An assessment of the Importance of Business Model Components among Different Industries
06-29-2015 (final version)
Liling Wang No.10830413
Supervisor: Dr. Stephan von Delft
MSc. in Business Administration-Strategy Track
Statement of originality
This document is written by Liling Wang who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This paper aims to explore the distinct importance of business model components among different industries through assessing different rankings of components among four diversified industries including online apparel retail, management consulting, telecom operation and furniture manufacturing. The nine building blocks created by Osterwalder & Pigneur (2005) are regarded as the unitary business model components in this paper. The main methodology of AHP (Analytic Hierarchy Process) is adopted to investigate the differences of top important components of business model among the four industries. The consequences reveal that the four industries emphasize on dissimilar components in terms of their particularly industrial characteristics and competition patterns to create a competitive business model. Furthermore, underlying relationships between components and generally industrial characteristics are discussed. The achievements of this paper not only provide reference for managers in the four industries to decide how to conduct business model creation and change, but also demonstrate a universal methodology that can be applied in wider industries to explore their own emphasis on business model components.
Key words
Table of contents
1. Introduction... 1
2. Literature review... 4
2.1 Business model concept...5
2.2 Business model components... 7
2.3 Prioritizing indicators using AHP (Analytic Hierarchy Process)... 12
2.4 Research question... 12 3. Methodology... 12 3.1 Research design...12 3.2 Data collection... 12 3.3 Data analysis... 12 4. Discussion... 12
4.1 Relationships between highly ranked components and specific industry... 12
4.1.1 Online apparel retail industry... 12
4.1.2 Telecom operation industry...12
4.1.3 Management consulting industry...12
4.1.4 Furniture manufacturing industry... 12
4.2 Relationships between the nine components and specific industrial characteristics... 12
4.2.1 Value propositions...12 4.2.2 Customer segments... 12 4.2.3 Customer relationships...12 4.2.4 Channels...12 4.2.5 Key resources...12 4.2.6 Key activities...12 4.2.7 Key partnerships... 12
4.2.8 Cost structure... 12
4.2.9 Revenue streams... 12
4.3 Implications for theory...12
4.4 Implications of practice...12
4.5 Limitations and future research... 12
5. Conclusions... 12
Reference... 12
1. Introduction
In recent years, the business model has gained substantial attention from both practical and academic fields. Over last 20 years, we can see that two basic consensuses that have been reached by extensive scholars. On the one hand, they realize the uniqueness and importance of business model that differs from strategy, process and financial structure and so on (Chesbrough & Rosenbloom, 2002; Morris, 2005; Osterwalder and Pigneur, 2005; Osterwalder and Pigneur, 2005; Zott, Amit & Massa, 2011; George & Bock, 2011). On the other hand, the business model rationale of an organization is to create, deliver, and capture value (Chesbrough & Rosenbloom, 2002; Osterwalder and Pigneur, 2005; Zott & Amit, 2008; Johnson et al., 2008; Teece, 2010; George & Bock, 2011). However, while the majority of researchers agree on the essence of a business model, there is a lack of a unitary conceptualization of the business model in academic literature (Shafer et al., 2005). Subsequently, changes within the available definitions offer substantial challenges for delimiting the components of a model, and also in determining what constitutes a good model (Morris, Schindehutte & Allen, 2005). The lack of unitary cognition of business model components results in absence of common language in analyzing and comparing distinctions and similarities of business models in different industries (Hedman & Kalling, 2003). Therefore, when practitioners execute a business model, this vagueness of business model often leads to the misunderstanding or partial understanding of it (George & Bock, 2011). By now, scholars barely pay attention to this problem and they do not create systematic approach to deal with it, which is caused by two main reasons. Firstly, recent studies concentrate on dynamic nature of business model, especially like innovation, in order to address change (Demil & Lecocq, 2010). Secondly, the development of business model hasn’t entered into mature age, the recognition of this problem emerges along with more information accelerated from practice of business model application, which needs time (Eckhardt, 2013).
In recent years, some scholars tried to identify common components of business model that serve as common language in business model research and practice (Baden-Fuller & Morgan, 2010). Consequently, a variety of common components are created. Regardless of the variance in common components, researchers should consider how to exploit common components (Shefar et
al., 2005). Al-Debei & Avison (2010) also advocate further examination in common dimensions,
because different industries may place dissimilar emphasis on those dimensions. “Although there have been efforts to define, describe, and classify business models, current literature does not provide a structured method of comparing business models between industries” (Hedman & Kalling, 2003:52). Short of explicitly significant components for specific industry, managers are vulnerable to getting lost in shaping and coordinating action (Mason & Spring, 2011). Hence, from the theoretical and practical perspectives, it is necessary to know what components matter very much to particular industry. Under this circumstance, they will be able to know how to operate their businesses in a better way. For example, “while manufacturing companies may draw more attention to their value networks as they belong to a tight supply chain system, telecommunication providers are likely to lay more emphasis on their value architectures as being the primary enablers of value propositions” (Al-Debei & Avison, 2010: 374). The premise is that executives of manufacturing companies and telecommunication providers respectively identify that supply chain system and value propositions that are parts of business model component in Al-Debei & Avison,’s view, are most significant factors to their businesses. As a matter of fact, this study intends to reveal such kind of premise in some industries.
In order to explore to what extent do different industries explain the degree of importance in the components of business model, this study firstly introduces a common components of business model that will serve as unit of analysis. It is created by Osterwalder & Pigneur (2005) and consists of nine components, namely, value propositions, customer segments, channels, customer relationships, key partnerships, key activities, key resources, cost structure, and revenue streams. These nine dimensions are required to be ranked in terms of different industries.
This study chooses several industries as research targets. There is a very crucial criterion to select industries that they should be different with each other to a large extent. Because it is possible to conduct horizontal (within four industries) comparisons for dissecting the results if selected industries match this criterion. Besides, it is better if selected industries are frequently researched in business model domain, which indicates that more relevant information and experiences would exist to verify the reasonability of relationship between highly ranked components and particular industry. All these limitations of picking industries would result in more valid and convincing consequences. Three frequently studied areas that are identified by Zott, Amit, and Massa (2011) could be refined into three aspects: e-business, information technology management, and strategy & innovation management. In addition, Lambert & Davidson (2013) reveal that information, media and telecommunication enterprises feature business model most frequently by analyzing 69 articles. Therefore, three distinctive industries that are considered representing Zott et al.’s three aspects and taking Lambert & Davidson’s research consequences into account would become the investigated targets. What’s more, connecting the first criterion, this paper adds furniture manufacturing industry to diversify and enrich the investigated industries. In conclusion, research industries in this study are: online apparel retail industry, management consulting industry, telecom operation industry, and furniture manufacturing industry.
