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Int. J. Technology Management, Vol. 57, Nos. 1/2/3, 2012

Impact of use of information technology on lean production adoption: evidence from the automotive industry José Moyano-Fuentes*, Pedro José Martínez-Jurado, Juan Manuel Maqueira-Marín and Sebastián Bruque-Cámara Department of Business Administration, Accounting and Sociology, University of Jaén, E.P.S. Linares, C/Alfonso X el Sabio, 28, 23700 Linares (Jaen), Spain Fax: +34 953 648 508 E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: In this paper we analyse the existing interrelationships between information technology (IT) and the adoption of lean production. More specifically, the level of adoption of lean production is studied in accordance with the degree of use and the kind of IT used (internal and external IT). The results of the study show how companies need to augment the degree of use of internal or intra-organisational IT in order to increase the level of implementation of lean production and therefore improve efficiency. Results also show that external or inter-organisational IT only has a significant negative influence on the level of adoption of lean production when internal IT is controlled. These findings provide managers with empirical evidence and a theoretical framework on the balance between internal and external IT in order to increase lean production adoption, thus offering practical guidance on how to manage IT and lean production adoption. Keywords: lean production; LP; information technology; internal IT; external IT; automotive industry. Reference to this paper should be made as follows: Moyano-Fuentes, J., Martínez-Jurado, P.J., Maqueira-Marín, J.M. and Bruque-Cámara, S. (2012) ‘Impact of use of information technology on lean production adoption: evidence from the automotive industry’, Int. J. Technology Management, Vol. 57, Nos. 1/2/3, pp.132–148. Biographical notes: José Moyano-Fuentes is an Associate Professor of Management in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He currently conducts research on the lean production, supply chain management and firm performance in the automotive industry. He also has interests in the role of technology in organisations, with current emphasis involving social networks influence on employees’ technology acceptance. His research has appeared in the Administrative Science Quarterly, Journal of Management of Information Systems, Journal of Management Studies, International Journal of Management Reviews, Small Business Economics, Technology Analysis and Strategic Management and Technovation. Copyright © 2012 Inderscience Enterprises Ltd.

Impact of use of information technology on lean production adoption

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Pedro J. Martínez-Jurado is a PhD student and a Researcher on Lean Production in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He is currently conducting research on factors leading to lean production adoption in the automotive industry. He develops his doctoral thesis with funds from Andalusian Regional Government. Juan M. Maqueira-Marín is an Assistant Professor of Management and Researcher on Information Technology Adoption in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He is currently conducting research on factors leading to grid technology adoption. He has a wide experience as a practitioner in some technological firms such us Fujitsu Services Inc. Currently he is involved as a student in the doctoral program on technology management at the University of Jaén. Sebastián Bruque-Cámara is an Associate Professor of Management in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He currently conducts research on organisational factors affecting IT adoption and social networks effects on workers’ acceptance of technological changes. He has been a Visitor Researcher at the University of Nijmegen (The Netherlands) and his research has appeared in the Journal of Management of Information Systems, European Journal of Information Systems, Internet Research, Journal of High Technology Management Research, Technovation and Technology Analysis and Strategic Management.

1

Introduction

Lead production is an innovative management system aimed at achieving maximum company efficiency by developing operations at a minimum costs and in a zero-waste environment (Womack et al., 1990). This management system has been the object of more and more interest from directors searching for the secrets that produced the Toyota miracle (Womack and Jones, 1996; Spear and Bowen, 1999). This search, added to the difficulty of repeating the strong impact on results as obtained by Toyota, even when the most characteristic lean production (LP) practices are followed, has resulted in greater interest by researchers in the theoretical principles of LP (Shah and Ward, 2003, 2007; Suzuki, 2004; De Treville and Antonakis, 2006; Narasimhan et al., 2006) and its effects on the value chain (Bullington, 2003; Martínez and Pérez, 2004; Cagliano et al., 2006). Nevertheless, this interest by researchers fails to take into account the role of a series of powerful tools that are widely used by most companies in order to improve their competitive results: information technology (IT). IT enables companies to better manage more information, more flexibility, more functions and more features (Bruun and Mefford, 2004). IT can facilitate the implementation of the principles and practices related to LP given that the two groups of tools (IT and LP) complement each other (Riezebos and Klingenberg, 2009). However, IT and LP may compete with each other at the management level for two reasons. Firstly, the source of organisational expertise required is quite different for each tool, and secondly, the financial resources and top management

