A Survey of Manufacturing Strategy and Technology in the Chinese Furniture Industry

Pergamon

European Management Journal Vol. 21, No. 4, pp. 484–496, 2003  2003 Elsevier Ltd. All rights reserved. Printed in Great Britain doi:10.1016/S0263-2373(03)00079-3 0263-2373 $30.00 + 0.00

A Survey of Manufacturing Strategy and Technology in the Chinese Furniture Industry DAVID ROBB, University of Auckland BIN XIE, Tsinghua University We investigate the manufacturing strategy of 72 Chinese furniture companies based on a nationwide survey conducted in mid-2001, just prior to WTO accession. We provide an overview of the industry and its context before reporting on the operations objectives of the firms — focusing on their relationship to financial performance and technology. We report on the current status of, and future plans for, manufacturing technology implementation and initiatives (such as computeraided design, safety improvement, new product introduction, and reducing changeover times). We make comparisons with other studies, in particular in the US — where Chinese furniture imports are increasingly viewed as a competitive threat.  2003 Elsevier Ltd. All rights reserved. Keywords: Manufacturing in China, Operations strategy, Advanced manufacturing technology, Production management, Quality management

Introduction With increasing attention focused on the Chinese economy, it is useful to consider the state of manufacturing (which comprises half of China’s GDP), particularly in industries where exports are growing rapidly. This paper presents the results of a survey of the practices and performance of 72 furniture manufacturers located throughout China. The survey, con484

ducted just prior to China’s WTO accession in late 2001, considers both manufacturing strategy (with a particular interest in manufacturing technology) and performance (including financial). There are currently some 30,000 furniture manufacturers in China, employing a total of 3 million people (Volpe, 2002). While the industry constitutes only 1.6 per cent of total Chinese manufacturing and Chinese exports, some of its features render it particularly interesting. For instance, its very rapid growth, in both domestic and export markets, and its relatively low labour productivity are worth noting. The remainder of the paper provides a review of manufacturing strategy in the furniture industry and in China, and characteristics of Chinese furniture manufacturing. Following a discussion of the survey instrument and administration, we present the results of the survey, which focuses on competitive objectives and financial performance, and their relationship to manufacturing, technology, and human resource management practice.

Literature Review Manufacturing Strategy and Technology Numerous studies conducted during the past two decades demonstrate the importance of manufacturEuropean Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

ing strategy in relation to firm performance (Demeter, 2003). This stream of research includes work highlighting the connection between performance and manufacturing technology (Beaumont and Schroder, 1997; Das and Narasimhan, 2001), and quality management practices (related to both people and systems/assets) (Dow et al., 1999). In the context of this research, single industry, single-country studies provide a useful contribution by controlling for industry and national effects and distinctions. The Furniture Industry and Manufacturing Strategy Studies of the furniture industry in the United Kingdom (Deeks, 1976) and the United States (Skinner and Rogers, 1968; Moorman and Montgomery, 1998) show an industry comprised largely of small, privately-owned firms (the majority employing less than 100), with many operating in a ‘craft’ production mode and very labour intensive. Cost structures are dominated by high material (average 40–48 per cent) and direct labour (average 19–27 per cent) costs, with average profitability in all three studies stated as 4– 5 per cent after tax. Raw materials have had a strong bearing on the industry’s development — in terms of plant location, efforts to secure overseas supply (e.g. shortages of hardwoods), and product design (e.g. use of veneered woods, metals, and plastics). With processes such as assembly and finishing notoriously difficult to automate, the furniture industry in general is not known for highly advanced manufacturing technology — the level is ‘reasonable but not overwhelming’ (Vickery et al., 1994). In the US, sales are cyclical and closely related to discretionary income, consumer credit, and house sales, lagging new-home sales by 1–2 years (Moorman and Montgomery, 1998). Products can be classified according to primary material (wood, upholstered, metal, other), use (case goods [dining room and bedroom furniture], occasional furniture [coffee and end tables]), as well as style, finish, quality, and price. Generally only the largest firms target more than one segment of the market. A 1990 study of 65 US furniture firms with sales above US$ 10 million showed that manufacturing strategy, expressed in terms of ‘production competence’, was strongly associated with business strategy and firm performance (Vickery et al., 1993). Manufacturing Strategy and Technology in China A 1997 survey of 46 companies in the Beijing area (Robb and Xie, 2001) compared the manufacturing practices and performance of foreign-invested with Chinese-owned firms. The authors found strong evidence that Chinese-owned firms were lagging behind Foreign-Invested Enterprises when it came to comEuropean Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

peting on time. A similar survey conducted with 120 firms predominantly in the Shanghai region (Pyke et al., 2002) found few differences related to ownership. In another survey of 72 Chinese manufacturing firms (predominantly textiles, consumer goods and electronics) (Li, 2000) showed manufacturing initiatives to be strongly correlated with sales volume, market share, and return on investment, but did not have any significant predictive relationship with profit after tax. A study of eight companies during the 1990s (Forrester and Hassard, 2000) concluded that concepts and frameworks of contemporary Western manufacturing strategy and quality management are applicable in China, but that they ‘only provide a partial explanation for manufacturing management practice.’ A focus on technological advancement and productivity improvement (through economies of scale), and the political context are more influential than the market.