An exploring method called AHP (Analytic Hierarchy Process) will be employed to generate distinct rankings of importance of the nine components in the four industries. As to a company, the ultimate goal of a business model is to make the company competitive in market (Casadesus-Masanell & Zhu, 2013). The measurement criterion behind the ranking is to see what components can contribute to a competitive business model that makes a company successful in an industry. Finally, the research question comes out to be: What are differences of the importance of the nine components among online apparel retail, management consulting, telecom operation, and furniture manufacturing industry for creating a competitive business model?
This paper has several contributions. In theoretical side, the research topic is a further development of business model components. Admittedly, common components are exploited by some researchers to study topics like innovation (Doganova & Eyquem-Renault, 2009). However, the novel research gap this paper tries to address is a relatively new direction to expand the research of business model components. It aims to take advantage of achievements of common components and distinguish the differences of top important components in different industries based on common components. Therefore, it brings a new insight and extension of the vertical development of common business model components. Besides, the methodology provides systematical research pattern for universally valid use in extensive industries. Lastly, other than e-business model is frequently studied, business model research in other fields and industries is scattered and scarce (Mason & Spring, 2011). In consequence, the findings reinforce tremendously the perceptions of business model in wider industries. In practical side, managers can benefit from the findings. Because highly ranked components mean a lot to competitive business model and to successful business. Hence, managers know it is time to conduct business model changes when their businesses encounter problems that are closely related to highly ranked components of business model. The usefulness and predictable power of findings are expected to help entrepreneurs make more informed decisions, thus increasing the chances of success.
2. Literature review
In the following section, the main insights from current literature on business model and AHP (Analytic Hierarchy Process) will be delineated. Firstly, the business model concepts will be described, which serves as foundation for further understanding in business model components. Secondly, current situation about business model components will be identified, which will provide a background to comprehend the research gap in a better way. Especially, the knowledge
about the nine building blocks will be explained. Thirdly, applications of AHP in prioritizing the elements in management domain will be presented. Lastly, the end of this section will reveal the research gap and identify the research question.
2.1 Business model concept
Since the mid-1990s, the business model concept has become prevalent together with the emergence of Internet (Zott, Amit, & Massa, 2011). The term “business model” has been frequently used by managers, consultants, and scholars from various domains over the last 20 years, which manifests the significance of business model (Baden-Fuller & Morgan, 2010). With the efforts of a good number of investigators, a solid ground of business model has been achieved by most of them. They argue that the principle of a business model is about creating, delivering and capturing value and it can’t be equal to other prevalent terms in the management literature like strategy, business concept, profit model, finance model, or even business process modeling (Zott & Amit, 2001; Chesbrough & Rosenbloom, 2002; Morris, 2005; Osterwalder & Pigneur, 2005; Johnson et al., 2008; Teece, 2010; Zott,Amit, and Massa, 2011; George & Bock, 2011; Calors & Peter, 2014). However, “concepts are developed largely in silos according to the phenomena of interest to the respective researchers” (Zott et al., 2011: 1020). In other words, it still hasn’t established wide consistency regarding the definitions and compositions of the business model concept (Lambert & Davidson, 2013). In order to achieve a common comprehension of business model, a large amount of conceptualizations of business model must be distinguished systematically (Osterwalder & Pigneur, 2005). Therefore, some researchers contribute efforts to this, and conclude with divergent classifications for business model concepts.
Al-Debei & Avison (2010) distinguish four types of business model concept. The definition of each type places emphasis on different perspectives such as business model dimensions, functions, scopes, and modeling principles. First of all, some conceptualizations depict business model through its components. Zott & Amit (2001: 511) argue that “a business model depicts the content,
structure, and governance of transactions designed so as to create value through the exploitation of business opportunities”. And then, some researchers describe divergent functions when defining business model concept. Synthesizing the literature, “business model is referred to as a statement, a description, a representation, an architecture, a conceptual tool, a model, a structural template, a method, a framework, a pattern or a set” (Zott, Amit & Massa, 2011:1023 ). Additionally, business model can be defined by explicating the ontology or scope of it. For example, business model is a detailed conceptualization of an enterprise’s strategy at an abstract level or business model is a theoretical intermediate layer between strategy and business process (Casadesus-Masanell & Zhu, 2013). Lastly, a part of business model concepts only outline abstract modeling principles that stand for lacking of fundamental details depicted in concepts and using abstract images to illustrate what a business model is. For instance, Haaker et al. (2006: 648) define business model as “a blueprint of collaborative effort of multiple components to offer a joint proposition to their consumers”. Based on the phenomenon of diversified concepts, we can see that a mass of the confusion about business model derives from different researchers talking about business models when they do not necessarily mean the same thing (Linder and Cantrell, 2001).
From another perspective, Osterwalde & Pigneur (2005) also distinguish three levels to show what the different researchers address when they mention business models. The first level contains overarching business model concepts that are characterized as abstract definitions. In accord with ‘modeling principles’, concepts of the first level delineate abstract rudiment of what a business model is. Partially in keeping with ‘business model dimensions’, the second level presents a series of classified business models, each of which explains a set of businesses containing common dimensions. Not necessarily a sub-class of an overarching business model concept, the second level incorporates generic concepts that consist of some common characteristics but apply to particular fields (Weill and Vitale, 2001). Fox example, Sabatier, Mangematin, & Rousselle (2010) come up with a business model concept to analyze biopharmaceutical industry, while Zhu &
Kraemer (2005) develop a business model for e-businesses. The third level, which can be named instance level, depicts aspects or conceptualizations of a specific real world business model. Other than the two kinds of criteria, which are used to classify business model concepts conducted by Al-Debei & Avison (2010) and Osterwalde & Pigneur (2005), there exist other classifications according to different criteria. For example, Morris et al. (2005) propose three general categories of definitions based on their primary keys, which can be labeled economic, operational, and strategic. No matter what kind of taxonomies, it is impossible to achieve mutually exclusive (George & Bock, 2011). However, at least they provide easier understanding of the characteristics of existing notions. Relatively unitary conceptualization is a solid foundation for figuring out common components for business model (Linder & Cantrell, 2001). Nevertheless, the fact of chaos in business model concept presents an implication that the development of business model components is inevitably trapped into complicated situation (Morris, Schindehutte, & Allen, 2005). Therefore, a widely received notion should be created to make a good preparation for development of business model components.
2.2 Business model components
According to what mentioned above, it is manifested that business model lacks of theoretical consensus in this field of research. Hedman & Kalling (2003: 49) also argue that “the concept is often used independently from theory, meaning model components and their interrelations are relatively obscure”. Changes within the available definitions offer substantial challenges for delimiting components of a model, and also in determining what constitutes a good model (Morris, Schindehutte, & Allen, 2005). Until now, great part of the research which focuses on business models, concerns e-business (Zott et al., 2011). However, fuzziness about components in e-business is still highly debated among researchers, let alone other fields that are investigated in greatly less frequent way than e-business (Doganova & Eyquem-Renault, 2009)
Based on the fact that the vagueness concerning the business model components, it is difficult to perform valid comparative empirical research (Onetti et al, 2012). Therefore, identifying mutual and unified components in whole business model field is helpful to create common language in analyzing and comparing the variances and similarities among different industries (Al-Debei & Avison, 2010). Thus, a need exists to build a structure that addresses all relevant components of a firm’s business model (Eckhardt, 2013). A few scholars realized the significance of it at the beginning of e-business model booming, and attempted to distinguish the different elements between particular fields and no field limitation. For example, Applegate (2001) deems generic market role, digital business, and platform as the three elements of e-business model, whereas he proposes three more comprehensive dimensions to describe business model including concept, capabilities, and value.
