily by a need for belonging or afﬁliation and are responsible for promoting the well-being of others (Kabasakal and Bodur, 2004). In a culture with high HO, the interests of others are important; welfare outweighs achievement; relations are important; and needs outweigh rewards (Kull and Wacker, 2010). This

behaviour is fundamental for successfully implementing lean, by supporting practices such as group problem solving, teamwork, and employee suggestions. These arguments suggest that high HO is a fundamental characteristic of successful lean plants that should not punish workers but value their contributions to achieve excellence (Bortolotti et al., 2015).

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17 H2h1: The impact of fitness practices on performance is stronger in plants that have a higher HO.

H2h2: The impact of JIT practices on performance is stronger in plants that have a higher HO. H2h3: The impact of TQM practices on performance is stronger in plants that have a higher HO.

H2h4: The impact of fitness practices on performance is stronger in countries that have a higher HO.

H2h5: The impact of JIT practices on performance is stronger in countries that have a higher HO.

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18 The schematic overview of the above stated hypotheses is shown in figure 1.

Figure 1: Conceptual model Methodology

To test the hypotheses the High-Performance Manufacturing (HPM) database is used. This is a database that was collected by an international team of researchers. The plants that participated in the survey are from various industries. They operate in: machinery, electronics and transportation sectors in ten different countries (Finland, US, Japan, Germany, Sweden, South Korea, Italy, Austria, Spain and China). These countries were selected because of their diversity of economic character, but also because of their diverse cultures, which is helpful for the current study. A couple of restrictions were put into place to make sure the data displayed the reality in that country. To this end, the research teams had to randomly select the plants from a list of manufacturing plants. An approximate equal amount of high performing and traditional manufacturing units was included. As a sort of control variable, the plants had to have at least 100 employees. Because the 100 employees were required, probably enough employees were able to fill in the survey (Naor et al., 2010). Out of the plants that were asked to fill in the survey, data from 317 plants was returned.

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19 measurement scales are based on the literature and are previously used (e.g. Bortolotti et al., 2015).

The measurement of the OC concept is based on the articles of Naor et al., (2010) and Bortolotti et al., (2015). The eight dimensions that are being used in this research are: PD, IC, IG, FO, PO, AS, UA and HO. The questions that were asked mainly targeted shop floor

employees, supervisors and human resource managers. These three groups were asked to give their opinions on a seven-point Likert scale. Were 1 denoted strongly disagree, and 7 strongly agree. For the NC-dimension scores the data of the GLOBE project are used and this data is listed in table 2. Both OC- and NC-dimensions are measured in the same way so that doing analysis on them can be done in the same way. The questions that were asked regarding the OC-dimensions and their means, standard deviations and Cronbach’s alpha can be found in Appendix C.

Table 2: House et al., 2004, Source: http://globeproject.com/results

To measure the LM concept different variables are provided to distinguish between the fitness bundle, JIT and TQM bundles. These three bundles were conceptualized and measured using a multi-item scale. The items were measured just like the cultural dimensions on a seven-point Likert scale were 1 denotes strongly disagree and were 7 denotes strongly agree. The LM concepts of Fitness, JIT and TQM consists of different variables that come from the literature. For the Fitness concept variables like employee suggestion, Multi-functional employees, small group problem solving, and Supplier

partnership are used. For the JIT concept there are variables like Daily schedule adherence, equipment layout and JIT delivery by suppliers. For the TQM concept these variables are

Germany U.S.A. Japan Finland South-Korea Sweden Italy China Australia Spain

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20 Customer involvement, Feedback and process control. These constructs are taken over from the article of Bortolotti et al., (2015) on the sand cone model. A complete list of the variables is shown in table 3 And the questions related with these variables can be found in Appendix A together with their averages and standard deviations. From table 3 also the related Cronbach’s alpha of the first-order constructs can be derived.

Table 3 sensitivity analysis three Lean bundles

Finally, performance was measured using four different constructs that followed Ferdows and De Meyer’s (1990) dimensions. Each manager of the plant under investigation was asked to provide his opinion about the plant performance in comparison to its competitors on a five-point Likert scale where one denoted a poor performance and 5 a superior

performance. This question was only for one person because the plant’s manager is highly likely to know the performance of the plant on multiple dimensions. The questions that were asked with regard to performance are listed in appendix B To reduce potential bias due to using a single respondent for performance, we ensured that the perceptual performance

Fitness Standardized Cronbach's alpha

Employee suggestion 0,861

Multi-functional employees 0,794

Small group problem solving 0,873

Manufacturing-Business strategy linkage 0,786

cleanliness and organization 0,877

continuous improvement 0,778

Supplier partnership 0,803

Total preventive maintenance 0,768

JIT

Daily schedule adherence 0,854

Equipment Layout 0,829

JIT delivery by suppliers 0,748

Kanban 0,862

Setup time reduction 0,817

TQM

Customer Involvement 0,809

Feedback 0,862

Process control 0,904

Top management leadership for quality 0,855

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21 measures were correlated with independent, objective data, gathered from different

respondents who were knowledgeable about individual performance measures. For delivery and flexibility performance two-item measures were used that are validated by Liu et al. (2009) and McKone-Sweet and Lee (2009). Quality and cost on the other hand have been measured using a single item, these are the same as the ones of Bozarth et al. (2009). To end up with one construct being an overall performance the average of the aforementioned constructs was taken and used as new overall performance variable being the dependent variable in the model.

