Anssi Mattila, InBCT 4.2

The Different Dimensions of Seamless Use Experience in Electronic Environment[1]

 

 

Abstract

The purpose of this paper is to demonstrate the relationship and dependencies between different dimensions of the seamless use experience in an electronic environment. This paper outlines the factors affecting the seamless use experience in both mobile and fixed-line Internet services from the customer’s perspective. The customer’s perception about seamless use experience results mainly of the experienced interaction in the customer-technology interface. However, our results show that the seamless use experience is defined by many more variables such as satisfaction towards the service provider and customer’s previous use experience. The results are based on a large consumer survey conducted among mobile and fixed-line Internet users in Finland during summer 2003.   

 

Keywords: seamless, electronic channels, customer interface

 

 

 

 

1.    Introduction

Several extensive collections of general user interface guidelines (Brown 1988, Marshall et al. 1987, Mayhew 1992, Smith and Mosier 1986) and methodologies (e.g. LUCID, Kreitzberg 1996) to develop and to enhance user interfaces has been published. In our study we are not trying to define the place of a key on a cell phone or the place of an icon on a screen, but instead, the focus is on the seamless use of the mobile and fixed-line services itself. Designers' assumptions shape their predictions about the final product and how it might perform in interaction with its users (Hasdogan 1996). However, the predictions designers make about the product's usage and performance do not always match the expectations of the user and actual usage of the product (Nogier 2001). Such mismatches between the designers' predictions and actual product use are likely to lead to customer dissatisfaction and frustration with the product.

 

Traditionally usability testing has been device and technology specific. The main usability research method has been non-participatory observation in laboratory settings with a very small sample size (Ivory et al. 2001). The satisfaction has been measured in relation to the system (Nielsen 1993, 33). However, experiments have shown that “usability” of a service cannot be predicted from the technical quality of its components. This is to a large extent due to the interaction between objective performance measures and functionality (Boves et al. 1999). Usability becomes seamless use experience, when the service use context and content are taken into account. Seamless use experience research is more customer-centric analyzing the value proposition of a service throughout the value chain. A common research method in seamless use experience studies is survey (Ivory et al. 2001) and the customer satisfaction is often measured in relation to the service and content provider.   

 

2.    Usability attributes

In this paper we focus on five usability attributes previously defined by Nielsen (1993, 26-37): learnability, efficiency of use, memorability, satisfaction and errors. Nielsen has concentrated in his research on the graphical user interface usability testing. However, these attributes can be easily understood also when put into a context such as mobile or fixed-line services. Nielsen’s attributes represent the most generic model among the usability research. The purpose of this study is the map the different dimensions of seamless use experience in the electronic service context. Therefore, Nielsen’s model provides us a suitable starting point. 

 

Other definitions do exist including more or less overlapping attributes. Different definitions can include the same attributes, which are defined dissimilarly. ISO 9241 Part 11 (1995) introduces definition of usability of a given computer system and uses three attributes: efficiency, effectiveness and satisfaction, in which efficiency includes learnability.  Dix et al. (1997, 162-175) defines three main categories: learnability, flexibility and robustness. They are further defined to include more specific principles supporting the main categories. For example, Dix et al. (1997, 163) define learnability as including principles like predictability, synthesizability, familiarity, generalizability and consistency. For mobile systems, collection of usability properties would include intuitiveness, ease of use, efficiency of use and reliability (Clevenger 2002).    

 

With learnability as a usability attribute we refer to the difficulties customers experience when trying to learn how to use the electronic service. At least novice users tend to think that mobile services are expensive to use (Munnukka et al. 2003), so it is important that services are easy to use right from the beginning. These novice users might not want to spend their money on learning. Highly learnable systems have steep incline in the beginning of the learning curve (Nielsen 1993, 28), which means that it is relatively easy for the users to learn to use the system within short time period (F1).  The most common way to measure proficiency (referring to F1) is to check whether the users are able to complete particular tasks successfully.

