What is the impact of privacy concerns over consumer willingness to provide personal information for Omnichannel solutions?

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What is the impact of privacy concerns over consumer willingness to provide

personal information for Omnichannel solutions?

Supervised and guided by: Dhr E. Peelen

University of Amsterdam

Written by: Adriana Sora Ballesteros

Student ID: 11168331

Submitted on: June 30

th

₂₀₁₇

Executive Programme Business Studies

Marketing Track

Amsterdam Business School

Faculty of Business and Economics

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Atlanta, GA, June 30

th

2017

STATEMENT OF ORIGINALITY

This document is written by Student Adriana Sora Ballesteros 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.

Signature,

_____________________________

Adriana Sora Ballesteros

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Dhr E. Peelen has guided me in the completion of this research document from January until June

2017. I am grateful with him for his patience, insightful guidance and valuable feedback during this

journey. I would like to thank the University of Amsterdam and Laura Keessen, Program Manager

of the Executive Programme Business Studies program, who helped me navigate the complexities

of completing the program while moving from the Netherlands to a different country.

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Omnichannel, privacy, consumer’s perception, personal information, consumer journey

ABSTRACT

Customers are becoming more and more savvy in terms of shopping online. They are not only

waiting for product availability and better prices but also, they are expecting to have a better

customer experience and tailored offers to meet their needs. They expect be able to shop anywhere

at any time and to have flexible delivery options. With the significant growth of the e-commerce

industry during the last 20 years, a new buzzword has arisen: Omnichannel.

Moved by their desire to keep their customers and to enter new market segments, companies are

adapting their business to offer omnichannel solutions. This new strategy requires not only being

able to manage their operations in a way that they can deliver through multiple channels, but also

having an advanced knowledge of their customers and what they value. Privacy concerns have been

called as one of the most important issues of the information age when individuals have started

feeling concerned about their privacy. The objective of this research is to investigate the impact of

privacy concerns over consumer’s willingness to share sensitive information with firms that provide

omnichannel solutions. This document analyses the consumer’s perception towards the control and

management of their personal information and ends with a conclusion about how this concern

affects the consumer’s willingness to share personal information in order to purchase in

Omnichannel solutions.

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CHAPTER 1

1. INTRODUCTION

In the era of disruption technology, companies are constantly looking for new ways to create

customer value. The implementation of new channels that allow customers to acquire products and services

anywhere and anytime has turned into company's top priority. “Successful companies will engage customers

through omnichanel retailing: a mashup of digital and physical experiences” (Rigby, 2011). Retailers want

to exceed customer expectations, and nowadays consumers are becoming more exigent and demand better

alternatives to buy. However, buying a product does not imply going to a physical store to interact with the

company. Many buyers have become accustomed to using various distribution channels at different stages

of their decision-and-shopping cycles (Pantano, 2015). Consumers not only want to buy at the store, mobile

or laptop, but also, they want to have valuable experiences buying through these channels. Many researches

(Gao, Su, 2016; Verhoef, Kannan, Inman, 2015) agree that Omnichannel is the future of e-commerce

shopping, influencing shoppers to move through channels in their process of searching and buying for a

product. Omnichannel implies combining online and physical channels in one seamless experience,

consumer data integration, security and seamless payment solutions.

Previous research suggests that the implementation of Omnichannel enables competitive advantage

(Grewal, Comer, & Mehta 2001), creates customer satisfaction (Neslin, 2009) and improves process

(Hoogveld & Koster, 2016). A study from Harvard Business Review (Sopadjieva, 2017) shows that

Omnichannel retailing works because it creates customer satisfaction and adds more value to the business.

If a company wants to implement Omnichannel strategy to create a seamless experience for their customers,

it needs to pay special attention to synchronizing their operating processes and aligning the experience that

they provide through all the channels in order to present only one offer to the customer. For instance, the

idea that the customer buys a product online with the option to pick-up at the store and in case the product

does not fit customer expectations and offering the alternative to return the product without any cost. This

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company that allows having a better experience during the purchase process. With Omnichannel solutions,

the big challenge is to find seamless solutions for both customer’s experience and internal processes.

Omnichannel implies that customers need to share personal and sensitive information in order to

receive personalized offers. To what extent can privacy concerns offset the positive effect of receiving

personalized offers? Does offering omnichannel experiences eliminate privacy concerns? Does loyalty and

the expectation of having a seamless experience eliminate privacy concerns? Is the customer willing to share

private information in exchange of improving their user experience?

The above questions, call for further research. The purpose of this paper is to analyse multichannel

and omnichannel strategy solutions as starting point to understand consumer attitude towards today's

shopping environment. This paper analyses the impact of privacy concerns in omnichannel solutions

exploring consumer perceptions around different touch points towards a firm, evaluating customer

experience and taking into account how privacy concerns affect customer final decision before and after the

interaction with omnichannel solutions. Furthermore, the proposed research question is: What is the impact

of privacy concerns over consumer willingness to provide personal information for Omnichannel solutions?

The theoretical model, variables to consider and hypothesis to be tested are based on the literature

review that takes into account elements such as consumer experience, customer journey and privacy construct

that impact privacy concerns on consumer’s final decision to purchase a product or service in firms that offer

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CHAPTER 2

2. LITERATURE OVERVIEW

This chapter provides elements to understand the impact of privacy concerns on consumers when

interacting with Omnichannel solutions through a literature overview that introduces the most relevant

elements around the topic and serves as the basis to develop a conceptual framework that answers the

research question. The literature review explains the differences between single, multi and Omnichannel

consumer touch points, the consumer experience, journey, and ends with the analysis of the literature privacy

concerns. Literature available today has extensive material about the development of multichannel strategies

and their impact over consumer behaviour; however, the impact of privacy concerns towards omnichannel

has not been extensively analysed yet and requires further analysis to answer if consumers care about privacy

when interacting with omnichannel solutions.

2.1 From single channel to Omnichannel

Historically, companies and consumers have been interacting through only one channel: the

bricks-and-mortar retail store, catalogues or advisor as the only mechanism to buy products. (Blattberg, 2008).

