19th International Conference on Production Research
EXPLORING THE CONGRUENCE OF FUNCTIONAL STRATEGIES AND
CUSTOMER INTEGRATION STRATEGY
Xiang Zhang1
Rongqiu Chen2
Yubo Ma3
(1School of Management and Economics, Beijing Institute of Technology, Beijing, China, 100081, and
School of Management, Huazhong University of Science and Technology, Wuhan, China, 430074
2, 3School of Management, Huazhong University of Science and Technology, Wuhan, China, 430074)
Abstract
To better cope with the future of competition, more and more firms tend to integrate customers into value
co-creation process that requires customer-firm interaction. Also, mass customization can occur at various
points along the value chain, ranging from the simple standardized build-to-to-order product, up to fully
customized design one, which requires the coordination of the functional strategies. Although customer
integration and functional strategies coordination are critical to a successful customerization, few studies
explore the congruence between these two aspects. This paper is an attempt towards this direction. The
purpose of this paper is to empirically investigate the associations between functional strategies and
customer interaction as well as their impacts on firm’s competitive priorities. A multi-method approach was
used to collect the data at the Chinese manufacturing industry. Based on the analysis, this study makes the
contributions in three aspects: First, the study provides empirical evidence to support the argument of
customer integration in operations. Second, this study found that functional strategies significantly
associated with customer interaction. Third, the congruence of both functional strategies coordination and
customer interaction impacts significantly on firm’s competitive priorities. Firms with aligned customer
integration strategy and functional strategies can achieve significantly better competitive priorities in cost,
speed, flexibility and service. The empirical evidence of the paper deepens the understanding of value
co-creation system and enables the practitioners to support the promise of customerization by integrating
customer.
Key words:
mass customization customer integration
1.
value co-creation system
INTRODUCTION
To better cope with the future of competition, more and
more firms tend to integrate customers into value
co-creation process that requires customer-firm
interaction. Also, mass customization can occur at various
points along the value chain, ranging from the simple
standardized build-to-to-order product, up to fully
customized design one, which requires the coordination of
the functional strategies. Although customer integration
and functional strategies coordination are critical to a
successful customerization, few studies explore the
congruence between these two aspects. This paper is an
attempt towards this direction. The purpose of this paper
is to empirically investigate the associations between
functional strategies and customer interaction as well as
their impacts on firm’s competitive priorities.
2.
LITERATURE REVIEW
To satisfy the individual demand of customers, firms
inevitably need to interact with customers during the
product customization, which in turn involve customers
into firm’s operations. Meaningful participation is a
systematical process, not simply the application of
isolated, one-off participation activities or events [1].
Companies may co-create value with customers alone the
value-adding chain of customization, from the
co-development of new products [2], to production,
assembly, distribution, retail, after sales service and usage
[3][4][5], “…. (most of the) activities and processes which
used to be seen as the domain of the companies” [6].
Customer becomes a co-producer, resulting in a system of
value co-creation that requires company-customer
interaction and adaptation for attaining added value to
competitive priorities
both sides [7][8]. Moreover, the degree of customer
participation is critical to determine the degree of
uniqueness and customization of final product [5][9][10].
Thus the participation of customers becomes critical to the
success of customization.
Mass customization goes beyond the traditional boarder
of functional areas, requiring the coordination of
manufacturing and marketing strategies [11][12]. Based
on the manufacturing strategy and product life cycle theory,
Hayes and Wheelwright propose the product-process
matrix (PPM), suggesting that product plans and process
choice should be linked together in order to gain
competitive advantages [13][14]. In the continuous
spectrum of operations from mass production to
customerization, companies operating on or close to the
diagonal of PPM outperform those with extreme
off-diagonal positions [13][14].
Product-process matrix provides a way to analyze the
strategic match of functional strategies and is verified by a
number of researchers. Using empirical data, Safizadeh et
al. show that firms with matched functional strategies can
achieve better competitiveness, thus supporting the PPM
[15]. However, based on the case study of US power tool
industry, McDermott et al. found that PPM, although
captured the many aspects of strategic manufacturing
environment in 1970s and 1980s, fails to explain the
articulation and formulation of operations strategy from
1990s onwards[16]. With changes in competition,
technology and customer demand, more researchers tend
to suggest a necessary extension to PPM to reflect and
explain new changes [17][18]. For example, the B2C-PPM
[19].