FIGURE 1          Learning curve of a system focusing on novice users (Nielsen 1993, 28)

 

Efficiency of use has two aspects, effectiveness and efficiency (e.g. ISO 9241 Part 11 1995). Efficiency of use in usability context normally refers to expert user’s normal performance level (Nielsen 1993, 30). In certain systems average users might not even reach that performance level. In our study context efficiency of use refers to effectiveness and efficiency. By effectiveness we mean how accurately and precisely customers achieve their goals of usage. By efficiency we refer to the customers’ spent resources including time and money.

 

Electronic services should be easy to remember, which contributes to the memorability attribute. This includes finding the service and being able to easily access the service repeatedly. The customers shouldn’t have to learn to use the service again and again. Instead, the service should be designed in a way that the customers feel comfortable as they return to use it even though the use of the service/services might be non-regular.

 

Bowen and Chen (2001) found that the relationship between customer loyalty and satisfaction is non-linear. According to Coyne (1989) there are two critical thresholds affecting the link between satisfaction and customer loyalty. On the other side, when customer satisfaction reaches a certain level, the loyalty increases very strongly, and at the low end, when satisfaction decreases to a certain point, the loyalty drops very strongly (Oliva et al. 1992). Using the electronic service should constitute a pleasant experience leaving the customer with a feel of satisfaction and making her long for re-using the service.

 

Errors as a usability attribute in our context is two-fold like efficiency of use. We refer to two kinds of errors, namely minor and catastrophic errors (Nielsen 1993, 31). Minor errors hinder the use of the electronic services, but don’t affect the final outcome. Minor errors include typos, using wrong links, pressing wrong keys and so on. Minor errors have been found to be closely interrelated with efficiency of use (for example Nielsen 1993, 32). Catastrophic errors lead into a situation, in which the customer is unable to finish the use of electronic service in a desired way. The customer may be left without a confirmation of a successful transaction, the use session cuts off and so on. Minor errors are such that customers should be able to recover easily from them whereas catastrophic errors have far reaching effects and should never happen. 

 

3.    Seamless use Experience in Electronic Delivery Channels

In our research we are trying to see usability in a larger scale, and therefore we use the term seamless use experience, which refers to the service as a whole. What is hindering the usage of the services, what do customers really want to accomplish with the service, what are the ultimate goals of the customers, are they really satisfied with the service level and so on. We are trying to provide the service developers tools to create more focused services by knowing which features in the service should be stressed and in which context. The customers waste their own time and money on these services, and if they are not satisfied they are more likely to change the service provider.

 

WAP-based services, especially when accessed via very small screens, have suffered a great deal of criticism from both the popular press and technology experts (e.g. Nielsen 2000, Weeks 2000). Contrary opinions have been also presented. According to Buchanan et al. (2001), most people find the basic WAP scheme easy to learn and simple to interact with. However, the WAP system was found ineffective to complete tasks and error-prone. One must keep in mind though, that Buchanan et al. (2001) conducted their survey among 110 students who were also experienced mobile phone users.

 

In the case of Web site design, too much attention has been paid to the aesthetics, which lead to amazing looking Web sites but actually cause frustration because customers have difficulty in finding what they are looking for. A Web site should reflect the value proposition which satisfies the customer needs to ensure repeat visits (Cox et al. 2002). Cox et al. (2002) categorize six key Web site quality factors affecting the seamless use experience: clarity of purpose, design, accessibility and speed, content, customer service and customer relationships. The above mentioned factors reflect the usability of the Web site during customer navigation and aim to reduce customer frustration. It has been found that the design of a Web site will affect customers’ decisions to include online shopping as a channel option (Schoenbachler 2002). As the marketer takes a more customer-centric approach and focuses on the consumer rather than the channel, many of the multi-channel challenges fade away. 