With the introduction of the Internet around 1950s, new mechanisms were created to allow effective ways

of communication with customers: computers, mobile devices, call centers, social media, catalogues, retail

stores, among others.

Neslin (2006) defines a channel as a customer touch point or a way through which a firm and

customer interact in the negotiation. Examples of single channels interaction are selling over the phone or

selling on a physical store but not both at the same time. In 1979, the first e-commerce idea started to appear

when Michael Aldrich demonstrates the first online shopping system (Tkacz, 2009). From that moment, a

new way to make business started to arise and a new channel to communicate with customers emerged.

Multichannel retailing is the set of activities involved in selling merchandise or services to consumers

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information on a company website and then to buy it at the store, could be considered part of multichannel

mechanism, allowing consumers to gain power using different channels to search, to compare prices, and to

buy the ideal product or service. Companies such as Albert Heijn, Amazon, Walmart and Apple are leading

multichannel mechanisms allowing customers to create shopping experiences. “When interacting with a particular channel, a consumer can engage in a variety of behaviours such as searching for product

information, product selection, transacting the purchase, and experiencing a service or consuming a product” (Dholakia, 2010).

Research about multichannel strategies has concluded that firms need to implement new strategies

in order to gain acceptability with its stakeholders (DiMaggio & Powell 1983), to improve services and to

gain competitive within the industry (Grewal, Comer, & Mehta 2001), to reduce costs and to improve revenue

in services (Dutta, Heide, Bergen, & John 1995). But, is it enough for companies to offer multichannel to

create customer value? Offering a customer experience implies not only offering channels to search or to

buy, but also to connect and to integrate one channel to another during the entire purchase journey. In other

words, an Omnichannel solution needs to be created: multiple channels with one single customer view that

allow to create seamless experiences across those channels.

2.2 Omnichannel solutions

As discussed in the previous section, multichannel strategy allows companies to create customer

value through using different channels to search, to purchase the product and to evaluate the purchase post

completion. However, customers are looking for new experiences dynamically and continuously in order to

extract more value. For decades, the online channel has been considered as a separate business line.

Nonetheless, many companies have realized the need to integrate their existing channels to enrich customer

value proposition and improve operational efficiency. Shankar (2002) advocated that a seamless shopping

experience leads to create customer satisfaction and to retain valuable customers, which can be achieved by

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(2016) Omnichannel strategy seeks to provide customers with a seamless shopping experience through all

available shopping channels.

Figure 1. Differences between single, multi and Omnichannel

Adapted from: Omni-channel a Deloitte point of view

Figure 1 clarifies the differences between single, multi and Omni-channel point of view. Verhoefa

(2015) defines Omnichannel management as the synergetic management of the multichannel and customer

touch points, in such a way that the customer experience across channels and the performance over channels

is optimized. Among Omnichannel benefits for both customers and firms, to allow customers to buy online

and pick up in store (BOPS) is considered the most important one (Gao, 2016 and Forrester Research 2014).

According to this research, 39% of consumers are unlikely to visit a company store if the online store does

not provide physical store inventory information. In order to implement this strategy, the firm requires to

design operational strategies such as price among channels (Su, 2007), supply chain performance (Su &

Zhang 2008) and channel integration (Hoogveld, 2016). Researchers agree that the integration of customer

data across channels is fundamental for an Omnichannel strategy. “Creating and maintaining cross-channel

databases and understanding individual preferences for channel use can help firms create superior

multichannel shopping experience and this can be achieved by using Customer Relationship Management

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Gao & Su (2016), have fulfilled a study about Omnichannel strategy:

buy-online-and-pick-up-in-store (BOPS) and they have found out that BOPS attracts customer demand through information and a

convenience effect. Products that are available for store pick up must be in stock and with this assurance,

customers are more willing to visit the store. It is interesting that when consumers perceive that online and

store-based channels are integrated, they are less likely to switch retailers in the case of stock-outs in one

channel. (Pentina, 2009).

Multichannel is moving towards Omnichannel solutions, which implies to pay attention to vital areas

such as customer service, higher availability of the product and most important customer data integration.

2.3 Consumer interaction in Omnichannel solutions

The following section evaluates consumer experience through customer journey, which explains

how customer evaluates each step in the omnichannel solution.

2.3.1 Consumer behavior

According to the American Marketing Association, consumer behaviour is defined as “the dynamic interaction, of affect and cognition, behaviour and the environment by which human begins conduct the

exchange aspects of their lives”. In other words, consumer behaviour implies affect (such as emotions, feelings, and attitudes), cognition (such as knowledge, beliefs, and evaluations) and environment (such as

social stimuli and physical stimuli).

Verhoef, Neslin & Vroomen (2007) have distinguished between purely search attributes (for

example, ease of gathering information), purely purchase attributes (for example, speed of obtaining the

product), and attributes that apply for both search and purchase (for example, product assortment). The

attractiveness of each channel influences the process of searching, purchasing and the positive/negative

evaluation towards each channel together with social norms influence the final intention to behave.

In 1991, Ajzen proposed a conceptual framework called the theory of planned behaviour, that

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proxy measure of actual control and a measure of confidence in one’s ability. According to Ajzen, perceived behavioural control is formed by control beliefs that facilitate or inhibit factors multiplied by the power of

those factors to inhibit/facilitate the behaviour in question. In other words, meaning that person believes is

attainable with his/her power to behave.

Figure 2. Theory of planned behaviour

Source: Ajzen, 1991

The theory of Planned behaviour has been used by many authors to analyse consumer behaviour in

ecommerce such as adoption of mobile technology (Luarn & Lin, 2005), consumer attitude (Liao & Cheung,

2001) and customer satisfaction in the use of e-service (Liao, Chen & Yen, 2007).

