3. Research design and methodology

"Building theory from case studies is a research strategy that involves using one or more cases to create theoretical constructs, propositions and/or midrange theory from case-based, empirical evidence" ([26], p. 25). Yin defines the case study research method as "an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used" ([27], p. 23). Some critics suggest case study research is useful only as an exploratory tool or for establishing a hypothesis, and some would claim it is unscientific [28]. When it comes to the validity of qualitative case study research, the validity refers to the extent to which the qualitative research results accurately represent the collected data (internal validity) can be generalized or transferred to other contexts or settings (external validity) [28]. Ultimately, each case can be viewed as a discrete experiment that could be repeated [29].

This chapter seeks to explore how acquisition-based dynamic capabilities underpinning a reinvention of business models in the M&A process. As objects of research, the author selected the company that is especially active and successful in online shopping and particularly in the online and offline grocery business. The unit of analysis is dynamic capabilities. In this research, two stages of research work will be involved. Firstly, to justify propositions, the author did the contextual content analysis which relied on an archival search that included financial statements, annual reports, internal documents, industry publications, and CEO statements to get at a microlevel understanding that really boosts data and the better understanding of the microfoundations of DC and building blocks of business models of acquirers and targets.

Even though a strategy-as-practice or process-based approaches in empirical qualitative research usually have an element of ethnographic or discursive analysis using primary data (sometimes in addition to secondary data, sometimes alone), the current chapter relied on an extensive search of secondary data. The key to secondary data analysis is to apply theoretical knowledge and conceptual skills to utilize existing data to address the research propositions. The major advantages associated with secondary analysis are the cost-effectiveness and convenience it provides [30]. A major disadvantage of using secondary data is that the secondary researcher did not participate in the data collection process and does not know exactly how it was conducted. However, the obvious benefits of using secondary data can be overshadowed by its limitations [31]. Original survey research rarely uses all of the data collected, and this unused data can provide answers or different perspectives to other questions or issues [30]. In a time where vast amounts of data are being collected and archived by researchers all over the world, the practicality of utilizing existing data for research is becoming more prevalent [30, 32].

categories), and identified compatibilities and complementarity of companies' business models. Then, the author has allocated operationalized components of the business model into each cluster of dynamic capabilities (sensing, seizing, and transforming) to demonstrate how acquisition-based dynamic capabilities underpinning the transformation of the business model. The second stage of research involves a demonstration of the development process of the new conceptual model of research by using illustrative content analysis finding and literature research outcomes. This empirical research helps to fill a gap in the literature which is primarily 75% theoretical and only 25% empirical—focusing on proving the existence of dynamic capability [43]. The chapter discusses and interprets the results of

The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon

Teece argues that individual corporate histories and illuminative case studies yield powerful insights to dynamic capabilities research. [5]. In a move that surprised the 2017 year, Amazon, the largest online retailer, announced its intention to purchase Whole Foods for \$13.7B in cash. Amazon had been dabbling with traditional brick-and-mortar activities for a few years already—from owning a few physical stores to running experiments like "Amazon Fresh" and later "Amazon Go." However, its competitors including Walmart were far ahead than Amazon with revenues of \$ 486 billion as compared to Amazon's \$136 billion [44]. Some have interpreted Amazon's move as a signal that the online giant is finally giving in and investing big in brick-and-mortar retail. How is this particular acquisition different from any other acquisition where the target firm is attractive because of its business channels and market reach? Most acquisitions are carried out to acquire these target firm's capabilities; how is the Amazon acquisition of Whole Foods different? The answer is this acquisition is carried out to acquire big data of more affluent customers with an interest in eating healthy and sustainable foods spending extra money to purchase. Digging deeper, though, it is clear that Amazon's real interest is in two things: first, the treasure trove of consumer data that comes with this acquisition; and second, Whole Foods private brand product [44]. The big data from Whole Foods customers are literally "rich." What exactly is in the Whole Foods data that Amazon would want? The answer is grocery buying habits and patterns. Preferences and correlations between purchases of different products and even different categories [44]. Jeremy Stanley, vice president of data science for Instacart, one of Amazon's competitors in the grocery space, recently told CNBC: "One of the wonderful things about groceries is that compared to other e-commerce purchases, groceries are habitual and frequent. People need groceries every week" [44]. Amazon can also use its process and technology expertise to take enormous costs out of the supply chain and store operations of Whole Foods while improving the in-store experience. Amazon has mastered the "test and learn" approach to large-scale innovation that most companies aspire to. Whole Foods provides Ama-

zon with an incredible platform for the transformation of industry [45].

between the dynamic capabilities of two merging businesses.

