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Weekly UpdatesHypothesis 4: There is a direct positive relationship between the level of strategic consensus (SC) and the degree of trod itionally-correct product-Process alignment (PPA).
Hypothesis 5: There is a direct positive relationship between the degree of traditionally- correct product-process alignment (PPA) and manufacturing performance (MP).
Advanced Systems and New Technologies
A number of advanced systems and new technologies have been developed to improve manufacturing performance and competitive effectiveness. Computer-based and manual systems offer the promise of changing the ways business units compete and of helping business units to be more competitive in world markets (Voss, 1986). The potential benefits of advanced systems and other new technologies have received attention in the recent strategy and manufacturing literature. Sanchez (1995) proposes that two sets of related innovations, one technological and one managerial, are jointly creating and escalating the process of change that is diffusing and transforming competition. Kotha (1995) suggests that mass production and mass customization might be pursued simultaneously. Bettis and Hitt (1995) believe that in an era of rapid technological change and corresponding forecasting difficulties, sustainable advantages are likely to come from internal organizational competencies. Static models that dictate either/or choices hav e come into question. For example, Sanchez (1995) points out that firms trying to compete by adhering to traditional strategies of low cost, differentiation, or focus, may find themselves challenged by firms with superior flexibilities in terms of quicker response times, more new products, broader product lines, and rapid product upgrades.
As suggested by Jelinek and Goldhar (1984), Wharton (1987), and Meredith (1987), the use of new manufacturing technologies and advanced systems might enable manufacturing firms to operate outside of the product-process matrix prescriptions and still attain superior performance. New technologies and processes could distort the traditional trade-off between process flexibility and lower unit cost by providing additional operational benefits, such as increased flexibility, improved product quality, and lower unit costs. To test the influence of these new technologies and systems on traditional product-process alignment, the following hypotheses are proposed:
Hypothesis 6: There is an inverse (negative) relationship between advanced systems use (ASU) and the degree of traditionally-correct product-process alignment (PPA).
Hypothesis 7: There is a direct positive relationship between advanced systems use (ASU) and manufacturing performance (MP).
These seven hypotheses provided the basis for the development of the initial conceptual model presented in Figure I. The next section of this article discusses our research methodology and statistical analysis, followed by sections on results, discussion, and conclusions.
METHODOLOGY
Sample
Sample characteristics are presented in Table 1. The sample included 27 strategic business units (SBU) selected from three major multinational, U.S.-based electronics manufacturers. The electronics industry produces a variety of products in various stages of the life cycle for a diverse set of product markets, thus this industry was chosen to represent a suitable cross-section of strategies. A strategic business unit was defined as a product group, major product line, and/or group of smaller similar products that shared a common planning process, marketing strategy, product life cycle stage, production process, and production volume level. Questionnaires were used to survey individuals within each SBU and included responses from: (1) strategic planners, such as general managers, business planners, and marketing managers, and (2) operations managers, such as manufacturing managers, production control managers, and quality assurance managers. The sample included a total of 162 respondents. The products manufac tured by the strategic business units include electronic products such as pagers, computer interface modules, and electronic automotive components.
Measurement Scales
Strategic Consensus (SC). The level of strategic consensus (SC) among SBU managers was measured using an augmented version of the Dess and Davis (1984) scale of strategic or competitive methods. The competitive method instrument consists of both marketing-related and operations-related competitive dimensions, thus the instrument provided the necessary bridge for measuring the degree of strategic consensus among SBU-level strategic planners and operations managers. Dess and Davis (1984) factor analyzed this scale to demonstrate its congruence with, and use as a measure of, Porter's (1980, 1985) generic strategies (low cost, product differentiation, focus). Furthermore, Dess (1987) successfully employed the instrument to determine the degree of consensus among top management regarding the relative importance of different aspects related to the firm's actual strategic emphasis. Factor analysis of the augmented SC scale produced the three factors representing Porter's (1980, 1985) generic strategies, thus the re sults were consistent with expectations for content criteria. Additionally, the assessed reliability of the measurement scale was high, with Cronbach's Alpha equal to .86.
