Transfer From Offline Trust to Key Online Perceptions: An Empirical Study
Kun Chang Lee,* In Won Kang** and D. Harrison McKnight***
*Professor of MIS
School of Business Administration
Sungkyunkwan University
Seoul 110-745, Korea
leekc@skku.ac.kr
**Assistant Professor
School of Economics & International Trade
Kyunghee University
Seoul 130-701, Korea
iwkang@khu.ac.kr
***Assistant Professor
Eli Broad College of Business
Michigan State University
East Lansing, MI 48824-1121
mcknight@bus.msu.edu
Forthcoming IEEE-TEM
Index Terms: Trust, trust transfer, structural assurance, online banking, online trust, marketing channel, flow, website satisfaction, extent of use, coherence, cognitive overhead.
Transfer From Offline Trust to Key Online Perceptions: An Empirical Study
Abstract- Research has provided little evidence that trust in an offline bank can encourage adoption of the bank’s online business. Yet more and more brick-and-mortar banks and other businesses are investing in online websites that supposedly “leverage” positive consumer impressions of their offline business. The main purpose of this study is to test empirically whether or not trust in an offline bank transfers (i.e., influences) perceptions about that company’s online bank. In order to do so, we analyze how trust in an offline bank influences four perceptions about its online banking counterpart (flow, structural assurance, perceived website satisfaction and perceived extent of future use). The study tests the hypothesized influence of offline trust using a sample of 199 South Korean consumers responding about offline and online banking. Results show that offline trust influences all four online perceptions, just as proposed. These effects were especially prominent among respondents new to online banking. Thus, offline-to-online transfer should be considered when designing strategies for online channels. This study fills a key research gap by examining transfer of cognitive beliefs from an offline to an online setting.
I. INTRODUCTION
Trust is a central construct in the study of commercial transactions, both in information systems (IS) and such reference disciplines as marketing, sociology, and organizational behavior [27, 31, 73, 75, 95]. Trust plays an important role in both offline and online commercial transactions [106]. Several IS studies on the role of trust in electronic commerce (e-commerce) have been conducted in recent years [5, 33, 34, 36, 43, 50, 58, 71, 80, 81, 96, 103]. Especially, with the advent of online marketplaces on the Internet as a new business paradigm, trust has been dealt with as a crucial enabling factor for business-to-consumer relationships [33, 50] as well for business-to-business marketplaces [80].
A number of trust constructs including institution-based trust [70, 81, 108] have been defined [34, 72]. Interpersonal or inter-party trust definitions largely fall into two categories:
Willingness to become vulnerable to another [67, 71], such as “a willingness to rely on an exchange partner in whom one has confidence” [74].
Positive perceptions or beliefs about the attributes of another. This includes the perception of “confidence in the exchange partner’s reliability and integrity” [75], and the perceived credibility (honesty) and benevolence of a particular target [30, 56]. Several have listed integrity, benevolence, and ability as attributes [8, 34, 71]. In buyer-seller relational exchanges, which are the most popular forms of transactions between persons or companies, two dimensions of trust are perhaps most pertinent. The first, credibility/honesty, is the expectation that words or written statements can be relied upon or depended upon [61]. The second, benevolence, is the extent to which one partner is genuinely interested in the other’s welfare and is motivated to seek mutual gain [57].
Trust is important in relational exchanges because it allows partners to transcend short-run inequities or risks to concentrate on long-term profits or gains [73]. Personal relational exchanges are typified by qualities such as intensity, interaction frequency, relationship duration, and future relational expectations [48]. These qualities inherent in offline relational exchange facilitate trust building. By contrast, trust is more difficult to create online because parties do not typically have intense, face-to-face contact that enables trust to be built through tangible cues. One can enter a bank, for example, and learn to trust the bank tellers through repeated personal interactions that provide interpersonal cues. One can also become secure quite rapidly with the bank institution itself by entering the bank and observing the look-and-feel of the building, its furnishings, and the banking procedures—physical cues on which to base trust [71]. By contrast, the online bank has no such physical cues for trust building, although its website provides certain online cues.
One way to solve this trust building problem is to transfer trust from a known brick-and-mortar entity to positive perceptions in the unknown online entity. We postulate that trust gained through experience with an offline company positively influences key customer perceptions of the same company’s online division, such as website satisfaction or intention to use its site. Stewart [96], who called this phenomenon “trust transfer,” applied it specifically to business-to-consumer e-commerce in terms of buying computers online. The results revealed that websites that had a picture and street address of their land-based store generated a higher consumer intention to buy from the store. Stewart [96] did not use specific trust-related perceptions about the offline store to predict online perceptions, a gap this paper addresses. Today’s Internet-oriented world has made it even more important for marketers to study the interplay between offline and online channels when analyzing customer behavior. Those who do so are rewarded with a level of predictive power that affords them a distinct advantage over their competitors. Potentially, this study contributes by testing an instance of the effects of offline bank trust on four specific consumer perceptions regarding the bank’s online counterpart.
