Relationship between organizational capabilities and performance of target costing: an empirical study of Japanese companies.

Huh, Sungkyoo ; Yook, Keun-Hyo ; Kim, Il-woon 等

INTRODUCTION

Target costing is officially defined in Japan as an overall profit management process by which quality, price, reliability, delivery term and other targets are set at the time of product planning and development at the levels that meet the perceived customer needs. Achievement of these targets is simultaneously attempted in all areas from the upstream to downstream processes (Japan Accounting Association, 1996). As such, for the last 30 years, target costing has made a significant contribution to many Japanese companies by enhancing their competitive positions in the global market (Ansari and Bell, 1997).

Due to a relatively short history of target costing implementation, low performance of target costing in Western companies can be attributed to two reasons: 1) lack of an empirically proven theoretical framework and generalized guidelines for implementation and 2) inability in terms of employees' attitude and organizational maturity to adapt to radical changes caused by the introduction of target costing (Yook, 2003). During the last decade, many studies have been conducted using a case approach or questionnaire and helped identify key prerequisites in introducing target costing successfully (Ansari and Bell, 1997; Cooper and Slagmulder, 1999a; Kato, 1993; Tani and Kato, 1994; Tani, 1995). These studies, however, failed to identify the core success factors that should be aggressively managed when target costing is introduced, to find out how to evaluate the performance of target costing once implemented, and to test if a company is ready for target costing. Some of the previous studies defined success factors as a combination of organizational resources and routines developed within the organization, such as necessary tools (e.g., VE, Cost Table, etc.), cross-functional structure, top management support, and a heavyweight project manager.

This study will focus on the organizational capabilities as success factors and examine the relationships between the success factors and the performance of target costing. The main reason for focusing on the organizational capabilities is that target costing is not a collection of tools and techniques, but a dynamic system of connecting them. Organizational capabilities will also show many different aspects of various knowledge accumulated in the organization. Since the scope and depth of target costing in Japanese companies are substantially more intensive than U.S. counterparts, the results of this study will provide valuable insights on target costing to U.S. companies.

PREVIOUS RESEARCH

During the last decade, numerous studies have been conducted on the effectiveness of target costing systems in Japan as well as outside Japan (Kato et. al, 1995). Three different approaches have been generally employed in these studies: descriptive or narrative, analytical, and empirical. Most of the descriptive and empirical studies on target costing were not based on any conceptual foundation of target costing mainly due to the lack of research dealing with theoretical aspects of target costing. This section provides a brief review of existing literature in the three categories. The majority of the studies on target costing have used the descriptive approach which includes case studies. For example, Tani (1998) and Yoshikawa et al. (1990) explain different kinds of cost tables and their roles in a target costing system. Cost tables are widely known as a major database for target costing activities. Cooper and Slagmulder (1997) discuss VE (value engineering) as the most popular technique used in the target costing process. Another topic studied using the descriptive approach was the determination and allocation of target costs. Koga (1999) uses the concept of product life-cycle costs to demonstrate that actual costs always exceed the target in the target costing process. The studies by Cooper (1995) and Hiromoto (1988) are also representative on this topic. Some studies applied activity-based costing (ABC) to determine and allocate target costs. For example, Cokins (2002) shows that ABC can provide key cost data to assure the 'target' in target costing is attained. It is well known that target costing is inevitably linked to the development of a new product (1994; Cooper and Slagmulder, 1997; 1999a), and many descriptive studies have been conducted, focusing on this issue.

Like the analytical approach, the empirical approach has not been used much for target costing research. Tani (1994; 1995) and Tani and Kato (1994) argue that the effectiveness of a target costing system depends on the business environment and strategy which determine the organizational structure. Yoshida (2001; 2002) investigates the relationships between critical success factors and performance of target costing, using Japanese companies. He has found that the process and structure of the organization are more important than target costing support tools and that competitive environment is also a major factor affecting the organization's capability to implement target costing successfully.

