Operating Models in Supply Chain Management and Their Effect on Performance

INFLUENCE OF THE CONNECTION BETWEEN MANUFACTURING STRATEGY AND OPERATIONS ON PERFORMANCE SURVEY RESULTS FROM CENTRAL AND EASTERN EUROPE

Attila Chikán and Krisztina Demeter

Corvinus University of Budapest Fővám tér 8. Budapest, Hungary, H-1093

Key words: manufacturing strategy, action programs, performance

ABSTRACT The connection between manufacturing strategy (represented as competitive priorities) and everyday operations (represented by action programs), and their effect on operational performance is a perpetual issue. In our paper we examine these relationships in the context of Hungary, as a representative of the Central and Eastern European (CEE) region using the data of 54 Hungarian companies of two international surveys: the International Manufacturing Strategy Survey (IMSS) and the survey of the Global Manufacturing Research Group (GMRG). On the basis of our results there are strong connections among competitive priorities, action programs and operational performance. In particular, the priorities of cost, delivery timeliness and environment/safety have the most significant effect on the use of action programs. The use of manufacturing technologies and processes, as well as the HRM programs has the strongest effect on performance.

INTRODUCTION Manufacturing is a core business function within companies. The majority of resources (equipments, people, and facilities) are used there and the majority of costs arise at the manufacturing function. The final product, sold later to the customers, gets shape through manufacturing. Thus the operational performance of companies, such as the circumstances of deliveries, as well as the performance of delivered products and product structure depends heavily on the everyday operations of manufacturing. Since companies have limited resources they need clear strategy about what to produce and how to do that. Manufacturing strategy serve that purpose. Based on business strategy it identifies competitive priorities and makes decisions on strategic questions (Voss, 1995). Thinking about strategy is very different form implementing it. Even if strategy is clear and companies see the potential benefits of the given strategy, they may fail to implement it within their manufacturing organization. It is even more difficult today, in the era of integration, when business functions cannot be separated from each other, and companies

1 are closely linked through various business processes (Lambert-Cooper, 2000). Businesses have to react fast and change dynamically to sustain their competitiveness. In this environment manufacturing strategy, besides the classical issues of competitive priority identification and resource management, inevitably involves issues on supply chains and product development in order to provide the necessary speed and change. We can find very well developed manufacturing strategies in developed countries. Some cases, like Toyota (Dyer, 2000; Spear-Bowen, 1999) or recently Zara (Ferdows et al, 2004) are classical examples for the success achieved through operations. On the basis of international studies, we can see that there are some areas, such as streamlining, pull production, productivity enhancing programs or environment and safety centered practices which nowadays provide competitive advantage from the side of manufacturing. Programs of quality management and information systems have lost that role (Laugen et al, 2005). Globalization, as a driving force behind integration, does not avoid developing countries. Foreign companies take their strategies, resources and methods in these countries and domestic companies also try to follow international trends. Nevertheless, it is a question, to what extent manufacturing strategy, and especially manufacturing practices can contribute to business success, and what kind of strategies are worthwhile to follow in these countries, where, we believe, the major constraint is the lack of capital (see also Moattar and O’Brian, 2004). The most important consequence of this shortage that although the manufacturing strategies are similar in developing countries to those followed in developed regions, the level and kind of practices used may be different. In this paper we examine the case of Hungary as a representative of the Central and Eastern European region. Our objective is to see what kind of manufacturing strategies Hungarian companies follow and how these strategies affect the use of manufacturing practices and operational performances. We used a survey for this purpose. The structure of the paper is the following. First we review the literature, and then introduce our research model. Next the survey is described. After operationalization of the model and the analysis of the data discussion and conclusion close the paper.

LITERATURE REVIEW Manufacturing strategy as a missing link between business strategy and operations was formulated first by Skinner (1969). The area went through tremendous development since that time. Although there is no agreement on the definition of manufacturing strategy, researchers agree that manufacturing strategy can be divided into process and content (Voss, 1995). Within content, which is the focus of this paper Voss (1995) identified three paradigms, and argued that “none (of these paradigms) by itself is sufficient for effective development of manufacturing strategy over the long term. Together they contain all that is required for an effective strategy.” The three paradigms are competing through manufacturing, strategic choice and best practices.  Competing through manufacturing “argues that the firm should compete through its manufacturing capabilities, and should align its capabilities with the key success factors, its corporate and marketing strategies and the demands of the marketplace”. Wheelwright and Hayes (1985) and Hill (1993) are two important contributors to this paradigm.

2  Strategic choices paradigm “is based on the need for internal and external consistency between choices in manufacturing strategy.” The two basic groups of choices are structural and infrastructural decisions.  The underlying assumption of the best practice paradigm is that best practices lead to superior performance and capabilities. World class manufacturing literature, which collects manufacturing programs and practices leading to superior performance, is a good representative of this paradigm (e.g. Voss and Blackmon, 1996). In this paper we connect the first and third paradigms. Although it is a well researched connection as stated by Voss, 1995 there were few specific studies on dealing with these issues in developing countries (Moattar and O’Brian, 2004 or Mellor and Hyland, 2005). In the following these two paradigms are developed further.

