In an open innovation environment, it is meaningful for manufacturing enterprises targeting global markets to integrate qualified innovation resources. In this paper, the linkage between product modularity and open innovation is first discussed, revealing a role that modular product architecture plays in linking enterprises’ innovation requirements and innovation resources as external innovation inputs. Next, indices for evaluating external innovation resources are developed. An evaluation method based on fuzzy distance is then proposed, which is intended to select optimal resources for the core modules of modular product architecture. A modular product of Haier Group is used as a typical case to verify the proposed method. Consistent evaluation results of innovation resources are achieved for different decision-making attitudes. Another finding regarding the case enterprise is that the resource management mechanisms it employs lead to a win-win cooperative relationship with its partners.
As the industrial chain is growing more open than ever, the traditional vertical integration model where a product is manufactured by a single enterprise independently is no longer the trend. The significance of an open innovation system for corporate technical innovations is becoming unquestionably evident [
In the open innovation theory of Chesbrough [
Schmitt pointed out that, in an interdependent relationship between supply and demand sides, the establishment of a long-term mechanism contributes substantially to resource sharing and continued coordination [
In addition, with the development of economic globalization, large manufacturing enterprises involved in global markets pursue a more professional division of labor and coordination. Complicated products are decomposed into multiple functional modules, while external innovation resources such as design houses and modular suppliers are integrated into corresponding stages of product design, procurement, manufacturing, and service with the assistance of standardized module interfaces, thus forming a modular innovation network. Based on the above discussion, this study explores an effective method, aiming at leveraging innovation resources for modular products of large manufacturing enterprises under open innovation scenarios. The remainder of this article is organized as follows. Section
Modularity refers to a process where a complicated system is broken down into a number of modules with standard interfaces [
Linkage between innovation resources and modular product architecture.
In an open innovation environment driven by product modularity, the supply and demand sides, as innovation stakeholders, are able to rapidly align their new innovation tasks and requirements with each other based on “transparent design rules” of modules. Meanwhile, they can eliminate barriers at innovation interfaces possibly resulting from information asymmetries and subjective differences. This in turn leads to optimal quantity and quality of external resources as well as reduced cost of communication and coordination.
For enterprises implementing product modularity, there are multiple possible forms of collaboration with external resources like “university-enterprise”, “research institute-enterprise”, and “supplier-enterprise”. Such collaboration is expected to promote enterprise innovation competitiveness through the interaction of elements such as knowledge and technology [
Scholars have demonstrated that basic qualification, performance, and availability are critical for the evaluation and selection of external resources [
According to our survey and observation, the evaluation and selection of external resources by an enterprise implementing product modularity are not merely based on technology innovation and organization management aspects. The abilities of external resources to improve the performance of the module value chain need to be considered as well. Hence, this paper defines evaluation indices for external innovation resources, including basic qualification and reputation (P1), technology innovation ability (P2), complementarity (P3), ability to perform a contract (P4), integration difficulty (P5), management and control difficulty (P6) (P5 describes the difficulty to integrate external resources into open innovation activities, while P6 is a measure of the difficulty for an enterprise to coordinate with resources in a cooperative innovation project), cost performance (P7), ability to provide value-added services (P8), and ability to manage and control subresources (P9).
Considering the nature of the evaluation and selection of strategic innovation resources for core modules (systems), a fuzzy method is usually adopted for ranking comprehensive performances of candidate resources. However, there exist certain shortcomings of traditional fuzzy ranking methods [
The fuzzy linguistics made by evaluation experts is converted to triangular fuzzy numbers. For instance, five levels of fuzzy linguistics, i.e., very low (VL), low (L), moderate (M), high (H), and very high (VH), can be employed to describe the importance of different indices (Figure
Membership functions for ranking indices.
Membership functions for ranking resources.
It is assumed that there are
A combination of significance values assigned by different experts to the index gives the fuzzy weight factor
Since the above evaluation assignment process for external module innovation resources still leads to fuzzy numbers, it is not yet possible to determine the final ranking of module innovation resources. A fuzzy distance measurement method is, therefore, adopted for further comparison of the fuzzy numbers [
Following the theory of fuzzy distance measurement method [
Hence,
Different
Based on the above analysis, the following characteristics of the proposed innovation resource evaluation method based on fuzzy distance measurement can be observed. First, compared with traditional evaluation and ranking methods, e.g., the analytic hierarchy process (AHP), the calculation process of the proposed method is simpler and visualized. Second, various
Haier Group, a typical Chinese manufacturing enterprise evolving rapidly in the time of Reform and Opening, is selected for a case study to verify the proposed method. There are four major reasons for selecting Haier as the case sample. (1) Haier is now a leader in the Chinese home appliance industry, and also one of the large pioneering Chinese enterprises that have strategically built their worldwide R&D, production, marketing, and sales networks. (2) Despite its rapid development in recent decades, Haier realizes that it has become impossible to meet ever-increasing product design complexity and customer demands by relying only on its own R&D capabilities. Consequently, Haier adopts an open innovation strategy to exploit innovation potential via external partners. Meanwhile, Haier has established an open innovation platform, Haier Open Partnership Ecosystem (HOPE), on which it interacts with external resources to come up with innovative solutions and fulfill global users’ requirements. (3) In 2011, Haier switched from traditional component design to a product modularity model for its large home appliance lines. Modularity has, thus, become a key pillar for the company to leverage product innovations and pursue business model transformations.