In a milestone book published by Consortium for Advanced Manufacturing--International, Ansari and Bell (1997) provided intellectual and practical foundations of target costing. They view target costing as an open system that is responsive to customer needs and competitive threats and present six fundamental principles of target costing: price led costing, focus on customers, focus on design, cross-functional involvement, life cycle orientation, and value chain involvement. Ewert and Ernst (1999) present a theoretical analysis of target costing as one of the most prominent approaches of strategic management accounting. They analyze three distinct characteristics of this strategic management accounting tool, namely its market orientation, its use as a coordination instrument and its interaction with other factors affecting long-term cost structure in the form of strategic learning.

ORGANIZATIONAL CAPABILITIES

In the markets where the competitive landscape is shifting, the dynamic capabilities by which firm managers integrate, build, and reconfigure internal and external competencies to address rapidly changing environments become the sources of sustained competitive advantage (Teece et al., 1997). While there are many different types of dynamic capabilities, this study is based on the organizational capability model proposed by Kusunoki et al. (1995) due to the fact that their model provides new points of view which are not available in the traditional theories on organizations and corporate strategy. For example, it is well understood that target costing is not a mere combination of individual tools, such as cost tables, value engineering, etc., but is a dynamic system which integrates all these tools. Based on their model, the concept of organizational capability using the multi-level knowledge can be applied to identify the differences between a comprehensive target costing system and a simple combination of individual tools.

In a study on new product development of Japanese companies, Kusunoki et al. (1995) extend the concept of multilayered organization, which was originally proposed by Nonaka (1994), and classify the organizational knowledge into three overlapping layers: knowledge base, knowledge frame, and knowledge dynamics. First, the knowledge base is a layer of knowledge focusing on individual units of knowledge which is distinguishable based on a specific physical unit. Some examples are functional knowledge obtained by individuals with respect to product development, information processing system, database, and patents. This knowledge base provides an organization with local capabilities. Second, the knowledge frame includes knowledge about mutual relationships among or priority of individual knowledge that has a stable pattern or structure, and is a layer focusing on the organizational structure and strategy determining such a stable pattern. Examples include relationships between multi-functional development groups, power structure, and resource allocation to teams. Organizational capabilities coming from the knowledge frame are called architectural capabilities. Third, knowledge dynamics is another layer which focuses on the dynamic process of combining and changing individual knowledge through interactions among the knowledge. They include communication and coordination across the functions of product development and transfer of engineers who are equipped with specific knowledge. Since organizational capabilities provided by the knowledge dynamics are based on the process of knowledge interactions, they are called process capabilities.

Figure 1 presents the three layers of knowledge capabilities: local, architectural, and process. The organizational capabilities are represented by two dimensions on the horizontal axis: element and linkage. The element represents the capabilities that depend on individual knowledge, and the linkage represents the capabilities that depend on combining the knowledge. The vertical axis shows whether the capabilities can be designed and, therefore, manipulated by managers or embedded in the organization. For example, the process capabilities deal with the linkage of individual knowledge which is embedded in the organization, making them difficult to be designed by managers.

[FIGURE 1 OMITTED]

Local capabilities, such as engineers, databases, and patents, can be traded in the market, and managers generally understand each of the local capabilities and can see the results of their interactions. Hence, it can be commonly observed in many organizations to restructure these capabilities toward a more desirable direction. Process capabilities, on the other hand, are very difficult to design and manage by an organization and, therefore, it is almost impossible for managers to find cause-and-effect relationships among these capabilities. Thus, process capabilities are cumulative and path-dependent (Teece, 1988). In terms of their nature, the architectural capabilities are between the local and process capabilities. Compared to local capabilities, architectural capabilities are not clearly visible, but they are transferable to some extent from other successful organizations through imitation and learning because they can be partially manipulated by the design of strategy and organizational structure.