Furniture Manufacturing in China Buoyed by a strong domestic economy and construction sector along with a booming export business, furniture manufacturing has grown rapidly — with a doubling of production in the second half of the 1990s, and subsequent double-digit annual growth (see Table 1). Mirroring many industries in China, a capacity glut emerged, leading to vicious price competition, with wholesale prices halving over the second half of the 1990s (Anon, 2001). Initial estimates by the China National Furniture Association (Zhang, 2003) suggest total Chinese furniture production in 2002 was US$20 billion, up 17 per cent from 2001. US furniture production in 2000 was US$75.5 billion (US Census Bureau, 2002). Double digit annual growth is expected during this decade (Sun and Bean, 2001), driven both by export markets and increases in per capita furniture consumption. The latter is still relatively low for emerging markets, but is increasing as both disposable income and home ownership, which became possible in 1998, continue to rise. Joint ventures, which currently number one thousand and supply some 30 per cent of the domestic market (Anon, 2001), are expected to increase. With entry costs to the industry relatively low (perhaps 300,000 RMB), the typical firm is small in scale. However, there are some very large manufacturers such Tiantan, a public company founded in 1956. The largest furniture company in China, it has 22 factories (5 Joint Ventures), 3600 employees, 1998 sales of US$100 million and 400 sales outlets in more than 150 cities (Anon, 2001). 485

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Table 1

Furniture Furniture Furniture Apparent

Chinese Furniture Industry. All Figures in US$ Billions (1 RMB = US$ 0.12)

production exports imports domestic consumption of furniture

1995

2000

2002

Compound annual growth rate 1995–2000

Compound annual growth rate 2000–2002

6.78 1.10 0.08 5.76

12.74 3.65 0.10 9.19

19.95 5.30 0.10 14.75

13% 27% 5% 10%

25% 21% 0% 27%

Source: Elaboration of CSIL data (Anon, 2001) and CNFA data (Anon, 2003)

Several recent reviews of the industry (All China Marketing Research, 2001; Anon, 2001) confirm that furniture manufacturers are diversifying into new products and new markets, especially exports. Trade Chinese furniture exports have risen dramatically in recent years (see Table 1), and are likely to continue with WTO membership securing China ‘equal treatment’. In less than a decade China has risen from the 11th largest furniture exporter to now vie for first place with Italy — with exports growing at 30 per cent per year (Zhang, 2003). Half of the exports are destined for the US, where they now comprise close to half of US furniture imports. Some now perceive China as the ‘biggest competitive threat to US furniture manufacturing’ (Engel, 2002), even in the highend of the market (Wille and Adams, 2001). Some leading US furniture manufacturers have made dumping claims (Zhang, 2003). Furniture imports comprise less than 1 per cent of domestic furniture demand and are relatively static. Some commentators had expected substantial drops in tariffs, now scheduled for elimination in 2005, to result in increased imports. However, an increasing number of foreign-invested enterprises and an improvement in the medium quality furniture subsectors (Shen and Cao, 1999) have so far staved off any growth. Another factor in limiting import growth is the relatively high cost of logistics - shipping, customs clearance, and domestic distribution. Manufacturing Technology Most firms are very labour intensive. Increased automation and the emergence of private companies have markedly improved labour productivity over the past decade. Despite these gains, labour productivity remains comparatively low. Gross-value added per employee in Chinese furniture manufacturing in 1997 was only 5 per cent of that in the U.S.1 The average comparative China-US labour productivity across all industries is 7.6 per cent (Wu, 2001). One should bear in mind that average pay rates for furniture production workers in China are about 4 per cent of those in the US. In China, the average furniture manufacturer has 486

limited technology, but there are significant exceptions, particularly among foreign-invested firms. For example, some firms have annual sales per worker as high as US$ 25,000 — ten times higher than the norm (Volpe, 2002), and recently two Beijing manufacturers invested in excess of US$ 10 million on imported furniture manufacturing equipment (Shen and Cao, 1999). One source even claims that ‘most [Chinese furniture manufacturers] are operating with technology and machinery more advanced than that found in the average US furniture factory’ (Wille and Adams, 2001). While the majority of AMT is imported, predominantly from Italy, Germany, and Taiwan, the proportion is decreasing as local supply improves. The 600 domestic equipment suppliers have generally been viewed as being 10–15 years behind (Anon, 2001)). Quality Management Even the domestic sources report quality as a major concern in China, e.g. a survey made by the National Bureau of Quality Control and Quarantine revealed that one third of wood furniture has a quality problem (All China Marketing Research, 2001). Human Resources The importance of human resource management in Chinese manufacturing has been highlighted by numerous authors (Forrester and Hassard, 2000; Sun et al., 2001). A 1996 study concluded that many of the problems of computer-integrated manufacturing implementation ‘are the result of management development lagging behind technology advancement, outdated organizational structure being unable to adapt to the needs of technology development and market economic environment, improper and inadequate use of human resources and lack of business-led CIM strategy’ (Zhou and Chuah, 2002). In this regard, teamwork and the alignment of bonus systems with performance criteria are especially important (Li et al., 2000). One multi-industry survey (Li, 2000) conducts a multiple regression and establishes human resource practices (relating to employee empowerment, job enlargement, labour – management relationships, and performance measurement) as significantly related to profitability (P ⬍ 0.01) and return on investment (P ⬍ 0.05), as well as market share and sales volume. European Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

Table 2 Responses (Note Responses in the High Income Regions include 13 Responses from 55 Phone Calls in the Beijing Area)

Average GDP/capita (RMB/yr) Responses

Low income Middle income regions High income regions regions (Henan, (Hebei, Heilongjiang, Hubei, (Beijing, Guangdong, Shaanxi, Sichuan) Jilin, Liaoning, Shandong) Zhejiang)

Total regions of China (comprising 54% of total population and 58% of GDP)

5101

8506

12,365

8281

23/90 (26%)

22/180 (12%)

27/145 (19%)

72/415 (17%)

Survey Methodology Questionnaire The questionnaire closely followed previous instruments used in Chinese manufacturing studies (Robb and Xie, 2001; Pyke et al., 2002). The Chinese version of the survey (used by all but one respondent) was back-translated into English to establish translation accuracy.

Sampling and Administration The survey was conducted in mid-2001, just prior to the announcement of China’s World Trade Organization Accession. We mailed 30 surveys to each of twelve provinces selected to reflect a variety of regions and income levels (see Table 2). In each province 20 surveys went to companies randomly selected from the 2001 directory of the 4000-member China National Furniture Association and 10 surveys went to non-CNFA members. Seeking to overcome the very low, often single digit, response rates associated with mail surveys in China, each survey included a reply paid envelope and a letter of endorsement from the CNFA. With the level of analysis being the plant, the survey was sent to the General Manager at each plant, but asked if they wanted to forward it to someone else in the plant (e.g. a Senior Production/ Manufacturing/Plant Manager). Table 3 provides the respondent position.