The Chinese air-conditioning industry has entered a highly competitive stage in recent years. On the one hand, the tasks of energy conservation and emission reduction are demanding, and real estate regulation and control policies suppress further expansion of the industry. With the release of energy-saving product subsidy policies, the production cost of air conditioners is gradually rising. On the other hand, too many homogeneous Chinese air-conditioning products lacking technological innovation are competing more intensely than before in the market. Realizing that the in-house R&D force alone would no longer completely meet global customer needs, Haier CEO Zhang Ruimin calls for a move from a closed organization to an open one.
Our analysis involves a high-end air conditioner product (T-AC) of Haier Group that features a modular design. This product is a response to a survey of over 600,000 consumers. It is mainly intended to address issues or needs related to air-conditioning diseases, cold air, natural air, and remote control.
The modular product architecture of T-AC was created using the MFD methodology given by Ericsson and Erixon [
The modular product architecture of T-AC.
Being regarded as one core module (system), the air-supplying module system is closely related to air output, air supply distance, and air supply range of T-AC (Figure
Composition of the air-supplying module system of T-AC.
With the evaluation method described in Section
Fuzzy evaluation matrix of evaluation indices.
Index | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Expert | E1 | VH (0.7, 1.0, 1.0) | VH (0.7, 1.0, 1.0) | VL (0, 0, 0.3) | ||||||
E2 | VH (0.7, 1.0, 1.0) | |||||||||
E3 | VH (0.7, 1.0, 1.0) | VH (0.7, 1.0, 1.0) | VH (0.7, 1.0, 1.0) | VL (0, 0, 0.3) | ||||||
Average | (0.57, 0.8, 1.0) | (0.63, 0.9, 1.0) | (0.47, 0.73, 0.93) | (0.13, 0.43, 0.7) | (0.23, 0.5, 0.77) | (0.63, 0.9, 1.0) | (0.3, 0.57, 0.87) | (0.13, 0.43, 0.7) | (0, 0.1, 0.37) |
Seven levels of fuzzy language, i.e., very good (VG), good (G), relatively good (RG), moderate (M), relatively poor (RP), poor (P), and very poor (VP), are then used by three experts to evaluate each innovation resource for different indices. The fuzzy evaluation matrix of external modular resources based on the evaluation by three experts is given in Table
Fuzzy evaluation matrix of module innovation resources.
Resources | Indices | ||||||||
---|---|---|---|---|---|---|---|---|---|
P1 | P2 | P3 | P4 | P5 | P6 | P7 | P8 | P9 | |
M1 | RP, RP, | VG, GG, VG | RG, | RG, VG, RG | RG, VG, | VG, | |||
M2 | RG, | VP, VP, | RG, VG, VG | ||||||
M3 | VG, VG, | RP, | VG, VG, | VG, RG, VG | RG, | ||||
M4 | RG, | RG, | RG, | RG, | |||||
M5 | VP, VP, | RG, | RP, RP, VP | RG, RG, | RG, | VG, VG, VG | |||
M6 | RG, | VP, | RG, RG, | ||||||
M7 | RG, | RG, RG, | VP, | RG, | RP, RP, RP | ||||
M8 | RP, | RG, VG, | RG, | ||||||
M9 | RG, | RG, | VG, |
The fuzzy rating values of all module innovation resources can be derived from (
By selecting
Evaluation of module innovation resources using the distance measurement method.
Dmax, | M1 | M2 | M3 | M4 | M5 | M6 | M7 | M8 | M9 | |
4.1117 | 3.8432 | 4.4135 | 3.9998 | 2.3915 | 2.8137 | 2.9611 | 3.6627 | 3.6723 | ||
3.0425 | 3.28148 | 2.7797 | 3.1736 | 4.7060 | 4.2674 | 4.1024 | 3.4875 | 3.4715 | ||
4.0819 | 3.7919 | 4.3918 | 3.9654 | 2.3414 | 2.7512 | 2.9224 | 3.6277 | 3.6149 | ||
3.0214 | 3.2559 | 2.7414 | 3.1539 | 4.7264 | 4.3057 | 4.1215 | 3.4757 | 3.4825 | ||
4.0635 | 3.7882 | 4.3791 | 3.9442 | 2.3092 | 2.7102 | 2.8974 | 3.6059 | 3.5907 | ||
3.0140 | 3.2745 | 2.7184 | 3.1430 | 4.7408 | 4.3319 | 4.1349 | 3.4696 | 3.4498 | ||
4.0425 | 3.7633 | 4.3654 | 3.9200 | 2.2705 | 2.6600 | 2.8670 | 3.2810 | 3.5529 | ||
3.0000 | 3.2757 | 2.6805 | 3.1281 | 4.7719 | 4.3866 | 4.1636 | 3.7629 | 3.4977 |
Visualization of the evaluation of module innovation resources at
Visualization of the evaluation of module innovation resources at
Visualization of the evaluation of module innovation resources at
Visualization of the evaluation of module innovation resources at
During the cooperation with a selected strategic supplier (a bid winner), Haier implemented resource management mechanisms. First, a contract-binding mechanism was used to regulate the rights and responsibilities of both parties, leading to well-defined delivery times, prices, and supporting services for innovative air supply module services. Second, a dynamic optimization mechanism was used to keep the strategic supplier competitive, driving its capability upgrading. Third, Haier focused on a practical incentive mechanism called “big resources in exchange for big resources.” For example, large-volume module purchase orders were placed to stimulate adequate innovation inputs from the strategic supplier during its cooperation with Haier.
