Usability of user interfaces has been studied in depth, therefore several extensive collections of general user interface guidelines (among others Brown 1988, Marshall et al. 1987, Mayhew 1992, Smith et al. 1986) and methodologies (eg. LUCID, Kreitzberg 1996) to develop and to enhance user interfaces exist. In our research we are not trying to define the place of a button on a cell phone or the place of an icon on a screen, but we are trying to focus more on the usage of the mobile and fixed-line services itself. The goal is to find out what kind of things affect or hinder seamless usage of the mobile and fixed-line services. Conventional usability testing does not pay much attention to real use environment (Lindroth et al. 2001, Kim et al. 2002). The importance of use context should be seen in the case of mobile services, which are used via mobile devices. The environment in which usage takes place can be a long way off an office of any kind: normally usability tests are performed in an office environment. Interaction between a mobile device and a user might proceed very differently from the designers’ assumptions, and this might lead to customer dissatisfaction and frustration (Babbar et al. 2002).

Ketola (2002, 64) points out that sometimes mobile phones are blamed for the failures due to network or service problems. People do not understand the pile or structure of different layers (Figure 1) that is needed to provide mobile services. The orginal model by Ketola (2002) was presented in a pyramid format, in which each layer was dependent on the underlying ones. We argue that the hourglass format is better in describing the interface hierarchy. Thus, the central operations are radially dependant from both upper and lower layers. The mobile phone itself is not useful without functioning services, which on the other hand trust the network infrastructure to e.g. take care of the messages to be sent. Accessories on the top of the pyramid are useless without functioning phone. Ketola continues that during the mobile phone design and development it is quite impossible to take into consideration or affect all the service related issues, because those are partly reliant on communication quality, which is still dependent on the prevailing capabilities of terminals and network systems. (Ketola 2002, 64) In this study, we do not take stand on things, which are related in network or infrastructure issues. The focus of this study is described by the dotted line in Figure 1. As we are concentrating on actions in and on the customer interface, the dotted line between user interface and service interface describes the focus. Customer interface is dependent on service interface and user interface. As both user interfaces and electronic services are increasing in complexity and functionality, we believe that a deeper reasoning for their optimal integration is required.

Figure 1: Interface hierarchy (modified from Ketola 2002, 64)

Marlatt (1998) seeks for a mediator to interpret the users’ needs to language understood by design/development people. From service developers’ point of view it is important to notice that there is strong evidence on the link between customer loyalty and satisfaction (e.g. Oliva et al. 1992). In electronic commerce retaining loyalty of the customers is seen very crucial, and the value of an Internet store is closely related to the number of loyal customers (Lee et al. 2000). In the case of mobile services technological determinism might not be the answer, but taking customers’, users’ of mobile services, perspective as the basis to enhance mobile services. Usability problems are understood as one of the most critical barriers for mobile Internet (Creativegood 2000).

During the first few years of Internet shopping it was noticed, that it is not the latest technology that brings customers. Customers do not view shopping from technology perspective, but shopping perspective. The unique characteristics of this, new at that time, retail channel have to be used to support the way customers shop. (Järvenpää 1997) In today’s electronic commerce, especially in mobile services’ context, this is a point to consider and never to forget.

In our study we are try to see usability problems in larger scale, and therefore we use the term seamless user experience, with which we refer to the mobile services as a whole. What kinds of things hinder the usage of the services, what do the customers really want to accomplish with the service, what are the ultimate goals of the customers, are they really satisfied and so on? We are trying to find a way or tools to help the service developers to be able to work out better, 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 might change to use the services of another provider.

Vaughan (1999) surveyed users (mainly students) of Internet search tools and found out that utility knocked out convenience. Three out of four of the respondents (72.6% vs. 22.6%) preferred utility in choosing between different web search tools. This might imply that utility of electronic services in general should not be underrated. The present/future third generation (3G) or UMTS (Universal Mobile Telecommunications System) related electronic services should offer customers, who have been listening to promises of service providers and network operators, real value to gain acceptance.

In the literature there are several definitions for usability, how usability is divided into several attributes, which together constitute the overall usability. In this study we focus on the customers’ seamless use experience in mobile and stationary electronic services’ environment. In addition to general usability problems related to human-technology interaction, we want to stress the context and the purpose of use equally. The main research question in this study is:

“How are the different dimensions of seamless service use experience formed in mobile and fixed-line Internet?”

In the research papers we present insights on the dimensions of seamless use experience and how it varies depending on the service delivery channel, customer specific variables (such as demographics and innovativeness), use context and purpose of use (content). For example, Romar et al. (2003) have made a research proposition according to which “customer experience will be important in determining both adoption of and satisfaction with technology products”. Although the main emphasis is on mobile services and mobile Internet service interface, it was necessary to include also the current fixed-line Internet users in this study as they possess valuable insights on the usage of technology-based services and may form a group of potential future mobile Internet customers.

1.2 Survey study in seamless use experience research

A survey is a way of getting a picture of the current state of a group. In many cases, surveys are snapshots, pictures of a particular point or period in time (Janes 1999). Longitudinal surveys take place over longer periods of time. The steps of building a good survey do not happen in a vacuum. Writing a good, nonbiased, answerable questionnaire is challenging. The order of questions may have an impact on the answers one gets (Janes 1999). It is important to be specific in questions and sometimes even give specific instructions how to answer the survey questions. Some use a free-response technique (open questions) to determine important factors or causes while others ask customers to check or rank a set of predetermined factors (structured questionnaire) (see for example Yammarino et al. 1991, Parker et al. 1983).

Non-response is a feature of virtually all surveys, damaging the inferential value of the sample survey methods (Lin et al. 1995). The non-response has been attacked by advanced letters, payments to respondents, and timing calls on sample (see for example Groves 1989) and through adjusting post-survey by weighting cases by estimated probabilities of co-operation and by known population quantities, imputation, and selection bias models (see for example Little et al. 1987). Difficulties of reporting and interpretation are also related in surveys.

Arguments on behalf and against online surveys have been presented actively during the few last years. E-mail surveys have been said to offer higher response speed and rate than postal surveys (Comely 1996, Schaefer et al. 1998, Weible et al. 1998, Cho et al. 1999, Dommeyer et al. 2000, Adam et al. 2000). Zadeh et al. (2000) claim, that online survey allows more intricate ranking and rate matrices than postal survey. However, Couper (2000) presents doubts about the validity of online surveys. The misuse of respondent information is present in the online environment (Cho et al. 1999). There is also some concern that given time as novelty wears off, the online surveys will suffer from the same disadvantages as the traditional methods (McDonald et al. 2003).

1.2.1 Causal modeling

Exploratory, descriptive and causal researches are the most typical, classical examples of research design found in the literature (e.g. Aaker et al. 1995, Churchill et al. 1995, Zikmund 1991). Exploratory research stresses the discovery of ideas and insights. Exploratory research deploys data analysis, experience surveys, focus groups and case analysis as research methods (Churchill et al. 1995, 147-163). Descriptive research is used in characterizing certain groups, estimating the proportion of subjects with a certain feature in a certain population and making specific predictions. It deploys longitudinal analysis and cross-sectional analysis as research methods (Churchill et al. 1995, 163-180). The very fundamental point in descriptive research is “to name the properties of things: you may do more, but you cannot do less and still have description” (Cooper et al. 1995, 11). Zikmund (1991, 33) points out the paramount importance of accuracy in descriptive research.

Causal research tries to find out cause-and-effect relationships (Aaker et al. 1995, 73-75). From the scientific research perspective causality is impossible to prove, but still researchers seek evidence to be able to understand and predict relationships (Zikmund 1991, 34-35). In causal research instead of empirically demonstrate that variable ‘A’ produces ‘B’, or ‘A’ forces ‘B’ to occur, probabilistic statements based on observations and measurements are produced (Cooper et al. 1995, 123). If there, according to calculations, is a link between ‘A’ and ‘B’, then an association is expected to prevail (Bagozzi 1980, 33).

