大規模定制中消費偏好測量準確度對定製品品質的影響研究

Examining the Effect of Measurement Accuracy of Consumer Preference on Product Quality in Mass Customization

Student thesis: Doctoral Thesis

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Awarding Institution
Supervisors/Advisors
  • Zhilin YANG (Supervisor)
  • Mingjie Rui (External person) (External Supervisor)
Award date26 Jun 2020

Abstract

進入21世紀,現代企業所處的環境正在發生前所未有的巨大變化。客戶需求日益個性化、多樣化,原有的以規模經濟優勢生產大批量標準化產品的大規模生產模式已越來越無法滿足企業競爭和市場需要。隨著互聯網信息科技、智能製造技術的發展,一種面向未來的產業範式——大規模定制應運而生。大規模定制將大規模生產和定制生產有機結合,目的在於解決大規模標準化生產與消費者個性化需求之間的根本性衝突,以大規模生產的低成本和高效率生產個性化定制產品。大規模定制已成為理論界和企業界公認的21世紀的主流生產模式。 越多越多的企業在大規模定制實踐中遇到了各種各樣尚待解決的問題,這些問題成為學術研究的重要課題源泉。

本研究即是基於大規模定制中的以下三個問題展開研究:
首先,大規模定制是以顧客為中心的訂單驅動型生產模式。在生產前,企業需要盡可能詳細了解顧客需求,測量消費者對產品的偏好,測量是否準確直接關係到企業能否成功實施大規模定制。那麼,消費偏好測量是如何影響到最終的定製品品質的?其內在作用機制是什麼?其次,從生產過程來看,個性化訂單經過智能製造工廠的柔性生產,完成定製品生產並送達客戶手中。測量是訂單生成的過程,生產是訂單實現的過程。那麼,生產製造過程在消費偏好測量和定製品品質之間的作用機制是什麼?最後,消費偏好測量需要顧客的參與,不同的顧客參與程度在定制過程中起到了什麼作用?

基於以上問題,本論文以大規模定制理論和模塊化理論為基礎,結合消費偏好測量理論和顧客參與理論,以企業為研究層面,從智能製造視角出發,研究消費偏好測量對定製品品質的影響機制,同時引入生產製造的柔性程度和顧客參與這兩個構念,分別探討這二者在其中的中介作用和調節作用,在此基礎上提出研究假設,並且構建了消費偏好測量準確度、生產製造的柔性程度、定製品品質和顧客參與這四個變量的結構方程模型。在實證研究部分,本文通過實地調研和問卷調查進行了數據收集,採用SPSS進行數據統計分析,對理論模型中各變量之間的關係進行了驗證。

本論文得出的主要研究結論是:
第一,消費偏好測量準確度對定製品品質具有顯著的正向影響作用,即消費偏好測量越準確,最終的產品品質越高。對實踐的啟示是,企業需要通過更合理的產品模塊化設計最大化產品的外部多樣性,盡可能涵蓋更多的消費者需求,為測量的外部化形式提供充足的隱性內容,為提高消費偏好測量準確度創造更多的基礎條件,從而最終提升產品品質。

第二,生產製造的柔性程度在消費偏好測量準確度和定製品品質之間起到中介作用。 模塊化理論將模塊化分為模塊分解和模塊集成兩個過程,本研究中的消費偏好測量是模塊分解過程,生產製造是模塊集成過程,模塊分解正向影響模塊集成並通過模塊集成最終影響到產品品質,只有當模塊的分解與集成相互匹配,最終產品品質方可得以提升。對實踐的啟示是,企業對模塊化產品設計的完善需以生產能力為基礎,因為個性化訂單是通過生產製造實現的,即使消費偏好測量再準確,若生產製造的柔性程度不匹配,也無法提高產品品質,反而可能對品質起到負向作用。

第三,顧客參與在消費偏好測量準確度和生產製造的柔性程度之間起到調節作用。顧客參與分為下訂單時的參與和下訂單後的參與兩個階段,顧客參與作為外生變量會對消費偏好測量和生產製造的柔性程度之間的匹配關係造成干擾,進而降低二者之間的正向相關性。對實踐的啟示是,企業在顧客參與時應鼓勵表達準確的消費偏好,約束做不到的企業承諾,將顧客參與的程度通過適當引導控制在企業的可控範圍內,以避免顧客過於離散的需求對企業整體生產運行系統造成負向擾動,從而影響最終產品品質。

本論文的實踐意義在於:
第一,企業戰略層面上,通過厘清大規模定制的機理和本質,找到阻礙企業向大規模定制成功轉型的原因,並為其轉型提供適當的策略建議,為大規模定制企業的轉型之路提供戰略新思路。

