Materials Science Forum Vols. 505-507 (2006) pp 883-888 online at http://www.scientific.net © (2006) Trans Tech Publications, Switzerland Online available since 2006/Jan/15
Development of Manufacturing Strategy- Influence of Technology orientation and Customer orientation: An Empirical Study Approach Ming-Lang Tseng 1,a, Jiu-Hsiang Chiang 2,b, Anthony SF Chiu3, c 1
#51 University Road, 613 Chiayi County, Toko University, Taiwan
2
#51 University Road, 613 Chiayi County, Toko University, Taiwan 3
#2504 Taft Avenue, Manila, De La Salle University, Philippines
a
[email protected] ,
[email protected],
[email protected]
Keywords: manufacturing strategy, manufacturing flexibility, advanced manufacturing technology, customer satisfaction and customer focus
Abstract. Using survey data, this research identified the relationship between technology orientation (manufacturing flexibility and advance manufacturing technology), and customer orientation (customer focus and customer satisfaction) to development of manufacturing strategy. This framework is then tested on a sample of 52 firms in plastics injection industry, Taipei County, Taiwan. The results show significant relationships in the framework with four models. They support the argument found in the literatures that manufacturing strategy builds should related to technological development and market place. Implications of the findings are discussed. Introduction The firms that operate in developing, and industrialized countries, face many uncertainties when venturing into the modern global business environment, they should be able to survive and adjust to this continuously changing realm. More importantly, can they meet the challenge of strategically implementing, advanced manufacturing technology (AMT) in an flexible environment where the ability to adopt has become the manufacturing flexibility and therefore integrated into development manufacturing strategy (MS) and the information from the needs of customers. Today, throughout the 20th century, management has embraced the mass production philosophy, and the factories have realized unprecedented gains in efficiency and productivity. Mass production insulates the factory from variability in customer demand, but it does so by categorizing customers and products and trivializing customer interaction [1]. Firms must now maintain a manufacturing strategy of customer focus and concentrate on those factors with provided value to customers included not only low cost, but also high quality, flexibility of product characteristics and dependability of supply [2], which is referred to the manufacturing competitive priorities of Hayes and wheelwright manufacturing strategy framework [3]. In order to clarify the manufacturing strategy, Swamidass [4] defined as the development and deployment of manufacturing capabilities in total alignment with the firm’s goals and strategies. Currently, the manufacturing strengths and weaknesses are critical factors in the determination of the most effective bases on which a company should attempt to compete in the marketplace or external information [5]. However, from a management perspective,
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the manufacturing strategy still has attaining a high degree of manufacturing flexibility implies the commitment of a substantial amount of the organization’s resources such as AMT selection or implementation. Therefore, decisions made to adopt new manufacturing technologies and management practices are like to be associated with MS assessment. Williams [6] resulted on the manufacturing emphasis on technology orientation and market orientation provide consistent finding, both are the most significant variables dealt with an aspect of quality or manufacturing function. The fundamental design principles pursued throughout the research used a customerfocus approach. Similar to developing a market-oriented product to reflect customer needs in R & D, the manufacturing strategy workshop took shape by working closely with customers to explore and exploit their need/satisfaction, also contribute to the quality of the workshop as well as their commitment to the MS development process [7]. The main objective of this research is to determine what extend the impact of customer orientation and technology orientation to MS development. Figure 1. Presents the proposed theoretical model and associated hypotheses. The framework proposes that technology orientation (Manufacturing flexibility and AMT) and customer orientation (Customer Focus and Customer satisfaction) impact on MS.