Armitage & Christian (2003) analysed the theory of planned behaviour and argued that perceived

lack of correspondence between attitude and behaviour led to examination of variables either moderated

(attitude strength) or mediated (behavioural intentions). Applying this theory in the context of omnichannel

shopper behaviour, positive beliefs influence attitudes towards a specific channel (either to search or to buy

a product). Perceived behavioural control, makes an individual evaluates which channel is appropriate for

her/him and creates a belief that helps to behave in a specific way. Finally, subjective norms are formed by

what other people think as an appropriate behaviour, for example, family or friend’s opinions about

experiences searching information or buying a product are more important compared with strangers’ opinion.

2.3.2 Customer experience

Lemon (2016) said that creating customer experience should be considered one of the top company's

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(2014) viewed customer experience as one of its most important research challenges, because of the

increasing number and complexity of customer touch points and the belief that creating strong, positive

experiences within the customer journey will result in improvements to the bottom line. This can only be

achieved by improving performance in the customer journey at multiple touch points (i.e., higher conversion

rates) and through improved customer loyalty and word of mouth.

Variety of definitions of customer experience exist in the literature. Earlier literature defined

customer experience as “what people desire are not products but satisfying experiences” (Abbot, 1955). According to Lemon (2016), in the 80’s some authors recommended to analyse consumer behaviour that

recognized emotional aspects of decision making. Most recently literature concluded that consumer

experience is a multidimensional construct that involves cognitive (think), emotional (feel), behavioural

(act), sensorial (sense), and social components (relative experiences) (Verhoef, 2009). Now, applying these

concepts in a retiling context, Grewal, Levy and Kumar (2009) suggested that customer experience could be

categorized along the lines of the retail mix such as search, price, experience, promotions.

Limayem (2000), investigated factors that affect consumer online shopping and concluded that

perceived consequences from the Theory of Planned Behaviour, have both direct and indirect effect on

intentions. For that reason, understating customer needs and offering them integrated solutions empowers

firms to offer valuable customer experiences in terms of price, product availability and promotions that

incentives the intention to use of channels to resolve specific needs. This is consistent with Rowley (1996)

study that most customers expect to be able to compare products, their prices from different channels and

online stores.

In general, customer experience includes every touch point between the customer, the product or

service and the firm. According to Blattberg, Byung-Do, and Scott (2008), a single customer view will help

the firm to understand the interaction of customers with its channels at all stages of the customer decision

process. The strategy to manage customer experience represents an exchange between the firm and its

customers that satisfies customer needs leading to increased customer satisfaction and customer loyalty

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2.3.3 Customer journey

Customer preferences are fundamental to determine which channel to use. For example, a customer

could first search for product information in one channel (e.g. Internet) and based on his/her previous

experiences decide to buy the product through another channel.

Literature highlights the follow customer behaviours that are influenced by Omnichannel solutions:

(1) Cross-buying: defined as the quantity of different product categories that a customer has bought from

the firm. Customers with high degree of cross-buying would be inclined to purchase across multiple channels

and will be more familiar with the company (Kumar, 2005). (2) Frequency of web: customers with higher

frequency of web-based interactions will have higher likelihood of multichannel shopping (Kumar, 2005).

(3) Customer tenure: Customers who have been purchasing from a firm for a long time are familiar with

the brand and the firm and this familiarity reduces the risk perceived in making purchases (Schoenbachler,

2002). (4) Purchase frequency: Customers who complete purchases more frequently are expected to

increase trust with the company and will have higher likelihood of multichannel shopping (Kumar, 2005).

(5) Returns: if a company resolve customer’s problems, these customers will turn loyal to the brand and to

the company (Kumar, 2005). However, it is important to take into account that customer with high levels of

product return, tend to purchase less frequently and have a reduced motivation to buy products through

multiple channels (Schoenbachler, 2002).

Offering multiple channels to interact results in more complex customer journey (Lemon, 2016).

Experts have found individual variables that describe customers who use multiple channels rather than single

channels: purchase frequency and returns (Blattberg, Byung-Do & Scott, 2008), level of cross buying (Kumar

& Venkatesan, 2005), shopper income and loyalty (Blattberg, 2008). In more details, Blattberg (2008)

explains his framework of customer journey (Fig 3): (1) recognizes a need, then (2) searches for product

information that addresses the need, then (3) purchases the product and then (4) seeks after-sales service.

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this process is guided by the customer’s attitudes towards various channels, by firm’s marketing efforts and

by the outcomes of precious states in the process.

Fig 3. Customer Journey

Source: Blattberg (2008)

Lemon (2016) examined customer experience during the customer journey or purchase phases. The

author focussed in three stages: (1) pre-purchase which encompasses customer interaction with the brand,

firm and its environment. This phase is characterized by need, recognition, search and consideration (Hoyer,

1984). (2) purchase phase is characterized by consumer behaviours such as choice, ordering and payments.

Lemon (2016) explains that marketing efforts influence drastically in consumer final decision through

environment, choice overload, purchase confidence, and decision satisfaction. The final phase in consumer

journey is (3) post-purchase covers costumer’s experience after purchase, service recovery, decision to

return the product and repurchase. This phase will influence future consumer experience with the product

and the firm.

To summarize, offering omnichannel solutions implies understanding how customer think and being

able to map customer journey among all channels. An analysis of the consumer research-behaviour is

necessary prior to the analyses of the impact of privacy concerns in each step of the customer journey due to

the consumer’s attitude towards each of the steps in consumer journey.

2.3.4 The research-shopper phenomenon

According to Verhoef (2007), three factors explain research shopping: (1) Attribute-based

decision-making: the consumer perception is that one channel (e.g Internet) excels on attributes that

determines search, while the other one (e.g store) excels on attitudes that drives purchase. (2) Lack of

channel lock-in: the author hypothesizes that the Internet has relatively low lock-in, because consumers

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“information source,” not a “shopping venue”. (3) Cross-channel synergy: searching on Channel A enhances the experience of purchasing on Channel B.

Omnichannel enable user experience that produce satisfaction among its users. A Harvard Business

Review study reveals that among 46.000 customers who made a purchase during a 14-month period, 73% of

them used multiple channels during their shopping journey. This study confirms that the more channels a

customer uses, the more valuable they are. The Omnichannel customer is expecting to have valuable

shopping experiences, willing to spend more and to become more loyal.