Before being able to test the hypotheses the HPM dataset had to be cleaned so that all the variables and data were good enough to be used. In practice this meant that one company was removed from the data-set because of very few responses to the questions asked. Also, some questions had to be reversed because they were reverse coded. For the analysis of the data, the data was first standardized and mean centred before it was used. When items of a certain construct were missing these were filled up with the mean of that construct. This was done to not lose a lot of data. Sensitivity analysis was performed, and Cronbach’s alpha is used to assess the reliability of the scales. This was done for each of the variables

mentioned in table 3. For every variable the Cronbach’s alpha had to be at least be 0,7 to be optimal (Flynn et al., and 1990; Hair et al., 1995). Whenever a variable gave a Cronbach’s alpha below 0,7 or when the Cronbach’s alpha could be improved, factor analysis was used to delete items one by one. This was done for each variable but at least three constructs were used per variable. This method was used for the LM bundles of Fitness, JIT and TQM, but also for the OC-dimensions.

To test the hypotheses a linear regression was used. For the relation between The LM bundles and the LM concept itself a linear regression is the appropriate method. For

measuring the moderating effect the cultural dimensions had to be multiplied with the three different lean bundles to get the moderating effect. In that way also, the hypotheses on OC- and NC-dimensions can be checked.

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22 were one by one included. Starting the analysis, the first three hypotheses were tested using the linear regression and performance as dependent variable and the tree LM bundles as independent variables.

Results

The first analysis for hypothesis 1 led to the results that can be found in table 4. what can be learned from these results is the following. According to the linear regression the fitness and JIT bundle contribute significant to the performance of a firm and thereby confirm

hypotheses H1a and H1b. However, the TQM bundle does not significantly improve performance and therefore the data does not support hypothesis H1c. Even when for performance only the quality construct is used (PER2 in Appendix B), TQM does not significantly contribute to performance. These results reflect the result from Flynn et al., (1995) because they found that JIT and corresponding infrastructural practices contributed performance, but that TQM has no significant effect on performance.

Variables β coefficient t-value significance

Fitness 0,254 2,731 0,007

JIT 0,184 2,775 0,006

TQM -0,054 -0,613 0,540

Table 4 regression results LM bundles

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23 What is shown in table 5 is that for OC-PD there is no significant moderating effect on the relation between the LM bundles and performance. Therefore, the outcome does not support hypotheses H2a1, H2a2 and H2a3. This implies that is does not matter if there is high or low PD within an organization to reach certain performance. This result agrees with Kull and Wacker (2010) even though their research was on QM only. This outcome suggests that high PD in companies will have a similar effect on performance as low PD in companies.

FITNESS 0,244 2,596 0,010 JIT 0,191 2,844 0,005 TQM -0,037 -0,416 0,678 PD -0,050 -0,928 0,354 ZPD_ZFITNESS -0,041 -0,458 0,648 ZPD_ZJIT 0,017 0,236 0,813 ZPD_ZTQM 0,086 1,047 0,296

Table 5 regression results for OC-PD

For the NC-PD it is shown in table 6 that there is a significant moderating effect from PD on the relation between the JIT bundle and performance (β=-0.137, P<0.05). This result shows that in countries with higher PD the impact of JIT has a weaker effect on performance. Also, this means that in countries with higher PD the impact of JIT practices on performance is stronger and thus the data is supporting hypotheses H2a5. This does not correspond to the article of Kull et al., (2014) as they find that PD does not moderate the relation between LM and performance. Perhaps that is because in that article an overall LM measure is used and, in this research, the LM practices are split into three bundles. However, the other results are not significant and therefore not supporting hypotheses H2a4 and H2a6 and these results are therefore in line with the article of Kull et al., (2014).

FITNESS 0,277 2,958 0,003 JIT 0,176 2,664 0,008 TQM -0,098 -1,107 0,269 NCPD 0,092 1,710 0,088 ZNCPD_ZFITNESS 0,134 1,468 0,143 ZNCPD_ZJIT -0,137 -1,986 0,048 ZNCPD_ZTQM 0,076 0,879 0,380

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24 For OC-IC it is shown in table 7 that there are no significant moderating effects of OC-IC on the relation between the LM bundles and performance. Therefore, hypotheses H2b1, H2b2 and H2b3 are not supported by the data. This result is not equal to the result of Wiengarten et al., (2015). They state that OC-IC does significantly moderate the relation between LM and performance. In other words: lean practices indeed have a stronger impact on operations performance in plants practicing high levels of collectivism when compared to plants practicing an individualistic organisational culture (Wiengarten et al., 2015). However as stated the data used here does not support that conclusion.