Competing through manufacturing The strategic objectives of manufacturing show direction to the operation of the manufacturing function. The most common way in the manufacturing strategy literature is to formulate strategic objectives around cost, quality, reliability, flexibility and services (Miller et al, 1992, Voss, 1995). Although Skinner (1969) argues that there are trade-offs between these competitive objectives, there are some practical and theoretical improvements which, at least partly, contradict to this argument, just think of the success of Japanies cars in America since the 1970s (Hayes-Pisano, 1994), where Japanese companies have been able to deliver good quality cars at low cost; or think of the sand cone model (Ferdows-De Meyer, 1990), where there is a hierarchy among the objectives and quality constitutes the basis followed by reliability, flexibility and cost efficiency.

Best practices There are many researches which support the contribution of quality management practices, especially TQM to business performance. For example, Hendricks and Singhal (2001) examined the relationship between firm characteristics, such as size or diversification, TQM and business performance. Although they found some firm characteristics as important moderating factors, the implementation of TQM practices in general had a positive effect on performance. Samson and Terziovski (1999) also found significant connections between TQM practices and operational performance. They concluded that especially the categories of leadership, management of people and customer focus were the strongest significant predictors of operational performance. But quality management is not only about TQM. As Laugen et al (2005) figured out equipment productivity improvement programs and environment friendly solutions, both of which goes parallel with producing high quality products are also important contributors to business success. Manufacturing strategy makes decisions on resources. Two important resources are technologies and human resources. We could see in Samson and Terziovski (1999) that the management of human resources can significantly affect how successfully various programs can be implemented and how they effect performance. Ahmad and Schroeder (2003) clearly identify the role of HRM in operational performance. Roth and Miller (1992) also conclude that managers and leaders have a much more significant effect on business success than any manufacturing programs. Although having enough capital is a basic requirement to have the right quantity and quality resources, the combination of these resources, and the routines set by the

3 companies, or in other words, the capabilities will determine the competitive position and progress of companies (Voss, 1995), since the resources themselves are available for any company on the market. One good example of the performance effect of using the same technology differently is described by Jaikumar (1986). JIT and lean management as programs which combine resources and capabilities along specific principles are strong contributors to business success (Laugen, 1995). Furthermore, implementing JIT, TQM and TPM programs (Cua et al, 2001) or JIT, TQM and supply chain management (for example supplier development programs) practices together can have some synergic effect (Kannan and Tan, 2005). This latter reference makes clear that using internal resources is a critical step towards success, but not enough. Globalization and shorter life cycles demand faster reaction from companies. In order to react faster companies focus more and more on their core competences, outsource less important processes and rely heavily on their partners. Clear supplier segmentation rules (Bensaou, 1999); strategic partnerships (Mentzer et al, 2000); integrated information systems; partner-specific investments (Dyer, 1996) help partners or even whole supply chains to improve their competitiveness. Frohlich and Westbrook (2001) nicely show that companies who make efforts for tighter coordination both towards customers and suppliers can improve faster. Continuous change does not let companies to relax on their existing, well working internal and external processes and products. They have to develop new products and new processes in order to sustain their competitive position. So fastening and streamlining product development efforts by leadership tactics (such as explicit goals, rewards, pre- training), by organizational integration of manufacturing and product development to achieve faster ramp up (e.g. team work, co-location), by design analysis tactics (DFM, QFD) as well as computer based tools (e.g. CAD-CAM) must be part of manufacturing practices (Swink, 2002). Tseng (2006) also found that early cooperation between product development and manufacturing can fasten new product introduction to market.

Connection between priorities and best practices All of these efforts have to take into account the priorities set by business and manufacturing strategy. If, for example companies focus on cost reduction, action programs have to eliminate wastes from processes, have to concentrate on efficiency issues, or have to select suppliers on the basis of prices. On the other hand, if flexibility is in focus, companies have to attack time issues and technological flexibility. Operational performance may show how companies could fit their objectives and practices. If their objectives were clear and they invested into the right actions they must have improved their operational performance.

THE MODEL We developed a very simple model to link manufacturing strategy and actions made as well as their effect on operational performance. Our model can be seen in Figure 1.

4 Manufacturing strategy (Competitive priorities) H1 Programs (best practices)

Manufacturing Quality HRM and Supply chain Product technology and management organization management development processes

H3 H2 Operational performance

Figure 1: The link between manufacturing strategy, action programs and performance

In our model competitive priorities affect the use of best practices. If companies are forced by the European market to improve quality and delivery timeliness then they will make actions to make that happen. They can, of course, follow different routes; the only objective is to obtain the required capability (Hayes and Pisano, 1994). Competitive priorities affect operational performance. This effect, as we believe, is mainly indirect. That is, if we decide to compete on quality then we have to implement quality management programs, such as TQM, or have to certify our processes by ISO and these steps will lead to improved operational performance. However, there might be some direct effects, as well. If companies make a good selection of the priorities, which really fit the marketing requirements, then that in itself can result in higher performance. Using the research model in Figure 1 our hypotheses are the following: H1: Companies with different sets of strategic priorities implement different sets of programs. H2: Companies with different sets of priorities improve different operational performance measures. In other words, manufacturing strategy has a direct effect on operational performance. H3: The different sets of programs lead to different operational improvements.