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attention required by each of these initiatives often prevent companies from initiating both IT use and LP on a large scale at the same time (Ward and Zhou, 2006). On the academic research level, few papers analyse the existing relationships between IT and LP principles and practices (Homer and Thompson, 2001; Bruun and Mefford, 2004; Ward and Zhou, 2006; Cagliano et al., 2006; Riezebos et al., 2009). This paper aims to cover this gap and study the role played by IT in the level of adoption of LP. To do so, IT will be analysed from two outlooks or focal points: IT focused on the company’s internal operations, such as those used in Computer Integrated Manufacturing, and external IT systems focused on the relationship the company has with its environment, such as the case of web technologies for e-commerce and e-business activities. In order to achieve our objective we have structured the paper in six sections including this introduction. Sections 2 and 3 cover the research background and the formulation of the hypothesis. We then describe the methodology used in Section 4. Section 5 highlights the results of the study, while the conclusions and the challenges faced by researchers in the future are presented in section 6.

2

Research background

2.1 The practices of LP The term ‘lean production’ was first used by International Motor Vehicle Program (IMVP) researcher John Krafcik (1988) to provide a thorough description of this management system and, ever since the model was made public (Womack et al., 1990), a clear trend has been detected towards the adoption of its principles that not only affect the internal operations of companies, but also their external organisation (Shah and Ward, 2007). LP arose in Toyota in the 1950’s (Ohno, 1988) and represents a radical and innovative change in the way companies are run due to the need to serve smaller markets with a greater variety of products, which requires greater flexibility in production. The main goal of the model is to achieve maximum efficiency by developing operations at minimum cost and with no wastage. To do so, the model aims to act upon the causes of variability or losses (such as anything that the customer does not perceive as added value), and upon the causes of inflexibility (anything that does not adapt to customer demand) with a view to achieving an improvement in quality, costs, and delivery and other times. By using this model companies adopt a management philosophy based on continuous improvement that offers the possibility of improving results and in which all levels of the organisation are involved (Womack and Jones, 1996). The basic principles of LP (Krafcik, 1988; Womack et al., 1990; Hines et al., 2004; Holweg, 2007) can be summed up as a series of practices (Karlsson and Ahlström, 1996; Hopp and Spearman, 2004; Shah and Ward, 2007), with a high level of consensus to identify the most characteristic practices associated with its adoption in the following cases: 1

just-in-time production (JIT)

2

single minute exchange die (SMED)

3

Kanban

Impact of use of information technology on lean production adoption 4

cellular manufacturing

5

total productive maintenance (TPM)

6

total quality management (TQM) (McLachlin, 1997; Shah and Ward, 2003; Narasimhan et al., 2006).

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With regard to the LP practices, it is important to remember that LP is considered more as a philosophy than a set of practices (Bhasin and Burcher, 2006), and that it is in constant evolution (Papadopoulou and Özbayrak, 2005). LP must therefore be considered from a multidimensional focus covering a variety of management practices in an integrated system, none of which are equivalent to LP when looked at separately, but that constitute the system as a whole (Shah and Ward, 2003, 2007).