Today’s literature focuses in understanding how costumers react to diverse channels marketing strategies, price promotions, store environments and diverse mechanisms to satisfy customer needs.

However, there is a need to understand how privacy concerns may affect interactions between both parts in

omnichannel solutions. In order to receive valuable experiences, customers need to share their personal

information and in terms of privacy, consumers have become more aware of what is happening with their

personal information. Numerous surveys (Equifax-Harris, 1995, 1996) indicate that consumers are aware of

their privacy and how companies use their information. This fact emerges the next question: does the

customer agree with the idea that she/he needs to share its own personal information in exchange of having

a better user experience? Could their privacy concerns change when interacting with omnichannel solutions?

2.4 Privacy concerns

Petrison and Wang (1995) found that privacy includes lot of dimensions such as (1) controlling

access to information about oneself; (2) being alone; (3) not being bothered by others; (4) living away from

others. Bellman, Johnson, Kobrin & Lohse (2004) explained that the primary dimension of privacy that

causes concern among customers is informational privacy. Concerns about privacy are not a new topic. Firms

collect and analyse customer data in return of providing them with more appropriate products, services and

offers. According to Acquisti (2015), both firms and individuals can benefit from the sharing information

and from the application of increasingly sophisticated analytics to larger and more interconnected databases.

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them (Blattberg, Byung-Do, Scott, 2008). Could privacy concerns affect the omnichannel interaction

between firms and customer?

2.4.1. Privacy construct

According to Tavani (2007) some authors have argued that is more useful to see privacy in terms of

interest (to keep information protected) rather than a right. For other authors, privacy is a form of power

about controlling the information about ourselves. Prosser (1960) created a framework that identified four

legal torts invasions of privacy: (1) false light, explained as individual false public portrayals, (2)

appropriation, using a person identity or image without permission, (3) disclosure, embarrassing an

individual with private facts and finally (4) intrusion, invading a person relationships. Based on Prosser

(1960), Phelps (2000) holds that consumers and marketers perceive privacy concerns in terms of information

control: E.g., who has access to my personal data? How personal data is used? and what volume of marketing

campaigns arise from the use of personal data?

Privacy is a right to determine when, how, and to what extent information about ourselves is

communicated to others (Westin, 1967). People have a need for intimacy and protection from social

influence and control. However, studies have found that there is a large discrepancy between people concerns

and their privacy behaviour.

In order to measure the first hypothesis, the Westin (1991) privacy categorization will be used in this

research to analyse results and to categorize participants according to their privacy concerns. The author

created a survey (see appendix 1) asking people about their privacy concerns and based on their answers, He

categorized them into three groups:

The privacy Fundamentalists: “Fundamentalists are generally distrustful of organizations that ask

for their personal information, worried about the accuracy of computerized information and additional

uses made of it, and are in favour of new laws and regulatory actions to spell out privacy rights and

provide enforceable remedies. They generally choose privacy controls over consumer-service benefits

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The Pragmatic: “They weigh the benefits to them of various consumer opportunities and services,

protections of public safety or enforcement of personal morality against the degree of intrusiveness of

personal information sought and the increase in government power involved. They look to see what

practical procedures for accuracy, challenge and correction of errors the business organization or

government agency follows when consumer or citizen evaluations are involved. They believe that

business organizations or government should "earn" the public's trust rather than assume automatically

that they have it. And, where consumer matters are involved, they want the opportunity to decide whether

to opt out of even non-evaluative uses of their personal information as in compilations of mailing lists”.

The Unconcerned: “The Unconcerned are generally trustful of organizations collecting their

personal information, comfortable with existing organizational procedures and uses are ready to forego

privacy claims to secure consumer-service benefits or public-order values and not in favour of the

enactment of new privacy laws or regulations”.

A firm that seeks to offer Omnichannel solutions needs to be prepared to synchronize all different

touch points. According to Phelps (2000), “consumers are concerned about what companies know about

them, how companies obtain and use personal information, and the accuracy of the information used”. The

author examined consumers’ information concern-behaviour consistency and their perceptions regarding to

the exchange of information with firms. In his research, Phelps found that there is a strong relationship

between consumer’s privacy concerns over the way firms use personal information and respondent’s

information-related beliefs and behaviours. Extending this effort to identify concerns on personal

information, this research predicts that:

H1. Consumer’s original privacy concerns influence consumer perception about how companies should

manage customer’s information and how much they are willing to check

Consumer privacy concerns appears when a person limit its accessibility and control the release of

information about itself, and on the other hand, invasion of privacy occurs when control is lost or unwillingly

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moderator of consumer privacy concerns. Culnan (1995) and Milne (1997) on the other hand suggested that

marketers should view customers’ exchange of personal information as a social contract. Based on this, Phelps (2000) underlines two assumptions under privacy social contract: (1) most consumers would like to

have more control over their personal information and (2) giving consumers more control over how

information about them is used will alleviate their privacy concerns. Therefore, a hypothesis to be exanimated

is:

H2. Consumer’s original privacy concerns have a direct positive impact over their desire to keep control on

how their personal information is managed

Omnichannel strategy comes with many benefits for customers: e.g order online and pick up at the

store (Gao & Su, 2016), one single customer view (Blattberg, Byung-Do, Scott, 2008) and the creation of

user experience (UX). The last hypothesis has been formulated to explore the impact that privacy concerns

have over the desire to keep control over personal information. As it was discussed, Omnichannel allows

customers to receive benefits for them through the design of personalized offers and rewards program, access

to variety of channels and more. Does the interaction with Omnichannel solutions reduce consumer privacy

concerns?

Customers need to share personal information in order to receive personalized offers for them and

to be able to create seamless shopping experience. This brings an important question to analyse: To, what

extent the customer is able to waive its privacy in order to obtain user experience? According to Goodwin

(1991), the high level of consumer privacy concern appears to have had little discernible impact on

consumer’s' shopping behaviours. Most consumers are willing to give up some of their privacy to participate in a consumer society.