Table 3 Position

Respondent Position Number

GM 19 Vice General Manager 9 Factory/Plant Manager 6 Assistant GM 4 President 3 Chairman of Board 2 Manufacturing/Production Manager 2 Other 22 Not stated 6

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Responses were received from 72 plants — a 17 per cent response rate (see Table 2). There were 59 responses from 360 mailed surveys. This was supplemented with personal interviews with managers at 13 additional plants resulting from 55 phone calls to randomly selected furniture companies in the Beijing ‘Yellow pages’. These interviews assisted in assessing validity as well as methods variance.

Measurement Items on the questionnaire included three and sevenpoint Likert scales as well as nominal qualitative and metric measures. For financial performance, we requested total sales figures for 1999 and 2000, but assessed profitability and market share using Likert scales — being aware of the tendency of Chinese firms to inflate earnings. Several reverse-coded questions provided support for content validity.

Results Demographics Company Size Table 4 provides summarized data of company size. Mean annual sales turnover was 40.5 million RMB (US$4.9 million), a mere 4 per cent of the US$122 million mean sales in the 1990 US study (Vickery et al., 1994). Table 5 provides a distribution of sales revenues. The mean number of employees in 2001 was 377 (median 225), 28 per cent of the equivalent figure of 1364 in the 1990 US study (Vickery et al., 1994). With the average number of employees in the industry as a whole reported as 100 (Anon, 2001) and 70 (Volpe, 2002), our sample is biased towards larger firms (see Table 6). Despite growth during the previous five years (1996 figures were 336 (median 114)), 21 firms (30 per cent) reported a decline in work-force size. An average of 78 per cent of employees were classified as ‘operators’, very similar to the equivalent figure in the US of 80 per cent (US Census Bureau, 2002). The mean (year 2000) sales per employee for respon487

A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

Table 4

Company Size Characteristics

Sales (2000) (million RMB) Sales Growth (1999–2000) Number of employees (mid–2001) Sales (2000) per employee (mid-2001)

Table 5

Mean

SD

Median

Minimum

40.5 23.1% 377 111

70.4 35.7% 554 87

18.0 16.7% 225 78

0.6 ⫺50% 16 9

Enterprise Size — Annual Sales (2000)

Annual Sales (million RMB)

Number

Per cent

Cumulative per cent

⬍5 5–9.99 10–24.99 25–49.99 50–99.99 100–249.99 ⬎250 Not stated

7 14 24 10 9 4 2 2

10% 20% 34% 14% 13% 6% 3%

10% 30% 64% 79% 91% 97% 100%

Table 6

Enterprise Size — Workforce

Number of employees Number

Per cent

Cumulative per cent

⬍50 50–99 100–249 250–499 500–999 ⱖ1000 Not stated

3% 15% 38% 23% 15% 6%

3% 18% 56% 79% 94% 100%

Table 7

2 11 27 16 11 4 1

Ownership

Form of ownership

Number

Average proportion of total ownership (69 firms)

State Collective Private Foreign Mixed (joint) Not stated

8 4 44 2 11 3

17% 9% 67% 7%

dents was 111,000 RMB (US$ 13,405), about twice the aggregate Chinese furniture industry figure of US$ 6300 (CSIL 2001), but still only 15 per cent of the US$ 89,500 reported in the 1990 US study (Vickery et al., 1994), and only 11 per cent of the year 2000 Annual Survey of US Manufacturers value of US$ 117,500 (US Census Bureau, 2002). While the majority of firms (67 per cent) were totally privately-owned (see Table 7), ownership when weighted by year 2000 sales was 47 per cent State 488

Maximum 467.3 150 % 4000 391

and 37 per cent private, i.e., the privately-held firms tend to be smaller. The survey included six joint ventures (two American, two Hong Kong, one Swedish and one Japanese) and two wholly-foreign owned enterprises (US and Hong Kong). Products Companies were asked to list up to three major product categories. Office, bedroom, and living room furniture dominated (see Table 8). We found few companies specializing in only one segment of the market, confirming the findings of (Anon, 2001) and supporting the observations of a high degree of competition and diversification strategies, e.g. ‘Every factory ... that was category-specific wants to broaden into other areas’ (Slaughter, 2001). Companies reported an average of 321 (median 67, SD 1253) products in their range.These findings suggest a greater degree of diversification than the US, particularly when one considers the smaller size of Chinese firms. Exports Average exports constituted 14 per cent of sales (median 5 per cent, SD 24 per cent), somewhat less than the 29 per cent figure for total Chinese production in 2000. This difference is likely due to the geographic stratification of our sample, with Guangdong Province enterprises comprising only 10 per cent of our responses (and 7 per cent of surveys) but accounting for 20 per cent of furniture companies and some 60 per cent of exports (Anon, 2001).