RESEARCH DESIGN

Research Model

Due to the fact that the concept of organizational capabilities has a great potential to contribute to target costing research, the interest in the concept has been increasing significantly during the last decade (Kato, 1993). It was expected that, based on empirical studies using the concept, theoretical and practical implications of target costing would be examined effectively. However, not many studies have been published yet on organizational capabilities, and empirical studies investigating the dynamic nature of these capabilities are almost nonexistent. As stated before, this study applies the concept of the organizational capabilities, as presented by Kusunoki et al. (1995), in testing the performance of target costing. The definitions of organizational capabilities, however, will be modified because of the following two reasons: 1) the concept of cost management is not clearly defined in their model and 2) it is necessary to include the success factors derived from the previous research on target costing. These new definitions will make the model more applicable to target costing research. Hence, for the purpose of this study, the research model is presented in Figure 2. First, there are three levels of organizational capabilities affecting the performance of target costing: local, architectural, and process. As the lowest level, the process capabilities consist of communication, experience and information sharing, and autonomy. The architectural capabilities at the next level are defined as top management support, organizational structure, and link to strategies. The local capabilities consist of database and product technology/knowledge base. It can be conjectured that these organizational capabilities are success factors which will affect the performance of target costing implementation and, consequently, profitability of the company.

[FIGURE 2 OMITTED]

Research Questions

There are two research questions to be investigated in this study. The first is the relationship between target costing performance and three different types of organizational capabilities as defined in Figure 2. This has been an important question among adopters of target costing in Japan to determine whether their infrastructure to implement target costing successfully is well laid out, but no research has been conducted on the significance of the relationship. The second question deals with specific capabilities and examines their relationships with different types of performance. This is an important question because target costing is multi-dimensional, and its performance should be measured from several different perspectives.

Definition of Dependent and Independent Variables

For the purpose of this study, the dependent variables are the performance results of target costing implementation, and the independent variables are local capabilities, architectural capabilities, and process capabilities. Specific definitions and measurement issues are discussed below.

Performance results

In measuring the performance of target costing, twelve variables have been identified based on a comprehensive review of the empirical studies on target costing (Yoshida, 2001; Kubota, 2002; and Yook, 2003, in particular) and then classified into three categories: development and design efficiency, marketability, and cost reduction. First, development and design efficiency is a performance variable concerning the efficient management of R&D and design steps, such as design to cost, improving development/design process, and cost reduction efforts by engineers. Improvement in quality and delivery deals with marketability of new products through improvement in quality and functions, shortening lead-time for new product development, and timely introduction of new products. Finally, cost reduction is a measure for financial achievement through effective product cost management and supply chain management. These three are dependent variables which are used to measure short-term effects of product development, such as increases in sales and profitability.

Local capabilities

Two specific factors are selected to represent the local capabilities of the sample firms in this study: database and product technology/knowledge. These factors show how much personnel, financial, and technological resources are available to implement target costing, compared to those of other competitors, and they are quantitative measures demonstrating the abundance of individual knowledge. Database includes information about VE (value engineering), VRP (variety reduction program which is the standardization of parts and reduction of the number of parts), QFD (quality function deployment) and cost table. Product technology/knowledge includes new technology and materials developed through R&D, manufacturing and quality control process, and employees' knowledge about cost.

Architectural capabilities

Architectural capabilities in target costing consist of three basic elements: the link to strategy, commitment of top management, and organizational structure. These are a collection of lower-level elements associated with strategy or organizational structure that provides a stable pattern of local capabilities in an organization. They also reflect the frame of knowledge that the employees possess.

Process capabilities

To measure process capabilities, three factors have been used in this study: cross-department communication, autonomy, and transfer of experience. These factors represent the dynamic interaction of knowledge within the organization. Cross-department communication demonstrates the frequency of knowledge exchange, and shows how much information exchange and activity coordination take place among the functional departments participating in target costing and product development, such as R&D, production and marketing (Allen, 1977). On the other hand, autonomy focuses on empowering employees, performance evaluation, and tradeoff between organizational integration and coordination. It is a factor that can be used to measure how much empowering and delegation of authority contribute to the performance of employees. Experience transfer refers to knowledge exchange generated by the transfer of experience obtained by employees through their activities in the organization (Kusunoki and Numagami, 1995).