2.4.2. Privacy Paradox

With the internet revolution, people started to communicate through emails, text, social media and

with the development of the e-commerce, people have started to purchase products and services online and

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Omnichannel customers are demanding convenient and multiple variety of payments solutions, more

alternatives to purchase and different ways to pick up the product. However, consumers have worried for

years about their personal data and how are used by the government and businesses (Udo, 2001).

According to Westin (1991), when the participants were asked about their privacy, they defined

themselves as the first category (fundamentalists) caring about privacy and expressing fear about losing

control of their information. However, later studies have found that people did not care about their privacy

and share sensitive information in exchange of receiving discount to purchase a determinant product.

According to Acquisti (2015), this discrepancy between attitudes and behaviours is called “privacy

paradox”. The author explained that privacy behaviour is the result of a “calculus” of cost and benefits:

people will reveal sensitive information (cost - abstract), if there is an immediate gratification (benefit -

tangible).

In the context of present research, a third hypothesis to develop is related with consumer desire to

keep control over its personal information:

H3. Consumer’s original privacy concerns have a direct positive impact over their desire to keep control on

how their personal information is managed but the interaction with a firm through different channels will reduce privacy concerns

Previous literature has confirmed that consumers are concerned about their privacy and has explained

that consumers want to know how firms manage their personal data. However, when people interact with

solutions for their needs, they will be willing to share information and their privacy concerns will be reduced.

According Acquisti (2015), privacy context-dependence means that a person can exhibit extreme concern to

apathy about privacy. For example, social expectations can affect beliefs, regarding what is privacy and what

is public; the presence of government regulation has shown to reduce consumer concern and observing other

people reveal information increase likelihood that one will reveal its information. The same author found

that consumers do not respond to a marketing offer in order to avoid giving information that can be used to

identify and classify them. It would also arise any time a consumer uses cash rather than some other preferred

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Therefore, another hypothesis needs to be exanimated based on consumer willingness to share

information when interacting with firms that offer omnichannel solutions:

H4. Consumer’s original privacy concerns have a negative effect over Consumer’s willingness to share

information with the firm

2.4.3. Consumer purchase intention

So far, literature review has analysed when firms collect personal information about customers,

creates privacy concerns. Customers need to feel comfortable when interacting with those firms to reveal

information, which in turn helps the firm better serve the customer (Schoenbachler, 2002).

In the last two steps on the customer journey, purchase and post purchase are fundamental part in

any omnichannel strategy. According to Lemon (2016) the purchase step is characterized by behaviours such

as choice, ordering, and payment. The purchase phenomenon has been received significant attention in the

marketing literature about how marketing strategies or environment and atmospherics can influence the

purchase behaviour. However, there is lack in literature that explores how purchase behaviour could be

affected by privacy concerns. Phelps (2000), justified that firms can influence consumer willingness to

purchase explaining consumers how they are going to use their information and the benefits to reveal

information. He concluded that marketers that incentives to provide more consumers control may be able not

only to cover the cost incurred in developing and maintaining customer’s programs but also to increase

profits. For that reason, is imperative to analyse consumer purchase intention in every step on the customer

journey to analyse customer perception towards its privacy concerns in every step when interacting in

omnichannel solution and to be able to answers questions such as what will the impact of privacy concerns

on consumer purchase intention when interacting in omnichannel solution. Can consumer purchase intention

be modified if the person feels control over its personal information? These questions are pillars to develop

the last hypothesis in this research about consumer intention to purchase a product in every step of the

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H5. Consumer’s original privacy concerns don’t have a direct impact over consumer willingness to

purchase

Bellman, Johnson, Kobrin & Lohse (2004), explained that when customers finally trust online firms

with their personal data, those firms will be able to make “the most of the possibilities offered by global database marketing”. The authors concluded that in order to provide a high level of trust, companies will need to customize their information collection and management strategies to match customer privacy

concerns. One potential driver of data driven relationship marketing is trust (Milne, Rohm, & Boza, 1998).

Omnichannel strategies are dependent on customer information to target customers’ desired products and to

offer them seamless customer experience through all available shopping channels. Bellman, Johnson, Kobrin

& Lohse (2004), found that firms that can build long-term customer relationship through trust development

should foster greater loyalty and in the long term, firm profitability. However, as it was discussed before,

consumer perception towards the use of personal information seem to vary depending on the situation making

challenging for firms to create mechanisms to build trust among customers. Who believe they are asked to

provide excessive amount of personal information, have less control over what happens to the information

collected (Nowak & Phelps, 1992) and many of them express concern about the ways companies use personal

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CHAPTER 3

3. METHODOLOGY

This chapter describes the methodology used to tests hypotheses based on the conceptual model, and

key constructs.

3.1 Conceptual model and key constructs

Based on the previous literature and the analysis of the impact of privacy concerns in omnichannel

experiences, the theoretical framework (figure 4) has been created in order to respond the following research

question: What is the impact of privacy concerns over consumer willingness to provide personal

information for Omnichannel solutions?

Figure 4. Theoretical framework - Privacy concerns in Omnichannel solutions

According to the previous literature, privacy concerns might have a direct impact on consumer

behavior towards a consumer decision to purchase a product or service. The interaction between the

customer, the firm and different touch points may have an impact on privacy concerns and allow customers

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that reason, the research elaborates the theoretical framework based on the following constructs: consumer

privacy concerns (IV), consumer perception towards collecting personal information (DV), consumer

control over personal information (DV), consumer willingness to share personal information (DV) and

consumer purchase intention (DV).

According to Fazio (1990), an attitude is viewed as an association in memory between a given object

and one's evaluation of that object. Ajzen (1981) on the other hand confirmed that attitude strength is

considered as a key moderator variable because stronger attitudes are likely to be more predictive of people’s

behavior than weak attitude. The willingness to share sensitive information depends on the situation on the

purpose of the information use. Most consumers are willing to share personal information to participate in a

consumer society (Phelps 2000). Finally, Lemon (2016) concluded that customer experience is a

multidimensional construct that focus on customer’s cognitive, emotional, behavioral, sensorial and social responses to a firm’s offerings during customer journey. These variables are fundamental to test the hypothesis that are based on the theoretical framework.