2.2 The role of IT in LP There is currently a wide level of consensus in the scientific community regarding the role of IT as a way to generate efficiency and eventually competitive advantages. Nevertheless, IT is not able to generate intrinsically sustained competitive advantages by itself, mainly due to their imitable character (Carr, 2004). It is in conjunction with other business resources and capabilities that complement IT (Barney, 1991), such as human and business resources (Powell and Dent-Micallef, 1997), that IT is seen to be a powerful tool able to produce drastic changes in the structures and practices of different sectors of the economy. IT is, therefore, a powerful tool that facilitates the achievement of long-term objectives, especially when is adopted together with other key resources (i.e., human or business resources) in order to increase their efficiency (Powell and Dent-Micallef, 1997). As we have aforementioned, LP also focuses on company efficiency by eliminating anything that fails to add value to the client and that is therefore considered waste. Unlike IT, however, LP does create a competitive advantage (Womack et al., 1990; Lewis, 2000; Shah and Ward, 2003) that might be sustained in the long run (Lewis, 2000). Given that IT are powerful tools to achieve efficiency in companies, while lean is a philosophy that rules out everything that is unnecessary for efficiency, IT can therefore be considered as an adequate instrument for the purposes of the Lean framework. Likewise, IT and lean practices can be considered as two different layers of the same system aiming to achieve a common objective which consists of the increase of overall firm efficiency. The research issue we are addressing in this paper is if the use of IT is positively associated with the level of adoption of LP. In order to address this issue we have analysed the role of IT from two different points of view. The first focuses on internal IT, meaning IT used by a company to achieve efficiency in the tasks and projects carried out within the company. This group includes: 1

IT used in product design, such as computer aided design (CAD)

2

IT used in computer aided engineering (CAE) in order to develop, analyse and simulate engineering designs, characteristics and technical feasibility

3

IT used in the design and development of manufacturing processes involved in computer aided manufacturing (CAM)

4

IT used in the computer aided process planning (CAPP)

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5

IT involved in flexible manufacturing systems (FMS) that enable companies to manufacture a wide range of products through the management of automated processes

6

IT used in the integration of production planning and control with the rest of functions of the firm (enterprise resource planning: ERP).

This typology is based on prior literature, specifically on the elements used to define computer-aided production management systems (Riezebos et al., 2009; Narashiman et al., 2006). From the point of view of internal IT, these projects could result in the elimination of waste as required by LP practices. A second perspective focuses on IT practices used by companies when exchanging information with suppliers and clients, which are an important part of their external environment. This information needs to be transmitted quickly in order to minimise time devoted to routine processes such as those related to the selection of components and products or the purchase and sale of those components. This group, which we have called external IT, includes web technologies that enable business to business (B2B) transactions through the internet and that can result in efficiency by increasing the speed of routine processes, so enabling companies to: 1

find and choose suppliers able to deliver commodity components online

2

purchase materials efficiently by online auctions

3

collaborate with suppliers by exchanging information in such a way that production scheduling and material purchasing is carried out online.

This group also includes EDI-web information exchange systems between companies which have developed from former EDI systems. External IT and particularly the irruption of the internet at a business level have shown that IT is a powerful tool for any business strategy (Porter, 2001). External IT could therefore be considered a tool with which to facilitate the adoption of lean practices in pursues of overall efficiency.

3

Hypotheses

Conceptually, lean principles and practices can be carried out successfully in a very simple way without using IT, or may reach a high level of sophistication if backed by IT. For example, one simple Lean technique used to ensure internal JIT production of components from one manufacturing cell to others is the kanban card system. Many companies currently use this system without IT support, although there are innovative firms that use internal IT support to automate their kanbans and make them more efficient by providing the product with labels to codify information by radiofrequency and indicate the status of intermediate storage or consumption, among other additional information. Information systems are able to analyse this data and inform each production centre of how much product to be produced and when, so avoiding human errors that can occur when using visual information. The same situation exists with source error control systems known as poka-yoke which, in the automotive industry, have been evolved from simple human inspection systems to complex computer vision systems based on internal IT. TQM also takes advantage of the fact that IT offers a powerful tool for the statistical management of processes through quality control charts.