Sample Firms and the Questionnaire

In finding the sample companies, the records of the 1,500 companies listed in the First Section of the Tokyo Stock Exchange were reviewed to check the companies having a target costing department or any department with a similar function, such as cost planning or cost engineering. The First Section lists the companies with Japan SIC codes 6 through 32, representing a wide range of industries from automobile to construction. For the companies that were not clear about the use of target costing based on their organizational structure, phone calls were made to confirm the implementation of target costing. Several companies were actually visited, as needed, for further clarification. In the process, 880 companies were identified as the final sample.

A questionnaire was developed and initially tested by five managers and three academic experts from the fields of cost management and industrial engineering. They were instructed to designate each question as 'Keep,' 'Modify,' or 'Drop' and to comment on the appropriateness of the research constructs. The instruments were revised to reflect feedback from the participants. The final questionnaire consisted of three parts: 18 questions for organizational capabilities as success factors; 14 questions for performance; nine questions for implementation scope and others. Except for demography items, five point Likert scales were used to measure target costing system practices. Respondents were asked to indicate the strength of their agreement with each question. The possible responses included 1, corresponding to none; 5, corresponding to extensive; and NA, not applicable.

The questionnaire was sent to target costing senior managers of all 880 companies. An introductory cover letter, the survey questionnaire, and postage-paid return envelope were mailed to these potential respondents. After the second mailing with a one-month interval, 162 responses were received with a response rate of 18.4 percent. Phone calls and actual visits helped significantly boost the response rate.

RESULTS OF SURVEY RESPONSES

In this section, the characteristics of the sample firms were first examined. The reliability and appropriateness of the questions were then examined using a factor analysis. Finally, multiple regression analyses were conducted to identify the degree of impact of each success factor on target costing performance.

Sample Characteristics

The sample companies are diversified based on the following statistics: 4.4 percent from steel and metal; 12.7 percent from machine; 16.5 percent from electric and electronics; 31.7 percent from automobile and airplane; 5.7 percent from precision machine; 23.4 percent from construction; 5.6 from other industries. Considering the different industry backgrounds among the sample companies, the performance of target costing can be affected by various factors that are not directly related to the effectiveness of the target costing system in place. In particular, it can be presumed that large companies have more financial and personnel resources than small companies so that the performance result can be biased toward large companies. As an attempt to control the size effect, total revenue was used as a control variable. It has turned out that seventy percent of the companies are large companies, having sales revenue over $3 billion and employees over 5,000.

The average time period of using target costing is about 17 years, which is much longer than the period of the U.S. sample counterparts. In a survey that was conducted in the U.S., 25 percent of 48 companies used target costing for over five years and 50 percent were in the range of 1-3 years (Ansari et al., 1999). The depth of target costing implementation is also very extensive for Japanese companies (70.3 percent for company-wide implementation), compared to that of U.S. companies (only 19 percent for company-wide implementation; Ansari et al., 1999). Seventy-four percent of the sample companies in this study have an official department to support target costing functions, and 65.8 percent have it at the headquarters and 34.2 percent in the factory. (Twenty-four percent have the target costing department at both headquarters and factory.) The average number of employees working full-time for target costing is 23.

Statistical Characteristics of the Dependent and Independent Variables

Correlations among the variables used in this study are presented in Table 1. As expected, all three explanatory variables show a positive relationship with most of the performance results, but the relationship between dysfunction and three organizational capabilities is not statistically significant. Multicollinearity does not exist among the independent variables. The result of the Durbin-Watson test shows that there is no autocorrelation.