Consumer privacy concerns and control over the information

The first construct is based on Westin (1991) methodology that created the “General Privacy

Concern Index” that divides participants into three groups: “the privacy fundamentalist”, “the pragmatic”, “the unconcerned”. Many researches have been using these privacy indexes as a benchmark to test privacy concerns in different sceneries. According to his studies, many people declared to be “privacy

fundamentalist” caring about their privacy and concern to lose control of their personal information.

Consumer perception towards collecting personal information

Westin (1967) argued that collecting personal information process arises concerns in consumers.

This variable will be tested based on the concern that extensive amounts of personal data are being collected

and stored by firms. The process used in this study include the methodology by Smith, Milberg and Burke

(1996) and Bellman, Johnson, Kobrin and Lohse (2004) which analyze the effects of collecting personal

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Consumer willingness to share personal information and willingness to purchase

The third variable will be measured using Phelps, Nowak and Ferell (2000) research about privacy

concerns and willingness to share personal information. An 11-page survey was created and tested factors

such as “Control over information use”, “Type of personal information”, “Shopping benefits”.

3.2 Research method and survey distribution

This research seeks to analyse if privacy concerns affect customer willingness to provide personal

information, which is the fundamental part on in any Omnichannel strategy. For this purpose, a survey has

been created to test the hypothesis previously raised. The target group will be asked about privacy concerns

and willingness to share personal information based on four scenarios. For instance, the target group will be

online consumers between 18 and 60 years old that interact continuously in different shopping channels such

as online, store and smartphones. The survey will use the “Likert-type scale” and will be measured on a scale

of 1 (strongly disagree/ very concerned) to 5 (strongly agree/ Not concerned at all). Participants were not

allowing to entry data lower than 1 or higher than 5 scale.

The survey contains 4 scenarios that are related with the design of the customer journey: 1.

Recognition of a need, 2. Search product information, 3. Purchase product and 4. After sales service. For

each scenario, the survey explains a situation related on the customer journey and asks questions according

to the respective variable to analyse:

1. Recognition of a need: “You are planning to buy a new computer so you have started to

browse for options on internet using websites such as bol.com, amazon.com mercadolibre.com as well as

your preferred brand’s website. A couple of minutes later, you log into your Facebook account and see advertising for computers with the same characteristics that you are looking for, but at better prices.”

2. Search product information: “You have selected a good deal and now you are ready to

purchase your new computer. The company that you have selected offers you options to interact across

different channels. For example: in the store, on a website (desktop/laptop), or in an app (on your

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3. Purchase product: “Now you are buying your new computer and among all the channels,

you have selected to purchase the product on the company website. The process to purchase the product

consists in five steps: (1) Select the product – (2) Fill in your delivery address, plus contact details – (3)

Select payment method – (4) Sharing payment details – (5) Confirmation

4. After sales service: “Now that you have bought the computer, the company offers you the

option to ship the product to your home or to pick it up at the store. In order to have access to those

privileges, the company is asking you to fill out the following information to set up an account. So that

next time you can buy products from them on an easier way, because they already have some of your

information.”

The survey (see appendix 2) consists in 28 quantitative questions and were collected via online

through social media campaigns (Facebook, Twitter, Linkedin) and personal emails. Theses campaigns were

launched during the month of May in 2017 and collected 167 responses. However, only complete responses

were accepted in the analysis. Therefore, the total number of accepted responses were 132. The data received

was analysed on SPSS Statistics. Only one question has counter indicative items (question number 28) and

was transformed of the rating values (1=5, 2=4, 3=3, 4=2, 5=1) in order to match with privacy concerns

questions.

3.3 Sample characteristics

Of the answers obtained, 73.5% (97) were female and 26.5% (35) were male. At the same time, 6.8%

(9) are participants between age 15-19, 22% (29) are participants between age 20-29, 53% (70) between age

30-39, 16.7% (22) between age 40-60 and 1.5% (2) more than 60 years old. The majority of the participants

are living in central and South America with 47.7% (63), second north America with 18.2% (24) and finally

31.1% (41) in Europe. 74.2% (98) participants responded that they buy online less than 5 times per month,

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3.4 Descriptive statistics

For each construct, a new variable has been created based on its respective questions. Each variable

has a mean, which is used to create the regression analysis. After analysis of the results, six variables have

been created and 2 are discarded due to low Cronbach alpha correlation. Most of the variables have a normal

distribution as Skewness and Kurtosis are around 0 and between -1 and 1. Each one of the constructs were

analysed with Cronbach's Alpha. According to Heo (2015), the Cronbach alpha is an adjusted proportion of

total variance of the item scores explained by the sum of covariance between item scores, and thus ranges

between 0 and 1 if all covariance elements are non-negative.

Table 1. Descriptive statistics

The first variable created (independent variable) was Privacy Concern Information (PriConcInfo1)

which measures the consumer concern regarding to the privacy before interacting with a firm that offers

omnichannel solutions. The first question was asked before starting the consumer journey (in the first

scenario) and the same question was asked after finished the consumer journey (in the fourth scenario). This

construct resulted in a α=0.747. The second and third variables were Control of the Information (ControlFIN) and Control of the Information after interaction (ControlAfterFIN) which measures

consumer perception on control over their personal information before and after interaction with consumer

journey. The final α for these constructs were around 0.696 and 0.717 respectively. The forth variable was Willingness to share information (WilligInfoFIN) which measures consumer willingness to share their personal information with firms when interacting in omnichannel strategies. The final was α=0.728. Finally, the last variable was about Consumer willingness to purchase (WilligPurFIN) with α=0.747. At the same

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3.5 Hypothesis testing

In order to validate the hypothesis presented in this research, the hierarchical multiple regression

was executed taking into account one independent variable: Privacy Concern Information (PriConcInfo1)

and three control variables: gender, age and continent (live). For each hypothesis, two models have been

created to investigate the impact of independent variables over the corresponding dependent variable for each

hypothesis, after controlling variables such as gender, age and place to live.