In marketing causality is seen more like an assumption or an inference than a verifiable phenomenon. However, it is feasible to come up with rough subjective likelihoods how reasonable an association between two variables might be. What constitutes a reasonable “certainty” is up to persons and circumstances. (Zaltman et al. 1982, 48). Bagozzi (1975) contends that exchanges are generated by human behavior, where people not only react to events or actions of others, but also self-generate their own acts, which are purposeful, intentional and motivated.

The concept of causality is seen complex. There is a gap between common-sense notion and scientific notion of causality. According to common sense, a relationship ‘A’ → ‘B’ is deterministic, but precise scientific approach sees only probabilistic relationship between the two variables. Common sense might state that there is only a single cause of an event, but scientific method finds this single cause being only one of the multiple causes. Common sense says that there can be enough evidence to prove that causal relationship exists between two variables, but scientific approach denies this promising only a possibility to infer that a variable is a cause of another. (Aaker et al. 1995, 324-325)

Shett et al. (1988) has described and evaluated all the major schools of marketing thought that have emerges since marketing was understood as an independent discipline in the early 1900s. They divide the different schools of thought into four groups: Noninteractive-Economic, Interactive-Economic, Noninteractive-Noneconomic and Interactive-Noneconomic. A school of marketing thought has to possess few criteria: It must have a distinct focus which is relevant to marketing goals and objectives by answering to question that who will or should benefit from marketing activities and practices, and secondly the viewpoint of the pioneer scholar must have been interesting and worth pursuing in marketing. (Sheth et al. 1988, 19)

According to classification of marketing schools of thought by Sheth et al. (1988, 20) this study would be best categorized as belonging to the buyer behavior school which has noninteractive and noneconomic perspective. This specific school of thought has focus on customers in the marketplace, and its important topics have been how many and who are the customers and why customers behave the way they do. The unique characteristics of the buyer behavior school are to great extent outcome of the why aspect. Consumer behavior is considered as a subset of human behavior, which differs from treating it as a unique phenomenon similar to abnormal or deviant behavior. Emphasis in the buyer behavior school has been to great excess on consumer products such as packaged goods and consumer durables, but there has been increasing interest in industrial and services buying behavior. Instead of trying to understand choices of product class, volume or timing the school of thought has delimited itself to understanding brand choice behavior. (Sheth et al. 1988, 109-110)

The ultimate goal in social science is to find or uncover patterns conducive to explanations and predications (Johannessen 1997). Causal path modeling (also known as structural equation modeling) is based on utilization of data analytic techniques such as regression analysis and structural equation modeling, which make use of quantitative data (Bozionelos 2003). Structural equation modeling is a generic term to signify techniques, e.g. AMOS (Arbuckle 1995), EQS (Bentler 1995), LISREL (Joreskog 1974), SAS-PROC CALIS (SAS Institute 1989), that are based on less restrictive assumptions than the least-square regression analysis. “These techniques allow testing of measurement models between latent variables, which are the constructs that are represented by the researcher’s measures, and their measurements, or manifest variables” (Bozionelos 2003).

The author of causal path analysis, Wright (1921, 1934) has stressed the importance of last step, which involves decisions regarding the paths to be retained and the assignment of values to the respective path coefficients. Data to be used in causal pat modeling can be obtained with the quantitative research designs that are available in social sciences including longitudinal and cross-sectional designs (McDonald 1977, Asher 1983).

1.2.2 Methodological limitations

“Human behavior can never be predicted with certainty because of its intrinsic “wave” nature. In fact, one can now see that the variance, the error that is evident in all experimental data, is the ignored volitional side of the human subject. Our “wave” side is the reason there is a “built-in” variability that can never be accounted for in the purely “particle” approach of an objective social science as psychology is presently conceived.” (Valle 1981, 433)

The determination of a cause is very useful for marketers if the cause is manipulative. By manipulating the cause marketers can achieve desired outcomes, be it the sale of a product or service. More certain estimates of how reasonable a particular causal relationship is can be achieved through a better understanding of the issues related to dealing with causality. (Zaltman et al. 1982, 69)

Causal modeling includes at least three unsolved conceptual problems related to scientific explanations, namely reductionism, reification and explanation across levels of analysis. Reductionism is defined by Hoult (1972, 267) as “idea that the principles explaining one range of phenomena are adequate for explaining a totally different range of phenomena – for example, the idea that human social behavior is ultimately psychological, or that human psychological behavior is ultimately biological.” In marketing at least two types of reductionisms can be pointed out. The first one implies that all marketing phenomena at the social level can be simplified to dyadic exchanges. The latter one goes even farther by stating that all marketing behavior can be presumed reducible to the actions or characteristics of individuals, especially as represented in psychological phenomena and laws. (Bagozzi 1980, 57-58)

Reification is defined by Keat et al. (1975, 138) as “the ideological distortion by which social phenomena are seen not as constructions of human activity, but as material things having natural rather than social properties.” From marketing researcher this requires exercising extreme caution in inferring causality between aggregate or social constructs in such case where the variables and the relationships between them are purely abstractions in the mind of the observer and are lacking in lawlike or natural necessity content. (Bagozzi 1980, 59)

The problem of explanation across levels of analysis comes up when both social and psychological variables, one is tried to explain with the other, are included in theories. Cause-and-effect is supposed to occur between social and psychological variables. (Parsons et al. 1976, 16-17) The possibility of spurious relationships and false inferences might cause a problem in employing concepts across levels of analysis. Exogenous variables or unknown processes involving the modeled phenomena may cause the correlation of systematic or environmental variables with e.g. organization structural variables – the cause-and-effect processes must be demonstrated. (Bagozzi 1980, 59-60)

1.3 Mobile communications: past, present and future

As the generations of mobile phones change from one to another, the versatile service aspect comes more and more real: The first generation of mobile phones was meant to satisfy the same need that normal landline phone was supposed to. Non-telephony functions like text messaging, calendars and finally Internet connectivity and possibility to send multimedia messages are features of average present day’s mobile phones. Now, a mobile phone is an interactive system[1], an information appliance[2] and a personal communication system enabling person-to-person and person-to-interactive system communication – not anything less.

First-generation mobile communications system was an analog system for voice transmission only. System development and standardization were very country specific issues. After introduction of second-generation digital systems, some of the countries run down the analog systems, but e.g. United States runs both systems parallel, because analog system’s coverage is wide and charges low. In Japan the first analog mobile communications systems was NTT car phone service, which was introduces in 1979. About at the same time in Nordic Countries plus in Germany and in France was the first analog systems introduced for public usage.

Second-generation mobile communications systems are digital and they enable the provision of voice, data, facsimile and various other value-added services. The GSM system has been the leader of second-generation mobile communications in Europe, Asia, Africa and Oceania enabling seamless communications through roaming across national boundaries. In the United States three systems – TDMA, CDMA, PCS1900 are used in parallel. Japan has adopted the PDC system, which is different from either the European or US systems. In PDC system services are offered within the domestic market only.

Third-generation mobile communications systems are called IMT-2000, which is a generic name for five systems established so far. International Telecommunication Union Radiocommunication Sector (ITU-R) recommends the provision of multimedia service and seamless service by setting certain conditions for communications speed. With the aim to develop networks that can provide services on an internationally seamless basis, standardization plays major role and is run by organizations in Japan, the United States and Europe.

The vision of future is one that fully supports all forms of mobility including personal, terminal, session and code. The two main research areas on fourth-generation technologies include better modulation methods and smart antenna technology (PriceWaterHouseCoopers 2001). The Internet from ten years from now will be characterized by a move away from intelligence within the network or at the edges to intelligence everyway (Reynolds 2003). Internet 2010 can be defined as “a simplified access for the user to all of their services across multiple radio technologies and networks. Their services adapting, notably to the available bit rate, without forcing them to manage the consequential complexities.” (Reynolds 2003). The Internet 2010 will evolve towards a more generic solution making the support for services by different networks easier (Wu 1999) and possible to use differing technologies to support services in a way to optimize performance and cost trade-offs (Reynolds 2003). How to provide seamless mobile station transmissions while the mobile unit is moving at high speed among small wireless cells in is an important issue for the future (Chao 2001).