II. LITERATURE REVIEW AND RESEARCH MODEL
A. Trust Transfer Process—Four Types
Narrowly defined, trust transfer means transfer of trust from one domain, such as offline, to another, such as online. We define trust transfer more broadly to include the influence of trust in one domain on attitudes and perceptions in another domain. For example, consumer trust of an offline bank can affect perceptions about the same firm’s online bank. Figure 1 depicts several types of trust transfer. The Type 1 TTP shows how trust (or other perceptions) can be transferred from offline to offline channels. For example, the trust that customers perceive in an offline company, like General Electric (GE), tends to extend easily to favorable perceptions about all other GE products or services.General (lot. generalis - umumiy, bosh) - qurolli kuchlardagi harbiy unvon (daraja). Dastlab, 16-a.da Fransiyada joriy qilingan. Rossiyada 17-a.ning 2-yarmidan maʼlum. Oʻzbekiston qurolli kuchlarida G. Trust for a certain company means consumer brand knowledge which relates to the cognitive representation of the brand [83]. Consumer brand knowledge can be defined in terms of the personal meaning about a brand stored in consumer memory. Therefore, if customers possess a sound memory about an offline company’s brand, then such memory affects consumer purchase behavior about the product and/or service offered by the same or similar offline brand.
Figure 1. Trust Transfer Process (TTP)
In the mid-1990s, many firms began performing marketing activities both offline and online (Type 2). As the Internet has proven an ever more effective global communication medium, marketing strategies have shifted from offline to online channels. One key issue has been whether consumer trust, something offline firms had worked for years to accumulate, would translate into favorable perceptions of online products. Examples both support and cast doubt on such trust transfer. Offline-turned-online channels such as Barnes & Noble Company (http://www.barnesandnoble.com) and Samsung Electronics Corporation (http://www.sec.co.kr) have maintained offline trust and brand loyalty online as well as offline. On the other hand, FTD (Florists’ Trans world Delivery) and Hallmark have had trouble leveraging their offline business into online successes [15].
Although many pure online companies have fizzled out, some continue to succeed (e.g., Dell Computer). Continuing questions about Dell’s survival prospects are based on whether the online trust it has built thus far will remain stable in the future, when stronger competition is expected. It follows, then (Type 3), that if existing online companies wish to expand their online products and service offerings, they will have to maintain or increase their level of consumer trust. Stewart [96] suggests that, in online B2C, trust transfers from trusted websites to unfamiliar websites based on hyperlinks between them.
There are rare cases of Type 4 trust transfer, in which customers’ trust in online channels move to offline channels. In South Korea, which has a very high Internet adoption rate due to its highly advanced Internet infrastructure, a number of successful online companies have expanded their business into offline channels. In the home shopping industry, two companies, CJ Home Shopping (www.cjmall.com) and GS Home Shopping (www.gseshop.co.kr), have successfully opened offline shops, taking advantage of their online reputation. MISSHA (www.beautynet.co.kr), a quality-based and low-priced cosmetics company that originally started as a pure online company and accumulated a solid reputation by innovating a process of developing new cosmetic products on the basis of online polls, is recently receiving a great deal of attention from the Korean cosmetics industry and mass media, due to its fast and successful expansion into offline markets.
In Figure 1, TTP is categorized as either intra-channel (Types 1 and 3) or inter-channel (Types 2 and 4). Regardless of type, TTP indicates that trust amassed over time in one channel (online or offline) may influence the evaluation of a product or service in the same channel or in another channel.
A customer’s evaluation of a new brand is based on the schema developed from experience and knowledge of it [66]. Customers evaluate products and services in order to reduce transaction risks [12], and it has been established that customers use their experience to determine their purchase intentions [86]. The consumer schema remains in memory and is converted into trust in the vendor. Knowledge of TTP can help marketing strategists enhance consumer loyalty and expand it into different channels.
This study fills a research gap by focusing on Type 2 (Offline-to-Online) TTP, which has received almost no attention. Offline to online TTP is a pervasive phenomenon, since most businesses and individual customers are already involved in some form of e-commerce or Internet business. Type 1 (Offline-to-Offline) TTP has already been studied by numerous researchers [14, 54, 82]. Once an offline brand (or company) has succeeded in acquiring a certain level of consumer trust, it can extend easily into another offline business under the same brand category. By contrast, real cases of Type 3 (Online-to-Online) and Type 4 (Online-to-Offline) TTP are relatively rare, although Stewart [96] has addressed Type 3.