Customerization is one of new developments in
operations strategy and is regarded as the next revolution
of mass customization [12]. In contrast to mass
customization, customerization take customers as an
integral part of firm’s value co-creation system. To
implement customerization, firms need customer
participation during value co-creation where customers
are seen as a new source of competitive advantages
[12][20].
Customers do not determine corporate strategy. However,
their values and expectations for the company’s products
and services are influential. Although the present research
in customer integration strategies sheds lights on the
importance of customer co-creation strategy, few analyses
have tested its link to functional strategies. As customer
participation for value co-creation is the future of
competition [20], to verify the empirical link helps firms
focus on the key issues in building order-winning
strategies. In addition, the congruence of customer
strategy and functional strategies is one of the key issues
concerned by researchers regarding customerization [12].
Although intuitively appealing, the impact of such
congruence on firm’s competitive advantages has
received little attention, hence remaining unclear. Also, the
disagreement of PPM warrants a further examination,
especially in the emerging market. Therefore, this study is
a step towards this direction and answers the following
questions:
(1) Does the PPM fit for Chinese manufacturing industry?
(2) Does the functional strategies correspond to customer
participation strategy?
(3) Do companies with coordinated customer strategy and
functional strategies operate better than those without
coordination?
3.
RESEARCH DESIGN AND METHODOLOGIES
This study is exploratory in nature and is part of a larger
research program. As a convenient sample, 150
manufacturing companies located in the mid-China were
randomly selected. A multi-method approach (mainly
including survey and follow-up interviews) was used to
collect the data at the Chinese manufacturing industry.
The pilot study was organized among senior managers of
18 companies during their attendance as EMBA students
at the authors’ university. All respondents have job titles of
Table 1
Chairman, VP Operation, Manufacturing Manager, or
Marketing Manager. 15 valid questionnaires were returned.
Items in the pilot study were firstly purified by using
corrected item-total correlation with all results above 0.50
[21]. Secondly, exploratory factor analysis (EFA) using
varimax rotation was executed to assess the
unidimensionality of the scales. Factor loads above 0.60
and alpha values over 0.7 were considered acceptable
[22].
In the large-scale survey, the respondents were either
called and then sent through E-mail or directly sent
through E-mail. 8 deliveries failed due to the changed
address. The total 84 valid questionnaires returned,
representing a responding rate of 56%. To further ensure
the validity of the survey, some items were reversely
coded. In addition, this study replicated the survey from
the second respondent in 15 companies. The intra-class
correlation was calculated to assess the inter-rater
agreement [23]. The minimum intra-class correlation
coefficients of three constructs were above 85%
(significant at 0.01 level), indicating an acceptable
inter-rater agreement.
The targeted respondents had the job titles of corporate
president (7.2%), department manager (54.2%), section
chief (22.7%), group leader (2.6%) and others (13.3%).
84.1% of the respondents have management positions
that may help provide more reliable information. The
demographic information is shown in Table 1.
The response/non-response bias was calculated by
comparing earlier returned questionnaire to late returned
ones in terms of people, assets and sales volume,
because the original list did not provide the needed
demographic information. No significant differences were
found between the two groups using 2 statistics and
p<0.05.
Follow-up interviews with 15 selected managers at
different companies were conducted after large-scale
sampling. Mutli-method coupled with great attention to
selected high-ranking officers helps further control
common method bias and increase the reliability of
evaluation data [24] and is consistent with the triangulation
data gathering approach [25].
The demographic information of the sample
Frequency Percentage
Industry
Telecommunication and related equipment
Steel and related manufacturing
Electronic and electric equipment
Chemical and related fabrication
Common manufacturing
Transportation manufacturing
Miscellaneous manufacturing
5
7
15
27
15
9
6
5.95%
8.33%
17.86%
32.14%
17.86%
10.71%
7.14%
Assets
<10 Million RMB
10～50 Million RMB
50～100 Million RMB
100～500 Million RMB
500～1000 Million RMB
1～5 billion RMB
>50 billion RMB
unspecified
5
11
15
20
8
14
7
4
5.95%
13.10%
17.86%
23.81%
9.52%
16.67%
8.33%
4.76%
People
≤499
17
20.24%
19th International Conference on Production Research
18
19
15
12
3
84
500～1499
1500～3999
4000~9999
≥10000
unspecified
Total
4.
ANALYSIS AND RESULTS
4.1 Item Generation and Purification
All items were initially derived from relevant literature. The
items that measure the product and process strategy were
adopted from [15]. The respondents were asked to select
the most appropriate description about their companies.