Hypothesis 1:

Hypothesis 1 uses as dependent variable (DV) the Collect Information variable (CollInfoFIN). The

variable collects information referring to consumer’s perception towards how companies manage consumer

personal information. It is useful to remember that Phelps (2000) found that consumers are concerned about

how their information is used by companies.

Table 3. Hierarchical regression model of Collect Information variable

As the table 3 shows, PrivConcInfo1 influences the Collect Information variable with a β=0.404 with

sadistically significant p<0.00, meaning that privacy concern has a positive impact over the consumer’s

perception about how companies should manage personal information. In other words, if a person is

concerned about their privacy, the perception about how their personal information will be managed will

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information. e.a., people who lives in South and Central America thinks differently about how information

will be managed by companies. Nevertheless, the relationship between variable live and privacy concerns

needs more development in future research.

Hypothesis 2:

For hypothesis 2, the DV used is the Control Information (ControlInfo) which explores consumer

desire to have control over their personal information. In the first model, only control variables have been

analysed, resulting in a statistically significant model F (3, 128) = 0.868; p < 0.5 and explains 2% of variance

in control of the information.

Table 4. ANOVA analysis

In the second model, independent variable (privacy concern variable) was included into the model

with statically significant F (5, 126) = 6.262. The R square can then serve as a measure of reliability. When

the independent variable is introduced in the second model, variance increases by 20%, showing the direct

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Table 5. Hierarchical regression model of Control Information variable

On the other hand, as it can be presented on table 5, the independent variable Privacy Concern record

higher beta value with β= 0.383, p<0.01, explaining the positive impact of the privacy concerns in the desire to have control of the personal information. As a result, privacy concerns increase the desire to keep control

over consumer personal information.

Hypothesis 3:

The dependent variable used to measure hypothesis 3 is called Control information after interaction

(ControlAfterFIN) which measures the desire to keep control of the information after interacting with a

firm through different channels. According to the previous literature review, the privacy paradox is a result

of a calculous of cost and benefits: people will reveal sensitive information (cost - abstract), if there is an

immediate gratification (benefit - tangible). The objective of testing this hypothesis is to prove if the

interaction through omnichannel reduces privacy concerns and the positive impact over the desire to keep

control on how their personal information is managed. To measure H3, the participant was requested to

complete the two previous steps in the consumer journey (search and interaction) before entering on the

purchase phase. As the table 6 shows in the second model, IV (privacy concern) has not statistical

significance over the DV (Control info after interaction) neither of the control variables (gender, age, live).

This result also shows that IV doesn’t seem to be a significant effect on the DV because R2 (after the

introduction of independent variables) is 9% which is extremely low and doesn’t provide solid grounds to

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previous interaction with the firm has occurred. As a result, after an interaction between a person and a firm’s

channels, will reduce consumer privacy concerns and the desire to have control over personal information.

Table 6. Hierarchical regression model of Control Information variable after interacting with firm

Hypothesis 4:

The dependent variable used to measure hypothesis 4 is called Willingness to share information

(WilligInFIN) which measures the consumer’ desire to share personal information with the firm. To measure

this hypothesis, it is imperative to analyse if the consumer is willing to share its personal information with

the firm in order to have access to omnichannel benefits. In the step 3 of the consumer journey, the participant

has been asked about the willingness to share its information after three previous steps (search, interaction

and purchase). In the third step, the participant needs to share personal information in order to buy the

product. Do privacy concerns affect the willingness to share its information? Does the necessity to buy the

product change consumer willingness to share the information with the firm? According with the literature,

consumers will be concern about how companies use their information as well consumers will want to keep

control over their information.

The table 7 compares two models that examine the impact of control variables and independent

variables on the willingness to share information. As a result, neither in the first and second model, variables

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Table 7. Model summary of willingness to share information

Once privacy concern variable (independent variable) is included in the second model, not significant

difference is found in the variable (variance 3.1%), meaning that the regression coefficients are not

significant to measure hypothesis 4.

Table 8. Hierarchical regression model of willingness to share information

Table 8 shows that there is an inverse correlation between privacy concerns and the willingness to

share personal information with β= -0.136, however, there is not statistical significant in this variable,

meaning that privacy concerns could not have impact over consumer willingness to share personal

information. In order to have a complete tested hypothesis, this research verifies the information provided

by the questions. Observing the attitude about willingness to share information on table 9, participants are

not completely sure to provide the information in order to receive the product (mean: 2.59 out of a 1-5 scale)

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Table 9. Attitude towards willingness to share information

According to the previous results, H4 was discarded due to low statistical significance among its

variables and could be explained by methodological error creating variables that support the model or

because effectively the research finds that consumer does not feel secure providing personal information to

firms.

Hypothesis 5:

Hypothesis 5 has been formulated to examine consumer willingness to purchase when interacting

with omnichannel solution. The dependent variable used to measure hypothesis 5 is called consumer

willingness to purchase (WilligPurFIN). Same four questions have been asked for each scenario on the

consumer journey. H5 asserts that most consumers’ willingness to purchase will not be impacted by privacy

concerns when interacting in Omnichannel solutions. Will the consumer change its attitude to purchase the

product once interact deeply with the firm through omnichannel solution?

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Even though that table 10 shows negative significant effect of privacy concerns on consumer

willingness to purchase (β= -0.065), it also shows that none of the predictors had statistically significant. These results indicate that consumers may be concerned about their privacy but there is not a correlation

between its privacy concern and the willingness to purchase the product.

Table 10. Model summary of willingness to purchase

With the introduction of the independent variables (Privacy Concerns) in the second model and

controlling gender, age and live, the model has a variance of 8.8% with F (5,126) = 2.417. Furthermore, the

willingness to purchase in omnichannel solutions will not be impacted by the privacy concerns however,

taking that the model didn’t find statistically significant between its variables that helps to support this hypothesis for that reason, the H5 was discarded.