Hypothesis 1. Technology orientation is not related to MS development H1.1. Technology orientation is not related to Role of MS interact with external environment H1.2. Technology orientation is not related to Role of MS with worker participation Hypothesis 2. Customer orientation is not related to MS development H2.1. Customer orientation is not related to Role of MS interact with external environment H2.2. Customer orientation is not related to Role of MS with worker participation Research Methodology Data collection. The data for the empirical investigation of the model were obtained through a field study. Data were collected from participating firms predominantly via face-to-face interviews with vice president and executives/managers in charge of the manufacturing function from 52 selected plastics injection firms in Industrial Parks in Taipei county, Taiwan. Measurement instrument. Prior to data collection, the survey instrument was pre-tested for content validity in two stages. In the first stage, six experienced researchers were asked to critique the questionnaire for the ambiguity, clarity and appropriateness of the items used to operationalized each construct, based on feedback received from these researchers, the instrument was modified to enhance clarity and appropriateness of the measures purporting to tap the constructs. In the second stage, the survey instrument was mailed to five management executives affiliated with the Philippines institute of industrial engineering (PIIE). These executives were asked to review the questionnaire for structure, readability, ambiguity and completeness. This process yielded a survey instrument that was judged to exhibit high content validity. The dependent /independent variables
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were derived from various previously studies following the AMT [8], the Manufacturing flexibility [9], the Customer focus [10], the Customer satisfactions [11] and the MS development [9]. Statistical procedure used. In order to test the hypotheses, the research objective in this study are to investigate the relationships between dependent and independent variables. From a methodological perspective, this research therefore needs to choose an appropriate dependency model (e.g., correlation analysis, multiple regression). As noted above, the data set did not contain any categorical variables. Hence, if the data set does not show signs of multicollinearity, regression analysis would be the method of choice; the correlation matrix of the research variables was examined for the signs of multicollinearity. Although some significant correlations existed, none were large enough to pose serious multicollinearity problems. In addition, the variance inflation factor (VIF) measured using the collinearity diagnostic available in SPSS 10.0, was tightly distributed between 1.00 and 2.18. Hair et al [12] suggests that multicollinearity is indicated when the vale of VIF exceeds 10. This suggests that the data are not ill-condition, and permits the use of regression in this study. Factor analysis was considered as a data reduction step prior to regression analysis. As a rule of thumb, factor analysis is best suited when ratio of respondents to variables is high (10:1). Low ratios could result in sample-specific results. This research had five variables and the sample size was 52. Because of the nature of this research, its objectives would be best served by using regression analysis. Mathematical modeling. Regression model was constructed; one to test each hypothesis. Because of the ambiguity in literature on the relationship between the dependent and the independent variables, the mathematical models have been presented in the more generalized form, rather than a form that indicated the presumed sign of individual coefficients. The four models and the results of the statistical analysis are presented in Table 1 and are discussed below. Table 1. Multiple regression analysis results and collinearity test Model 1. Role of MS interact with external environment = f (technology orientation); (H1.1) Adjusted R square = .401; F = 35.131; Durbin-Watson = 2.084; VIF= 1.0; Sig.=0.000 Variables
β
T-stat.
Sig.
Products design flexibility Production function Flexibility
.642 -.166
5.927 -1.554
0.000* .127
Fabrication & assembly technology Machine automation & engineering design technology Inspection & communication technology
.148 -.042 .011
1.362 -.382 .092
.179 .704 .927
Model 2. Role of MS interact with external environment = f (customer orientation); (H2.1) Adjusted R square = .079; F = 5.4; Durbin-Watson = 2.658; VIF= 1.0; Sig.=0.024 Variables
β
T-stat.
Sig.
Product design to meet customer needs & expectation
-.312
-2.324
0.024*
Understand the future needs of customer
.129
.854
.397
Measurement of customer satisfaction in the period Customer perception on product quality
-.19 0.024
-1.401 .175
.167 .862
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Model 3. Role of MS with worker participation = f (technology orientation); (H1.2) Adjusted R square = .548; F = 31.944; Durbin-Watson = 2.024; VIF= 1.105; Sig.=0.00 Variables
β
T-stat.
Sig.