187

or acquisition) is provided by the degree of similarities and complementarity

Justification of proposition 1. The success of consolidative strategies (merger

The persistence of existing dynamic capabilities depends on the impetus for change (sensing), the strength of the perceived need to change (seizing), and the managerial capacity to integrate and recombine resources (transforming) as desired [46, 10, 7]. Zahra et al. [10] argue that the lack of success to solve a problem with current capabilities triggers the development and use of new dynamic capabilities.

the qualitative and explorative research in the next subchapters.

4. Data analysis and interpretation

DOI: http://dx.doi.org/10.5772/intechopen.85134

The aim of the content analysis of illustrative case study of Amazon's acquisition of Whole Foods at 2017 is to explicate the relationship between acquisitions-based dynamic capability and reinvention of acquirer business model and, thus, sustained competitive advantage. Content analysis is a qualitative research method that uses a set of procedures to classify or otherwise categorize communications [33]. Typically relying on archival data to extract criteria of interest to strategic management scholars, content analysis has aided in analyzing corporate strategies [34], organizational boundaries [35], new product development [36], organizational resources [37], strategic groups [38], and joint ventures [39]. Any source of communication such as shareholder letters, interview narratives, video records, speeches, or transcripts from recorded meetings of executives could be used by a strategy researcher as an effective data source for content analysis. It provides a good match theoretically between the information being assessed (how information is being content analyzed) and the context from which it is drawn (does the type of text being used as a source of content analysis data fit the propositions?).

Generally, three broad types of content methodologies exist [40, 41]: humanscored schema, individual word count systems, and computerized systems using artificial intelligence. Human-scored systems involve training of coders to classify text according to specific classification categories. In this system, the first step is a determination of what aspect of text will serve as the unit of analysis (word, phrase, sentence, paragraph, full text). Then, categories are developed for classification, and coding rules are developed for each category. In contrast to human-scored schemas, individual work count systems classify text into several semantically equivalent categories and then use frequency of an occurrence to determine the relative importance of each category in a text [33]. Finally, artificial intelligence systems incorporate features that consider the syntax and lexicon of words [41]. Thus, there is a mechanism to resolve words with more than a single meaning. For this study, the author has chosen human-scored systems and individual work count systems. Dynamic capabilities served as a unit of analysis.

To justify the first proposition, the author has chosen human-scored systems and classified text into three specific classification categories, namely, sensing, seizing, and transforming dynamic capabilities. When it comes to the format of the presentation, the author has adopted a conceptual frame developed by Teece [42]. The conceptual frame helped to unravel data in the text that the author has collected in search of similarities and complementarity of the micro-foundations of the dynamic capabilities of both companies. To justify the second proposition, the author applied an individual work count system, the text has been allocated within nine building blocks of the business model of both companies (as semantically equivalent

The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon DOI: http://dx.doi.org/10.5772/intechopen.85134

categories), and identified compatibilities and complementarity of companies' business models. Then, the author has allocated operationalized components of the business model into each cluster of dynamic capabilities (sensing, seizing, and transforming) to demonstrate how acquisition-based dynamic capabilities underpinning the transformation of the business model. The second stage of research involves a demonstration of the development process of the new conceptual model of research by using illustrative content analysis finding and literature research outcomes. This empirical research helps to fill a gap in the literature which is primarily 75% theoretical and only 25% empirical—focusing on proving the existence of dynamic capability [43]. The chapter discusses and interprets the results of the qualitative and explorative research in the next subchapters.