FITNESS 0,225 2,390 0,017 JIT 0,205 3,024 0,003 TQM -0,033 -0,375 0,708 IC 0,038 0,714 0,476 ZIC_ZFITNESS 0,053 0,512 0,609 ZIC_ZJIT -0,031 -0,424 0,672 ZIC_ZTQM -0,143 -1,493 0,136

Table 7 regression results for OC-IC

The results of the regression on NC-IC are shown in table 8 and suggest that there is no significant moderating effect of NC-IC on the relation between the LM bundles and

performance. This result is not equal to the result of Wiengarten et al., (2015) as they find that NC-IC has a significant moderating effect. However, because of this result the data does not support hypotheses H2b4, H2b5 and H2b6.

FITNESS 0,264 2,817 0,005 JIT 0,183 2,692 0,007 TQM -0,064 -0,719 0,473 NCIC -0,048 -0,888 0,375 ZNCIC_ZFITNESS -0,083 -0,954 0,341 ZNCIC_ZJIT 0,037 0,547 0,585 ZNCIC_ZTQM 0,074 0,836 0,404

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25 The results from OC-IG are shown in table 9 and suggest that there does not exist a

significant moderating effect. Therefore, the data does not support H2c1, H2c2 and H2c3.

FITNESS 0,237 2,513 0,012 JIT 0,207 3,036 0,003 TQM -0,045 -0,504 0,615 IG 0,063 1,166 0,244 ZIG_ZFITNESS 0,012 0,131 0,895 ZIG_ZJIT -0,074 -1,077 0,282 ZIG_ZTQM -0,007 -0,085 0,932

Table 9 regression results for OC-IG

The results for NC-IG are shown in table 10 and suggest, just as for OC-IC, that there is no significant moderating effect. Therefore, the data does not support H2c4, H2c5 and H2c6.

FITNESS 0,246 2,635 0,009 JIT 0,177 2,656 0,008 TQM -0,048 -0,540 0,589 NCIG 0,024 0,440 0,661 ZNCIG_ZFITNESS -0,137 -1,451 0,148 ZNCIG_ZJIT 0,074 1,153 0,250 ZNCIG_ZTQM -0,071 -0,778 0,437

Table 10 regression results for NC-IG

For OC-FO there is no significant moderating effect, and this is shown in table 11. Because of this result the data does not support hypotheses H2d1, H2d2 and H2d3.

FITNESS 0,275 2,934 0,004 JIT 0,178 2,674 0,008 TQM -0,062 -0,703 0,483 FO -0,036 -0,661 0,509 ZFO_ZFITNESS 0,064 0,710 0,478 ZFO_ZJIT -0,051 -0,754 0,451 ZFO_ZTQM 0,067 0,772 0,440

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26 As for OC-FO, NC-FO does not show a moderating effect and therefore the data does not support hypotheses H2d4, H2d5 and H2d6. This is shown in table 12. From the article of Kull et al., (2014) it is shown that FO might have a negative moderating effect. If this data is used to back up this result it can be stated that for the fitness bundle the β=-0.151 and thus there is a negative relation. However, the results are not significant for p<0.05 and can therefore not back up the conclusion of Kull et al., (2014)

FITNESS 0,257 2,738 0,007 JIT 0,182 2,672 0,008 TQM -0,059 -0,666 0,506 NCFO 0,025 0,458 0,648 ZNCFO_ZFITNESS -0,151 -1,571 0,117 ZNCFO_ZJIT 0,061 0,839 0,402 ZNCFO_ZTQM 0,079 0,838 0,403

Table 12 regression results for NC-FO

Regarding hypotheses H2e1, h2e2 and h2e3 the data shows no significant results for a moderating effect of OC-PO and this is shown in table 13.

FITNESS 0,259 2,739 0,007 JIT 0,172 2,539 0,012 TQM -0,051 -0,572 0,568 PO 0,052 0,958 0,339 ZPO_ZFITNESS 0,048 0,540 0,590 ZPO_ZJIT -0,032 -0,476 0,634 ZPO_ZTQM -0,024 -0,270 0,787

Table 13 regression results for OC-PO

For NC-PO there are, as shown in table 14, no significant moderating results and thus the data does not support hypotheses H2e4, H2e5 and H2e6.

FITNESS 0,256 2,561 0,011 JIT 0,180 2,607 0,010 TQM -0,053 -0,565 0,573 NCPO -0,008 -0,142 0,887 ZNCPO_ZFITNESS -0,004 -0,038 0,970 ZNCPO_ZJIT -0,002 -0,030 0,976 ZNCPO_ZTQM -0,014 -0,146 0,884

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27 For OC-AS there is no significant result to be found. And this is shown in table 14. Therefore, the data does not support hypotheses H2f1, H2f2 and H2f3.