1.3.1 Case NTT DoCoMo, Japan

As early as 1996 president of NTT DoCoMo, Mr. Koji Oboshi, saw the need to develop new services and capabilities into mobile phones. Otherwise, the demand for new mobile phones would peak and it would be difficult to get consumers to trade in their old mobile for a new, improved one. NTT DoCoMo is the leading mobile communications company in Japan, therefore the possible fading away of the customer base was a real concern. (Bradley et al. 2002)

The vision of Koji Oboshi was that the future lay in non-voice, or data, communications. In the beginning of the year 1997, Keiichi Enoki was delegated responsibility to build a new organization, which would concentrate on non-voice communications for retail consumers. From a staff of 10 Gateway Business increased the number to a total of 70 by August 1997. The newborn organization was working on a new service called i-mode, which would offer mobile Internet service to customers over their mobile phones. (Kodama 2002)

To be able to make i-mode successful Gateway had to develop a network enabling the content delivery, develop the mobile phones that could receive the content, and together with the Internet service providers design the content appealing to the end-user customers. As Keiichi Enoki realized the amount of work to be done he saw a solution in collaboration with other divisions within DoCoMo, Internet service providers, terminal manufacturers and platform vendors. Collaboration between several parties was not smooth at all times, but instead of running away from conflicts, Enoki used them as a basis for debate. (Kodama 2002)

NTT DoCoMo started the i-mode service in the beginning of 1999. Three different strategies were developed to create an explosive growth in the take-up of the service. DoCoMo outside ISPs comprised a portal community for developing the portal strategy, which aimed at creating content, an advertisement delivery service and a financial service linked to the Net-based banking service. (Jonason et al. 2001)

DoCoMo together with companies such as Sony Computer Entertainment and Sun Microsystems formed the technical community (the terminal strategy). By keeping on top of technical advances and making improvements to the phones, DoCoMo thought that customers would be keen to pay to add new features to their phones and thus create a new source of revenue for DoCoMo. The platform community worked on new platforms (game consoles, car navigation systems) also trying to create a new source of revenue. (Kodama 2002)

The pace at which customers took up the new service was more swift than expected. By June 2002, the i-mode service had over 33 million subscribers. In July 2001, Gateway became the i-mode business division and began work on IMT-2000 (3^rd generation mobile service). (Kodama 2002, Information & Communications in Japan 2003)

Mobile services offered in Japan can be categorized into five groups as follows: Photo mail service by mobile terminals with built-in digital cameras, video mail service by mobile terminals with built-in digital cameras, location information service, video distribution service and application downloading service. For the moment, Japan is the largest mobile Internet market with about 55 million users. NTT DoCoMo has started to offer i-mode services overseas – in Germany, The Netherlands, Belgium, France, The United Kingdom, Taiwan, Malaysia and Spain. (Information & Communications in Japan 2003)

1.3.2 Mobile phone services in France

The three French mobile carriers – Itineris, SFR and Bouygues Telecom – have introduced numerous commercial and organizational innovations (Hamdouch et al. 2001). The mobile phone services have been marketed since 1987 in France. The technological and legal evolutions forced Itineris to expand its monopoly to other service providers. The competition on mobile phone services market had concentrated on development of infrastructures until the arrival of Bouygues Telecom in 1996, which launched price competition and carriers trying to increase their network’s value for enticing new customers (Hamdouch et al. 2001).

Commercial innovations modified the service modalities to affect the customer’s evaluation of the service and thus the carrier’s image (Hamdouch et al. 2001). The commercial innovations included new products sold to customers and better relations to customers. The first commercial innovation consisted in discriminating customers according to their communication time. On the other hand, new services such as taxi or restaurant booking and on-line news became available (Hamdouch et al. 2000). Organizational innovations included new functions and tools for customer care. The adoption of project-based management increased the carrier’s flexibility. Carriers developed new or prioritized activities, which previously appeared as minor. Carriers devoted specific staff for specific tasks and become increasingly aware of the importance of proper distribution channel structure and marketing functions (Hamdouch et al. 2001).

1.3.3 Mobile communication development in Finland

The first car phone network (ARP) in Finland was opened in 1971 and covered the whole country by year 1978 (see Figure 2). The telephone exchange was manually operated although it was systematically automated. Car phones had separate frequencies for receiving and transmission of phone calls (Kangasluoma 1977). ARP-network was shut down in year 2000. The development of common Nordic radiophone network (NMT) was started on the 70s and it was taken under a commercial use in year 1982. It was started as a 450 MHz network but quickly developed into a 900 MHz network to add capacity. The updated version of NMT-network was taken in use in 1987 (Suomi 1990, 15-16). NMT-network was fully automated and offered also value-added services such as voicemail and phone conferences (Pasanen 1991). NTM-network in Finland was shut down in year 2000. Finnish operator Radiolinja was the first in the world to open GSM-network in 1991. All the phonecalls traveling in GSM-network are encrypted. GSM is a worldwide standard and offers unnumbered amount of value-added services. With GSM, the short messaging services SMS was introduced. (Uusitupa 1995). Also data phonecalls and faxcimile are possible via GSM-network (Söderbacka 1994).

3G 4G xG

Figure 2: Mobile phone network development in Finland

GPRS-network in Finland is built on GSM-network and opened in 2000. GPRS-network is packet switched network offering a data transfer speed of 115kbit/s. The introduction of GPRS is expected to boost the use of mobile Internet services, as the pricing of GPRS is based on transferred amount of data instead of time and GPRS is also enabling more efficient and seamless use of WAP-services. So-called third generation network UMTS has been in trial use in some regions (for example in city of Oulu) since year 2002. For starters, UMTS-network offers data transfer at a speed of 384kbit/s but the speed is expected to grow up to 2Mbit/s. Its full deployment is expected to take place within couple of years.

1.4 Introducing the dissertation papers

1.4.1 # 1: The Different Dimensions of Seamless Use Experience in Electronic Environment

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.

1.4.2 # 2: The Effect on Demographics on Seamless Mobile Service Interface

The purpose of this paper is to demonstrate the effect of demographic variables on choice of a service delivery channel and on the factors affecting the seamless user experience related in different electronic channels. Profession proved to have the most diverse effect in this study as it affects the usage of all the other channels except the option of personal service. To elaborate the relationship between demographics and dimensions of seamless use experience further, we conducted ANOVA for all the user segments – Fixed-line, Mobile and Combined users. The results are based on a large consumer survey conducted among mobile and fixed-line Internet users in Finland during summer 2003.

1.4.3 # 3: Service Content and Context Affecting the Dimensions of Seamless Mobile Service Interface: Case Errors

The results presented in this paper outline, in which context the mobile Internet services are used and how services fall into different purposes of use. This paper focuses on identifying the errors, which people experience while using the mobile Internet in different contexts and for different purposes of use (content). The importance of use context should be seen in the case of mobile services, which are used via mobile devices. The real use environment is not taken too profoundly into consideration as usability tests are conducted. However, we did not find results supporting the claim that mobile Internet services are used in movement. We found three different types of errors: technology, service and user related. Based on Fixed-line users’ beliefs on low error rates in the case of mobile Internet, we conclude that usability doubts are not hindering their usage of mobile Internet.