#### 4. Data analysis and interpretation

Even though a strategy-as-practice or process-based approaches in empirical qualitative research usually have an element of ethnographic or discursive analysis using primary data (sometimes in addition to secondary data, sometimes alone), the current chapter relied on an extensive search of secondary data. The key to secondary data analysis is to apply theoretical knowledge and conceptual skills to utilize existing data to address the research propositions. The major advantages associated with secondary analysis are the cost-effectiveness and convenience it provides [30]. A major disadvantage of using secondary data is that the secondary researcher did not participate in the data collection process and does not know exactly how it was

conducted. However, the obvious benefits of using secondary data can be

existing data for research is becoming more prevalent [30, 32].

Strategy and Behaviors in the Digital Economy

as a source of content analysis data fit the propositions?).

systems. Dynamic capabilities served as a unit of analysis.

186

overshadowed by its limitations [31]. Original survey research rarely uses all of the data collected, and this unused data can provide answers or different perspectives to other questions or issues [30]. In a time where vast amounts of data are being collected and archived by researchers all over the world, the practicality of utilizing

The aim of the content analysis of illustrative case study of Amazon's acquisition of Whole Foods at 2017 is to explicate the relationship between acquisitions-based dynamic capability and reinvention of acquirer business model and, thus, sustained competitive advantage. Content analysis is a qualitative research method that uses a set of procedures to classify or otherwise categorize communications [33]. Typically relying on archival data to extract criteria of interest to strategic management scholars, content analysis has aided in analyzing corporate strategies [34], organizational boundaries [35], new product development [36], organizational resources [37], strategic groups [38], and joint ventures [39]. Any source of communication such as shareholder letters, interview narratives, video records, speeches, or transcripts from recorded meetings of executives could be used by a strategy researcher as an effective data source for content analysis. It provides a good match theoretically between the information being assessed (how information is being content analyzed) and the context from which it is drawn (does the type of text being used

Generally, three broad types of content methodologies exist [40, 41]: humanscored schema, individual word count systems, and computerized systems using artificial intelligence. Human-scored systems involve training of coders to classify text according to specific classification categories. In this system, the first step is a determination of what aspect of text will serve as the unit of analysis (word, phrase, sentence, paragraph, full text). Then, categories are developed for classification, and coding rules are developed for each category. In contrast to human-scored schemas, individual work count systems classify text into several semantically equivalent categories and then use frequency of an occurrence to determine the relative importance of each category in a text [33]. Finally, artificial intelligence systems incorporate features that consider the syntax and lexicon of words [41]. Thus, there is a mechanism to resolve words with more than a single meaning. For this study, the author has chosen human-scored systems and individual work count

To justify the first proposition, the author has chosen human-scored systems and classified text into three specific classification categories, namely, sensing, seizing, and transforming dynamic capabilities. When it comes to the format of the presentation, the author has adopted a conceptual frame developed by Teece [42]. The conceptual frame helped to unravel data in the text that the author has collected in search of similarities and complementarity of the micro-foundations of the dynamic capabilities of both companies. To justify the second proposition, the author applied an individual work count system, the text has been allocated within nine building blocks of the business model of both companies (as semantically equivalent