FITNESS 0,270 2,872 0,004 JIT 0,186 2,766 0,006 TQM -0,066 -0,738 0,461 AS -0,051 -0,928 0,354 ZAS_ZFITNESS 0,067 0,808 0,420 ZAS_ZJIT -0,064 -0,951 0,342 ZAS_ZTQM 0,017 0,195 0,846

Table 15 regression results for OC-AS

For NC-AS there is also no significant effect. However, as shown in table 16 there is a nearly significant effect for the moderation of NC-AS on the relation between JIT and performance (β=0.125, P<0.05). This would imply that in countries with higher AS the impact of JIT practices on performance is stronger. This still does not apply to hypotheses H2f5 because that hypothesis implies a negative relation. This is in high contrast with what other

researchers found because high AS is consistent with individualism and self-initiative (Kluckhohn and Strodtbeck,1973). Also, the competition among individuals and groups that is emphasized in a high AS culture works against cross-functional cooperation, which is required for an effective use of JIT practices (Safayeni and Purdy, 1991; Wafa and Yasin, 1998). However, the result is not significant, but it might imply something. Hypotheses H2f4 and H2f6 are not significant and therefore not supported by the data.

FITNESS 0,276 2,917 0,004 JIT 0,151 2,262 0,024 TQM -0,074 -0,833 0,406 NCAS -0,059 -1,118 0,264 ZNCAS_ZFITNESS -0,102 -1,106 0,270 ZNCAS_ZJIT 0,125 1,799 0,073 ZNCAS_ZTQM -0,120 -1,388 0,166

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28 For OC-UA there is no significant moderating effect detected during the regression. The results are show in table 17. Because of these results the data does not support hypotheses H2g1, H2g2 and H2g3.

FITNESS 0,251 2,681 0,008 JIT 0,180 2,661 0,008 TQM -0,058 -0,640 0,523 UA -0,024 -0,443 0,658 ZUA_ZFITNESS 0,101 1,008 0,314 ZUA_ZJIT 0,014 0,208 0,836 ZUA_ZTQM -0,122 -1,245 0,214

Table 17 regression results for OC-UA

For NC-UA there is also no significant result and therefore the data does not support any moderating effect there and thus hypotheses H2g4, H2g5 and H2g6 are not supported by the data. The results are shown in table 18.

FITNESS 0,211 2,176 0,030 JIT 0,209 2,915 0,004 TQM -0,021 -0,225 0,822 NCUA -0,079 -1,404 0,161 ZNCUA_ZFITNESS -0,061 -0,592 0,554 ZNCUA_ZJIT 0,005 0,068 0,946 ZNCUA_ZTQM 0,108 1,102 0,271

Table 18 regression results for NC-UA

The last cultural dimension is HO. For OC-HO the regression shows that there is a

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29 and Wacker, 2010; Kull et al., 2014; Vecchi and Brennan, 2011). A possible reason is that they only researched the NC and not the OC. The results in table 19 thus give support to hypothesis H2g1 but do not support H2g2 and H2g3.

FITNESS 0,262 2,837 0,005 JIT 0,193 2,924 0,004 TQM -0,049 -0,556 0,579 HO 0,086 1,612 0,108 ZHO_ZFITNESS 0,172 2,034 0,043 ZHO_ZJIT -0,016 -0,234 0,815 ZHO_ZTQM -0,262 -3,186 0,002

Table 19 regression results for OC-HO

Finally, for NC-HO the regression shows no significant moderating effect. The results are shown in table 20 and do not support hypotheses H2g4, H2g5 and H2g6.

FITNESS 0,250 2,530 0,012 JIT 0,182 2,622 0,009 TQM -0,047 -0,519 0,604 NCHO -0,021 -0,382 0,703 ZNCHO_ZFITNESS 0,023 0,205 0,838 ZNCHO_ZJIT -0,038 -0,495 0,621 ZNCHO_ZTQM 0,074 0,740 0,460

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30 Discussion

Based on the articles of Wiengarten et al., (2015); Kull and Wacker, (2010) and Kull et al., (2014) the aim of this research was to find if there was a moderating effect from OC and/or NC on the relation between LM and performance. This research differentiates from these other articles by using three bundles of LM instead of using an overall construct of lean. Furthermore, this research takes both OC and NC into account where the other articles only consider NC or just one dimension of the GLOBE cultural dimensions for both OC and NC. In the operations management literature there has been considerable debate as to what extent the success of best practices in general, and lean practices in particular, are

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31 moderating effect of PD. In the article of Kull and Wacker (2010) there is no significant moderating effect. The fact that in this research there is a significant effect implies that the higher the PD in a country the weaker the LM effectiveness. In practice this means that in a low PD country, employees feel freer to express themselves and their input might help improving the organization and therefore the lean program. Just as for PD a negative moderating effect was expected for AS. However, all the results were insignificant implying that AS does not have a significant moderating effect on LM effectiveness. What was surprising to find out is that for the JIT bundle there was a positive moderating effect from the country level AS were a negative one was expected. The result is not significant for p<0.05, however, it is significant for p<0.1 and might hence imply that AS is a good thing. However, this has never been noted before in previous research. AS was only researched as having negative moderating effect or a non-significant impact, just ass in this research. (Kull et al., (2014); Kull and Wacker, (2010); Vecchi and Brennan, (2011). The last cultural

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32 Conclusions

This research adds to the on-going debate on the importance of culture in LM practices. Consistent with prior research, the findings in this research suggest that LM practices have influence on the performance of the firm (e.g. Flynn et al., 1995). Also, in line with other studies, this research provides more results on the moderating effect of both OC and NC on the effectiveness of LM. Not all the dimensions researched had the significant effect the hypotheses expected or hoped for, but some dimensions are moderators. Furthermore, this research continues to see LM as practices and brings them together in three LM bundles of fitness, JIT and TQM (Shah and Ward, 2007; Bortolotti et al., 2015).