 

New mobile devices and services have been found to be more realistic and useful than the previous models. They give customers a seamless service even when customers are moving between network connections (Nielsen 2003). Seamless use experience reduces sales costs and shortens sales cycles, which improves Return On Investment (ROI) (Rhodes 2001). Products which are easier to use are easier to sell. Besides matching services and delivery channels, the attributes of the service delivery channels themselves will also be influential when customers make channel choices (Black et al. 2002). Whether or not a customer has access to a channel (e.g. does the consumer have a mobile Internet access?) is probably the most basic determinant of the set of channels considered. After solving this issue, factors such as convenience, costs and risk need to be addressed, because seamless use experience affects the service delivery channel choice. For example, usability refers to the same level of technical system quality regardless of the use location. Accessing Internet at home or in a public library represents the same level of experienced usability. But accessing Internet at home is more convenient and therefore more likely to score higher on the scale of seamless use experience than getting to a public library in a snowstorm, queuing there to get access to the computer, and so forth.

 

4.    Methodology and data collection

In this study, the mobile Internet is defined as usage of Internet via handheld devices such as mobile phones of PDAs. The aforementioned attributes by Nielsen (Nielsen 1993, 26-37) were chosen as they are rather generally laid out. For example, the division presented by Dix et al. (1997), refers more towards a development of user interfaces alone. It wasn’t in our research interests to make such a granulated division beforehand but to investigate first and base the interpretations about the dimension division on the data collected. Before the actual data collection, focus group interviews among expert users were conducted. The meaning of these interviews was to map the possible options for survey questions. The questionnaire was pre-tested on a group of 60 students and modified accordingly.  

 

A postal survey was conducted in May 2003. The sample was drawn from TeliaSonera[2] Finland’s customer database.  The sample was stratified in three active user segments of mobile users, fixed-line users and combined users equal in size depending on the main electronic service delivery channel in their use. The questionnaires were tailored respectively. We call the customers, who did not own according to the database a private fixed-line connection at home, the Mobile users. The customers collected under this sample had the highest volume of mobile data transfers (GPRS, high-speed data) during the last six months in comparison to other customers in the database. They represented in every way the most active mobile Internet users the database had. The Combined users had a private fixed-line Internet connection in use at home. Further, their customer record showed active usage of mobile Internet (GPRS, high-speed data) connection and WAP-services during the last six months. The Fixed-line users owned a mobile phone and they were using regular mobile phone services such as SMS. There was no sign of Internet related activities during the last six months in their customer record. They had a private fixed-line Internet connection (mainly ADSL) in use at home.  

FIGURE 2          The division of response rate among the different user segments of customers

 

 

After a second follow-up, 778 responses were accepted under further analyses. The final response rate was 25.9%, which is acceptable according to economic science standards. The response rate is normal considering the research method (postal survey) and the profile of the sample (mobile or Internet customers). In the future, it may be beneficial to consider alternative survey methods such as online or SMS-based surveys. The distribution of the responses in different user segments is presented in figure 2. A small minority of respondents reported using mobile phone (GRPS or high-speed data connection) as a modem in connection with a laptop as their primary electronic delivery channel. Among the Mobile users there were 16 such a customers and among both the Fixed-line users and the Combined users two in each segment.    

 

The respondents were asked to fill out a structured questionnaire on a 7-point Likert scale concerning their preferences, experiences and beliefs towards usage of mobile and Internet services. There were up to 27 questions in each tailored questionnaire. The Mobile users were answering mobile Internet specific questions whereas the Fixed-line users were answering fixed-line Internet specific questions. As the Combined users segment had knowledge on both types of electronic services and delivery channels, half of them received a questionnaire regarding the mobile Internet seamless use experience and the other half was answering to questions concerning the fixed-line services. The survey questionnaire included questions concerning the respondent’s basic demographic variables, psychological determinants such as level of innovativeness and mobile Internet usage, which was further categorized under for main themes: usage context, service content, seamless interface dimensions and use experience.