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Furthermore, IT provides supports to the maintenance function through an effective performance monitoring and evaluation which can prevent interruptions and suboptimal behaviour (Riezebos et al., 2009). The lean framework also seeks a low inventory level at the production point where components need to be delivered when required, in other words, JIT (White et al., 1999), with the required quality and continual improvement (kaizen) (Montabon, 2005). In this way, companies with highly developed internal IT systems will achieve automated information flow among their internal processes, which will have a positive influence on quality, delivery time and continuous improvement. Although lean practices are part of a philosophy reaching all areas within the company and that, on a conceptual level, could be carried out without the help of IT, it seems that internal IT could be considered as tools to facilitate the adoption of lean practices. There are some research antecedents that support a positive relationship between some IT systems and the implementation of some lean practices. Likewise, Bruun and Meeford (2004) discussed how IT integration can facilitate lean practices, while Ward and Zhou (2006) found that internal IT integration is associated with the implementation and the use of effective lean practices. Nevertheless, Bruun and Meeford (2004) did not perform an empirical study to test their hypothesis, whereas Ward and Zhou (2006) focussed on the mediating effect of lean practices on the relationship between IT integration on lead-time performance. They found that when lean practices are in use, the effect of ERP on lead time is higher. Taking into consideration all the aforementioned arguments, we can consider that high level of use of internal IT would facilitate a higher level of adoption of LP as stated in the following hypothesis: H1

There is a positive relationship between the use of internal or intra-organisational IT and the level of adoption of LP.

External IT systems can also have a role of facilitator of the level of adoption of LP, given the need to create and maintain a high implication by suppliers. Certain lean practices, such as JIT and TQM, are particularly sensitive to the implication of suppliers, and external IT systems can play an important role in their adoption. Web technologies can favour lean practices by allowing more standardised components to be found quickly and online. In the same way, web technologies favour the online selection of suppliers more capable of delivering the components required quickly, in better conditions and with the required quality. External IT systems, such as online auctions, also achieve efficiency through the elimination of unnecessary costs, while the use of external IT that enable online collaboration with suppliers when planning production and the delivery of materials could have a great influence on the adoption of lean practices. Companies using the LP framework, together with the use of organisational configurations based on external IT systems and e-commerce are giving rise to a new evolutionary kind of production system that is much more agile, flexible and can be adapted to a constantlychanging environment, which is the logical next step after LP and is known as agile manufacturing (Hormozi, 2001). The above argument is supported by previous research. Ward and Zhou (2006) found that lean practices mediate the influence of between-firm IT integration on lead-time performance. They state that there is an empowering effect of lean practices on external IT systems used to tighten the links between organisations (such as web technologies, e-commerce and e-business) and their relationship with lead-time. Homer and Thompson (2001), when studying the use of e-commerce to develop lean practices by

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interconnecting the supply chain of 20 medium-sized firms in the automotive sector in Europe, state that these e-commerce systems need to adjust and be complementary to lean practices in order to achieve a successful implementation. Bruun and Mefford (2004) also state that the internet and e-commerce acquire a role of facilitators when developing lean practices according to the study of three relevant cases: 1

Computer manufacturer Dell Computer interconnects all its suppliers via web technology so that all computers bought via e-commerce are available using JIT without the need for a stock of items

2

Cisco Systems, leading manufacturer of network routers, receives over 80% of all orders via the internet, and uses over 37 electronic service manufacturer companies around the world to manufacture its equipment and carry out deliveries through logistic operators that are also interconnected electronically in such a way that Cisco employees never handle the products

3

Østergaard Danish Automotive Materials (ØDAM), which imports and exports auto spare parts, underwent a radical transformation after incorporating web and e-commerce technologies with its clients and suppliers.

Although Bruun and Mefford’s (2004) conceptually backs the idea of a positive association between external IT and LP, it needs of further empirical evidence. Taking into account the aforementioned arguments: H2

4

There is a positive relationship between the use of external or inter-organisational IT and the level of adoption of LP