1.4.4 # 4: Relationship between Seamless Use Experience, Customer Satisfaction and Recommendation

Relying on SERVQUAL service quality dimensions by Parasuraman et al. (1985, 1988), this study identifies the service quality dimensions pertaining seamless use experience and investigates the relationship between customer satisfaction and intention to recommend mobile Internet services. According to our analysis, which is based on data comprising of 778 survey responses among mobile and fixed-line users, the level of satisfaction after using mobile Internet services, intention to encourage the use of mobile Internet services and willingness to recommend the use of mobile services are strongly interrelated.

2 Seamless mobility: A framework development

2.1 Remarks from literature synthesis

Blazevic et al. (2003) define mobile innovations as any new services that are delivered with the support of wireless devices. Mobile services enable users to make purchases, request services, access news and information, and pay bills, using mobile communication devices such as PDAs, laptops, and mobile phones (Siau et al. 2003). Siau et al. (2003) define four key drivers for mobile services: mobility, reachability, localization, and personalization, of which they see the mobility as the primary advantage of mobile services. Through mobile devices, entities are able to reach customers anywhere, anytime. The knowledge of a user’s physical location at a particular moment also adds significant value to mobile services, and personalization filters information or provide services in ways appropriate to a tailored user (Siau et al. 2003).

“An interface is the visible piece of a system that a user sees or hears or touches.” (Head 1999, 4)When computer vendors understood the significance of users’ standpoint term “user friendly” came up. However, a system being friendly to one may not feel that nice to another. Since then user interface professionals have introduces several terms referring to the same area of interest. Familiar names are like CHI (computer-human interaction), HCI (human-computer interaction), UCD (user-centered design), MMI (man-machine interface), HMI (human-machine interface), OMI (operator-machine interface), UID (user interface design) etc. (Nielsen 1993, 23)

Usability is a collection of various interacting properties including intuitiveness, ease of use, efficiency of use, and reliability. In this case mobile system is defined as a combination of software and a specific device (Clevenger 2002). Experiments have shown that “usability” of a service cannot be predicted from the technical quality of its components. This is because of the interaction between objective performance measures and functionality (Boves et al. 1999). Usability can be also defined as part of the culture of a company when virtually all processes are built around the true needs of users. Narrowly, usability is defined as a product attribute (Rhodes 2001). Product usability is achieved or improved by first understanding users’ needs, which are determined by collecting data on actual representative users’ interactions with products.

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. With learnability as a usability atribute we refer to the difficulties customers experience when trying to learn how to use the electronic service. 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. Memorability 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. Errors as a usability attribute in our context is two-fold like efficiency of use. Minor errors hinder the use of the electronic services, but don’t affect the final outcome. Catastrophic errors lead into a situation, in which the customer is unable to finish the use of electronic service in a desired way. ). 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.

2.2 Theoretical background

A consumer, who is a beginner in mobile Internet service usage, may possess minimal knowledge about the set of service alternatives available, the attributes possessed by these alternatives, and the decision criteria to evaluate these alternatives. To simplify the decision process, the consumer may turn to a friend, relative or peer for a recommendation. When seeking a recommendation, the consumer has no particular alternative under consideration (Gershoff et al. 2001). Customers on a trying stage of electronic service usage can quite easily evaluate and compare the benefits of competing services and switching costs are low. Thus, customer retention in e-services is of paramount importance (Reichheld et al. 2000).

Marketers must expand their horizons as mobile business emerges. Marketers need to wrestle with time-sensitive microsegmentation – marketing to the individual customer at specific points in time (Armstrong et al. 1996). New technologies applied to user interfaces such as virtual worlds and network-based games, have been targeted to increase sales. Abad et al. (1998) argued that by adopting new user-interface technologies customers can be offered powerful and easier-to-use tools to use electronic services in such way that they need not to be concerned about technical issues related to their communication media. In a world where product becomes place becomes promotion, the value proposition is recasted. Information-defined transactions – value creation and extraction in the marketspace – are creating new ways of thinking about making money (Rayport et al. 1994). The technology-based interactions are expected to become a key criterion for long-term business success (Meuter et al. 2000).

Dabholkar (1992) explored how attitude toward computerized products and a need for interaction with service employees affect attitudes. He found that both factors influence consumer attitude towards using technology-based service. Traditionally mobile telephone has been examined as an independent service (Baldwin et al. 1996) but it can be also put into a wider context of interconnected technologies (Lundgren 1991, Dutton 1996). Distribution channels for mobile telephony compete with and become connected to distribution channels for example for computers and other products of interconnected technologies. Links between technologies within a technological system will change over time and affect the structure of the industrial network and firm behavior (Andersson et al. 1997).

It has been recognized in the academic studies that technology in the delivery of services will have a critical importance (Bitner et al. 2000; Fabholkar 1994, 1996; Parasuraman 1996; Quinn 1996). Internet can be performance-enhancing as readily as it can be performance-destroying. Demand-side advantage enables firms to charge higher prices at a given level of demand or generate a higher demand at a given price (Geyskens et al. 2002). The Internet can increase sales in three ways: market expansion, brand switching, and relationship deepening (Quelch et al. 1996). Degeratu et al. (2000) suggested that during the honeymoon period of the Internet market, consumers are less price sensitive and more affluent. Blazevic et al. (2003) present a similar kind of research finding. The Internet may also offer supply-side advantages through reduced production and transaction costs: transaction processing is eased, thereby reducing paperwork (Hoffman et al. 1995), inventory costs may be reduced as intermediaries are bypassed (Benjamin et al. 1995) and some marketing functions are shifted to the customer.

Perhaps the ultimate goal of any service organization is to deliver seamless service (Grinstead et al. 1994). Lee et al. (2000a) states that Internet stores wanting to succeed in electronic commerce need an appropriate customer interface, i.e. the user interface of e-commerce systems. Tolonen (1999) describes the future customers as calling for immediate actions and solutions for their problems. She continues that the next century generation has grown up with mobile phones, Internet connections and hectic lifestyles. She suspects that the success in Web information management will not only depend on high capacity networks but also on the quality of service provided to the users.

Convenience is integral to the marketing of both goods and services. The continuous rise in consumer demand for convenience has been attributed to socioeconomic change, technological progress, more competitive business environments, and opportunity costs that have risen with incomes (Etgar 1978, Berry 1979, Gross 1987, Seiders et al. 2000). Marketers must develop a more precise and complete understanding of the concept of convenience (Berry et al. 2002). Morganosky (1986) found that consumers are willing to sacrifice convenience for lower price as well as pay for convenience. Due this and other inconclusive findings (e.g. Reilly 1982, Bellante et al. 1984, Voli 1998), researchers have yet to understand the price-convenience trade-off process. Romar et al. (2003) propose that “consumer adoption of wireless technology will depend on cost of ownership of the technology and of the perceived value it provides”.

Too few built Web sites with clearly defined goals and target markets. Too little attention is given on the context of use, for example (Lindroth et al. 2000) and yet understanding where and when users experience difficulties while performing tasks on a Web site is critical to improving the design of a site (Waterson et al. 2002). Internet service providers have been successful in developing new features but are less successful in focusing their attention on those features that are most desired by the customer (Sultan et al. 2000). In order to support business decision-making, investment decisions, and the development of purposeful mobile services, an understanding of the elements and special features of wireless electronic channels that are value-adding from the consumer’s point of view needs to be built (Anckar et al. 2002). Mobile services have been said to comprise time and space advantages in comparison to Internet services (Barnett et al. 2000, O’Shea et al. 2001) but one of the critical requirements for the success of electronic commerce is the appropriate customer interface (Lee 2000b).

Wireless carriers have generally been successful in gaining considerable revenue from customers and have, hence often been very profitable (Jonason et al. 2001). Barwise et al. (2002) suggest that consumer response to permission-based mobile advertising is not particularly vulnerable to wearout. There was no sign of declining enthusiasm or consumer acceptance in samples taken at different stages when they studied consumer response to the experience of receiving permission-based mobile advertising. Voice messaging services provide an example of an industry that has successfully handled the transition to the electronic environment (Rayport et al. 1994). Operator could attempt to provide its own content for profits as Evans et al. (2000) have said: the content provider brings the richness while the operators bring the reach.