 

Besides trying to establish causality between the different dimensions of seamless use experience, we used somewhat ethnographic approach in our survey. Literature (Cooper et al. 1995; Järvenpää et al. 1997; Crisp et al. 1997) as well as prior conducted surveys guided us in defining the scales to measure the customers’ perceived seamless use experience. To get a more accurate and objective results, the mean value of the respondents’ subjective responses were calculated and used as the basis of our evaluation. Statistical methods such as ANOVA, crosstabulation, correlation coefficients, rotated factor analyses, Chi squares and finally structural modeling (AMOS) were applied to our data. Only results relevant to this paper are presented in here. Cronbach’s alpha was used to measure the reliability of the results.

 

5.    Results

The demographic profile of the respondents is presented in table 1. One third (33.9%) of the respondents were women and two thirds (64.8%) were men. The majority (59.8%) of the respondents were 25-49 years old and their annual household income (28.1%) before taxes was in a range of 20 000 – 30 000 euros, which matches with the average annual income of two adults family in Finland. Only every fifth (18.2%) of the respondents had two or more children living at home. The majority of all the respondents were workers (40.6%). This result is compatible with the result of the educational background of the respondents, which was in most cases (29.0%) vocational school. Obviously Internet and its services are becoming available for all the consumer segments regardless of their annual household income or educational background.    

 

 

 

 

 

TABLE 1             Profile of respondents

 

Demographic characteristics	Mobile users		Combined users		Fixed-line users		Total
	No	%	No	%	No	%	No	%
Total	211	100.0	257	100.0	310	100.0	778	100.0
Gender
Male	157	74.4	192	74.7	155	50.0	504	64.8
Female	54	25.6	55	21.4	155	50.0	263	33.9
Missing	0	0	10	3.9	0	0	10	1.3
s.d.	0.437		0.417		0.501
Age
Under 24 years of age	64	30.3	33	12.9	43	13.9	140	18.0
25-34 years	81	38.4	96	37.4	62	20.0	239	30.7
35-49 years	43	20.4	83	32.3	100	32.3	226	29.1
Over 50 years of age	20	9.5	41	15.9	104	24.5	129	16.6
Missing	3	1.4	4	1.6	1	0.3	8	1.0
s.d.	0.998		0.974		1.196
Annual household income
Less than 10 000 euros	33	15.6	21	8.2	43	13.9	97	12.3
10 001 – 20 000 euros	54	25.6	48	18.7	82	26.5	184	23.7
20 001 – 30 000 euros	59	28.0	87	33.9	73	23.5	219	28.1
30 001 – 40 000 euros	25	11.8	37	14.4	40	12.9	102	13.1
More than 40 001 euros	29	13.8	53	20.5	60	19.3	142	18.3
Missing	11	5.2	11	4.3	12	3.9	34	4.5
s.d.	1.650		1.875		1.741
Marital status
Married	27	12.8	101	39.3	128	41.3	256	33.0
Cohabitation	60	28.4	69	26.8	58	18.7	187	24.0
Single (incl. widow, divorced)	115	54.5	80	31.1	116	37.5	311	39.9
Missing	9	4.3	7	2.7	8	2.6	24	3.1
s.d.	0.940		1.154		1.397
Number of children living at home
0	165	78.2	152	59.1	176	57.0	493	63.4
1	21	10.0	45	17.5	71	23.0	137	17.6
2	14	6.6	29	11.3	42	13.6	85	11.0
3 or more	8	3.8	28	10.9	20	6.5	56	7.2
Missing	3	1.4	3	1.2	1	0.3	7	0.8
s.d.	0.791		1.074		1.019
Education
Elementary school	24	11.4	31	12.1	48	15.5	103	13.2
Secondary education	34	16.1	63	24.5	64	20.7	161	20.7
Vocational school	69	32.7	85	33.1	72	23.2	226	29.0
University degree	48	22.8	39	15.2	82	26.4	169	21.7
Other	33	15.6	36	14.1	41	13.2	110	14.2
Missing	3	1.4	3	1.2	3	1.0	9	1.2
s.d.	1.952		1.916		2.063
Profession
Leading position	10	4.7	20	7.8	20	6.5	50	6.4
Worker	96	45.5	116	45.1	104	33.5	316	40.6
Public servant	28	13.3	31	12.1	40	12.9	99	12.7
Other	71	33.6	85	33.0	144	46.3	300	38.5
Missing	6	2.8	5	1.9	2	0.6	13	1.8
s.d.	2.367		2.526		2.547