Teece argues that individual corporate histories and illuminative case studies yield powerful insights to dynamic capabilities research. [5]. In a move that surprised the 2017 year, Amazon, the largest online retailer, announced its intention to purchase Whole Foods for \$13.7B in cash. Amazon had been dabbling with traditional brick-and-mortar activities for a few years already—from owning a few physical stores to running experiments like "Amazon Fresh" and later "Amazon Go." However, its competitors including Walmart were far ahead than Amazon with revenues of \$ 486 billion as compared to Amazon's \$136 billion [44]. Some have interpreted Amazon's move as a signal that the online giant is finally giving in and investing big in brick-and-mortar retail. How is this particular acquisition different from any other acquisition where the target firm is attractive because of its business channels and market reach? Most acquisitions are carried out to acquire these target firm's capabilities; how is the Amazon acquisition of Whole Foods different? The answer is this acquisition is carried out to acquire big data of more affluent customers with an interest in eating healthy and sustainable foods spending extra money to purchase. Digging deeper, though, it is clear that Amazon's real interest is in two things: first, the treasure trove of consumer data that comes with this acquisition; and second, Whole Foods private brand product [44]. The big data from Whole Foods customers are literally "rich." What exactly is in the Whole Foods data that Amazon would want? The answer is grocery buying habits and patterns. Preferences and correlations between purchases of different products and even different categories [44]. Jeremy Stanley, vice president of data science for Instacart, one of Amazon's competitors in the grocery space, recently told CNBC: "One of the wonderful things about groceries is that compared to other e-commerce purchases, groceries are habitual and frequent. People need groceries every week" [44]. Amazon can also use its process and technology expertise to take enormous costs out of the supply chain and store operations of Whole Foods while improving the in-store experience. Amazon has mastered the "test and learn" approach to large-scale innovation that most companies aspire to. Whole Foods provides Amazon with an incredible platform for the transformation of industry [45].

Justification of proposition 1. The success of consolidative strategies (merger or acquisition) is provided by the degree of similarities and complementarity between the dynamic capabilities of two merging businesses.

The persistence of existing dynamic capabilities depends on the impetus for change (sensing), the strength of the perceived need to change (seizing), and the managerial capacity to integrate and recombine resources (transforming) as desired [46, 10, 7]. Zahra et al. [10] argue that the lack of success to solve a problem with current capabilities triggers the development and use of new dynamic capabilities.

The research has explored the selected dynamic capabilities of the target's company and acquirer's company. The justification of the first proposition is given in Tables 2 and 3. The research has identified several similarities in the dynamic capabilities of two companies. Both companies were successful to sense emerging market demands, to seize opportunities by developing products and platforms, keeping leading positions. Thereby, the dynamic capabilities of sensing and seizing of two companies are quite similar.

supermarket which distinguishes itself by offering "highest quality natural and organic products." However, Whole Foods recent poor performance stems from a major strategic mistake they made about 4 years ago. Whole Foods in its current incarnation is a niche business that can only profitably sell "food for the 1%" but is trying to sell to everyone [45]. Therefore, Amazon can provide resources for future Whole Foods development, and at the same time, Amazon can develop their own

The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon

Justification of proposition 2. Business model's elements of both acquirer's and the target's companies can successfully fold into the new business model by means of acquisition-based dynamic capabilities and contribute to reduce cost, to create a new revenue stream, to deliver a new value proposition, and therefore to sustain

Having analyzed both Amazon and Whole Foods building blocks of business models, the research justified the second proposition, as shown in Tables 4 and 5. The acquisition-based dynamic capabilities helped Amazon to reinvent of building blocks of the business model as follows. Amazon sensed new key activities and new customers'segments for their business: Whole Foods customer has over \$1000 per month disposable income. Amazon has a better understanding of the customer than any other retailer. The Motley Fool estimates that over 80 million people are Amazon Prime members. With this big data, it is capable of building analytic models which can predict what these consumers will want, how much they will want, and

Amazon seized new key (idiosyncratic) resources by acquiring Whole Foods

To be successful in the offline retail food segment and in own-brand grocery stores, Amazon needs to have knowledge of traditional retailing and effective supply chain management in both factories and retail stores. Amazon has limited knowledge and experience in the offline retail environment. The company learned about food market through Amazon Fresh but now can learn about food stores or grocery manufacturing. Amazon has good supply chain management in a warehouse for online retail order, but now Amazon is certain whether this experience is transferable to an offline retail store. Hence, Amazon reconfigured new customers'