A limitation of this study is that it assumes that the NC of a country is the same for the whole country. This is the case because the GLOBE framework does not take subcultures into account. However, the assumption of a unified NC is very common in cultural studies that rely on Hofstede’s or GLOBE data sets (Naor et al., 2010). Another limitation is the way of data analysis. The way data was analysed in this research was by multiplying the moderators with the independent variables. Looking back on the process it might have been better to use Lisrel for a critical factor analysis (CFA) and on that basis of the results obtained from that move on to measure the moderating effect.

A call for further research not only from this research but also from other papers is to focus on the possible interaction between NC and OC. Bortolotti et al., (2015) mention this in their article as does Naor et al., (2010). However, that was not the focus of this research, but it could give some interesting insights about which of the two is the most dominant and needs therefore more attention than the other one.

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33 References

Achanga, P., Shehab, E., Roy, R., Nelder, G., 2006. Critical success factors for lean implementation within SMEs. J. Manuf. Technol. Manage. 17 (4), 460–471

Ahire, S.L., Dreyfus, P., 2000. The impact of design management and process management on quality: an empirical investigation. J. Oper. Manage. 18 (5), 549–575.

Aiken, C., and S. Keller. 2009. “The Irrational Side of Change Management.” McKinsey Quarterly 2 (Jun.): 100–109.

Aksu, M.B., 2003. TQM readiness level perceived by the administrators working for the central organization of the Ministry of National Education in Turkey. Total Qual. Manage. Bus. Excellence 14 (5), 591–604.

Ashkanasy, N., Gupta, V., Mayﬁeld, M.S., Trevor-Roberts, E., 2004. Future orientation. In: House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W., Gupta, V. (Eds.), Culture, Leadership and Organizations. Sage, London

Atkinson, P., 2010. Lean is a cultural issue. Manage. Serv. 54, 35–44.

Baird, K., Hu, K., Reeve, R., 2011. The relationships between organizational culture, total quality management practices and operational performance. Int. J. Oper. Prod. Manage. 31 (7), 789–814

Bates, K.A., Amundson, S.D., Schroeder, R.G. and Morris, W.T. (1995), “The crucial interrelationship between manufacturing strategy and organizational culture”, Management Science, 41 (10), 1565-1580.

Beer, M., and N. Nohria. 2001. Cracking the Code of Change. Harvard Business Review, 78 (3), 133–141.

Bortolotti, T., Boscari, S., Danese, P., 2015. Successful lean implementation: Organizational culture and soft lean practices. Int. J. Production Economics. 160, 182-201.

Bortolotti, T., Danese, P., Flynn, B.B., Romano, P., 2015. Leveraging ﬁtness and lean bundles to build the cumulative performance sand cone model, International Journal

Production Economics, 162, 227-241.

Bozarth, C.C., Warsing, D.P., Flynn, B.B., Flynn, E.J., 2009. The impact of supply chain complexity on manufacturing plant performance. J. Oper. Manage. 27 (1), 8–93. Caglian, 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.

Claver, Enrique, Juan Llopis, Jose L. Gasco, Hipolito Molina, and Francisco J. Conca. 1999. Public Administration: From Bureaucratic Culture to Citizen-Oriented Culture. International Journal of Public Sector Management, 12(5), 455–64.

(34)

34 Denison, D.R., Mishra, A., 1995. Toward a theory of organizational culture and effectiveness.

Organ. Sci. 6 (2), 204–223.

Detert, J., Schroeder, R.G., Mauriel, J., 2000. A framework for linking culture and improvement initiatives in organizations. Acad. Manage. Rev. 25 (4), 850–863. Ferdows, K., De Meyer, A., 1990. Lasting improvements in manufacturing performance: in

search of a new theory. J. Oper. Manage. 9 (2), 168–184

Fey, C.F., Denison, D.R., 2003. Organizational culture and effectiveness: can American theory be applied in Asia? Organ. Sci. 14 (6), 686–706.

Flynn, B.B., Sakakibara, S., Schroeder, R.G., Bates, K.A., Flynn, E.J., 1995. Empirical research methods in operations management. Journal of Operations Management 9(2)250-284.

Flynn, B.B., Sakakibara, S., Schroeder, R.G., Bates, K.A., Flynn, E.J., 1995. Relationship between JIT and TQM: practices and performance. Acad. Manage. J. 38 (5), 1325– 1360.

Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1994. A framework for quality management research and an associated measurement instrument. J. Oper. Manage. 11, 339–366. Fullerton, R.R., McWatters, C.S., 2002. The role of performance measures and incentive

systems in relation to the degree of JIT implementation. Acc. Organ. Soc. 27 (8), 711– 735.

Gelfand, M.J., Bhawuk, D.P.S., Nishii, L.H., Bechtold, D.J., (2004), Individualism and

collectivism in: House, Hanges, Javidan, Dorfman Gupta, (Eds), Culture leadership and Organizations, Sage Londen.