 

 

In overall, fixed-line connection seems to remain the most popular means of accessing Internet among all user segments. Even those respondents, who according to the operator’s database had the highest amount of mobile Internet data transfers on their personal accounts compared to other customers, reported using fixed-line Internet services daily and more often than mobile Internet services (see table 2). Among the Finnish population in general, fixed-line Internet connection is very common and over 90 percent have it on use. Mobile phone (GPRS or high speed data transfer) as a modem in connection with a computer is used only monthly by all user segments. All segments are using personal services mainly occasionally and self-services tend to be used more frequently compared to personal services.

 

The most popular mobile Internet service (α=0.8321) appears to be ordering occasionally ringing tones (50.8%) and logos (50.1). The most popular weekly used mobile Internet services were SMS-chat (6.8%) and using Multimedia Messaging Services MMS (3.7%). Fixed-line Internet connection (α=0.7206) was always (24.8%) or often (41.9%) used for banking. It was also often used for information search (42.7%) and communication (37.6%).

 

TABLE 2             Internet usage

	Mobile users	Fixed-line users
% Never uses mobile Internet connection	8.5 %	32.0 %
% Never uses fixed-line Internet connection	7.0%	0.8 %
% Uses daily mobile Internet connection	11.4 %	1.7 %
% Uses daily fixed-line Internet connection	42.3 %	64.7%
% Uses weekly (excl. daily use) mobile Internet connection	25.9 %	3.3 %
% Uses weekly (excl. daily use) fixed-line Internet	29.8 %	19.1 %

 

The respondents were asked to join different dimensions of seamless use experience with different Internet service delivery channels either according to their perceptions or actual use experience. Both segments of Mobile and Fixed-line users reported similar kind of beliefs about the dimensions of seamless use experience in different electronic channels. All the dimensions were rated more negatively in the case of mobile Internet than in the case of fixed-line Internet. Mobile Internet was seen as prone to errors (Mobile users 29.5% and Fixed-line users 13.5%) and difficult to remember (Mobile users 33.2% and Fixed-line users 21.3%) whereas the fixed-line Internet was seen easy to learn (Mobile users 75.6% and Fixed-line users 81.3%) and seamless to use (Mobile users 75.0% and Fixed-line users 76.2%).

 

The Fixed-line users trusted their primary delivery channel (fixed-line connection) even when feeling busy (56.6%) or traveling (18.0%). They also perceived mobile phone as a modem in connection with a laptop as free from time and place (21.9%) as the mobile Internet connection via mobile device (23.2%). It can be concluded that when a fixed-line Internet connection is not available, a typical Fixed-line user would be likely to choose the mobile phone as a modem the next best connection option. The Mobile users felt that mobile Internet is the most independent from time and place (66.0%) and also the easiest to use when traveling (54.0%). The Mobile users didn’t seem to believe in the mass adoption of mobile Internet services’ usage as they estimated that only 4.6 percent among their peers is currently using mobile Internet services.      

FIGURE 3                         Crosstabulation among the Fixed-line users on Internet usage frequency

and perception of the electronic service delivery channel’s seamless use experience

 

According to the conducted crosstabulation (see figures 3 and 4), the more customer is using a certain delivery channel, the higher the perceived seamless use experience towards that channel. For example, in figure 3 we have presented the perception of the Fixed-line users towards the seamless use experience in relation to their fixed-line Internet usage frequency. Respondents, who are daily using fixed-line Internet connection, also feel that it’s very seamless way of accessing Internet-based services. Similarly among the Mobile users, the perception of seamless use experience grows in relation to their mobile Internet usage frequency. Correspondingly the perception of seamless use experience towards fixed-line Internet lowers among the Mobile users as their daily mobile Internet usage grows and fixed-line Internet usage decreases.