A later, but more generic stream thrives at beginning of this decade. Because more and more researchers agree with the logic that common business model components are the foundation of convenient and efficient research in different industries (Onetti et al., 2012). Similarly, based on the review of the widely ramified literature, many authors contribute their efforts to this foundation. Some achievements are presented in table 1. From this table, we can see that several components such as value proposition, resources, profit, are repeatedly included in different achievements, which means that basic perceptions of business model components are analogous. However, we also can find out that some unique components like competitive strategy (Morris et al. 2005), competitors (Hedman & Kalling, 2003), also constitute a business model, which shows that research on this topic is still confounded by inconsistent components and boundaries (George & Bock, 2011). Especially, looking into the nine components created by Osterwalder & Pigneur (2005), reason why some components should not be encompassed into nine building blocks is that only one author mentions them, which indicates lack of prevalence (Osterwalder & Pigneur, 2011). On the other hand, the second reason is that even if some components are very important to realize
and implement business model, they are not part of business model’s ontology (Chesbrough & Rosenbloom, 2002).
Table 1 - Components of Business Model
Author(s), Year Business Model Components
Hamel, 2000 Customer logic; Strategy; Resources and network
Linder & Cantrell, 2001
Pricing; Revenue; Channel, Commerce process; Internet-enabled commerce relationship; Organizational form; Value proposition
Afuah & Tucci , 2001
Profit site; Customer value; Scope; Price; Revenue sources; Connected activities; Implementation; Capabilities; Sustainability; Cost structure Zott & Amit, 2001 Content; Structure; Governance
Hedman &
Kalling, 2003
Customers; Competitors; Offering; Activities and organization; Resources; Supply of factor and product input; Longitudinal process Osterwalder &
Pigneur, 2005
Value proposition; Customer relationships; Customer segment; Key partners; Key activities; Key resource; Channels; Cost structure; Revenue model
Morris et al., 2005 Offering; Market; Internal capability; Competitive strategy; Economic; Investor
Richardson, 2008 Offering; Target customer; Basic strategy; Resources and capabilities; Organization; Position in the value network; Revenue sources; Economics of the business
Johnson, 2008 Customer value proposition; Profit formula; Key process; Key
resources
Although researchers frequently adopt particular definitions that are hard to make completely compatible with each other (Zott, Amit & Massa, 2011), at least two basic consensuses have been reached. On the one hand, they realize the uniqueness and importance of business model that
differs from strategy, process and cost structure, etc. (Chesbrough & Rosenbloom, 2002; Morris et al., 2005; Osterwalder and Pigneur, 2005; Zott & Amit, 2011; George & Bock, 2011). On the other hand, the business model rationale of an organization is to create, deliver, and capture value (Chesbrough & Rosenbloom, 2002; Osterwalder and Pigneur, 2005; Zott & Amit, 2008; Johnson et al., 2008; Teece, 2010; George & Bock, 2011). While the agreement about the nature of business model has been fundamentally achieved, fierce arguments still reside in the role of business model in the way to create, deliver, and capture value. Notably, researchers are seeing different aspects of business model by gazing through different fields or industries (Shafer et al., 2005). To sum up, these phenomena indicate that the common components should incorporate two characteristics: a) it should be built upon the two basic consensuses; b) it is capable to be studied and compared by different industries only when it is concrete and comprehensive enough.
Looking into the nine building blocks created by Osterwalder & Pigneur (2005), first of all, it satisfies the two basic consensuses of business model. Osterwalder and Pigneur (2005) delimit strictly business model from strategy, enterprise model, business structure, business process as well as implementation of business model. Besides, the start point of the nine building blocks is to create, deliver, and capture value. Furthermore, it has already been applied and tested around the world and is already used in organizations such as IBM, Ericsson, Deloitte, the Public Works and the Government Service of Canada, and many more (Osterwalder and Pigneur, 2011). Undeniably, other authors also propose common components that meet the basic two consensuses like Amit & Zott (2001), Johnson et al. (2008). But the nine building blocks are more concrete and comprehensive, which not only serves better for theoretical foundation but also to measure method (Doganova & Eyquem-Renault, 2009). Compared to Johnson et al. (2008) who believe that a business model consists of four interlocking elements including customer value proposition, profit formula, key process, and key resource, the nine building blocks divide business model components into more details. Fox example, Johnson’s profit formula in the nine building blocks is divided into revenue streams and cost structure. The detailed components enable the difference
between components obvious in research result, which is a precondition to make the result valid and to guide real action (Shafer et al., 2005). Because, the distinctions of what business model components make a big difference in the performance of different industries are subtle, which is unable to be shown in broad components. To give an example, steel-making industry and solar power industry all concern profit formula very much. Steel-making industry usually pays more attention to cost structure because of excess capacity, which requires the enhancement in cost control to increase profit. However, solar power industry tries best to deal with revenue streams, which primarily calls for the innovation of technology to generate revenue (Mason K, Spring, 2011). Obviously, this distinction in the components of Johnson et al. (2008) cannot be reflected, which directly makes a pointless result. Hence, explicit and concrete division of the nine building blocks makes this research actually operational. The same problem happens in Zott & Amit ‘s (2001) business model components. Furthermore, the final components of the nine building blocks derive from integrating a large number of articles that relate to different fields, while Zott & Amit’s (2001: 511) three components are “based on analysis of the sources of value creation in e-business”. The chosen components will be applied in extremely different industries. Thus, the nine building blocks are more convincing in comprehensiveness aspect than Zott & Amit’s (2001). Admittedly, while the nine building blocks are more detailed, they are not superior from the view of mutually exclusive components (Onetti, Zucchella & Jones, 2012). However, the emphasis of this research is more inclined to find out the relationship between the elements of business model and different industries. In other words, this study aims to discover what elements contribute greatly to excellent performance in creating, delivering value of specific industries. Therefore, even though the business model components of Johnson et al. (2008) and Zott & Amit (2001) seamlessly connect with each other and very prevalent, they are not suitable in this research.