Table 8 Items Manufactured (up to Three Listed by Each Firm) Furniture type

Number of firms manufacturing

Office furniture Sofas Bedroom furniture (includes mattresses and beds) Hotel furniture Dining room furniture General furniture Wooden furniture School/university furniture Living room/lounge Other

30 26 20 13 13 13 9 5 5 56

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A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

Performance In this section we report on self-reported firm performance, in terms of competitive priorities and financial measures. Competitive Objectives The importance of various competitive objectives was assessed on responses to 7-point Likert scale questions soliciting the degree of emphasis (relative to competitors) placed on each of 13 competitive objectives (see Table 9 — which lists the objectives in decreasing order of mean response). In a similar manner, plant performance was assessed by requesting the degree of improvement during the past year on the 13 objectives along with two financial measures — market share and profitability. Sales growth was calculated from sales figures reported for 1999 and 2000. Correlations between importance and performance averaged 0.42 — from 0.18 (product mix flexibility) to 0.63 (after sales service). This high level of consistency provides some evidence of validity (Vickery et al., 1994) Correlations among the 13 competitive objectives in terms of importance averaged 0.35 (minimum 0.03, maximum 0.67). For performance the average was higher (0.41, minimum 0.20, maximum 0.87). For importance and performance, the maximum correlation was between delivery speed and delivery reliability. The relatively high correlations suggest the usefulness of factor analysis. Factor Analysis To reduce the number of variables from 13 we conducted a (common) factor analysis on the importance of the competitive objectives using the Principal Components method with varimax rotation to extract factors. Scree plot and latent root criteria (eigenvalue ⬎ 1) supported the use of four factors. All items had at least one standardized factor loading exceeding 0.55 (0.5 or above is considered ‘practically significant’ (Hair et al., 1998)). Table 9 presents these results. The first factor comprises six competitive objectives: Product Reliability, Consistent Quality, Product Durability, Delivery Dependability, After-sale Service, and Low Production Cost. The loading of cost with quality objectives, a phenomenon also observed in a 1990 study of US furniture manufacturers (Vickery et al., 1997), led us to denote this factor ‘Value’. We believe this grouping of quality with both cost and delivery dependability emphases indicates a level of maturity in the industry regarding quality as a precondition for performance on the dimensions, as is touted by the ‘sandcone’ model (Ferdows and De Meyer, 1990). European Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

Interestingly, the six objectives loading on to Value are also the six highest-ranked objectives, and include all of the quality objectives. The emphasis on quality is consistent with previous studies of Chinese manufacturing (Robb and Xie, 2001) and industry observations that quality has improved markedly and can ‘no longer be dismissed as low-end suppliers. Indeed, several Chinese furniture plants (joint ventures as well as 100 per cent domestic plants) are even attempting to penetrate the highend US markets’ (Wille and Adams, 2001). Production time and Delivery time load onto the second factor, which we denote by ‘Speed’. The average delivery date is 14 days (median 10 days) after order placement. The third and fourth factors comprise objectives traditionally falling under the rubric of external or market-based flexibility. The third factor is comprised of Modification Flexibility (described as ‘Adding New Functions to Existing Products’) and Volume Flexibility, and denoted by ‘Flexibility’. Modification would generally involve additional parts and/or processing, e.g., to add a PC shelf or a lighting fixture to a desk, to add a cabinet in the centre of a ‘gate’ table, to rotate the top bed in a bunk set by 90 degrees to allow a desk set to be incorporated underneath, or to allow variations in the types of pads on a mattress. Clearly such flexibility places additional pressure and uncertainty on production capacity, so it’s co-loading with volume flexibility is natural. Interestingly, however, these two objectives have the lowest average scores of the 13 objectives — in both performance and importance. We comment further on this when considering financial performance. The three objectives loading on the fourth factor are New Products, New Product Development Time, and (the intuitively related) Product Mix Flexibility, leading us to designate it as ‘Innovation’. Earlier observations of the furniture industry, describing it in some respects as a fashion industry ‘especially in upholstery, where fabric tastes are constantly changing and where new ideas are introduced frequently’ (Deeks, 1976), are echoed in our own study. Some interviewees recounted that style was becoming more important, with customers changing their furniture more frequently and demand becoming more diversified. However, it is generally acknowledged that the Chinese furniture industry is lacking in product design and innovation, with designs that are ‘simply imitated and lack originality’ (All China Marketing Research, 2001) and with increasing calls for ‘creating innovative designs’ (Zhang, 2003). The situation closely parallels the US furniture industry many years ago where firms avoided design costs by ‘using the markets as a source of their new patterns and styles’ (Skinner and Rogers, 1968). 489

490

Named

Eigenvalue Proportion variance explained Cumulative variance explained

6.2 6.2 6.1 6.0 5.8 5.8 5.8 5.8 5.7 5.7 5.6 5.4 5.0

Delivery dependability Product reliability After-sale service Consistent quality Product durability Low production cost Production time New products Delivery time New product development time Product mix flexibility Volume flexibility Modification flexibility

1.2 1.1 1.3 1.1 1.4 1.4 1.3 1.4 1.5 1.7 1.5 1.5 1.7

Mean score SD

0.714 0.737 0.696 0.723 0.735 0.491 0.830 0.699 0.763 0.741 0.662 0.604 0.825

Communality

Value

3.361 0.259 0.259

0.709 0.806 0.668 0.784 0.718 0.556 0.052 0.357 0.279 0.295 0.027 0.146 0.085

Factor 1

Speed

2.270 0.175 0.433

0.368 0.269 0.128 ⫺0.201 0.153 0.324 0.896 ⫺0.064 0.795 0.500 0.098 0.398 0.142

Factor 2

Flexibility

Innovation

1.665 0.128 0.709

0.262 0.104 ⫺0.144 0.111 0.123 0.245 0.083 0.591 0.084 0.613 0.803 0.278 0.125

⫺0.083 0.067 0.461 0.237 0.426 ⫺0.129 0.134 0.467 0.214 0.167 0.080 0.589 0.884 1.924 0.148 0.581

Factor 4

Factor 3

Rotated factor pattern

0.245 0.294 0.214 0.312 0.205 0.194 ⫺0.122 0.011 ⫺0.025 ⫺0.038 ⫺0.113 ⫺0.121 ⫺0.148

Factor 1

0.092 0.035 ⫺0.021 ⫺0.257 ⫺0.057 0.092 0.499 ⫺0.226 0.404 0.138 ⫺0.093 0.118 ⫺0.025

Factor 2

⫺0.257 ⫺0.131 0.229 0.035 0.149 ⫺0.256 ⫺0.004 0.182 0.023 ⫺0.075 ⫺0.088 0.318 0.588