Research is needed with respect to the influence of technology on all customer responses, such as perceived value, satisfaction and loyalty (Parasuraman et al. 2000) Solomon et al. (1985) explored personalization in the dyadic interaction between service providers and customers and the resulting customer satisfaction with the service. Developing insight into the determinants of satisfaction is important for the managers in charge of designing the service. Avkiran (1999) postulates that quality customer service demands human contact. He argued that those advocating high-technology solutions as substitutes for personal service may be ignoring the essence of high customer service quality which involves staff-customer contact. In the spirit of Avkiran’s (1999) postulation, Lee et al. (2000) found tangibles to be more important factor in the facility/equipment based than in the people-based service industries.

“The way that you accomplish tasks with a product-what you do and how it responds-that’s the interface” (Raskin 2000, 2). Many of the interface designers understand the need for user or customer centered design but too frequently opinions are asked from experts who do not excel in human psychology. (Raskin 2000, 2) When user-centered design is applied end-users are involved throughout the design process. To guarantee fulfillment of end-users’ expectations the design process is highly iterative: user centered approach deploys parallel testing and measurement techniques which are based on design guidelines. (Head 1999, 27).

2.3 Model construct

Path analysis is a useful tool for evaluating the relationship among a set of variables. To address the model depicted in Figure 3, a computer program AMOS will be used, by specifying an analysis based on the sample correlation matrix with maximum likelihood estimation. The postulations presented in table 1 have been formulated based on extensive literature review.

Figure 3: A causal diagram of the S-C-R model

Table 1: Research postulations

... affects positively learnability

Good manuals and written instructions

Personal instructions from the operator

Logical navigation

Customers were involved in the service development

Personal abilities and qualities of the user

Possibility to get further instructions if needed

Previous experience in the use of electronic services

Previous experience in the use of technical devices

By learning the service I will benefit personally

…affects positively efficiency of use

Service fulfills my needs

Use of service doesn’t consume too much time or money

Placement and interrelated order of keys on the device

Constant level of service quality

Features of screen (size, colors)

…affects negatively efficiency of use

Slow speed of data transfer

Unnecessary device features

Amount of unnecessary information within the service

Device specific limitations in the use of service

…affects positively 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

Links available to other related services

Logical service

Service content remains the same

…affects negatively errors (adding to perception of experienced errors)

Device gets jammed

Speed of data transfer is lower than promised

Service is not what I expected

Data which I entered wasn’t saved

Downloaded program is not working on my device

Connection cannot be established at all

Too little memory on the device

No logic in service performance

I don’t remember how to use the device

Insufficient instructions on how to use the service

Unsuitable device to operate the service

…affects positively satisfaction

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

I’m pleased with my operator’s Web site

Operator provides secure data transfers

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

New Internet connection is installed within the promised timeframe

Mobile Internet users

P10

P11

P12

P13

P14

P15

P16

P17

P18

P19

P20

P21

P22

P23

P24

P25

P26

P27

P28

P29

P30

P31

P32

P33

P34

P35

P36

P37

P38

P39

P40

P41

P42

P43

P44

P45

P46

P47

P48

Fixed-line Internet users

P10

P11

P12

P13

P14

P15

P16

P17

P18

P19

P20

P21

P22

P23

P24

P25

P26

P27

P28

P29

P30

P31

P32

P33

P34

P35

P36

P37

P38

P39

P40

P41

P42

P43

P44

P45

P46

P47

P48

3 DISCUSSION

3.1 Data collection

In this study, the mobile Internet is defined as usage of Internet via handheld devices such as mobile phones of PDAs. Mobile Internet services do not include SMS and other typical mobile phone services. Mobile Internet services in Finland mainly consist of services accessed via GPRS and/or WAP-enabled mobile phone. Our study can be seen as a cross-sectional one, because it provides a snapshot of the variables we are interested in at a single point in time, namely summer 2003, and due to the number of respondents in each user group the sampling units form a representative sample of the mobile and fixed-line users of electronic services (see e.g. Churchill 1995, 177).

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[3] 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.

Armstrong et al. (1977) recommend the use of reminders to generate more replies. In this study, a reminder was sent two weeks after dispatching the questionnaires. No monetary or other incentive was used to raise the response rate. In order to reduce the possibility of demand bias, the following steps were taken as suggested in the literature (see for example Churchill et al. 1995, Dorsch et al. 1998). The initial response rate was increased by sending a cover letter that informed respondents about the content and purpose of the survey as well as a guarantee that the replies will be held in confidence. It has been argued that the more information cover letters provide about the content of the survey, the higher the response rate (Singer 1978; Morton-Williams and Young 1987).

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. The questionnaire could not be attached as an appendix on this dissertation due to confidentiality reasons. 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.

Based on the suggestions of Swan et al. (1984) we examined the uniformity of responses across the three target groups. Responses to the survey were comparatively analogous in terms of responses received: the Mobile users (n=211), the Combined users (n=257), and the Fixed-line users (n=310). Additionally, no significant item nonresponse (i.e. refusing to answer some specific questions) bias was detected. The t-test results did not reveal any significant bias in the response pattern.

After a second follow-up, 778 responses were accepted under further analyses. Hoelter (1983) defines the critical size of a sample to be approximately 200. 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 4.

Figure 4: The division of response rate among the different user segments of customers

Besides trying to establish causality between the different dimensions of seamless use experience, we used somewhat ethnographic approach in our survey. 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 causal path modeling (AMOS) were applied to our data. Cronbach’s alpha was used to measure the reliability of the results.

3.2 Review of the descriptive statistics

The results of this study are mainly presented in the research articles. In this compilation, we merely present some descriptive statistics.

The demographic profile of the respondents is presented in Table 2. 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.

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. 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: Profile of respondents