2.3 Prioritizing indicators using AHP (Analytic Hierarchy Process)
AHP is the abbreviation of Analytic Hierarchy Process that is a systematic analysis method created in 1980 by Saaty (Saaty, 1980). Originally, AHP is applied to be a multi-criteria decision-making approach. For over 30 years, this approach has been used and studied extensively in several other fields, such as activity planning, optimization, resource allocation, conflict resolution and so on (Ahamd, et al., 2006). Generally speaking, scholars often combine other methods or algorithms to develop the application of AHP in other fields, but majority of them preserve the rationale of AHP. The basic idea of AHP is a series of standard processes that consist of three steps. At the beginning, “hierarchic factors that are important for a decision are structured descending from an overall goal to criteria, subcriteria and alternatives in successive levels” (Satty, 1994: 426). Next, numerical judgments correspond to verbal judgment of each factor. Finally, the weights for each factor are calculated through a series of mathematical processes (Altuzarra & Salvador, 2007).
Although AHP hasn’t been used to make the prioritization of business model components, it has already been adopted widely to prioritize key performance indicators in other management fields. This is a development of AHP through combining indicator system with fundamental principles of AHP. Shahin & Mahbod (2007) carry out AHP to prioritize organizational key performance indicators in terms of the criteria of SMART (Specific, Measurable, Achievable, Realistic, Timely) goal setting. Finally, a new approach is outlined according to the prioritization, encompassing clear and logic introductions for decision makers to conduct the organizational operation. Similarly, Bozbura & Beskese (2007) get the ranking of organizational capital measurement indicators including deployment of the strategic values, investments in the technology and flexibility of the organizational structure via AHP. In addition, the application of AHP makes it possible to set the priority among criteria in the mobile telecom operation industry (Han & Han, 2004). By that analog, AHP has great potential to be applied in business model components
domain, because the nine common components of business model are key indicators of business performance.
Usually, researchers are inclined to figure out the business model components of an industry when they want to distinguish the prior importance components of business model of an industry. Next, picking up a typical company within the industry as representative, they evaluate impacts of each component in profit performance of the company, which can be quantified (Ban, Koppinger, & Stanley, 2006). Finally, a ranking of components comes out according to the evaluation value (Han & Han, 2004). This method is suitable to single industry and the accuracy of result remains suspicious. In order to apply in a larger scale, this paper employs AHP. Since AHP is suitable in a broad scale survey because of its convenience, manipulity and comparability (Leung & Cao, 2000). Therefore, AHP is an appropriate method for this paper to rank the degree of importance of the nine components among four industries.
2.4 Research question
Nowadays, the current trend about business model is identifying common components, which serves as common language in business model research and practice (Baden-Fuller & Morgan, 2010). Now that identifying common components is for the sake of further research, we should consider what deep academic development and practical application could be dag out based on this common language. Actually, despite of changes in recognizing common components, different industries even may place dissimilar emphasis on unitary components (Al-Debei & Avison, 2010). Therefore, distinguishing common components is a good foundation, but not enough for guiding practice. In order to elaborate the implication of business model dimensions in practice, it is necessary to discuss dimensional dominance according to different industries (George & Bock, 2011). In other words, it is worthwhile to find out the differences of top important components among different industries.
Although scholars barely put efforts on this problem, some relevant contributions still can be found in this field. Ban, Koppinger and Stanley (2006) use a component business model of automotive industry to prioritize business changes affecting key performance indicators for the business. Based on judging the degree of significance of different components, they know how to grasp opportunity to improve business process and tackle warranty problem. In addition, Fetscherin & Knolmayer (2004) outline 5 components of a business model for content delivery including the product, the consumer, the revenue, the price, and the delivery. They use the newspaper and magazine industry as an example, and empirically test the impacts of these 5 components on profit. As a result, the most important key profit driver is the product, followed by revenue and price, and the least important are consumer and delivery. In order to deal with the problem that to what extent do distinct industries explain importance differences in the components of business model, some heuristic thinking can be stimulated from these examples: unitary business model components allow a more consistent way to compare distinctions among different industries (Fetscherin & Knolmayer, 2004); ranking the degree of importance of each component is a suitable way to compare distinctions among different industries; a measurement criteria for ranking of components like effects on key performance (Koppinger & Stanley, 2006)
or impacts on profit ((Fetscherin & Knolmayer, 2004) is needed. This paper believes that each component as a part of a business model, they are all responsible to what a business model achieves. In other words, each component is capable to influence the creation of a competitive business model that helps a company achieve leading place in an industry. Admittedly, under different industrial conditions, contribution of a component to a business model differs, which is the rationale why the rankings make sense. From the above, integrating the four industries that this paper refers to previously, the research question of this paper is as followed:
What are differences of the importance of the nine components among online apparel retail, management consulting, telecom operation, and furniture manufacturing industry for developing a competitive business model?
3. Methodology
3.1 Research design
This paper adopts AHP as an exploring methodology, which is carried out in two phases: hierarchy design and evaluation (Vargas, 1990). For the first part hierarchy design, this paper follows the nine building blocks of business model (Osterwalder & Pigneur, 2005). Furthermore, the nine building blocks are integrated into two hierarchies according to their relationships. The hierarchical structure is presented below (figure 1). It shows clear logic from wider scope to detailed scope, which is helpful for participants to judge the prioritization. From the figure 1, we can see that component of value propositions belongs to product that is in upper level. Because the value proposition is the overall view that represents company’s different products and services in targeting different customer segments (Osterwalder & Pigneur, 2004). Customer interface contains three components, namely, customer relationships, customer segments, and channels. Apparently, these three dimensions are closely associated with customer side. Infrastructure management supports the accomplishment of product including key resources, key activities, and key partnerships. Lastly, financial aspects encompass revenue streams and cost structure.
Also, some indicators for each component are listed in table 2 (Hedman & Kalling, 2003; Osterwalder & Pigneur, 2004; Johnson et al., 2008; Al-Debei & Avison, 2010; Zott, Amit & Massa, 2011), which visualizes abstract picture of the nine components. Checking the reified indicators, it is helpful for participants to judge the importance comparison between different components.
Table 2 - Indicators for the Nine Components
Components Indicators
Value propositions What value does a company deliver to customers; which one of
customers’ problems helped to solve; what bundles of products and services does a company offer to each customer segment
Customer segments Identifying distinct segments with common needs, common behaviors, or other attributes; defining several customer segments
Customer relationships Some related activities to acquire, retain customer, and boost sales
Channels Raising awareness about product, helping customers evaluate value
proposition, allowing customers to purchase products, delivering value proposition to customers, providing post-purchase customer support Key resources Talented staff, information, technology, reputation, brand
Key activities Production, problem-solving, platform
Key partnerships Buyer-supplier, joint venture, strategic alliance between
non-competitors or competitors
Cost structure How costs are allocated: includes cost of key assets, direct costs, indirect costs, economics of scales
Revenue streams How much money generated from different segments: how to make
price mechanism; how would customers prefer to pay; how are consumers currently paying; for what value are our customers really willing to pay
Furthermore, the definition and description of each component are provided in appendix 1, which is relatively brief. There are two considerations for this design. On the one hand, too much information for participants to read and understand in questionnaire will result in the psychological resistance and low efficiency of information digestion (Flynn & Schroeder, 1994). On the other hand, brief introduction of the nine business model components as heuristic information is more likely to induce and facilitate the communication between participants and researcher (Charnes & Cooper, 1978). As a matter of fact, the main objective of this survey is to attain the consensus to a certain degree. However, the diversely subjective thinking makes the objective hard to achieve. Hence, sufficient communication before the scoring is conducive to participants to comprehend the clear delimitation of nine components, the principle of this survey, the measurement standard behind the scoring and the objective logic of the pair comparison, etc. Absolutely, the communication is not allowed to lure the independent judgment and only convey basic and essential knowledge to participants (Khorramshahgo & Moustakis, 1988). Only when participants receive the unitary and essential information for this survey, can the external effects to the consensus be controlled in a minimized manner.