The results of descriptive statistics and factor analyses for independent variables (16 success factors) and dependent variables (12 performance result items) are presented in Tables 2 and 3, respectively. Table 2 shows that the most important success factor among the16 variables is top management support (4.57), followed by tools and information system (4.25), cost estimation (4.22), and information sharing (4.19). Less important factors for Japanese companies are cross-functional transfer of employees (3.32), cooperation with other departments (3.50) and empowerment (3.68). Table 3 shows that, among the three major categories of dependent variables, target costing is most effective for cost reduction (with an average score of 3.81), followed by efficiency (3.68) and marketability (3.22). Individually, production cost reduction (4.02) and cost reduction of raw materials (4.01) both improved most significantly, and timely introduction of new product (3.01) and reducing new product development time (3.05) are the least improved areas by implementing target costing.

In order to test the relationships between three major success factors and target costing implementation results, a set of new measurement items for each success factor was developed based on previous research. Hence, factor analyses based on Varimax were conducted to test the conceptual validity and reliability of newly developed success factors and measurement variables. Using the Eigen value of 1.0 as the base, the result of a factor analysis classified 16 success factors into three major capabilities (i.e., local, architectural, and process), and the explanatory power for each success factor, as measured with factor loading scores, was about 70 percent as an average as presented in the last column of Table 2. Hence, it can be concluded that the classification was properly done. A similar result was obtained for the performance measures (Table 3). Loading scores of all 12 measures were about 70 percent or above each for most factors. In addition, to check the reliability of the questionnaire of this study, Cronbach's a was used. As presented in Tables 2 and 3, Cronbach's a's of all three success categories and all three measurement categories were about 70 percent or above. In general, when they are greater than 60 percent, they are regarded as being reliable.

Results of Regression Analyses

Five independent variables (i.e., type of business, firm size, local capabilities, architectural capabilities, and process capabilities) were regressed on the three dependent variables (i.e., efficiency, marketability, and cost reduction), and the results are presented in Table 4. First, marketability (quality and lead time) depends significantly on the architectural and process capabilities of the organization (significant at the five percent and one percent levels, respectively), while local capabilities do not have much impact on marketability. This implies that the stronger the organization's dynamic power becomes, the efforts for improvement of marketability can be more effective. It should be noted that the process capabilities which consist of coordination with other departments, experience and information sharing, and empowerment are the most important variables in improving marketability. One important implication is that simply having abundant knowledge base within the organization is not enough for improving marketability. Rather, dynamic interaction among the individual knowledge is the key for success. In terms of the relationship between the organizational capabilities and efficiency of new product development and design, the architectural capabilities are the most important variable in improving efficiency (significant at the one percent level), followed by the process capabilities (significant at the five percent level). Like the marketability variable, the local capabilities have turned out to be insignificant. In the case of cost reduction which focuses on the financial aspect of target costing, both architectural and local capabilities are equally important (significant at the one percent level) while the process capabilities are insignificant. It should be noted that the local capabilities have a significant effect on cost reduction. This result implies that database and knowledge base are critical factors in controlling costs in the target costing process.

Based on these results of the regression analyses, it is clear that the architectural capabilities, such as top management support, linkage to profit planning, and a cross-functional team, are the most important variables for successful implementation of target costing. They have a positive relationship with all three major dependent variables: efficiency, marketability, and cost reduction. The next important factor for the success of target costing is the process capabilities, which affect two major dependent variables: improving marketability and efficiency of designing and product development. The impact of the local capabilities is relatively weak on the performance of target costing. This is particularly true for efficiency and marketability for new product development. This finding is consistent with the Kato study (1993), which states that, as target costing support systems (such as cost tables) are becoming well established, employees tend to rely on them more heavily and consequently deplete the ideas for new product development and design. In sum, it appears that the dynamic capabilities focusing on interactions of individual knowledge are more important on the performance of target costing than the local capabilities that consist of observable individual knowledge.