Items of customer participation were structured from [26],
[27] and [28]. The respondents were asked to select the
most appropriate description about their companies where
“1= high customer participation, 2=medium participation,
3=low participation and 4=no participation.” Competitive
priorities commonly include cost, speed, quality and
flexibility. However, service has also become one of the
important competitive priorities [29][30] since Fuchs
proposes the arrival of service economy [31]. Therefore,
service was included in this study and was generated from
[29] and [31]. Items of cost, speed, quality and flexibility
Table 2
4.2
The Test of the Fit of PPM
According to Safizadeh et al. (p1581), cells to the
immediate right or left of the main diagonal to be classified
“on-diagonal” [15]. The results is shown in Table 3. 50
Customization
Process
job-shop
batch production
Assembly Line
Continuous Line
Sum
Customized
product
5 （6.02%）
7 （8.43%）
5 （6.02%）
17
were based on [24]. The respondents were asked to make
the comparison with their major competitors, where “1=
much lower than the competitor” and “5=much higher than
the competitor.” Corresponding to the research emphasis,
the unit of analysis was directed at organizational level.
Exploratory factor analysis with varimax rotation was
conducted on items. Items with factor loadings below 0.60
or with cross-loadings above 0.1 were eliminated. All items
were factor analyzed together. The results are shown in
Table 2. Without specifying the number, five factors of
competitive priorities with Eigen-values greater than 1
emerged. All items were loaded on the five factors as
theoretically hypothesized, with all loadings above 0.6. The
results of factor analysis were consistent with these prior
identified item groupings, which provide evidence of
factorial validity [32]. The alpha value of each factor was
above 0.80, indicating a good reliability [33].
Results of factor analysis
Items
Quality Speed
Product quality consistency
.830
Product performance
.754
Product quality perceived by the customers .848
Number of features on the products
.690
Fast delivery
.854
Dependability on delivery
.853
Shorten the delivery time
.844
Product price
Product cost
Ability to make design changes
Adjust process to respond to volume swings
Adjust capability rapidly
The ability of new service creation
Providing unique service experience
Providing multi-kind service
Providing customized value-adding service
Table 3
21.43%
22.62%
17.86%
14.29%
3.57%
100.00%
Cost Flexibility
Service
.801
.934
.886
.833
.796
.878
.821
.820
.866
Mean
3.41
3.35
3.45
3.49
3.27
3.47
3.29
3.37
3.22
3.30
3.06
3.35
3.13
2.99
2.98
3.08
SD
0.89
0.89
0.84
0.76
1.00
1.00
0.95
0.95
1.05
1.01
1.06
0.99
1.09
1.01
0.98
1.00
 value
0.8588
0.9023
0.8605
0.9223
firms were on-diagonal (60.24% of the total firms sampled)
while other 33 firms were off-diagonal (39.76% of the total
firms sampled).
The illustration of sample companies on PPM
Both standard
Standard
Standard
Standard
Sum
product and
product with
product with product with no
options can be options modified standard
options
modified to order
to order
options
6
1 （1.20%）
5 （6.02%）
12 （14.57%） 4 （4.81%） 6 （7.22%） 34
25
2 （2.41%）
6 （7.22%） 7 （8.43%） 5 （6.02%）
4 （4.81%） 1 （1.20%） 14 （16.87%） 19
12
26
7
22
84
To further analyze the fit of the PPM, the data were
analyzed using partial correlation methods with two-tailed
test of significance. Industry, people and assets were
controlled to account for the possible effects on the results.
The total partial correlation coefficient between product
and process strategy was -0.4651 (significant at 0.000).
The correlation coefficients of on-diagonal companies
were -0.941 (p=0.000) for product-process and -0.681
(p=0.000) for batch-process. However, the correlation
coefficients of off-diagonal companies were 0.124
(p=0.493) for product-process and 0.242 (p=0.175) for
batch-process. The results reveal that the off-diagonal
sample deviate the total correlation coefficients. To test
the impact of strategic fit on firms performance, data were
analyzed using ANOVA methods. The results show that
on-diagonal companies achieved better performance on
cost (p=0.020), delivery speed (p=0.044) and service
(p=0.095) than those of off-diagonal companies.
In general, the above results provide support evidences
that PPM fits for the analysis of local manufacturing
Table 4
environment.
4.3
The Congruence between functional strategies
and customer interaction
To examine the congruence, this study adopted partial
correlation analysis, controlling industry, people and
assets. The results are shown in Table 4.