THE SURVEY Our analysis is based on the Hungarian data of IMSS-IV (International Manufacturing Strategy Survey) and GMRG-III (Global Manufacturing Research Group) surveys conducted between November 2005 and January 2006. Both international surveys started more than 15 years ago with the objective to have an international picture on how companies work all over the world (Whybark 1993, 1997, Lindberg et al 1998). A lot of papers used manufacturing data of these surveys as an empirical base (eg., Laugen et al, 2005; Husseini, 2004; Acur et al 2003; Demeter, 2003; Corbett et al (2001), Frohlich- Westbrook, 2001). It is our tradition in Hungary to put the two international questionnaires of these surveys into one set and data are collected for the two surveys from the same companies. The fact that the two surveys have some questions which relates to the same or very similar issues,

5 provide a good opportunity to check the reliability of data and can provide basis for deeper analysis. The causes of redundancies are carefully explained to managers in order to avoid frustration. Since this double questionnaire is relatively long (23 pages) it might prevent some companies to fill it in. The number of incoming questionnaires however was high enough not to worry about this problem. The sample was selected on the basis of company data issued by the Hungarian Central Statistical Office on a CD in the middle of 2005. The CD contained company names, industry, sales and employee data (both categorized), and access data. All companies were selected which satisfied three criteria: a) they belong to ISIC sectors 28-35 (fabricated metal; machinery; office equipment; electrical machinery; radio, television, communication equipment; medical and precision instruments; motor vehicles; other transportation), b) they have more than 50 employees and c) have existed at least since 2002. IMSS-IV placed restrictions a) and b), and due to some parts which are related to status quo 2 or 3 years ago, we set restriction c). Altogether 789 companies were identified, as our starting population. Some companies did not provide access data in the database (631 remained). Also, pre-selection were made to find better performing companies on the basis of sales and employee data, it was a request from IMSS (435 companies remained). Then we tried to access companies to get the names and direct access of production managers. At the end of the process described above 244 companies remained. This is the size of our targeted sample. Then we sent out an invitation letter and some days afterwards students directly contacted production managers. Students made calls week by week to force companies to fill in the questionnaire. Altogether we got 54 questionnaires back, which is a 22% response rate.

OPERATIONALIZATION AND RESULTS Shortly, the steps of analyses were the following: 1. We created two clusters on the basis of strategic priorities: cost reducers and differentiators. 2. Using the model described in Figure one, constructs were identified for action programs and for operational performances. 3. We used ANOVA and correlation analysis to test our hypotheses. For statistical analyses we used SPSS 11.0.

Strategic priorities: cost reducers and differentiators Our first task was to find out what kind of strategies companies follow. A usual problem, as we discovered in previous IMSS and GMRG surveys, that competitive priorities are detected through Likert scales and companies are inclined to answer that all or at least very many objectives are of high importance for manufacturing. In GMRG III this question has been changed and companies had to divide 100 points among some priorities (see the related questions in the Appendix, and sample averages is Table 1). We decided to use this question in order to find differences in strategies, and we intentionally created two groups by cluster analysis (k-means cluster). The intention came from theoretical and methodological sources. First, in Porter’s book (1980) two fundamental types of strategies were identified: cost leader and differentiator strategies. Cost leaders focus on reducing costs and earning profit by the higher difference between market prices and their own cost (we call them cost reducers, because they are not necessarily leaders but compete majorily

6 on costs and prices). Differentiators earn profit by differentiating themselves from the competitors. The differentiating factor can be quality, flexibility, time, company image or any other factor but cost. The latter strategy is followed more frequently since this kind of competitive advantage can be attacked less easily than cost leadership. Second, our original sample size is 54 (but 4 companies did not answer these questions) which, in order to ensure large enough sizes of the subgroups do not allow us to use more than 2 groups (Lehmann, 1989), especially if we make further analyses on these groups. The results of our cluster analysis can be found in Table 1.

Table 1: Manufacturing priorities as set by top management – based on cluster analysis Clusters Sample Cost Differen- F Manufacturing priorities average reducers tiators (significance) (points) (points) (points) Cost (price) 37 53 22 112.3 (0.000) Quality (conformance to specification) 24 21 27 9.3 (0.004) Delivery timeliness 18 12 22 19.8 (0.000) Product Variety/Volume 8 5 11 5.7 (0.210) New Product Design/Innovation 7 5 9 4.7 (0.036) Environment/Safety 6 4 9 10.2 (0.002) Total 100 points 100 points 100 points Number of companies 50 23 27

Obviously in case of cost reducers the highest priority is put on cost. Although quality and delivery timeliness are still relatively important, their values are significantly lower than among differentiators. In this latter group, although price have a relatively high priority the first is inevitably quality. Important to see, that new product design and environmental issues are used more frequently in this group as a competitive priority.