FIGURE 4                              Crosstabulation among the Mobile users on Internet usage frequency and

perception of the electronic service delivery channel’s seamless use experience

 

An exploratory factor analysis was used in order to identify underlying constructs and investigate relationships among key survey interval-scaled questions regarding seamless use experience (see tables 3-5). It was necessary to repeat the factor analyses among each user segment to capture to possible differences in how they define seamless use experience. Principal Axis Factoring was carried out, followed by Varimax Rotation with Kaiser Normalization. The Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy (0.91-0.94) were well above the 0.5 recommendation level, and Bartlett’s test of sphericity (p=0.0 and p=0.0) provided as well support for the validity of the factor analysis of the data set (Malhorta 1999). Varimax Rotation facilitated interpretability. In addition, Gronbach’s alphas were counted for each factor scoring above the level of acceptance set by Nunnally (1978). Hence, the data set can be defined as reliable.

 

Initial runs based on a screen plot and eigenvalues showed support for five factors. Only factors with eigenvalues above 1 were expected. In our analyses the eigenvalues varied between 5.6475 and 2.4532. The criterion for assignment of reasons to a certain factor was a minimum factor loading of 0.5. The factors were labeled as learnability, satisfaction, errors, memorability and efficiency of use respectively.

 

Examination of the factor analysis for the dimensions of seamless use experience (presented in tables 3-5) suggests that the efficiency of use and memorability, and learnability and memorability are interrelated. The better one is able to learn the use of service, the easier its use is to remember and the more efficiently it can be exploited. The common factors for all user segments are bolded, the distinct factors are on italic and the common ones but loading a different factor are underlined.   

 

 

 

 

 

 

 

 

 

 

 

TABLE 3             Seamless use experience in the case of mobile Internet

MOBILE USERS and their perceptions about seamless use experience on MOBILE INTERNET	Factors
	1 31.0% α=.64	2 21.5% α=.87	3 15.6% α=.76	4 15.2% α=.84	5 14.3% α=.69
Factor 1: Learnability Previous experience in the use of electronic services Previous experience in the use of technical devices Structure and logic of navigation (site or menu) Personal abilities and qualities of the user Learning the services isn’t waste of money Good written instructions / manuals Factor 2: Satisfaction Problems are treated with discretion and confidentiality Problems are solved in a timely manner Operator offers after-sales services suitable for my needs Operator provides updated software needed to use mobile Internet services on their Web site Operator provides secure data transfers Speed of data transfer equals what operator promised Operator is never too busy to answer my questions I’m pleased with my operator’s Web site Factor 3: Errors Device gets jammed Service is not what I expected Speed of data transfer is lower than promised Data which I entered wasn’t saved There is no logic in service performance Downloaded program is not working on my device Connection cannot be established at all Too little memory on the device Insufficient instructions on how to use the service Factor 4: Memorability Distinct service name / site location / number Service functions in use resemble each other Device features remain constant regardless of the product generation Service’s name and location remains unchanged Service is actively advertised Login and passwords may be chosen by customer herself Service content remains the same Factor 5: Efficiency of use Amount of unnecessary information within the service Device specific limitations in the use of service Placement and interrelated order of keys on the device Level of service quality is constant Unnecessary device features	.778 .667 .629 .593 .577 .517	.743 .724 .674 .674   .657 .635 .591 .505	.675 .661 .651 .620 .619 .588 .581 .519 .515	.723 .723 .679   .623 .589 .544 .507	.715 .555 .545 .533 .528

 

 

Extraction Method: Principal Axis Factoring. 

Rotation Method: Varimax with Kaiser Normalization.