第二,企業經營層面上,幫助大規模定制企業深刻理解消費偏好測量和顧客參與在定制過程中發生作用的機制,使企業能夠根據自身實際情況,合理制定消費者偏好測量和顧客參與策略,最大限度提升企業的產品品質。
As they enter the 21st century, modern enterprises face unprecedentedly challenging environmental changes. Along with ever-increasing personalized and diversified consumer demands, the current mass production mode, which is based on economies of scale for high volume production, has steadily become less efficient in coping with growing competition and evolving market needs of enterprises. With the growth of Internet information and intelligent manufacturing technology, a new kind of future-oriented industrial paradigm called Mass Customization (MC) has been emerging. Mass customization is an organic integration of mass and customized production aimed at solving the fundamental contradiction between mass standardized production and consumers’ personalized demands by producing customized products at the low cost of mass production. MC is becoming the mainstream production mode of the 21st century recognized by both academia and industry. However, many enterprises have encountered a range of problems to be resolved in the actual practice of mass customization. These issues have become an important source of academic research.

Accordingly, this research is related to the following three problems in MC:
Firstly, MC is a customer-oriented and order-driven production mode. The enterprise needs to measure the consumer’s preference as clearly as possible before production. The accuracy of the Consumer Preference Measurement ( CPM ) will have direct impact on the success of the enterprise’ s MC implementation. So, how does CPM affect the final quality of mass customized products ? Which internal functional mechanism is involved?

Secondly, from the perspective of the production process, personalized orders are delivered to customers through factories utilizing the flexible production advantages of intelligent manufacturing. CPM is the process of order generation, while manufacturing is the process of order realization. So, what is the functional mechanism of the manufacturing process inter-positioned between CPM and the quality of mass customized products ?

Lastly, CPM needs Consumer Participation (CP). There are different levels of Consumer participation. How do the different levels of CP affect the MC process ?

Based on the above problems, this research studied the effects of CPM on the quality of mass customized products from the intelligent manufacturing perspective by integrating CPM and CP theories as well as introducing another two constructs, namely Flexibility of Manufacturing (FM) and Consumer Participation (CP). After investigating the effects of MF and CP separately as mediator variable and moderator variable, respectively, this research put forward a series of hypotheses and formulated a Structural Equation Model ( SEM ) with four variables such as CPM, FM, CP and the quality of mass customized products. During the empirical research, field investigations and questionnaire surveys were conducted for data collection. SPSS was used to analyze the data and verify the intervariable effects hypothesized in the SEM.

The main conclusions of this research include:
Firstly, CPM has significant positive effects on the quality of mass customized products, e.g., the more accurate the CPM, the higher the final product quality. The primary implication for business practice is that the MC enterprise needs to maximize the external product variety through more reasonable modular production design, cover consumer demands to the extent possible, and offer back-up contents for the external forms of measurement as adequately as possible. This is to create more effective foundational conditions to improve the accuracy of CPM and ultimately improve product quality.

Secondly, FM is the mediator between CPM and the quality of mass customized products. The modularity includes modular decomposition and integration according to Modular Theory. In this research CPM is regarded as modular decomposition while manufacturing is regarded as modular integration. Modular decomposition has positive effects on modular integration, all of which affects final product quality. Product quality can be improved only when modular decomposition matches modular integration. The instructive contribution of this research to business practices is that enterprises’ efforts to improve product modular design should be based on the basis of their production capability, because customized orders are realized through manufacturing. Even though CPM can be accurate enough, if it does not match FM, product quality still cannot be improved. Instead, a mismatch may lead to negative impact on quality.

Thirdly, CP is the moderator between CPM and FM. CP is divided into participation at the order placement stage and participation after order placement. As an external variable, CP would reduce the positive correlation between CPM and FM by disturbing their matching equilibrium. Business practices can be enlightened by these findings in the sense that the enterprises should adopt a cautious attitude based on proper encouragement to CP,and keep the CP level within a controllable scope through proper guidance, so as to avoid an excess of discrete consumer demands which create negative turbulence within the whole manufacturing system, ultimately culminating in diminution of quality.

The practical significance of this research includes:
Firstly, at the strategic level, through clarifying the mechanism and essence of MC , this research dynamically reveals the reasons which hinder the enterprises’ successful transformation to MC, and offers proper suggestions and inspiration for implementation of new strategic approaches within MC enterprises.

Secondly, at the operational level, this research empowers MC enterprises to thoroughly understand the functional mechanisms of CPM and CP during the mass customization process, thus enabling enterprises to formulate optimal CPM and CP strategies so as to maximally improve product quality.

    Research areas

  • Mass Customization, Modularity, Consumer Preference Measurement, Flexibility of Manufacturing, Mass Customized Product Quality, Consumer Participation