Constructs on action programs and operational performances First, we created constructs of action programs (see Figure 1), such as quality management, manufacturing technologies and processes, etc. For example, in case of quality management we asked in the questionnaire the extent of use on a 5 point Likert scale of the following practices: - Undertaking programs for quality improvement and control (e.g. TQM programs, 6 projects, quality circles, etc.) - Undertaking programs for the improvement of your equipment productivity (e.g. Total Productive Maintenance programs) - Undertaking programmes to improve environmental performance of processes and products (e.g. environmental management system, Life-Cycle Analysis, Design for Environment, Environmental certification) The Cronbach alpha used to check the reliability of the constructs. For the items above Cronbach alpha is 0.64 (which is acceptable on the basis of Forza (2002)), and there is no item the elimination of which would considerably increase this value. Also, factor analysis was used to check consistency among items (Forza, 2002). Thus after accepting the three items as parts of the quality management construct, we created the construct by simply summing up the three items. With using the construct we got one value of action programs

7 in quality management instead of three. The same approach was used to create constructs for manufacturing technologies and processes, HRM and organization, supply chain management and product development. Table 2 contains our results (complete questions can be found in the Appendix).

Table 2: Constructs of action programs Item/construct Cronbach alpha / Factor Action programs (1-5 scale) and CONSTRUCTS average* loadings** QUALITY MANAGEMENT 7.91 0.64 Quality improvement programs (eg. TQM) 2.95 0.68 Equipment productivity improvement programs 2.69 0.87 Improve environmental performance 2.28 0.73 MANUFACTURING TECHNOLOGY AND PROCESS 10.07 0.71 (Expanding manufacturing capacity) (3.38) (0.53, left out) Restructuring manufacturing processes and layout to obtain 2.81 0.79 process focus and streamlining Action programs to implement pull production 2.62 0.73 Engaging in process automation programs 2.08 0.61 Implementing ICT and/or ERP software 2.58 0.80 HRM AND ORGANIZATION 10.42 0.72 Increase the level of delegation and knowledge of your 2.54 0.82 workforce Implementing the Lean Organisation Model (reduce levels, 2.56 0.70 broaden span of control) Continuous Improvement Programs through systematic 2.31 0.80 initiatives (eg. kaizen) Increasing the level of workforce flexibility 3.02 0.65 SUPPLY CHAIN MANAGEMENT 11.89 0.75 Supply strategy, suppliers portfolio (e.g. outsourcing, and 2.80 0.76 supply base reduction) supplier development and vendor rating 2.78 0.69 Increasing the level of coordination of planning decisions 2.02 0.75 and flow of goods with suppliers Distribution strategy in order to change the level of 2.21 0.67 intermediation (e.g. using direct selling) Increasing the level of coordination of planning decisions 2.07 0.67 and flow of goods with customers PRODUCT DEVELOPMENT (PD) 8.04 0.77 Increasing performance of PD through e.g. platform design, 2.75 0.82 standardization and modularization Increasing the organizational integration between product 2.63 0.86 development and manufacturing Increasing the technological integration between product 2.67 0.80 development and manufacturing through e.g. CAD-CAM *construct average is the sum of the related item averages. ** Cronbach alpha for the construct and factor loadings for the items

There was only one item, expanding manufacturing capacity, which we had to leave out due to low factor loading. All other items can be used and the resulting constructs are reliable.

8 Second, we used similar procedure for operational performance. Since our strategic groups were organized around a) cost (price) and b) other differentiating priorities (like quality, reliability, flexibility, etc.), we decided to create two constructs: cost related measures and non-cost measures. Data can be found in Table 3.

Table 3: Constructs of operational performance Operational performances (1-7 scale) and CONSTRUCTS Item/construct Cronbach alpha / Factor average* loadings** COST PERFORMANCE 8.20 0.76 direct manufacturing costs 4.12 0.90 total product costs 4.08 0.90 raw material costs (3.67) (0.58, left out) NON-COST PERFORMANCE 29.57 0.85 (product features) (4.87) (0.51, left out) product performance 4.90 0.65 perceived overall product quality 4.92 0.67 order fulfillment speed 4.94 0.80 delivery as promised 4.96 0.82 delivery flexibility 5.27 0.82 (flexibility to change output volume) (5.04) (0.57, left out) (flexibility to change product mix) (4.74) (0.50. left out) manufacturing throughput time 4.59 0.73 (new product design time) (4.06) (0.55, left out) *construct average is the sum of the related item averages. ** Cronbach alpha for the construct and factor loadings for the items

Due to low factor loadings some items, mainly flexibility performances, such as volume, mix and product flexibility had to be left out. Both resulting constructs seem to be very reliable.

Testing hypotheses After having the constructs we can have a look at the effect of strategy on action programs (hypothesis 1). Table 4 shows the results.

Table 4: The effect of strategy on the use of action programs (one way ANOVA, H1) Strategic cluster values Constructs of action programs F (significance) Cost reducers Differentiators Quality management 6.79 8.77 7.04 (0.012) Manufacturing technologies and processes 8.36 11.33 13.19 (0.001) HRM and organization 9.17 11.46 8.84 (0.005) Supply chain management 10.78 12.72 4.69 (0.036) Product development 7.10 8.70 2.99 (0.092)

Differentiators devote higher attention to all the investigated areas than cost reducers. Their advantage is extremely high in the use of various manufacturing technologies and processes and in HRM and organizational issues. While investing in new technologies might be expensive, and can prevent smaller or poorer companies to improve the area, organizational issues are different. Lean organization for example require commitment and

9 know how but not too much investment especially as compared to the savings that might be achieved. Since the basis of differentiation can be different, we checked how the competitive priorities are one by one related to the constructs of action programs (see Table 5).