While Amazon's purchase of Whole Foods enables them to add a tremendous amount of data to their coffers, the true differentiator lies in the company's mastery of using data to better understand their customer's needs, predict shopping behaviour and generate longevity with its loyal customer base [47]. Therefore, Amazon transformed its customer value proposition, delivering new value to the clients of both companies and capturing new value for shareholders. "This partnership presents an opportunity to maximize value for Whole Foods Market's shareholders, while at the same time extending our mission and bringing the highest quality, experience, convenience, and innovation to our customers," John Mackey, Whole Foods CEO, said in a statement [49]. Given the jump in Amazon's stock price after the announcement, shareholder approval of the deal has virtually paid its total cost. When people suggest that Amazon has overpaid for Whole Foods, they completely miss this point [45]. Amazon also can help Whole Foods buy high-quality products more cost-effectively and thus improve gross margins while keeping customers satisfied. As results, Amazon can change cost structure as well as potentially increase revenue streams for mobile professional users and can result in a new competitive advantage. Adding Whole Foods selection of items to its Amazon Fresh grocery delivery service could give the company a competitive advantage against Peapod, FreshDirect, and Google, whose express delivery service now reaches almost 90%

logistic system, customer's base, and a key partners' network.

offline grocery business.

DOI: http://dx.doi.org/10.5772/intechopen.85134

competitive advantage.

when they will want it.

relationship and channels.

of the USA [50].

189

However, companies were not always successful in transformation or reshaping resources: Amazon's low grocery's margins, difficulties to deliver food considering their perishability nature, as well as Amazon Go store's technology faced problems. Regarding Whole Foods, there is a massive cost disadvantage compared to their traditional grocery competitors. There are also several complementarities of the dynamic capabilities of an acquirer and a target. One of Amazon's weaknesses is the huge cost of losses due to food items becoming bad, a problem which the company had never faced with toys and books. Even though the grocery business was approximately \$ 800 billion per the year 2016 in the USA alone [47], Amazon has limited knowledge and experience in the offline retail environment. That is why, for Amazon Fresh to be successful, the company needed to acquire more expertise in perishable grocery procurement. In contrast, Whole Foods becomes an organic


Source: Developed by author.

#### Table 2.

Dynamic capabilities of Amazon before the acquisition of Whole Foods.


#### Table 3.

Dynamic capabilities of Whole Foods before the acquisition.

#### The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon DOI: http://dx.doi.org/10.5772/intechopen.85134

supermarket which distinguishes itself by offering "highest quality natural and organic products." However, Whole Foods recent poor performance stems from a major strategic mistake they made about 4 years ago. Whole Foods in its current incarnation is a niche business that can only profitably sell "food for the 1%" but is trying to sell to everyone [45]. Therefore, Amazon can provide resources for future Whole Foods development, and at the same time, Amazon can develop their own offline grocery business.

Justification of proposition 2. Business model's elements of both acquirer's and the target's companies can successfully fold into the new business model by means of acquisition-based dynamic capabilities and contribute to reduce cost, to create a new revenue stream, to deliver a new value proposition, and therefore to sustain competitive advantage.

Having analyzed both Amazon and Whole Foods building blocks of business models, the research justified the second proposition, as shown in Tables 4 and 5. The acquisition-based dynamic capabilities helped Amazon to reinvent of building blocks of the business model as follows. Amazon sensed new key activities and new customers'segments for their business: Whole Foods customer has over \$1000 per month disposable income. Amazon has a better understanding of the customer than any other retailer. The Motley Fool estimates that over 80 million people are Amazon Prime members. With this big data, it is capable of building analytic models which can predict what these consumers will want, how much they will want, and when they will want it.

Amazon seized new key (idiosyncratic) resources by acquiring Whole Foods logistic system, customer's base, and a key partners' network.

To be successful in the offline retail food segment and in own-brand grocery stores, Amazon needs to have knowledge of traditional retailing and effective supply chain management in both factories and retail stores. Amazon has limited knowledge and experience in the offline retail environment. The company learned about food market through Amazon Fresh but now can learn about food stores or grocery manufacturing. Amazon has good supply chain management in a warehouse for online retail order, but now Amazon is certain whether this experience is transferable to an offline retail store. Hence, Amazon reconfigured new customers' relationship and channels.