Demographic characteristics	Mobile users		Combined users		Fixed-line users		Total
	No	%	No	%	No	%	No	%
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
Total	211	100.0	257	100.0	310	100.0	778	100.0
s.d.	0.437		0.417		0.501
Age
Under 18 years	2	0.9	2	0.8	4	1.3	8	1.0
18-24 years	62	29.4	31	12.1	39	12.6	132	17.0
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
50-64 years	17	8.1	36	14.0	76	24.5	129	16.6
65 years and over	3	1.4	5	1.9	28	9.0	36	4.6
Missing	3	1.4	4	1.6	1	0.3	8	1.0
Total	211	100.0	257	100.0	310	100.0	778	100.0
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
40 001 – 50 000 euros	14	6.6	23	8.9	30	9.7	67	8.6
50 001 – 60 000 euros	4	1.9	8	3.1	12	3.9	24	3.1
60 001 – 70 000 euros	4	1.9	7	2.7	7	2.3	18	2.3
70 001 – 80 000 euros	1	0.5	5	1.9	4	1.3	10	1.3
80 001 – 90 000 euros	3	1.4	4	1.6	0	0	7	0.9
90 001 – 100 000 euros	0	0	4	1.6	2	0.6	6	0.8
More than 100 001 euros	3	1.4	2	0.8	5	1.6	10	1.3
Missing	11	5.2	11	4.3	12	3.9	34	4.5
Total	211	100.0	257	100.0	310	100.0	778	100.0
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	102	48.3	61	23.7	66	21.3	229	29.4
Widow	1	0.5	0	0	7	2.3	8	1.0
Divorced	12	5.7	19	7.4	43	13.9	74	9.5
Missing	9	4.3	7	2.7	8	2.6	24	3.1
Total	211	100.0	257	100.0	310	100.0	778	100.0
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	7	3.3	25	9.7	11	3.6	43	5.5
4 or more	1	0.5	3	1.2	9	2.9	13	1.7
Missing	3	1.4	3	1.2	1	0.3	7	0.8
Total	211	100.0	257	100.0	310	100.0	778	100.0
s.d.	0.791		1.074		1.019
Education
Elementary school	24	11.4	31	12.1	48	15.5	103	13.2
Business school	16	7.6	34	13.2	29	9.4	79	10.2
Vocational school	69	32.7	85	33.1	72	23.2	226	29.0
Technical school	18	8.5	29	11.3	35	11.3	82	10.5
Polytechnic institution	21	10.0	19	7.4	28	9.0	68	8.7
University degree	27	12.8	20	7.8	54	17.4	101	13.0
High school graduate	31	14.7	32	12.5	31	10.0	94	12.1
Other	2	0.9	4	1.6	10	3.2	16	2.1
Missing	3	1.4	3	1.2	3	1.0	9	1.2
Total	211	100.0	257	100.0	310	100.0	778	100.0
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
Government officer	5	2.4	6	2.3	23	7.4	34	4.4
Public servant	28	13.3	31	12.1	40	12.9	99	12.7
Student	27	12.8	23	8.9	28	9.0	78	10.0
Farmer	2	0.9	3	1.2	6	1.9	11	1.4
Pensioner	8	3.8	14	5.4	46	14.8	68	8.7
Entrepreneur	20	9.5	23	8.9	17	5.5	60	7.7
Unemployed	7	3.3	13	5.1	19	6.1	39	5.0
Other	2	0.9	3	1.2	5	1.6	10	1.3
Missing	6	2.8	5	1.9	2	0.6	13	1.8
Total	211	100.0	257	100.0	310	100.0	778	100.0
s.d.	2.367		2.526		2.547
Line of business
Heavy industry	55	26.1	60	23.3	41	13.2	156	20.0
Public administration	13	6.2	23	8.9	50	16.1	86	11.1
Transportation	25	11.8	32	12.5	16	5.2	73	9.4
Services sector	50	23.7	50	19.5	77	24.8	177	22.8
Banking and Insurance	3	1.4	5	1.9	8	2.6	16	2.1
Computing and Telecommunications	10	4.7	20	7.8	18	5.8	48	6.2
Commerce	16	7.6	11	4.3	18	5.8	45	5.8
Primary production	5	2.4	7	2.7	8	2.6	20	2.6
Missing	34	16.2	49	19.1	74	23.9	157	20.0
Total	211	100.0	257	100.0	310	100.0	778	100.0
s.d.	2.065		2.025		1.962

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.

Tähän tyhjä sivu ja liitä kanavakäyttögraafi poikittain Figure 5

All the demographics correlated with one or more service delivery channels. Gender is a significant factor for the Combined (men) and Fixed-line users (female) when choosing mobile phone as a modem via PC as their primary electronic service delivery channel. Age affects the choice of mobile (younger) and fixed-line Internet (younger) and the usage of mobile phone as a modem to connect on the Internet (older). Profession proved to have the most diverse effect in this study as it affects the usage of all the other channels except the option of personal service. There is also a correlation between personal service and marital status, which might be partially also due to the number of children married people may have and children’s needs in regard with the service delivery channel choice. Line of business did not correlate with any of the distribution channels. The higher education led to a lower level of experienced seamless usage of mobile service (r=-.354, p<.05).

Over half of the respondents (59.5%) were customers only to one operator. Every third of the respondents (33.8) had customer relationship with two operators and 5.2 percent of the respondents were customers to three operators. Minority of the respondents (1.4%) had four or more customer relationships with different operators. There was a significant correlation between the number of customer relationships with operators and frequency of particular electronic service delivery channel usage (see Table 3). The heavy users of Mobile Internet are more likely to be customers to several operators (r=.217, p<.01). Also, the more often one uses mobile phone as a modem in connection with PC to access Internet services (r=.354, p<0.1) and the more often on uses PDA to access mobile Internet services (r=.253, p<.01), the more customer relationships with different operators one will have.

Table 3: Correlation between number of customer relationships and service delivery channel usage

How often you use the following service delivery channels?	With how many operators you have a customer relationship with?
Mobile Internet	.217**
Fixed-line Internet	.067
Mobile phone as a modem in connection with PC	.354**
via PDA	.253**
Self-service	.077
Personal service	.039

** Correlation is significant at the 0.01 level.

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 (see Figures 6 & 7). 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%).

Figure 6: Mobile Internet users’ perceptions about the seamless use experience dimensions in different electronic service delivery channels

Figure 7: Fixed-line Internet users’ perceptions about the seamless use experience dimensions in different electronic service delivery channels

The Fixed-line users did not prove to be very knowledgeable in terms of mobile Internet services. For example, they said that they would be willing to use mobile Internet services, if a) they would work on countryside b) if they would work abroad c) if they could be used to order services used via other devices. All these options are already valid in the case of mobile Internet services and perhaps the current non-users merely need to be told about them for example with means of marketing communications.

Figure 8: “I would start using mobile Internet services if….” (The Fixed-line users)

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.

Figure 9: The Fixed-line users’ beliefs about mobile Internet services

Figure 10: The Mobile users’ experience about using mobile Internet services

The Fixed-line users are not worried with seamless user experience issues related in mobile Internet services. They are more concerned with pricing and technology-centrism, which they related in mobile Internet service use experience (see Figure 9). Keen et al. (2000) found that pricing might be one of those factors that contribute to decision-making process on the choice of mode by providing an incentive to use that mode. The actual users experience about mobile Internet services seem to be little bit more skeptical. The Mobile users pay attention also on factors, which are part of seamless use experience (see Figure 10). The Fixed-line users had a very similar opinion about the use experience of fixed-line Internet services than what they believed the mobile services usage to be (see Figure 11).

Figure 11: The Fixed-line users’ experience about using fixed-line Internet services

Over third (37.3%) of the Mobile users use mobile services weekly and four out of five (83.8%) Fixed-line users use fixed-line electronic services weekly. The Mobile users think that they are mostly going to add using search engines (50.2%) via mobile Internet. The Mobile users also believe that they are going to use reservations (31.5%) and e-mail (25.0%) more in the near future via mobile Internet. The Fixed-line users were also asked how they feel about starting to use mobile Internet services in the near future. Every fifth (21.1%) of the Fixed-line users believed that it is likely that they will start using mobile services related in home and living, children and family, or traveling in the near future. The second most popular future mobile services among current fixed-line heavy users were search engines and real-time chat. The Fixed-line users also believed that they are likely to start using services for pleasure (comics, horoscope, puzzles) via mobile Internet (see Figure 12).

Figure 12: The mobile services which will be used more or started using in the near future

Over third (37.3%) of the Mobile users use mobile services weekly and four out of five (83.8%) Fixed-line users use fixed-line electronic services weekly. The Mobile users report of using mainly five services. The Fixed-line users suppose that they needed a bundle of two services, if they would be daily using mobile services. The most commonly used mobile services used are related to home and family, hobbies and leisure time, and making reservation. Over the fixed-line Internet connection customers access mostly search engine, communication and financial services. Among the customers who are not currently using mobile services, the most tempting service bundle comprises of gender specific services (e.g. www.soneraplaza.net/ellit), search engine and using mobile service for remote control purposes (e.g. activating burglar alarm).

There were no differences in opinion between user segments how they classified the services. Shopping was seen as purely hedonic by 12 percent of the respondents. If the customers were thinking about shopping through the Internet, this finding makes sense. Sports news was also classified as hedonic whereas news in general was used for more utilitarian purposes. The mobile Internet services with the most hedonic purpose of use in the minds of the customers were: real-time chat, relationship, downloaded services, gambling and games. The mobile Internet services with the most utilitarian purpose of use in the minds of the customers were: search engines, remote diagnostics, traveling, finance, e-mail, health, career and education, news and reservations. The content of the mobile Internet services was seen more utilitarian than hedonic. This finding is challenging the general opinion, which relates the use of mobile Internet services more often in hedonic purposes than utilitarian ones.