Increase in sales and contribution margin is also an expected economic return in the new product development. In fact, increase in sales/contribution margin and new product developments have a very high correlation with the sample of this study (factor loading=0.83; Eigen value=1.75). Hence, the economic return was regressed on three independent variables (cost reduction, efficiency of product development, and improvement on marketability) to obtain the following result: adjusted R-squared=0.33; F-statistics=26.02; p-value<0.001. Efficiency and marketability were significant at the 1 percent level, and cost reduction was significant at the 10 percent level. It is apparent that all three variables are important determinants of the short-term economic return of the sample companies. It was also tested if the three types of organizational capabilities could result in dysfunction by employees in implementing target costing, such as burnout of design engineers, increasing conflicts of interest, supplier fatigue, and over-engineering of the product (product diversification, proliferation of options, etc). Empowerment is generally considered instrumental for knowledge creation (Nonaka and Takeuchi, 1995). However, it may result in tiredness of design engineers which is one of the negative aspects of target costing, and this will consequently lead to burnout (Kato, 1993; Cherniss, 1980). It has turned out that no significant correlation exists between the capabilities and dysfunction.

CONCLUSION

Many case studies have been reported in the accounting literature to demonstrate successful implementation of target costing. However, there has been a lack of research from the standpoint of the companies introducing target costing to investigate critical success factors and evaluate the performance of target costing. Therefore, the main purposes of this study were to present a basic framework for understanding the success factors (i.e., organizational capabilities) of target costing based on multiple layers of distinctive individual knowledge and to examine the relationships between the organizational capabilities and performance of target costing for Japanese companies using a questionnaire. It has been shown that the dynamic capabilities are the critical factor for the successful implementation of target costing and that they are closely tied to the competitive advantage of Japanese companies in the global market. More detailed regression analyses show the following three points:

1. the architectural capabilities are significantly related to the all of the performance variables.

2. the process capabilities have a significant impact on the efficiency of design and development and improvement of quality and on-time delivery, but their impact on cost reduction is limited.

3. the local capabilities are significantly related only to cost reduction and show an insignificant relationship with other performance factors.

It can be concluded that the local capabilities are necessary, but not sufficient for the success of target costing and that the dynamic capabilities, such as architectural and process capabilities, are more important in implementing target costing. Traditionally, it has been emphasized that having the right tools and techniques is critical to the success of target costing (Ansari and Bell, 1997, p. 138). This study shows that the software of target costing, such as dynamic capabilities, is more important than the hardware of target costing, such as tools and techniques.

A couple of methodological problems limit the interpretation of the results of this study. First, even though an attempt was made to control the size and type of industries, the industry differences were not investigated due to a lack of information. Second, the sample size was too small, relative to the number of independent variables. It is recommended in future studies to use a control group which consists of companies without a target costing program to see if there would be any differences in results between the sample and the control group. It would be also interesting to do a trend analysis of the same companies to see how the maturity of target costing affects the results of target costing implementation.

REFERENCES

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Sungkyoo Huh, California State University-San Bernardino

Keun-Hyo Yook, Pusan University of Foreign Studies

Il-woon Kim, University of Akron

Table 1: Correlations Matrix among the Variables

 Efficiency Marketability Cost
Efficiency 1 Savings
Marketability 0.318 (c) 0
Cost savings 0.429 (c) 0.344 (c) 1
Local 0.199 (b) 0.147 0.404 (c)
Architectural 0.372 (c) 0.281 (c) 0.407 (c)
Process 0.268 (c) 0.365 (c) 0.306 (c)
Dysfunction 0.225 (c) -0.087 0.171 (b)
Profitability 0.523 (c) 0.400 (c) 0.377 (c) 0.185 (b)

 Local Architectural Process Dysfunction
Efficiency
Marketability
Cost savings
Local 1
Architectural 0.527 (c) 1
Process 0.470 (c) 0.448 (c) 1
Dysfunction 0.051 0.023 0.009 1
Profitability 0.313 (c) 0.203 (b) 0.66