Factor 1

0.079 ⫺0.071 ⫺0.300 ⫺0.009 ⫺0.083 0.099 ⫺0.117 0.379 ⫺0.139 0.356 0.631 0.045 ⫺0.077

Factor 2

Standardized scoring coefficients

Factor Analysis of the Emphasis Rating (Four-Factor Solution, Varimax Rotation). Objectives Listed in Descending Order of Mean Emphasis

Emphasis (relative to competitors) on:

Table 9

A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

European Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

A SURVEY OF MANUFACTURING STRATEGY AND TECHNOLOGY IN THE CHINESE FURNITURE INDUSTRY

Financial Performance Interviews with Beijing respondents affirmed that competition in the industry is intense and increasing. However, quoted profit margins of 5–7 per cent are similar or above those found historically in the US and the UK. To examine the relationship between financial performance and the importance of various competitive objectives, we undertook factor score regression analyses with the current emphasis of the four factors as the dependent variable (see Table 10). Profitability (return on sales), generally viewed as the most important performance measure in the furniture industry (Vickery et al., 1994), was positively related to Value (P = 0.056). Sales Growth (percentage increase in the previous year) was positively related to Flexibility (P = 0.081). Market Share was positively related to both Value (P = 0.063) and Flexibility (P = 0.042). Other studies (Chang et al., 2003) have also established similar positive relationships between various aspects of Flexibility (both modification and volume flexibility) and financial performance (profitability and sales growth). It would appear that Value and Flexibility are order winners in the market, with the latter still relatively rare (it comprising the two least emphasized objectives). These results contrast with the 1990 study of 65 American furniture manufacturers which established that above average financial performance was associated with above average emphasis on a variety of operational competencies, including Innovation, but not Value (Vickery et al., 1997). Financial Performance (measured in terms of return on sales) was not strongly correlated to the size of the firm, either in terms of number of employees (P = 0.19) or annual sales (P = 0.38). This result concurs with that of an earlier British study (Deeks, 1976).

Management and Manufacturing Technology and Improvement Actions The survey examined various aspects of management and manufacturing technology, including strategy, product design, equipment, quality management,

Table 10

and human resource aspects. Table 11 reports the various aspects within these constructs, along with correlations with financial performance over the past year, and the importance of the four factors. In addition, for various technologies and improvement actions we assessed the current implementation status [1 = none, 2 = in progress, 3 = full] and future investment plans [1 = no plans, 2 = considering, and 3 = decided]. Table 12 lists the items ranked by mean current status, with correlations of current status with financial performance over the past year, and future plans with importance of the four factors. Strategy and Design Responses to the first two strategy questions (Strl and Str2) indicate support for the benefit of concurrent engineering, with high correlations with market share improvement. The negative correlations on the reverse-coded SO provide further evidence for content validity. The negative relationship between an emphasis on Speed and the ability to run small batches (implying low set-up costs) is somewhat disturbing. It would appear that some managers don’t realize that set-up time reduction is one way to strengthen the capabilities to compete on time, with reactive strategies such as overtime and additional capacity being pursued. While our results confirm that JIT principles have not been widely applied in the Chinese furniture industry (its current status ranked 18th among the 24 initiatives listed in Table 12), this appears set to change, with it ranking fifth among ‘future plans’. The strong relationship between Flexibility and longterm planning, as well as planning processes for new product releases, indicates that competing on this dimension requires a long-term commitment, e.g. to capability development and planning. Modular design (Des2) is strongly correlated, as expected, with Innovation. The average planning horizon for production capacity and facilities planning was 9.1 years (median 8). Equipment In the survey, the average equipment age ranged from 1 to 30 years, with a mean of 7.1 (median 5, SD 5.8). The average age in private firms is half that of other firms (4.9 versus 10.0 years). Running counter to several studies in which manu-

Results of the Regression Analyses

Dependent variables:

Entire model

Independent variables: (3 weights (p-values in parentheses))

Firm performance (past 12 months)

Adjusted R2

P-value

Factor 1 value

Sales growth (%) Market share (1–7) Return on sales (1–7)

0.010 0.075 0.041

0.335 0.063 0.155

⫺0.038 (0.299) 0.256 (0.063) 0.277 (0.056)

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Factor 2 speed ⫺0.013 (0.682) 0.084 (0.481) 0.034 (0.783)

Factor 3 flexibility

Factor 4 innovation

0.050 (0.081) 0.215 (0.042) 0.147 (0.183)

0.017 (0.553) 0.103 (0.333) 0.126 (0.261)

491

492

HRl HR2 HR3 HR4 HR5 HR6

Str7 Des t Des2 Des3 Eqp 1 Egp2 Egp3 Egp4

Str6

Str5

Str4

Str3

Str2

Strl

Manufacturing decisions are screened for consistency with marketing and business strategies/plans Manufacturing participates in making marketing, engineering and business strategy/planning decisions We only consider implementing new manufacturing practices or technologies if they have been adopted successfully by our competitors (i.e., we take a ‘follower’ approach) Manufacturing has the ability to run very small batches at virtually the same cost as larger batches Our manufacturing performance is evaluated on the basis of long term objectives Our manufacturing performance is evaluated on the basis of short term objectives Our product range, compared with our competitors is [1(7) = very narrow (wide)] We employ a well-defined plan for launching new products We design products using parts that are common to multiple products We design products for foreign markets as well as domestic markets Degree of specialization of production equipment Proportion of automated manufacturing equipment Proportion of production equipment developed by our firm The purpose of implementing new production technologies or equipment is mainly to reduce costs Our workers have no role in improving the manufacturing process Our workers are trained to manage different stages of the production process Our workers are consulted in deciding the production schedule Our production personnel are heavily involved in product design decisions Level of training given to workers The workers’ skills at doing their own jobs 1.4 1.6 1.7 1.5 1.6 1.5