No significant correlation was found between the willingness to recommend the mobile Internet services, telling positive things about using mobile Internet services, intention to encourage somebody’s use of mobile Internet services, level of satisfaction and how many operators the user is customer to. The customers seem to share the equal level of satisfaction after using mobile Internet services regardless of how many operators they are customers to. Proportionally the Mobile users appear to be more satisfied with the mobile Internet services than the Fixed-line users with fixed-line Internet services. Only half of the Fixed-line users using fixed-line Internet services daily felt themselves as satisfied after usage (64.7% vs. 33.7%) compared to the Mobile users, of which almost everybody with 93.0 % felt satisfied after daily use (11.4% vs. 10.6%). Customers felt that even though their expectations were not fully fulfilled, they still were satisfied with the service.

Besides pure demographic variables, the respondents’ level of innovativeness was measured using ethnographic arguments on a scale of -3 (totally disagree) to 3 (totally agree). Somewhat surprisingly, the Fixed-line users (mean 1.84, s.d. 1.877) appeared to value technical improvements over personal service more than the Mobile users (mean 0.53, s.d. 1.873). In overall, the Fixed-line users have more positive perceptions about technology and use of technology than the Mobile users. This might be due to the negative beliefs the Mobile users may have towards WAP-enabled services. Controversially, the Mobile users seem to be more favorable towards automated services (s.d. 1.861) and adapting to changes (s.d. 2.082) more easily than the Fixed-line users. The standard deviations were moderate or high for all arguments.

Table 4: Correlation matrix between innovativeness and errors encountered

CORRELATION MATRIX Type and level of innovativeness Þ Errors ß	Change driven	Personal service driven	Technology positive	Knowledgeable	Computer positive
Unsuitable device in terms of service usage	.232*	.225*	.361**	.240*
The connection keeps breaking				-.259**
Service downloads slowly			.195*	.345*
No recollection about the needed information to operate the service	.259*			.214*
Data gets lost, no confirmation about a (un)successful transfer					-.307*

** Correlation is significant at the 0.01 level.

* Correlation is significant at the 0.05 level.

The more technology positive and change driven the customer is, the more likely she is to experience technology and device related errors. The personal driven customers get frustrated when they feel that the device is unsuitable for replacing the personal service and therefore unsuitable for service delivery platform. The knowledgeable is well aware of the optional service delivery channels and therefore sensitive to the breaking connections and long download times as he knows that other service delivery channels may have better offerings.

Our focus on usability attributes is two-fold. We are interested in knowing the perceived importance of attributes and their experienced performance. By knowing the importance and performance of the services in relation to the usability attributes we are able to determine the following:

If importance and performance are perceived high, then users find this usability attribute very important, and this attribute is taken well into consideration while developing the services they use.
If importance is high and performance is low, then users value this usability attribute highly, but they see that it is not taken very well into consideration in the development of the services.
If importance is low and performance is low or high, then users do not value, or see the necessity of this usability attribute in a service, and even if this feature is taken well into consideration in the development of the service it might not have any impact on the users. In this case if performance is high, service developers would be able to stress other, more valued features in a service instead of this particular one.

We reason the overall priority of usability attributes by multiplying importance by performance. If customers feel that for example the importance of satisfaction attribute is very high, but they seldom encounter services with which they are satisfied, then from the service developers’ point of view it might be important to focus on such features in services that make their usage more pleasurable. It follows that

Σ I_iP_i = seamless use experience

i = n

in which I = Importance of seamless use experience dimension and P = Performance of seamless use experience dimension as reported by customers. If

Σ I_iP_i = 0 < 7 the attribute does not affect the seamless use experience

Σ I_iP_i = 8 < 21 attribute is important but low in performance à service provider

should focus on these ones

Σ I_iP_i = 22 < 49 attribute is important but also performs well

Figure 13: Importance & Performance grid for the Mobile users

Figure 14: Importance & Performance grid for the Combined users

Figure 15: Importance & Performance grid for the Fixed-line users

Efficiency of use and errors are seen as the most important usability attributes in every group (see Figure 13-15). However, even if both attributes are seen almost equally important, the performance of efficiency of use seems to reach higher level according to customers. This implies that the efficiency of use is taken better into consideration while designing the electronic services or the implementation has been more successful (more pleasing to the customers). The importance of memorability attribute is seen as the lowest in every group. The Mobile users seem to be experiencing least the seamless use as they rate all the attributes below zero in performance but above 1 in importance. The Fixed-line users perceive error handling as important but at the same time well taken care of. The Combined users perceive errors as important factor of seamless use experience too but at the same time, they feel that the performance of errors could be paid more attention to.

In Table 5 we present the scaled results of Importance-Performance findings. The efficiency of use raises as the most important attribute for all the user segments and is thus chosen as the starting point for comparison. For the Mobile users, memorability becomes next but for all the remaining user segments the second significant (importance-performance wise) attribute is satisfaction. Errors appear to be the third significant attribute for all the user segments. About 66 percent of the Mobile users encountered only once a week their valued attributes when using mobile Internet services. Mobile users’ memorability is the only attribute in this investigation, which falls in the category of “pay attention to these ones”.

Table 5: Importance-Performance scalability and user segments’ perceptions

Mobile users

Importance Performance Zigma value Scalability

Memorability 5.3662 3.7471 20.1077 0.88

Learnability 5.7042 3.9146 22.3290 0.98

Errors 6.0162 3.7004 22.2623 0.97

Efficiency of use 5.9834 3.8255 22.8894 1.00

Satisfaction 5.6833 3.8721 22.006 0.96

Fixed-line users

Importance Performance Zigma value Scalability

Memorability 5.2850 4.6400 24.5224 0.73

Learnability 5.8550 4.8150 28.1918 0.84

Errors 6.1250 4.3100 26.299 0.79

Efficiency of use 6.1700 5.4400 33.5648 1.00

Satisfaction 5.9950 5.4400 32.6128 0.97

Combined users (especially fixed-line focus group)

Importance Performance Zigma value Scalability

Memorability 5.3250 4.6650 24.8411 0.77

Learnability 5.8450 4.9350 28.845 0.89

Errors 6.0300 4.5400 27.3762 0.85

Efficiency of use 6.2500 5.1700 33.3125 1.00

Satisfaction 5.9500 5.2050 30.9698 0.96

Combined users (especially mobile Internet focus group)

Importance Performance Zigma value Scalability

Memorability 5.2625 4.5135 23.7529 0.74

Learnability 5.5195 5.1005 28.1522 0.88

Errors 5.9537 4.9109 29.2383 0.91

Efficiency of use 6.1500 5.2236 32.1251 1.00

Satisfaction 5.9369 5.0526 29.9068 0.93

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).

3.2.1 Insights from the framework

Cronbach’s alpha coefficients were used to assess the realibility of the measuring instruments to address the research postulations. The alphas were above 0.6 which is regarded as an acceptable minimum level for further analysis: Learnability 0.71, Efficiency of use 0.73, Memorability 0.69, Errors 0.74 and Satisfaction 0.67. To establish whether or not each item of the questionnaire represents a measurement of the various latent constructs as the literature suggests and to address the exogenous variables, a correlation matrix of the 48 items supposed to measure learnability, efficiency of use, memorability, errors and satisfaction was subjected to an unrestricted factor analysis (presented in research article 1). There was no significant difference between the proposed model and the estimated model. The goodness of fit index and the adjusted goodness of fit index were both above 0.9 indicating a good fit to the data.

Learnability does not seem to constitute to learnability for the Fixed-line users seamless use experience. In here, no significant relationship were detected between seamless use experience of fixed-line Internet services and learnability either. Postulations 1-3 and 5-7 were supported for the Mobile users learnability experience as part of seamless mobile Internet service usage. Not being a waste of money and time constitutes to efficiency of use for the Mobile users. Also fulfillment of expectations contributes positively to the efficiency of use in the Mobile user segment.