Measurement of strategic consensus involved all six product group strategic and operations managers within each SBU (162 respondents). These managers were asked to indicate how important each of the 25 competitive methods was to their business unit's (product group's) overall competitive strategy. Responses were measured using a 5-point Likert scale. Following Dess (1987), the standard deviation of the team member responses for each item was computed. The sum of the item standard deviations then produced a total strategic consensus score (SC) for the manufacturing business unit.
Manufacturing Task Consensus (MTC). In addition to strategic consensus (SC) a second consensus measure, manufacturing task consensus (MTC), was employed. A 12-item manufacturing-specific task consensus measurement scale was developed to correspond to the four manufacturing strategic dimensions (low cost, flexibility, quality, and dependability) defined by Wheelwright (1978). Factor analysis of the MTC scale produced the expected four factors, consistent with expectations for content criteria. Cronbach's Alpha equaled .76.
The same 162 respondents who completed the strategic consensus scale were asked to indicate how important each of the 12 manufacturing task items was to the overall competitive strategy chosen by the business unit's general manager. Responses were measured on a 5-point Likert scale. Quantification of the MTC consensus score was then accomplished in the same manner as the strategic consensus measure (summing the standard deviations of scale item responses of the product group team members).
Flexible Manufacturing Systems/Robotics (FMS/RB). The use of flexible automation was determined as follows. The manufacturing manager and the production control manager within each business unit were asked to supply a specific designation as to the extent to which flexible manufacturing systems and robotics were employed in the manufacture of the focal product (54 respondents). A 5-point Likert scale was employed (zero indicated no usage). Scores were summed creating a total measure of the degree of flexible automation use. Cronbach's Alpha was .65.
This measurement scale was originally designed to reflect a number of advanced systems and technologies, such as Optimized Production Technology (OPT), Flexible Manufacturing System (FMS), Materials Requirements Planning (MRP), and Just-In-Time Manufacturing (JIT). Unfortunately the measurement scale produced a very low level of reliability (Coefficient Alpha = .30). A subsequent factor analysis of the scale items produced two factors (FMS and Robotics) loading highly (.80) on a single common factor. Thus, a reduced advanced systems measurement scale (FMS/Robotics) was defined which provided a sufficient degree of reliability for statistical analysis.
Product-process Alignment (PPA). To determine the extent of product-process alignment, the SBU general manager was asked to determine the current life cycle stage (introductory, growth, maturity, continuation, or decline) for the focal product. Independent of this event, the manufacturing manager in the same SBU was asked to designate the dominant type of operational process (job shop, batch process, assembly line, or continuous process) used to manufacture the focal product. A subsequent comparison indicated whether or not a specific product-process match conformed to the prescriptive correct diagonal placement recommendations of Hayes and Wheelwright (1979a,b).
Originally designed to accommodate a wide range of potential product-process misalignment, the measurement scale was designed as a Likert-type interval scale with measures of 1 to 4 per item (4 implying a position on the diagonal, 1 implying a position furthest from the diagonal). The data obtained from the sample of twenty-seven product groups, however, showed the maximum level of product-process misalignment was limited to one interval of misalignment. Thus, the sample data produced only two values related to product-process alignment, aligned (on diagonal) and nonaligned (one stage off diagonal). SBU's were nearly equally represented among the two designations.
Manufacturing Performance (MP). A manufacturing performance measurement scale was designed to provide a non-financial manufacturing specific measure of performance. The twelve-item, 7-point Likert scale reflected an equal balance of the manufacturing performance criteria of cost, flexibility, quality, and dependability (Wheelwright, 1978). Measurement scale items employed many of the items empirically tested by prior researchers (Swamidass, 1986; Huete and Roth, 1987; Sharma, 1987). Factor analysis produced the expected four factors, thus the scale was deemed consistent with expectations for performance criteria. A Coefficient Alpha level of .65 was obtained.
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