B. Offline Trust and Online Mental Models
Figure 2 represents the general interaction of offline trust with a mental model of online banking. We begin with this general model before proceeding to the specific research model. A mental model is the representation of objects and semantic relations that a user constructs when he or she is processing new information [38]. Customers who view hyperdocuments on an online banking website must be able to form quick and clear mental models before attempting to perform online banking transactions.
Coherence positively influences the ability to form mental models, while cognitive overhead inhibits it. By definition, a document is coherent if a customer can construct a mental model from it that approximates reality [52]. A website that combines design factors to create a user-friendly website design improves customer coherence [63].
Figure 2. Relationships between Offline Trust and Online Customers’ Mental Model
Note: Dotted line box indicates constructs not in this study
Cognitive overhead, on the other hand, is the additional effort and concentration users need to perform one or more complex tasks at once [17]. Cognitive overhead is influenced by orientation, navigation and interface design [101]. For example, multimedia overkill in a Web interface (e.g., excessive graphics, color, animation, sound) can cause excessive cognitive overhead because the capacity for human information processing is limited. We thus argue that various website design factors affect both coherence and cognitive overhead.
Based on Thuring et al. [101], this study argues that flow and structural assurance affect perceived website satisfaction and extent of use through coherence and cognitive overhead. While this study does not measure coherence and cognitive overhead, it argues that flow and structural assurance partly influence the Figure 2 outcomes by their effects on coherence and cognitive overhead. Flow means an optimal experience with a task [20]. Structural assurance means the belief that situational factors like contracts, regulations and guarantees support the likelihood of success [71]. Using both coherence/cognitive overhead and their causes (flow and structural assurance) in the model seemed like overkill in terms of model complexity. Also, because it is viable to test a subset of a larger theoretical model [99], we chose to test a model that only included flow and structural assurance.
C. Offline Trust and Flow
Arguments are now made for why trust will transfer in general, and then reasons for why trust will transfer to online flow. Trust in an offline business should transfer to perceptions about an online business because of brand knowledge. Since brand knowledge is the cognitive representation of a particular brand [83], it is also defined as the personal meaning that is stored in consumer memory: descriptive and evaluative brand-related information [54]. Brand knowledge involves a synthesis of multiple factors such as awareness, attributes, benefits, images, thoughts, feelings, attitudes, and experiences [54]. Among those factors, trustworthiness perceptions about the brand are implicitly included in attitude, which is believed to transfer to the other entity (refer to Figure 2 in [54]). Thus, consumer trust in a certain brand will transfer to products and services related to that brand, regardless of channel.
The concept of flow involves the optimized processing of experiences that occur when customers navigate or browse the Internet. Online interactivity between companies and their customers is carried out through flow [44, 101]. Flow helps explain certain aspects of human-computer interaction [20].
Figure 3 shows the research model that will now be justified. A common measure of flow is the level of intrinsic enjoyment of an activity, not unlike the emotional response of pleasure in environmental psychology [55]. In an online environment, flow is based on three aspects: shopping enjoyment, perceived control, and concentration/attention. This study, accordingly, defines flow using these three aspects. Just as shopping enjoyment is important in offline markets, it is important online, where it can have a significant impact on customers’ attitudes and intentions about online shopping [49, 55]. Internet shopping does not always provide the emotionally fulfilling experience of conventional shopping because it is mostly limited to two-dimensional text and pictures [55].
Figure 3. Research Model
One aspect of online shopping enjoyment is the perception that the website has interesting content. The second aspect of flow, perceived system user control (i.e., not being controlled by the system), concerns the information environment on the Internet. A high level of consumer control should be guaranteed by companies that wish their customers to conduct online transactions [6, 44]. The third aspect of flow, concentration/attention, is not always easy to maintain on a website. In an online banking situation, customers do not engage with tellers personally. Such face-to-face interaction can be very engaging. Online interaction can also be engaging [20]. However, online concentration/attention may be discouraged by limited time and lack of information processing resources [86], lack of a real space where people can meet each other face to face [55], and other distractions, such as email, pop-ups, and instant messaging.
Trust in an offline bank probably reduces user hesitance to give attention to the system, because without trust, the perceived risk of using the system would interfere. Trust therefore obviates uncertainty or concern and facilitates the development of flow. It is hard for the user to experience flow when the mind is bogged down in uncertainty or risk. That is, flow means a feeling of total involvement [20]. It is hard to feel total involvement using the online system of a bank one does not trust. Trust has long been seen as a way to address uncertainty [64]. Trust can act as a substitute for control because one feels more in control and less uncertain with a person one trusts [64]. Offline bank trust would thus positively influence flow in terms of perceived control because one who trusts the offline bank would feel more in control and less uncertain when using the bank’s system.