Table 1: Research postulations

... affects positively learnability

Good manuals and written instructions

Personal instructions from the operator

Logical navigation

Customers were involved in the service development

Personal abilities and qualities of the user

Possibility to get further instructions if needed

Previous experience in the use of electronic services

Previous experience in the use of technical devices

By learning the service I will benefit personally

…affects positively efficiency of use

Service fulfills my needs

Use of service doesn’t consume too much time or money

Placement and interrelated order of keys on the device

Constant level of service quality

Features of screen (size, colors)

…affects negatively efficiency of use

Slow speed of data transfer

Unnecessary device features

Amount of unnecessary information within the service

Device specific limitations in the use of service

…affects positively 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

Links available to other related services

Logical service

Service content remains the same

…affects negatively errors (adding to perception of experienced errors)

Device gets jammed

Speed of data transfer is lower than promised

Service is not what I expected

Data which I entered wasn’t saved

Downloaded program is not working on my device

Connection cannot be established at all

Too little memory on the device

No logic in service performance

I don’t remember how to use the device

Insufficient instructions on how to use the service

Unsuitable device to operate the service

…affects positively satisfaction

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

I’m pleased with my operator’s Web site

Operator provides secure data transfers

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

New Internet connection is installed within the promised timeframe

Mobile Internet users

Fixed-line Internet users

Not finding proper keys

Tekstikehys: Learnability Tekstikehys: Efficiency of use Tekstikehys: Errors Tekstikehys: Memorability Tekstikehys: Satisfaction

Tekstikehys: Learnability Tekstikehys: Efficiency of use Tekstikehys: Errors Tekstikehys: Memorability Tekstikehys: Satisfaction

Slow speed of data transfer was the thorn of the Fixed-line users’ perceived efficiency of use having a negative effect on effectiveness. How the memorability is comprised varied among different user segments. Postulations 22, 24, and 26 were supported in the Mobile user segment whereas the research postulations 23 and 25 held true for the Fixed-line users. The Mobile Internet service usage was characterized with errors as five out of eleven postulations were supported. Feel of satisfaction in seamless use experience was formed from timely problem solving (the Mobile users) and installations (the Fixed-line users) as well as security of data transfers (the Fixed-line users).

3.3 Business implications

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.

Demographic variables affecting the choice of a service delivery channel among Fixed-line users seem to be gender, age, marital status and profession. Gender seems to have significant effect as females find the learnability of mobile services more important. The older respondents place higher importance on the satisfaction and the younger ones seem to be more irritated with their belief of expected errors in mobile service usage.

Surprisingly, the Fixed-line users appear to value technical improvements over personal service more than the Mobile users. On the other hand, Mobile users seem to adapt to changes more easily, and they are more favorable towards automated services. Demographic variables affecting the choice of a service delivery channel among Mobile users appears to be age, education, income and profession. Less educated Mobile users seem to perceive mobile service delivery channel as seamless, and independent from time and place. Female Mobile users seem to be more affluent to errors, and male value memorability of mobile services higher.

The huge mass of potential mobile service customers will need an available and reliable infrastructure to access electronic services. The expected improvements in present and future generations of mobile phones will encourage the uptake of mobile services. Marketers need some directions of future customers’ perceptions and likings to be able to focus on right issues in marketing mobile services.

There are three different types of errors: technology (device or connection) related, service related and user related. We found that technology related errors tend to be catastrophic and hinder the use completely. The user related errors tend to be milder and minor by nature. The service related errors can be very irritating and hampering the achievement of goals set on the service usage but rarely completely catastrophic. The less the customers used a specific service delivery channel, the more they experienced channel specific errors. In the case of all the errors, over half of the Mobile users related them primarily in mobile Internet. The Mobile users related the second most errors in mobile phone usage as a modem and only few errors were related in fixed-line Internet in this user segment. It appears the Mobile users related catastrophic errors such as technology errors in their primary delivery channel, mobile Internet, and minor errors such as user specific errors in the secondary service delivery channel, fixed-line Internet. On the other hand, the Fixed-line users related most of the errors in fixed-line Internet.

Based on the Fixed-line users’ beliefs on low error rates in the case of mobile Internet, we conclude that usability doubts are not hindering their usage of mobile Internet. There was no clear interdependency between service content and experienced errors in the segment of Mobile users. They seemed to relate both catastrophic (technology specific) and service specific errors in both utilitarian and hedonic purposes of use. However, the user specific errors did not have a significant correlation with the service content at all. Catastrophic errors seem to relate closely in personal context whereas minor errors relate in environmental context. There are more errors having dependencies with personal context of mobile Internet service use than with environmental context. When users were alone, they felt more errors than average. Tiredness seems to correlate with many experienced errors as well.

Over half of the Mobile users thought that it is likely that they will recommend the use of mobile Internet services and majority of the Mobile users went even further by saying that it is likely that they will encourage their friends and relatives to start using mobile Internet services. Two thirds of the Mobile users reported of telling positive things about using mobile Internet services to their friends and almost half of them thought that it is likely that they will complain about problems in mobile Internet service usage to their friends. Every fifth said that they would change the service provider (operator) if they encounter problems in the mobile Internet usage.

Customers felt that even though their expectations were not fully fulfilled, they still were satisfied with the service. Apparently, customers tend to relate their feel of satisfaction primarily to the service provider instead of device used to operate the service or service content or context. It is an acknowledged phenomenon in marketing, that customers are rarely straightforward in how their satisfaction constitutes. Surprisingly, almost 20 percent of the customers with a seamless use experience are also reluctant to recommend the use of mobile Internet services. For example, every fifth (20.7%) of the customers, who report high satisfaction figures are not going to recommend the use of mobile Internet services. Service provider might think about the following: If customers feel that the services are functioning well, and they still will not encourage people to use them or even recommend the use of the services, why should we enhance the usability of services. It is very probable, that there are other dimensions for satisfaction than service provider related variables.

3.4 Recommendations for the future research

Our future research interest include the closer examination of the current non-users of mobile Internet services and the factors hindering their usage. Based on this study, the hindering factors are not to do so much with usability of service but perhaps more with pricing and technology perception in general.

Future research should be considered to reveal more possible factors of customer satisfaction. In this study only service provider (operator) related factors were found significant. However, low number of satisfaction factors found in this study indicate that there is more to this than meets the eye.

In the future we are also interested to know whether mobile Internet services can ever become truly global and compete with fixed-line Internet services. So far the majority of mobile services have remained national regardless of international standardization. Perhaps the problem has been the technology-centric focus (network standardization) instead of concentrating on global product extensions. We wonder, if the differences in diffusion speed has to do with technological differences or is it culturally born.

Qualitative research methods need to be applied in the future to further map the dimensions of seamless use experience. We expect qualitative methods to give deeper sounding and help us better capture the salient attributes of customer decision-making. We were left riddled by some dimensions of seamless use experience and the underlying constructs and will continue our journey in seamless marketspace on the magic carpet of qualititative methods.

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YHTEENVETO (FINNISH SUMMARY)

To be added.

Part II:

Research articles

[1] ”A combination of hardware and software components that receive input from and communicate output to a human user in order to support his or her performance or a task” according to ISO 13407.

[2] ”An information appliance is designed to perform a specific activity, such as music, photography, or writing. A distinguishing function of information appliance is the ability to share information” according to Bergman (2000).

[3] Based on the number of customers, TeliaSonera is the largest mobile operator in Sweden and Finland, the second largest operator in Norway, and the fourth largest operator in Denmark. TeliaSonera is also the largest fixed voice and data provider in the region with leading positions in Sweden and Finland and a significant position in Denmark. TeliaSonera International Carrier is the leading IP wholesaler in Europe with a 10% market share. TeliaSonera is listed on the Stockholm Exchange, the Helsinki Exchange and Nasdaq Stock Market in the USA.