As to the evaluation in second part, the first step is collecting data. Data will be obtained through the designed marking tables of pairwise comparison of components to investigate preferences of the nine building blocks in contributing to a competitive business model for four different industries. The design of survey is showed in appendix 1, which consists of two parts: background introduction and scoring tables. The introduction section is indispensable in AHP, because it provides preliminary information for participants to judge (Khorramshahgol & Moustaki, 1988). Firstly, it shows the hierarchical structure of business model (figure 1). Next, a description of each component is provided. In each hierarchical level, pairwise comparisons of the elements are made by respondents via using a numerical scale, which is a process of transforming verbal judgments into quantitative judgments (Altuzarra et al., 2007). This process is accomplished by the use of a ‘fundamental scale’ created by Saaty (1990). The second section includes four scoring tables for
two hierarchical levels, one for first level and three for second level. Scoring these four tables mainly needs comprehension about “fundamental scale” and description of nine components. Checking the indicator list (table 2) provided in communication, if participants consider making attractive price mechanism is very strong important than allocating cost among different departments, perhaps, the cell representing revenue streams compared to cost structure should be scored 7. With regard to this scenario, there are three points should be announced here. Firstly, the indicator list is not complete, but a reference for better comprehension about the nine components. Participants should be able to judge complicated real situation according to their knowledge. Secondly, all aspects belonging to a component should be taken into consideration. They come into being a synthesizing view to compare with other components rather than just one aspect listed in the scenario. Thirdly, the degree of importance comparison derives from subjective perception. Referring to fundamental scale (appendix 1), corresponding grade to degree can be locked, as degree of “very strong important” in the scenario is defined 7.
Traditionally, AHP is a tool for decision maker to scientifically analyze alternatives and make optimal choice. Usually, one participant can complete whole process. As the advancement of AHP, the accuracy of result calls for more respondents of which the number must be odd to take part in scoring (Saaty, 1994). As to the requirements of participants, it varies according to idiosyncratic cases (Khorramshahgol & Moustakis, 2011). For this research, owing to the reliability of results highly depending on these scoring and business model is a relatively professional domain, it asks for that the respondents should be experts who understand business model very well, such as CEOs, senior workers, management researchers. In addition, this survey plans to invite 5 experts to score for each industry. There are total 20 samples will be recollected.
Actually, different experts come out different preferences on scoring, which may cause contradiction in results when experts’ opinions are different with each other to a large extent. A kind of inconsistent phenomenon may occur like this: component A >component B; component B>component C; component C> component A. This problem will be detected in the consistency
check. Hence, this research will operate a several rounds multiple-experts scoring to obtain relatively unanimous outcomes in order to avoid contradiction. Certainly, it is just homologous rather than identical judgments. This is a combination of Delphi and AHP, which makes the consequences more reliable and precise (Khorramshahgol & Moustakis, 2011).
After collecting data, a series of standard mathematical analysis should be conducted, which can be simplified as followed. Firstly, pairwise comparisons are structured into an n-by-n reciprocal matrix C, called the judgment matrix (Lin, Lee & Ho, 2011).
ij n n nn n n n nC
a
a
a
a
a
a
a
a
a
C
...
...
...
2 1 2 22 21 1 12 11
;a
ij
a
i/
a
j,
i
,
j
1
,
2
...
n
Secondly, λ is an eigenvalue of C, and
w
(
w
1,
w
2,
w
3,...,
w
n)
Tis the normalizing eigenvector of matrix C. The solution of w in the quotation of Cw=λw is the weight of components (Saaty, 1990). Thirdly, Consistency check of AHP is a critical issue, which can be verified by consistency ratio (Leung & Cao, 2000). The consistency ratio (C.R.) is obtained by determining the C.I. ratio and the random index (R.I.) (Lin, Lee & Ho, 2011).1
.
.
max
n
n
I
C
, where λmaxis the largesteigenvalue of C (Xu, 2000). R.I. can be given in consistency index (table 3)
Table 3 - The Mean Consistency Index of Randomly Generated Matrices
n 1 2 3 4 5 6 7 8 9 10
R.I. 0.00 0.00 0.52 0.89 1,12 1.25 1.35 1.42 1.46 1.49 Source from Leung & Cao (2000)
We know from Saaty (1990) that the maximum consistency tolerance allowed is 0.10. Therefore, only when
.
.
.
.
.
.
I
R
I
C
R
C
<0.10, the relative weights we obtained would be regarded as consistent and be included for further analysis (Leung & Cao, 2000). Otherwise, we should try to adjust the judgment matrix until it is considered as consistent.3.2 Data collection
The separate data collections from online apparel retail, management consulting, telecom operation, and furniture manufacturing industry in China were held. According to the research design, similar and clear procedures were followed to accomplish data collection. As described in research design, AHP and Delphi were combined to be applied in this study. In the part of questionnaire design and data analysis, AHP was the principal rationale to follow. However, in the section of data collection, the method of Delphi guided the implementation. This technique aims at evaluating and developing a consensus through repeated iterations of questionnaires (Okoli & Pawlowski, 2004). Although the consistency ratio is the final judgment to the validation of data, the feedback of each round is not to inform participants that the final consensus hasn’t been achieved because of the consistency ratio exceeding 0.10. More detailed description of different opinions were delivered. Hence, in the stage of information feedback to participants, not only the consistency ratio was calculated to test the consensus of opinions, but also the explanation of the primary deviation through the observation of results was provided to participants (Khorramshahgol & Moustakis, 1988). For researcher and participants, the unacceptable consistency ratio was used to be the direct indicator to show the continuation of the next round inquiry. In addition, the interpretation of inconsistent consequences was the solid basis of scoring modification to participants.
Data collection of each industry was implemented independently, accordingly, which would be elaborated separately. However, some principles regulated by Delphi that were abode mutually by all the industries would be declared firstly. Although most of the participants were unfamiliar with each other, some of them were not. Participants who were acquaintances were asked to fill out the questionnaire without discussion. In a word, every participant should present individual understanding for the questions on the basis of themselves’ knowledge (Charnes & Cooper, 1978). Besides, even though the information of participants were exposed to researcher, the integration of
the results of each round inquiry was presented in anonymous. This means that participants only received anonymous feedback without knowing any information about the participants. All in all, independence and anonymity were two fundamental rules during the data collection (Okoli & Pawlowski, 2004).