Products design flexibility Production function Flexibility
.148 -.541
1.436 -5.059
.157 0.00*
Fabrication & assembly technology Machine automation & engineering design technology
.037 .077
.383 .778
.704 .440
Inspection & communication technology
.326
3.046
0.004*
Model 4. Role of MS with worker participation = f (customer orientation). (H2.2) Adjusted R square = .26; F = 18.964; Durbin-Watson = 2.441; VIF= 1.0; Sig.=0.000 Variables
β
T-stat.
Sig.
Product design to meet customer needs & expectation Understand the future needs of customer
.135 -.156
1.105 -1.302
.275 .199
Measurement of customer satisfaction in the period Customer perception on product quality
.524 .012
4.355 .096
.000* .924
Test of Hypotheses. Model 1. Hypothesis H1 relates to the framework of technology orientation to the role of MS interact with external environment in Fig. 1. The F-statistic for the overall model (table 1) was significant (p = .000) and H1.1 was rejected and H1.2 was accepted. In other words, at least one predictor variable contributes information for the prediction of the dependent variable. To explore this further, this research tested for significance of individual regression coefficient estimates. As noted in Table 1, only one coefficient was significant. Specially, the products design flexibility variable (t = 5.927, p = .000) was significantly and positively correlated with the role of MS interact with external environment. Model 2. Hypothesis H2 predicts no relationship between customer orientations and MS development. The regression (table 1) finds the F-statistic was significant (p = 0.024), therefore reject the null and conclude that at least one regression coefficient estimates were evaluated. only one coefficient was significant. Specially, the product design to meet customer needs & expectation (t = -2.324, p = 0.024) was significantly and negatively correlated with the role of MS interact with external environment. Model 3 predicts no correlated between the Role of MS with worker participation and technology orientation. The regression finds the F statistic was significant (p =. 000). Thus H1.1 and H1.2 both are rejected. Products design flexibility was significantly and inversely correlated to the Role of MS with worker participation (t = -5.059, p = .000), whereas the inspection & communication technology (t = 3.046, p=0.004) was significantly correlated with the Role of MS with worker participation. Model 4 predicts no correlated between the Role of MS with worker participation and customer orientation. The overall regression finds the F statistic was significant (F = 18.964, p =. 000). Thus H2.1 accepted and H2.2 rejected. Measurement of customer satisfaction in the period was significantly correlated to the Role of MS with worker participation (t = 4.355, p = .000). Findings and Discussions The tests on hypotheses H1 and H2 support existing theory [5, 13] on the relationship between
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manufacturing strategy, advance manufacturing strategy, customer focus and customer satisfaction. Based on the finding relationships on Table 1, the manufacturers are preferred to have mass production rather than the product design to meet customer expectation. Because emphasis on innovative manufacturing processes, product quality and variety of product offerings might through a decrease in the level of capacity slack maintained [6]. Findings. Our finding suggest that in the plastics injection firms, business units that chose higher level of products design flexibility reflected this emphasis in their manufacturing strategy through increased emphasis on interact with environment and worker suggestion on manufacturing policies and through a decrease in the level of product design to meet customer expectation. The reader should note that this pattern may not be generalized to all industries. Clearly, each industry’s unique characteristics influences the way the technology and customer orientation can support the manufacturing strategy be formulized. However, our finding suggest that within an industry, business units tend to follow a pattern as they configure their need in technology and market orientation to best support the development of MS. Taken together, our finding on manufacturing emphasis on technology orientation and customer orientation provide consistent findings. In both orientations, the most significant variables dealt with an aspect of the role of manufacturing strategy in business organization (i.e. interact with external environment and worker participation on manufacturing policies). Steps taken by the position of manufacturing strategy being formulated function is to enhance the competitive position in these areas would result in improved manufacturing performance of business units. Limitations of the study. It is the relatively weak relationships that were observed (as indicated by somewhat low