Table 5: The effect of competitive priorities on action programs (correlation, H1) Constructs of action Competitive priorities* programs Cost Quality Reliability Variety Innovation Environment Quality management –0.400 0.132 0.231 0.158 0.146 0.490 Manufacturing technologies –0.487 0.103 0.269 0.197 0.212 0.509 and processes HRM and organization –0.393 0.050 0.337 0.069 0.153 0.461 Supply chain management –0.291 -0.004 0.226 0.139 0.015 0.348 Product development –0.288 0.154 0.139 0.069 –0.028 0.544 *Bold values are significant at 0.05 level, italic values are significant at 0.1 level

As we already discovered the more companies focus on costs and prices the less investment they make in any of the areas (see the results for cost reducers in Table 4). If we analyze the single cost priority we get the same result: all the correlations are negative and significant. Quality focus does not lead to difference in the use of any action program constructs. The same is true for product variety/volume and product design/innovation items. Companies focusing on dependent deliveries use manufacturing technology and processes programs (correlation is 0.27, p=0.062) as well as HRM and organizational programs (r=0.34, p=0.018) more frequently. And finally, quite interestingly, environmental/safety focus is highly correlated to all the constructs (the lowest correlation is 0.35 related to a significance level of 0.017). Our next step is to look at how strategic priorities are related to operational performance (hypothesis 2). The results are summarized in Table 6 and 7.

Table 6: The effect of strategy on operational performance (one way ANOVA, H2) Strategic cluster values Performance constructs F (significance) Cost reducers Differentiators Cost performance 7.71 8.59 3.36 (0.073) Non-cost performance 27.50 31.26 8.45 (0.006)

Table 7: The effect of priorities on operational performance (correlation, H2) Operational performance constructs Strategic priorities Cost performance Non-cost performance Cost –0.261 –0.255 Quality 0.103 0.220 Reliability (delivery timeliness) 0.265 0.271 Variety 0.195 –0.046 Innovation –0.095 –0.128 Environment/safety 0.038 0.257 *Italic values are significant at 0.1 level

Cost focus definitely has a negative impact on both cost (r=–0.261, p=0.074) and non-cost (r=–0.255, p=0.077) operational performance. If we go deeper again into the kind of

10 differentiation (Table 6), we can see that delivery timeliness is the only focus which has a weak positive correlation with both cost (r=0.265, p=0.069) and non-cost performance (r=0.271, p=0.059). Besides, focus on environment and safety results in better non-cost performance (r=0.257, p=0.075). Other differentiating factors, such as quality conformance, product variety/volume and product design/innovation are not related significantly to operational performance.

Table 8: The correlation of action programs with operational performance (H3) Operational performance contructs Action program constructs Cost performance Non-cost performance Quality management 0.260 (0.105) 0.346 (0.031) Manufacturing technologies and processes 0.255 (0.084) 0.302 (0.037) HRM and organization 0.357 (0.014) 0.311 (0.031) Supply chain management 0.105 (0.521) 0.259 (0.111) Product development 0.047 (0.750) 0.249 (0.091)

The use of action programs in general has stronger effects on operational performance than the competitive priorities themselves (compare Table 7 and 8). Implementing action programs in manufacturing technologies/processes and in HRM/organization has a direct positive effect on both cost and non-cost performance. Quality management and product development programs affect only non-cost performance significantly. Supply chain management practices do not affect operational performance.

DISCUSSION OF THE RESULTS Cost reducers and differentiators are very different in using various action programs in manufacturing. In general, differentiators use all the action programs at higher level than cost reducers (Table 4). It means that cost reduction activities are so strong in the group of cost reducers, that they make limited investments in manufacturing to improve their performance. The smallest difference between cost reducers and differentiators is in the use of product development programs. This can be explained with the generally low level of innovation in Hungary (Chikán et al, 2002), even in multinational companies who usually make R&D activities elsewhere. Different set of priorities leads to different operational results. Differentiators achieve better performance in both cost and non-cost terms (Table 6). It is on a way a very contradictory result: those who concentrate on cost achieve worse cost performance. We can have two explanations here. First, reducing costs, for example by laying off people, lowering wages, reducing the level of quality control might easily result in worse customer service due to late deliveries, slower reaction to customer requests and complaints, poorer product quality. If customers consider these aspects as important part of the service package then they will replace the supplier. Second, in the rapidly changing world companies continuously have to make investments in order to maintain their competitiveness. Focusing on costs too heavily might result in holding back necessary investments which can directly lead to deteriorative competitiveness and poor performance. This second explanation directly leads us to the connections between action programs and performance (Table 8), which are also strong, especially in case of non-cost performance.