Research methodology

4.1 Data collection and sample characteristics In the automotive industry there is much greater interdependence between assemblers and suppliers. The relationships between assemblers and suppliers are not confined to the pursuit of short-term economic imperatives of cost reduction but embrace innovation in technology and creative, and joint, research and development. The influences of globalisation, implementation of LP and the development of modularisation have had profound influences on the relationship between automobile assemblers and their suppliers, in particular those in the first tier (Morris et al., 2004). This industry is also well-known for using electronic linkages with their trading partners (Kim et al., 2006). The hypotheses have been tested using data from a sample of manufacturing plants which are first tier suppliers to original equipment manufacturers (OEMs) in the Spanish automotive industry. The initial sample frame is from the database of the Spanish Automotive Equipment and Components Manufacturers Association (SERNAUTO). SERNAUTO is the only Spanish association in the automotive sector which gathers all equipment and component manufacturers located in Spain. SERNAUTO’s staff draws up periodical reports and statistics about the situation of the equipment and component manufacturing industry. To draw up the aforementioned reports and periodical statistics, SERNAUTO built up a database with information about the structural and organisational features of each manufacturing plant in the industry. This database can be used for


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research purposes upon SERNAUTO’s authorisation and has been frequently used in prior literature (Martínez and Perez, 2003; Lapiedra et al., 2004). SERNAUTO’s database was made up (on December 31st 2007) by a total of 216 manufacturing plants belonging to 74 different companies (first tier suppliers). Before sending the questionnaire, a draft version was tested with three directors working for one of the most important automotive components and equipment suppliers in the world with presence in 22 countries and a panel of five renowned researchers (full and associate professors) who authored, at least, three articles in leading production and operations management journals (indexed in the JCR of ISI) in the last five years. The questionnaires were sent to the aforementioned directors and researchers by e-mail. With the e-mail, we attached a form so that the directors and researchers could include any relevant comments about item wording, content and order within the questionnaire. All the forms were returned using the same means (e-mail) by the directors and researchers after a phone follow-up and within the expected deadline. A pilot study was then carried out in three different manufacturing plants to ensure that the definitions of items were meaningful and comprehensive for the sample. This ensured content validity. According to Phillips (1981), high (versus low) ranking informants tend to be more reliable sources of information. We chose to sample CEOs since they have the required knowledge of LP adoption. The questionnaire was sent to the CEOs in January and February 2008 by a combination of regular mail, e-mail and internet-based survey methods. Attached to the questionnaire was an explanatory letter highlighting the purpose and aims of the study and asking the CEO to take part. The letter also mentioned that other directors were participating in the survey. After a telephone follow-up process, 84 fully completed questionnaires were obtained (39%), giving a sample error of + 8.54% with a confidence level of 95%. With regards to respondents, as well as CEOs, in ten cases the director of operations also took part and in 27 cases the director of human resources. The regional distribution of the plants in the sample is similar to the distribution of the population as a whole. Most plants are located in the north of Spain (60.7% of the sample as opposed to 64.9% of the population). The two regions with greater presence of manufacturing plants, both in terms of population and in the sample, are Catalonia (38%) and Castile and Leon (13%). The sample covers different manufacturing activities related to the manufacturing and assembly of components to OEMs automotive industry. Table 1 shows the distribution of the sample and the population in the most representative industrial activities and shows a similar distribution in the sample compared to population. With regard to distribution by sample size, small plants (up to 249 employees) account for 41.7% of the sample, medium-sized plants (from 250 to 499 employees) account for 34.5%, while large plants (from 500 employees up) account for 23.8%. Finally, random telephone calls were made to plants that did not return the questionnaire, with no evidence of any specific pattern explaining why companies failed to respond or reasons for not doing so. In general, there does not seem to be a particular kind of plant that was more likely to respond, so reducing the non-response bias that could appear in mailed surveys. Also, early versus late respondents were compared (Armstrong and Overton, 1977) and no statistically significant differences were found on any study variables (α = 0.05).

