Abstract
This study tests the hypothesis that companies who move away from the traditional Hong Kong business model by adopting ‘up-grading’ strategies enjoy superior performance. A set of 14 variables is used to capture the dimensions of strategy, encompassing the business, technology and design domains. The results of both comparative and configurational approaches show that there are indeed performance benefits to be had. The broader implication is that Hong Kong manufacturing firms are beginning to escape the ‘iron fetters’ of a business model originally imposed on them by both material and ideational constraints, and to reap performance benefits as a result.
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Howard Davies is an Associate Dean in the Faculty of Business at the Hong Kong Polytechnic University. David Ko completed his DBA thesis under Prof. Davies's supervision.
Appendices
Appendix 1
A Measurement Model for Six Strategy Constructs
Fit measures | Standardized loading |
Chi-square=451.9, Degrees of freedom=197, Number of parameters estimated=56; Observations per parameter estimated=366/48=6.5; Chi-square per df=2.29; GFI=0.900; TLI=0.914; CFI=0.926; RMSEA=0.060 | |
Emphasis on efficiency | |
Construct reliability=0.87 | |
I1 Operating the factor at full capacity | 0.64 |
I2 Operating efficiency | 0.90 |
I3 Efficiency in getting materials and components | 0.83 |
I4 Reducing production costs | 0.81 |
Product line breadth | |
Construct reliability=0.73 | |
J1Offering a broad line of products | 0.78 |
J2 Offering a wide variety of products | 0.70 |
J3 Meeting the needs of all potential customers | 0.57 |
J4 Selling to a small group of customers (deleted) | |
Price leadership | |
Construct reliability=0.78 | |
K1Selling at low prices | 0.80 |
K2 Pricing below other firms in the industry | 0.92 |
K3 Being a price leader | 0.43 |
K4 Offering a lower price for the same quality | 0.56 |
Branding | |
Construct reliability=0.75 | |
L1 Heavy spending on advertising | 0.71 |
L2 Intensive marketing effort | 0.85 |
L3 Building strong brand identification | 0.56 |
Environmental scanning | |
Construct reliability=0.82 | |
M1. Meeting customers to identify their future needs | 0.64 |
M2. Doing market research | 0.69 |
M3.Asking customers to assess the quality of our products | 0.83 |
M4. Collecting information on the industry | 0.77 |
Commodity/specialty products | |
Construct reliability=0.85 | |
P1. Uniqueness of your products | 0.78 |
P2. Targeting a clearly identified segment | 0.80 |
P3. Offering products suitable for high prices | 0.70 |
P4.Offering specialty products | 0.79 |
Appendix 2
A Measurement Model for Two Strategy Constructs
Fit measures | Standardized loading |
Chi-square = 34.8; Degrees of freedom = 13, Number of parameters estimated = 15; Observations per parameter estimated = 366/15 = 24.4; Chi-square per df = 2.68; GFI = 0.973; TLI = 0.987; CFI = 0.992; RMSEA = 0.068 | |
China as a market | |
Construct reliability=0.97 | |
N1 Selling electronic products in Mainland China | 0.86 |
N2 Developing the Mainland China market | 0.96 |
N3 Increasing sales in Mainland China | 0.98 |
N4 Finding new customers in Mainland China | 0.96 |
China for resources | |
Construct reliability=0.90 | |
O1 Producing in Mainland China | 0.82 |
O2 Using lower cost facilities in Mainland China | 0.89 |
O3 Using cheaper labour and premises in China | 0.90 |
Appendix 3
A Measurement Model for Zahra and Covin's ‘Technology Policy’ Constructs
Fit measures | Standardized loading |
Chi-square = 222.1, Degrees of freedom = 51, Number of parameters estimated = 27; Observations per parameter estimated = 366/27 = 13.6; Chi-square per df = 4.36; GFI = 0.91; TLI = 0.94; CFI = 0.95; RMSEA = 0.096 | |
Aggressive technological posture | |
Construct reliability=0.92 | |
Q1 We try to lead the industry in technology, not follow | 0.81 |
Q2 Our company seeks a reputation for being the first to introduce new technologies | 0.89 |
Q3 Our technology development work allows us to enter new markets before our competitors | 0.92 |
Q4 Our technology is more advanced than our competitors' | 0.84 |
Process innovation | |
Construct reliability=0.92 | |
R1 We aim to have a higher level of automation than competitors | 0.84 |
R2 We spend more on up-grading our equipment than competitors | 0.88 |
R3 Our production process is more advanced than our competitors | 0.91 |
R4 Process innovation gives us a competitive advantage | 0.81 |
New product development | |
Construct reliability=0.89 | |
S1 We aim to introduce more new products than competitors | 0.83 |
S2 We spend more on new product development than competitors | 0.84 |
S3 We try to introduce products that are “new to the world:” | 0.79 |
S4 Our new products give us a competitive advantage | 0.82 |
Appendix 4
A Measurement Model for Three New ‘Technology Policy’ Constructs
Fit measures | Standardized loading |
Chi-square = 309.3, Degrees of freedom = 62, Number of parameters estimated = 29; Observations per parameter estimated = 366/29 = 12.6; Chi-square per df = 4.99; GFI = 0.90; TLI = 0.90; CFI = 0.91; RMSEA = 0.105 | |
Original equipment manufacture | |
Construct reliability = 0.83 | |
T2 We rely on our customers for product design | 0.55 |
T3 Our most important products are designed by customers | 0.71 |
T4 it is not our strategy to design our own products | 0.82 |
T5 OEM is more important to us than ODM | 0.87 |
Original design and manufacture | |
Construct reliability = 0.92 | |
U1 We rely on our own product design capability | 0.82 |
U2 Our most important products were designed by ourselves | 0.92 |
U3 In-house product design is an important part of our strategy | 0.92 |
U4 ODM is more important to us than ODM | 0.71 |
U5 We spend more than competitors on in-house product design | 0.76 |
Imitation/competition-based technology development | |
Construct reliability = 0.81 | |
V2 We design products by modifying competitors' designs. | 0.53 |
V3 We improve on competitors designs for our products | 0.60 |
V4 Competitors' product design shows us the way | 0.84 |
V5 Imitating successful product designs from other companies is our strategy | 0.91 |
Appendix 5
Measurement Model for the Performance Constructs
Fit statistics for the three factor model shown below: GFI = 0.910, TLI = 0.926, CFI = 0.945 | ||
| Standardized loadings | Construct reliability |
Satisfaction with the achievement of strategic objectives | ||
W1.We are very satisfied with the overall performance of our enterprise | 0.823 | 0.87 |
W2.We are very satisfied with our performance compared with our competitors | 0.881 | |
W3. We have been very successful in achieving our strategic objectives | 0.801 | |
Effective adaptation | ||
W4. Our company does a good job in anticipating problems | 0.796 | 0.88 |
W5. We do a good job of keeping up with changes | 0.854 | |
W6. Our company implements changes very quickly | 0.826 | |
W7. When emergencies occur, this company copes very successfully | 0.730 | |
Financial performance (very poor performance = 1, average = 4, excellent performance = 7) | ||
W8. Total sales | 0.805 | 0.93 |
W9. Total profits | 0.847 | |
W10. Growth of sales 2000–2002 | 0.915 | |
W11. Growth of profits 2000–2002 | 0.937 |
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Davies, H., Ko, D. Up-grading and performance: the role of design, technology and business strategy in Hong Kong's electronics industry. Asia Pacific J Manage 23, 255–282 (2006). https://doi.org/10.1007/s10490-006-9001-8
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DOI: https://doi.org/10.1007/s10490-006-9001-8