Note: (a) = significant at P-value < 0.1

(b) = significant at P-value < 0.05

(c) = significant at P-value < 0.01

Table 2: Descriptive Statistics and Factor Analysis: Independent
Variables

Critical Success Factors Mean Standard Factor
 Deviation Loadings

Local capabilities (Cronbach's a = 0.7553
(X1) Tools and information 4.25 0.67 0.61
 system
(X2) Knowledge about cost 4.04 0.81 0.603
(X3) New technology/materials 3.83 0.77 0.646
 from R&D
(X4) Technology in 3.92 0.70 0.629
 production/quality
(X5) Cost estimation capability 4.22 0.59 0.614
(X6) functional knowledge 4.11 0.63 0.498
 of team members
Average 4.06

Architectural capabilities (Cronbach's a = 0.6954)
(X7) Top management support 4.57 0.67 0.582
(X8) Empowered project manager 3.87 0.90 0.541
(X9) Concurrent engineering 3.46 0.90 0.666
(X10) cross-functional 3.71 0.83 0.674
 team (org. structure)
(X11) linkage to profit 4.16 0.71 0.628
 planning
Average 3.95

Process capabilities (Cronbach's a = 0.7071)
(X12) Cooperation with 3.50 0.76 0.533
 other departments
(X13) Information sharing 4.19 0.66 0.588
(X14) Cross-functional 3.32 0.78 0.478
 transfer of employees
(X15) Autonomy of employees 4.03 0.78 0.751
(X16) Delegation of 3.68 0.64 0.755
 power/responsibility
Average 3.73

Note: The means are calculated based on the 5-point scale:

(1) = none;

(2) = slight;

(3) = moderate;

(4) = substantial;

(5) = extensive.

Table 3: Descriptive Statistics and Factor Analysis: Dependent
Variables

Performance Result Items Mean Standard Factor
 Deviation Loading

Efficiency (Cronbach's a = 0.7823)
(Y1) Design-to-cost 3.79 0.80 0.678
(Y2) Strengthening design/ 3.42 0.81 0.805
 development process
(Y3) Cost reduction efforts 3.97 0.68 0.627
 by engineers
(Y4) Improving design/ 3.54 0.75 0.761
 development technology
Average 3.68

Marketability (Cronbach's a = 0.7272)
(Y5) Quality improvement 3.47 0.69 0.697
(Y6) Reducing development 3.05 0.76 0.731
 lead time
(Y7) Product features based 3.35 0.72 0.664
 on customer needs
(Y8) Timely introduction 3.01 0.69 0.763
 of new product
Average 3.22

Cost reduction (Cronbach's a = 0.7225)
(Y9) Product cost reduction 4.02 0.69 0.604
(Y10) Upstream cost reduction 3.41 0.71 0.607
(Y11) Reduction of raw 4.01 0.67 0.499
 materials purchased
(Y12) Waste reduction on 3.8 0.66 0.84
 the factory floor
Average 3.81

Note: The means are calculated based on the 5-point scale:

(1) = none;

(2) = slight;

(3) = moderate;

(4) = substantial;

(5) = extensive

Table 4: Results of Regression Analysis

Independent Variables Dependent Variables

 Efficiency Marketability
Business type 0.271 (3.633) (c) 0.033 (0.431)
Firm size 0.011 (0.151) 0.030 (0.381)
Local -0.053 (-0.586) -0.113 (-1.223)
Architectural 0.328 (3.632) (c) 0.199 (2.141) (b)
Process 0.160 (1.831) (a) 0.323 (3.595) (c)
F-statistics 8.635 5.780
R-squared 0.229 0.163
Durbin-Watson 1.741 1.921

Independent Variables Dependent Variables

 Cost reduction
Business type -0.053 (-0.726)
Firm size 0.160 (2.167) (b)
Local 0.233 (2.656) (c)
Architectural 0.250 (2.839) (c)
Process 0.049 (0.573)
F-statistics 10.181
R-squared 0.257
Durbin-Watson 2.188

Note: (a) = significant at P-value < 0.1

(b) = significant at P-value < 0.05

(c) = significant at P-value < 0.01