1.7

4.5 2.8 4.8 3.6 5.0 4.8 5.0

1.7 1.2 1.3 1.8 1.3 1.6 1.5

1.8

1.3

1.7

1.7

1.3

1.1

SD

4.8 5.5 5.5 4.7 5.4 4.1 2.5

4.0

5.0

3.0

3.3

5.7

6.0

Mean

Manufacturing Strategy and Decision Areas Italics P ⬍ 0.05 Bold P ⬍ 0.01

Manufacturing decision areas

Table 11

0.11 ⫺0.29 ⫺0.21 0.01 0.04 0.28 0.50

⫺0.20 0.07 0.07 0.13 0.08 0.17

0.20 0.11 ⫺0.04 0.16 0.35 0.17 0.17

⫺0.05 0.09 0.29 0.00 0.30 0.44

0.10

0.25 0.16 ⫺0.18 0.21 0.32 0.23 0.37

0.21

⫺0.09

0.00

0.23 ⫺0.02 ⫺0.02 0.14 0.12 0.23 0.17

0.08

0.01 0.15

⫺0.13

⫺0.02

⫺0.16

0.22

0.15

0.09 ⫺0.04 0.03 ⫺0.02 0.43 0.34

0.01 0.00 0.05 0.29 0.28 0.04

0.07

0.17 0.08 ⫺0.09 0.08 0.16 0.10 ⫺0.19

⫺0.04 0.26 0.12 0.19 0.31 0.03 0.10 0.01

⫺0.13

0.23

⫺0.28

⫺0.02

0.35

0.07

0.06

0.02

⫺0.15

ⴚ0.34

0.29

0.34

0.18 0.09 0.19 0.25 0.12 0.05

0.04

0.17 0.36 0.13 0.25 0.18 0.19 0.37

⫺0.04

0.40

0.13

⫺0.27

0.33

⫺0.07

0.00

0.08

⫺0.15 0.07 ⫺0.04 0.04 0.21 0.00

0.07

0.24 ⫺0.01 0.25 0.24 0.13 0.37 ⫺0.11

⫺0.05

⫺0.07

⫺0.01

⫺0.29

Speed flexibility innovation

(Pearson) correlation with (current emphasis of) factors

Return on Value sales

0.12

⫺0.31

⫺0.03

0.04

0.30

0.14

Market share

0.20

0.09

Sales

(Pearson) correlation with (performance improvement in past year of) factors

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2.76 2.72 2.68 2.67 2.54 2.53 2.52 2.52 2.45 2.43 2.30 2.26 2.20 2.13 2.09 1.89 1.74 1.72 1.66 1.56 1.49 1.38 1.24 1.01

Improvement action or technology

Introduce more new products Improve worker safety Reduce production cost Motivate workers Change the labour/management relationship Increase supervisor training Provide more worker training Promote Quality Circles Adopt ISO 9000 Increase production capacity Reduce the time to adjust (set-up) machines Modify the functions of existing products Give workers more planning responsibility Give workers a broader range of tasks CAD (Computer aided design) Reduce workforce size Adopt ISO 14000 JIT (Producing parts only when products are needed) Automation in Production (equipment) Shift manufacturing operations to lower cost regions Statistical Process Control (SPC) CAM (Computer aided manufacturing) Robotics FMS (Flexible manufacturing systems)

2.34 2.58 2.17 2.34 2.24 2.01 1.97 2.01 1.96 2.03 1.90 1.87 1.87 1.77 2.55 1.58 1.08 2.25 2.14 1.21 2.11 2.06 1.64 1.32

Future plans (mean response)

0.19 0.12 0.03 0.08 0.28 0.10 0.14 0.22 0.16 0.26 0.17 ⫺0.09 0.25 ⫺0.17 0.11 ⫺0.03 0.15 0.17 0.20 0.01 ⫺0.17 0.01 0.30 ⫺0.08

Sales 0.40 0.20 0.00 0.23 ⫺0.03 0.19 0.27 0.40 0.06 0.12 0.15 0.16 0.14 ⫺0.19 0.08 0.04 0.08 ⫺0.01 0.07 ⫺0.17 0.09 ⫺0.09 0.22 ⫺0.08

Market share 0.30 0.17 0.10 0.28 0.08 ⫺0.02 0.13 0.36 0.16 0.07 0.08 0.12 0.10 ⫺0.06 0.23 ⫺0.07 ⫺0.03 0.18 0.26 ⫺0.11 0.15 0.14 0.28 0.06

0.05 0.00 0.13 0.07 0.01 0.03 0.10 0.13 0.05 ⫺0.02 ⫺0.20 ⫺0.05 ⫺0.09 ⫺0.07 0.03 0.02 ⫺0.14 ⫺0.08 ⫺0.01 0.07 ⫺0.10 ⫺0.17 ⫺0.03 ⫺0.16

–0.24 ⫺0.02 ⫺0.08 ⫺0.11 0.19 ⫺0.04 ⫺0.01 ⫺0.04 ⫺0.05 ⫺0.11 0.02 ⫺0.04 0.06 0.06 0.08 0.14 ⫺0.02 0.00 0.09 0.20 0.15 ⫺0.01 ⫺0.02 ⫺0.17

Speed

Innovation 0.12 0.08 ⫺0.03 ⫺0.01 0.08 0.09 0.16 0.07 0.09 0.15 0.07 0.09 0.13 0.15 0.08 0.01 0.21 0.31 0.16 0.26 0.32 0.27 0.05 0.20

Flexibility ⫺0.02 0.25 ⫺0.04 ⫺0.07 0.19 0.14 0.04 0.30 0.26 ⫺0.03 0.11 0.16 0.16 0.03 0.18 ⫺0.12 0.27 0.27 0.07 0.14 0.18 0.11 0.21 –0.07

(Pearson) correlation of future plans with (current emphasis of) factors

Return on Value sales

(Pearson) correlation of current status with (performance improvement in past year)

Improvement Actions and Technology (In Descending Order of Mean Current Status) Italics P ⬍ 0.05 Bold P ⬍ 0.01 Current status (mean response)