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Table 1

Industry distribution of the sample and the population

ISIC

Industry

Sample

Population

n

%

N

%

343

Manufacture of parts and accessories for motor vehicles and their engines

49

58.3

107

49.5

252

Manufacture of plastics products

11

13.1

26

12

319

Manufacture of other electrical equipment

6

7.1

13

6.1

289

Manufacture of other fabricated metal products, metalworking service activities

6

7.1

10

4.6

Other industries (22 industries)

12

14.4

60

27.8

Total

84

100

216

100

4.2 Measures We employed a number of measures addressing internal IT, external IT, LP and control variables. Each set is described in detail below (Table 2). In the case of internal IT, respondents were asked to rate the extent the level of implementation of internal IT (1 = not implemented to 7 = fully implemented). In the case of external IT respondents were asked to rate the level of implementation of e-business technologies (1= not implemented to 7 = fully implemented). To identify the main underlying constructs we used a factor analysis complemented with a varimax rotation. Factor analysis estimates how much of the variability is due to common factors (‘communality’); this method is able to analyse variability among observed variables in terms of fewer unobserved variables called factors. Factor analysis assumes that every observed variable can be described as a linear combination of the unobserved variables (factors), being the factor loadings the constants which multiply every factor in the linear equation (1). Varimax rotation is a change of coordinates used in the analysis that maximises the sum of the variance of the squared loadings (Kaiser, 1958). xi − μi = li1F1 + ... + likFk + εi

(1)

xi = observable random variable i μi = mean for variable i lij = factor loading for xi on factor j F1 = factor j εi = error in variable i Results of factor analysis are shown in Table 2. There are two resulting factors; all initial eigen values were higher than one and the total variance explained was 67.5%. The first factor measures internal IT and includes: a

the use of CAD for parts and items design in the manufacturing process

b

the use of CAM in order to plan and control the manufacturing process


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c

the use of CAE, which includes software to support engineers in tasks such as analysis, simulation, design, diagnosis and repair

d

the use of CAPP in order to transform design specifications into manufacturing instructions

e

the use of FMS, which is a combination of software and hardware elements that enable the manufacturing system to react to changes

f

the use of ERP in order to integrate the manufacturing with the rest of functions. This construct (internal IT) is made up of the elements used to define computer-aided production management systems (Riezebos et al., 2009; Narasimhan et al., 2006).

Table 2

Internal and external IT

Factor

Variable

Internal IT

External IT

Variable average

Factor loading

Factor average

Cronbach’s α

5.31

0.757

4.94

0.77

Using CAM

4.25

0.611

Using CAE

4.45

0.836

Using CAPP

4.55

0.855

Using FMS

4.40

0.864 3.20

0.71

Using CAD

Using ERP

6.70

0.655

Online finding and selecting of suppliers for commodity components

2.53

0.611

Purchasing material through online auctions

2.69

0.767

Support web-based EDI

4.23

0.641

Enabling collaboration with suppliers on scheduling and replenishment online

3.37

0.804

The second factor (external IT) follows Devaraj et al.’s (2007) definition and is made up of: a

online finding and selecting of suppliers for commodity components, using the internet as the main means (corporate portals, vertical portals, specialised online-marketplaces, etc.)

b

purchasing materials through online auctions

c

the use of web-based EDI in order to transfer electronic documents between organisations

d

enabling collaboration with suppliers on scheduling and replenishment online.

All participants used the same list of IT definitions while answering the questionnaire. These two factors were then used as independent variables in the regression models, in order to look into their effect on the level of adoption of LP. In the case of LP practices respondents were asked to rate the extent to which statements regarding practice implementation applied to their plant, as compared to their

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industry average (1 = much less, 4 = about the same, 7 = to a much greater extent). In fact, we measured the implementation of LP practices by means of the use of a JIT system, Kanban, SMED, cellular manufacturing, and the adoption of TPM and TQM (Table 3). Indeed, the construct consists of the items commonly used to define LP (Womack and Jones, 1996; Shah and Ward, 2003; Narasimhan et al., 2006). This construct was then used as dependent variable in the regression models. Table 3