Gordon, G.G., DiTomaso, N., 1992. Predicting corporate performance from organizational culture. J. Manage. Stud. 29 (6), 783–798.

Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 1995. Multivariate Data Analysis 4th_ed.

Prentice Hall, Upper saddle river, NJ.

Hartog, D.N.D., 2004. Assertiveness. In: House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W., Gupta, V. (Eds.), Culture, Leadership and Organizations. Sage, London

Hayes, R.H., Wheelwright, S.C., Clark, K.B., 1988. Dynamic Manufacturing: Creating the Learning Organization. The Free Press, New York, NY.

Holweg, M., 2007. The genealogy of lean production. Journal of Operations Management, 25, 420–437

Hofer, A.R., Hofer, C., Eroglu, C., Waller, M.A., 2011. An institutional theoretic perspective on forces driving adoption of lean production globally: China vis-àvis the USA. Int. J. Logist. Manage. 22 (2), 148–178.

(35)

35 Hofstede, G., and G. J. Hofstede. 2005. Cultures and Organizations: Software of the Mind.

New York: McGraw-Hill.

Hofstede, G., Neuijen, B., Ohayv, D.D., Sanders, G., 1990. Measuring organizational cultures: a qualitative and quantitative study across twenty cases. Admin. Sci. Q. 35, 286–316. House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W., Gupta, V., 2004. Culture, Leadership,

and Organizations: The GLOBE Study of 62 Societies. Sage Publications, Thousand Oaks, CA.

Jung, T., Scott, T., Davies, H.T.O., Bower, P., Whalley, D., McNally, R., Mannion, R., 2009. Instruments for exploring organizational culture: a review of the literature. Public Admin. Rev. 69 (6), 1087–1096.

Kabasakal, H., Bodur, M., 2004. Humane orientation in societies, organizations, and leader attributes. In: House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W., Gupta, V. (Eds.), Culture, Leadership and Organizations. Sage, London

Kloot, Louise, and John Martin. 2007. Public Sector Change, Organizational Culture and Financial Information: A Study of Local Government. Australian Journal of Public Administration 66(4), 485–97.

Kluckhohn, F.R., Strodtbeck, F.L., 1973. Variations in Value Orientations. Greenwood Press, Westport, Conn

Kotter, J. P. 1995. “Leading Change: Why Transformation Efforts Fail.” Harvard Business Review 73 (2), 59–67.

Krafcik, J. F. 1988. “Triumph of the Lean Production System.” Sloan Management Review 30 (1), 41–51.

Kull, T. J., and J. G. Wacker. 2010. “Quality Management Effectiveness in Asia: The Inﬂuence of Culture.” Journal of Operations Management 28 (3), 223–239.

Kull, T.J., Yan, T., Liu, Z., Wacker, J.G., (2014), The moderation of lean manufacturing

effectiveness by dimensions of national culture: Testing practice-culture congruence hypotheses, Int. J. Production Economics, 153, 1-12.

Lee, S.K.J., Yu, K., 2004. Corporate culture and organizational performance. J. Managerial Psychol. 19 (4), 340–359.

Liker, J.K., 2004. The Toyota Way. McGraw-Hill, New York, NY.

Liker, J.K., Rother, M., 2011. Why Lean Programs Fail. Lean Enterprise Institute.

Liu, G., McKone-Sweet, K., Shah, R., 2009. Assessing the performance impact of supply chain planning in net-enhanced organizations. Oper. Manage. Res. 2, 33–43

(36)

36 Lozeau, D., Langley, A., Denis, L.J., 2002. The corruption of managerial techniques by

organizations, Human relations, 55(5), 537-564.

Lucey, J., N. Bateman, and P. Hines. 2005. “Why Major Lean Transitions Have Not Been Sustained.” Management Services 49 (2), 9–13.

Mackelprang, A. W., and A. Nair. 2010. “Relationship between Just-in-time Manufacturing Practices and Performance: A Meta analytic Investigation.” Journal of Operations Management 28 (4), 283–302.

Mannion, Russell, Huw T. O. Davies, and Martin N. Marshall. 2005. Cultures for Performance in Health Care. Maidenhead, UK: Open University Press.

McDermott, C.M., Stock, G.N., 1999. Organizational culture and advanced manufacturing technology implementation, Journal of Operations Management, 17, 521-533. McKone, K.E., Schroeder, R.G., Cua, K.O., 2001. The impact of total productive maintenance

on manufacturing performance. Journal of Operations Management 19 (1), 39–58. McKone-Sweet, K., Lee, Y., 2009. Development and analysis of a supply chain strategy

taxonomy. J. Supply Chain Manage. 45 (3), 2–24

Morgan, Philip I., and Emmanuel Ogbonna. 2008. Subcultural Dynamics in Transformation: A Multi-Perspective Study of Healthcare Professionals. Human Relations 61(1), 39–65. Moyano-Fuentes, J., Sacristán-Díaz, M., 2012. Learning on lean: a review of thinking and

research. Int. J. Oper. Prod. Manage. 32 (5), 551–582.