Table 12

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facturing equipment was found to have little impact on financial performance (Beaumont and Schroder, 1997; Demeter, 2003), we found several significant positive correlations e.g. with degree of automation. Here we are suggesting neither causality nor effectiveness in terms of strategy — it is possible that financially successful companies are the ones who have funds to invest in AMTS. Similarly, a company with extensive AMT investment may be a leader in technology, or might be one incorrectly deploying technology to solve other problems. Additional results regarding the relationship of equipment to competitive objectives include: (i) specialized equipment is related to an emphasis on Value (intuitively one would expect dedicated equipment to be adopted for cost and/or quality reasons); (ii) automation is related to an emphasis on Innovation (perhaps suggesting a linkage between product and process innovation); and (iii) in-house development is related to an emphasis on Flexibility (perhaps due to modification being facilitated through local process knowledge and ‘tinkering’ in design, engineering and production). Our results indicate Advanced Manufacturing Technology (AMT) to be more closely associated with emphases on Flexibility and Innovation, than on Value and Speed. This result partially confirms most AMT studies, which suggest AMTS are deployed to improve flexibility, but also quality and delivery, rather than cost. Table 12 shows CAD to be the most popular manufacturing technology, both with respect to current status and future plans, with CAM, robotics, and FMS playing only very limited roles. This result is consistent with new product introduction ranking first in terms of current initiatives, and supports findings that CAD is among the most common and often the first technology implemented (Boyer, 1998). Quality Management Plants reported a relatively high average of 70 per cent of quality efforts being devoted to identifying and eliminating the source of errors during the production process, as opposed to being expended at the end of the process. In our survey, several firms had positioned themselves as high quality providers, providing repair, replace, or full refund policies, and one firm reported no customer complaints in 10 years. There is a very strong correlation between Quality Circles and Financial Performance. ISO certification (9000 and 14000) does not have the same relationship, but is positively associated with Flexibility, perhaps a function of the foresight required in both of the areas. SPC is currently ranked low, but intentions to invest in this area are relatively strong, particularly among firms strong on Innovation. Again, these results suggest that advances in products and processes are closely linked to an overall concept of Innovation. 494

Human Resources The HR section of Table 11, and the ranked list in Table 12 shows training, development, empowerment, enrichment and safety initiatives, accorded relatively high priority, with several areas having strongly positive relationships to financial performance. Skill levels are very closely correlated with firms emphasizing Value. Pay is generally based on productivity, via piecework rates. In many plants workers lack formal education — often being part-time village farmers. One respondent commented that workers were managed more by control than motivation, leading to difficulties in implementing AMT. Similarly management training is also limited, with one manager commenting that finance and cost management were particularly weak.

Regional Differences One motive in employing a stratified sample was to compare responses between different regions of China. The three regions (see Table 2) were selected based on income levels (measured by GDP/capita) but also correspond largely with three geographical areas: Coastal (high income), North-East (middle income), and Central-Western (low income). Despite a heavy industry strategy and injection of tens of billions of dollars from the Chinese Government, western regions have not grown significantly. In fact, regional inequality has increased since the mid-1980s (Yang, 2002). Based on the above observations we expected to see substantial differences between the regions. What was noteworthy, however, was the lack of differences between regions. Conducting two-tailed t-tests between low and middle, and middle and high, income regions, revealed only seven questions where both pairs were significant, even at the 0.10 level. Even more surprisingly, in each of these cases it was the middle income region that was the outlier — recording the highest average in: performance improvement on product cost, worker involvement in process improvement, current status of programmes to improve worker motivation, reduce set-up times, reduce workforce size, and modify the functions of existing products, and future intentions with respect to worker safety.These findings suggest that business practice has diffused throughout China, at least among survey respondents. Fourteen of the responses were from non-CNFA members (seven from high income regions, and seven from low/middle income regions). Paired twotailed t-tests revealed (at the 0.05 level) a limited number of significant differences compared to the CNFA member population, viz., smaller size (onehalf the number of employees, and one-third the European Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

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sales revenue on average), less automation (P ⬍ 0.01) and in-house development of production equipment, shorter planning horizons (average of 6.2 versus 9.6 years), a greater likelihood of production technology adoption being motivated by cost (P ⬍ 0.01), less worker planning responsibility, and less plans for production automation and FMS. Despite these results indicating a lower level of manufacturing strategy, differences in financial performance, which included lower average sales growth (11 versus 25 per cent for CNFA members), were not significant at the 0.05 level.

Conclusions Chinese furniture manufacturing appears to follow general principles of manufacturing strategy. An emphasis on cost is not divorced from the importance of quality, indicating some maturity. A number of manufacturing policies, including those related to hard and soft technology and human resource areas are strongly connected to both competitive objectives and the financial performance of the firm. Value (in particular quality) and Flexibility (in particular modification) are highly related to financial performance, suggesting their importance as order winners in this market. It is apparent that many firms, especially larger ones, are seeking to increase AMT adoption, in particular computer-aided manufacturing. This will likely enhance the ability of Chinese firms to compete, in foreign markets and with foreign-invested firms in China, by lifting the level of performance on a variety of objectives. In terms of the future of the industry, WTO accession appears likely to fuel the continued expansion, and performance, of the industry, and place pressure on other major exporting nations. The Secretary-General of the CNFA predicts that within 20 years Chinese furniture will ‘match foreign producers for variety, quality and technique’ (Zhang, 2003). The response of European and North American manufacturers will be interesting to observe. Perhaps co-operation and alliances will prove the most sustainable path - along the lines of David Mathison’s call for ‘US companies to delve deep in their relationships with countries such as China and to become true partners, not shortterm opportunists’ (Engel, 2002). Co-operation in areas such as design and development, manufacturing systems and technology, management training and development, and distribution may be such areas — with or without equity investment. However, the path to improved performance will not be easy — one pundit predicts the future of Chinese furniture manufacturers over the first decade of WTO as ‘one third developing, one-third specializing, and one-third going bankrupt’ (All China Marketing European Management Journal Vol. 21, No. 4, pp. 484–496, August 2003

Research, 2001). The results of our survey suggest that manufacturing, technology, and human resource decisions will have a strong bearing on these outcomes. Future research could include extending the study longitudinally to assess the impact of WTO accession.