Lean production Variable average

Factor loading

Factor average

Cronbach’s α

Location of machines and nearby process in plant

5.69

0.729

5.06

0.79

Manufacturing cells

5.42

0.598

Layout permits reduced inventory levels and faster manufacturing

5.24

0.710

TQM

5.12

0.757

Factor Lean production

Variable

SMED

4.72

0.535

A portion everyday to planned equipment maintenance related activities

5.07

0.742

Maintain all equipment regularly

5.19

0.721

JIT

4.54

0.666

Kanban

4.55

0.650

We tested the validity of each of the constructs. Convergent validity was demonstrated by each factor having loadings in excess of 0.5 (Bagozzi and Yi, 1988), and discriminant validity was also supported, since none of the variables had loadings higher than 0.4 on more than one factor (Fullerton and McWatters, 2001). Construct validity was also supported by the existence of similar measures within the literature (Spina and Zotteri, 2001). Internal consistency was tested using Cronbach’s α. All the constructs have satisfactory alphas (α ≥ 0.7). Control variables were used in the regression model to account for costs and structural factors and all of them have been used in the literature for similar purposes (Johnston and Wright, 2004; Cagliano et al., 2006). The variables used were: number of employees (as a measure of the size of the company), age of plant (as a measure of the age of the factory) and percentage of total costs over direct materials and subcontracting (as a proxy of vertical integration). Descriptive statistics and correlations among the variables used in the analysis are shown in Table 4. Significant correlations exist among control, dependent and independent variables, thus requiring this to be taken into consideration in further analyses.

Impact of use of information technology on lean production adoption Table 4

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Means, standard deviations and Pearson correlations coefficients

Variable

Mean

Standard deviation

1 Lean production

5.14

0.73

2 Internal IT

4.91

0.88

0.38**

3 External IT

3.21

1.31

–0.23*

0.31*

4 Number of employees

377.67

276.19

0.27*

0.07

–0.06

5 Age of plant

23.89

16.12

–0.16

0.09

0.25*

0.32**

6 Percentage of purchasing costs

63.43

11.26

0.15

–0.51**

–0.01

0.03

1

2

3

4

5

–0.22

Notes: N = 84. *Correlations are significant at p < 0.05. **Correlations are significant at p < 0.01.

4.3 Model testing The hypotheses were tested using hierarchical regression analysis. This approach enables the researcher to highlight the percentage of variance explained by each independent variable separately (Pedhazur and Schmelkin, 1991; Cagliano et al., 2006). Partitioning the variance using hierarchical regression analysis is an appropriate methodological choice when some correlations exist among independent variables (Table 4). In order to test the hypotheses, the sets of variables were entered one by one, starting with control variables (Model 1) and subsequently adding internal IT only (Model 2), external IT only (Model 3) and finally adding the two sets of IT together (Model 4). We assessed the contribution of each set of variables by determining the significance of the F-statistic associated with the change in R2 after each set was introduced (Pedhazur and Schmelkin, 1991; Cagliano et al., 2006).

5

Results

The results of the hierarchical regression analysis are shown in Table 5. Model 1, which includes only control variables, does not show any significant relationship between the independent and dependent variables. Model 2 shows that the degree of use of internal IT has a significant influence on the level of adoption of LP. Nevertheless, external IT only have a significant influence on the level of adoption of LP when internal IT systems are controlled (Model 3 and Model 4). These results show that the degree of use of IT has a positive relationship with the level of adoption of LP. The highest level of the R2 is reached by model 4. Therefore, Hypothesis 1 is supported while Hypothesis 2 is not supported.

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Table 5

Analysis of regression of influence of internal and external IT systems in LP

Independent variables

Model 1

Model 2

Model 3

Model 4

Number of employees

0.29

0.31*

0.27

0.18

Age of plant

–0.09

–0.12

–0.02

0.01

Percentage of purchasing costs

0.18

0.31

0.14

0.51**

Internal IT

0.38*

External IT (e-commerce) F 2

R

2

Adjusted R 2

ΔR

0.72*** –0.13

–0.48*

2.27

2.98*

1.53

4.36**

0.12

0.23

0.13

0.38

0.07

0.15

0.05

0.29

0.01

0.26

0.11 2

Notes: Values are standardised regression coefficients (βs). Changes in R are calculated comparing Models 2, 3, 4 to Model 1. *p < 0.05; **p < 0.01; ***p < 0.001.