Driven by these mechanisms, the open innovation network was operated in a self-organized way. Following the implementation of its corporate transition strategy in recent years, Haier has concluded that it must rely on such operation mechanisms to improve the quality and performance of innovation resources so as to boost open innovation.
In response to Haier’s technology requirements, a number of global resources have been included in collaborative innovation, and they are evaluated under equal competition and access conditions. On this basis, a reasonable innovative solution may be proposed by any qualified innovation source in accordance with modular requirements. Previously, the majority of external resources of Haier conditioners were based in China. Starting from 2000, Haier has carried out the innovation strategy of “taking the world as our R&D center”. This has driven the resource integration process of Haier toward globalization. Under the right circumstances, networking tools allow resources in other countries/regions to participate in the fair bidding procedures of Haier and to interact with the company easily. On the other hand, due to the function of the innovation resource filtering mechanism, the innovation resources in the circles of collaborative innovation have to continuously enhance their capabilities and adjust their service strategies based on the dynamic needs of Haier’s T-AC. In addition, the ability to secure qualified innovation resources has been included in the assessment of Key Performance Indexes (KPIs) of relevant employees.
In order to manage innovation resources within a controllable scope, their behaviors are well regulated so as to avoid possible risks during collaborative innovation. Specifically, strict clauses relating to participation qualifications are defined in contracts between Haier and innovation resources, thus eliminating the possibility of a deliberate withdrawal from cooperation and misconduct. Through the use of incentive compatibility measures, innovation resources are able to tap their potential effectively for the purpose of profit-sharing. For example, a Chinese Southern manufacturer Sunwill was originally only responsible for supplying the fan module of T-AC, but later, it became the designer and supplier of the whole air supply module system thanks to Haier’s incentive compatibility mechanism. A purchase order of more than 100,000 units (module systems) per quarter was given to Sunwill together with a contract commission for at least two years. As a result, Sunwill now manages other module suppliers of the air supply module system, including those offering motors and wind deflectors.
The core modules (air supply module system, evaporator module system, etc.) of the modular product architecture of T-AC were developed in the headquarters’ R&D center of Haier. At this center, Haier utilizes its R&D capacities and interacts with innovation resources to strengthen its innovation competence. With high-qualification requirements for standard modules among such innovation resources, resource optimization frequency is low. Haier seeks to establish a strategic cooperation relationship with a number of excellent selected candidates. Individualized modules/systems (formaldehyde elimination module, double-way fresh air module, etc.) are developed in areas close to target markets. The benefits include more synergies with innovation resources, lower cost, and higher service efficiency. To cater for varying user needs, the optimization frequency of the innovation resources in these areas is relatively high.
To fill the gaps in existing studies, the relationship between modularity and open innovation is first analyzed. Module innovation resources in an open environment are then grouped. In order to select qualified innovation resources for core modules of modular product architecture, nine evaluation indices are constructed in this study. Next, a fuzzy distance measurement method is presented to compare fuzzy numbers and decide which innovation resource is optimal. By using a case study of one of Haier Group’s modular products, consistent evaluation and selection results are achieved for different decision-making attitudes, proving that the method proposed in this paper is robust.
Based on the case study of the Haier Group, modular product architecture plays a vital role in linking the enterprise’s innovation requirements with external innovation resources. Meanwhile, it is discovered that strategic suppliers not only collaborate with Haier in terms of procurement but also actively get involved in core module system innovation. Through the implementation of strategic supplier management mechanisms such as contract binding, dynamic optimization, and big resources in exchange for big resources, a strategic supplier is able to improve its capabilities continuously, thus engaging in open innovation with the company in a win-win context.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that they have no conflicts of interest.
This research was supported by the Chinese National Funding of Social Sciences (19BGL045), Liaoning Public Welfare Research Project (2020JH4/10100023), and the Project is sponsored by Liaoning BaiQianWan Talents Program (2020921084). The authors herewith show appreciation for their support.