Nahm, A.Y., Vonderembse, M.A., Koufteros, X.A., 2004. The impact of organizational culture on time-based manufacturing and performance. Decis. Sci. 35 (4), 579–607.

Naor, M., Goldstein, S., Linderman, K.W., Schroeder, R.G., 2008. The role of culture as driver of quality management and performance: infrastructure versus core quality practices. Decis. Sci. 39 (4), 671–702.

Naor, M., Linderman, K., Schroeder, R.G., 2010. The globalization of operations in Eastern and Western countries: unpacking the relationship between national and

organizational culture and its impact on manufacturing performance. J. Oper. Manage. 28 (3), 194–205.

Narasimhan, Ram, Kull, T.J., Nahm, A., 2012. Alternative relationships among integrative beliefs, time-based manufacturing and performance. Int. J. Oper. Prod. Manage. 32 (4), 496–524.

Netland, T.H., 2016. Critical success factors for implementing lean production: the effect of contingencies, International Journal of Production Research, 54 (8), 2433-2448. Nikolic, M., Saciv, M., Cockalo, D., Vukonjanski, J., Jovanovic, D., 2011. The impact of

(37)

37 O’Reilly, C., Chatman, J.A., Caldwell, D.F., 1991. People and organizational culture: a profile

comparison approach to assessing person-organization fit. Acad. Manage. J. 34 (3), 487–516.

Ouchi, W.G., 1981. Theory Z: How American Business Can Meet the Japanese Challenge. Addison-Wesley, Reading, MA.

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.

Pakdil, F., and Leonard, K.M., (2017) Implementing and sustaining lean processes: the dilemma of societal culture effects, International Journal of Production Research, 55:3, 700-717.

Patel, P., Cardon, M., 2010. Adopting HRM practices and their effectiveness in small firms facing product-market competition. Hum. Resour. Manage. 49 (2), 265–290.

Pay, R. 2008. Everybody’s Jumping on the Lean Bandwagon, but Many Are Being Taken for a Ride. Industry Week, March 1, 2008.

Peters, T.J., Waterman, R.H., 1982. In Search of Excellence. Harper & Row, New York, NY. Prajogo, D., McDermott, C., 2005. The relationship between total quality management

practices and organizational culture. Int. J. Oper. Prod. Manage. 25 (11), 1101–1122 Prajogo, D., McDermott, C., 2011. The relationship between multidimensional organizational

culture and performance. Int. J. Oper. Prod. Manage. 31 (7), 712–735

Puvanasvaran, P., Megat, H., Hong, T.S., Mohd.Razali, M., 2009. The roles of communication process for an effective lean manufacturing implementation. J. Ind. Eng. Manag. 2 (1), 128–152.

Quinn, R.E., Rohrbaugh, J., 1983. A spatial model of effectiveness criteria: towards a competing values approach to organizational analysis. Manage. Sci. 29, 363–377. Rother, M., 2009. Toyota Kata: Managing People for Improvement, Adaptiveness and

Superior Results. McGraw-Hill

Safayeni, F., Purdy, L., 1991. A behavioural case study of just-in-time implementation. Journal of operations management 10(2), 213-228.

Schein, E., 1985. Organizational Culture and Leadership, Jossey-Bass, San Francisco, CA. Schein, E.H., 1984. Coming to a new awareness of organizational culture. Sloan Manage. Rev.

25 (2), 3–16.

(38)

38 Schwartz, S.H., 1994. Beyond individualism/collectivism: new cultural dimensions of values.

In: Kim, U., Triandis, H.C., Kagitcibasi, C., Choi, S.C., Yoon, G. (Eds.), Individualism and Collectivism: Theory Method and Applications. Sage, Thousand Oaks, CA, pp. 85–119. Shah, R., Ward, P.T., 2003. Lean manufacturing: context, practice bundles, and performance.

J. Oper. Manage. 21, 129–149.

Shah, R., Ward, P.T., 2007. Defining and developing measures of lean production. J. Oper. Manage. 25, 785–805.

Sim, K.L., Rogers, J.W., 2009. Implementing lean production systems: barriers to change. Manage. Res. News 32 (1), 37–49.

Skinner, W., 1969. Manufacturing—missing link in corporate strategy. Harv. Bus.Rev. 47 (3), 136–145.

Smith, P.B., 2006. When Elephants fight, the grass gets trampled: the GLOBE and Hofstede projects. Journal of International Business Studies 37 (6), 915–921.

Snell, S.A, Dean, J.W., 1994. Strategic compensation for integrated manufacturing: the moderating effects of job and organizational inertia. Academy of Management Journal 37 (5), 1109–1140.

Spear, S.J., Bowen, H.K., 1999. Decoding the DNA of the Toyota production system. Harv. Bus. Rev. 77 (9/10), 97–106.

Stock, G.N., McFadden, K.L., Gowen, C.R., (2007), Organizational culture, critical success factors, and the reduction of hospital errors, Int. J. Production Economics, 106, 368-392.44

Storch, R., Lim, S., 1999. Improving ﬂow to achieve lean manufacturing in shipbuilding. Prod. Plan. Control 10 (2), 127–137.