At the beginning of survey, as mentioned in research design, adequate communication between researcher and participants are essential. In order to make sure that all the basic background information, measurement criteria, survey goal and scoring rules, etc. were fully comprehended by participants, researcher spent two to three days to answer the questions from participants through E-mail. Especially, some tools like indicator list (table 2) was used by researcher to explicate. During the communication, a sample of scoring table that was required by many participants was provided. As shown in the table 3, participants were only asked to score the upper right part above the main diagonal, which was helpful to reduce the workload and organize the scoring logic clearly. Since the grades of cells in the bottom left side were reciprocal to corresponding cells in upper right side, researcher would gain the whole grades after participants finished the half part. In the meantime, the pairwise comparison would easily lead to the discrepancy of the importance ranking, hence, a remind of checking the logic of importance ranking by themselves was announced before the survey.
Table 4 - A Sample of Scoring Table
Items Product Customer Interfaces Infrastructure Management Financial Aspects Product 1 1/2 2 3 Customer Interfaces 2 1 4 6 Infrastructure Management 1/2 1/4 1 2 Financial Aspects 1/3 1/6 1/2 1
In order to guarantee the reliability and accuracy of consequences, the research samples were selected carefully according to the particular situation of the industry. Who are correspondents for each industry and why are they knowledgeable will be stated in the following part.
Online apparel retail industry
Although the rising of online apparel shopping has only lasted several years in China, the growth momentum is amazing (Batjargal, 2007). Taobao is the largest online retail platform including apparel retail in China, which aggregates 2.5 million registered online shops for now (Yung & Qian, 2014). Participants of online apparel retail industry are picked from Taobao, which indicates that selected representatives from this highly competitive platform must know how to survive and perform well. Their perceptions of emphasis on business model dimensions are vital to guide their behavior to built a competitive business model. Based on a 2014 sale report of Taobao’s apparel branch released by YuBoZhiYe that is a authoritative market research institution, this research chose shops ranked within top 50 in sale revenue as qualified and potential respondents. All of the 50 shops were contacted through online customer service staff, only half of them were willing to consult the superior leaders for researcher to do further conversation. Finally 5 senior managers from five different shops ranked in range of 12 to 45 were persuaded to participate in this survey. For online apparel retail industry, the first and second hierarchy of business model components gains accord of scoring through two rounds and four rounds respectively.
Telecom operation industry
As the revolution and restructuring event launched in 2008, three state-run telecom operators dominates the telecom operation industry, namely, China Telecom, China Unicom and China Mobile (Lv & Kang, 2010). Since then, all of them obtained 3G licenses and joined the competition of fixed-line, mobile, and Internet businesses. Apparently, participants of this industry should include these three various companies. However, only participants from two telecom operators were finally invited to conduct this survey. Notably, some of them possess compound work experience in all the three companies. Based on investigation of their outstanding achievements in
career, they were believed to be equipped with comprehensive industry knowledge. Hence, the background limitation of participants would not jeopardize their rational judgment of the industrial situation and this small limitation for final result is acceptable. Eventually, three managers of business hall from China Telecom and China mobile and two strategy analysts with work experience more than ten years from headquarter of China Telecom were invited to take part in this survey. For telecom operation industry, 3 rounds and 5 rounds were carried out for first and second level of business model components to get consistent results.
Management Consulting industry
Unlike telecom operation industry with several operators, management consulting industry is full of plenty of big international players and small local businesses (Qiang, 2013). In general, international consultancies hold advantages because of abundant experience, brand awareness and reputation, which makes them dominate management consulting market (Zeng, 2013). At the meantime, local firms are struggling for development, which is in an emerging and promising momentum (Zeng, 2013). This research planned to invite three participants from international company and two participants from local firms to share their perspectives. As a result, two senior consultants from Deloitee, one senior consultant from Pwc, one advanced partner from YuanXun and one senior consultant from Adfaith constitute the respondent group. Among them, Deloitee and Pwc are international companies and YuanXun and Adfaith are leading local firms. All of these companies perform well in management consulting industry in China. Participants from these companies are supposed to know better about the business model in management consulting industry. For management consulting industry, it took 2 rounds and 3 rounds to achieve similar agreement for first hierarchy and second hierarchy respectively.
Furniture manufacturing industry
It doesn’t exist a furniture manufacturer whose output excesses 1% of whole industrial output, which implies that industrial concentration is very low (Lu & Tao, 2014). Also, Jiang, Zhang & Ding (2013) suggests that furniture manufacturing industry focuses on competition between small
and medium-sized enterprises, especially medium-sized ones. They would be washed out immediately once their business models can’t adapt to the rapidly changing environment (Jiang, Zhang & Ding, 2013). This severe competition pattern determined that sample should be collected from small and medium-sized firms who know not only how to survive but how to achieve industry-leading position. GuangDong province is the most advanced area in furniture manufacturing (Lu & Tao, 2014). This research locked top 30 out of several hundred manufacturers in profit in 2014 that were revealed by the annually industrial statistics of GuangDong province. As a result, 5 participants from three manufacturers were persuaded to participant in this survey. The three manufacturers including MingPai, NanHeng, and DaGongGuan are located in the top 30 manufacturers and history of them is all more than ten years. The 5 participants consist of 3 senior managers from MingPai, 1 senior manager from NanHeng and 1 senior manager from DaGongGuan. Although 3 senior managers from MingPai know each other very well, they are required to finish the survey independently. Three rounds were simultaneously conducted for both levels to gain the final data.
3.3 Data analysis
As requested before, this study received 5 similar but distinct samples for each level of each industry, which will be integrated into one matrix for being further processed. Five different numbers for one cell are averaged and rounded into nearest integer to constitute the matrix (Millet & Harker, 1990). The integrated matrix were processed according to the steps introduced in research design section, which would subsequently come out results that represent weight of each component within each matrix. Because the consistency ratio has been tested in the information feedback stage to make sure the accomplishment of data collecting, the data handling would focus on calculating proportion for each component. Certainly, consistency ratios will also be exhibited in tables and all of them are under 0.10.
For each industry, there are five tables are shown to carve the characteristics of different business models. First table reflects importance distribution of the four aspects in the first hierarchy. Following three tables respectively describe the compared importance of components within different aspects including customer interfaces, infrastructure management and financial aspects. Particularly, because the weight of product revealed in the first table is equivalent to component of value propositions in the second hierarchy that is the only component under product category. Hence, the weight of component of value propositions is not contained in a independent table necessarily and will be embodied in the last table directly. Last table is called hierarchical total arrangement that takes on the final proportion distribution of the nine components in contributing to a competitive business model (Vaidya & Kumar, 2006). As the table name implies, the final proportion derives from the total two hierarchies, which means the ultimate value of a component equals to that value of the component generated in level two multiply the value of aspect that the component pertains to in level one.