While Amazon's purchase of Whole Foods enables them to add a tremendous amount of data to their coffers, the true differentiator lies in the company's mastery of using data to better understand their customer's needs, predict shopping behaviour and generate longevity with its loyal customer base [47]. Therefore, Amazon transformed its customer value proposition, delivering new value to the clients of both companies and capturing new value for shareholders. "This partnership presents an opportunity to maximize value for Whole Foods Market's shareholders, while at the same time extending our mission and bringing the highest quality, experience, convenience, and innovation to our customers," John Mackey, Whole Foods CEO, said in a statement [49]. Given the jump in Amazon's stock price after the announcement, shareholder approval of the deal has virtually paid its total cost. When people suggest that Amazon has overpaid for Whole Foods, they completely miss this point [45]. Amazon also can help Whole Foods buy high-quality products more cost-effectively and thus improve gross margins while keeping customers satisfied. As results, Amazon can change cost structure as well as potentially increase revenue streams for mobile professional users and can result in a new competitive advantage. Adding Whole Foods selection of items to its Amazon Fresh grocery delivery service could give the company a competitive advantage against Peapod, FreshDirect, and Google, whose express delivery service now reaches almost 90% of the USA [50].

The research has explored the selected dynamic capabilities of the target's company

However, companies were not always successful in transformation or reshaping resources: Amazon's low grocery's margins, difficulties to deliver food considering their perishability nature, as well as Amazon Go store's technology faced problems. Regarding Whole Foods, there is a massive cost disadvantage compared to their traditional grocery competitors. There are also several complementarities of the dynamic capabilities of an acquirer and a target. One of Amazon's weaknesses is the huge cost of losses due to food items becoming bad, a problem which the company had never faced with toys and books. Even though the grocery business was approximately \$ 800 billion per the year 2016 in the USA alone [47], Amazon has limited knowledge and experience in the offline retail environment. That is why, for Amazon Fresh to be successful, the company needed to acquire more expertise in perishable grocery procurement. In contrast, Whole Foods becomes an organic

and acquirer's company. The justification of the first proposition is given in Tables 2 and 3. The research has identified several similarities in the dynamic capabilities of two companies. Both companies were successful to sense emerging market demands, to seize opportunities by developing products and platforms, keeping leading positions. Thereby, the dynamic capabilities of sensing and seizing

Products Sensing Seizing Transforming Result in

Product Sensing Seizing Transforming Result in

Whole Foods becomes an organic supermarket which distinguishes itself by offering "highest quality natural and organic products"

In March 2017, Amazon announced Amazon Fresh Pickup, a drive-intype grocery store for Amazon Prime subscribers. In January 2018, Amazon started up offline retailing Amazon Go, first brick-and-mortar convenience food store on Amazon

Whole Foods attempted to expand to 1000 stores, it could either build stores more closely together or build lower-cost stores in areas that had more price-conscious consumers [32]

Grocery's margins were low, and its goods were difficult to deliver considering their perishability nature. Amazon Go store's technology faced problem in tracking over 20 people

Whole Foods has a massive cost disadvantage compared to its traditional grocery competitors [32]

Amazon set up a subsidiary Amazon Fresh, a grocery delivery service. Later Amazon decided to enter into food and consumable goods manufacturing through Amazon Elements, by establishing a partnership with TreeHouse Food Inc.

Dynamic capabilities of Amazon before the acquisition of Whole Foods.

Dynamic capabilities of Whole Foods before the acquisition.

of two companies are quite similar.

Strategy and Behaviors in the Digital Economy

Amazon sensed the need for having its footprint in the physical stores combined with online stores. Amazon saw a grocery business as an emerging business opportunity

Online and offline food stores

Source: Developed by author.

Source: Developed by author.

Whole Foods found that "where food comes from and how it is grown matter" (case)

Table 2.

Whole Foods

Table 3.