 

TABLE 4             Seamless use experience in the case of mobile Internet

 

FIXED-LINE USERS and their perceptions about seamless use experience on MOBILE INTERNET	Factors
	1 28.1% α=.67	2 23.2% α=.72	3 14.2% α=.74	4 19.3% α=.81	5 11.5% α=.62
Factor 1: Learnability Structure and logic of navigation (site or menu) Previous experience in the use of electronic services Consumers have been included in the service development Further instructions available upon request Personal abilities and qualities of the user Previous experience in the use of technical devices Personal instructing by the operator Service fulfills the goals I have set on it Factor 2: Satisfaction Service satisfies my needs Operator offers after-sales services suitable for my needs Operator is never too busy to answer my questions Problems are solved in a timely manner Problems are treated with discretion and confidentiality Operator provides secure data transfers Factor 3: Errors Service is not working in general Data gets lost and there is no guarantee of a successful transaction I don’t remember the information needed to access the service There is no suitable payment method available for me Cannot find the needed keys to operate the service Factor 4: Memorability Device features remain constant regardless of the product generation Service content remains the same Distinct service name / site location / number Service functions in use resemble each other Service’s name and location remains unchanged Service is actively advertised Factor 5: Efficiency of use Amount of unnecessary information within the service Unnecessary device features Device specific limitations in the use of service Slow speed of data transfer Level of service quality is constant Placement and interrelated order of keys on the device Operator remembers me with personal gifts	.725 .669 .625 .618 .586 .578 .571 .552	.751 .732 .694 .689 .573 .508	.646 .602   .571 .567 .533	.732   .701 .656 .647 .530 .526	.752 .749 .715 .605 .574 .569 .522

 

 

Extraction Method: Principal Axis Factoring. 

Rotation Method: Varimax with Kaiser Normalization.

 

 

TABLE 5             Seamless use experience in the case of fixed-line Internet

 

COMBINED USERS and their perceptions about seamless use experience on FIXED-LINE INTERNET	Factors
	1 30.2% α=.62	2 16.4% α=.78	3 11.4% α=.83	4 24.1% α=.63	5 11.2% α=.69
Factor 1: Learnability Previous experience in the use of electronic services Previous experience in the use of technical devices Factor 2: Satisfaction Problems are solved in a timely manner Problems are treated with discretion and confidentiality Operator offers after-sales services suitable for my needs I’m pleased with my operator’s Web site Operator provides secure data transfers Operator is never too busy to answer my questions Speed of data transfer equals what operator promised Operator provides updated software needed to use mobile Internet services on their Web site I’m offered unique customized offers and benefits Factor 3: Errors Connection cannot be established at all Speed of data transfer is lower than promised Device gets jammed Too little memory on the device Service is not what I expected Downloaded program is not working on my device Data which I entered wasn’t saved There is no logic in service performance Factor 4: Memorability Placement and interrelated order of keys on the device Device features remain constant regardless of the product generation Good written instructions / manuals Level of service quality is constant Structure and logic of navigation (site or menu) Rationality of provided service Service content remains the same Service functions in use resemble each other Amount of unnecessary information within the service Further instructions available upon request Factor 5: Efficiency of use Compatibility issues with device or service Web site is slow to download Service is not working in general	.655 .526	.772 .694 .685 .675 .668 .653 .605 .595   .555	.776 .708 .707 .679 .674 .673 .655 .632	.663 .646   .578 .568 .564 .560 .552 .543 .542 .523	.615 .555 .536

Extraction Method: Principal Axis Factoring. 

Rotation Method: Varimax with Kaiser Normalization.

 

Factors one, two and four appear to be defined by a mix of items that are mutual to all user segments (see bolded in tables 3-5). For learnability the common dimensions segment wise are previous experience in the use of electronic services and previous experience in the user of technical devices. For satisfaction we found four common dimensions: problems are treated with discretion and confidentially, operator offers after-sales services suitable for customer’s needs, operator provides secure data transfers and operator is never too busy to answer customer’s questions. For memorability the common dimensions among different user segments were service functions in use resemble each other and device features remain constant regardless of the product generation.  Vice versa, some of the dimensions were descriptive only for one user segment (tables 3-5 on italic). Furthermore, some of the dimensions accounted for the total variance of various factors depending on the user segment (table 6, also tables 3-5 underlined).