The analysis of congruence between functional strategies and customer interaction
Product customization
On-diagonal Product customization
1.000
n=50
Volume
-.682***
Dominant process
-.941***
Interaction
-.332*
Off-diagonal Product customization
1.000
n=33
Volume
-.253
Dominant process
.124
Interaction
-.639***
*** Correlation is significant at the 0.000 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
The results of Table 4 show that the degree of customer
participation in on-diagonal companies is significantly
associate with the degree of product customization
(r=-0.332，p=0.019), batch size (r=0.374，p=0.007) and
process strategy (r=0.340 ， p=0.016). In contrast in
off-diagonal companies, the degree of customer
participation is only associated with the degree of product
customization (r=-0.639，p=0.000), with no significance
existing with batch size (r=0.117，p=0.517) and process
strategy (r=-0.262，p=0.141). These results reveal that the
on-diagonal firms can better coordinate the functional
strategies and customers interaction during their
Table 5
Volume
Dominant process
1.000
.681***
.374**
1.000
.340*
1.000
.242
.117
1.000
-.262
Mean
2.58
3.40
2.76
2.46
2.94
3.36
2.52
2.27
SD
1.28
1.16
1.00
0.93
1.78
1.06
0.71
0.94
operations while off-diagonal firms are not only lack of
coordination in functional strategies but also disconnected
customer from their operations strategies.
4.4
The impacts of customer strategies and
functional strategies on firms performances
To examine the impacts of congruence on firms
performance, this study adopted multivariate analysis of
variance using performance as dependent variables.
Firms were classified by the degree of customer
interaction (high-low interaction) and the distance to
diagonal (far-near diagonal), which were used as fixed
factors. The results are shown in Table 5.
The impacts of customer interaction and functional strategies on firms performances
On-diagonal
Customer interaction
On-diagonal and
customer interaction
variables
cost
quality
speed
flex.
service
cost
quality
speed
flex.
service
cost
quality
speed
flex.
service
The results of Table 5 show that on-diagonal companies
are better in cost (F=3.244, p=0.076), delivery speed
(F=3.113, p=0.082) and service（F=3.156, p=0.080）than
those of off-diagonal companies. Also, firms with higher
degree of customer interaction have significant difference
in service performance (F=9.863, p=0.002). The
interaction effects of high-low interaction and far-near the
diagonal are significant in flexibility (F=3.289, p=0.074)
and
service
(F=3.212,p=0.077).
These
results
demonstrate that companies with coordinated customer
strategy and functional strategies operate better in cost,
service and flexibility than those without coordination.
Both the customer interaction and functional strategies
impact significantly on firms performances.
MS
3.135
.308
3.094
.107
2.629
.119
.926
.316
.633
8.215
1.555
0.063
.302
3.176
2.675
5.
F值
3.244
.314
3.113
.111
3.156
.124
.945
.318
.656
9.863
1.609
.065
.304
3.289
3.212
Sig.
.076
.577
.082
.740
.080
.726
.334
.574
.421
.002
.208
.800
.583
.074
.077
IMPLICATIONS AND CONCLUSIONS
The results of this study show that the degree of customer
interaction has significant association with functional
strategies. Firms with better congruence may achieve
better performance from the congruence between
customer interaction and matched functional strategies
than those of firms that do not. These competitive
advantages include better service, cost saving and higher
flexibility. This results confirm that customers as
co-producer is an integral part of value co-creation system,
thus supporting the logic of customerization. Although the
findings of this study can not be directly compared due to
the lack of empirical literature, this study may alert firms
should strategically determine the involvement of
customer during operations of customization.
Although the results are encouraging and supporting, the
19th International Conference on Production Research
sample was not truly representative of the national
population of manufacturing industry. Specifically, the
sample tended to be larger in sales revenue or people and
a significantly higher proportion of firms located in the
middle of China. Therefore, the interpretation to other
markets should be cautious. However for an exploratory
study, none of these problems was considered to
seriously bias the research results.
Based on the analysis, this study makes the contributions
in three aspects: First, the study provides empirical
evidence to support the argument of customer integration
in operations. Second, this study found that functional
strategies significantly associated with customer
interaction. Third, the congruence of both functional
strategies coordination and customer interaction impacts
significantly on firm’s competitive priorities. Firms with
aligned customer integration strategy and functional
strategies can achieve significantly better competitive
priorities in cost, speed, flexibility and service. The
empirical evidence of the paper deepens the
understanding of value co-creation system and enables
the practitioners to support the promise of customerization
by integrating customer.
ACKNOWLEDGEMENTS
This study is supported by National Natural Science
Foundation of China (No.70332001).
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