Acknowledgements The authors are grateful to Qunying Guo and Xiaoyang Wang for their administrative assistance. They would also like to acknowledge research funding from The University of Auckland and Tsinghua University.

Note 1. Employing the geometric mean of Chinese producer prices and US producer prices ratios

References Anon (2001) The Furniture Industry in China. CSIL, Milan. All China Marketing Research (2001) Research Report on Furniture Industry & Market of China. China Daily Information Company, Beijing. Beaumont, N. and Schroder, R. (1997) Technology, manufacturing performance and business performance amongst Australian manufacturers. Technovation 17(6), 297–307. Boyer, K. (1998) Longitudinal linkages between intended and realized operations strategies. International Journal of Operations and Production Management 18(4), 356–373. Chang, S.-C., Yang, C.-L., Cheng, H.-C. and Sheu, C. (2003) Manufacturing flexibility and business strategy: an empirical study of small and medium sized firms. International Journal of Production Economics 83(1), 13–26. Das, A. and Narasimhan, R. (2001) Process-technology fit and its implications for manufacturing performance. Journal of Operations Management 19(5), 521–540. Deeks, J. (1976) The Small Firm Owner-Manager: Entrepreneurial Behaviour and Management Practice. New York, Praeger. Demeter, K. (2003) Manufacturing strategy and competitiveness. International Journal of Production Economics 8182, 205–213. Dow, D., Samson, D. and Ford, S. (1999) Exploding the myth: do all quality management practices contribute to superior quality performance? Production and Operations Management 8(1), 1–27. Engel, C. (2002) China: threat or salvation? Furniture/Today. Ferdows, K. and De Meyer, A. (1990) Lasting improvements in manufacturing performance: in search of a new theory. Journal of Operations Management 9(2), 168–184. Forrester, P.L. and Hassard, J.S. (2000) Managing factory operations in China: empirical evidence on the integration of design and production. International Journal of Manufacturing Technology and Management 1(4-5), 412–427. Hair, J. Jr, Anderson, R., Tatham, R. and Black, W. (1998) Multivariate Data Analysis. Prentice-Hall, Englewood Cliffs, NJ. Li, J.T., Tsui, A.S. and Weldon, E. (2000) Management and Organizations in the Chinese Context. MacMillan Press, Basingstoke. Li, L. (2000) An analysis of sources of competitiveness and performance of Chinese manufacturers. International Journal of Operations and Production Management 20(3), 299–315. Moorman, C.W. and Montgomery, C.A. (1998) The Household Furniture Industry in 1986. Pyke, D.F., Farley, J. and Robb, D.J. (2002) Manufacturing

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technology and operations in China: a survey of Stateowned enterprises, private firms, joint ventures and wholly-owned subsidiaries. European Management Journal 20(4), 356–375. Robb, D.J. and Xie, B. (2001) A survey of manufacturing strategies in China-based enterprises. International Journal of Production Economics 72(2), 181–199. Shen, D. and Cao, M. (1999) Furniture Sales. Industry Sector Analysis, 1–29. Skinner, W. and Rogers, D.C.D. (1968) Manufacturing Policy in the Furniture Industry: A Casebook of Major Production Problems. R.D. Irwin, Homewood, IL. Slaughter, P. (2001) U.S. factories move to counter China. Furniture/Today 25(9), 50. Sun, H., Tian, Y. and Cui, J. (2001) Evaluating advanced manufacturing technologies in Chinese state-owned enterprises: A survey and case studies. International Journal of Advanced Manufacturing Technology 18(7), 528–536. Sun, X. and Bean, R. (2001) China, Peoples Republic of Solid Wood Products Furniture Industry Report 2001. Global Agriculture Information Network Report. US Census Bureau (2002) Statistics for Industry Groups and Industries: 2000. US Department of Commerce, Vickery, S.K., Droge, C. and Markland, R.E. (1993) Production

competence and business strategy: do they affect business performance? Decision Sciences 24(2), 435–455. Vickery, S.K., Droge, C. and Markland, R.E. (1994) Strategic production competence: convergent, discriminant and predictive validity. Production and Operations Management 3(4), 308–318. Vickery, S.K., Droge, C. and Markland, R.E. (1997) Dimensions of manufacturing strength in the furniture industry. Journal of Operations Management 15(4), 317–330. Volpe, A. (2002) Markets: China’s high performance. World Furniture: International Markets Review 16, 12–13. Wille, S. and Adams, M. (2001) Outside the comfort zone. ITTO report 11. Wu, H.X. (2001) China’s comparative labor productivity performance in manufacturing 1952–1997: catching up or falling behind? China Economic Review 12, 162–189. Yang, D.T. (2002) What has caused regional inequality in China? China Economic Review 13(4), 331–334. Zhang, L. (2003) Chinese furniture export set to soar in 2003. China Daily, 10 February, p. 5. Zhou, Y. and Chuah, K.B. (2002) Computer-integrated manufacturing in China: a report of industrial field surveys. International Journal of Operations and Production Management 22(3), 271–288.

DAVID ROBB, Department of Management Science and Information Systems, University of Auckland Business School, Private Bag 92019, Auckland, New Zealand. E-mail: [email protected]

BIN XIE, Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing 100083, PR China. Email: xieb@e./tsinghua.edu.cn

David Robb is Associate Professor of Operations Management and Postgraduate Co-ordinator at the University of Auckland. His teaching and research interests are in supply chain management and operations strategy with publicaions in numerous management journals.

Bin Xie is Associate Professor of Operations Management at Tsinghua University. His teaching and research interests include operations management, supply chain management and quality management.

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