 

TABLE 6             Descriptive elements of seamless use experience by user segments

	Mobile users on mobile Internet	Combined users on fixed-line Internet	Fixed-line users on mobile Internet
Structure and logic of navigation (site or menu)	L	M	L
Learning the services isn’t waste of money	L
Good written instructions / manuals	L	M
Consumers have been included in the service development			L
Further instructions available upon request		M	L
I’m offered unique customized offers and benefits		S
Service satisfies my needs			S
Insufficient instructions on how to use the service	ER
Service is not working in general	EF		ER
Data gets lost and there is no guarantee of a successful transaction			ER
I don’t remember the information needed to access the service			ER
There is no suitable payment method available for me			ER
Cannot find the needed keys to operate the service			ER
Login and passwords may be chosen by customer herself	M
Placement and interrelated order of keys on the device	EF	M	EF
Level of service quality is constant	EF	M	EF
Rationality of provided service		M
Amount of unnecessary information within the service	EF	M	EF
Slow speed of data transfer			EF
Operator remembers me with personal gifts			EF

 

L = Learnability, S = Satisfaction, ER = Errors, M = Memorability, EF = Efficiency of use

In the case of mobile services, the interrelated placement of keys is part of efficiency of use whereas in the case of fixed-line electronic services it’s part of memorability. Written manuals affect the memorability of fixed-line electronic services and the learnability of mobile services. It can be concluded that customers perceive the usage of fixed-line Internet easier to learn than mobile Internet. It follows, that written instructions are rather needed when trying to remember how to use the services than when trying to learn how to use the service. In the case of mobile Internet, support from the written instructions is sought already during the learning period. Structure and logic of navigation constitutes learnability for seamless mobile service usage and memorability for seamless fixed-line electronic service. The constancy of service quality constitutes to efficiency of use for seamless mobile service usage and memorability for seamless fixed-line electronic service. Amount of unnecessary information within the service has a similar kind of effect on seamless use experience as the above mentioned service quality. When service is unworkable, the Mobile users perceive it as an inefficiency of use and the Fixed-line users relate it to errors in use.

 

6.    Discussion

On a scale of -3 to 3, efficiency of use and errors are seen as the most important usability attributes for both mobile and fixed-line Internet as an electronic service delivery channel. The mean value of efficiency of use for mobile services is 1.98 (s.d. 1.362) and for fixed-line electronic services 2.17 (s.d. 2.242). The mean value of errors for use of mobile services is 2.02 (s.d. 1.052) and fixed-line electronic services 2.13 (s.d. 1.017). However, even if both attributes are seen almost equally important, the performance of efficiency of use seems to get higher ratings among respondents (mobile -0.17, s.d. 1.558; for fixed-line 1.43, s.d. 2.330). This implies that the efficiency of use is taken better under consideration while designing the fixed-line electronic services or the implementation has been more successful in the eyes of the customers.

 

The importance of memorability attribute is perceived as the least meaningful by each segment. Perhaps customers don’t feel there are many things to remember in the usage of electronic services. Also, if customers are using an average of three mobile services as the results of this study indicate, usage of such a small number of frequently used services can be easily memorized. The performance of memorability was rated low for both channels (mobile -0.25, s.d. 1.406; fixed-line 0.64, s.d. 1.830) but doesn’t necessarily lead to extensive actions by the marketers and designers as the importance of this factor was also rated low (mobile 1.37, s.d 1.179; fixed-line 1.28, s.d. 1.463).

 

The seamless use experience dimension of satisfaction appears to be service provider related rather than service content or device specific. For example, the promised speed of data transfer by the operator (r = .271, p<0.01) and the installation of Internet connection in time (r = 0.160, p<0.001) correlate with the satisfaction. Different dimensions may be mutually descriptive for several factors whereas one dimension may be descriptive only for one particular factor. We have a reason to believe that the different dimensions of seamless use experience vary also depending on customer’s demographic, technographic and psychographic profile. By knowing customer and service delivery specific dimensions of seamless use experience, marketers are able to focus on accurate dimensions describing each factor. When one may be lacking learnability, other’s memorability may be needing attention. 

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