Swink, M., Narasimhan, R., Kim, S.W., 2005. Manufacturing practices and strategy integration: effects on cost efficiency, flexibility, and market-based performance. Decis. Sci. 36 (3), 427–475

Swamidass, P. M. 2007. “The Effect of TPS on US Manufacturing during 1981–1998:

Inventory Increased or Decreased as a Function of Plant Performance.” International Journal of Production Research 45 (16): 3763–3778.

Triandis, H.C., (1989), The self and social-behavior in different cultural contexts, Psychol. Rev., 96(3), 506-520.

Vecchi, A., and L. Brennan. 2011. “Quality Management: A Cross-cultural Perspective Based on the GLOBE Framework.” International Journal of Operations & Production

Management 31 (5): 527–553.

(39)

39 Waterhouse, Jennifer, and Dianne Lewis. 2004. Communicating Culture Change: HRM

Implications for Public Sector Organizations. Public Management Review 6(3): 353– 76.

Wincel, J., Kull, T., 2013. People, Process, and Culture: Lean Manufacturing in the Real World. CRC Press, Boca Raton

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.

Womack, J.P., Jones, D T, 1996. Lean Thinking—Banishing Waste and Creating Wealth in Your Corporation. Simon and Schuster, New York, NY

Womack, J.P., Jones, D.T., Roos, D., 1990. The Machine that Changed the World. Rawson Associates, New York, NY. Yasin, M., Small, M., Wafa, M., 2003.

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40 Appendix

Appendix A MEAN ST. dev

Fitness

Management takes all product and process

improvement suggestions seriously. 5,28 0,72

Employee suggestion

We are encouraged to make suggestions for

improving performance at this plant. 5,53 0,74

Management tells us why our suggestions are

implemented or not used. 4,71 0,83

Many useful suggestions are implemented at this

plant. 5,18 0,76

My suggestions are never taken seriously around

here. 5,52 0,73

Our employees receive training to perform multiple

tasks. _5,19 _0,82

Multi-functional employees

Employees at this plant learn how to perform a

variety of tasks. _5,25 _0,73

The longer an employee has been at this plant, the

more tasks they learn to perform. _5,17 _0,77

Employees are cross-trained at this plant, so that they

can fill in for others, if necessary. _5,17 _0,77

During problem solving sessions, we make an effort to get all team members’ opinions and ideas before

making a decision. _5,18 _0,66

Small group problem solving Our plant forms teams to solve problems. 5,27 0,87

In the past three years, many problems have been

solved through small group sessions. 5,04 0,80

Problem solving teams have helped improve

manufacturing processes at this plant. 5,13 0,83

Employee teams are encouraged to try to solve their

own problems, as much as possible. 5,16 0,75

We don’t use problem solving teams much, in this

plant. 4,90 0,91

Our business strategy is translated into

manufacturing terms. 5,13 0,96

Manufacturing-Business strategy Linkage

Potential manufacturing investments are screened for consistency with our business strategy.

5,76 0,76

At our plant, manufacturing is kept in step with our

business strategy. _5,31 _0,78

Manufacturing management is not aware of our

business strategy. _5,60 _1,02

Corporate decisions are often made without

consideration of the manufacturing strategy. _4,84 _1,07

Our plant emphasizes putting all tools and fixtures in

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41 cleanliness and organization We take pride in keeping our plant neat and clean. 5,60 0,79

Our plant is kept clean at all times. 5,23 0,89

Our plant is disorganized and dirty. 5,87 0,83

We strive to continually improve all aspects of products and processes, rather than taking a static

approach. _5,55 _0,68

continuous improvement

If we aren’t constantly improving and learning, our

performance will suffer in the long term. _6,16 _0,49

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

attack. _5,25 _0,85

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

improvement. _6,05 _0,50

Our organization is not a static entity, but engages in dynamically changing itself to better serve its

customers. _5,51 _0,64

We maintain cooperative relationships with our

suppliers. 5,56 0,57

Supplier partnership We provide a fair return to our suppliers 4,96 0,73

We help our suppliers to improve their quality. 5,37 0,63

We maintain close communications with suppliers

about quality considerations and design changes. 5,37 0,67

Our key suppliers provide input into our product

development projects. 4,70 0,80

We upgrade inferior equipment, in order to prevent

equipment problems. _5,10 _0,86

Total preventive maintenance

We estimate the lifespan of our equipment, so that

repair or replacement can be planned. _4,80 _1,01

We use equipment diagnostic techniques to predict

equipment lifespan. _3,93 _1,08

We do not conduct technical analysis of major

breakdowns. _5,40 _1,01

JIT We usually meet the production schedule each day. 5,27 0,89

Daily schedule adherence Our daily schedule is reasonable to complete on time. 5,12 0,90

We usually complete our daily schedule as planned.

5,32 0,82

We cannot adhere to our schedule on a daily basis.

4,71 1,08

It seems like we are always behind schedule. 4,75 1,11

We have laid out the shop floor so that processes and

Master Thesis MSc Technology & Operations Management

Master Thesis

“Lean management performance considering organizational

and national culture”

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