Notably, capital letters and numbers are adopted to make the presented tables concise. For better understanding results, the implications of characters used in tables are listed below (see table 4). Referring to this table, we can readily know the meaning of the combination of characters. Final consequences and more detailed data analysis will be elaborated in terms of different industries.
Table 5 - Implications of Character
Character Implication Character Implication
A Online apparel retail industry 11 Value proposition
B telecom operation industry 21 Customer segments
C Management consulting industry 22 Customer relationships
D Furniture manufacturing industry 23 Channels
1 Product 31 Key resources
3 Infrastructure management 33 Key partnership
4 Financial aspects 41 Cost structure
42 Revenue stream
Online apparel retail industry
The final averaged data are translated into the matrix below. The distribution of weight of the four different aspects shows that financial aspects play a significant role in developing a competitive business model for online apparel industry compared to other three parts, which occupies 50.7%. On the contrary, customer interfaces is the least important one among the four parts, which is at a value of 7.8%. As to product and infrastructure management, they are allocated 26.3% and 15.2% in explaining the variance of a competitive business model.
Table 6 - Hierarchical Single Arrangement of First Level for Online Apparel Retail Industry
A1 A2 A3 A4 Weight Consistency ratio
A1 1 3 2 1/2 0.263
C.R.=0.004
A2 1/3 1 1/2 1/7 0.078
A3 1/2 2 1 1/3 0.152
A4 2 7 3 1 0.507
Regarding the second level, significance of components is revealed in the following three tables. Within customer interfaces field, customer relationships take a leading place with a percentage of 62.6%. Besides, component of channels is more important than component of customer segments, which are at 29.3% and 8.1% respectively. As to management infrastructure, component of key partnerships matters a lot, which accounts for over 50%. The rest proportion is shared by component of key resources and key activities, at 39.3% and 8.2% separately. In case of financial
aspects,component of cost structure is deemed to commit as double responsibility as component of revenue streams.
Table 7 - Hierarchical Single Arrangement of Customer Interfaces for Online Apparel Retail Industry
A21 A22 A23 Weight Consistency ratio
A21 1 1/6 1/4 0.081
R.I.= 0.091
A22 6 1 3 0.626
A23 4 1/2 1 0.293
Table 8 - Hierarchical Single Arrangement of Infrastructure Management for Online Apparel Retail Industry
A31 A32 A33 Weight Consistency ratio
A31 1 1/4 1/7 0.082
R.I.= 0.060
A32 7 1 1/2 0.393
A33 4 2 1 0.525
Table 9 - Hierarchical Single Arrangement of Financial Aspects for Online Apparel Retail Industry
A41 A42 Weight Consistency ratio
A41 1 2 0.667
R.I.= 0.000
A42 1/2 1 0.333
Synthesizing all the figures provided previously, the final result of hierarchical total arrangement is presented in table 10. Obviously, component of cost structure draws most attention in developing a competitive business model. Next, component of value propositions should not be
neglected to work on, since it occupies the second place with a percentage of 26.3%. Notably, most of the rest components gain a value below 10% except component of revenue streams at 16.9%.
Table 10 - Hierarchical Total Arrangement for Online Apparel Retail Industry Ai Aij A1 0.263 A2 0.078 A3 0.152 A4 0.507 Hierarchical Total Arrangement RANKING A11 0.263 -- -- -- 0.263 2 A21 -- 0.081 -- -- 0.006 9 A22 -- 0.626 -- -- 0.049 6 A23 -- 0.293 -- -- 0.023 7 A31 -- -- 0.082 -- 0.012 8 A32 -- -- 0.393 -- 0.060 5 A33 -- -- 0.525 -- 0.080 4 A41 -- -- -- 0.667 0.338 1 A42 -- -- -- 0.333 0.169 3
Telecom operation industry
The customer interfaces with value of 37% are considered as the most important aspect in creating a competitive business model in telecom operation industry. Infrastructure management is slightly lower than customer interface with near the value of 35% taking up the second place. As to financial aspects and product, they are the least important two aspects and share the rest portion at 18.5% and 10% separately.
Table 11 - Hierarchical Single Arrangement of first level for Telecom Operation Industry
B1 B2 B3 B4 Weight Consistency ratio
B2 4 1 1 2 0.370
B3 3 1 1 2 0.345
B4 2 1/2 1/2 1 0.185
When it comes to the second level, values of importance distribution within different classifications vary greatly. As for customer interfaces, component of customer segments is regarded as most important, which is at 58.2%. Followed by component of channels, which is about half of component of customer segments, but about three times of component of customer relationships. Subsequently, component of key activities pertaining to infrastructure management dominates 71.5%, and the other two components only occupy a small value. Lastly, component of revenue streams and cost structure accruing to financial aspects commit 50% equally.
Table 12 - Hierarchical Single Arrangement of Customer Interfaces for Telecom Operation Industry
B21 B22 B23 Weight Consistency ratio
B21 1 5 2 0.582
R.I.= 0.002
B22 1/5 1 1/3 0.110
B23 1/2 3 1 0.309
Table 13 - Hierarchical Single Arrangement of Infrastructure Management for Telecom Operation Industry
B31 B32 B33 Weight Consistency ratio
B31 1 1/7 1/2 0.098
R.I.= 0.001
B32 7 1 4 0.715
Table 14 - Hierarchical Single Arrangement of Financial Aspects for Telecom Operation Industry
B41 B42 Weight Consistency ratio
B41 1 1 0.500
R.I.= 0.000
B42 1 1 0.500
Seeing the consequence of hierarchical total arrangement, the distribution of proportion is relatively uniform without prominent value. Component of key activities plays the most significant part with a portion of 24.7%. For the following second and third place, the value of component of customer segments approximately doubles that of component of channels, which is at 21.5% and 11.4% respectively. Additionally, component of value propositions is assigned in fourth place with a value of 10%. The rest components don’t differ greatly and are all under 10%.
Table 15 - Hierarchical Total Arrangement for Telecom Operation Industry Bi Bij B1 0.010 B2 0.370 B3 0.345 B4 0.185 Hierarchical Total Arrangement Ranking B11 0.010 -- -- -- 0.010 4 B21 -- 0.582 -- -- 0.215 2 B22 -- 0.110 -- -- 0.041 8 B23 -- 0.309 -- -- 0.114 3 B31 -- -- 0.098 -- 0.034 9 B32 -- -- 0.715 -- 0.247 1 B33 -- -- 0.187 -- 0.065 7 B41 -- -- -- 0.500 0.093 5 B42 -- -- -- 0.500 0.093 5
Management consulting industry
Product and infrastructure management all occupy 35.1% of the importance. Both of them are regarded contributing to a competitive business model equally in management consulting industry by five participants. In the meantime, financial aspects and customer interfaces take up the third and forth place with values of 18.9% and 10.9%, respectively.