11 More specifically, the use of quality management programs, manufacturing technologies and processes and HRM programs are good predictors of good performance. Summarizing the results of the hypotheses, the sets of priorities have a direct effect on both the use of the action programs and on operational performance: companies using the strategy of differentiating implement all the action programs, in general, more heavily, and achieve better operational performance. The use of action programs is worthwhile, especially in increasing the level of non-cost performance.

Going deeper into the specific competitive priorities, there were three of them: environment/safety, cost, and delivery timeliness which had a significant impact on the use of action programs (see Table 5). Among them, placing emphasis on environmental issues has the largest impact on action programs and it also has some weak correlation with operational performance. A possible answer to this result can be that companies who focus on environmental issues are rather advanced in solving the problems in other areas, implemented the majority of action programs, and environmental progress is the next step of development in their life. For example, companies first obtain ISO 9000 certificate and they go for ISO only in the next step (or sometimes paralelly, but definitely not before). There are other answers, however. Thorpe and Prakash-Mani (2003), for example describes the benefits of greening through case studies: as they argue, companies can reduce costs by saving energy and material with eco-production, and they can also win by lower pollution fees and fines. Moreover, improved working environment and safety conditions increase productivity. Striving for better products and processes increases innovativeness, and help involvement of people. All in all, sustainability seems to pay-off. Gonzales-Benito and Gonzales-Benito (2005) used a survey and examined the relationship between environmental proactivity and business performance. They could only partly support the relationship. They found some practices which affected negatively business performance. On the other hand, Laugen et al (2005) found that environmental practices can be one of the competitive edges nowadays. Concentrating mainly on cost, on the other hand, has negative impact on the use of action programs and on both cost and non-cost operational performance. This result clearly shows that high cost focus can prevent introducing programs (“we do not have money for this”) which could lead to improvements and benefits. This kind of short-sightedness refers to the lack of strategy in these companies, but also it can also be connected to the lack of financial resources at SMEs, since bank loans are very expensive. Delivery timeliness requires internal actions from companies. Process focus and pull techniques as well as the use of information technology can improve delivery reliability. However, improvements in manufacturing (and information) technology require intensive employee training to learn to handle new machines and tools. Moreover, improvements in processes, in addition, require a completely new approach to look at processes and customers. Actually, changing the attitudes and habits of employees is much more time consuming and difficult than implementing new technology. Quite interestingly supply chain management is not in correlation with delivery timeliness. We think this can be explained by the very low level of supply chain management practices used in Hungary, especially on the customer and distribution side (see the averages in Table 2 and also Demeter, 2000). If we have a look at the direct connection between specific competitive priorities and operational performance (Table 7), the results are not very convincing. Again, cost,

12 delivery timeliness and environmental focus are responsible for some weak significant result.

CONCLUSIONS Every country has its own manufacturing practice. As Whybark (1997) wrote the differences between countries are larger than the differences between industries. Ahmad and Schroeder (2003) got the same result studying the connection between HRM practices and operational performance. Although they found some differences between industries (especially between the automobile and other industries), the differences were larger at country level. Nevertheless, both studies could draw some conclusions which are valid worldwide. In our analysis we think there are some things which might be unique for CEE and emerging economies. For example, the low use of product development and supply chain management programs can be explained by cultural, historical and economic reasons in CEE (Humphrey and Schmitz, 1998). The lack of capital is a specialty of emerging countries, not only of the CEE region (Moattar and O’Brian). However, we believe, that the critical role of environment and safety issues among the priorities is one result which can be generalized. The importance of manufacturing processes is supported on international level by Laugen (2005). The use of HRM programs and their effect on operational performance is also an important result, especially if we take into account that this field got very little attention so far in the operations management literature, as mentioned by Ahmad and Schroeder (2003). And finally, the relationship between competitive priorities, action programs and operational performance can also be generalized. The main contribution of this paper is that a region is in the focus, which was not studied very heavily in previous years. Nevertheless, in the last decade or so it became an attractive point of investment.

REFERENCES Acur, N., Gertsen, F., Hongyi S., Frick, J. (2003): The formalisation of manufacturing strategy and its influence on the relationship between competitive objectives, improvement goals, and action plans, International Journal of Operations & Production Management; 2003, Vol. 23 Issue 10, p1114, 28p Ahmed, S. and Schroeder, R. G. (2003): The impact of human resource management practices on operational performance: recognizing country and industry differences, Journal of Operations Management, Vol. 21, pp. 19-43 Bensaou, M. (1999): Portfolios of Buyer – Supplier Relationships, Sloan Management Review, Summer, pp.35-44 Chikán, A., Czakó, E. and Zoltayné Paprika, Z. (editors) (2002): National Competitiveness in Global Economy, Akadémiai Kiadó, 2002 Corbett, Lawrence M., Whybark, D. Clay: Searching for the sandcone in the GMRG data, International Journal of Operations & Production Management; 2001, Vol. 21 Issue 7, p965-980, 16p Cua, K. O., McKone, K. E. and Schroeder, R. G. (2001): Relationships between implementation of TQM, JIT, and TPM and manufacturing performance, Journal of Operations Management, Vol. 19, pp. 675-694 Demeter, K. (2003): Manufacturing strategy and competitiveness, International Journal of Production Economics, Vol. 81-82, 2003, pp. 205-213