One possible explanation could be related with the consumer perception about the necessity to share

personal information with the firm in order to buy the product and in that point privacy concerns could impact

willingness to share information. However, the desire to obtain the product allows the consumer to leave the

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CHAPTER 4

4.1 Discussion

As presented before, omnichannel strategies are essential part of the future of e-commerce. Being

able to offer product availability 24/7, combining mobile, store and online shopping and offering customers

solutions are part of these strategies. Customer data is fundamental part to integrate channels. Nevertheless,

is the consumer willing to share its personal information in exchange of customer experience? Is the

consumer willing to purchase a product when interacting in omnichannel solutions? Even more important,

does requesting personal information affect the willingness to share information and purchase the product in

omnichannel solutions? According to Acquisti (2015), depending on the situation, an individual can exhibit

anything ranging from extreme concern to apathy about privacy. In this research, an initial question was

raised: What is the impact of privacy concerns over consumer willingness to provide personal information

for Omnichannel solutions? Five different hypotheses were created to respond this question and were measured in order to understand consumer perception towards privacy concerns and to analyse consumer

final decision to share information and to purchase a product.

The first hypothesis is related with the consumer desire to know how its personal information is

being used by the firm. Trying to find empirical support for this construct, Smith, Milberg & Burke (1996),

measured individual concerns about organizational practices and they found that concerns towards collection

information reflect one of the most important concerns that individuals have. This research confirms the

positive correlation between consumer privacy concerns and its perception about how firms are managing

their data. A potential explanation for this behaviour is that the individual is concerned about the improper

access to his or her personal information. Therefore, if a consumer increases its own privacy concerns, its

concerns about how companies should manage personal information will increase as well. When testing

hypothesis 2, regression coefficients represented positive correlation (β= 0.382) between privacy concerns

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more secure when he/she feels that is keeping control over its personal information and its privacy concerns

will decrease. If the other case is raised and individuals feel that they are losing control over their information

(due to technological constraints or third parties access), their privacy concerns will increase.

The research has confirmed with H1 and H2, that consumers have privacy concerns when interacting

with firms that ask for personal information. However, does omnichannel solutions allow changing privacy

concern perception through channel interaction and the offering of personalized strategies? Analysing

hypothesis 3 the model did not find significant statistical correlation between privacy concerns and the desire

to keep control of the information after the interaction with the firm. This can be explained because privacy

concerns still have influence over consumer’s interaction with omnichannel solutions and is reflected in the fact that the majority of respondents desire to have more control over their information, and their perception

will not easily change with Omnichannel's interaction.

Regarding hypothesis 4, even though no positive regression coefficients were found in this research

related on privacy concerns and consumer willingness to share information, the variance obtained in the

second model which introduced the dependent variable is around 2%, meaning that the model fits were

extremely low however, none of the variables proved statistical significant, meaning that privacy concerns

could not have significant effect on consumer willingness to share information.

Finalizing with hypothesis 5, this research found that a negative correlation between privacy

concerns and consumer willingness to purchase. The adjusted R square can serve as a measure of reliability

with 8% for the second model when the independent variable is included, however, none of the variables

proved statistical significant. Therefore, this research could not find support for hypothesis 5.

To summarize, this research has confirmed theories that studied strong relationship between privacy

concerns and the consumer desire to know how its personal information is being managed by firms and the

consumers desire to keep control over its personal information. These variables impact consumer’s privacy

concerns that influence the willingness to share personal information which is considerable important when

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4.2 Conclusion

This research was based on two recent streams. First, it uses the Westin (1990) methodology that

created the general privacy concern index used to predict general concern level and privacy concern level.

Second, it continues the effort of Phelps, Nowak and Ferrell (2000) to identify relationship between level of

concern over the way companies use personal information and respondents’ information-related beliefs and behaviours. However, the consumer willingness to provide personal information in omnichannel solutions

requires more examination.

Omnichannel provides huge opportunities for firms in terms of marketing effectiveness, revenue

driver and supply chain competitiveness. The seamless channel integration implies a customer single view,

which means that firms need to collect personal information in order to offer omnichannel benefits. However,

offering accessibility to diverse channels and creating personalized offers for them are not enough for

customers. The impact of privacy concerns over consumer willingness to share personal information is

notable since participants were not completely sure to provide the information in order to receive the product.

The findings consistently expose a strong relationship between privacy concerns and privacy constructs such

as desire to keep control over the personal information and perception about how companies should manage

information. The results indicate that consumers desire more information control and they want to know how

its information has been used by companies. These constructs need to be taken into account when firms are

developing omnichannel strategies.

To conclude, the answer to the research question is that privacy concerns does have an impact over

consumer perception about how firms are managing their data and also the desired to keep control over

personal information. However, the research could find an effect of privacy concerns and consumer

willingness to share information since implementing omnichannel solutions requires consumer’s personal

information to accomplish seamless and personalized customer experience. Furthermore, if the final purpose

for firms is to have customer rich data, is necessary to explain how customer information is going to be

managed and give them more control over their information so consumers are more willing to share personal

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4.3 Limitations and recommendations for future research

This research analyses few constructs of consumer privacy concerns and therefore there is a need to

examine consumer beliefs and preferences related with privacy concerns. For example, to explore the type

of information that consumers are willing to exchange for shopping benefits. According to Phelps, Nowak

and Ferrell (2000) consumers are least willing to provide financial and personal information. Also,

behaviours, country regulators and lack of experience with the internet need to be taken into account to

analyse consumer perception. Another limitation in this research is about the participants. The majority of

participants in this research are from the Americas and the Netherlands, meaning that there is a need to

explore consumer privacy concerns as a global database.

Finally, the biggest limitation about this research is related with the use of a survey as a mechanism

to collect information. There are potential problems when using surveys: missing data, incorrect data and not

real mechanism for actual behaviour. It is most likely that interviewing participant in a real omnichannel

solution environment has different responses about privacy concerns.

Despite these limitations, finding in this research illustrate the importance of privacy concerns when

What is the impact of privacy concerns over consumer willingness to provide personal information for Omnichannel solutions?