model R2). This is probably because development of MS is a result of a concerned effort of all the manufacturing functional areas within an organization, of which technology and market orientation is just two. It is expected that viewing the affect of multi-functional activities on manufacturing decisions [14] would provide improved results. For example, the included long-term capacity strategy, facilities strategy, vertical integration, managing changes [3], and indicate that the need to include other manufacturing functional areas of business units Conclusion. In this paper, the researchers have attempted to extend the existing theory base in the manufacturing strategy development by investigating the relationship with technology orientation and customer orientation. Past research on business MS is synthesized and parsimonious framework is developed to examine the relationship between technology orientation, customer orientation and MS development. Because of the exploratory nature of this study, the researchers have consciously limited the scope of the theory testing process to a single industry. This approach essentially controlled for industry specific factors. However, the framework be easily modified to handle industry specific contingencies. For example, it would not be difficult to incorporate and test for moderating and intervening industry characteristics in the framework. This provides another avenue for fruitful research aimed at developing a model that is generalizable across industry. Despite its limited focus, we believe that the findings of this study maybe applicable to other industries that have similar structures to this industry. The further research may need to be done to confirm whether the model developed in this paper could be applicable these industries. This paper
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contributes to the existing body of knowledge on MS that is presented the relationship between technology orientation customer orientation and MS development in a single framework. The attractiveness of the model lies in its simplicity. The parsimonious representation of the MS development on two dimensions provides researchers and practitioners with an uncomplicated model for reviewing the associated relationships. The useful of the framework developed in this research paper lies in its potential applicability to many industries. Future research effort should build on the existing knowledge base and focus on the development of contingency frameworks that could explain and predict recurring phenomena related to the MS developing. The framework presented in this paper is a step in the direction. Researchers may want to test the framework in other industries. References [1] Lampal, J. and Mintzberg H., Customizing customization: Sloan management review, Vol. 38, (1996), pp21-30 [2] Harrison S.P.G.., and Poole M., Customer-focused manufacturing strategy and the use of operations-based non-financial performance measures: a research note : Accounting, organizations and society, Vol. 22, no.6, (1997), pp557-572 [3] Hayes, Robert H. and Wheelwright, Steven C. Restoring our competitive edge: competing through manufacturing. (John Wiley & Sons Inc, 1984) [4] Swamidass, P.M. & Newell, W.T.. Manufacturing strategy, environmental uncertainty and performance: A path analytic model : Management Science, Vol. 33(4), 1987, pp. 509-524. [5] Hill Terry. Manufacturing Strategy test and cases. (Irwin McGraw-Hill, 3rd Edition 2000) [6] Williams F.P.; D’Souza D.E.; Rosenfeldt M.E.; Kassaee, M., Manufacturing strategy, business strategy and firm performance in mature industry: Journal of operations management, Vol. 13, (1995), pp19-33 [7] Hwang, Ahn-Sook. Designing a customer-focused workshop for strategic planning: Journal of management development, Vol. 17(5), (1998), pp.338-350 [8] Baldwin J., and Lin Z.,. Impediments to advanced technology adoption for Canadian manufacturers. Research policy, Vol. 31, (2002) [9] Ho, Chin-Fu, A contingency theoretical model of manufacturing strategy: International journal of operations and production management, Vol. 16( 5), (1996), pp. 74-98 [10] Lee, R. G., & Dale, B. G., Business process management: a review and evaluation: Business Process Management Journal, Vol. 4(3), (1998), pp 214-225. [11] Ugboro, IO., and Obeng, K.. Top management leadership, employee empowerment, job satisfaction and customer satisfaction in TQM organizations: an empirical study: Journal of quality management, Vol. 5, (2000), pp.247-272 [12] Hair et al. Multivariate data analysis. (Prentice hall 5th edition, 1999) [13] Standard, C. and Davis, D. Running Today’s factory- a proven strategy for lean manufacturing. (Hanser Gardner Publications. p.100 and pp. 238-239, 1999) [14] Hays, R.H.; Wheelwright, S.C; Clark, K.B., Dynamic manufacturing- creating the learning organization.( The Free Press- a Division of Macmillan, Inc, 1988)