13 Demeter, K. (2000): Buyer-supplier relations in manufacturing: integration in practice — Experiences of an international survey, Business Briefing: European Purchasing and Supply Chain Strategies, July 2000, pp. 149-155 Demeter, K. – Gelei, A. (2003): Supply chain management framework: Dimensions and development stages; EUROMA Annual Conference 2003: “One world – one view”, Proceedings, Servizi Grafici Editoriali, Padova – Italy Dyer, J. H. (1996): Specialized Supplier Networks as a Source of Competitive Advantage: Evidence from the Auto Industry, Strategic Management Journal, Vol.17., No. 4, 271-291 Dyer, J. H. and Nobeoka, K. (2000): Creating and managing a high-performance knowledge-sharing network: the Toyota case, Strategic Management Journal, Vol. 21., pp. 345-367 Ferdows, K., Lewis, M. A. and Machuca, J. (2004): Rapid-fire fulfillment, Harvard Business Review, Nov, pp. 104-110 Ferdows, K. and de Meyer, A. [1990]: Lasting improvements in manufacturing Performance: in search of a new theory, Journal of Operations Management, Vol. 9 No. 2, 1990, pp. 168–184. Forza, C. (2002): Survey research in operations management: a process based perspective, International Journal of Operations and Production Management, Vol. 22, No. 2, pp. 152-194 Frohlich, M. T., and Westbrook, R. (2001): Arcs of integration: An international study of supply chain strategies, Journal of Operations Management, Vol 19. pp. 185-200 Gonzales-Benito, J. and Gonzales-Benito, O. (2005): Environmental proactivity and business performance: an empirical analysis, OMEGA, Vol. 33, No. 1. Hayes, R. H. and Pisano, G. P. [1994]: The new manufacturing strategy, Harvard Business Review, Vol. 72, No. 1, pp. 77–86. Hill, T. [1993]: Manufacturing Strategy: The Strategic Management of the Manufacturing Function, Second Edition, MacMillan, London Humphrey, J. and Schmitz (1998): Trust and inter-firm relations in developing and transition economies, The Journal of Development Studies, Vol. 34, No. 4, April 1998, pp. 32-61 Jaikumar, R. (1986): Postindustrial manufacturing, Harvard Business Review, Nov-Dec. pp. 69-76 Kannan, V. R. and Tan, K. C. (2005): Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance, OMEGA, Vol. 33, pp. 153- 162 Lambert, D. M. and Cooper, M. C. (2000), Issues in Supply Chain Management, Industrial Marketing Management, Vol. 29, No. 1, pp. 65-83 Laugen, B. T., Acur, N., Boer, H., Frick, J. (2005): Best manufacturing practices – What do best- performing companies do?, International Journal of Operations & Production Management, Vol. 25., No. 2. Lehmann, D. R. (1979): Market Research and Analysis, Third Edition, Irwin, Homewood, IL Lindberg, P., Voss, C. and Blackmon, K. L. (editors) (1998): International Manufacturing Strategies, Kluwer Academic Publishers, Netherland Mellor, R. and Hyland, P. W. (2005): Manufacturing management programs: are developing economies bridging the strategic gap?, Technovation, Vol. 25, pp. 857-863 Mentzer, J. T. – Min, S. – Zacharia, Z. G. (2000): The nature of interfirm partnering in SCM, Journal of Retailing, Vol. 76 (4), pp. 549-568 Miller, J. G., De Meyer, A. and Nakane, J. (1992): Benchmarking Global Manufacturing, Business One Irwin, Homewood, Illinois

14 Moattar, H. S. M. and O'Brien, C. (2004): Strategic implications of manufacturing performance comparisions for newly industrialising countries. International Journal of Operations & Production Management Porter, M. (1980), Competitive Strategy, The Free Press, New York Roth, A. and Miller, J. G. [1992]: Success factors in manufacturing, Business Horizons, Vol. 35 No. 4, pp. 73–81. Skinner, W. (1969): Manufacturing: missing link in corporate strategy, Harvard Business Review, Vol. 47, No. 3, pp. 136–45. Spear, S. – Bowen, H. K. (1999): Decoding the DNA of the Toyota Production System, Harvard Business Review, September-October Swink, M. (2002): Product development – faster, on time, Research-Technology Management, Vol. 45, No. 4, July-August, pp. 50-58. Thorpe, J. and Prakash-Mani, K. (2003): Developing value – The business case for sustainability in emerging markets, Greener Management International, Winter, Vol. 44, pp. 17-33. Tseng, Y. H. (2006): Examining the relationship between the design-manufacturing cooperation and new product development time performance: the moderating role of technological innovativeness, Journal of American Academy of Business, Vol. 9, No. 1, pp. 133-138. Voss, C. A. [1995]: ”Alternative paradigms for manufacturing strategy”, International Journal of Operations and Production Management, Vol. 15 No. 4, 1995 pp. 5–16. Voss, C. and Blackmon, K. (1996): The impact of national and parent company origin on world-class manufacturing, International Journal of Operations and Production Management, Vol. 16, No. 11, pp. 98- 115 Wheelwright, S. C. and Hayes, R. H. (1985): Competing through manufacturing, Harvard Business Review, Vol. 63, No. 1, pp. 99–109 Whybark, D. C. (1997): GMRG survey research in operations management, International Journal of Operations and Production Management, Vol. 17. No. 7. pp. 686-696 Whybark, D. C. and Vastag, Gy. (editors) (1993): Global Manufacturing Practices, Collected papers, Elsevier, Amsterdam