Table 16 - Hierarchical Single Arrangement of First Level For Management Consulting Industry
C1 C2 C3 C4 Weight Consistency ratio
C1 1 3 1 2 0.351
C.R.=0.003
C2 1/3 1 1/3 1/2 0.109
C3 1 3 1 2 0.351
C4 1/2 2 1/2 1 0.189
With respect to second level, different components play discriminating roles according to the suggestions of participants. Firstly, we observe the consequence of customer interfaces classification. They think highly of component of customer relationship, which is attached to a ratio of 64.8%. The rest part is divided by component of customer segments at 23% and component of channels at 12.2%. Secondly, on the subject of infrastructure management, component of key resources exceed half of the proportion at 55%. Additionally, component of key activities and key partnerships share the remaining portion at 31.3% and 13.8% respectively. Lastly, it is apparent that component of revenue streams is 5 times as important as component of cost structure. Consequently, component of cost structure only explains 16.7% of the importance within financial aspects.
Table 17 - Hierarchical Single Arrangement of Customer Interface For Management Consulting Industry
C21 C22 C23 Weight Consistency ratio
C21 1 1/3 2 0.230
R.I.= 0.002
C22 3 1 5 0.648
C23 1/2 1/5 1 0.122
Table 18 - Hierarchical Single Arrangement of Infrastructure Management For Management Consulting Industry
C31 C32 C33 Weight Consistency ratio
C31 1 2 4 0.550
R.I.= 0.069
C32 1/2 1 2 0.313
C33 1/4 1/2 1 0.138
Table 19 - Hierarchical Single Arrangement of Financial Aspects for Management Consulting Industry
C41 C42 Weight Consistency ratio
C41 1 1/5 0.167
R.I.= 0.000
C42 5 1 0.833
Observing the hierarchical total arrangement, we can see that several top-ranking components centralize most of the proportion. Specially, component of value propositions is endowed more than one of third taking up the first place. Component of key resources, key activities as well as revenue stream are all between 10% to 20%. The residual five components are all under 10% and exist little difference.
Table 20 - Hierarchical Total Arrangement for Management Consulting Industry Ci Cij C1 0.351 C2 0.109 C3 0.351 C4 0.189 Hierarchical Total Arrangement RANKING C11 0.351 -- -- -- 0.351 1 C21 -- 0.230 -- -- 0.025 8 C22 -- 0.648 -- -- 0.071 5 C23 -- 0.122 -- -- 0.013 9 C31 -- -- 0.550 -- 0.193 2 C32 -- -- 0.313 -- 0.110 4 C33 -- -- 0.138 -- 0.048 6 C41 -- -- -- 0.167 0.032 7 C42 -- -- -- 0.833 0.157 3
Furniture manufacturing industry
According to the viewpoints from 5 participants, they consider that customer interfaces and management infrastructure are equally important, which are endowed value of 35.9%. On the contrary, product seems to be the least important part revealed by a value at 8.2%. The rest portion of 20% goes to infrastructure management.
Table 21 - Hierarchical Single Arrangement of First Level for Furniture Manufacturing Industry
D1 D2 D3 D4 Weight Consistency ratio
D1 1 1/4 1/4 1/3 0.082
C.R.=0.069
D2 4 1 1 2 0.359
D3 4 1 1 2 0.359
As to the second level, prominent differences of values exist throughout all categories. Table 22 shows apparent preference to component of customer relationships, which takes up proportion over three quarters within customer interfaces. Regarding the components within management infrastructure category, component of key activities and key partnerships are expected to make a big difference in business model. Lastly, participants all suggest that component of cost structure is a key point to contribute to financial aspects. The fingers in table 24 show that the importance of component of cost structure is six times as much important as component of revenue streams, which are at 85.7% and 14.3% respectively.
Table 22 - Hierarchical Single Arrangement of Customer Interfaces for Furniture Manufacturing Industry
D21 D22 D23 Weight Consistency ratio
D21 1 1/7 1 0.108
R.I.= 0.01
D22 7 1 8 0.789
D23 1 1/8 1 0.103
Table 23 - Hierarchical Single Arrangement of Infrastructure Management for Furniture Manufacturing Industry
D31 D32 D33 Weight Consistency ratio
D31 1 1/5 1/4 0.101
R.I.= 0.003
D32 5 1 1 0.467
D33 4 1 1 0.433
Table 24 - Hierarchical Single Arrangement of Financial Aspects for Furniture Manufacturing Industry
D41 1 6 0.857
R.I.= 0.000
D42 1/6 1 0.143
Looking at the hierarchical total arrangement, component of customer relationships is the only one that over 25%, which makes it rank first. Followed by component of cost structure that is in the second place with a value of 17.1%. Next, component of key activities is slightly higher than component of key relationships, which is at 16.8% and 15.5% respectively. Finally, the remaining components ranking from 5 to 9 are all under 10%.
Table 25 - Hierarchical Total Arrangement for Furniture Manufacturing Industry Di Dij D1 0.082 D2 0.359 D3 0.359 D4 0.200 Hierarchical Total Arrangement RANKING D11 0.082 -- -- -- 0.082 5 D21 -- 0.108 -- -- 0.039 6 D22 -- 0.789 -- -- 0.283 1 D23 -- 0.103 -- -- 0.037 7 D31 -- -- 0.101 -- 0.036 8 D32 -- -- 0.467 -- 0.168 3 D33 -- -- 0.433 -- 0.155 4 D41 -- -- -- 0.857 0.171 2 D42 -- -- -- 0.143 0.029 9
4. Discussion
This research set out to test what business model components that are vital to specific industry in creating a competitive business model should be attached great attention to. As presented above,
objective description of statistical results has delivered some basic perceptions of discussion to this topic. In order to explore it deeply, some underlying meanings of the results should be dag out based on the vertical and horizontal analysis. In the following section, findings of this research are discussed, firstly conducting the vertical analysis to explain the relationship between highly ranked business model components and competitive business model in terms of different industries, followed by presenting the horizontal analysis to reveal whether different emphasis on business model components for particular industries are necessary. Subsequently, the implications for theory and practice are outlined. The section ends with an overview of the limitations and roads for future research.
4.1 Relationships between highly ranked components and specific industry
It is manifest that the four industries, namely, online apparel retail, telecom operation, management consulting, and furniture manufacturing differ greatly with each other in prior consideration of business model components for creating a competitive business model according to the outcomes of data analysis. Now that some components are considered crucial for specific industry, this vertical exploration tries to describe working mechanism of a highly ranked component contributing to the development of a competitive business model. Thanks to participants with knowledgeable background derived from China, relationship exploration is studied under the industrial circumstances of China. In the following part, basic and unique features of the four industries will be introduced, which serves as background information to the understanding of rankings. Looking into the consequences of rankings, an obvious trait should be noticed that mostly the top four components commit the majority of proportion and values of the rest five components are usually under 10% and close to each other. This indicates that discussion about the relationship between highly ranked components and specific industry is prone to focus on the top four business model components for each industry. Components that will be discussed for each industry are shown in table 26.