H1: Trust in an offline bank positively influences perceived user flow with the online bank system.
D. Offline Trust and Structural Assurance
While Internet customers can access products and services efficiently regardless of location or time, they have limited means of assessing the characteristics of the products and services they purchase [22, 49, 87]. They can only view products on-screen. This is one reason many customers perceive transaction risk when shopping on the Internet [86]. Risky situations result in customer uncertainty: unexpected worries, concerns and psychological misgivings at the time of purchase or adoption [7, 26, 100].
Structural assurance, a form of institution-based trust particularly key for minimizing perceived risk in online transactions, means consumer projections of success due to such safety nets as legal recourse, guarantees and regulations that exist in the context [23, 71]. Trust in the e-vendor results from the security customers feel due to these safety nets [34].
Online banking requires a high level of security, since private information must be completely protected against computer hacking attacks or technical failures that would damage customers’ financial status. Online banking transactions should therefore result in positive consequences with regard to the amount of money and financial conditions involved. In this study, structural assurance focuses on situations in which customers contemplate online banking transactions in a known service class. If a consumer trusts the offline business, this trust should transfer to beliefs that the firm’s online system is safe and secure, i.e., to structural assurance beliefs. If an offline bank is trusted, it should also be perceived as having adequate online safeguards. This is as natural as believing a trusted retail store will back its product guarantees in a new line of business, just as it already does for existing lines of business.
H2: Trust in an offline bank positively influences structural assurance of the bank’s online system.
E. Offline Trust and Perceived Website Satisfaction
User satisfaction with a specific web-based system depends on numerous factors, including web design [62, 79, 105], content [85], user interface [94], navigation and information structure [69, 90], and contextual marketing [65].
User satisfaction was initially promoted as a proxy for the success of an information system. Such systems were evaluated in an attempt to specify their quality from the user’s point of view [32], and many instruments were developed that successfully measured different aspects of user experiences and opinions [21].
From a marketing perspective, user satisfaction depends largely on performance. Product experiences alone do not determine overall satisfaction, however; a large body of research has shown that the level of performance the customer expects is also important [16, 78], as is knowledge of outcomes that were not experienced. When people evaluate outcomes they compare their actual results with the results that might have occurred had they chosen differently [11, 53]. Similarly, trust development has been depicted as the process of setting expectations of another’s behavior and then evaluating whether or not those actions are confirmed [89]. Trust expectations can also act as cognitive filtering devices by predisposing one to interpret the other’s behavior as consistent with the original expectations. For example, Holmes [46] found that trusting marriage partners tended to block out or reinterpret (positively) actions by their partner that did not match their positive trusting expectations. Likewise, one who trusts has expectations that will likely be confirmed in terms of perceived website satisfaction. If one has found an offline bank to be trustworthy, then one is likely to project positive satisfaction towards its online counterpart. Thus trust in the offline bank should positively affect perceived satisfaction with the website.
H3: Trust in an offline bank positively influences perceived online bank website satisfaction.
F. Offline Trust and Perceived Extent of Use
Extent of use means expected or planned future behavior — the probability that a customer will translate beliefs and attitudes into user-related actions. Different factors can influence extent of use in online transactions, including product perceptions, purchasing experiences, customer service and transaction risk [49].
Online products are perceived through interactions between people and machines, while products in offline transactions are perceived directly. Thus, online transactions highlight customer risk [45], since customers are unable to directly experience products and services. The level of risk that customers perceive in online transactions influences their level of satisfaction with a website. Extent of use depends on the level of satisfaction with several factors about the website. So far, research on extent of use in offline and online transactions has assumed that every extent of use applies only to one channel [8, 103, 106]. However, Ramaswami et al. [88], applying to both offline and online transactions, suggests two factors influence purchase of online financial products: 1) prior clues a consumer gains in the offline channel; and 2) use of the online channel for information search.
Therefore, consumer online behavior is often determined by prior clues in the offline channel, which are translated into the mental model in the online channel [88]. If a customer is satisfied with a product in the offline channel, he or she is more likely to favor that product in an online channel. When a consumer’s experience with an offline vendor is satisfactory, the consumer will trust the offline vendor. Trust in the offline vendor should then transfer into positive attitudes towards the vendor’s online products. Gefen et al. [35] found that trust in an e-commerce vendor leads to intentions to purchase from that vendor. Similarly, trust in the offline bank should positively influence extent of intended use of the bank’s online system.
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