Appendix COMPETITIVE PRIORITIES Given the following goals, rate the extent that the plant is evaluated by top management? (Totals to 100 points)? Overall Competitive Goal Weight percentage Cost (Price) ______Points Quality (conformance to specifications) ______Points Delivery timeliness ______Points Product Variety/Volume ______Points New Product Design/Innovation ______Points Environment/Safety ______Points Total (Sums to 100 Points) 100 Points

15 OPERATIONAL PERFORMANCE For each of the items listed below, how does your plant’s performance compare with your competitors? (Circle a number.) Far Worse Competitive Far better Direct manufacturing costs 1 2 3 4 5 6 7 Total product costs 1 2 3 4 5 6 7 Raw material costs 1 2 3 4 5 6 7 Product features 1 2 3 4 5 6 7 Product performance 1 2 3 4 5 6 7 Perceived overall product quality 1 2 3 4 5 6 7 Order fulfillment speed 1 2 3 4 5 6 7 Delivery as promised 1 2 3 4 5 6 7 Delivery flexibility 1 2 3 4 5 6 7 Flexibility to change output volume 1 2 3 4 5 6 7 Flexibility to change product mix 1 2 3 4 5 6 7 Manufacturing throughput time 1 2 3 4 5 6 7 New product design time 1 2 3 4 5 6 7

ACTION PROGRAMS Indicate degree of the following action programmes undertaken over the last three years and planned efforts for the coming three years. Degree of use Action programs last 3 years None High QUALITY MANAGEMENT PROGRAMS Undertaking programs for quality improvement and control (e.g. TQM programs, 6 projects, 1 2 3 4 5 quality circles, etc.) Undertaking programs for the improvement of your equipment productivity (e.g. Total Productive 1 2 3 4 5 Maintenance programs) Undertaking programmes to improve environmental performance of processes and products (e.g. environmental management system, Life-Cycle Analysis, Design for Environment, Environmental 1 2 3 4 5 certification) MANUFACTURING TECHNOLOGY AND PROCESS PROGRAMS Expanding manufacturing capacity (e.g. buying new machines; hiring new people; building new 1 2 3 4 5 facilities; etc.) Restructuring manufacturing processes and layout to obtain process focus and streamlining (e.g. 1 2 3 4 5 reorganize plant-within -a-plant; cellular layout, etc.) Undertaking actions to implement pull production (e.g. reducing batches, setup time, using kanban 1 2 3 4 5 systems, etc.), Engaging in process automation programs 1 2 3 4 5 Implementing Information and Communication Technologies and/or ERP software 1 2 3 4 5 HUMAN RESOURCE MANAGEMENT AND ORGANIZATION PROGRAMS Implementing actions to increase the level of delegation and knowledge of your workforce (e.g. 1 2 3 4 5 empowerment, training, autonomous teams, etc.) Implementing the Lean Organisation Model by e.g. reducing the number of levels and broadening the 1 2 3 4 5 span of control. Implementing Continuous Improvement Programs through systematic initiatives (e.g. kaizen, 1 2 3 4 5 improvement teams, etc.) Increasing the level of workforce flexibility following your business unit’s competitive strategy (e.g. 1 2 3 4 5 temporary workers, part time, job sharing, variable working hours, etc.)

16 SUPPLY CHAIN MANAGEMENT PROGRAMS Rethinking and restructuring supply strategy and the organization and management of suppliers 1 2 3 4 5 portfolio through e.g. tiered networks, bundled outsourcing, and supply base reduction. Implementing supplier development and vendor rating programs 1 2 3 4 5 Increasing the level of coordination of planning decisions and flow of goods with suppliers including dedicated investments (in e.g. Extranet/ EDI systems, dedicated capacity/tools/equipment, dedicated 1 2 3 4 5 workforce, etc.) Rethinking and restructuring distribution strategy in order to change the level of intermediation (e.g. 1 2 3 4 5 using direct selling, demand aggregators, multi-echelon chains, etc.) Increasing the level of coordination of planning decisions and flow of goods with customers including dedicated investments (in e.g. Extranet/ EDI systems, dedicated capacity/tools/equipment, dedicated 1 2 3 4 5 workforce, etc.) PRODUCT DEVELOPMENT PROGRAMS Increasing performance of product development and manufacturing through e.g. platform design, 1 2 3 4 5 standardization and modularisation Increasing the organizational integration between product development and manufacturing through e.g. Quality Function Deployment, Design for manufacturing, Design for assembly, teamwork, job rotation 1 2 3 4 5 and co-location, etc. Increasing the technological integration between product development and manufacturing through e.g. 1 2 3 4 5 CAD-CAM