6

Discussion and implications

The role played by IT systems in the implementation of LP is a field that has not been covered extensively, while the empirical evidence available does not provide conclusive results regarding the influence of IT on the development and adoption of lean practices (Cagliano et al., 2006; Ward and Zhou, 2006). In this paper we have shed light on this matter by finding a direct relationship between the degree of use of internal IT and the level of adoption of LP, while our results show that external IT are not directly related to the adoption of lean practices. We have identified a combined effect which shows that there is a strong relationship between internal IT and LP. This relationship is even stronger when external IT is introduced in the model, yielding in this case a significant negative association between external IT and LP adoption. Taking these two effects together with the relevant increase in explained variance between models #2 and #4 would imply that internal IT is the main independent variable in all the regression models being considered. Furthermore, internal IT overshadows the effect of external IT on LP adoption. Provided that internal IT adoption is high, the relationship between external IT and LP is significant and negative. This result would entail that the greater the investment in internal IT (and lower in external IT), the more advanced the implementation of LP practices. These findings can be considered a significant contribution toward explaining the degree of adoption of LP depending on the level of use and the kind of IT used. Our results point out that in order to develop in the implementation of LP and so increase internal efficiency, companies need to use internal IT that should also be developed intensely before seeking higher external efficiency in activities in which other firms are involved. Companies need to develop internal IT that are more directly related to the efficiency aimed at by lean practices, especially in internal processes that constitute their core components. The use of external IT does not have a positive effect on LP adoption. According to our findings, internal IT effects might outshine the effect exerted by


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external IT on LP adoption. Likewise, the higher the investment in internal IT and the lower the investment in external IT, the higher the level of LP implementation. These findings are related with those stated by Boone and Ganeshan (2001) in which the use of technology is the factor that determines the relationship between IT implementation and productivity. A greater use of internal IT will result in a higher level of efficiency due to having advanced in the level of adoption of LP. The above results offer significant implications for managers involved in the implementation of LP. Managers should carefully analyse investment options in internal vs. external IT if they want to achieve a higher level of LP implementation. If the main corporate target consists of achieving efficiency gains through lean implementation, managers should first increase the amount of investment in internal IT, comparatively reducing at the same time the investment being made in external IT. Conversely, firms might consider higher investments in external IT if they are primarily interested in other non-efficiency targets such as market expansion or sales growth. In later stages, companies with highly developed internal IT would be suited to interconnect in network configurations with companies orchestrated by web technologies for e-business. In this sense, the development of the internal IT of organisations involved in the network is an indispensable prior step in order to add efficiency through external IT. If we look at IT as a wide conjunction including both internal and external IT, and in line with the arguments offered by Powell and Dent-Micallef (1997), LP could be identified as a complementary business resource to IT systems would enable said systems to generate competitive advantages in their companies. Some limitations can be identified in this study. In this paper we have studied the level of adoption of LP in first tier suppliers in the automotive industry. It would be interesting, given that the focus is on a supplier’s relationship with its most important supplier and is therefore somewhat biased, to put the model to test by using multiple informants from each company, not just the information supplied by managers. Moreover, this research has studied the automotive supply chain and we do not attempt to suggest that the findings are universally applicable across different industries in different countries. A logical extension to this paper would be to replicate our model in contrasting empirical contexts. Future papers could also extend the study to all agents in the supply chain by analysing the relationship between supply chain integration and the level of use of internal and external IT. Furthermore, we could not extract causal and time-dependant inferences due to the cross-sectional nature of our data. Hence, longitudinal data is needed for studying causal effects. Given that a cross sectional survey method was employed, causal inferences were derived from theory and existing research only. In this sense, in the future it would be necessary to look at the lag (or temporary delay) effect produced between the moment when the company advances in the level of use of IT, the type of IT being used (internal vs. external), and the advance in the degree of adoption of LP. Future research directions should also focus on the relationship between IT implementation (internal vs. external), LP and the strategic objectives set up by the firm, such as internal efficiency vs. market growth.

Acknowledgements This study was funded by the research projects P8-SEJ3607 and SEJ2006–04777 of the Andalusian Regional Government and the Spanish Ministry of Science and Education.

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