188


The reinvention of the business model of

Selection, sensing, and shaping new activities and new

• Research & Development • Low-cost structure

DOI: http://dx.doi.org/10.5772/intechopen.85134

• Revenues from product and service sales • Utility computing fees (for AWS) • Economy of scale

Amazon business model Dynamic capability

of Amazon

The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon

Acquisition based dynamic capabilities of Amazon.com in the reinvention of their business model by acquiring

Identification and seizing new resources and a new

Reconfiguration and transforming new customer relationship, new channels, and new customer value proposition. Result in new cost structure and new revenue Microfoundations of acquisition-based dynamic

Whole Food business model

• The operation and development of the online sales channel • The maintenance of IT and communications infrastructure

• The sale of various organic and fair-trade

products

Amazon did not just buy Whole Foods grocery stores. It bought 431 upper-income, prime-location distribution nodes for everything it does [44]. Amazon has mastered the "test and learn" approach to largescale innovation that most companies aspire to. Therefore, Whole Foods provides Amazon with an incredible platform for the transformation of an

This acquisition gives Amazon to reinvent and reengineer the process of buying, moving, and selling goods of Whole Foods. With 460 locations and a history of highly localized habits and preferences, Amazon will benefit from a trove of data that it can mine to write the future [52]. The brand Whole Foods is a good compliment to Amazon Fresh and Go and allow them to more aggressively target fresh food delivery to the at-home market. Amazon will ultimately be able to tailor the grocery shopping experience to the individual to better understand their needs, predict shopping behavior, and generate

longevity with loyal customers

Amazon is discovering the power of virtual and physical channels that interact seamlessly in support of the customer. Amazon has begun to test that logic with its venture into physical bookstores. Amazon is sensing more affluent customer with an interest in eating healthy and sustainable foods spending extra money to purchase. The proposed acquisition of Whole Foods catapults those efforts and provides extraordinary opportunities for experimentation in and execution of integrated retailing [45]

capabilities of Amazon.com

industry

Bridging perspectives together: the reinvention of the business model and micro-foundations of acquisition-based

Amazon.com

Building blocks of the business model

Revenue streams

Table 4.

Whole Food.

partnership

stream

Table 5.

191

Source: Developed by author.

dynamic capabilities.

customer's segments

Source: Developed by author

The Transformation of Business Models in Technology-Enabled M&A: A Case Study of Amazon DOI: http://dx.doi.org/10.5772/intechopen.85134

#### Table 4.

Building blocks of the business model

Customer segments (Scope)

Key activities (Scope)

Key partners (Resources)

Key resources (Resources)

Channels (Organization)

Customer relationship (Organization)

Customer value propositions

190

Amazon business model Dynamic capability

• Millennials • Global consumer market (North America, Europe, Asia)

Strategy and Behaviors in the Digital Economy

• Customer focused product development • Well-developed supply

• The business alliances and collaborations with logistic partners • Partnership with third-party sellers

• Amazon Web Services • Big data analytics • Productive employees • Physical warehouses

• Amazon.com • Country-specific online

• Fuse data, technology, and content to engage a loyalty program (their best customers) with geo-location reminders to incentivize store

portals • API (for AWS)

visits

Cost structure • Investing profit back

• Eliminating the checkout line • Real-time offers via mobile push notifications when customers are in store

> into the technology and the infrastructure

chain

of Amazon

Whole Food business model

• The more affluent customer with an interest in eating healthy and sustainable foods spending extra money to purchase

• Natural and organic foods supermarket chain operations • Production of packaged goods, prepared foods, body care, pet foods, and household

goods

• Supplier and

• Distribution & procurement centres • The network of 412 stores across 42 US states, as well as ten stores in Canada, and nine stores in the UK

• The network of physical retail outlets • Retail infrastructure, procurement, production, and distribution network

• A full range of products to its customers on a self-service basis through its online sales channel, which enables customers to browse products, place orders, and arranges deliveries

• The diverse catalog of premium products • The commitment to organic and sustainable

• The procurement of products and supplies

sourcing • Offering online shopping services on desktop and mobile platforms

procurement partners • Agriculture and sustainability partners • Whole trade certifier partners

Acquisition based dynamic capabilities of Amazon.com in the reinvention of their business model by acquiring Whole Food.


#### Table 5.

Bridging perspectives together: the reinvention of the business model and micro-foundations of acquisition-based dynamic capabilities.
